Representation of Mean Arctic Precipitation from NCEP–NCAR and ERA Reanalyses

Mark C. Serreze Division of Cryospheric and Polar Processes, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Ciaran M. Hurst Division of Cryospheric and Polar Processes, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Abstract

An improved monthly precipitation climatology for the Arctic is developed by blending the Legates and Willmott gridded product with measurements from Russian “North Pole” drifting stations and gauge-corrected station data for Eurasia and Canada. The improved climatology is used to examine the accuracy of mean precipitation forecasts from the National Centers for Environmental Prediction (NCEP) and European Reanalysis Agency (ERA) reanalysis models, based on data for the period 1979–88. Both models capture the major spatial features of annual mean precipitation and general aspects of the seasonal cycle but with some notable errors. Both underestimate precipitation over the Atlantic side of the Arctic. NCEP overestimates annual totals over land areas and to a somewhat lesser extent over the central Arctic Ocean. Except for the North Atlantic–Scandinavia sector, the NCEP model also depicts the seasonal precipitation maximum consistently one month early in July. Overall, the ERA predictions are better. Both models perform best during winter and worst during summer.

The most significant problem with the NCEP model is a severe oversimulation of summer precipitation over land areas, due to excessive convective precipitation. Further investigation for July reveals that both the NCEP analyses and 12-h forecasts are too wet below about 850 mb and have more negative low-level temperature gradients as compared to available rawinsonde profiles. This suggests that low-level observations are not being effectively incorporated in the analyses. Given this finding, the high humidities are consistent with excessive surface evaporation rates. This problem may in turn relate to soil moisture, which NCEP updates by the modeled precipitation. If soil moisture is too high, this would favor excessive evaporation and high low-level humidities, fostering excessive precipitation, in turn keeping soil moisture and evaporation rates high. The NCEP downwelling shortwave fluxes are also much too high, contributing to excessive evaporation and possibly influencing the low-level temperature gradients. By comparison, soil moisture in the ERA model is adjusted using the difference between the model first guess and analysis value (the analysis increment) of low-level humidity, which prevents model drift. The ERA downwelling shortwave fluxes are also closer to observations. These attributes are consistent with the superior ERA precipitation forecasts in summer and suggest avenues for improving the performance of the NCEP model.

Corresponding author address: Dr. Mark C. Serreze, Division of Cryospheric and Polar Processes, CIRES, Campus Box 449, University of Colorado, Boulder, CO 80309-0449.

Abstract

An improved monthly precipitation climatology for the Arctic is developed by blending the Legates and Willmott gridded product with measurements from Russian “North Pole” drifting stations and gauge-corrected station data for Eurasia and Canada. The improved climatology is used to examine the accuracy of mean precipitation forecasts from the National Centers for Environmental Prediction (NCEP) and European Reanalysis Agency (ERA) reanalysis models, based on data for the period 1979–88. Both models capture the major spatial features of annual mean precipitation and general aspects of the seasonal cycle but with some notable errors. Both underestimate precipitation over the Atlantic side of the Arctic. NCEP overestimates annual totals over land areas and to a somewhat lesser extent over the central Arctic Ocean. Except for the North Atlantic–Scandinavia sector, the NCEP model also depicts the seasonal precipitation maximum consistently one month early in July. Overall, the ERA predictions are better. Both models perform best during winter and worst during summer.

The most significant problem with the NCEP model is a severe oversimulation of summer precipitation over land areas, due to excessive convective precipitation. Further investigation for July reveals that both the NCEP analyses and 12-h forecasts are too wet below about 850 mb and have more negative low-level temperature gradients as compared to available rawinsonde profiles. This suggests that low-level observations are not being effectively incorporated in the analyses. Given this finding, the high humidities are consistent with excessive surface evaporation rates. This problem may in turn relate to soil moisture, which NCEP updates by the modeled precipitation. If soil moisture is too high, this would favor excessive evaporation and high low-level humidities, fostering excessive precipitation, in turn keeping soil moisture and evaporation rates high. The NCEP downwelling shortwave fluxes are also much too high, contributing to excessive evaporation and possibly influencing the low-level temperature gradients. By comparison, soil moisture in the ERA model is adjusted using the difference between the model first guess and analysis value (the analysis increment) of low-level humidity, which prevents model drift. The ERA downwelling shortwave fluxes are also closer to observations. These attributes are consistent with the superior ERA precipitation forecasts in summer and suggest avenues for improving the performance of the NCEP model.

Corresponding author address: Dr. Mark C. Serreze, Division of Cryospheric and Polar Processes, CIRES, Campus Box 449, University of Colorado, Boulder, CO 80309-0449.

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