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Simulations of precipitation using NRCM and comparisons with satellite observations and CAM: annual cycle

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Abstract

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36 km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000–2005) from within the Tropics (30°S–30°N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulated precipitation. The 6-year mean precipitation simulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the long-time mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both models. Overall, the results seem to indicate that employing a higher spatial resolution (36 km) does not significantly improve simulation of precipitation. We speculate that a combination of several physics parameterizations and lack of model tuning gives rise to the observed differences between NRCM and the observations.

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Acknowledgments

Funding for this research is partially provided by the NOAA Climate Prediction Program for the Americas (CPPA) to Pacific Northwest National Laboratory (PNNL). PNNL is operated for the US Department of Energy by Battelle Memorial Institute under contract DE-AC06-76RLO1830. Additional funding was provided by NASA grant NNX07AD67G to Texas A&M University. We acknowledge NASA for use of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA). TMPA (3B42) data were obtained from the Goddard Earth Sciences Data and Information Services Center (http://disc.gsfc.nasa.gov/). The NCAR CAM simulations were carried out at the Texas A&M Supercomputing Center.

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Authors and Affiliations

  1. Department of Atmospheric Sciences, Texas A&M University, 3150 TAMU, College Station, TX, 77843, USA

    Aditya Murthi & Kenneth P. Bowman

  2. Pacific Northwest National Laboratory, PO Box 999, MSIN: K9-24, Richland, WA, 99352, USA

    L. Ruby Leung

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  1. Aditya Murthi
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Correspondence to Aditya Murthi.

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Murthi, A., Bowman, K.P. & Leung, L.R. Simulations of precipitation using NRCM and comparisons with satellite observations and CAM: annual cycle. Clim Dyn 36, 1659–1679 (2011). https://doi.org/10.1007/s00382-010-0878-z

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