Creation of a long-term high-resolution hydrometeorological archive for the Russian Arctic: methodology and first results
Abstract Taking into account that dangerous phenomena on the Arctic coast are increasing in number, providing the region with detailed hydrometeorological and climatic information with a horizontal resolution of at least several kilometers becomes particularly important. In this work, we obtain for...
| Published in: | IOP Conference Series: Earth and Environmental Science |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | unknown |
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IOP Publishing
2019
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1088/1755-1315/386/1/012039 https://iopscience.iop.org/article/10.1088/1755-1315/386/1/012039/pdf https://iopscience.iop.org/article/10.1088/1755-1315/386/1/012039 |
| Summary: | Abstract Taking into account that dangerous phenomena on the Arctic coast are increasing in number, providing the region with detailed hydrometeorological and climatic information with a horizontal resolution of at least several kilometers becomes particularly important. In this work, we obtain for the first time a detailed archive of many hydrometeorological parameters with a spatial resolution of less than 5 km based on long-term simulation experiments. Detailed hydrometeorological fields in the Arctic basin over a long period (1980 – 2016) are derived by a two-step downscaling technology with domains of horizontal resolutions of~13 km and ~4 km that cover most of the Russian Artic, by using a regional non-hydrostatic model, COSMO-CLM. First results of verification with hundreds of Russian Arctic stations allow us to select the best configuration of the model and domains, including many turbulent scheme options and starting time of the experiments. The model results for the coast have shown good agreement with observations (with mean errors of 1 - 2 C). The larger temperature biases over the Eastern Siberia inland have been partially reduced by using selected turbulence scheme options (with mean errors of 5 - 6 C to 2 – 3 C). The differences between the ERA-Interim and ERA5 driving conditions are not great. Therefore, the former are chosen as basic reanalysis, taking into account the data volume and limitations on computational resources. A possible future regional reanalysis output would be useful in many applications, e.g. modelling ocean’s characteristics, coastal ecosystems, detailed investigation of individual extreme phenomena in nested domains, analysis of trends in the frequency of occurrence of extreme events and features of their spatial distribution, study of the hydrometeorological regime of coastal areas, the climatology and tracking of polar mesocyclones, etc. |
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