Uncertainties in Arctic Precipitation

Author: I. Majhi and Judah Cohen
December 5, 2012
Poster presentation
AGU Fall Meeting 2012

Ipshita Majhi; Vladimir A. Alexeev; Jessica E. Cherry; Judah L. Cohen; Pavel Y. Groisman (2012) Uncertainties in Arctic Precipitation. AGU Fall Meeting, San Francisco, CA.

Arctic precipitation is riddled with measurement biases; to address the problem is imperative. Our study focuses on comparison of various datasets and analyzing their biases for the region of Siberia and caution that is needed when using them. Five sources of data were used ranging from NOAA’s product (RAW, Bogdanova’s correction), Yang’s correction technique and two reanalysis products (ERA-Interim and NCEP). The reanalysis dataset performed better for some months in comparison to Yang’s product, which tends to overestimate precipitation, and the raw dataset, which tends to underestimate. The sources of bias vary from topography, to wind, to missing data .The final three products chosen show higher biases during the winter and spring season. Emphasis on equations which incorporate blizzards, blowing snow and higher wind speed is necessary for regions which are influenced by any or all of these factors; Bogdanova’s correction technique is the most robust of all the datasets analyzed and gives the most reasonable results. One of our future goals is to analyze the impact of precipitation uncertainties on water budget analysis for the Siberian Rivers.