Evaluation of six atmospheric reanalyses over Arctic sea ice from winter to early summer
Journal of Climate, ISSN: 0894-8755, Vol: 32, Issue: 14, Page: 4121-4143
2019
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
This study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations fromtheNorwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January-March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positivewintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3-19Wm. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April-May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5-79Wm) and underestimate the net longwave flux (8-38Wm). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85068025259&origin=inward; http://dx.doi.org/10.1175/jcli-d-18-0643.1; https://journals.ametsoc.org/view/journals/clim/32/14/jcli-d-18-0643.1.xml; https://journals.ametsoc.org/downloadpdf/journals/clim/32/14/jcli-d-18-0643.1.xml; http://journals.ametsoc.org/jcli/article-pdf/32/14/4121/4840035/jcli-d-18-0643_1.pdf; https://dx.doi.org/10.1175/jcli-d-18-0643.1; https://journals.ametsoc.org/doi/10.1175/JCLI-D-18-0643.1
American Meteorological Society
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