Meteorological forcing datasets for blowing snow modeling on the Tibetan Plateau: Evaluation and intercomparison

Meteorological forcing datasets for blowing snow modeling on the Tibetan Plateau: Evaluation and... AbstractIn this paper, the reliability of the wind speed, temperature, humidity, pressure and precipitation values of three surface meteorological forcing products (CLDAS-2, CMFD and MERRA-2) in the Tibetan Plateau (TP) region was investigated from 2008-2014. Compared with the China Meteorological Administration (CMA) observations, CLDAS-2 exhibited the highest correlation coefficient for wind speed; CMFD displayed the best coefficients for temperature and specific humidity; and MERRA-2 best reflected pressure variations. Based on the biases, CLDAS-2 exhibited the best overall performance for temperature, specific humidity and pressure, while CMFD displayed the best performance for wind speed. The high overall accuracy and false alarm ratio of precipitation based on MERRA-2 both stem from its continuous overestimation of the precipitation frequency. Both CLDAS-2 and CMFD overestimated the non-precipitation frequency in comparisons with CMA observations, and a significant positive bias exists in MERRA-2 based on our analysis of daily precipitation. The results obtained from the comparisons with field observations over the TP and CMA observations are similar, except for the temperature and humidity biases of CLDAS-2. The meteorological effects on the coupled land-blowing snow modeling discussed in this paper suggest that the occurrence of blowing snow and snowdrift sublimation are projected to be reduced by CLDAS-2 due to the underestimation of wind speed, continuous less of snowfall event and the positive biases in low temperatures and humidity, while simulations of blowing processes by MERRA-2 are likely to be much more serious than they actually are. These results may contribute to identifying deficiencies associated with the development of land surface models coupled with blowing snow model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrometeorology American Meteorological Society

Meteorological forcing datasets for blowing snow modeling on the Tibetan Plateau: Evaluation and intercomparison

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1525-7541
D.O.I.
10.1175/JHM-D-17-0075.1
Publisher site
See Article on Publisher Site

Abstract

AbstractIn this paper, the reliability of the wind speed, temperature, humidity, pressure and precipitation values of three surface meteorological forcing products (CLDAS-2, CMFD and MERRA-2) in the Tibetan Plateau (TP) region was investigated from 2008-2014. Compared with the China Meteorological Administration (CMA) observations, CLDAS-2 exhibited the highest correlation coefficient for wind speed; CMFD displayed the best coefficients for temperature and specific humidity; and MERRA-2 best reflected pressure variations. Based on the biases, CLDAS-2 exhibited the best overall performance for temperature, specific humidity and pressure, while CMFD displayed the best performance for wind speed. The high overall accuracy and false alarm ratio of precipitation based on MERRA-2 both stem from its continuous overestimation of the precipitation frequency. Both CLDAS-2 and CMFD overestimated the non-precipitation frequency in comparisons with CMA observations, and a significant positive bias exists in MERRA-2 based on our analysis of daily precipitation. The results obtained from the comparisons with field observations over the TP and CMA observations are similar, except for the temperature and humidity biases of CLDAS-2. The meteorological effects on the coupled land-blowing snow modeling discussed in this paper suggest that the occurrence of blowing snow and snowdrift sublimation are projected to be reduced by CLDAS-2 due to the underestimation of wind speed, continuous less of snowfall event and the positive biases in low temperatures and humidity, while simulations of blowing processes by MERRA-2 are likely to be much more serious than they actually are. These results may contribute to identifying deficiencies associated with the development of land surface models coupled with blowing snow model.

Journal

Journal of HydrometeorologyAmerican Meteorological Society

Published: Aug 23, 2017

References

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