Land-Atmosphere Coupling Strength over the U.S. during Summer: Comparison among Observations, Reanalysis Datasets and Numerical Models

Date of Completion

January 2012


Atmospheric Sciences|Engineering, Environmental




The impact of sea surface temperature (SST) and soil moisture on summer precipitation is first studied with a conditioned correlation approach based on observational SST and precipitation, and VIC-simulated soil moisture focusing on two regions: the Upper Mississippi River Basin and the Great Plains. Soil moisture-precipitation correlation is more likely to be positive and significant in the years with large precipitation anomalies, and in the years when the skill of precipitation prediction based on SST alone is low. It underlines the complementary roles both SST and soil moisture play in determining precipitation and the importance of including soil moisture for climate extreme predictions. ^ The probability density function of conditioned correlation between soil moisture and subsequent precipitation or near-surface temperature during the years of large precipitation anomalies is then used as a measure for the land-atmosphere coupling strength to compare among observations, reanalysis data and numerical models. Among the eight sub-regions (classified by land cover types), the transition zone Great Plains (and to a less extent Midwest and Southeast) are identified as hot spots for strong land-atmosphere coupling; coupling strength is stronger for temperature than for precipitation. In addition, coupling strength in CAM4-CLM4 is found to be weaker than in CAM3-CLM3, which is further supported by GLACE1-type experiments and attributed to changes in CAM rather than modifications in CLM. However, contrary to previous studies, the coupling strength is stronger in observational and reanalysis products than in the models examined. ^ Land-atmosphere coupling strength and the potential utility of realistic soil moisture initialization in improving climate forecasts are further investigated based on a regional climate model RegCM4 with GLACE1 and GLACE2 approaches. Consistent with previous GCMs studies, GLACE1-type experiments identify the central U.S. as a region of strong land-atmosphere coupling and the soil moisture-temperature coupling is stronger than soil moisture-precipitation coupling; GLACE2-type experiments indicate that realistic soil moisture initialization is more promising in improving temperature forecasts than precipitation. Further GLACE2-type experiments driven by GCM-produced LBCs suggest that the intrinsic land-atmosphere coupling strength within the regional model is the dominant factor for the added forecast skill at the short lead time (115 days), while the impact of LBCs attributable to the soil moisture initialization from the GCM may play a dominant role at longer time lead (16-30 days). ^