A13G-3261:
The Attribution of Land-Atmosphere Interactions on the Seasonal Predictability of Drought
Monday, 15 December 2014
Joshua K Roundy, NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, Greenbelt, MD, United States, Joseph A Santanello, NASA, Alexandria, VA, United States, Randal D Koster, NASA Goddard SFC, Greenbelt, MD, United States and Eric F Wood, Princeton University, Princeton, NJ, United States
Abstract:
Recent summers in the United States have been plagued by intense droughts that have caused significant economic impact to society that could be reduced through seasonal prediction. Skillful seasonal predictions of drought relevant variables are possible due to the slowly varying boundary conditions and their predictability. In particular, during the convective season, when the potential of extreme drought is the highest, the soil moisture can provide a means of predictability through land-atmosphere (L-A) interactions. There has been a significant amount of work in the last decade to better understand the predictability of L-A interactions. In particular, recent work has developed a classification approach that was the basis for a new Coupling Drought Index (CDI) and the development of the Coupling Statistical Model (CSM), which uses a Markov Chain framework to make statistical predictions. The CDI and CSM have been used to understand the predictability of L-A interactions in NCEP’s Climate Forecasts System version 2 (CFSv2) and indicated that there were strong biases in the coupling that produced biases in the precipitation and limited the predictability of drought. Although the CDI and CSM have been useful in understanding L-A coupling and seasonal predictability, the extent to which the classification is influenced by large-scale climate factors (SSTs) is unknown. In this work the CDI and CSM are used to evaluate the NASA GMAO modeling framework through the MERRA reanalysis and AMIP runs using the GEOS-5 model in order to isolate the impact of SSTs on the coupling metrics. The analysis focuses on 1979 to present with a particular emphasis on drought years. In addition to the CDI and CSM, other metrics that diagnose the coupling between the land and atmosphere are also used in order to further assess the CDI and CSM as coupling metrics. These results are also compared with those from previous studies using the CFSv2, in order to understand the extent to which these results are model specific and to provide a better understanding of the impact of land-atmosphere interactions on seasonal prediction.
