Back to Search
Start Over
Subseasonal Dynamical Prediction of East Asian Cold Surges.
- Source :
- Weather & Forecasting; Aug2017, Vol. 32 Issue 4, p1675-1694, 20p
- Publication Year :
- 2017
-
Abstract
- Predictability of East Asian cold surges is studied using daily data from the hindcasts of 45-day integrations by the NCEP Climate Forecast System version 2 (CFSv2). Prediction skills of the CFSv2 in forecasting cold surges, their annual variation, and their physical links to large-scale atmospheric circulation patterns are examined. Results show that the climatological characteristics of the East Asian winter monsoon can be reasonably reproduced by the CFSv2. The model can well capture the frequency, intensity, and location of cold surges at a lead time of about two weeks. Obviously, fewer-than-observed cold surge days are found in the predictions when the lead time is above 14 days. The spatiotemporal evolutions of high-, mid-, and low-level circulation patterns during cold surge occurrences are all accurately indicated in the CFSv2 prediction. Except for precipitation, the other variables associated with cold surges, such as geopotential height, wind, sea level pressure, and surface air temperature, exhibit higher skills. The lead time of skillful prediction of precipitation is limited to around 1 week, with systematic wet biases over the South China Sea, the Philippine Islands, and the northwest Pacific, but dry biases over India, the Indo-China Peninsula, and most high-latitude regions. Wave train-like patterns of geopotential height and wind differ distinguishably when cold surges occur in northern and southern regions (using 35°N as the dividing line), and the CFSv2 gives a consistent prediction to these anomalous patterns. A weaker-than-observed Siberian high and weaker northerly winds over eastern China are found in the predictions especially at longer lead times. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08828156
- Volume :
- 32
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Weather & Forecasting
- Publication Type :
- Academic Journal
- Accession number :
- 126889677
- Full Text :
- https://doi.org/10.1175/WAF-D-16-0209.1