Development of Bias-Corrected Precipitation Database and Climatology for the Arctic Regions Daqing Yang, Principal Investigator Douglas L. Kane, Co-Investigator Institute of Northern Engineering University of Alaska Fairbanks David R. Legates, Co-Investigator Center for Climatic Research Department of Geography University of Delaware

Outline Background /Goals Methods - Results and applications of WMO gauge intercomparison project Data Sources Major Tasks Results/Products/Impacts

Uncertainties of Precipitation Records and Climatology in the Arctic regions Sparseness of the precipitation observation networks; Uneven distribution of measurement sites, i.e. biased toward coastal and the low-elevation areas; Spatial and temporal discontinuities of precipitation measurements induced by changes in observation methods and by different observation techniques used across national borders; and Biases of gauge measurements, such as wind-induced undercatch, wetting and evaporation losses, and underestimate of trace amount of precipitation.

Research Goals Evaluate and define the accuracy of precipitation measurements in the Arctic regions. Implement the consistent bias-correction methods over the pan-Arctic, i.e. Alaska, northern Canada, Siberia, northern Europe, Greenland, and the Arctic Ocean. Develop biased-corrected and compatible precipitation database (including grid products) and climatology for the Arctic regions as a whole.

US Wyoming snow system in Barrow, AKWMO double fence intercomparison reference (DFIR) in Barrow, AK

Overall mean for the NP drifting stations, (Yang, 1999) Overall mean for 61 climate stations in Siberia, (Yang and Ohata, 2001)

Data Sources Daily precipitation, temperature and wind speed are needed for this research. National Climatic Data Center (NCDC), global daily surface data archive (1994-present) for over 8,000 stations around the world, WMO GTS, the Global Climate Observing System (GCOS) Surface Network (GSN), Arctic Precipitation Data Archive (APDA) at the Global Precipitation Data Center (GPDC),

Arctic Ocean (6 hourly and daily) met data collected at the Russian NP drifting station, National Snow and Ice Data Center (NSIDC) Station and gauge info: –type of precipitation gauge –height of gauge and wind sensor –wind shield WMO and national weather services: –USA, Canada –Russia, Finland, Denmark,...

Synoptic/climate stations on land above 45  N and the Arctic Ocean drifting stations will be used for this research

Major Task 1: Evaluation and Implementation of the WMO Bias Correction Methods - threshold wind 6.5m/s Analysis of wind regimes over the arctic regions Focus on winter season and on snowfall days Define regions where the WMO bias correction methods may not be appropriate and therefore alternative approaches or further experimental studies should be considered

Major Task 2: Development of Bias-Corrected Arctic Precipitation Database and Climatology Implement the WMO methods to all the stations in the Arctic regions for last 30 years, ??? Create bias-corrected daily precipitation dataset- an important basis for analyses of Arctic regional precipitation, i.e. long-term mean, seasonal cycle, year- to-year variation, and trend

Develop improved precipitation climatology for the Arctic regions –Consider terrain and the orographic effect on precipitation distribution, use high-resolution digital elevation models (DEM) to determine elevation, slope, and aspect of the topography –Apply PRISM (Daly et al., 1994) and the High-Resolution Weather Data System (HRWxDS) (Legates et al,. 1999) to generate regional maps of monthly/yearly bias-corrected precipitation –Develop gridded precipitation data, use equal-area EASE grid system, compatible with ACSYS/Arctic Precipitation Data Archive (APDA), hydrological model intercomparison project, and RS snowcover (SCE/SWE) products

Major Task 3: Comparison and Validation of the Results Compare our results with other precipitation datasets/products, such as Legates and Willmott (1990), Jaeger (1983), UNESCO (1978), Adam and Lettenmaier (2003), and others? Compare gauge measurements/corrections with snowcover accumulation in selected regions/basins Assess the impact of precipitation bias corrections to regional hydrologic model analyses (Zhang et al., 2000) Compare GCM/RCM precipitation simulation with the observed and bias-corrected precipitation fields in selected regions, i.e. Alaska and central Siberia –model simulation agrees better to bias-corrected precipitation fields particularly in winter months and over windy areas !?

Results/Products/Impacts Practical procedures for correcting gauge-measured precipitation data in the high latitude regions Bias-corrected daily/monthly/yearly (station) precipitation records/correction factors (CF, %) for arctic regions across national boundaries Bias-corrected, gridded monthly/yearly regional precipitation data/climatology for the arctic regions Impacts: –water balance calculations of both the Arctic Ocean and terrestrial systems –climate change analysis and hydrologic modeling –validation of GCM/RCM simulations –calibration of remote sensing data/products