Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early SummerSource: Journal of Climate:;2019:;volume 032:;issue 014::page 4121Author:Graham, Robert M.
,
Cohen, Lana
,
Ritzhaupt, Nicole
,
Segger, Benjamin
,
Graversen, Rune G.
,
Rinke, Annette
,
Walden, Von P.
,
Granskog, Mats A.
,
Hudson, Stephen R.
DOI: 10.1175/JCLI-D-18-0643.1Publisher: American Meteorological Society
Abstract: AbstractThis 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 from the Norwegian 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 positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3?19 W m?2. 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?79 W m?2) and underestimate the net longwave flux (8?38 W m?2). 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.
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contributor author | Graham, Robert M. | |
contributor author | Cohen, Lana | |
contributor author | Ritzhaupt, Nicole | |
contributor author | Segger, Benjamin | |
contributor author | Graversen, Rune G. | |
contributor author | Rinke, Annette | |
contributor author | Walden, Von P. | |
contributor author | Granskog, Mats A. | |
contributor author | Hudson, Stephen R. | |
date accessioned | 2019-10-05T06:42:43Z | |
date available | 2019-10-05T06:42:43Z | |
date copyright | 5/9/2019 12:00:00 AM | |
date issued | 2019 | |
identifier other | JCLI-D-18-0643.1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4263177 | |
description abstract | AbstractThis 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 from the Norwegian 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 positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3?19 W m?2. 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?79 W m?2) and underestimate the net longwave flux (8?38 W m?2). 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. | |
publisher | American Meteorological Society | |
title | Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer | |
type | Journal Paper | |
journal volume | 32 | |
journal issue | 14 | |
journal title | Journal of Climate | |
identifier doi | 10.1175/JCLI-D-18-0643.1 | |
journal fristpage | 4121 | |
journal lastpage | 4143 | |
tree | Journal of Climate:;2019:;volume 032:;issue 014 | |
contenttype | Fulltext |