
The Impact of a Low Bias in Snow Water Equivalent Initialization on CFS Seasonal Forecasts
Author(s) -
P. D. Broxton,
Xubin Zeng,
Nicholas Dawson
Publication year - 2017
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-17-0072.1
Subject(s) - snowpack , climatology , environmental science , snow , snowmelt , northern hemisphere , initialization , atmospheric sciences , meteorology , geography , geology , computer science , programming language
Across much of the Northern Hemisphere, Climate Forecast System forecasts made earlier in the winter (e.g., on 1 January) are found to have more snow water equivalent (SWE) in April-June than forecasts made later (e.g., on 1 April); furthermore, later forecasts tend to predict earlier snowmelt than earlier forecasts. As a result, other forecasted model quantities (e.g., soil moisture in April-June) show systematic differences dependent on the forecast lead time. Notably, earlier forecasts predict much colder near-surface air temperatures in April-June than later forecasts. Although the later forecasts of temperature are more accurate, earlier forecasts of SWE are more realistic, suggesting that the improvement in temperature forecasts occurs for the wrong reasons. Thus, this study highlights the need to improve atmospheric processes in the model (e.g., radiative transfer, turbulence) that would cause cold biaseswhen a more realistic amount of snowis on the ground. Furthermore, SWE differences in earlier versus later forecasts are found to much more strongly affect April-June temperature forecasts than the sea surface temperature differences over different regions, suggesting the major role of snowpack in seasonal prediction during the spring-summer transition over snowy regions