Assessing the Performance of the South American Land Data Assimilation System Version 2 (SALDAS-2) Energy Balance across Diverse Biomes

Author:

de Ávila Álvaro Vasconcellos Araujo1,de Gonçalves Luis Gustavo Gonçalves2ORCID,Souza Vanessa de Arruda34ORCID,Alves Laurizio Emanuel Ribeiro1ORCID,Galetti Giovanna Deponte1,Maske Bianca Muss1,Getirana Augusto5ORCID,Ruhoff Anderson3ORCID,Biudes Marcelo Sacardi6ORCID,Machado Nadja Gomes7ORCID,Roberti Débora Regina4ORCID

Affiliation:

1. Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), Instituto Nacional de Pesquisas Espaciais (INPE), Cachoeira Paulista 12630-000, Brazil

2. Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 40127 Bologna, Italy

3. Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, Brazil

4. Departamento de Física, Universidade Federal de Santa Maria (UFSM), Santa Maria 97105-900, Brazil

5. Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

6. Instituto de Física, Universidade Federal de Mato Grosso (UFMT), Cuiabá 78060-900, Brazil

7. Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso (IFMT), Cuiabá 78005-390, Brazil

Abstract

Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance.

Funder

National Council for Scientific and Technological Development

Coordination for the Improvement of Higher Education Personnel

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

Reference97 articles.

1. Perspectives on the Future of Land Surface Models and the Challenges of Representing Complex Terrestrial Systems;Fisher;J. Adv. Model. Earth Syst.,2020

2. Advances in Land Surface Modelling;Blyth;Curr. Clim. Chang. Reports,2021

3. Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration;Glenn;CRC. Crit. Rev. Plant Sci.,2007

4. Pörtner, H.-O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., and Möller, V. (2022). Climate Change 2022: Impacts, Adaptation, and Vulnerability.

5. High-Resolution CSR GRACE RL05 Mascons;Save;J. Geophys. Res. Solid Earth,2016

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