Skillful Subseasonal Prediction of United States Extreme Warm Days and Standardized Precipitation Index in Boreal Summer
نویسندگان
چکیده
Abstract Skillful subseasonal prediction of extreme heat and precipitation greatly benefits multiple sectors, including water management, public health, agriculture, in mitigating the impact events. A statistical model is developed to predict weekly frequency warm days 14-day standardized index (SPI) during boreal summer United States (US). We use a leading principal component US soil moisture an based on North Pacific sea surface temperature (SST) as predictors. The outperforms NCEP’s Climate Forecast System version 2 (CFSv2) at weeks 3-4 eastern US. It found that SST anomalies persist several are associated with persistent wave train pattern (WTZ500), which leads increased occurrences blocking over Extreme dry conditions into week 4 increase sensible flux decrease latent flux, may help maintain overlying anticyclone. clear sky anticyclones further days. This skillful has potential aid irrigation scheduling, crop planning, reservoir operation, provide mitigation impacts from
منابع مشابه
Subseasonal Predictability of Boreal Summer Monsoon Rainfall from Ensemble Forecasts
Subseasonal forecast skill over the broadly defined North American (NAM), West African (WAM) and Asian (AM) summer monsoon regions is investigated using three Ensemble Prediction Systems (EPS) at sub-monthly lead times. Extended Logistic Regression (ELR) is used to produce probabilistic forecasts of weekly and week 3–4 averages of precipitation with starts in May–Aug, over the 1999–2010 period....
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ژورنال
عنوان ژورنال: Journal of Climate
سال: 2021
ISSN: ['1520-0442', '0894-8755']
DOI: https://doi.org/10.1175/jcli-d-20-0878.1