scholarly journals Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic

2013 ◽  
Vol 6 (3) ◽  
pp. 849-859 ◽  
Author(s):  
P. Berg ◽  
R. Döscher ◽  
T. Koenigk
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled System ◽  
The Arctic ◽  
Spectral Nudging ◽  
The North ◽  
Temperature And Precipitation

Abstract. The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX (COordinated Regional climate Downscaling EXperiment) region, with an emphasis on its suitability to be coupled to a regional ocean and sea ice model. Large biases in mean sea level pressure (MSLP) are identified, with pronounced too-high pressure centred over the North Pole in summer of over 5 hPa, and too-low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea ice biases in a future coupled system. The large-scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large-scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables, such as surface radiative components, two-metre temperature and precipitation.

scholarly journals Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic

2013 ◽  
Vol 6 (1) ◽  
pp. 495-520 ◽  
Author(s):  
P. Berg ◽  
R. Döscher ◽  
T. Koenigk
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled System ◽  
The Arctic ◽  
Spectral Nudging ◽  
The North ◽  
Temperature And Precipitation

Abstract. The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX region, with an emphasis on its suitability to be coupled to a regional ocean and sea-ice model. Large biases in mean sea level pressure (MSLP) are identified, with pronounced too high pressure centred over the North Pole in summer of over 5 hPa, and too low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea-ice biases in a future coupled system. The large scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables such as surface radiative components, two metre temperature and precipitation.

scholarly journals Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model

2022 ◽  
Vol 22 (1) ◽  
pp. 441-463
Author(s):  
Carolina Viceto ◽  
Irina V. Gorodetskaya ◽  
Annette Rinke ◽  
Marion Maturilli ◽  
Alfredo Rocha ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
The Arctic ◽  
Atmospheric Rivers ◽  
The North ◽  
Tracking Algorithms ◽  
North Eastern ◽  
Sea Ice Edge

Abstract. Recently, a significant increase in the atmospheric moisture content has been documented over the Arctic, where both local contributions and poleward moisture transport from lower latitudes can play a role. This study focuses on the anomalous moisture transport events confined to long and narrow corridors, known as atmospheric rivers (ARs), which are expected to have a strong influence on Arctic moisture amounts, precipitation, and the energy budget. During two concerted intensive measurement campaigns – Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL) – that took place at and near Svalbard, three high-water-vapour-transport events were identified as ARs, based on two tracking algorithms: the 30 May event, the 6 June event, and the 9 June 2017 event. We explore the temporal and spatial evolution of the events identified as ARs and the associated precipitation patterns in detail using measurements from the French (Polar Institute Paul Emile Victor) and German (Alfred Wegener Institute for Polar and Marine Research) Arctic Research Base (AWIPEV) in Ny-Ålesund, satellite-borne measurements, several reanalysis products (the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) Interim (ERA-Interim); the ERA5 reanalysis; the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2); the Climate Forecast System version 2 (CFSv2); and the Japanese 55-Year Reanalysis (JRA-55)), and the HIRHAM regional climate model version 5 (HIRHAM5). Results show that the tracking algorithms detected the events differently, which is partly due to differences in the spatial and temporal resolution as well as differences in the criteria used in the tracking algorithms. The first event extended from western Siberia to Svalbard, caused mixed-phase precipitation, and was associated with a retreat of the sea-ice edge. The second event, 1 week later, had a similar trajectory, and most precipitation occurred as rain, although mixed-phase precipitation or only snowfall occurred in some areas, mainly over the coast of north-eastern Greenland and the north-east of Iceland, and no differences were noted in the sea-ice edge. The third event showed a different pathway extending from the north-eastern Atlantic towards Greenland before turning south-eastward and reaching Svalbard. This last AR caused high precipitation amounts on the east coast of Greenland in the form of rain and snow and showed no precipitation in the Svalbard region. The vertical profiles of specific humidity show layers of enhanced moisture that were concurrent with dry layers during the first two events and that were not captured by all of the reanalysis datasets, whereas the HIRHAM5 model misrepresented humidity at all vertical levels. There was an increase in wind speed with height during the first and last events, whereas there were no major changes in the wind speed during the second event. The accuracy of the representation of wind speed by the reanalyses and the model depended on the event. The objective of this paper was to build knowledge from detailed AR case studies, with the purpose of performing long-term analysis. Thus, we adapted a regional AR detection algorithm to the Arctic and analysed how well it identified ARs, we used different datasets (observational, reanalyses, and model) and identified the most suitable dataset, and we analysed the evolution of the ARs and their impacts in terms of precipitation. This study shows the importance of the Atlantic and Siberian pathways of ARs during spring and beginning of summer in the Arctic; the significance of the AR-associated strong heat increase, moisture increase, and precipitation phase transition; and the requirement for high-spatio-temporal-resolution datasets when studying these intense short-duration events.

scholarly journals Validation of the sea ice surface albedo scheme of the regional climate model HIRHAM–NAOSIM using aircraft measurements during the ACLOUD/PASCAL campaigns

2019 ◽  
Author(s):  
Evelyn Jäkel ◽  
Johannes Stapf ◽  
Manfred Wendisch ◽  
Marcel Nicolaus ◽  
Wolfgang Dorn ◽  
...  
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Large Scale ◽  
Surface Albedo ◽  
Climate Model ◽  
Mean Squared Error ◽  
Functional Dependence ◽  
Regional Climate ◽  
Arctic Boundary Layer ◽  
Ice Surface

Abstract. For large scale and long term Arctic climate simulations appropriate parameterization of the surface albedo are required. Therefore, the sea ice surface (SIS) albedo parameterization of the coupled regional climate model HIRHAM–NAOSIM was examined against measurements performed during the joint ACLOUD (Arctic CLoud Observations Using airborne mea-surements during polar Day) and PASCAL (Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL) cam-paigns which were performed in May/June 2017 north of Svalbard. The SIS albedo parameterization was tested using measured quantities of the prognostic variables surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes (snow covered ice, bare ice, and melt ponds) derived from digital camera images taken onboard of the Polar 5/6 aircraft. Based on data gained during 12 flights, it was found that the range of parameterized SIS albedo for individual days is smaller than that of the measurements. This was attributed to the biased functional dependence of the SIS albedo parameterization on temperature. Furthermore, a temporal bias was observed with higher values compared to the modeled SIS albedo (0.88 compared to 0.84 for 29 May 2017) in the beginning of the campaign, and an opposite trend towards the end of the campaign (0.67 versus 0.83 for 25 June 2017). Furthermore, the surface type fraction parameterization was tested against the camera image product which revealed an agreement within 1 %. An adjustment of the variables, defining the parameterized SIS albedo, and additionally accounting for the cloud cover could reduce the root mean squared error from 0.14 to 0.04 for cloud free/broken cloud situations and from 0.06 to 0.05 for overcast conditions.

scholarly journals Effects of sea ice change on the Arctic climate: insights from experiments with a polar atmospheric regional climate model

2021 ◽  
Author(s):  
Xiying Liu ◽  
Chenchen Lu
Keyword(s):  
Sea Ice ◽  
Boundary Conditions ◽  
Regional Climate Model ◽  
Air Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Lower Boundary ◽  
Arctic Climate ◽  
The Arctic ◽  
Sea Ice Concentration

Abstract To get insights into the effects of sea ice change on the Arctic climate, a polar atmospheric regional climate model was used to perform two groups of numerical experiments with prescribed sea ice cover of typical mild and severe sea ice. In experiments within the same group, the lateral boundary conditions and initial values were kept the same. The prescribed sea ice concentration (SIC) and other fields for the lower boundary conditions were changed every six hours. 10-year integration was completed, and monthly mean results were saved for analysis in each experiment. It is shown that the changes in annual mean surface air temperature have close connections with that in SIC, and the maximum change of temperature surpasses 15 K. The effects of SIC changes on 850 hPa air temperature is also evident, with more significant changes in the group with reduced sea ice. The higher the height, the weaker the response in air temperature to SIC change. The annual mean SIC change creates the pattern of differences in annual mean sea level pressure. The degree of significance in pressure change is modulated by atmospheric stratification stability. In response to reduction/increase of sea ice, the intensity of polar vortex weakens/strengthens.

scholarly journals The influence of ocean heat transport in the Barents Sea on the regional sea ice and the atmospheric static stability

2019 ◽  
Vol 59 (4) ◽  
pp. 529-538
Author(s):  
M. G. Akperov ◽  
V. A. Semenov ◽  
I. I. Mokhov ◽  
M. A. Dembitskaya ◽  
D. D. Bokuchava ◽  
...  
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Climate Model ◽  
Barents Sea ◽  
Regional Climate ◽  
Static Stability ◽  
The Arctic ◽  
Oceanic Water ◽  
Ensemble Simulations ◽  
The Barents Sea

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.

scholarly journals Validation of the sea ice surface albedo scheme of the regional climate model HIRHAM–NAOSIM using aircraft measurements during the ACLOUD/PASCAL campaigns

2019 ◽  
Vol 13 (6) ◽  
pp. 1695-1708 ◽  
Author(s):  
Evelyn Jäkel ◽  
Johannes Stapf ◽  
Manfred Wendisch ◽  
Marcel Nicolaus ◽  
Wolfgang Dorn ◽  
...  
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Large Scale ◽  
Surface Albedo ◽  
Climate Model ◽  
Mean Squared Error ◽  
Functional Dependence ◽  
Regional Climate ◽  
Airborne Measurements ◽  
Ice Surface

Abstract. For large-scale and long-term Arctic climate simulations appropriate parameterization of the surface albedo is required. Therefore, the sea ice surface (SIS) albedo parameterization of the coupled regional climate model HIRHAM–NAOSIM was examined against broadband surface albedo measurements performed during the joint ACLOUD (Arctic CLoud Observations Using airborne measurements during polar Day) and PASCAL (Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL) campaigns, which were performed in May–June 2017 north of Svalbard. The SIS albedo parameterization was tested using measured quantities of the prognostic variables surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes (snow-covered ice, bare ice, and melt ponds) derived from digital camera images taken on board the Polar 5 and 6 aircraft. The selected low-altitude (less than 100 m) flight sections of overall 12 flights were performed over surfaces dominated by snow-covered ice. It was found that the range of parameterized SIS albedo for individual days is smaller than that of the measurements. This was attributed to the biased functional dependence of the SIS albedo parameterization on temperature. Furthermore, a time-variable bias was observed with higher values compared to the modeled SIS albedo (0.88 compared to 0.84 for 29 May 2017) in the beginning of the campaign, and an opposite trend towards the end of the campaign (0.67 versus 0.83 for 25 June 2017). Furthermore, the surface type fraction parameterization was tested against the camera image product, which revealed an agreement within 1 %. An adjustment of the variables, defining the parameterized SIS albedo, and additionally accounting for the cloud cover could reduce the root-mean-squared error from 0.14 to 0.04 for cloud free/broken cloud situations and from 0.06 to 0.05 for overcast conditions.

scholarly journals A Dynamical Downscaling Case Study for Typhoons in Southeast Asia Using a Regional Climate Model

2008 ◽  
Vol 136 (5) ◽  
pp. 1806-1815 ◽  
Author(s):  
Frauke Feser ◽  
Hans von Storch
Keyword(s):  
Boundary Conditions ◽  
Southeast Asia ◽  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Lateral Boundary ◽  
Spectral Nudging ◽  
Lateral Boundary Conditions ◽  
Initial Starting

Abstract This study explores the possibility of reconstructing the weather of Southeast Asia for the last decades using an atmospheric regional climate model, the Climate version of the Lokal-Modell (CLM). For this purpose global National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses data were dynamically downscaled to 50 km and in a double-nesting approach to 18-km grid distance. To prevent the regional model from deviating significantly from the reanalyses with respect to large-scale circulation and large-scale weather phenomena, a spectral nudging technique was used. The performance of this technique in dealing with Southeast Asian typhoons is now examined by considering an ensemble of one simulated typhoon case. This analysis is new insofar as it deals with simulations done in the climate mode (so that any skill of reproducing the typhoon is not related to details of initial conditions), is done in ensemble mode (the same development is described by several simulations), and is done with a spectral nudging constraint (so that the observed large-scale state is enforced in the model domain). This case indicates that tropical storms that are coarsely described by the reanalyses are correctly identified and tracked; considerably deeper core pressure and higher wind speeds are simulated compared to the driving reanalyses. When the regional atmospheric model is run without spectral nudging, significant intraensemble variability occurs; also additional, nonobserved typhoons form. Thus, the insufficiency of lateral boundary conditions alone for determining the details of the dynamic developments in the interior becomes very clear. The same lateral boundary conditions are consistent with different developments in the interior. Several sensitivity experiments were performed concerning varied grid distances, different initial starting dates of the simulations, and changed spectral nudging parameters.

scholarly journals Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central Europe

2020 ◽  
Vol 11 (3) ◽  
pp. 617-640 ◽  
Author(s):  
Andrea Böhnisch ◽  
Ralf Ludwig ◽  
Martin Leduc
Keyword(s):  
Regional Climate Model ◽  
North Atlantic ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Internal Variability ◽  
Single Model ◽  
Central European ◽  
The North ◽  
The North Atlantic Oscillation

Abstract. Central European weather and climate are closely related to atmospheric mass advection triggered by the North Atlantic Oscillation (NAO), which is a relevant index for quantifying internal climate variability on multi-annual timescales. It remains unclear, however, how large-scale circulation variability affects local climate characteristics when downscaled using a regional climate model. In this study, 50 members of a single-model initial-condition large ensemble (LE) of a nested regional climate model are analyzed for a NAO–climate relationship. The overall goal of the study is to assess whether the range of NAO internal variability is represented consistently between the driving global climate model (GCM; the Canadian Earth System Model version 2 – CanESM2) and the nested regional climate model (RCM; the Canadian Regional Climate Model version 5 – CRCM5). Responses of mean surface air temperature and total precipitation to changes in the NAO index value are examined in a central European domain in both CanESM2-LE and CRCM5-LE via Pearson correlation coefficients and the change per unit index change for historical (1981–2010) and future (2070–2099) winters. Results show that statistically robust NAO patterns are found in the CanESM2-LE under current forcing conditions. NAO flow pattern reproductions in the CanESM2-LE trigger responses in the high-resolution CRCM5-LE that are comparable to reanalysis data. NAO–response relationships weaken in the future period, but their inter-member spread shows no significant change. The results stress the value of single-model ensembles for the evaluation of internal variability by pointing out the large differences of NAO–response relationships among individual members. They also strengthen the validity of the nested ensemble for further impact modeling using RCM data only, since important large-scale teleconnections present in the driving data propagate properly to the fine-scale dynamics in the RCM.

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