A31I-08
Understanding the land-atmospheric interaction in drought forecast from CFSv2 for the 2011 Texas and 2012 Upper Midwest US droughts

Wednesday, 16 December 2015: 09:45
3006 (Moscone West)
Yu Zhang1, Joshua K Roundy2, Michael B Ek3 and Eric F Wood1, (1)Princeton University, Princeton, NJ, United States, (2)University of Kansas, Lawrence, KS, United States, (3)Environmental Modeling Center, NOAA NWS NCEP/EMC, College Park, MD, United States
Abstract:
Prediction and thus preparedness in advance of hydrological extremes, such as drought and flood events, is crucial for proactively reducing their social and economic impacts. In the summers of 2011 Texas, and 2012 the Upper Midwest, experienced intense droughts that affected crops and the food market in the US. It is expected that seasonal forecasts with sufficient skill would reduce the negative impacts through planning and preparation. However, the forecast skill from models such as Climate Forecast System Version 2 (CFSv2) from National Centers for Environmental Prediction (NCEP) is low over the US, especially during the warm season (Jun - Sep), which restricts their practical use for drought prediction. This study analyzes the processes that lead to premature termination of 2011 and 2012 US summer droughts in CFSv2 forecast resulting in its low forecast skill.

Using the North American Land Data Assimilation System version 2 (NLDAS2) and Climate Forecast System Reanalysis (CFSR) as references, this study investigates the forecast skills of CFSv2 initialized at 00, 06, 12, 18z from May 15 - 31 (leads out to September) for each event in terms of land-atmosphere interaction, through a recently developed Coupling Drought Index (CDI), which is based on the Convective Triggering Potential-Humidity Index-soil moisture (CTP-HI-SM) classification of four climate regimes: wet coupling, dry coupling, transitional and atmospherically controlled.

A recycling model is used to trace the moisture sources in the CFSv2 forecasts of anomalous precipitation, which lead to the breakdown of drought conditions and a lack of drought forecasting skills. This is then compared with tracing the moisture source in CFSR with the same recycling model, which is used as the verification for the same periods. This helps to identify the parameterization that triggered precipitation in CFSv2 during 2011 and 2012 summer in the US thus has the potential to improve the forecast skill of CSFv2.