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- Author or Editor: Lana Cohen x
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Abstract
Synoptic classifications over the Southern Ocean in the Ross Sea region of Antarctica (50°S–Antarctic coast, 150°E–90°W) have been derived from NCEP reanalysis data (1979–2011), producing a set of six synoptic types for the region. These types describe realistic synoptic conditions for the region and represent the moisture-bearing low pressure systems that circulate around Antarctica. The types are described as follows: low Bellingshausen/Amundsen (L-BA), low (L), zonal (Z), low Ross (L-R), ridge (R), and low Amundsen (L-A).
Seasonal frequencies of the synoptic types reflect the seasonal zonal shift of the Amundsen Sea low (ASL) and also correlate well with the Southern Oscillation index (SOI) and the southern annular mode (SAM). Variability in the occurrences of the synoptic types L-R and L-BA indicate a shifting of the position of the ASL farther east (west) toward (away from) the Antarctic Peninsula during La Niña (El Niño) and positive (negative) SAM conditions. A joint linear regression of the SOI and SAM indices show the strongest correlations with the types L-BA and L-R in the spring and quantifies the joint forcing effect of these climate cycles on synoptic variability in the region.
As a demonstration of how synoptic classification provides links between large-scale atmospheric circulation and local climate parameters, the synoptic types are related to precipitation and temperature at Roosevelt Island, an ice core site on the Ross Ice Shelf (80°S, 160°W). The synoptic types provide quantification of distinct precipitation and temperature regimes at this site, which allows for more fundamental understanding of the precipitation source regions and transport pathways that drive the variability in snow and ice proxies.
Abstract
Synoptic classifications over the Southern Ocean in the Ross Sea region of Antarctica (50°S–Antarctic coast, 150°E–90°W) have been derived from NCEP reanalysis data (1979–2011), producing a set of six synoptic types for the region. These types describe realistic synoptic conditions for the region and represent the moisture-bearing low pressure systems that circulate around Antarctica. The types are described as follows: low Bellingshausen/Amundsen (L-BA), low (L), zonal (Z), low Ross (L-R), ridge (R), and low Amundsen (L-A).
Seasonal frequencies of the synoptic types reflect the seasonal zonal shift of the Amundsen Sea low (ASL) and also correlate well with the Southern Oscillation index (SOI) and the southern annular mode (SAM). Variability in the occurrences of the synoptic types L-R and L-BA indicate a shifting of the position of the ASL farther east (west) toward (away from) the Antarctic Peninsula during La Niña (El Niño) and positive (negative) SAM conditions. A joint linear regression of the SOI and SAM indices show the strongest correlations with the types L-BA and L-R in the spring and quantifies the joint forcing effect of these climate cycles on synoptic variability in the region.
As a demonstration of how synoptic classification provides links between large-scale atmospheric circulation and local climate parameters, the synoptic types are related to precipitation and temperature at Roosevelt Island, an ice core site on the Ross Ice Shelf (80°S, 160°W). The synoptic types provide quantification of distinct precipitation and temperature regimes at this site, which allows for more fundamental understanding of the precipitation source regions and transport pathways that drive the variability in snow and ice proxies.
Abstract
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 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.
Abstract
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 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.
