Articles | Volume 15, issue 3
https://doi.org/10.5194/essd-15-1419-2023
© Author(s) 2023. 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-15-1419-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A GeoNEX-based high-spatiotemporal-resolution product of land surface downward shortwave radiation and photosynthetically active radiation
Ruohan Li
Department of Geographical Sciences, University of Maryland, College
Park, MD 20742, USA
Dongdong Wang
CORRESPONDING AUTHOR
Department of Geographical Sciences, University of Maryland, College
Park, MD 20742, USA
Weile Wang
NASA Ames Research Center, Mountain View, CA 94043, USA
Ramakrishna Nemani
NASA Ames Research Center, Mountain View, CA 94043, USA
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Conor T. Doherty, Weile Wang, Hirofumi Hashimoto, and Ian G. Brosnan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1886, https://doi.org/10.5194/egusphere-2024-1886, 2024
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We present, analyze, and validate a methodology for quantifying uncertainty in gridded meteorological data products produced by spatial interpolation. In a validation case study using daily maximum near-surface air temperature (Tmax), the method works well and produces predictive distributions with closely matching theoretical versus actual coverage levels. Application of the method reveals that the magnitude of uncertainty in interpolated Tmax varies significantly in both space and time.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
E. P. Maurer, D. L. Ficklin, and W. Wang
Hydrol. Earth Syst. Sci., 20, 685–696, https://doi.org/10.5194/hess-20-685-2016, https://doi.org/10.5194/hess-20-685-2016, 2016
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To translate climate model output from its native coarse scale to a finer scale more representative of that at which societal impacts are experienced, a common method applied is statistical downscaling. A component of many statistical downscaling techniques is quantile mapping (QM). QM can be applied at different spatial scales, and here we study how skill varies with spatial scale. We find the highest skill is generally obtained when applying QM at approximately a 50 km spatial scale.
W. Wang and R. Nemani
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-13957-2014, https://doi.org/10.5194/bgd-11-13957-2014, 2014
Revised manuscript not accepted
D. C. Morton, G. J. Collatz, D. Wang, J. T. Randerson, L. Giglio, and Y. Chen
Biogeosciences, 10, 247–260, https://doi.org/10.5194/bg-10-247-2013, https://doi.org/10.5194/bg-10-247-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Energy and Emissions
Meteorological, snow and soil data, CO2, water and energy fluxes from a low-Arctic valley of Northern Quebec
Systematically tracking the hourly progression of large wildfires using GOES satellite observations
GloCAB: global cropland burned area from mid-2002 to 2020
Greenhouse gas emissions and their trends over the last 3 decades across Africa
A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products
Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5)
Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution
An adapted hourly Himawari-8 fire product for China: principle, methodology and verification
Mapping photovoltaic power plants in China using Landsat, random forest, and Google Earth Engine
Florent Domine, Denis Sarrazin, Daniel F. Nadeau, Georg Lackner, and Maria Belke-Brea
Earth Syst. Sci. Data, 16, 1523–1541, https://doi.org/10.5194/essd-16-1523-2024, https://doi.org/10.5194/essd-16-1523-2024, 2024
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The forest–tundra ecotone is the transition region between the boreal forest and Arctic tundra. It spans over 13 000 km across the Arctic and is evolving rapidly because of climate change. We provide extensive data sets of two sites 850 m apart, one in tundra and one in forest in this ecotone for use in various models. Data include meteorological and flux data and unique snow and soil physics data.
Tianjia Liu, James T. Randerson, Yang Chen, Douglas C. Morton, Elizabeth B. Wiggins, Padhraic Smyth, Efi Foufoula-Georgiou, Roy Nadler, and Omer Nevo
Earth Syst. Sci. Data, 16, 1395–1424, https://doi.org/10.5194/essd-16-1395-2024, https://doi.org/10.5194/essd-16-1395-2024, 2024
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To improve our understanding of extreme wildfire behavior, we use geostationary satellite data to develop the GOFER algorithm and track the hourly fire progression of large wildfires. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery and reveals considerable variability in fire spread rates on diurnal timescales. We create a product of hourly fire perimeters, active-fire lines, and fire spread rates for 28 fires in California.
Joanne V. Hall, Fernanda Argueta, Maria Zubkova, Yang Chen, James T. Randerson, and Louis Giglio
Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, https://doi.org/10.5194/essd-16-867-2024, 2024
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Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
Mounia Mostefaoui, Philippe Ciais, Matthew J. McGrath, Philippe Peylin, Prabir K. Patra, and Yolandi Ernst
Earth Syst. Sci. Data, 16, 245–275, https://doi.org/10.5194/essd-16-245-2024, https://doi.org/10.5194/essd-16-245-2024, 2024
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Our aim is to assess African anthropogenic greenhouse gas emissions and removals by using different data products, including inventories and process-based models, and to compare their relative merits with inversion data coming from satellites. We show a good match among the various estimates in terms of overall trends at a regional level and on a decadal basis, but large differences exist even among similar data types, which is a limit to the possibility of verification of country-reported data.
Fei Pan, Xiaodan Wu, Qicheng Zeng, Rongqi Tang, Jingping Wang, Xingwen Lin, Dongqin You, Jianguang Wen, and Qing Xiao
Earth Syst. Sci. Data, 16, 161–176, https://doi.org/10.5194/essd-16-161-2024, https://doi.org/10.5194/essd-16-161-2024, 2024
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To effectively tackle the challenges posed by spatial-scale differences and spatial heterogeneity, this paper presents a distinctive coarse pixel-scale ground “truth" dataset by upscaling sparsely distributed in situ measurements. This dataset is a valuable resource for validating and correcting global surface albedo products, enhancing reference data accuracy by 6.04 %. Remarkably, it substantially enhances 17.09 % in regions with strong spatial heterogeneity.
Yang Chen, Joanne Hall, Dave van Wees, Niels Andela, Stijn Hantson, Louis Giglio, Guido R. van der Werf, Douglas C. Morton, and James T. Randerson
Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, https://doi.org/10.5194/essd-15-5227-2023, 2023
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Using multiple sets of remotely sensed data, we created a dataset of monthly global burned area from 1997 to 2020. The estimated annual global burned area is 774 million hectares, significantly higher than previous estimates. Burned area declined by 1.21% per year due to extensive fire loss in savanna, grassland, and cropland ecosystems. This study enhances our understanding of the impact of fire on the carbon cycle and climate system, and may improve the predictions of future fire changes.
Mark Omara, Ritesh Gautam, Madeleine A. O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David R. Lyon, Apisada Chulakadabba, Christopher Chan Miller, Jonathan Franklin, Steven C. Wofsy, and Steven P. Hamburg
Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, https://doi.org/10.5194/essd-15-3761-2023, 2023
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We acquire, integrate, and analyze ~ 6 million geospatial oil and gas infrastructure data records based on information available in the public domain and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fulfill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.
Jie Chen, Qiancheng Lv, Shuang Wu, Yelu Zeng, Manchun Li, Ziyue Chen, Enze Zhou, Wei Zheng, Cheng Liu, Xiao Chen, Jing Yang, and Bingbo Gao
Earth Syst. Sci. Data, 15, 1911–1931, https://doi.org/10.5194/essd-15-1911-2023, https://doi.org/10.5194/essd-15-1911-2023, 2023
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The Himawari-8 fire product is the mainstream fire product with the highest temporal resolution, yet it presents large uncertainties and is not suitable for reliable real-time fire monitoring in China. To address this issue, we proposed an adaptive hourly NSMC (National Satellite Meteorological Center) Himawari-8 fire product for China; the overall accuracy increased from 54 % (original Himawari product) to 80 %. This product can largely enhance real-time fire monitoring and relevant research.
Xunhe Zhang, Ming Xu, Shujian Wang, Yongkai Huang, and Zunyi Xie
Earth Syst. Sci. Data, 14, 3743–3755, https://doi.org/10.5194/essd-14-3743-2022, https://doi.org/10.5194/essd-14-3743-2022, 2022
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Photovoltaic (PV) power plants have been increasingly built across the world to mitigate climate change. A map of the PV power plants is important for policy management and environmental assessment. We established a map of PV power plants in China by 2020, covering a total area of 2917 km2. Based on the derived map, we found that most PV power plants were situated on cropland. In addition, the installation of PV power plants has generally decreased the vegetation cover.
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Short summary
There has been an increasing need for high-spatiotemporal-resolution surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) data for ecological, hydrological, carbon, and solar photovoltaic research. This study produced a new 1 km hourly product of land surface DSR and PAR from the enhanced GeoNEX new-generation geostationary data. Our validation indicated that the GeoNEX DSR and PAR product has a higher accuracy than other existing products.
There has been an increasing need for high-spatiotemporal-resolution surface downward shortwave...
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