Data set: Huai et al. (2021). JAMC. Quantifying rainfall in Greenland: a combined observational and modelling approach
Abstract Paper. This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercat...
| Main Authors: | , , , |
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| Format: | Dataset |
| Language: | unknown |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://zenodo.org/record/5034582 https://doi.org/10.5281/zenodo.5034582 |
| Summary: | Abstract Paper. This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a Dynamic Correction Model (DCM) for Automatic Weather Stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R=0.3-0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02-1.40) are smaller than those for snowfall (1.27-2.80), and hence the observations more robust. With a horizontal resolution of 5.5 km and simulation period from 1958-present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients. The dataset contains: Automatic weather station data: AWS-daily.zip: per station daily values of snowfall and rain fall derived from raw precipitation data and for 7 methods to divide between rain and snowfall AWS-factork.zip: per station the factor with which the data is corrected for undercatch AWS-script.zip: the scripts used for the analyses Staffed weather stations: Meteo-daily.zip: per station daily values of snowfall and rain fall derived from the precipitation data and for 7 methods to divide between rain and snowfall Meteo-factork.zip: per station the factor with which the data is corrected for undercatch Meteo-script.zip: the scripts used for ... |
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