Premium
Effects of realistic land surface initializations on subseasonal to seasonal soil moisture and temperature predictability in North America and in changing climate simulated by CCSM4
Author(s) -
Kumar Sanjiv,
Dirmeyer Paul A.,
Lawrence David M.,
DelSole Timothy,
Altshuler Eric L.,
Cash Benjamin A.,
Fennessy Michael J.,
Guo Zhichang,
Kinter James L.,
Straus David M.
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2014jd022110
Subject(s) - predictability , climatology , environmental science , precipitation , dryness , evapotranspiration , climate model , climate change , atmospheric sciences , meteorology , geography , mathematics , geology , ecology , statistics , oceanography , medicine , surgery , biology
Fully coupled global climate model experiments are performed using the Community Climate System Model version 4.0 (CCSM4) for preindustrial, present, and future climate to study the effects of realistic land surface initializations on subseasonal to seasonal climate forecasts. Model forecasts are verified against model control simulations (perfect model experiments), thus overcoming to some extent issues of uncertainties in the observations and/or model parameterizations. Findings suggest that realistic land surface initialization is important for climate predictability at subseasonal to seasonal time scales. We found the highest predictability for soil moisture, followed by evapotranspiration, temperature, and precipitation. The predictability is highest for the 16 to 30 days forecast period, and it progressively decreases for the second and third month forecasts. We found significant changes in the spatial distributions of temperature predictability in the present and future climate compared to the preindustrial climate, although the spatial average changes for North America were rather small (<10%). To attribute the potential cause of changes in land‐driven temperature predictability, they are correlated with the changes in land related climate metrics. The changes in temperature predictability are positively (0.40), and negatively (−0.35) correlated with the changes in nonrainy days evaporative fraction, and changes in dryness index respectively. From this result, the hypothesis arises that wetter conditions favor higher land‐driven temperature predictability in North America. We tested the hypothesis by rearranging the predictability experiment ensembles and found support for the hypothesis in the midlatitude regions and short‐term forecasts (16 to 30 days).