@Article{ZeriWCCVBMHCMAMG:2022:EvUsJU,
               author = "Zeri, Marcelo and Williams, Karina and Cunha, Ana Paula M. A. and 
                         Cunha Zeri, Gisleine da Silva and Vianna, Murilo S. and Blyth, 
                         Eleanor M. and Marthews, Toby R. and Hayman, Garry D. and Costa, 
                         Jos{\'e} Maria and Marengo, Jos{\'e} A. and Alval{\'a}, Regina 
                         C. S. and Moraes, Osvaldo L. L. and Galdos, Marcelo V.",
          affiliation = "{Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Met Office} and {Centro Nacional de Monitoramento 
                         e Alertas de Desastres Naturais (CEMADEN)} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {University of Leeds} and {UK 
                         Centre for Ecology \& Hydrology} and {UK Centre for Ecology \& 
                         Hydrology} and {UK Centre for Ecology \& Hydrology} and {Centro 
                         Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and 
                         {Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {University of Leeds}",
                title = "Importance of including soil moisture in drought monitoring over 
                         the Brazilian semiarid region: An evaluation using the JULES 
                         model, in situ observations, and remote sensing",
              journal = "Climate Resilience and Sustainability",
                 year = "2022",
               volume = "1",
               number = "1",
                pages = "e7",
             keywords = "drought, drought indices, drought management policies, land 
                         surface model, soil moisture.",
             abstract = "Soil moisture information is essential to monitoring of the 
                         intensity of droughts,the start of the rainy season, planting 
                         dates and early warnings of yield losses.We assess spatial and 
                         temporal trends of drought over the Brazilian semiaridregion by 
                         combining soil moisture observations from 360 stations, root zone 
                         soilmoisture from a leading land surface model, and a vegetation 
                         health index fromremote sensing. The soil moisture dataset was 
                         obtained from the network of sta-tions maintained by the National 
                         Center of Monitoring and Early Warning ofNatural Disasters 
                         (Cemaden), in Brazil. Soil water content at 10 to 35 cm depth,for 
                         the period 19792018, was obtained from running the JULES land 
                         surfacemodel (the Joint UK Land Environment Simulator). The 
                         modelled soil moisturewas correlated with measurements in the 
                         common period of 20152018, result-ing in an average correlation 
                         coefficient of 0.48 across the domain. The 
                         standard-izedsoilmoistureanomaly(SMA)wascalculatedforthelong-termmodelledsoilmoisture 
                         and revealed strong negative values during well-known drought 
                         peri-ods in the region, especially during El-Niņo years. The 
                         performance of SMA inidentifying droughts during the first 2 
                         months of the raining and cropping sea-son was similar to the 
                         Standardized Precipitation Index (SPI), commonly usedfor drought 
                         assessment: 1214 events were identified by both indices. Finally, 
                         thetemporal relationship between both SMA and SPI with the 
                         Vegetation HealthIndex (VHI) was assessed using the cross-wavelet 
                         transform. The results indi-cated lagged correlations of 1 to 1.5 
                         months in the annual scale, suggesting thatnegative trends in SMA 
                         and SPI can be an early warning to yield losses during the growing 
                         season. Public policies on drought assessment should consider 
                         thecombination of multiple drought indices, including soil 
                         moisture anomaly.",
                  doi = "10.1002/cli2.7",
                  url = "http://dx.doi.org/10.1002/cli2.7",
                 issn = "2692-4587",
                label = "lattes: 5644797510360085 4 ZeriWCZVBMHCMAMG:2022:EvUsJU",
             language = "en",
           targetfile = "Climate Resilience - 2021 - Zeri - Importance of including soil 
                         moisture in drought monitoring over the Brazilian semiarid.pdf",
        urlaccessdate = "30 abr. 2024"
}