Evaluation of reanalysis soil moisture products using Cosmic Ray Neutron Sensor observations across the globe. Zheng, Y., Coxon, G., Woods, R., Power, D., Rico-Ramirez, M. A., McJannet, D., Rosolem, R., Li, J., & Feng, P. October, 2023. ![Evaluation of reanalysis soil moisture products using Cosmic Ray Neutron Sensor observations across the globe [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper doi abstract bibtex Abstract. Accurate soil moisture information is vital for flood and drought predictions, crop growth and agricultural water management. Reanalysis soil moisture products with multi-decadal temporal coverage are gradually becoming a good alternative for providing global soil moisture data in various applications compared to in-situ measurements and satellite products. Much effort has been devoted to evaluating the performance of soil moisture products, yet the scale discrepancy between point measurements and grid cell soil moisture products limits the assessment quality. As the land surface and hydrological modelling community evolve towards the next generation of (sub)kilometer resolution models, Cosmic Ray Neutron Sensors (CRNS) that provide estimates of root-zone soil moisture at the field scale (~250 m radius from the sensor and up to 0.7 m deep), may consequently be more suitable for soil moisture product evaluation as they cover a relatively larger footprint, when compared to traditional methods. In this study, we perform a comprehensive evaluation of seven widely-used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40 and GLEAM datasets) against 135 CRNS sites from the UK, Europe, USA and Australia. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products exhibit good temporal correlation with the measurements, with the median of temporal correlation coefficient (R) values spanning from 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies timeseries, with R values varying from 0.49 to 0.70. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate in arid climates and underestimate in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high Bias are detected in some sites from west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CFSv2, CRA40, GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. We recommend ERA5-Land and CFSv2 should be used in humid climates, whereas CRA40 and GLEAM perform better in arid regions. GLEAM is more effective in shrubland regions. Our findings also provide insights on directions for improvement of soil moisture products for product developers.
@misc{zheng_evaluation_2023,
title = {Evaluation of reanalysis soil moisture products using {Cosmic} {Ray} {Neutron} {Sensor} observations across the globe},
copyright = {https://creativecommons.org/licenses/by/4.0/},
url = {https://hess.copernicus.org/preprints/hess-2023-224/hess-2023-224.pdf},
doi = {10.5194/hess-2023-224},
abstract = {Abstract. Accurate soil moisture information is vital for flood and drought predictions, crop growth and agricultural water management. Reanalysis soil moisture products with multi-decadal temporal coverage are gradually becoming a good alternative for providing global soil moisture data in various applications compared to in-situ measurements and satellite products. Much effort has been devoted to evaluating the performance of soil moisture products, yet the scale discrepancy between point measurements and grid cell soil moisture products limits the assessment quality. As the land surface and hydrological modelling community evolve towards the next generation of (sub)kilometer resolution models, Cosmic Ray Neutron Sensors (CRNS) that provide estimates of root-zone soil moisture at the field scale ({\textasciitilde}250 m radius from the sensor and up to 0.7 m deep), may consequently be more suitable for soil moisture product evaluation as they cover a relatively larger footprint, when compared to traditional methods. In this study, we perform a comprehensive evaluation of seven widely-used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40 and GLEAM datasets) against 135 CRNS sites from the UK, Europe, USA and Australia. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products exhibit good temporal correlation with the measurements, with the median of temporal correlation coefficient (R) values spanning from 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies timeseries, with R values varying from 0.49 to 0.70. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate in arid climates and underestimate in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high Bias are detected in some sites from west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CFSv2, CRA40, GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. We recommend ERA5-Land and CFSv2 should be used in humid climates, whereas CRA40 and GLEAM perform better in arid regions. GLEAM is more effective in shrubland regions. Our findings also provide insights on directions for improvement of soil moisture products for product developers.},
urldate = {2024-11-15},
publisher = {Global hydrology/Instruments and observation techniques},
author = {Zheng, Yanchen and Coxon, Gemma and Woods, Ross and Power, Daniel and Rico-Ramirez, Miguel Angel and McJannet, David and Rosolem, Rafael and Li, Jianzhu and Feng, Ping},
month = oct,
year = {2023},
}
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Reanalysis soil moisture products with multi-decadal temporal coverage are gradually becoming a good alternative for providing global soil moisture data in various applications compared to in-situ measurements and satellite products. Much effort has been devoted to evaluating the performance of soil moisture products, yet the scale discrepancy between point measurements and grid cell soil moisture products limits the assessment quality. As the land surface and hydrological modelling community evolve towards the next generation of (sub)kilometer resolution models, Cosmic Ray Neutron Sensors (CRNS) that provide estimates of root-zone soil moisture at the field scale (~250 m radius from the sensor and up to 0.7 m deep), may consequently be more suitable for soil moisture product evaluation as they cover a relatively larger footprint, when compared to traditional methods. In this study, we perform a comprehensive evaluation of seven widely-used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40 and GLEAM datasets) against 135 CRNS sites from the UK, Europe, USA and Australia. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products exhibit good temporal correlation with the measurements, with the median of temporal correlation coefficient (R) values spanning from 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies timeseries, with R values varying from 0.49 to 0.70. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate in arid climates and underestimate in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high Bias are detected in some sites from west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CFSv2, CRA40, GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. We recommend ERA5-Land and CFSv2 should be used in humid climates, whereas CRA40 and GLEAM perform better in arid regions. GLEAM is more effective in shrubland regions. Our findings also provide insights on directions for improvement of soil moisture products for product developers.","urldate":"2024-11-15","publisher":"Global hydrology/Instruments and observation techniques","author":[{"propositions":[],"lastnames":["Zheng"],"firstnames":["Yanchen"],"suffixes":[]},{"propositions":[],"lastnames":["Coxon"],"firstnames":["Gemma"],"suffixes":[]},{"propositions":[],"lastnames":["Woods"],"firstnames":["Ross"],"suffixes":[]},{"propositions":[],"lastnames":["Power"],"firstnames":["Daniel"],"suffixes":[]},{"propositions":[],"lastnames":["Rico-Ramirez"],"firstnames":["Miguel","Angel"],"suffixes":[]},{"propositions":[],"lastnames":["McJannet"],"firstnames":["David"],"suffixes":[]},{"propositions":[],"lastnames":["Rosolem"],"firstnames":["Rafael"],"suffixes":[]},{"propositions":[],"lastnames":["Li"],"firstnames":["Jianzhu"],"suffixes":[]},{"propositions":[],"lastnames":["Feng"],"firstnames":["Ping"],"suffixes":[]}],"month":"October","year":"2023","bibtex":"@misc{zheng_evaluation_2023,\n\ttitle = {Evaluation of reanalysis soil moisture products using {Cosmic} {Ray} {Neutron} {Sensor} observations across the globe},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\turl = {https://hess.copernicus.org/preprints/hess-2023-224/hess-2023-224.pdf},\n\tdoi = {10.5194/hess-2023-224},\n\tabstract = {Abstract. Accurate soil moisture information is vital for flood and drought predictions, crop growth and agricultural water management. Reanalysis soil moisture products with multi-decadal temporal coverage are gradually becoming a good alternative for providing global soil moisture data in various applications compared to in-situ measurements and satellite products. Much effort has been devoted to evaluating the performance of soil moisture products, yet the scale discrepancy between point measurements and grid cell soil moisture products limits the assessment quality. As the land surface and hydrological modelling community evolve towards the next generation of (sub)kilometer resolution models, Cosmic Ray Neutron Sensors (CRNS) that provide estimates of root-zone soil moisture at the field scale ({\\textasciitilde}250 m radius from the sensor and up to 0.7 m deep), may consequently be more suitable for soil moisture product evaluation as they cover a relatively larger footprint, when compared to traditional methods. In this study, we perform a comprehensive evaluation of seven widely-used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40 and GLEAM datasets) against 135 CRNS sites from the UK, Europe, USA and Australia. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products exhibit good temporal correlation with the measurements, with the median of temporal correlation coefficient (R) values spanning from 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies timeseries, with R values varying from 0.49 to 0.70. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate in arid climates and underestimate in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high Bias are detected in some sites from west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CFSv2, CRA40, GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. 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