Assessment of Seasonal Soil Moisture Forecasts over Southern South America with Emphasis on Dry and Wet Events

被引:0
|
作者
Spennemann, Pablo C. [1 ]
Rivera, Juan A. [2 ,3 ]
Osman, Marisol [1 ]
Celeste Saulo, A. [1 ,4 ]
Penalba, Olga C. [5 ,6 ]
机构
[1] Univ Buenos Aires, Consejo Nacl Invest Cient & Tecn, UMI Inst Franco Argentino Estudios Clima & Impact, Ctr Invest Mar & Atmosfera, Buenos Aires, DF, Argentina
[2] Consejo Nacl Invest Cient & Tecn, Inst Argentino Nivol Glaciol & Ciencias Ambiental, Ctr Cient Tecnol Mendoza, Mendoza, Argentina
[3] Univ Juan Agustin Maza, Mendoza, Argentina
[4] Serv Meteorol Nacl, Buenos Aires, DF, Argentina
[5] Univ Buenos Aires, Fac Ciencias Exactas & Nat, Dept Ciencias Atmosfera & Oceanos, Buenos Aires, DF, Argentina
[6] Consejo Nacl Invest Cient & Tecn, Buenos Aires, DF, Argentina
基金
美国国家科学基金会;
关键词
LA PLATA BASIN; METEOROLOGICAL DROUGHT; SURFACE TEMPERATURE; EL-NINO; PRECIPITATION; PREDICTION; SYSTEM; MODEL; EXTREMES;
D O I
10.1175/JHM-D-17-0015.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The importance of forecasting extreme wet and dry conditions from weeks to months in advance relies on the need to prevent considerable socioeconomic losses, mainly in regions of large populations and where agriculture is a key value for the economies, such as southern South America (SSA). To improve the understanding of the performance and uncertainties of seasonal soil moisture and precipitation forecasts over SSA, this study aims to 1) perform a general assessment of the Climate Forecast System, version 2 (CFSv2), soil moisture and precipitation forecasts against observations and soil moisture simulations based on GLDAS, version 2.0; 2) evaluate the ability of CFSv2 to represent wet and dry events through the forecasted standardized precipitation index (SPI) and standardized soil moisture anomalies (SSMA); and 3) analyze the capability of a statistical methodology (merging observations and forecasts) in representing a severe drought event. Results show that both SPI and SSMA forecast skill are regionally and seasonally dependent. In general, a fast degradation of the forecasts skill is observed as the lead time increases, resulting in almost no added value with regard to climatology at lead times longer than 3 months. Additionally, a better performance of the SSMA forecasts is observed compared to SPI calculated using three months of precipitation (SPI3), with a higher skill for dry events against wet events. The CFSv2 forecasts are able to represent the spatial patterns of the 2008/09 severe drought event, although it shows crucial limitations regarding the identification of drought onset, duration, severity, and demise, considering both meteorological (SPI) and agricultural (SSMA) drought conditions.
引用
收藏
页码:2297 / 2311
页数:15
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