CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States

Abstract

Abstract. This paper explored the potential of a global climate model for sub-seasonal forecasting of precipitation and 2 m air temperature. The categorical forecast skill of 10 precipitation and temperature indices was investigated using the 28-year sub-seasonal hindcasts from the Climate Forecast System version 2 (CFSv2) over the contiguous United States (CONUS). The forecast skill for mean precipitation and temperature as well as for the frequency and duration of extremes was highly dependent on the forecasting indices, regions, seasons, and leads. Forecasts for 7-and 14-day temperature indices showed skill even at weeks 3 and 4, and generally were more skillful than precipitation indices. Overall, temperature indices showed higher skill than precipitation indices over the entire CONUS region at sub-seasonal scale. While the forecast skill related to mean precipitations was low in summer over the CONUS, the number of rainy days, number of consecutive rainy days, and number of consecutive dry days showed considerably high skill for the western coastal region. The presence of active Madden-Julian Oscillation (MJO) events improved CFSv2 weekly mean precipitation forecast skill over most parts of the CONUS, but it did not necessarily improve the weekly mean temperature forecasts. The 30-day forecasts of precipitation and temperature indices calculated from the downscaled monthly CFSv2 forecasts were less skillful than those calculated directly from CFSv2 daily forecasts, suggesting the usefulness of CFSv2 for sub-seasonal hydrological forecasting.

Evaluation of synoptic‐scale patterns during extreme temperature and precipitation events in Alaska

“…As Tian et al . () discuss, many of the decisions involved in risk mitigation of extreme events fall into a sub‐seasonal to seasonal time frame requiring a firm understanding of the influences that large‐scale circulation has on local extremes. The analysis presented in this paper is motivated by the potential to improve forecast skill at timescales beyond that of the typical medium‐range weather forecasts.…”

Developing Subseasonal to Seasonal Climate Forecast Products for Hydrology and Water Management

“…; Tian et al. ). Multi‐model climate forecast ensembles have also demonstrated improved skill over single models (Doblas‐Reyes et al.…”

“…Recently, dynamical climate forecasts generated using initialized global climate models (GCMs) have shown skill improvements at the S2S time scale. One of these dynamical models, the fully coupled atmosphere-ocean-land model Climate Forecast System version 2 (CFSv2), which is run at the National Centers for Environmental Prediction (NCEP), demonstrates skill in projecting climate variables at various leads and seasons over the U.S. and improves upon its predecessor CFSv1 (Yuan et al 2011;Saha et al 2014;Tian et al 2017). Multi-model climate forecast ensembles have also demonstrated improved skill over single models Hagedorn et al 2005;Becker et al 2014).…”

Forecast Skill of Minimum and Maximum Temperatures on Subseasonal‐to‐Seasonal Timescales Over South Africa

“…In particular, the forecasts for frequency or duration of precipitation and temperature extremes can be directly tailored to different applications need. S2S forecast information is crucially important since early warning systems for high-impact weather events could be derived from these predictions (e.g., Tian et al, 2017). In particular, many extreme weather events (e.g., floods and droughts, heat, and cold waves) and their corresponding management decisions fall into subseasonal timescales.…”