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Atmosphere
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Regional Climate Modeling: Ocean–Atmosphere Coupling
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Regional Climate Modeling: Ocean–Atmosphere Coupling

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 23686

Special Issue Editors

Professor Bodo Ahrens

E-Mail Website
Guest Editor
Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt am Main, Frankfurt, Germany
Interests: Hydrometeorology, -climatology, climate system modelling, data assimilation, and information flow
Dr. Anika Obermann-Hellhund

E-Mail Website
Co-Guest Editor
Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt am Main, Frankfurt, Germany
Interests: ocean-atmosphere interactions; regional winds; climate simulations of Europe and its marginal seas; islands

Special Issue Information

Dear Colleagues,

We would like to invite you to contribute to a Special Issue of Atmospheres that will be dedicated to the field of ocean–atmosphere interactively coupled regional climate modeling. The development of high-resolution, fully-coupled climate models started in some regions (e.g., in the Baltic and Mediterranean area) more than ten years ago, but recently coupled systems including additional climate system components (e.g., ice physics, biochemistry) have been developed. Nowadays, they cover more regions of interest (e.g., the Bay of Bengal, the Arctic) and target higher-convection-permitting resolutions. Coordinated ensembles of regional coupled climate projections are part of, e.g., Med-CORDEX (http://www.medcordex.eu) and Baltic Earth (http://www.baltic.earth).  These developments are also recognized in regional climate assessment reports that rely on submitted or published papers.

The Special Issue will elucidate developments in coupled regional climate models and simulations. Both modeling studies on climate processes and studies on model evaluation and intercomparison are welcome. Manuscripts may also focus on climate predictions (from seasonal to centennial) using ensembles of coupled climate simulations and are not limited to specific areas. Studies using high-resolution simulations that, e.g., provide a better representation of processes close to the coast are encouraged. In addition, nesting and coupling strategies of different climate compartment models and new analysis techniques for the investigation of complex coupled systems applied to the air–sea challenge are of high interest.

Professor Bodo Ahrens
Dr. Anika Obermann-Hellhund
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Regional climate models
  • Interactive processes
  • Ocean–atmosphere coupling
  • High-resolution climate prediction/projections
  • Analysis methods for complex climate phenomena

Published Papers (5 papers)

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Research

36 pages, 9025 KiB  
Article
Internal Model Variability of the Regional Coupled System Model GCOAST-AHOI
by Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Sebastian Grayek, Ronny Petrik, Burkhardt Rockel, Joanna Staneva, Frauke Feser and Corinna Schrum
Atmosphere 2020, 11(3), 227; https://doi.org/10.3390/atmos11030227 - 26 Feb 2020
Cited by 15 | Viewed by 4243
Abstract
Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in [...] Read more.
Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September–31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions. Full article
(This article belongs to the Special Issue Regional Climate Modeling: Ocean–Atmosphere Coupling)
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Graphical abstract

18 pages, 7824 KiB  
Article
Added Value of Atmosphere-Ocean Coupling in a Century-Long Regional Climate Simulation
by Fanni Dóra Kelemen, Cristina Primo, Hendrik Feldmann and Bodo Ahrens
Atmosphere 2019, 10(9), 537; https://doi.org/10.3390/atmos10090537 - 11 Sep 2019
Cited by 15 | Viewed by 4307
Abstract
A twentieth century-long coupled atmosphere-ocean regional climate simulation with COSMO-CLM (Consortium for Small-Scale Modeling, Climate Limited-area Model) and NEMO (Nucleus for European Modelling of the Ocean) is studied here to evaluate the added value of coupled marginal seas over continental regions. The interactive [...] Read more.
A twentieth century-long coupled atmosphere-ocean regional climate simulation with COSMO-CLM (Consortium for Small-Scale Modeling, Climate Limited-area Model) and NEMO (Nucleus for European Modelling of the Ocean) is studied here to evaluate the added value of coupled marginal seas over continental regions. The interactive coupling of the marginal seas, namely the Mediterranean, the North and the Baltic Seas, to the atmosphere in the European region gives a comprehensive modelling system. It is expected to be able to describe the climatological features of this geographically complex area even more precisely than an atmosphere-only climate model. The investigated variables are precipitation and 2 m temperature. Sensitivity studies are used to assess the impact of SST (sea surface temperature) changes over land areas. The different SST values affect the continental precipitation more than the 2 m temperature. The simulated variables are compared to the CRU (Climatic Research Unit) observational data, and also to the HOAPS/GPCC (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, Global Precipitation Climatology Centre) data. In the coupled simulation, added skill is found primarily during winter over the eastern part of Europe. Our analysis shows that, over this region, the coupled system is dryer than the uncoupled system, both in terms of precipitation and soil moisture, which means a decrease in the bias of the system. Thus, the coupling improves the simulation of precipitation over the eastern part of Europe, due to cooler SST values and in consequence, drier soil. Full article
(This article belongs to the Special Issue Regional Climate Modeling: Ocean–Atmosphere Coupling)
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28 pages, 1336 KiB  
Article
Evaluation of the Sea-Ice Simulation in the Upgraded Version of the Coupled Regional Atmosphere-Ocean- Sea Ice Model HIRHAM–NAOSIM 2.0
by Wolfgang Dorn, Annette Rinke, Cornelia Köberle, Klaus Dethloff and Rüdiger Gerdes
Atmosphere 2019, 10(8), 431; https://doi.org/10.3390/atmos10080431 - 26 Jul 2019
Cited by 11 | Viewed by 4724
Abstract
The sea-ice climatology and sea-ice trends and variability are evaluated in simulations with the new version of the coupled Arctic atmosphere-ocean-sea ice model HIRHAM–NAOSIM 2.0. This version utilizes upgraded model components for the coupled subsystems, which include physical and numerical improvements and higher [...] Read more.
The sea-ice climatology and sea-ice trends and variability are evaluated in simulations with the new version of the coupled Arctic atmosphere-ocean-sea ice model HIRHAM–NAOSIM 2.0. This version utilizes upgraded model components for the coupled subsystems, which include physical and numerical improvements and higher horizontal and vertical resolution, and a revised coupling procedure with the aid of the coupling software YAC (Yet Another Coupler). The model performance is evaluated against observationally based data sets and compared with the previous version. Ensemble simulations for the period 1979–2016 reveal that Arctic sea ice is thicker in all seasons and closer to observations than in the previous version. Wintertime biases in sea-ice extent, upper ocean temperatures, and near-surface air temperatures are reduced, while summertime biases are of similar magnitude as in the previous version. Problematic issues of the current model configuration and potential corrective measures and further developments are discussed. Full article
(This article belongs to the Special Issue Regional Climate Modeling: Ocean–Atmosphere Coupling)
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26 pages, 3487 KiB  
Article
Surface Heat Budget over the North Sea in Climate Change Simulations
by Christian Dieterich, Shiyu Wang, Semjon Schimanke, Matthias Gröger, Birgit Klein, Robinson Hordoir, Patrick Samuelsson, Ye Liu, Lars Axell, Anders Höglund and H. E. Markus Meier
Atmosphere 2019, 10(5), 272; https://doi.org/10.3390/atmos10050272 - 14 May 2019
Cited by 27 | Viewed by 5795
Abstract
An ensemble of regional climate change scenarios for the North Sea is validated and analyzed. Five Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Models (GCMs) using three different Representative Concentration Pathways (RCPs) have been downscaled with the coupled atmosphere–ice–ocean model RCA4-NEMO. [...] Read more.
An ensemble of regional climate change scenarios for the North Sea is validated and analyzed. Five Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Models (GCMs) using three different Representative Concentration Pathways (RCPs) have been downscaled with the coupled atmosphere–ice–ocean model RCA4-NEMO. Validation of sea surface temperature (SST) against different datasets suggests that the model results are well within the spread of observational datasets. The ensemble mean SST with a bias of less than 1 ∘ C is the solution that fits the observations best and underlines the importance of ensemble modeling. The exchange of momentum, heat, and freshwater between atmosphere and ocean in the regional, coupled model compares well with available datasets. The climatological seasonal cycles of these fluxes are within the 95% confidence limits of the datasets. Towards the end of the 21st century the projected North Sea SST increases by 1.5 ∘ C (RCP 2.6), 2 ∘ C (RCP 4.5), and 4 ∘ C (RCP 8.5), respectively. Under this change the North Sea develops a specific pattern of the climate change signal for the air–sea temperature difference and latent heat flux in the RCP 4.5 and 8.5 scenarios. In the RCP 8.5 scenario the amplitude of the spatial heat flux anomaly increases to 5 W/m 2 at the end of the century. Different hypotheses are discussed that could contribute to the spatially non-uniform change in air–sea interaction. The most likely cause for an increased latent heat loss in the central western North Sea is a drier atmosphere towards the end of the century. Drier air in the lee of the British Isles affects the balance of the surface heat budget of the North Sea. This effect is an example of how regional characteristics modulate global climate change. For climate change projections on regional scales it is important to resolve processes and feedbacks at regional scales. Full article
(This article belongs to the Special Issue Regional Climate Modeling: Ocean–Atmosphere Coupling)
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19 pages, 4434 KiB  
Article
Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region
by Ashish Sharma, Alan F. Hamlet and Harindra J.S. Fernando
Atmosphere 2019, 10(5), 266; https://doi.org/10.3390/atmos10050266 - 13 May 2019
Cited by 4 | Viewed by 3564
Abstract
Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and [...] Read more.
Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and 4-km horizontal resolutions and compare it with 32-km NARR data and 1/16th-degree gridded observations for the Midwest U.S. and Great Lakes region from 1991 to 2000. We used daily climatology, inter-annual variability, percentile, and dry days as metrics for inter-comparison for precipitation. We also calculated the summer and winter daily seasonal minimum, maximum, and average temperature to delineate the temperature trends. Results showed that NARR data is a useful precipitation product for mean warm season and summer climatological studies, but performs extremely poorly for winter and cold seasons for this region. WRF model simulations at 12- and 4-km horizontal resolutions were able to capture the lake-effect precipitation successfully when driven by observed lake surface temperatures. Simulations at 4-km showed negative bias in capturing precipitation without convective parameterization but captured the number of dry days and 99th percentile precipitation extremes well. Overall, our study cautions against hastily pushing for increasingly higher resolution in climate studies, and highlights the need for the careful selection of large-scale boundary forcing data. Full article
(This article belongs to the Special Issue Regional Climate Modeling: Ocean–Atmosphere Coupling)
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