Climatic characteristics of drift ice in the northern Barents Sea

2019 ◽  
Vol 11 (3) ◽  
pp. 800-811
Author(s):  
Chenglin Duan ◽  
Sheng Dong ◽  
Zhifeng Wang ◽  
Zhenkun Liao

Abstract In this paper, a preliminary climatic description of the long-term offshore drift ice characteristics in the northern Barents Sea has been investigated from 1987 to 2016 based on the satellite ice motion datasets from National Snow and Ice Data Center (NSIDC) and reanalysis ice thickness datasets from National Centers for Environmental Prediction (NCEP)-Climate Forecast System Reanalysis (CFSR) and Climate Forecast System Version 2 (CFSv2). Both the ice velocity and thickness conditions have been studied at the three fixed locations from west to east. Annual and monthly drift ice roses indicate that the directions from WSW to SE are primarily prevailing, particularly in winter months. Besides, the annual ice speed extremums exceeding 40 cm s–1 mostly occur in the southerly directions from November to April. For the ice thickness, results reveal that it is prominently distributed in a thicker interval between 70 and 120 cm, and a thinner interval between 20 and 70 cm. The annual thickness maxima approximately range from 90 to 170 cm, primarily occurring from May to June, and demonstrate a light decreasing trend.

2019 ◽  
Vol 34 (2) ◽  
pp. 255-273
Author(s):  
Jeanne Moreira de Sousa ◽  
Luiz Antonio Candido ◽  
Julio Tota da Silva ◽  
Rita Valéria Andreoli ◽  
Mary Toshie Kayano ◽  
...  

Resumo A precipitação no norte da Amazônia dos verões e outonos austral, do período de 1988 a 1999, foi simulada utilizando o modelo regional Weather Research and Forecasting (WRF), através de uma abordagem em escalas distintas, com domínios aninhados de 45 e 15 km. As condições iniciais e de contorno foram obtidas da Climate Forecast System Reanalysis (CFSR) do National Centers for Environmental Prediction (NCEP). A habilidade do modelo foi testada usando diferentes bases de dados observacionais de precipitação, representativas de escalas espaciais distintas. O viés do modelo mostra dependências sazonal e espacial, com viés positivo no sudoeste da Amazônia brasileira durante o verão e, no noroeste da América do Sul, durante o outono. O refinamento de escala mostrou-se necessário para reproduzir as influências de superfície nos sistemas regionais e locais que afetam a distribuição das chuvas na região. O modelo WRF, em geral, reproduz os principais padrões espaciais observados de precipitação, sem o viés seco, típico dos modelos de circulação geral da atmosfera (MCGA). Os resultados indicam que a técnica de downscaling dinâmico melhora o desempenho do modelo WRF para a previsão climática sazonal na região Amazônica.


2018 ◽  
Vol 18 (18) ◽  
pp. 13547-13579 ◽  
Author(s):  
Zachary D. Lawrence ◽  
Gloria L. Manney ◽  
Krzysztof Wargan

Abstract. We compare herein polar processing diagnostics derived from the four most recent “full-input” reanalysis datasets: the National Centers for Environmental Prediction Climate Forecast System Reanalysis/Climate Forecast System, version 2 (CFSR/CFSv2), the European Centre for Medium-Range Weather Forecasts Interim (ERA-Interim) reanalysis, the Japanese Meteorological Agency's 55-year (JRA-55) reanalysis, and the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). We focus on diagnostics based on temperatures and potential vorticity (PV) in the lower-to-middle stratosphere that are related to formation of polar stratospheric clouds (PSCs), chlorine activation, and the strength, size, and longevity of the stratospheric polar vortex. Polar minimum temperatures (Tmin) and the area of regions having temperatures below PSC formation thresholds (APSC) show large persistent differences between the reanalyses, especially in the Southern Hemisphere (SH), for years prior to 1999. Average absolute differences of the reanalyses from the reanalysis ensemble mean (REM) in Tmin are as large as 3 K at some levels in the SH (1.5 K in the Northern Hemisphere – NH), and absolute differences of reanalysis APSC from the REM up to 1.5 % of a hemisphere (0.75 % of a hemisphere in the NH). After 1999, the reanalyses converge toward better agreement in both hemispheres, dramatically so in the SH: average Tmin differences from the REM are generally less than 1 K in both hemispheres, and average APSC differences less than 0.3 % of a hemisphere. The comparisons of diagnostics based on isentropic PV for assessing polar vortex characteristics, including maximum PV gradients (MPVGs) and the area of the vortex in sunlight (or sunlit vortex area, SVA), show more complex behavior: SH MPVGs showed convergence toward better agreement with the REM after 1999, while NH MPVGs differences remained largely constant over time; differences in SVA remained relatively constant in both hemispheres. While the average differences from the REM are generally small for these vortex diagnostics, understanding such differences among the reanalyses is complicated by the need to use different methods to obtain vertically resolved PV for the different reanalyses. We also evaluated other winter season summary diagnostics, including the winter mean volume of air below PSC thresholds, and vortex decay dates. For the volume of air below PSC thresholds, the reanalyses generally agree best in the SH, where relatively small interannual variability has led to many winter seasons with similar polar processing potential and duration, and thus low sensitivity to differences in meteorological conditions among the reanalyses. In contrast, the large interannual variability of NH winters has given rise to many seasons with marginal conditions that are more sensitive to reanalysis differences. For vortex decay dates, larger differences are seen in the SH than in the NH; in general, the differences in decay dates among the reanalyses follow from persistent differences in their vortex areas. Our results indicate that the transition from the reanalyses assimilating Tiros Operational Vertical Sounder (TOVS) data to advanced TOVS and other data around 1998–2000 resulted in a profound improvement in the agreement of the temperature diagnostics presented (especially in the SH) and to a lesser extent the agreement of the vortex diagnostics. We present several recommendations for using reanalyses in polar processing studies, particularly related to the sensitivity to changes in data inputs and assimilation. Because of these sensitivities, we urge great caution for studies aiming to assess trends derived from reanalysis temperatures. We also argue that one of the best ways to assess the sensitivity of scientific results on polar processing is to use multiple reanalysis datasets.


2021 ◽  
Vol 21 (7) ◽  
pp. 5355-5376
Author(s):  
Luis F. Millán ◽  
Gloria L. Manney ◽  
Zachary D. Lawrence

Abstract. Global reanalyses from data assimilation systems are among the most widely used datasets in weather and climate studies, and potential vorticity (PV) from reanalyses is invaluable for many studies of dynamical and transport processes. We assess how consistently modern reanalyses represent potential vorticity (PV) among each other, focusing not only on PV but also on process-oriented dynamical diagnostics including equivalent latitude calculated from PV and PV-based tropopause and stratospheric polar vortex characterization. In particular we assess the National Centers for Environmental Prediction Climate Forecast System Reanalysis/Climate Forecast System, version 2 (CFSR/CFSv2) reanalysis, the European Centre for Medium-Range Weather Forecasts Interim (ERA-Interim) reanalysis, the Japanese Meteorological Agency's 55-year (JRA-55) reanalysis, and the NASA Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). Overall, PV from all reanalyses agrees well with the reanalysis ensemble mean, providing some confidence that all of these recent reanalyses are suitable for most studies using PV-based diagnostics. Specific diagnostics where some larger differences are seen include PV-based tropopause locations in regions that have strong tropopause gradients (such as around the subtropical jets) or are sparse in high-resolution data (such as over Antarctica), and the stratospheric polar vortices during fall vortex formation and (especially) spring vortex breakup; studies of sensitive situations or regions such as these should examine PV from multiple reanalyses.


Author(s):  
Minh Tuan Bui ◽  
Jinmei Lu ◽  
Linmei Nie

Abstract The high-resolution Climate Forecast System Reanalysis (CFSR) data have recently become an alternative input for hydrological models in data-sparse regions. However, the quality of CFSR data for running hydrological models in the Arctic is not well studied yet. This paper aims to compare the quality of CFSR data with ground-based data for hydrological modeling in an Arctic watershed, Målselv. The QSWAT model, a coupling of the hydrological model SWAT (soil and water assessment tool) and the QGIS, was applied in this study. The model ran from 1995 to 2012 with a 3-year warm-up period (1995–1997). Calibration (1998–2007), validation (2008–2012), and uncertainty analyses were conducted by the model for each dataset at five hydro-gauging stations within the watershed. The objective function Nash–Sutcliffe coefficient of efficiency for calibration is 0.65–0.82 with CFSR data and 0.55–0.74 with ground-based data, which indicate higher performance of the high-resolution CFSR data than the existing scattered ground-based data. The CFSR weather grid points showed higher variation in precipitation than the ground-based weather stations across the whole watershed. The calculated average annual rainfall by CFSR data for the whole watershed is approximately 24% higher than that by ground-based data, which results in some higher water balance components. The CFSR data also demonstrate its high capacities to replicate the streamflow hydrograph, in terms of timing and magnitude of peak and low flow. Through examination of the uncertainty coefficients P-factors (≥0.7) and R-factors (≤1.5), this study concludes that CFSR data are a reliable source for running hydrological models in the Arctic watershed Målselv.


2012 ◽  
Vol 13 (5) ◽  
pp. 1621-1630 ◽  
Author(s):  
Jesse Meng ◽  
Rongqian Yang ◽  
Helin Wei ◽  
Michael Ek ◽  
George Gayno ◽  
...  

Abstract The NCEP Climate Forecast System Reanalysis (CFSR) uses the NASA Land Information System (LIS) to create its land surface analysis: the NCEP Global Land Data Assimilation System (GLDAS). Comparing to the previous two generations of NCEP global reanalyses, this is the first time a coupled land–atmosphere data assimilation system is included in a global reanalysis. Global observed precipitation is used as direct forcing to drive the land surface analysis, rather than the typical reanalysis approach of using precipitation assimilating from a background atmospheric model simulation. Global observed snow cover and snow depth fields are used to constrain the simulated snow variables. This paper describes 1) the design and implementation of GLDAS/LIS in CFSR, 2) the forcing of the observed global precipitation and snow fields, and 3) preliminary results of global and regional soil moisture content and land surface energy and water budgets closure. With special attention made during the design of CFSR GLDAS/LIS, all the source and sink terms in the CFSR land surface energy and water budgets can be assessed and the total budgets are balanced. This is one of many aspects indicating improvements in CFSR from the previous NCEP reanalyses.


2013 ◽  
Vol 70 ◽  
pp. 207-220 ◽  
Author(s):  
Justin E. Stopa ◽  
Kwok Fai Cheung ◽  
Hendrik L. Tolman ◽  
Arun Chawla

2015 ◽  
Vol 28 (3) ◽  
pp. 1166-1183 ◽  
Author(s):  
Lejiang Yu ◽  
Shiyuan Zhong ◽  
Xindi Bian ◽  
Warren E. Heilman

Abstract This study examines the spatial and temporal variability of wind speed at 80 m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the winter (summer), and higher (lower) speeds over much of the Midwest and U.S. Northeast (U.S. West and Southeast). Trends are also variable spatially, with more upward trends in areas of the Great Plains and Intermountain West of the United States and more downward trends elsewhere. The leading EOF mode, which accounts for 20% (summer) to 33% (winter) of the total variance and represents in-phase variations across the United States, responds mainly to the North Atlantic Oscillation (NAO) in summer and El Niño–Southern Oscillation (ENSO) in the other seasons. The dominant variation pattern can be explained by a southerly/southwesterly (westerly) anomaly over the U.S. East (U.S. West) as a result of the anomalous mean sea level pressure (MSLP) pattern. The second EOF mode, which explains about 15% of the total variance and shows a seesaw pattern, is mainly related to the springtime Arctic Oscillation (AO), the summertime recurrent circumglobal teleconnection (CGT), the autumn Pacific decadal oscillation (PDO), and the winter El Niño Modoki. The anomalous jet stream and MSLP patterns associated with these indices are responsible for the wind variation.


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