Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2725-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-2725-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
12 Nov 2020
Data description paper |
| 12 Nov 2020
| 12 Nov 2020
Improved estimate of global gross primary production for reproducing its long-term variation, 1982–2017
Yi Zheng
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Ruoque Shen
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Yawen Wang
Key Laboratory of Physical Oceanography, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China
Xiangqian Li
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Shuguang Liu
College of Life Science and Technology, Central South University of
Forestry and Technology (CSUFT), Changsha 410004, Hunan, China
Shunlin Liang
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Jing M. Chen
Department of Geography, University of Toronto, Toronto, M5G 3G3 Canada
College of Geographical Science, Fujian Normal University, Fuzhou 3500007, Fujian, China
Weimin Ju
International Institute for Earth System Sciences, Nanjing University,
Nanjing, China
Jiangsu Center for Collaborative Innovation in Geographical
Information Resource Development and Application, Nanjing, China
Li Zhang
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Wenping Yuan
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519000, Guangdong, China
Related authors
Yi Zheng, Ana Cláudia dos Santos Luciano, Jie Dong, and Wenping Yuan
Earth Syst. Sci. Data, 14, 2065–2080, https://doi.org/10.5194/essd-14-2065-2022, https://doi.org/10.5194/essd-14-2065-2022, 2022
Short summary
Short summary
Brazil is the largest sugarcane producer. Sugarcane in Brazil can be harvested all year round. The flexible phenology makes it difficult to identify sugarcane in Brazil at a country scale. We developed a phenology-based method which can identify sugarcane with limited training data. The sugarcane maps for Brazil obtain high accuracy through comparison against field samples and statistical data. The maps can be used to monitor growing conditions and evaluate the feedback to climate of sugarcane.
Jie Dong, Yangyang Fu, Jingjing Wang, Haifeng Tian, Shan Fu, Zheng Niu, Wei Han, Yi Zheng, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 3081–3095, https://doi.org/10.5194/essd-12-3081-2020, https://doi.org/10.5194/essd-12-3081-2020, 2020
Short summary
Short summary
For the first time, we produced a 30 m winter wheat distribution map in China for 3 years during 2016–2018. Validated with 33 776 survey samples, the map had perfect performance with an overall accuracy of 89.88 %. Moreover, the method can identify planting areas of winter wheat 3 months prior to harvest; that is valuable information for production predictions and is urgently necessary for policymakers to reduce economic loss and assess food security.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
Short summary
Short summary
We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Bing Li, Shunlin Liang, Han Ma, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-16, https://doi.org/10.5194/essd-2024-16, 2024
Preprint under review for ESSD
Short summary
Short summary
This study describes 1-km all-weather instantaneous, and daily mean LST datasets for global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long time-series, global scale. The generated datasets were evaluated by the observations in-situ stations and other LST datasets, and the evaluation indicated the dataset is sufficiently reliable.
Peng Li, Rong Shang, Jing M. Chen, Mingzhu Xu, Xudong Lin, Guirui Yu, Nianpeng He, and Li Xu
Biogeosciences, 21, 625–639, https://doi.org/10.5194/bg-21-625-2024, https://doi.org/10.5194/bg-21-625-2024, 2024
Short summary
Short summary
The amount of carbon that forests gain from the atmosphere, called net primary productivity (NPP), changes a lot with age. These forest NPP–age relationships could be modeled from field survey data, but we are not sure which model works best. Here we tested five different models using 3121 field survey samples in China, and the semi-empirical mathematical (SEM) function was determined as the optimal. The relationships built by SEM can improve China's forest carbon modeling and prediction.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2023-3032, https://doi.org/10.5194/egusphere-2023-3032, 2024
Short summary
Short summary
In this study, ecosystem COS fluxes data were employed to optimize GPP estimation across various ecosystems with the Boreal Ecosystem Productivity Simulator (BEPS), which was further developed for simulating the leaf COS uptake under its state-of-the-art ‘two-leaf’ framework. our results showcased the efficacy of COS in enhancing model prediction and reducing prediction uncertainty of GPP, and deepened insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Shuzhuang Feng, Fei Jiang, Tianlu Qian, Nan Wang, Mengwei Jia, Songci Zheng, Jiansong Chen, Fang Ying, and Weimin Ju
EGUsphere, https://doi.org/10.5194/egusphere-2023-2654, https://doi.org/10.5194/egusphere-2023-2654, 2024
Short summary
Short summary
We developed a multi-air pollutant inversion system to estimate non-methane volatile organic compound (NMVOC) emissions using TROPOMI formaldehyde retrievals. We found that the inversion significantly improved formaldehyde simulations and reduced NMVOC emission uncertainties. The optimized NMVOC emissions effectively corrected the overestimation of O3 levels, mainly by decreasing the rate of the RO2 + NO reaction and increasing the rate of the NO2 + OH reaction.
Shanlei Sun, Zaoying Bi, Jingfeng Xiao, Yi Liu, Ge Sun, Weimin Ju, Chunwei Liu, Mengyuan Mu, Jinjian Li, Yang Zhou, Xiaoyuan Li, Yibo Liu, and Haishan Chen
Earth Syst. Sci. Data, 15, 4849–4876, https://doi.org/10.5194/essd-15-4849-2023, https://doi.org/10.5194/essd-15-4849-2023, 2023
Short summary
Short summary
Based on various existing datasets, we comprehensively considered spatiotemporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth–Wallace model, and we generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration PT and soil evaporation PE) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Shuzhuang Feng, Fei Jiang, Zheng Wu, Hengmao Wang, Wei He, Yang Shen, Lingyu Zhang, Yanhua Zheng, Chenxi Lou, Ziqiang Jiang, and Weimin Ju
Geosci. Model Dev., 16, 5949–5977, https://doi.org/10.5194/gmd-16-5949-2023, https://doi.org/10.5194/gmd-16-5949-2023, 2023
Short summary
Short summary
We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1955, https://doi.org/10.5194/egusphere-2023-1955, 2023
Short summary
Short summary
In this work, Nanjing University Carbon Assimilation System (NUCAS) was developed. Data assimilation experiments were conducted to demonstrate the robustness and to investigate the feasibility and applicability of NUCAS. The assimilation of COS significantly improved the model performance in gross primary productivity, sensible heat, latent heat and even soil moisture, demonstrating that COS can provide strong constraints on parameters relevant to water, energy and carbon processes.
Xinyan Liu, Tao He, Shunlin Liang, Ruibo Li, Xiongxin Xiao, Rui Ma, and Yichuan Ma
Earth Syst. Sci. Data, 15, 3641–3671, https://doi.org/10.5194/essd-15-3641-2023, https://doi.org/10.5194/essd-15-3641-2023, 2023
Short summary
Short summary
We proposed a data fusion strategy that combines the complementary features of multiple-satellite cloud fraction (CF) datasets and generated a continuous monthly 1° daytime cloud fraction product covering the entire Arctic during the sunlit months in 2000–2020. This study has positive significance for reducing the uncertainties for the assessment of surface radiation fluxes and improving the accuracy of research related to climate change and energy budgets, both regionally and globally.
Ruoque Shen, Baihong Pan, Qiongyan Peng, Jie Dong, Xuebing Chen, Xi Zhang, Tao Ye, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 15, 3203–3222, https://doi.org/10.5194/essd-15-3203-2023, https://doi.org/10.5194/essd-15-3203-2023, 2023
Short summary
Short summary
Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. This study developed a new rice-mapping method and produced distribution maps of single-season rice in 21 provincial administrative regions of China from 2017 to 2022 at a 10 or 20 m resolution. The accuracy was examined using 108 195 survey samples and county-level statistical data, and we found that the distribution maps have good accuracy.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Qian Wang, Bing Li, Jianglei Xu, Guodong Zhang, Xiaobang Liu, and Changhao Xiong
Earth Syst. Sci. Data, 15, 2055–2079, https://doi.org/10.5194/essd-15-2055-2023, https://doi.org/10.5194/essd-15-2055-2023, 2023
Short summary
Short summary
Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
Short summary
Short summary
Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, and Bing Li
Earth Syst. Sci. Data, 14, 5333–5347, https://doi.org/10.5194/essd-14-5333-2022, https://doi.org/10.5194/essd-14-5333-2022, 2022
Short summary
Short summary
The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the essential climate variables. This study generated a global land surface FAPAR product with a 250 m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time series of observation information. Direct validation and intercomparison revealed that our product better meets user requirements and has a greater spatiotemporal continuity than other existing products.
Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Ning Dong
Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, https://doi.org/10.5194/essd-14-4077-2022, 2022
Short summary
Short summary
Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu
Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, https://doi.org/10.5194/gmd-15-6637-2022, 2022
Short summary
Short summary
Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
Short summary
Short summary
A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Jianglei Xu, Shunlin Liang, and Bo Jiang
Earth Syst. Sci. Data, 14, 2315–2341, https://doi.org/10.5194/essd-14-2315-2022, https://doi.org/10.5194/essd-14-2315-2022, 2022
Short summary
Short summary
Land surface all-wave net radiation (Rn) is a key parameter in many land processes. Current products have drawbacks of coarse resolutions, large uncertainty, and short time spans. A deep learning method was used to obtain global surface Rn. A long-term Rn product was generated from 1981 to 2019 using AVHRR data. The product has the highest accuracy and a reasonable spatiotemporal variation compared to three other products. Our product will play an important role in long-term climate change.
Yi Zheng, Ana Cláudia dos Santos Luciano, Jie Dong, and Wenping Yuan
Earth Syst. Sci. Data, 14, 2065–2080, https://doi.org/10.5194/essd-14-2065-2022, https://doi.org/10.5194/essd-14-2065-2022, 2022
Short summary
Short summary
Brazil is the largest sugarcane producer. Sugarcane in Brazil can be harvested all year round. The flexible phenology makes it difficult to identify sugarcane in Brazil at a country scale. We developed a phenology-based method which can identify sugarcane with limited training data. The sugarcane maps for Brazil obtain high accuracy through comparison against field samples and statistical data. The maps can be used to monitor growing conditions and evaluate the feedback to climate of sugarcane.
Xueyuan Gao, Shunlin Liang, Dongdong Wang, Yan Li, Bin He, and Aolin Jia
Earth Syst. Dynam., 13, 219–230, https://doi.org/10.5194/esd-13-219-2022, https://doi.org/10.5194/esd-13-219-2022, 2022
Short summary
Short summary
Numerical experiments with a coupled Earth system model show that large-scale nighttime artificial lighting in tropical forests will significantly increase carbon sink, local temperature, and precipitation, and it requires less energy than direct air carbon capture for capturing 1 t of carbon, suggesting that it could be a powerful climate mitigation option. Side effects include CO2 outgassing after the termination of the nighttime lighting and impacts on local wildlife.
Xiaona Chen, Shunlin Liang, Lian He, Yaping Yang, and Cong Yin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-279, https://doi.org/10.5194/essd-2021-279, 2021
Preprint withdrawn
Short summary
Short summary
The present study developed a 39 year consistent 8-day 0.05 degree gap-free SCE dataset over the NH for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite based on the NOAA AVHRR-SR CDR and several contributory datasets. Compared with published SCE datasets, GLASS SCE has several advantages in snow cover studies, including long time series, finer spatial resolution (especially for years before 2000), and complete spatial coverage.
Diyang Cui, Shunlin Liang, Dongdong Wang, and Zheng Liu
Earth Syst. Sci. Data, 13, 5087–5114, https://doi.org/10.5194/essd-13-5087-2021, https://doi.org/10.5194/essd-13-5087-2021, 2021
Short summary
Short summary
Large portions of the Earth's surface are expected to experience changes in climatic conditions. The rearrangement of climate distributions can lead to serious impacts on ecological and social systems. Major climate zones are distributed in a predictable pattern and are largely defined following the Köppen climate classification. This creates an urgent need to compile a series of Köppen climate classification maps with finer spatial and temporal resolutions and improved accuracy.
Yan Chen, Shunlin Liang, Han Ma, Bing Li, Tao He, and Qian Wang
Earth Syst. Sci. Data, 13, 4241–4261, https://doi.org/10.5194/essd-13-4241-2021, https://doi.org/10.5194/essd-13-4241-2021, 2021
Short summary
Short summary
This study used remotely sensed and assimilated data to estimate all-sky land surface air temperature (Ta) using a machine learning method, and developed an all-sky 1 km daily mean land Ta product for 2003–2019 over mainland China. Validation results demonstrated that this dataset has achieved satisfactory accuracy and high spatial resolution simultaneously, which fills the current dataset gap in this field and plays an important role in studies of climate change and the hydrological cycle.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
Short summary
Short summary
The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Diyang Cui, Shunlin Liang, Dongdong Wang, and Zheng Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-53, https://doi.org/10.5194/essd-2021-53, 2021
Preprint withdrawn
Short summary
Short summary
The Köppen-Geiger climate classification has been widely applied in climate change and ecology studies to characterize climatic conditions. We present a new 1-km global dataset of Köppen-Geiger climate classification and bioclimatic variables for historical and future climates. The new climate maps offer higher classification accuracy, correspond well with distributions of vegetation and topographic features, and demonstrate the ability to identify recent and future changes in climate zones.
Xiongxin Xiao, Shunlin Liang, Tao He, Daiqiang Wu, Congyuan Pei, and Jianya Gong
The Cryosphere, 15, 835–861, https://doi.org/10.5194/tc-15-835-2021, https://doi.org/10.5194/tc-15-835-2021, 2021
Short summary
Short summary
Daily time series and full space-covered sub-pixel snow cover area data are urgently needed for climate and reanalysis studies. Due to the fact that observations from optical satellite sensors are affected by clouds, this study attempts to capture dynamic characteristics of snow cover at a fine spatiotemporal resolution (daily; 6.25 km) accurately by using passive microwave data. We demonstrate the potential to use the passive microwave and the MODIS data to map the fractional snow cover area.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
Short summary
Short summary
We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Liangjun Zhu, Shuguang Liu, Haifeng Zhu, David J. Cooper, Danyang Yuan, Yu Zhu, Zongshan Li, Yuandong Zhang, Hanxue Liang, Xu Zhang, Wenqi Song, and Xiaochun Wang
Clim. Past Discuss., https://doi.org/10.5194/cp-2021-2, https://doi.org/10.5194/cp-2021-2, 2021
Manuscript not accepted for further review
Short summary
Short summary
In this study, we take the temperature reconstruction for Changbai Mountains in northeast China as an example to illustrate a novel tree-species mixing reconstruction method, which clearly improve the accuracy of tree-ring-based reconstructions in areas with unstable growth-climate relationships. Our reconstruction is more accurate than previous temperature reconstructions developed from a single species. The AMO plays a key role in modulating temperature in the northern Changbai Mountains.
Jin Ma, Ji Zhou, Frank-Michael Göttsche, Shunlin Liang, Shaofei Wang, and Mingsong Li
Earth Syst. Sci. Data, 12, 3247–3268, https://doi.org/10.5194/essd-12-3247-2020, https://doi.org/10.5194/essd-12-3247-2020, 2020
Short summary
Short summary
Land surface temperature is an important parameter in the research of climate change and many land surface processes. This article describes the development and testing of an algorithm for generating a consistent global long-term land surface temperature product from 20 years of NOAA AVHRR radiance data. The preliminary validation results indicate good accuracy of this new long-term product, which has been designed to simplify applications and support the scientific research community.
Jie Dong, Yangyang Fu, Jingjing Wang, Haifeng Tian, Shan Fu, Zheng Niu, Wei Han, Yi Zheng, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 3081–3095, https://doi.org/10.5194/essd-12-3081-2020, https://doi.org/10.5194/essd-12-3081-2020, 2020
Short summary
Short summary
For the first time, we produced a 30 m winter wheat distribution map in China for 3 years during 2016–2018. Validated with 33 776 survey samples, the map had perfect performance with an overall accuracy of 89.88 %. Moreover, the method can identify planting areas of winter wheat 3 months prior to harvest; that is valuable information for production predictions and is urgently necessary for policymakers to reduce economic loss and assess food security.
Han Liu, Peng Gong, Jie Wang, Nicholas Clinton, Yuqi Bai, and Shunlin Liang
Earth Syst. Sci. Data, 12, 1217–1243, https://doi.org/10.5194/essd-12-1217-2020, https://doi.org/10.5194/essd-12-1217-2020, 2020
Short summary
Short summary
We built the first set of 5 km resolution CDRs to record the annual dynamics of global land cover (GLASS-GLC) from 1982 to 2015. The average overall accuracy is 82 %. By conducting long-term change analysis, significant land cover changes and spatiotemporal patterns at various scales were found, which can improve our understanding of global environmental change and help achieve sustainable development goals. This will be further applied in Earth system modeling to facilitate relevant studies.
Aolin Jia, Shunlin Liang, Dongdong Wang, Bo Jiang, and Xiaotong Zhang
Atmos. Chem. Phys., 20, 881–899, https://doi.org/10.5194/acp-20-881-2020, https://doi.org/10.5194/acp-20-881-2020, 2020
Short summary
Short summary
The Tibetan Plateau (TP) plays a vital role in regional and global climate change due to its location and orography. After generating a long-term surface radiation (SR) dataset, we characterized the SR spatiotemporal variation along with temperature. Evidence from multiple data sources indicated that the TP dimming was primarily driven by increased aerosols from human activities, and the cooling effect of aerosol loading offsets TP surface warming, revealing the human impact on regional warming.
Hengmao Wang, Fei Jiang, Jun Wang, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, https://doi.org/10.5194/acp-19-12067-2019, 2019
Short summary
Short summary
The differences in inverted global and regional carbon fluxes from GOSAT and OCO-2 XCO2 from 1 January to 31 December 2015 are studied. We find significant differences for inverted terrestrial carbon fluxes on both global and regional scales. Overall, GOSAT XCO2 has a better performance than OCO-2, and GOSAT data can effectively improve carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement.
Xiaojin Qian, Liangyun Liu, Holly Croft, and Jingming Chen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-228, https://doi.org/10.5194/bg-2019-228, 2019
Preprint withdrawn
Short summary
Short summary
The leaf maximum carboxylation rate (Vcmax) is a key photosynthesis parameter. We attempt to investigate whether a universal and stable relationship exists between leaf Vcmax25 and chlorophyll content across different C3 plant types from a plant physiological perspective and verify it using field experiments. The results confirm that leaf chlorophyll can be a reliable proxy for estimating Vcmax25, providing an operational approach for the global mapping of Vcmax25 across different plant types.
Wei He, Ivar R. van der Velde, Arlyn E. Andrews, Colm Sweeney, John Miller, Pieter Tans, Ingrid T. van der Laan-Luijkx, Thomas Nehrkorn, Marikate Mountain, Weimin Ju, Wouter Peters, and Huilin Chen
Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, https://doi.org/10.5194/gmd-11-3515-2018, 2018
Short summary
Short summary
We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
Short summary
Short summary
Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Yawen Wang, Martin Wild, Arturo Sanchez-Lorenzo, and Veronica Manara
Ann. Geophys., 35, 839–851, https://doi.org/10.5194/angeo-35-839-2017, https://doi.org/10.5194/angeo-35-839-2017, 2017
Short summary
Short summary
Through the selection of 172 urban–rural station pairs, this study noted that urbanization significantly influenced the dimming trend in sunshine duration in China from 1960 until it leveled off after 1990. During 1960–1989, rural dimming was around two-thirds the rate of urban dimming; this ratio generally shows a positive correlation with urbanization level. There may be an overestimation of dimming in China when a dataset with more urban-scale sites than rural-scale sites is applied.
Yang Liu, Ronggao Liu, Jan Pisek, and Jing M. Chen
Biogeosciences, 14, 1093–1110, https://doi.org/10.5194/bg-14-1093-2017, https://doi.org/10.5194/bg-14-1093-2017, 2017
Short summary
Short summary
Forest overstory and understory layers differ in carbon and water cycle regimes and phenology, as well as ecosystem functions. In this paper, overstory and understory LAI values were estimated separately for global needleleaf and deciduous broadleaf forests. This work would help us better understand the seasonal patterns of forest structure, evaluate the ecosystem functions and improve the modeling of the forest carbon and water cycles.
S. Zhang, X. Zheng, J. M. Chen, Z. Chen, B. Dan, X. Yi, L. Wang, and G. Wu
Geosci. Model Dev., 8, 805–816, https://doi.org/10.5194/gmd-8-805-2015, https://doi.org/10.5194/gmd-8-805-2015, 2015
Short summary
Short summary
A Global Carbon Assimilation System based on the Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.
H. Zheng, Y. Li, J. M. Chen, T. Wang, Q. Huang, W. X. Huang, L. H. Wang, S. M. Li, W. P. Yuan, X. Zheng, S. P. Zhang, Z. Q. Chen, and F. Jiang
Biogeosciences, 12, 1131–1150, https://doi.org/10.5194/bg-12-1131-2015, https://doi.org/10.5194/bg-12-1131-2015, 2015
Short summary
Short summary
Ecological models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) for an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state on 1 degree grid cells simultaneously.
X. Xie, S. Meng, S. Liang, and Y. Yao
Hydrol. Earth Syst. Sci., 18, 3923–3936, https://doi.org/10.5194/hess-18-3923-2014, https://doi.org/10.5194/hess-18-3923-2014, 2014
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
Q. Shi and S. Liang
Atmos. Chem. Phys., 14, 5659–5677, https://doi.org/10.5194/acp-14-5659-2014, https://doi.org/10.5194/acp-14-5659-2014, 2014
Y. Liu, Y. Zhou, W. Ju, S. Wang, X. Wu, M. He, and G. Zhu
Biogeosciences, 11, 2583–2599, https://doi.org/10.5194/bg-11-2583-2014, https://doi.org/10.5194/bg-11-2583-2014, 2014
Y. Liu, Y. Zhou, W. Ju, J. Chen, S. Wang, H. He, H. Wang, D. Guan, F. Zhao, Y. Li, and Y. Hao
Hydrol. Earth Syst. Sci., 17, 4957–4980, https://doi.org/10.5194/hess-17-4957-2013, https://doi.org/10.5194/hess-17-4957-2013, 2013
M. Liu, H. Wang, H. Wang, T. Oda, Y. Zhao, X. Yang, R. Zang, B. Zang, J. Bi, and J. Chen
Atmos. Chem. Phys., 13, 10873–10882, https://doi.org/10.5194/acp-13-10873-2013, https://doi.org/10.5194/acp-13-10873-2013, 2013
W. Yuan, S. Liu, W. Cai, W. Dong, J. Chen, A. Arain, P. D. Blanken, A. Cescatti, G. Wohlfahrt, T. Georgiadis, L. Genesio, D. Gianelle, A. Grelle, G. Kiely, A. Knohl, D. Liu, M. Marek, L. Merbold, L. Montagnani, O. Panferov, M. Peltoniemi, S. Rambal, A. Raschi, A. Varlagin, and J. Xia
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-5475-2013, https://doi.org/10.5194/gmdd-6-5475-2013, 2013
Revised manuscript not accepted
F. Jiang, H. W. Wang, J. M. Chen, L. X. Zhou, W. M. Ju, A. J. Ding, L. X. Liu, and W. Peters
Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, https://doi.org/10.5194/bg-10-5311-2013, 2013
N. F. Liu, Q. Liu, L. Z. Wang, S. L. Liang, J. G. Wen, Y. Qu, and S. H. Liu
Hydrol. Earth Syst. Sci., 17, 2121–2129, https://doi.org/10.5194/hess-17-2121-2013, https://doi.org/10.5194/hess-17-2121-2013, 2013
T. R. Xu, S. M. Liu, Z. W. Xu, S. Liang, and L. Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-3927-2013, https://doi.org/10.5194/hessd-10-3927-2013, 2013
Preprint withdrawn
Related subject area
Data, Algorithms, and Models
Improved maps of surface water bodies, large dams, reservoirs, and lakes in China
The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation
A high-resolution inland surface water body dataset for the tundra and boreal forests of North America
A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan
HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand
A dataset of microphysical cloud parameters, retrieved from Fourier-transform infrared (FTIR) emission spectra measured in Arctic summer 2017
A global long-term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network
First SMOS Sea Surface Salinity dedicated products over the Baltic Sea
HomogWS-se: a century-long homogenized dataset of near-surface wind speed observations since 1925 rescued in Sweden
Mapping long-term and high-resolution global gridded photosynthetically active radiation using the ISCCP H-series cloud product and reanalysis data
Description of the China global Merged Surface Temperature version 2.0
TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning
Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations
Multi-site, multi-crop measurements in the soil–vegetation–atmosphere continuum: a comprehensive dataset from two climatically contrasting regions in southwestern Germany for the period 2009–2018
Full-coverage 1 km daily ambient PM2.5 and O3 concentrations of China in 2005–2017 based on a multi-variable random forest model
Median bed-material sediment particle size across rivers in the contiguous US
A flux tower dataset tailored for land model evaluation
A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018
A harmonized global land evaporation dataset from model-based products covering 1980–2017
Estimating population and urban areas at risk of coastal hazards, 1990–2015: how data choices matter
Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017
GRQA: Global River Water Quality Archive
A 1 km global cropland dataset from 10 000 BCE to 2100 CE
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables
SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach
Nitrogen deposition in the UK at 1 km resolution from 1990 to 2017
ERA5-Land: a state-of-the-art global reanalysis dataset for land applications
An all-sky 1 km daily land surface air temperature product over mainland China for 2003–2019 from MODIS and ancillary data
100 years of lake evolution over the Qinghai–Tibet Plateau
The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019
Coastal complexity of the Antarctic continent
UAV-based very high resolution point cloud, digital surface model and orthomosaic of the Chã das Caldeiras lava fields (Fogo, Cabo Verde)
AQ-Bench: a benchmark dataset for machine learning on global air quality metrics
Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018
A new merged dataset for analyzing clouds, precipitation and atmospheric parameters based on ERA5 reanalysis data and the measurements of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner
A new satellite-derived dataset for marine aquaculture areas in China's coastal region
Database of petrophysical properties of the Mid-German Crystalline Rise
Landsat-derived bathymetry of lakes on the Arctic Coastal Plain of northern Alaska
Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China
Hyperspectral-reflectance dataset of dry, wet and submerged marine litter
A climate service for ecologists: sharing pre-processed EURO-CORDEX regional climate scenario data using the eLTER Information System
Crowdsourced air traffic data from the OpenSky Network 2019–2020
A restructured and updated global soil respiration database (SRDB-V5)
The Berkeley Earth Land/Ocean Temperature Record
Dielectric database of organic Arctic soils (DDOAS)
Global Carbon Budget 2020
A global long-term (1981–2000) land surface temperature product for NOAA AVHRR
A coastally improved global dataset of wet tropospheric corrections for satellite altimetry
Xinxin Wang, Xiangming Xiao, Yuanwei Qin, Jinwei Dong, Jihua Wu, and Bo Li
Earth Syst. Sci. Data, 14, 3757–3771, https://doi.org/10.5194/essd-14-3757-2022, https://doi.org/10.5194/essd-14-3757-2022, 2022
Short summary
Short summary
We generated China’s surface water bodies, Large Dams, Reservoirs, and Lakes (China-LDRL) dataset by analyzing all available Landsat imagery in 2019 (19\,338 images) in Google Earth Engine. The dataset provides accurate information on the geographical locations and sizes of surface water bodies, large dams, reservoirs, and lakes in China. The China-LDRL dataset will contribute to the understanding of water security and water resources management in China.
Jie Chen, Qi Yao, Ziyue Chen, Manchun Li, Zhaozhan Hao, Cheng Liu, Wei Zheng, Miaoqing Xu, Xiao Chen, Jing Yang, Qiancheng Lv, and Bingbo Gao
Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022, https://doi.org/10.5194/essd-14-3489-2022, 2022
Short summary
Short summary
The potential degradation of mainstream global fire products leads to large uncertainty in the effective monitoring of wildfires and their influence. To fill this gap, we produced a Fengyun-3D (FY-3D) global active fire product with a similar spatial and temporal resolution to MODIS fire products, aiming to serve as continuity and a replacement for MODIS fire products. The FY-3D fire product is an ideal tool for global fire monitoring and can be preferably employed for fire monitoring in China.
Yijie Sui, Min Feng, Chunling Wang, and Xin Li
Earth Syst. Sci. Data, 14, 3349–3363, https://doi.org/10.5194/essd-14-3349-2022, https://doi.org/10.5194/essd-14-3349-2022, 2022
Short summary
Short summary
High-latitude water bodies differ greatly in their morphological and topological characteristics related to their formation, type, and vulnerability. In this paper, we present a water body dataset for the North American high latitudes (WBD-NAHL). Nearly 6.5 million water bodies were identified, with approximately 6 million (~90 %) of them smaller than 0.1 km2.
Amy McNally, Jossy Jacob, Kristi Arsenault, Kimberly Slinski, Daniel P. Sarmiento, Andrew Hoell, Shahriar Pervez, James Rowland, Mike Budde, Sujay Kumar, Christa Peters-Lidard, and James P. Verdin
Earth Syst. Sci. Data, 14, 3115–3135, https://doi.org/10.5194/essd-14-3115-2022, https://doi.org/10.5194/essd-14-3115-2022, 2022
Short summary
Short summary
The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams described here generate routine estimates of snow, soil moisture, runoff, and other variables useful for tracking water availability. These data are hosted by NASA and USGS data portals for public use.
Thomas R. Etherington, George L. W. Perry, and Janet M. Wilmshurst
Earth Syst. Sci. Data, 14, 2817–2832, https://doi.org/10.5194/essd-14-2817-2022, https://doi.org/10.5194/essd-14-2817-2022, 2022
Short summary
Short summary
Long time series of temperature and rainfall grids are fundamental to understanding how these variables affects environmental or ecological patterns and processes. We present a History of Open Temperature and Rainfall with Uncertainty in New Zealand (HOTRUNZ) that is an open-access dataset that provides monthly 1 km resolution grids of rainfall and mean, minimum, and maximum daily temperatures with associated uncertainties for New Zealand from 1910 to 2019.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Earth Syst. Sci. Data, 14, 2767–2784, https://doi.org/10.5194/essd-14-2767-2022, https://doi.org/10.5194/essd-14-2767-2022, 2022
Short summary
Short summary
We present a dataset of cloud optical depths, effective radii and water paths from optically thin clouds observed in the Arctic around Svalbard. The data have been retrieved from infrared spectral radiance measured using a Fourier-transform infrared (FTIR) spectrometer. Besides a description of the measurements and retrieval technique, the data are put into context with results of corresponding measurements from microwave radiometer, lidar and cloud radar.
Jianglei Xu, Shunlin Liang, and Bo Jiang
Earth Syst. Sci. Data, 14, 2315–2341, https://doi.org/10.5194/essd-14-2315-2022, https://doi.org/10.5194/essd-14-2315-2022, 2022
Short summary
Short summary
Land surface all-wave net radiation (Rn) is a key parameter in many land processes. Current products have drawbacks of coarse resolutions, large uncertainty, and short time spans. A deep learning method was used to obtain global surface Rn. A long-term Rn product was generated from 1981 to 2019 using AVHRR data. The product has the highest accuracy and a reasonable spatiotemporal variation compared to three other products. Our product will play an important role in long-term climate change.
Verónica González-Gambau, Estrella Olmedo, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Justino Martínez, Pekka Alenius, Laura Tuomi, Rafael Catany, Manuel Arias, Carolina Gabarró, Nina Hoareau, Marta Umbert, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 2343–2368, https://doi.org/10.5194/essd-14-2343-2022, https://doi.org/10.5194/essd-14-2343-2022, 2022
Short summary
Short summary
We present the first Soil Moisture and Ocean Salinity Sea Surface Salinity (SSS) dedicated products over the Baltic Sea (ESA Baltic+ Salinity Dynamics). The Baltic+ L3 product covers 9 days in a 0.25° grid. The Baltic+ L4 is derived by merging L3 SSS with sea surface temperature information, giving a daily product in a 0.05° grid. The accuracy of L3 is 0.7–0.8 and 0.4 psu for the L4. Baltic+ products have shown to be useful, covering spatiotemporal data gaps and for validating numerical models.
Chunlüe Zhou, Cesar Azorin-Molina, Erik Engström, Lorenzo Minola, Lennart Wern, Sverker Hellström, Jessika Lönn, and Deliang Chen
Earth Syst. Sci. Data, 14, 2167–2177, https://doi.org/10.5194/essd-14-2167-2022, https://doi.org/10.5194/essd-14-2167-2022, 2022
Short summary
Short summary
To fill the key gap of short availability and inhomogeneity of wind speed (WS) in Sweden, we rescued the early paper records of WS since 1925 and built the first 10-member centennial homogenized WS dataset (HomogWS-se) for community use. An initial WS stilling and recovery before the 1990s was observed, and a strong link with North Atlantic Oscillation was found. HomogWS-se improves our knowledge of uncertainty and causes of historical WS changes.
Wenjun Tang, Jun Qin, Kun Yang, Yaozhi Jiang, and Weihao Pan
Earth Syst. Sci. Data, 14, 2007–2019, https://doi.org/10.5194/essd-14-2007-2022, https://doi.org/10.5194/essd-14-2007-2022, 2022
Short summary
Short summary
Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fields. In this study, we produced a 35-year high-resolution global gridded PAR dataset. Compared with the well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES), our PAR product was found to be a more accurate dataset with higher resolution.
Wenbin Sun, Yang Yang, Liya Chao, Wenjie Dong, Boyin Huang, Phil Jones, and Qingxiang Li
Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, https://doi.org/10.5194/essd-14-1677-2022, 2022
Short summary
Short summary
The new China global Merged Surface Temperature CMST 2.0 is the updated version of CMST-Interim used in the IPCC's AR6. The updated dataset is described in this study, containing three versions: CMST2.0 – Nrec, CMST2.0 – Imax, and CMST2.0 – Imin. The reconstructed datasets significantly improve data coverage, especially in the high latitudes in the Northern Hemisphere, thus increasing the long-term trends at global, hemispheric, and regional scales since 1850.
Rohaifa Khaldi, Domingo Alcaraz-Segura, Emilio Guirado, Yassir Benhammou, Abdellatif El Afia, Francisco Herrera, and Siham Tabik
Earth Syst. Sci. Data, 14, 1377–1411, https://doi.org/10.5194/essd-14-1377-2022, https://doi.org/10.5194/essd-14-1377-2022, 2022
Short summary
Short summary
This dataset with millions of 22-year time series for seven spectral bands was built by merging Terra and Aqua satellite data and annotated for 29 LULC classes by spatial–temporal agreement across 15 global LULC products. The mean F1 score was 96 % at the coarsest classification level and 87 % at the finest one. The dataset is born to develop and evaluate machine learning models to perform global LULC mapping given the disagreement between current global LULC products.
Chuanmin Hu
Earth Syst. Sci. Data, 14, 1183–1192, https://doi.org/10.5194/essd-14-1183-2022, https://doi.org/10.5194/essd-14-1183-2022, 2022
Short summary
Short summary
Using data collected by the Hyperspectral Imager for the Coastal Ocean (HICO) between 2010–2014, hyperspectral reflectance of various floating matters in global oceans and lakes is derived for the spectral range of 400–800 nm. Such reflectance spectra are expected to provide spectral endmembers to differentiate and quantify the floating matters from existing multi-band satellite sensors and future hyperspectral satellite missions such as NASA’s PACE, SBG, and GLIMR missions.
Tobias K. D. Weber, Joachim Ingwersen, Petra Högy, Arne Poyda, Hans-Dieter Wizemann, Michael Scott Demyan, Kristina Bohm, Ravshan Eshonkulov, Sebastian Gayler, Pascal Kremer, Moritz Laub, Yvonne Funkiun Nkwain, Christian Troost, Irene Witte, Tim Reichenau, Thomas Berger, Georg Cadisch, Torsten Müller, Andreas Fangmeier, Volker Wulfmeyer, and Thilo Streck
Earth Syst. Sci. Data, 14, 1153–1181, https://doi.org/10.5194/essd-14-1153-2022, https://doi.org/10.5194/essd-14-1153-2022, 2022
Short summary
Short summary
Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
Runmei Ma, Jie Ban, Qing Wang, Yayi Zhang, Yang Yang, Shenshen Li, Wenjiao Shi, Zhen Zhou, Jiawei Zang, and Tiantian Li
Earth Syst. Sci. Data, 14, 943–954, https://doi.org/10.5194/essd-14-943-2022, https://doi.org/10.5194/essd-14-943-2022, 2022
Short summary
Short summary
We constructed multi-variable random forest models based on 10-fold cross-validation and estimated daily PM2.5 and O3 concentration of China in 2005–2017 at a resolution of 1 km. The daily R2 values of PM2.5 and O3 were 0.85 and 0.77. The meteorological variables can significantly affect both PM2.5 and O3 modeling. During 2005–2017, PM2.5 exhibited an overall downward trend, while O3 experienced the opposite. The temporal trend of PM2.5 and O3 had spatial characteristics during the study period.
Guta Wakbulcho Abeshu, Hong-Yi Li, Zhenduo Zhu, Zeli Tan, and L. Ruby Leung
Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
Short summary
Short summary
Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Anna M. Ukkola, Gab Abramowitz, and Martin G. De Kauwe
Earth Syst. Sci. Data, 14, 449–461, https://doi.org/10.5194/essd-14-449-2022, https://doi.org/10.5194/essd-14-449-2022, 2022
Short summary
Short summary
Flux towers provide measurements of water, energy, and carbon fluxes. Flux tower data are invaluable in improving and evaluating land models but are not suited to modelling applications as published. Here we present flux tower data tailored for land modelling, encompassing 170 sites globally. Our dataset resolves several key limitations hindering the use of flux tower data in land modelling, including incomplete forcing variable, data format, and low data quality.
Hui Tao, Kaishan Song, Ge Liu, Qiang Wang, Zhidan Wen, Pierre-Andre Jacinthe, Xiaofeng Xu, Jia Du, Yingxin Shang, Sijia Li, Zongming Wang, Lili Lyu, Junbin Hou, Xiang Wang, Dong Liu, Kun Shi, Baohua Zhang, and Hongtao Duan
Earth Syst. Sci. Data, 14, 79–94, https://doi.org/10.5194/essd-14-79-2022, https://doi.org/10.5194/essd-14-79-2022, 2022
Short summary
Short summary
During 1984–2018, lakes in the Tibetan-Qinghai Plateau had the clearest water (mean 3.32 ± 0.38 m), while those in the northeastern region had the lowest Secchi disk depth (SDD) (mean 0.60 ± 0.09 m). Among the 10 814 lakes with > 10 years of SDD results, 55.4 % and 3.5 % experienced significantly increasing and decreasing trends of SDD, respectively. With the exception of Inner Mongolia–Xinjiang, more than half of lakes in all the other regions exhibited a significant trend of increasing SDD.
Jiao Lu, Guojie Wang, Tiexi Chen, Shijie Li, Daniel Fiifi Tawia Hagan, Giri Kattel, Jian Peng, Tong Jiang, and Buda Su
Earth Syst. Sci. Data, 13, 5879–5898, https://doi.org/10.5194/essd-13-5879-2021, https://doi.org/10.5194/essd-13-5879-2021, 2021
Short summary
Short summary
This study has combined three existing land evaporation (ET) products to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25° to define the global proxy ET with lower uncertainties. The merged product is the best at capturing dynamics over different locations and times among all data sets. The merged product performed well over a range of vegetation cover scenarios and also captured the trend of land evaporation over different areas well.
Kytt MacManus, Deborah Balk, Hasim Engin, Gordon McGranahan, and Rya Inman
Earth Syst. Sci. Data, 13, 5747–5801, https://doi.org/10.5194/essd-13-5747-2021, https://doi.org/10.5194/essd-13-5747-2021, 2021
Short summary
Short summary
New estimates of population and land area by settlement types within low-elevation coastal zones (LECZs) based on four sources of population data, four sources of settlement data and four sources of elevation data for the years 1990, 2000 and 2015. The paper describes the sensitivity of these estimates and discusses the fitness of use guiding user decisions. Data choices impact the number of people estimated within LECZs, but across all sources the LECZs are predominantly urban and growing.
Yanhua Xie, Holly K. Gibbs, and Tyler J. Lark
Earth Syst. Sci. Data, 13, 5689–5710, https://doi.org/10.5194/essd-13-5689-2021, https://doi.org/10.5194/essd-13-5689-2021, 2021
Short summary
Short summary
We created 30 m resolution annual irrigation maps covering the conterminous US for the period of 1997–2017, together with derivative products and ground reference data. The products have several improvements over other data, including field-level details of change and frequency, an annual time step, a collection of ~ 10 000 ground reference locations for the eastern US, and improved mapping accuracy of over 90 %, especially in the east compared to others of 50 % to 80 %.
Holger Virro, Giuseppe Amatulli, Alexander Kmoch, Longzhu Shen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 5483–5507, https://doi.org/10.5194/essd-13-5483-2021, https://doi.org/10.5194/essd-13-5483-2021, 2021
Short summary
Short summary
Water quality modeling is essential for understanding and mitigating water quality deterioration in river networks due to agricultural and industrial pollution. Improving the availability and usability of open data is vital to support global water quality modeling efforts. The GRQA extends the spatial and temporal coverage of previously available water quality data and provides a reproducible workflow for combining multi-source water quality datasets.
Bowen Cao, Le Yu, Xuecao Li, Min Chen, Xia Li, Pengyu Hao, and Peng Gong
Earth Syst. Sci. Data, 13, 5403–5421, https://doi.org/10.5194/essd-13-5403-2021, https://doi.org/10.5194/essd-13-5403-2021, 2021
Short summary
Short summary
In the study, the first 1 km global cropland proportion dataset for 10 000 BCE–2100 CE was produced through the harmonization and downscaling framework. The mapping result coincides well with widely used datasets at present. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The dataset will be valuable for long-term simulations and precise analyses. The framework can be extended to specific regions or other land use types.
Diyang Cui, Shunlin Liang, Dongdong Wang, and Zheng Liu
Earth Syst. Sci. Data, 13, 5087–5114, https://doi.org/10.5194/essd-13-5087-2021, https://doi.org/10.5194/essd-13-5087-2021, 2021
Short summary
Short summary
Large portions of the Earth's surface are expected to experience changes in climatic conditions. The rearrangement of climate distributions can lead to serious impacts on ecological and social systems. Major climate zones are distributed in a predictable pattern and are largely defined following the Köppen climate classification. This creates an urgent need to compile a series of Köppen climate classification maps with finer spatial and temporal resolutions and improved accuracy.
Amanda R. Fay, Luke Gregor, Peter Landschützer, Galen A. McKinley, Nicolas Gruber, Marion Gehlen, Yosuke Iida, Goulven G. Laruelle, Christian Rödenbeck, Alizée Roobaert, and Jiye Zeng
Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, https://doi.org/10.5194/essd-13-4693-2021, 2021
Short summary
Short summary
The movement of carbon dioxide from the atmosphere to the ocean is estimated using surface ocean carbon (pCO2) measurements and an equation including variables such as temperature and wind speed; the choices of these variables lead to uncertainties. We introduce the SeaFlux ensemble which provides carbon flux maps calculated in a consistent manner, thus reducing uncertainty by using common choices for wind speed and a set definition of "global" coverage.
Samuel J. Tomlinson, Edward J. Carnell, Anthony J. Dore, and Ulrike Dragosits
Earth Syst. Sci. Data, 13, 4677–4692, https://doi.org/10.5194/essd-13-4677-2021, https://doi.org/10.5194/essd-13-4677-2021, 2021
Short summary
Short summary
Nitrogen (N) may impact the environment in many ways, and estimation of its deposition to the terrestrial surface is of interest. N deposition data have not been generated at a high resolution (1 km × 1 km) over a long time series in the UK before now. This study concludes that N deposition has reduced by ~ 40 % from 1990. The impact of these results allows analysis of environmental impacts at a high spatial and temporal resolution, using a consistent methodology and consistent set of input data.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
Short summary
Short summary
The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Yan Chen, Shunlin Liang, Han Ma, Bing Li, Tao He, and Qian Wang
Earth Syst. Sci. Data, 13, 4241–4261, https://doi.org/10.5194/essd-13-4241-2021, https://doi.org/10.5194/essd-13-4241-2021, 2021
Short summary
Short summary
This study used remotely sensed and assimilated data to estimate all-sky land surface air temperature (Ta) using a machine learning method, and developed an all-sky 1 km daily mean land Ta product for 2003–2019 over mainland China. Validation results demonstrated that this dataset has achieved satisfactory accuracy and high spatial resolution simultaneously, which fills the current dataset gap in this field and plays an important role in studies of climate change and the hydrological cycle.
Guoqing Zhang, Youhua Ran, Wei Wan, Wei Luo, Wenfeng Chen, Fenglin Xu, and Xin Li
Earth Syst. Sci. Data, 13, 3951–3966, https://doi.org/10.5194/essd-13-3951-2021, https://doi.org/10.5194/essd-13-3951-2021, 2021
Short summary
Short summary
Lakes can be effective indicators of climate change, especially over the Qinghai–Tibet Plateau. Here, we provide the most comprehensive lake mapping covering the past 100 years. The new features of this data set are (1) its temporal length, providing the longest period of lake observations from maps, (2) the data set provides a state-of-the-art lake inventory for the Landsat era (from the 1970s to 2020), and (3) it provides the densest lake observations for lakes with areas larger than 1 km2.
Jie Yang and Xin Huang
Earth Syst. Sci. Data, 13, 3907–3925, https://doi.org/10.5194/essd-13-3907-2021, https://doi.org/10.5194/essd-13-3907-2021, 2021
Short summary
Short summary
We produce the 30 m annual China land cover dataset (CLCD), with an accuracy reaching 79.31 %. Trends and patterns of land cover changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and increase in forest (+4.34 %). The CLCD generally reflected the rapid urbanization and a series of ecological projects in China and revealed the anthropogenic implications on LC under the condition of climate change.
Richard Porter-Smith, John McKinlay, Alexander D. Fraser, and Robert A. Massom
Earth Syst. Sci. Data, 13, 3103–3114, https://doi.org/10.5194/essd-13-3103-2021, https://doi.org/10.5194/essd-13-3103-2021, 2021
Short summary
Short summary
This study quantifies the characteristic complexity
signaturesaround the Antarctic outer coastal margin, giving a multiscale estimate of the magnitude and direction of undulation or complexity at each point location along the entire coastline. It has numerous applications for both geophysical and biological studies and will contribute to Antarctic research requiring quantitative information about this important interface.
Gonçalo Vieira, Carla Mora, Pedro Pina, Ricardo Ramalho, and Rui Fernandes
Earth Syst. Sci. Data, 13, 3179–3201, https://doi.org/10.5194/essd-13-3179-2021, https://doi.org/10.5194/essd-13-3179-2021, 2021
Short summary
Short summary
Fogo in Cabo Verde is one of the most active ocean island volcanoes on Earth, posing important hazards to local populations and at a regional level. The last eruption occurred from November 2014 to February 2015. A survey of the Chã das Caldeiras area was conducted using a fixed-wing unmanned aerial vehicle. A point cloud, digital surface model and orthomosaic with 10 and 25 cm resolutions are provided, together with the full aerial survey projects and datasets.
Clara Betancourt, Timo Stomberg, Ribana Roscher, Martin G. Schultz, and Scarlet Stadtler
Earth Syst. Sci. Data, 13, 3013–3033, https://doi.org/10.5194/essd-13-3013-2021, https://doi.org/10.5194/essd-13-3013-2021, 2021
Short summary
Short summary
With the AQ-Bench dataset, we contribute to shared data usage and machine learning methods in the field of environmental science. The AQ-Bench dataset contains air quality data and metadata from more than 5500 air quality observation stations all over the world. The dataset offers a low-threshold entrance to machine learning on a real-world environmental dataset. AQ-Bench thus provides a blueprint for environmental benchmark datasets.
Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann
Earth Syst. Sci. Data, 13, 2701–2722, https://doi.org/10.5194/essd-13-2701-2021, https://doi.org/10.5194/essd-13-2701-2021, 2021
Short summary
Short summary
Semi-arid regions depend on the freshwater resources from the rainy seasons as they are crucial for ensuring security for drinking water, food and electricity. Thus, forecasting the conditions for the next season is crucial for proactive water management. We hence present a seasonal forecast product for four semi-arid domains in Iran, Brazil, Sudan/Ethiopia and Ecuador/Peru. It provides a benchmark for seasonal forecasts and, finally, a crucial contribution for improved disaster preparedness.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Lilu Sun and Yunfei Fu
Earth Syst. Sci. Data, 13, 2293–2306, https://doi.org/10.5194/essd-13-2293-2021, https://doi.org/10.5194/essd-13-2293-2021, 2021
Short summary
Short summary
Multi-source dataset use is hampered by use of different spatial and temporal resolutions. We merged Tropical Rainfall Measuring Mission precipitation radar and visible and infrared scanner measurements with ERA5 reanalysis. The statistical results indicate this process has no unacceptable influence on the original data. The merged dataset can help in studying characteristics of and changes in cloud and precipitation systems and provides an opportunity for data analysis and model simulations.
Yongyong Fu, Jinsong Deng, Hongquan Wang, Alexis Comber, Wu Yang, Wenqiang Wu, Shixue You, Yi Lin, and Ke Wang
Earth Syst. Sci. Data, 13, 1829–1842, https://doi.org/10.5194/essd-13-1829-2021, https://doi.org/10.5194/essd-13-1829-2021, 2021
Short summary
Short summary
Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the first time. It was found to cover a total area of ~1100 km2, of which more than 85 % is marine plant culture areas, with 87 % found in four coastal provinces. The results confirm the applicability and effectiveness of deep learning when applied to GF-1 data at the national scale, identifying the detailed spatial distributions and supporting the sustainable management of coastal resources in China.
Sebastian Weinert, Kristian Bär, and Ingo Sass
Earth Syst. Sci. Data, 13, 1441–1459, https://doi.org/10.5194/essd-13-1441-2021, https://doi.org/10.5194/essd-13-1441-2021, 2021
Short summary
Short summary
Physical rock properties are a key element for resource exploration, the interpretation of results from geophysical methods or the parameterization of physical or geological models. Despite the need for physical rock properties, data are still very scarce and often not available for the area of interest. The database presented aims to provide easy access to physical rock properties measured at 224 locations in Bavaria, Hessen, Rhineland-Palatinate and Thuringia (Germany).
Claire E. Simpson, Christopher D. Arp, Yongwei Sheng, Mark L. Carroll, Benjamin M. Jones, and Laurence C. Smith
Earth Syst. Sci. Data, 13, 1135–1150, https://doi.org/10.5194/essd-13-1135-2021, https://doi.org/10.5194/essd-13-1135-2021, 2021
Short summary
Short summary
Sonar depth point measurements collected at 17 lakes on the Arctic Coastal Plain of Alaska are used to train and validate models to map lake bathymetry. These models predict depth from remotely sensed lake color and are able to explain 58.5–97.6 % of depth variability. To calculate water volumes, we integrate this modeled bathymetry with lake surface area. Knowledge of Alaskan lake bathymetries and volumes is crucial to better understanding water storage, energy balance, and ecological habitat.
Fei Feng and Kaicun Wang
Earth Syst. Sci. Data, 13, 907–922, https://doi.org/10.5194/essd-13-907-2021, https://doi.org/10.5194/essd-13-907-2021, 2021
Els Knaeps, Sindy Sterckx, Gert Strackx, Johan Mijnendonckx, Mehrdad Moshtaghi, Shungudzemwoyo P. Garaba, and Dieter Meire
Earth Syst. Sci. Data, 13, 713–730, https://doi.org/10.5194/essd-13-713-2021, https://doi.org/10.5194/essd-13-713-2021, 2021
Short summary
Short summary
This paper describes a dataset consisting of 47 hyperspectral-reflectance measurements of plastic litter samples. The plastic litter samples include virgin and real samples. They were measured in dry conditions, and a selection of the samples were also measured in wet conditions and submerged in a water tank. The dataset can be used to better understand the effect of water absorption on the plastics and develop algorithms to detect and characterize marine plastics.
Susannah Rennie, Klaus Goergen, Christoph Wohner, Sander Apweiler, Johannes Peterseil, and John Watkins
Earth Syst. Sci. Data, 13, 631–644, https://doi.org/10.5194/essd-13-631-2021, https://doi.org/10.5194/essd-13-631-2021, 2021
Short summary
Short summary
This paper describes a pan-European climate service data product intended for ecological researchers. Access to regional climate scenario data will save ecologists time, and, for many, it will allow them to work with data resources that they will not previously have used due to a lack of knowledge and skills to access them. Providing easy access to climate scenario data in this way enhances long-term ecological research, for example in general regional climate change or impact assessments.
Martin Strohmeier, Xavier Olive, Jannis Lübbe, Matthias Schäfer, and Vincent Lenders
Earth Syst. Sci. Data, 13, 357–366, https://doi.org/10.5194/essd-13-357-2021, https://doi.org/10.5194/essd-13-357-2021, 2021
Short summary
Short summary
Flight data have been used widely for research by academic researchers and (supra)national institutions. Example domains range from epidemiology (e.g. examining the spread of COVID-19 via air travel) to economics (e.g. use as proxy for immediate forecasting of the state of a country's economy) and Earth sciences (climatology in particular). Until now, accurate flight data have been available only in small pieces from closed, proprietary sources. This work changes this with a crowdsourced effort.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
Short summary
Short summary
Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Robert A. Rohde and Zeke Hausfather
Earth Syst. Sci. Data, 12, 3469–3479, https://doi.org/10.5194/essd-12-3469-2020, https://doi.org/10.5194/essd-12-3469-2020, 2020
Short summary
Short summary
A global land and ocean temperature record was created by combining the Berkeley Earth monthly land temperature field with a newly interpolated version of the HadSST3 ocean dataset. The resulting dataset covers the period from 1850 to present.
This paper describes the methods used to create that combination and compares the results to other estimates of global temperature and the associated recent climate change, giving similar results.
Igor Savin, Valery Mironov, Konstantin Muzalevskiy, Sergey Fomin, Andrey Karavayskiy, Zdenek Ruzicka, and Yuriy Lukin
Earth Syst. Sci. Data, 12, 3481–3487, https://doi.org/10.5194/essd-12-3481-2020, https://doi.org/10.5194/essd-12-3481-2020, 2020
Short summary
Short summary
This article presents a dielectric database of organic Arctic soils. This database was created based on dielectric measurements of seven samples of organic soils collected in various parts of the Arctic tundra. The created database can serve not only as a source of experimental data for the development of new soil dielectric models for the Arctic tundra but also as a source of training data for artificial intelligence satellite algorithms of soil moisture retrievals based on neural networks.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jin Ma, Ji Zhou, Frank-Michael Göttsche, Shunlin Liang, Shaofei Wang, and Mingsong Li
Earth Syst. Sci. Data, 12, 3247–3268, https://doi.org/10.5194/essd-12-3247-2020, https://doi.org/10.5194/essd-12-3247-2020, 2020
Short summary
Short summary
Land surface temperature is an important parameter in the research of climate change and many land surface processes. This article describes the development and testing of an algorithm for generating a consistent global long-term land surface temperature product from 20 years of NOAA AVHRR radiance data. The preliminary validation results indicate good accuracy of this new long-term product, which has been designed to simplify applications and support the scientific research community.
Clara Lázaro, Maria Joana Fernandes, Telmo Vieira, and Eliana Vieira
Earth Syst. Sci. Data, 12, 3205–3228, https://doi.org/10.5194/essd-12-3205-2020, https://doi.org/10.5194/essd-12-3205-2020, 2020
Short summary
Short summary
In satellite altimetry (SA), the wet tropospheric correction (WTC) accounts for the path delay induced mainly by atmospheric water vapour. In coastal regions, the accuracy of the WTC determined by the on-board radiometer deteriorates. The GPD+ methodology, developed by the University of Porto in the remit of ESA-funded projects, computes improved WTCs for SA. Global enhanced products are generated for all past and operational altimetric missions, forming a relevant dataset for coastal altimetry.
Cited articles
Ainsworth, E. A. and Long, S. P.: What have we learned from 15 years of free-air
CO2 enrichment (FACE)? A meta-analytic review of the responses of
photosynthesis, canopy, New Phytol., 165, 351–371,
https://doi.org/10.1111/j.1469-8137.2004.01224.x, 2005.
Alton, P. B., North, P. R., and Los, S. O.: The impact of diffuse sunlight on
canopy light-use efficiency, gross photosynthetic product and net ecosystem
exchange in three forest biomes, Global Change Biol., 13, 776–787,
https://doi.org/10.1111/j.1365-2486.2007.01316.x, 2007.
Anav, A., Friedlingstein, P., Beer, C., Ciais, P., Harper, A., Jones, C.,
Murray-Tortarolo, G., Papale, D., Parazoo, N.C., Peylin, P., Piao, S.,
Sitch, S., Viovy, N., Wiltshire, A., and Zhao, M.: Spatiotemporal patterns of
terrestrial gross primary production: A review, Rev. Geophys., 53, 785–818,
https://doi.org/10.1002/2015rg000483, 2015.
Asner, G. P., Martin, R. E., Knapp, D. E., Tupayachi, R., Anderson, C.,
Carranza, L., Martinez, P., Houcheime, M., Sinca, F., and Weiss, P.:
Spectroscopy of canopy chemicals in humid tropical forests, Remote Sens.
Environ., 115, 3587–3598, https://doi.org/10.1016/j.rse.2011.08.020, 2011.
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and Wood,
E. F.: Present and future Koppen-Geiger climate classification maps at 1-km
resolution, Sci. Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214, 2018.
Cai, W., Yuan, W., Liang, S., Zhang, X., Dong, W., Xia, J., Fu, Y., Chen,
Y., Liu, D., and Zhang, Q.: Improved estimations of gross primary production
using satellite-derived photosynthetically active radiation, J. Geophys.
Res.-Biogeo., 119, 110–123, https://doi.org/10.1002/2013jg002456, 2014.
Cai, W., Yuan, W., Liang, S., Liu, S., Dong, W., Chen, Y., Liu, D., and Zhang,
H.: Large Differences in Terrestrial Vegetation Production Derived from
Satellite-Based Light Use Efficiency Models, Remote Sens., 6, 8945–8965,
https://doi.org/10.3390/rs6098945, 2014.
Canadell, J. G., Le Quere, C., Raupach, M. R., Field, C. B., Buitenhuis, E. T.,
Ciais, P., Conway, T. J., Gillett, N. P., Houghton, R. A., and Marland, G.:
Contributions to accelerating atmospheric CO2 growth from economic
activity, carbon intensity, and efficiency of natural sinks, P. Natl.
Acad. Sci. USA, 104, 18866–18870, https://doi.org/10.1073/pnas.0702737104, 2007.
Chen, J. M., Liu, J., Cihlar, J., and Goulden, M. L.: Daily canopy photosynthesis
model through temporal and spatial scaling for remote sensing applications,
Ecol. Model., 124, 99–119, https://doi.org/10.1016/s0304-3800(99)00156-8, 1999.
Cho, M. A., Skidmore, A., Corsi, F., van Wieren, S. E., and Sobhan, I.: Estimation
of green grass/herb biomass from airborne hyperspectral imagery using
spectral indices and partial least squares regression, Int. J. Appl. Earth Observ. Geoinfo., 9, 414–424,
https://doi.org/10.1016/j.jag.2007.02.001, 2007.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Collatz, G. J., Ball, J. T., Grivet, C., and Berry, J. A.: Physiological and
environmental regulation of stomatal conductance, photosynthesis and
transpiration: a model that includes a laminar boundary layer, Agr. Forest.
Meteorol., 54, 107–136, 1991.
de Almeida, C. T., Delgado, R. C., Galvao, L. S., de Oliveira Cruz e Aragao,
L. E., and Concepcion Ramos, M.: Improvements of the MODIS Gross Primary
Productivity model based on a comprehensive uncertainty assessment over the
Brazilian Amazonia, ISPRS J. Photogramm. Remote Sens., 145, 268–283,
https://doi.org/10.1016/j.isprsjprs.2018.07.016, 2018.
de Cárcer, P. S., Vitasse, Y., Peñuelas, J., Jassey, V. E. J., Buttler,
A., and Signarbieux, C.: Vapor-pressure deficit and extreme climatic variables
limit tree growth, Global Change Biol., 24, 1108–1122,
https://doi.org/10.1111/gcb.13973, 2018.
Dechant, B., Cuntz, M., Vohland, M., Schulz, E., and Doktor, D.: Estimation of
photosynthesis traits from leaf reflectance spectra: Correlation to nitrogen
content as the dominant mechanism, Remote Sens. Environ., 196, 279–292,
https://doi.org/10.1016/j.rse.2017.05.019, 2017.
Ding, J., Yang, T., Zhao, Y., Liu, D., Wang, X., Yao, Y., Peng, S., Wang,
T., and Piao, S.: Increasingly Important Role of Atmospheric Aridity on Tibetan
Alpine Grasslands, Geophys. Res. Lett., 45, 2852–2859,
https://doi.org/10.1002/2017gl076803, 2018.
Fan, L., Wigneron, J.-P., Ciais, P., Chave, J., Brandt, M., Fensholt, R.,
Saatchi, S. S., Bastos, A., Al-Yaari, A., Hufkens, K., Qin, Y., Xiao, X.,
Chen, C., Myneni, R. B., Fernandez-Moran, R., Mialon, A.,
Rodriguez-Fernandez, N. J., Kerr, Y., Tian, F., and Penuelas, J.:
Satellite-observed pantropical carbon dynamics, Nat. Plants, 5, 944–951,
2019.
Farquhar, G.D., von Caemmerer, S., and Berry, J. A.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C 3 species, Planta, 149,
78–90, https://doi.org/10.1007/bf00386231, 1980.
Fletcher, A. L., Sinclair, T. R., and Allen, L. H.: Transpiration responses to
vapor pressure deficit in well watered “slow-wilting” and commercial
soybean, Environ. Exp. Bot., 61, 145–151,
https://doi.org/10.1016/j.envexpbot.2007.05.004, 2007.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R. W.,
Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A., Holland, E. A.,
Karl, D. M., Michaels, A. F., Porter, J. H., Townsend, A. R., and Vorosmarty, C. J.:
Nitrogen cycles: past, present, and future, Biogeochemistry, 70, 153–226,
https://doi.org/10.1007/s10533-004-0370-0, 2004.
Gilgen, H., Wild, M., and Ohmura, A.: Means and trends of shortwave irradiance
at the surface estimated from Global Energy Balance Archive data, J. Clim.,
11, 2042–2061, https://doi.org/10.1175/1520-0442-11.8.2042, 1998.
Gu, L. H., Baldocchi, D., Verma, S. B., Black, T. A., Vesala, T., Falge, E. M., and
Dowty, P. R.: Advantages of diffuse radiation for terrestrial ecosystem
productivity, J. Geophys. Res.-Atmos., 107, ACL 2-1–ACL 2-23, https://doi.org/10.1029/2001jd001242, 2002.
Gu, L. H., Baldocchi, D. D., Wofsy, S. C., Munger, J. W., Michalsky, J. J., Urbanski, S. P., and Boden, T. A.: Response of a deciduous forest to the Mount Pinatubo eruption: Enhanced photosynthesis, Science, 299, 2035–2038, https://doi.org/10.1126/science.1078366, 2003.
Jiang, C. and Ryu, Y.: Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS), Remote Sens. Environ., 186, 528–547, 2016.
Ju, W., Chen, J. M., Black, T. A., Barr, A. G., Liu, J., and Chen, B.: Modelling
multi-year coupled carbon and water fluxes in a boreal aspen forest, Agr.
Forest Meteorol., 140, 136–151, https://doi.org/10.1016/j.agrformet.2006.08.008, 2006.
Jain, A. K., Meiyappan, P., Song, Y., and House, J. I.: CO2 Emissions from
Land-Use Change Affected More by Nitrogen Cycle, than by the Choice of Land
Cover Data, Glob. Change Biol., 9, 2893–2906, 2013.
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S.,
Ahlstrom, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein, P.,
Gans, F., Ichii, K., Ain, A. K. J., Kato, E., Papale, D., Poulter, B., Raduly,
B., Rodenbeck, C., Tramontana, G., Viovy, N., Wang, Y.-P., Weber, U.,
Zaehle, S., and Zeng, N.: Compensatory water effects link yearly global land CO2
sink changes to temperature, Nature, 541, 516–520, https://doi.org/10.1038/nature20780,
2017.
Kanji, G. K.: 100 Statistical Tests, SAGE Publications, London, 1999.
Kanniah, K. D., Beringer, J., North, P., and Hutley, L.: Control of atmospheric
particles on diffuse radiation and terrestrial plant productivity: A review,
Progr. Phys. Geogr., 36, 209–237,
https://doi.org/10.1177/0309133311434244, 2012.
Kato, E., Kinoshita, T., Ito, A., Kawamiya, M., and Yamagata, Y.: Evaluation
of spatially explicit emission scenario of land-use change and biomass
burning using a process-based biogeochemical model, J. Land Use
Sci., 8, 104–122, 2013.
Keenan, T. F., Baker, I., Barr, A., Ciais, P., Davis, K., Dietze, M., Dragon,
D., Gough, C. M., Grant, R., Hollinger, D., Hufkens, K., Poulter, B.,
McCaughey, H., Raczka, B., Ryu, Y., Schaefer, K., Tian, H., Verbeeck, H.,
Zhao, M., and Richardson, A. D.: Terrestrial biosphere model performance for
inter-annual variability of land-atmosphere CO2 exchange, Global Change
Biol., 18, 1971–1987, https://doi.org/10.1111/j.1365-2486.2012.02678.x, 2012.
Keenan, T. F., Prentice, I. C., Canadell, J. G., Williams, C. A., Wang, H.,
Raupach, M., and Collatz, G. J.: Recent pause in the growth rate of atmospheric
CO2 due to enhanced terrestrial carbon uptake, Nat. Commun., 7, 13428,
https://doi.org/10.1038/ncomms13428, 2016.
Khair, U., Fahmi, H., Al Hakim, S., and Rahim, R.: Forecasting Error Calculation
with Mean Absolute Deviation and Mean Absolute Percentage Error, J. Phys. Conf. Ser., 930, 012002, https://doi.org/10.1088/1742-6596/930/1/012002,
2017.
King, D. A., Turner, D. P., and Ritts, W. D.: Parameterization of a diagnostic
carbon cycle model for continental scale application, Remote Sens. Environ.,
1157, 1653–1664, 2011.
Knyazikhin, Y., Schull, M. A., Stenberg, P., Mottus, M., Rautiainen, M.,
Yang, Y., Marshak, A., Latorre Carmona, P., Kaufmann, R. K., Lewis, P.,
Disney, M. I., Vanderbilt, V., Davis, A. B., Baret, F., Jacquemoud, S.,
Lyapustin, A., and Myneni, R. B.: Hyperspectral remote sensing of foliar nitrogen
content, Proc. Natl. Acad. Sci. USA, 110, E185–E192,
https://doi.org/10.1073/pnas.1210196109, 2013.
Kokaly, R. F. and Clark, R. N.: Spectroscopic determination of leaf biochemistry
using band-depth analysis of absorption features and stepwise multiple
linear regression, Remote Sens. Environ., 67, 267–287,
https://doi.org/10.1016/s0034-4257(98)00084-4, 1999.
Kondo, M., Ichii, K., Takagi, H., and Sasakawa, M.: Comparison of the data-driven top-down and bottom-up global terrestrial CO2 exchanges: GOSAT CO2 inversion and empirical eddy flux upscaling, J. Geophys. Res.-Biogeo., 120, 1226–1245, 2015.
Konings, A. G., Williams, A. P., and Gentine, P.: Sensitivity of grassland
productivity to aridity controlled by stomatal and xylem regulation, Nat.
Geosci., 10, 284–288, https://doi.org/10.1038/ngeo2903, 2017.
Korson, L., Drost-Hansen, W., and Millero, F. J.: Viscosity of water at various
temperatures, J. Phys. Chem., 73, 34–39, https://doi.org/10.1021/j100721a006, 1969.
Krinner, G., Viovy, N., de Noblet, N., Ogée, J., Friedlingstein, P.,
Ciais, P., Sitch, S., Polcher, J., and Prentice, I. C.: A dynamic global
vegetation model for studies of the coupled atmospherebiosphere system,
Global Biogeochem. Cy., 19, 1–33, 2005.
Krupkova, L., Markova, I., Havrankova, K., Pokorny, R., Urban, O., Sigut,
L., Pavelka, M., Cienciala, E., and Marek, M. V.: Comparison of different
approaches of radiation use efficiency of biomass formation estimation in
Mountain Norway spruce, Trees-Struct. Funct., 31, 325–337,
https://doi.org/10.1007/s00468-016-1486-2, 2017.
Lamarque, J. F., Kiehl, J. T., Brasseur, G. P., Butler, T., Cameron-Smith, P.,
Collins, W. D., Collins, W. J., Granier, C., Hauglustaine, D., Hess, P. G.,
Holland, E. A., Horowitz, L., Lawrence, M. G., McKenna, D., Merilees, P.,
Prather, M. J., Rasch, P. J., Rotman, D., Shindell, D., and Thornton, P.:
Assessing future nitrogen deposition and carbon cycle feedback using a
multimodel approach: Analysis of nitrogen deposition, J. Geophys. Res.-Atmos., 11, D19303, https://doi.org/10.1029/2005jd005825, 2005.
Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.: Global Carbon Budget 2016, Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, 2016.
Li, X. L., Liang, S. L., Yu, G. R., Yuan, W. P., Cheng, X., Xia, J. Z., Zhao,
T. B., Feng, J. M., Ma, Z. G., Ma, M. G., Liu, S. M., Chen, J. Q., Shao, C. L., Li,
S. G., Zhang, X. D., Zhang, Z. Q., Chen, S. P., Ohta, T., Varlagin, A., Miyata,
A., Takagi, K., Saiqusa, N., and Kato, T.: Estimation of gross primary
production over the terrestrial ecosystems in China, Ecol. Model., 261,
80–92, https://doi.org/10.1016/j.ecolmodel.2013.03.024, 2013.
Liu, L. and Greaver, T. L.: A review of nitrogen enrichment effects on three
biogenic GHGs: the CO2 sink may be largely offset by stimulated N2O and
CH4 emission, Ecol. Lett., 12, 1103–1117,
https://doi.org/10.1111/j.1461-0248.2009.01351.x, 2009.
Liu, S., Bond-Lamberty, B., Boysen, L. R., Ford, J. D., Fox, A., Gallo, K.,
Hatfield, J., Henebry, G. M., Huntington, T. G., Liu, Z., Loveland, T. R.,
Norby, R. J., Sohl, T., Steiner, A. L., Yuan, W., Zhang, Z., and Zhao, S.: Grand
Challenges in Understanding the Interplay of Climate and Land Changes, Earth
Interactions, 21, 1–43, https://doi.org/10.1175/ei-d-16-0012.1, 2017.
Liu, Y., Xiao, J., Ju, W., Zhu, G., Wu, X., Fan, W., Li, D., and Zhou, Y.:
Satellite-derived LAI products exhibit large discrepancies and can lead to
substantial uncertainty in simulated carbon and water fluxes, Remote Sens.
Environ., 206, 174–188, https://doi.org/10.1016/j.rse.2017.12.024, 2018.
Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., Canadell, J. G.,
McCabe, M. F., Evans, J. P., and Wang, G.: Recent reversal in loss of global
terrestrial biomass, Nat. Clim. Change, 5, 470–474, 2015.
Lobell, D. B., Roberts, M. J., Schlenker, W., Braun, N., Little, B. B.,
Rejesus, R. M., and Hammer, G. L.: Greater Sensitivity to Drought Accompanies
Maize Yield Increase in the US Midwest, Science, 344, 516–519,
https://doi.org/10.1126/science.1251423, 2014.
Monteith, J.: Solar radiation and productivity in tropical ecosystems, J.
Appl. Ecol., 9, 747–766, 1972.
Mahadevan, P., Wofsy, S. C., Matross, D. M., Xiao, X. M., Dunn, A. L., Lin,
J. C., Gerbig, C., Munger, J. W., Chow, V. Y., and Gottlieb, E. W.: A
satellite-based biosphere parameterization for net ecosystem CO2 exchange:
Vegetation Photosynthesis and Respiration Model VPRM, Global Biogeochem.
Cy., 222, 1–17, 2008.
Melton, J. R. and Arora, V. K.: Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0, Geosci. Model Dev., 9, 323–361, https://doi.org/10.5194/gmd-9-323-2016, 2016.
Norby, R. J., DeLucia, E. H., Gielen, B., Calfapietra, C., Giardina, C. P.,
King, J. S., Ledford, J., McCarthy, H. R., Moore, D. J. P., Ceulemans, R., De
Angelis, P., Finzi, A. C., Karnosky, D. F., Kubiske, M. E., Lukac, M.,
Pregitzer, K. S., Scarascia-Mugnozza, G. E., Schlesinger, W. H., and Oren, R.:
Forest response to elevated CO2 is conserved across a broad range of
productivity, P. Natl. Acad. Sci. USA, 102, 18052–18056,
https://doi.org/10.1073/pnas.0509478102, 2005.
Norby, R. J., Wullschleger, S. D., Gunderson, C. A., Johnson, D. W., and Ceulemans,
R.: Tree responses to rising CO2 in field experiments: implications for
the future forest, Plant Cell Environ., 22, 683–714,
https://doi.org/10.1046/j.1365-3040.1999.00391.x, 1999.
Novick, K. A., Ficklin, D. L., Stoy, P. C., Williams, C. A., Bohrer, G., Oishi,
A. C., Papuga, S. A., Blanken, P. D., Noormets, A., Sulman, B. N., Scott, R. L.,
Wang, L., and Phillips, R. P.: The increasing importance of atmospheric demand
for ecosystem water and carbon fluxes, Nat. Clim. Change, 6, 1023–1027,
https://doi.org/10.1038/nclimate3114, 2016.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M.,
Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S. C.,
Thornton, P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E.,
Lamarque, J., Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S.,
Ricciuto, D. M., Sacks, W., Tang, J., and Yang, Z.: Technical description of version 4.5 of the community land model (CLM), NCAR Tech. Note, NCAR/TN-503+ STR, 420, https://doi.org/0.5065/D6RR1W7M, 2013.
Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X.,
Ahlstrom, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung, M.,
Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M.R., Lu, M., Luo, Y., Ma,
Y., Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle, S., and
Zeng, N.: Evaluation of terrestrial carbon cycle models for their response
to climate variability and to CO2 trends, Global Change Biol., 19,
2117–2132, https://doi.org/10.1111/gcb.12187, 2013.
Pierce, D. W., Westerling, A. L., and Oyler, J.: Future humidity trends over the western United States in the CMIP5 global climate models and variable infiltration capacity hydrological modeling system, Hydrol. Earth Syst. Sci., 17, 1833–1850, https://doi.org/10.5194/hess-17-1833-2013, 2013.
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P. M.,
Mooney, H. A., and Klooster, S. A.: Terrestrial ecosystem production: A process
model-based on global satellite and surface data, Global Biogeochem. Cy.,
7, 811–841, https://doi.org/10.1029/93gb02725, 1993.
Prentice, I. C., Dong, N., Gleason, S. M., Maire, V., and Wright, I. J.: Balancing
the costs of carbon gain and water transport: testing a new theoretical
framework for plant functional ecology, Ecol. Lett., 17, 82–91,
https://doi.org/10.1111/ele.12211, 2014.
Rawson, H. M., Begg, J. E., and Woodward, R. G.: The effect of atmospheric humidity
on photosynthesis, transpiration and water use efficiency of leaves of
several plant species, Planta, 134, 5–10, https://doi.org/10.1007/bf00390086, 1977.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M.,
Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A.,
Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A.,
Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta,
F., Ourcival, J.-M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M.,
Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini,
R.: On the separation of net ecosystem exchange into assimilation and
ecosystem respiration: review and improved algorithm, Glob. Change Biol.,
11, 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Reick, C. H., Raddatz, T., Brovkin, V., and Gayler, V.: The representation of
natural and anthropogenic land cover change in MPIESM, J. Adv. Model. Earth
Syst., 5, 459–482, 2013.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu,
E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G.-K., Bloom, S.,
Chen, J., Collins, D., Conaty, A., Da Silva, A., Gu, W., Joiner, J., Koster,
R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder,
C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen,
J.: MERRA: NASA's modern-era retrospective analysis for research and
applications, J. Clim., 24, 3624–3648, https://doi.org/10.1175/jcli-d-11-00015.1, 2011.
Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M. S., Reeves, M., and
Hashimoto, H.: A continuous satellite-derived measure of global terrestrial
primary production, Bioscience, 54, 547–560,
https://doi.org/10.1641/0006-3568(2004)054[0547:acsmog]2.0.co;2, 2004.
Ryu, Y., Baldocchi, D. D., Kobayashi, H., van Ingen, C., Li, J., Black, T. A.,
Beringer, J., van Gorsel, E., Knohl, A., Law, B. E., and Roupsard, O.:
Integration of MODIS land and atmosphere products with a coupled-process
model to estimate gross primary productivity and evapotranspiration from 1 km to global scales, Global Biogeochem. Cy., 25, GB4017, https://doi.org/10.1029/2011gb004053,
2011.
Ryu, Y., Berry, J. A., and Baldocchi, D. D.: What is global photosynthesis?
History, uncertainties and opportunities, Remote Sens. Environ., 223,
95–114, https://doi.org/10.1016/j.rse.2019.01.016, 2019.
Saleska, S. R., Didan, K., Huete, A. R., and da Rocha, H. R.: Amazon forests
green-up during 2005 drought, Science, 318, 612–612,
https://doi.org/10.1126/science.1146663, 2007.
Samanta, A., Ganguly, S., Hashimoto, H., Devadiga, S., Vermote, E.,
Knyazikhin, Y., Nemani, R. R., and Myneni, R. B.: Amazon forests did not green-up
during the 2005 drought, Geophys. Res. Lett., 37, L05401, https://doi.org/10.1029/2009gl042154, 2010.
Serbin, S. P., Dillaway, D. N., Kruger, E. L., and Townsend, P. A.: Leaf optical
properties reflect variation in photosynthetic metabolism and its
sensitivity to temperature, J. Exp. Bot., 63, 489–502,
https://doi.org/10.1093/jxb/err294, 2012.
Simmons, A. J., Willett, K. M., Jones, P. D., Thorne, P. W., and Dee, D. P.:
Low-frequency variations in surface atmospheric humidity, temperature, and
precipitation: Inferences from reanalyses and monthly gridded observational
data sets, J. Geophys. Res.-Atmos., 115, D01110, https://doi.org/10.1029/2009jd012442, 2010.
Sjostrom, M., Zhao, M., Archibald, S., Arneth, A., Cappelaere, B., Falk, U.,
de Grandcourt, A., Hanan, N., Kergoat, L., Kutsch, W., Merbold, L., Mougin,
E., Nickless, A., Nouvellon, Y., Scholes, R. J., Veenendaal, E. M., and Ardo, J.:
Evaluation of MODIS gross primary productivity for Africa using eddy
covariance data, Remote Sens. Environ., 131, 275–286,
https://doi.org/10.1016/j.rse.2012.12.023, 2013.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014.
Smith, W. K., Reed, S. C., Cleveland, C. C., Ballantyne, A. P., Anderegg,
W. R. L., Wieder, W. R., Liu, Y. Y., and Running, S. W.: Large divergence of
satellite and Earth system model estimates of global terrestrial CO2
fertilization, Nat. Clim. Change, 6, 306–310, https://doi.org/10.1038/nclimate2879,
2016.
Stocker, B. D., Feissli, F., Strassmann, K. M., Spahni, R., and Joos, F.:
Past and future carbon fluxes from land use change, shifting cultivation and
wood harvest, Tellus B, 66, 23188, https://doi.org/10.3402/tellusb.v66.23188, 2014.
Stocker, B. D., Zscheischler, J., Keenan, T. F., Prentice, I. C., Seneviratne,
S. I., and Peñuelas, J.: Drought impacts on terrestrial primary production
underestimated by satellite monitoring, Nat. Geosci., 12, 264–270,
https://doi.org/10.1038/s41561-019-0318-6, 2019.
Sulman, B. N., Roman, D. T., Yi, K., Wang, L., Phillips, R. P., and Novick, K. A.:
High atmospheric demand for water can limit forest carbon uptake and
transpiration as severely as dry soil, Geophys. Res. Lett., 43, 9686–9695,
https://doi.org/10.1002/2016gl069416, 2016.
Tan, B., Woodcock, C. E., Hu, J., Zhang, P., Ozdogan, M., Huang, D., Yang,
W., Knyazikhin, Y., and Myneni, R. B.: The impact of gridding artifacts on the
local spatial properties of MODIS data: Implications for validation,
compositing, and band-to-band registration across resolutions, Remote Sens.
Environ., 105, 98–114, https://doi.org/10.1016/j.rse.2006.06.008, 2006.
Tang, S., Chen, J. M., Zhu, Q., Li, X., Chen, M., Sun, R., Zhou, Y., Deng,
F., and Xie, D.: LAI inversion algorithm based on directional reflectance
kernels, J. Environ. Manage., 85, 638–648,
https://doi.org/10.1016/j.jenvman.2006.08.018, 2007.
Turner, D. P., Ritts, W. D., Styles, J. M., Yang, Z., Cohen, W. B., Law, B. E., and
Thornton, P. E.: A diagnostic carbon flux model to monitor the effects of
disturbance and interannual variation in climate on regional NEP, Tellus B,
585, 476–490, 2006.
Urban, O., Janous, D., Acosta, M., Czerny, R., Markova, I., Navratil, M.,
Pavelka, M., Pokorny, R., Sprtova, M., Zhang, R., Spunda, V., Grace, J., and
Marek, M. V.: Ecophysiological controls over the net ecosystem exchange of
mountain spruce stand. Comparison of the response in direct vs. diffuse
solar radiation, Global Change Biol., 13, 157–168,
https://doi.org/10.1111/j.1365-2486.2006.01265.x, 2007.
Van Wijngaarden, W. A. and Vincent, L. A.: Trends in relative humidity in Canada from 1953–2003, B. Am. Meteorol. Soc., 4633–4636, 2004.
Veroustraete, F., Sabbe, H., and Eerens, H.: Estimation of carbon mass fluxes
over Europe using the C-Fix model and Euroflux data, Remote Sens. Environ.,
833, 376–399, 2002.
Vuichard, N. and Papale, D.: Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis, Earth Syst. Sci. Data, 7, 157–171, https://doi.org/10.5194/essd-7-157-2015, 2015.
Wang, Z., Skidmore, A. K., Darvishzadeh, R., and Wang, T.: Mapping forest canopy
nitrogen content by inversion of coupled leaf-canopy radiative transfer
models from airborne hyperspectral imagery, Agr. Forest. Meteorol., 253,
247–260, https://doi.org/10.1016/j.agrformet.2018.02.010, 2018.
Wild, M., Gilgen, H., Roesch, A., Ohmura, A., Long, C.N., Dutton, E.G.,
Forgan, B., Kallis, A., Russak, V., and Tsvetkov, A.: From dimming to
brightening: Decadal changes in solar radiation at Earth's surface, Science,
308, 847–850, https://doi.org/10.1126/science.1103215, 2005.
Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983–2006, https://doi.org/10.5194/cp-10-1983-2014, 2014.
Williams, A. P., Allen, C. D., Macalady, A. K., Griffin, D., Woodhouse, C. A.,
Meko, D. M., Swetnam, T. W., Rauscher, S. A., Seager, R., Grissino-Mayer, H. D.,
Dean, J. S., Cook, E. R., Gangodagamage, C., Cai, M., and McDowell, N. G.:
Temperature as a potent driver of regional forest drought stress and tree
mortality, Nat. Clim. Change, 3, 292–297, https://doi.org/10.1038/nclimate1693, 2013.
Wu, J., Albert, L. P., Lopes, A. P., Restrepo-Coupe, N., Hayek, M., Wiedemann,
K. T., Guan, K., Stark, S. C., Christoffersen, B., Prohaska, N., Tavares,
J. V., Marostica, S., Kobayashi, H., Ferreira, M. L., Campos, K. S., da Silva,
R., Brando, P. M., Dye, D. G., Huxman, T. E., Huete, A. R., Nelson, B. W.,
and Saleska, S. R.: Leaf development and demography explain photosynthetic
seasonality in Amazon evergreen forests, Science, 351, 972–976,
https://doi.org/10.1126/science.aad5068, 2016.
Wu, J., Guan, K., Hayek, M., Restrepo-Coupe, N., Wiedemann, K. T., Xu, X.,
Wehr, R., Christoffersen, B. O., Miao, G., da Silva, R., de Araujo, A. C.,
Oliviera, R. C., Camargo, P. B., Monson, R. K., Huete, A. R., and Saleska, S. R.:
Partitioning controls on Amazon forest photosynthesis between environmental
and biotic factors at hourly to interannual timescales, Global Change Biol.,
23, 1240–1257, https://doi.org/10.1111/gcb.13509, 2017.
Xiao, X. M., Zhang, Q. Y., Hollinger, D., Aber, J., and Moore, B.: Modeling gross
primary production of an evergreen needleleaf forest using MODIS and climate
data, Ecol. Appl., 15, 954–969, https://doi.org/10.1890/04-0470, 2005.
Xiao, Z., Liang, S., Wang, J., Xiang, Y., Zhao, X., and Song, J.:
Long-Time-Series Global Land Surface Satellite Leaf Area Index Product
Derived From MODIS and AVHRR Surface Reflectance, IEEE Trans. Geosci. Remote, 54, 5301–5318, https://doi.org/10.1109/tgrs.2016.2560522, 2016.
Xu, B., Li, J., Park, T., Liu, Q., Zeng, Y., Yin, G., Zhao, J., Fan, W.,
Yang, L., Knyazikhin, Y., Myneni, R. B.: An integrated method for validating
long-term leaf area index products using global networks of site-based
measurements, Remote Sens. Environ., 209, 134–151,
https://doi.org/10.1016/j.rse.2018.02.049, 2018.
Yoder, B. J. and Pettigrew-Crosby, R. E.: Predicting nitrogen and chlorophyll
content and concentrations from reflectance spectra (400–2500 nm) at leaf
and canopy scales, Remote Sens. Environ., 53, 199–211,
https://doi.org/10.1016/0034-4257(95)00135-n, 1995.
Yuan, W., Cai, W., Xia, J., Chen, J., Liu, S., Dong, W., Merbold, L., Law,
B., Arain, A., Beringer, J., Bernhofer, C., Black, A., Blanken, P. D.,
Cescatti, A., Chen, Y., Francois, L., Gianelle, D., Janssens, I. A., Jung,
M., Kato, T., Kiely, G., Liu, D., Marcolla, B., Montagnani, L., Raschi, A.,
Roupsard, O., Varlagin, A., and Wohlfahrt, G.: Global comparison of light use
efficiency models for simulating terrestrial vegetation gross primary
production based on the La Thuile database, Agr. Forest. Meteorol., 192,
108–120, https://doi.org/10.1016/j.agrformet.2014.03.007, 2014.
Yuan, W., Liu, S., Zhou, G., Zhou, G., Tieszen, L. L., Baldocchi, D.,
Bernhofer, C., Gholz, H., Goldstein, A. H., Goulden, M. L., Hollinger, D. Y.,
Hu, Y., Law, B. E., Stoy, P. C., Vesala, T., Wofsy, S. C., and other AmeriFlux collaborators:
Deriving a light use efficiency model from eddy covariance flux data for
predicting daily gross primary production across biomes, Agr. Forest.
Meteorol., 143, 189–207, https://doi.org/10.1016/j.agrformet.2006.12.001, 2007.
Yuan, W., Luo, Y., Li, X., Liu, S., Yu, G., Zhou, T., Bahn, M., Black, A.,
Desai, A. R., Cescatti, A., Marcolla, B., Jacobs, C., Chen, J., Aurela, M.,
Bernhofer, C., Gielen, B., Bohrer, G., Cook, D. R., Dragoni, D., Dunn, A. L.,
Gianelle, D., Gruenwald, T., Ibrom, A., Leclerc, M. Y., Lindroth, A., Liu,
H., Marchesini, L. B., Montagnani, L., Pita, G., Rodeghiero, M., Rodrigues,
A., Starr, G., and Stoy, P. C.: Redefinition and global estimation of basal
ecosystem respiration rate, Global Biogeochem. Cy.,
25, GB4002, https://doi.org/10.1029/2011gb004150, 2011.
Yuan, W., Liu, S., Yu, G., Bonnefond, J.-M., Chen, J., Davis, K., Desai,
A. R., Goldstein, A. H., Gianelle, D., Rossi, F., Suyker, A. E., and Verma, S. B.:
Global estimates of evapotranspiration and gross primary production based on
MODIS and global meteorology data, Remote Sens. Environ., 114, 1416–1431,
https://doi.org/10.1016/j.rse.2010.01.022, 2010.
Yuan, W., Zheng, Y., Piao, S., Ciais, P., Lombardozzi, D., Wang, Y., Ryu,
Y., Chen, G., Dong, W., Hu, Z., Jain, A.K., Jiang, C., Kato, E., Li, S.,
Lienert, S., Liu, S., Nabel, J. E. M. S., Qin, Z., Quine, T., Sitch, S., Smith,
W. K., Wang, F., Wu, C., Xiao, Z., and Yang, S.: Increased atmospheric vapor
pressure deficit reduces global vegetation growth, Sci. Adv., 5,
eaax1396, https://doi.org/10.1126/sciadv.aax1396, 2019.
Zhang, H. Q., Pak, B., Wang, Y. P., Zhou, X. Y., Zhang, Y. Q., and Zhang,
L.: Evaluating Surface Water Cycle Simulated by the Australian Community
Land Surface Model (CABLE) across Different Spatial and Temporal Domains, J.
Hydrometeorol., 14, 1119–1138, 2013.
Zhang, Y., Xiao, X., Wu, X., Zhou, S., Zhang, G., Qin, Y., and Dong, J.: Data
Descriptor: A global moderate resolution dataset of gross primary production
of vegetation for 2000–2016, Sci. Data, 4, 170165, https://doi.org/10.1038/sdata.2017.165, 2017.
Zhao, M. and Running, S. W.: Drought-Induced Reduction in Global Terrestrial Net
Primary Production from 2000 Through 2009, Science, 329, 940–943,
https://doi.org/10.1126/science.1192666, 2010.
Zheng, Y., Shen, R., Wang, Y., Li, X., Liu, S., Liang, S., Chen, J. M.,
Ju, W., Zhang, L., and Yuan, W.: Improved estimate of global gross primary
production for reproducing its long-term variation, 1982–2017, figshare,
Dataset, https://doi.org/10.6084/m9.figshare.8942336.v3, 2019.
Zheng, Y., Zhang, L., Xiao, J., Yuan, W., Yan, M., Li, T., and Zhang, Z.:
Sources of uncertainty in gross primary productivity simulated by light use
efficiency models: Model structure, parameters, input data, and spatial
resolution, Agr. Forest. Meteorol., 263, 242–257,
https://doi.org/10.1016/j.agrformet.2018.08.003, 2018.
Zhou, S., Williams, A. P., Berg, A. M., Cook, B. I., Zhang, Y., Hagemann,
S., Lorenz, R., Seneviratne, S. I., and Gentine, P.: Land-atmosphere
feedbacks exacerbate concurrent soil drought and atmospheric aridity, P.
Natl. Acad. Sci. USA., 116, 18848–18853, 2019a.
Zhou, S., Zhang, Y., Williams, A. P., and Gentine, P.: Projected increases
in intensity, frequency, and terrestrial carbon costs of compound drought
and aridity events, Sci. Adv., 5, eaau5740, https://doi.org/10.1126/sciadv.aau5740, 2019b.
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais,
P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E.,
Koven, C., Li, Y., Lian, X., Liu, Y., Liu, R., Mao, J., Pan, Y., Peng, S.,
Penuelas, J., Poulter, B., Pugh, T. A. M., Stocker, B. D., Viovy, N., Wang, X.,
Wang, Y., Xiao, Z., Yang, H., Zaehle, S., and Zeng, N.: Greening of the Earth
and its drivers, Nat. Clim. Change, 6, 791–796, https://doi.org/10.1038/nclimate3004,
2016.
Short summary
Accurately reproducing the interannual variations in vegetation gross primary production (GPP) is a major challenge. A global GPP dataset was generated by integrating the regulations of several major environmental variables with long-term changes. The dataset can effectively reproduce the spatial, seasonal, and particularly interannual variations in global GPP. Our study will contribute to accurate carbon flux estimates at long timescales.
Accurately reproducing the interannual variations in vegetation gross primary production (GPP)...
Altmetrics
Final-revised paper
Preprint