Articles | Volume 14, issue 6
https://doi.org/10.5194/essd-14-2613-2022
© Author(s) 2022. 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-14-2613-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A 1 km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019
Peilin Song
Key Laboratory of Water Cycle and Related Land Surface Processes,
Institute of Geographic Sciences and Natural Resources Research, The Chinese
Academy of Sciences, Beijing 100101, China
State Key Laboratory of Remote Sensing Science, Aerospace
Information Research Institute, Chinese Academy of Sciences. Beijing 100101,
China
now at: School of Electronic Science and Engineering, Xi'an
Jiaotong University, Xi'an, 710049, China
Key Laboratory of Water Cycle and Related Land Surface Processes,
Institute of Geographic Sciences and Natural Resources Research, The Chinese
Academy of Sciences, Beijing 100101, China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Jiancheng Shi
National Space Science Center, Chinese Academy of Sciences, Beijing
100190, China
Tianjie Zhao
State Key Laboratory of Remote Sensing Science, Aerospace
Information Research Institute, Chinese Academy of Sciences. Beijing 100101,
China
Bing Tong
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
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Deli Meng, Jianping Guo, Juan Chen, Xiaoran Guo, Ning Li, Yuping Sun, Zhen Zhang, Na Tang, Hui Xu, Tianmeng Chen, Rongfang Yang, and Jiajia Hua
Earth Syst. Sci. Data, 17, 4023–4037, https://doi.org/10.5194/essd-17-4023-2025, https://doi.org/10.5194/essd-17-4023-2025, 2025
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This study provides a high-resolution dataset of low-level atmospheric turbulence across China, using radar and weather balloon observations. It reveals regional and seasonal variations in turbulence, with stronger activity in spring and summer. The dataset supports weather forecasting, aviation safety, and low-altitude flight planning, aiding China's growing low-altitude economy, and is accessible at https://doi.org/10.5281/zenodo.14959025.
Yongyong Zhang, Yongqiang Zhang, Xiaoyan Zhai, Jun Xia, Qiuhong Tang, Wei Wang, Jian Wu, Xiaoyu Niu, and Bing Han
Hydrol. Earth Syst. Sci., 29, 3257–3275, https://doi.org/10.5194/hess-29-3257-2025, https://doi.org/10.5194/hess-29-3257-2025, 2025
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It is challenging to investigate flood variabilities and their formation mechanisms from massive event samples. This study explores spatiotemporal variabilities of 1446 flood events using hierarchical and partitional clustering methods. Control mechanisms of meteorological and physio-geographical factors are explored for individual flood event classes using constrained rank analysis. This gives insights into comprehensive changes in flood events and aids in flood prediction and control.
Xiaoran Guo, Jianping Guo, Deli Meng, Yuping Sun, Zhen Zhang, Hui Xu, Liping Zeng, Juan Chen, Ning Li, and Tianmeng Chen
Earth Syst. Sci. Data, 17, 3541–3552, https://doi.org/10.5194/essd-17-3541-2025, https://doi.org/10.5194/essd-17-3541-2025, 2025
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Optimal atmospheric dynamic conditions are essential for convective storms. This study generates a dataset of high-resolution divergence and vorticity profiles using the measurements of a radar wind profiler mesonet in Beijing. The negative divergence and positive vorticity are present ahead of rainfall events. This suggests that this dataset can help improve our understanding of the pre-storm environment and has the potential to be applied in weather forecasting.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Yutong Wang, Huazhe Shang, Chenqian Tang, Jian Xu, Tianyang Ji, Wenwu Wang, Lesi Wei, Yonghui Lei, Jiancheng Shi, and Husi Letu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2471, https://doi.org/10.5194/egusphere-2025-2471, 2025
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By analyzing global CloudSat data, we identified that most liquid cloud profiles have triangle-shaped or steadily decreasing structures, and we developed a new method using pattern recognition, fitting techniques, and machine learning to accurately estimate these profiles. This research advances our understanding of cloud life cycle and improves the ability to characterize cloud profiles, which is crucial for enhancing weather forecast and climate change research.
Xiaozhong Cao, Qiyun Guo, Haowen Luo, Rongkang Yang, Peng Zhang, Jianping Guo, Jincheng Wang, Die Xiao, Jianping Du, Zhongliang Sun, Shijun Liu, Sijie Chen, and Anfan Huang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2012, https://doi.org/10.5194/egusphere-2025-2012, 2025
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This study aims to introduce in-situ profiling techniques and cost-effective technology for upper-air observation—the Round-trip Drifting Sounding System (RDSS)—which reduces costs relative to intensive sounding and achieves three sounding phases: Ascent-Drift-Descent (ADD). The RDSS not only provides additional data for weather analysis and numerical prediction models but also makes substantial contributions to targeted observations.
Mingwei Li, Shouzhi Chen, Fanghua Hao, Nan Wang, Zhaofei Wu, Yue Xu, Jing Zhang, Yongqiang Zhang, and Yongshuo H. Fu
Hydrol. Earth Syst. Sci., 29, 2081–2095, https://doi.org/10.5194/hess-29-2081-2025, https://doi.org/10.5194/hess-29-2081-2025, 2025
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Climate-driven shifts in vegetation phenology have a significant impact on hydrological processes. In this study, we integrated a process-based phenology module into the SWAT-Carbon model, which led to a substantial improvement in the simulation of vegetation dynamics and hydrological processes in the Jinsha River watershed. Our findings highlight the critical need to incorporate vegetation phenology into hydrological models to achieve a more accurate representation of ecohydrological processes.
Defeng Feng, Tianjie Zhao, Jingyao Zheng, Yu Bai, Youhua Ran, Xiaokang Kou, Lingmei Jiang, Ziqian Zhang, Pei Yu, Jinbiao Zhu, Jie Pan, Jiancheng Shi, and Yuei-An Liou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-62, https://doi.org/10.5194/essd-2025-62, 2025
Revised manuscript accepted for ESSD
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This study introduces a downscaling approach that integrates passive microwave and optical satellite data to generate a long-term (2002–2023), high-resolution (0.05°) global near-surface FT state dataset, ensuring daily seamless continuity. The dataset achieves an overall accuracy of 83.78%, consistent with the microwave-based dataset while offering enhanced spatial detail. This record providing detailed FT information, enhancing the understanding of hydrological and ecological impacts globally.
Seoung Soo Lee, Chang Hoon Jung, Jinho Choi, Young Jun Yoon, Junshik Um, Youtong Zheng, Jianping Guo, Manguttathil G. Manoj, Sang-Keun Song, and Kyung-Ja Ha
Atmos. Chem. Phys., 25, 705–726, https://doi.org/10.5194/acp-25-705-2025, https://doi.org/10.5194/acp-25-705-2025, 2025
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This study attempts to test a general factor that explains differences in the properties of different mixed-phase clouds using a modeling tool. Although this attempt is not to identify a factor that can perfectly explain and represent the properties of different mixed-phase clouds, we believe that this attempt acts as a valuable stepping stone towards a more complete, general way of using climate models to better predict climate change.
Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen
Earth Syst. Sci. Data, 16, 5753–5766, https://doi.org/10.5194/essd-16-5753-2024, https://doi.org/10.5194/essd-16-5753-2024, 2024
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Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Deli Meng, Jianping Guo, Xiaoran Guo, Yinjun Wang, Ning Li, Yuping Sun, Zhen Zhang, Na Tang, Haoran Li, Fan Zhang, Bing Tong, Hui Xu, and Tianmeng Chen
Atmos. Chem. Phys., 24, 8703–8720, https://doi.org/10.5194/acp-24-8703-2024, https://doi.org/10.5194/acp-24-8703-2024, 2024
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The turbulence in the planetary boundary layer (PBL) over the Tibetan Plateau (TP) remains unclear. Here we elucidate the vertical profile of and temporal variation in the turbulence dissipation rate in the PBL over the TP based on a radar wind profiler (RWP) network. To the best of our knowledge, this is the first time that the turbulence profile over the whole TP has been revealed. Furthermore, the possible mechanisms of clouds acting on the PBL turbulence structure are investigated.
Xiaoran Guo, Jianping Guo, Tianmeng Chen, Ning Li, Fan Zhang, and Yuping Sun
Atmos. Chem. Phys., 24, 8067–8083, https://doi.org/10.5194/acp-24-8067-2024, https://doi.org/10.5194/acp-24-8067-2024, 2024
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The prediction of downhill thunderstorms (DSs) remains elusive. We propose an objective method to identify DSs, based on which enhanced and dissipated DSs are discriminated. A radar wind profiler (RWP) mesonet is used to derive divergence and vertical velocity. The mid-troposphere divergence and prevailing westerlies enhance the intensity of DSs, whereas low-level divergence is observed when the DS dissipates. The findings highlight the key role that an RWP mesonet plays in the evolution of DSs.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Boming Liu, Xin Ma, Jianping Guo, Renqiang Wen, Hui Li, Shikuan Jin, Yingying Ma, Xiaoran Guo, and Wei Gong
Atmos. Chem. Phys., 24, 4047–4063, https://doi.org/10.5194/acp-24-4047-2024, https://doi.org/10.5194/acp-24-4047-2024, 2024
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Accurate wind profile estimation, especially for the lowest few hundred meters of the atmosphere, is of great significance for the weather, climate, and renewable energy sector. We propose a novel method that combines the power-law method with the random forest algorithm to extend wind profiles beyond the surface layer. Compared with the traditional algorithm, this method has better stability and spatial applicability and can be used to obtain the wind profiles on different land cover types.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
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A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Hui Xu, Jianping Guo, Bing Tong, Jinqiang Zhang, Tianmeng Chen, Xiaoran Guo, Jian Zhang, and Wenqing Chen
Atmos. Chem. Phys., 23, 15011–15038, https://doi.org/10.5194/acp-23-15011-2023, https://doi.org/10.5194/acp-23-15011-2023, 2023
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The radiative effect of cloud remains one of the largest uncertain factors in climate change, largely due to the lack of cloud vertical structure (CVS) observations. The study presents the first near-global CVS climatology using high-vertical-resolution soundings. Single-layer cloud mainly occurs over arid regions. As the number of cloud layers increases, clouds tend to have lower bases and thinner layer thicknesses. The occurrence frequency of cloud exhibits a pronounced seasonal diurnal cycle.
Boming Liu, Xin Ma, Jianping Guo, Hui Li, Shikuan Jin, Yingying Ma, and Wei Gong
Atmos. Chem. Phys., 23, 3181–3193, https://doi.org/10.5194/acp-23-3181-2023, https://doi.org/10.5194/acp-23-3181-2023, 2023
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Wind energy is one of the most essential clean and renewable forms of energy in today’s world. However, the traditional power law method generally estimates the hub-height wind speed by assuming a constant exponent between surface and hub-height wind speeds. This inevitably leads to significant uncertainties in estimating the wind speed profile. To minimize the uncertainties, we here use a machine learning algorithm known as random forest to estimate the wind speed at hub height.
Seoung Soo Lee, Junshik Um, Won Jun Choi, Kyung-Ja Ha, Chang Hoon Jung, Jianping Guo, and Youtong Zheng
Atmos. Chem. Phys., 23, 273–286, https://doi.org/10.5194/acp-23-273-2023, https://doi.org/10.5194/acp-23-273-2023, 2023
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This paper elaborates on process-level mechanisms regarding how the interception of radiation by aerosols interacts with the surface heat fluxes and atmospheric instability in warm cumulus clouds. This paper elucidates how these mechanisms vary with the location or altitude of an aerosol layer. This elucidation indicates that the location of aerosol layers should be taken into account for parameterizations of aerosol–cloud interactions.
Shaoyang He, Yongqiang Zhang, Ning Ma, Jing Tian, Dongdong Kong, and Changming Liu
Earth Syst. Sci. Data, 14, 5463–5488, https://doi.org/10.5194/essd-14-5463-2022, https://doi.org/10.5194/essd-14-5463-2022, 2022
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This study developed a daily, 500 m evapotranspiration and gross primary production product (PML-V2(China)) using a locally calibrated water–carbon coupled model, PML-V2, which was well calibrated against observations at 26 flux sites across nine land cover types. PML-V2 (China) performs satisfactorily in the plot- and basin-scale evaluations compared with other mainstream products. It improved intra-annual ET and GPP dynamics, particularly in the cropland ecosystem.
Seoung Soo Lee, Jinho Choi, Goun Kim, Kyung-Ja Ha, Kyong-Hwan Seo, Chang Hoon Jung, Junshik Um, Youtong Zheng, Jianping Guo, Sang-Keun Song, Yun Gon Lee, and Nobuyuki Utsumi
Atmos. Chem. Phys., 22, 9059–9081, https://doi.org/10.5194/acp-22-9059-2022, https://doi.org/10.5194/acp-22-9059-2022, 2022
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This study investigates how aerosols affect clouds and precipitation and how the aerosol effects vary with varying types of clouds that are characterized by cloud depth in two metropolitan areas in East Asia. As cloud depth increases, the enhancement of precipitation amount transitions to no changes in precipitation amount with increasing aerosol concentrations. This indicates that cloud depth needs to be considered for a comprehensive understanding of aerosol-cloud interactions.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
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To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Kaixu Bai, Ke Li, Mingliang Ma, Kaitao Li, Zhengqiang Li, Jianping Guo, Ni-Bin Chang, Zhuo Tan, and Di Han
Earth Syst. Sci. Data, 14, 907–927, https://doi.org/10.5194/essd-14-907-2022, https://doi.org/10.5194/essd-14-907-2022, 2022
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The Long-term Gap-free High-resolution Air Pollutant concentration dataset, providing gap-free aerosol optical depth (AOD) and PM2.5 and PM10 concentration with a daily 1 km resolution for 2000–2020 in China, is generated and made publicly available. This is the first long-term gap-free high-resolution aerosol dataset in China and has great potential to trigger multidisciplinary applications in Earth observations, climate change, public health, ecosystem assessment, and environment management.
Linye Song, Shangfeng Chen, Wen Chen, Jianping Guo, Conglan Cheng, and Yong Wang
Atmos. Chem. Phys., 22, 1669–1688, https://doi.org/10.5194/acp-22-1669-2022, https://doi.org/10.5194/acp-22-1669-2022, 2022
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This study shows that in most years when haze pollution (HP) over the North China Plain (NCP) is more (less) serious in winter, air conditions in the following spring are also worse (better) than normal. Conversely, there are some years when HP in the following spring is opposed to that in winter. It is found that North Atlantic sea surface temperature (SST) anomalies play important roles in HP evolution over the NCP. Thus North Atlantic SST is an important preceding signal for NCP HP evolution.
Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-26, https://doi.org/10.5194/amt-2022-26, 2022
Publication in AMT not foreseen
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Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is the comparison of wind speed on a large scale between the Aeolus, ERA5 and RS , shedding important light on the data application of Aeolus wind products.
Jianping Guo, Jian Zhang, Kun Yang, Hong Liao, Shaodong Zhang, Kaiming Huang, Yanmin Lv, Jia Shao, Tao Yu, Bing Tong, Jian Li, Tianning Su, Steve H. L. Yim, Ad Stoffelen, Panmao Zhai, and Xiaofeng Xu
Atmos. Chem. Phys., 21, 17079–17097, https://doi.org/10.5194/acp-21-17079-2021, https://doi.org/10.5194/acp-21-17079-2021, 2021
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The planetary boundary layer (PBL) is the lowest part of the troposphere, and boundary layer height (BLH) is the depth of the PBL and is of critical importance to the dispersion of air pollution. The study presents the first near-global BLH climatology by using high-resolution (5-10 m) radiosonde measurements. The variations in BLH exhibit large spatial and temporal dependence, with a peak at 17:00 local solar time. The most promising reanalysis product is ERA-5 in terms of modeling BLH.
Seoung Soo Lee, Kyung-Ja Ha, Manguttathil Gopalakrishnan Manoj, Mohammad Kamruzzaman, Hyungjun Kim, Nobuyuki Utsumi, Youtong Zheng, Byung-Gon Kim, Chang Hoon Jung, Junshik Um, Jianping Guo, Kyoung Ock Choi, and Go-Un Kim
Atmos. Chem. Phys., 21, 16843–16868, https://doi.org/10.5194/acp-21-16843-2021, https://doi.org/10.5194/acp-21-16843-2021, 2021
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Using a modeling framework, a midlatitude stratocumulus cloud system is simulated. It is found that cloud mass in the system becomes very low due to interactions between ice and liquid particles compared to that in the absence of ice particles. It is also found that interactions between cloud mass and aerosols lead to a reduction in cloud mass in the system, and this is contrary to an aerosol-induced increase in cloud mass in the absence of ice particles.
Ifeanyichukwu C. Nduka, Chi-Yung Tam, Jianping Guo, and Steve Hung Lam Yim
Atmos. Chem. Phys., 21, 13443–13454, https://doi.org/10.5194/acp-21-13443-2021, https://doi.org/10.5194/acp-21-13443-2021, 2021
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This study analyzed the nature, mechanisms and drivers for hot-and-polluted episodes (HPEs) in the Pearl River Delta, China. A total of eight HPEs were identified and can be grouped into three clusters of HPEs that were respectively driven (1) by weak subsidence and convection induced by approaching tropical cyclones, (2) by calm conditions with low wind speed in the lower atmosphere and (3) by the combination of both aforementioned conditions.
Xiangjin Meng, Kebiao Mao, Fei Meng, Jiancheng Shi, Jiangyuan Zeng, Xinyi Shen, Yaokui Cui, Lingmei Jiang, and Zhonghua Guo
Earth Syst. Sci. Data, 13, 3239–3261, https://doi.org/10.5194/essd-13-3239-2021, https://doi.org/10.5194/essd-13-3239-2021, 2021
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In order to improve the accuracy of China's regional agricultural drought monitoring and climate change research, we produced a long-term series of soil moisture products by constructing a time and depth correction model for three soil moisture products with the help of ground observation data. The spatial resolution is improved by building a spatial weight decomposition model, and validation indicates that the new product can meet application needs.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
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This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Mengmeng Cao, Kebiao Mao, Yibo Yan, Jiancheng Shi, Han Wang, Tongren Xu, Shu Fang, and Zijin Yuan
Earth Syst. Sci. Data, 13, 2111–2134, https://doi.org/10.5194/essd-13-2111-2021, https://doi.org/10.5194/essd-13-2111-2021, 2021
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We constructed a temperature depth and observation time correction model to eliminate the sampling depth and temporal differences among different data. Then, we proposed a reconstructed spatial model that filters and removes missing pixels and low-quality pixels contaminated by clouds from raw SST images and retrieves real sea surface temperatures under cloud coverage based on multisource data to generate a high-quality unified global SST product with long-term spatiotemporal continuity.
Tianmeng Chen, Zhanqing Li, Ralph A. Kahn, Chuanfeng Zhao, Daniel Rosenfeld, Jianping Guo, Wenchao Han, and Dandan Chen
Atmos. Chem. Phys., 21, 6199–6220, https://doi.org/10.5194/acp-21-6199-2021, https://doi.org/10.5194/acp-21-6199-2021, 2021
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A convective cloud identification process is developed using geostationary satellite data from Himawari-8.
Convective cloud fraction is generally larger before noon and smaller in the afternoon under polluted conditions, but megacities and complex topography can influence the pattern.
A robust relationship between convective cloud and aerosol loading is found. This pattern varies with terrain height and is modulated by varying thermodynamic, dynamical, and humidity conditions during the day.
Jianping Guo, Boming Liu, Wei Gong, Lijuan Shi, Yong Zhang, Yingying Ma, Jian Zhang, Tianmeng Chen, Kaixu Bai, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys., 21, 2945–2958, https://doi.org/10.5194/acp-21-2945-2021, https://doi.org/10.5194/acp-21-2945-2021, 2021
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China have thus far not been evaluated by in situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future research and applications.
Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-41, https://doi.org/10.5194/acp-2021-41, 2021
Revised manuscript not accepted
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future researches and applications.
Kaixu Bai, Ke Li, Chengbo Wu, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 12, 3067–3080, https://doi.org/10.5194/essd-12-3067-2020, https://doi.org/10.5194/essd-12-3067-2020, 2020
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PM2.5 data from the national air quality monitoring network in China suffered from significant inconsistency and inhomogeneity issues. To create a coherent PM2.5 concentration dataset to advance our understanding of haze pollution and its impact on weather and climate, we homogenized this PM2.5 dataset between 2015 and 2019 after filling in the data gaps. The homogenized PM2.5 data is found to better characterize the variation of aerosol in space and time compared to the original dataset.
Yang Yang, Min Chen, Xiujuan Zhao, Dan Chen, Shuiyong Fan, Jianping Guo, and Shaukat Ali
Atmos. Chem. Phys., 20, 12527–12547, https://doi.org/10.5194/acp-20-12527-2020, https://doi.org/10.5194/acp-20-12527-2020, 2020
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This study analyzed the impacts of aerosol–radiation interaction on radiation and meteorological forecasts using the offline coupling of WRF and high-frequency updated AOD simulated by WRF-Chem. The results revealed that aerosol–radiation interaction had a positive influence on the improvement of predictive accuracy, including 2 m temperature (~ 73.9 %) and horizontal wind speed (~ 7.8 %), showing potential prospects for its application in regional numerical weather prediction in northern China.
Ruqian Miao, Qi Chen, Yan Zheng, Xi Cheng, Yele Sun, Paul I. Palmer, Manish Shrivastava, Jianping Guo, Qiang Zhang, Yuhan Liu, Zhaofeng Tan, Xuefei Ma, Shiyi Chen, Limin Zeng, Keding Lu, and Yuanhang Zhang
Atmos. Chem. Phys., 20, 12265–12284, https://doi.org/10.5194/acp-20-12265-2020, https://doi.org/10.5194/acp-20-12265-2020, 2020
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In this study we evaluated the model performances for simulating secondary inorganic aerosol (SIA) and organic aerosol (OA) in PM2.5 in China against comprehensive datasets. The potential biases from factors related to meteorology, emission, chemistry, and atmospheric removal are systematically investigated. This study provides a comprehensive understanding of modeling PM2.5, which is important for studies on the effectiveness of emission control strategies.
Bing Zhao, Kebiao Mao, Yulin Cai, Jiancheng Shi, Zhaoliang Li, Zhihao Qin, Xiangjin Meng, Xinyi Shen, and Zhonghua Guo
Earth Syst. Sci. Data, 12, 2555–2577, https://doi.org/10.5194/essd-12-2555-2020, https://doi.org/10.5194/essd-12-2555-2020, 2020
Short summary
Short summary
Land surface temperature is a key variable for climate and ecological environment research. We reconstructed a land surface temperature dataset (2003–2017) to take advantage of the ground observation site through building a reconstruction model which overcomes the effects of cloud. The reconstructed dataset exhibited significant improvements and can be used for the spatiotemporal evaluation of land surface temperature and for high-temperature and drought-monitoring studies.
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Short summary
Soil moisture information is crucial for understanding the earth surface, but currently available satellite-based soil moisture datasets are imperfect either in their spatiotemporal resolutions or in ensuring image completeness from cloudy weather. In this study, therefore, we developed one soil moisture data product over China that has tackled most of the above problems. This data product has the potential to promote the investigation of earth hydrology and be extended to the global scale.
Soil moisture information is crucial for understanding the earth surface, but currently...
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