Quantifying the Land-Atmosphere Coupling Behavior in Modern Reanalysis Products over the U.S. Southern Great Plains
Abstract
The coupling of the land with the planetary boundary layer (PBL) on diurnal timescales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve our understanding of land-atmosphere (L-A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this paper, we apply a suite of local land-atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-year period over the U. S. Southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation are applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface-PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land-PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. The implications for moist processes are also discussed, which warrants further investigation into the potential downstream impacts of land-PBL coupling on the diurnal cycle of clouds, convection, and precipitation. Lastly, the results are put into context of community investigations into drought assessment and predictability over the region and underscore that caution should be used when treating RAs as truth, as the coupled water and energy cycle representation in each can vary considerably.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2014
- Bibcode:
- 2014AGUFMNG33A3811S
- Keywords:
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- 1616 Climate variability;
- 1910 Data assimilation;
- integration and fusion;
- 3322 Land/atmosphere interactions;
- 4255 Numerical modeling