scholarly journals Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

2007 ◽  
Vol 87 (1-2) ◽  
pp. 35-50 ◽  
Author(s):  
Holger Göttel ◽  
Jörn Alexander ◽  
Elke Keup-Thiel ◽  
Diana Rechid ◽  
Stefan Hagemann ◽  
...  
2020 ◽  
Author(s):  
Mirseid Akperov ◽  
Vladimir A. Semenov ◽  
Igor I. Mokhov ◽  
Wolfgang Dorn ◽  
Annette Rinke

<p>The impact of the Atlantic water inflow (AW inflow) into the Barents Sea on the regional cyclone activity in winter is analyzed in 10 ensemble simulations with the coupled Arctic atmosphere-ocean-sea ice model HIRHAM-NAOSIM for the 1979–2016 period. The model shows a statistically robust connection between AW inflow and climate variability in the Barents Sea. The analysis reveals that anomalously high AW inflow leads to changed baroclinicity in the lower troposphere via changed static stability and wind shear, and thus favorable conditions for cyclogenesis in the Barents/Kara Seas. The frequency of occurrence of cyclones, but particularly of intense cyclones, is increased over the Barents Sea. Furthermore, the cyclones in the Barents Sea become larger (increased radius) and stronger (increased intensity) in response to an increased AW inflow into the Barents Sea, compared to years of anomalously low AW inflow.</p><p>The authors acknowledge the support by the Russian-German project funded by the Federal Ministry of Education and Research of Germany and Ministry of Science and Higher Education of the Russian Federation (grant 05.616.21.0109 (RFMEFI61619X0109)).</p>


2019 ◽  
Vol 59 (4) ◽  
pp. 529-538
Author(s):  
M. G. Akperov ◽  
V. A. Semenov ◽  
I. I. Mokhov ◽  
M. A. Dembitskaya ◽  
D. D. Bokuchava ◽  
...  

The influence of the oceanic heat inflow into the Barents Sea on the sea ice concentration and atmospheric characteristics, including the atmospheric static stability during winter months, is investigated on the basis of the results of ensemble simulations with the regional climate model HIRHAM/NAOSIM for the Arctic. The static stability of the atmosphere is the important indicator of the spatial and temporal variability of polar mesocyclones in the Arctic region. The results of the HIRHAM/NAOSIM regional climate model ensemble simulations (RCM) for the period from 1979 to 2016 were used for the analysis. The initial and lateral boundary conditions for RCM in the atmosphere were set in accordance with the ERA-Interim reanalysis data. An analysis of 10 ensemble simulations with identical boundary conditions and the same radiation forcing for the Arctic was performed. Various realizations of ensemble simulations with RCM were obtained by changing the initial conditions for integrating the oceanic block of the model. Different realizations of ensemble simulations with RCM are obtained by changing the initial conditions of the model oceanic block integration. The composites method was used for the analysis, i.e. the difference between the mean values for years with the maximum and minimum inflow of oceanic water into the Barents Sea. The statistical significance of the results (at a significance level of p < 0.05) was estimated using Student's t-test. In general, the regional climate model reproduces the seasonal changes in the inflow of the oceanic water and heat into the Barents Sea reasonably well. There is a strong relationship between the changes in the oceanic water and ocean heat inflow, sea ice concentration, and surface air temperature in the Barents Sea. Herewith, the increase in the oceanic water inflow into the Barents Sea in winter leads to a decrease in static stability, which contributes to changes in regional cyclonic activity. The decrease of the static stability is most pronounced in the southern part of the Barents Sea and also to the west of Svalbard.


2016 ◽  
Author(s):  
Andreas Dobler ◽  
Jan Erik Haugen ◽  
Rasmus Emil Benestad

Abstract. Regional climate models can provide estimates for quantities that are difficult to study in empirical studies, such as cloud cover, wind, sea-ice or dependencies between variables. In this study, the regional climate model COSMO-CLM was used to simulate local climate conditions over the Barents region and provide projections for the three emission scenarios RCP2.6, RCP4.5 and RCP8.5. The results indicate that the most pronounced local warming can be expected in winter in the high Arctic near the present sea-ice border. The changes reach up to 20K, resulting in future temperatures close to melting. Similar spatial patterns are seen for changes in precipitation and wind in all scenarios, but with different amplitudes. Precipitation sensitivities, however, show the highest values along the west coast of Norway and in the Arctic during summer. For clouds, the projections show a decrease in winter mean cloud cover over sea and an increase over land, dominated by changes in low layer clouds. Over the Barents sea, convective cloud fraction is projected to increase, together with an increases in convective and total precipitation. In contrast to the COSMO-CLM and two other regional climate models taken into account, the ensemble mean of the driving global models shows an increasing trend in total cloud cover over the Barents sea. An analysis of the opposing trends reveals that there is an added value in the regional climate model projections for the Barents region.


Author(s):  
Valeriy G. Yakubenko ◽  
Anna L. Chultsova

Identification of water masses in areas with complex water dynamics is a complex task, which is usually solved by the method of expert assessments. In this paper, it is proposed to use a formal procedure based on the application of the method of optimal multiparametric analysis (OMP analysis). The data of field measurements obtained in the 68th cruise of the R/V “Academician Mstislav Keldysh” in the summer of 2017 in the Barents Sea on the distribution of temperature, salinity, oxygen, silicates, nitrogen, and phosphorus concentration are used as a data for research. A comparison of the results with data on the distribution of water masses in literature based on expert assessments (Oziel et al., 2017), allows us to conclude about their close structural similarity. Some differences are related to spatial and temporal shifts of measurements. This indicates the feasibility of using the OMP analysis technique in oceanological studies to obtain quantitative data on the spatial distribution of different water masses.


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