A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America

This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the...

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Autores principales: Spennemann, P.C., Rivera, J.A., Celeste Saulo, A., Penalba, O.C.
Formato: JOUR
Materias:
Hydrometeorology
Land surface model
Soil moisture
South America
data assimilation
hydrometeorology
land surface
precipitation assessment
soil moisture
La Plata Basin
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_1525755X_v16_n1_p158_Spennemann
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_1525755X_v16_n1_p158_Spennemann
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spelling todo:paper_1525755X_v16_n1_p158_Spennemann2023-10-03T16:21:02Z A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America Spennemann, P.C. Rivera, J.A. Celeste Saulo, A. Penalba, O.C. Hydrometeorology Land surface model Soil moisture South America data assimilation hydrometeorology land surface precipitation assessment soil moisture La Plata Basin This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the need for assessing the reliability ofGLDASvariables to be used in the characterization of soil state and its variability at the regional scale. The focus is on the southeastern part of South America (SESA), which is part of the La Plata basin, one of the largest basins of the world, where agriculture is the main source of income. The results show thatGLDASdata capture soil moisture anomalies and their variability, taking into account regional and seasonal dependencies and showing correspondence with other proxies used to characterize soil states. Over large portions of the domain, and particularly over SESA, the correlation with the SPI is very high, with the second version of GLDAS, version 2 (GLDAS-2 v2), exhibiting the highest values regardless of the season. Similar results were obtained by comparing the surface soil moisture anomalies from theGLDASland surface model (LSM) against the satellite estimations for a shorter period of time. This work documents that the precipitation dataset used to force each LSM and the choice of the LSM are of major relevance for representing soil conditions in an adequate manner. The results are considered to support the use of GLDAS as an indicator of soil moisture states and for developing new soil moisture-monitoring indices that can be applied, for example, in the context of agricultural production management. © 2015 American Meteorological Society. Fil:Spennemann, P.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Celeste Saulo, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Penalba, O.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_1525755X_v16_n1_p158_Spennemann
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Hydrometeorology
Land surface model
Soil moisture
South America
data assimilation
hydrometeorology
land surface
precipitation assessment
soil moisture
La Plata Basin
spellingShingle Hydrometeorology
Land surface model
Soil moisture
South America
data assimilation
hydrometeorology
land surface
precipitation assessment
soil moisture
La Plata Basin
Spennemann, P.C.
Rivera, J.A.
Celeste Saulo, A.
Penalba, O.C.
A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America
topic_facet Hydrometeorology
Land surface model
Soil moisture
South America
data assimilation
hydrometeorology
land surface
precipitation assessment
soil moisture
La Plata Basin
description This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the need for assessing the reliability ofGLDASvariables to be used in the characterization of soil state and its variability at the regional scale. The focus is on the southeastern part of South America (SESA), which is part of the La Plata basin, one of the largest basins of the world, where agriculture is the main source of income. The results show thatGLDASdata capture soil moisture anomalies and their variability, taking into account regional and seasonal dependencies and showing correspondence with other proxies used to characterize soil states. Over large portions of the domain, and particularly over SESA, the correlation with the SPI is very high, with the second version of GLDAS, version 2 (GLDAS-2 v2), exhibiting the highest values regardless of the season. Similar results were obtained by comparing the surface soil moisture anomalies from theGLDASland surface model (LSM) against the satellite estimations for a shorter period of time. This work documents that the precipitation dataset used to force each LSM and the choice of the LSM are of major relevance for representing soil conditions in an adequate manner. The results are considered to support the use of GLDAS as an indicator of soil moisture states and for developing new soil moisture-monitoring indices that can be applied, for example, in the context of agricultural production management. © 2015 American Meteorological Society.
format JOUR
author Spennemann, P.C.
Rivera, J.A.
Celeste Saulo, A.
Penalba, O.C.
author_facet Spennemann, P.C.
Rivera, J.A.
Celeste Saulo, A.
Penalba, O.C.
author_sort Spennemann, P.C.
title A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America
title_short A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America
title_full A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America
title_fullStr A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America
title_full_unstemmed A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America
title_sort comparison of gldas soil moisture anomalies against standardized precipitation index and multisatellite estimations over south america
url http://hdl.handle.net/20.500.12110/paper_1525755X_v16_n1_p158_Spennemann
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