Multi-scale Variations of Precipitable Water over China based on 1999-2015 Ground-based GPS Observations and Evaluations of Reanalysis products

Multi-scale Variations of Precipitable Water over China based on 1999-2015 Ground-based GPS... AbstractThe dense ground-based GPS provides a good tool to study the water vapor distribution and multi-scale variations, especially for linear trends on the inter-annual scale and short-term variations on the diurnal scale. It can also serve as an independent data source to evaluate performances of reanalyses. In this study, the 6-hourly PW products at more than 260 GPS stations over China from 1999 to 2015 were analyzed and eight commonly used reanalyses, including 20CRv2, CFSR, ERA-Interim, JRA-25, JRA-55, MERRA, NCEP/NCAR and NCEP/DOE, were evaluated. The climatological annual mean GPS PW distribution over China roughly shows a decreasing trend from southeast to northwest, with largest annual and semi-annual amplitudes in the lower reaches of Yangtze River and mid-eastern China, respectively, while with smallest values in the Tibetan Plateau and southwestern China. All reanalyses (except for 20CRv2) can generally reproduce well the climatological annual mean PW (within 20%), annual amplitudes (within 20%) and semi-annual amplitudes (within 20% except in the tropical monsoon region), but they all show wet biases in the Tibetan Plateau. Diurnal variation amplitudes reproduced by all reanalysis products are smaller than amplitudes estimated from GPS observations over China as a whole, and none of the reanalyses can capture the diurnal phases correctly. PW linear trends at most GPS stations in the recent 16 years are insignificant or with absolute values smaller than 0.10 mm yr-1. However, due to the assimilation of the unhomogenized radiosonde humidity data, most reanalyses show artificial decreasing PW trends except for 20CRv2 and CFSR. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Climate American Meteorological Society

Multi-scale Variations of Precipitable Water over China based on 1999-2015 Ground-based GPS Observations and Evaluations of Reanalysis products

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0442
D.O.I.
10.1175/JCLI-D-17-0419.1
Publisher site
See Article on Publisher Site

Abstract

AbstractThe dense ground-based GPS provides a good tool to study the water vapor distribution and multi-scale variations, especially for linear trends on the inter-annual scale and short-term variations on the diurnal scale. It can also serve as an independent data source to evaluate performances of reanalyses. In this study, the 6-hourly PW products at more than 260 GPS stations over China from 1999 to 2015 were analyzed and eight commonly used reanalyses, including 20CRv2, CFSR, ERA-Interim, JRA-25, JRA-55, MERRA, NCEP/NCAR and NCEP/DOE, were evaluated. The climatological annual mean GPS PW distribution over China roughly shows a decreasing trend from southeast to northwest, with largest annual and semi-annual amplitudes in the lower reaches of Yangtze River and mid-eastern China, respectively, while with smallest values in the Tibetan Plateau and southwestern China. All reanalyses (except for 20CRv2) can generally reproduce well the climatological annual mean PW (within 20%), annual amplitudes (within 20%) and semi-annual amplitudes (within 20% except in the tropical monsoon region), but they all show wet biases in the Tibetan Plateau. Diurnal variation amplitudes reproduced by all reanalysis products are smaller than amplitudes estimated from GPS observations over China as a whole, and none of the reanalyses can capture the diurnal phases correctly. PW linear trends at most GPS stations in the recent 16 years are insignificant or with absolute values smaller than 0.10 mm yr-1. However, due to the assimilation of the unhomogenized radiosonde humidity data, most reanalyses show artificial decreasing PW trends except for 20CRv2 and CFSR.

Journal

Journal of ClimateAmerican Meteorological Society

Published: Nov 21, 2017

References

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