A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction

Abstract

[1] NOAA's National Centers for Environmental Prediction (NCEP) has transitioned to operationally use the second generation of their coupled ocean-atmosphere-land model, the Climate Forecast System version 2 (CFSv2), with advanced physics, increased resolution and refined initialization to improve the seasonal climate forecasts. We present a first look at the capability of CFSv2 on surface air temperature and precipitation predictions based on analyzing the 28-year (1982-2009) reforecasts. These variables are primary inputs to hydrological seasonal forecast procedures. Averaged globally, the CFSv2 increases the predictive skill for month-1 land surface air temperature and precipitation from the CFSv1 by 37% and 29%, respectively. The CFSv2 has comparable performance to the latest ECMWF model, the best among the current European seasonal forecast models. The soil moisture produced by CFSv2 also provides useful information in identifying several major drought events, especially over tropical regions. Though there is limited skill beyond month-1, the CFSv2 does show promising features for advancing hydrological forecast and application studies.

Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide

“…Although NWP skill for precipitation rapidly disappears after around 2 weeks [Yuan et al, 2011], that still accounts for about one fifth of the 2 month forecast period and therefore may still increase the skill of cumulative streamflow forecasts. Further analysis is needed to assess to what extent the contribution of climate forecasts from NWP and climate mode forecasts can enhance skill.…”

“…This is not yet done on an operational basis, for several possible reasons. First, the current generation of precipitation forecasts rapidly loses skill beyond the first 2 weeks [Lavers et al, 2009;Yuan et al, 2011], which is to a considerable extent a fundamental constraint caused by the chaotic evolution of the atmosphere [Westra and Sharma, 2010;Feng et al, 2011]. Moreover, GCM forecasts are issued at a resolution that is too coarse for most hydrological applications, and the forecasts, of precipitation in particular, are prone to biases.…”

Predictable patterns and predictive skills of monsoon precipitation in Northern Hemisphere summer in NCEP CFSv2 reforecasts

“…Recently, many efforts have been devoted to assessing CFSv2 products. These studies have reported prediction skill improvements in ENSO, the tropical Atlantic SST, global land precipitation, surface air temperature, and the Madden-Julian Oscillation in CFSv2 compared to CFSv1 (Yuan et al 2011;Weaver et al 2011;Jiang et al 2012;Jiang et al 2013;Hu et al 2012a), as well as biases in the CFSv2 Kim et al 2012;Liu et al 2012).…”

Seasonal dependence of the predictable low-level circulation patterns over the tropical Indo-Pacific domain

“…Besides, those features depicted above raise a question: what mechanisms should be responsible for the different prediction skills of those predictable patterns? Previous studies have demonstrated that the CFSv2 is capable of simulating and predicting the major climatological features over the Indo-Pacific region (Yuan et al 2011;Wang et al 2011;Weaver et al 2011). In this section, we depict the predictable patterns in the CFSv2 with multiseason leads.…”

“…Previous studies have investigated prediction and predictability of the climate variations within the Indo-Pacific region under the seasonal framework (e.g., Wang et al 2005;Yuan et al 2011;Jiang et al 2013a;Zuo et al 2013;Jia and Lin 2013;Yang and Jiang 2014). For instance, Liang et al (2009) found that the first and second most predictable patterns of the Asian and Indo-Pacific summer precipitation are characterized by different climate features of the onset and decay years of ENSO, respectively.…”