Comparison of land surface hydrology in regional climate simulations of the Baltic Sea catchment

2002 ◽  
Vol 255 (1-4) ◽  
pp. 169-193 ◽  
Author(s):  
B.J.J.M. van den Hurk ◽  
L.P. Graham ◽  
P. Viterbo
2021 ◽  
Author(s):  
Matthias Gröger ◽  
Christian Dieterich ◽  
Jari Haapala ◽  
Ha Thi Minh Ho-Hagemann ◽  
Stefan Hagemann ◽  
...  

Abstract. Non-linear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross compartmental feedback loops in the earth system. These feedbacks are less well represented in traditional standalone atmosphere and ocean models on which many of today's regional climate assessments rely on (e.g. EuroCordex, NOSCCA, BACC II). This promotes the development of regional climate models for the Baltic Sea region by coupling different compartments of the earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed into the region by using prescribed boundary conditions, and thus, permit a higher degree of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress of model systems that allow two way communication between atmosphere and ocean models, models for the land surface including the terrestrial biosphere, as well as wave models at the air sea interface and hydrology models for water cycle closure. However, several processes that have so far mostly been realized by one way coupling such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g. aerosols) are not considered here.Compared to uncoupled standalone models, coupled earth system models models can modify mean near surface air temperatures locally up to several degrees compared to their standalone atmospheric counterparts using prescribed surface boundary conditions. Over open ocean areas, the representation of small scale oceanic processes such as vertical mixing, and sea ice dynamics appear essential to accurately resolve the air sea heat exchange in the Baltic Sea region and can only be provided by online coupled high resolution ocean models. In addition, the coupling of wave models at the ocean-atmosphere interface allows a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes like e.g. heavy precipitation, storms, or tropical nights, and appear to be sensitive to coupling.For the present-day climate, many coupled atmosphere-ocean and atmosphere-land surface models demonstrate added value with respect to single climate variables in particular when low quality boundary data were used in the respective standalone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models for closing the water cycle remains problematic as the accuracy of precipitation provided by the atmosphere models is in most cases insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments.Many regional standalone ocean and atmosphere models are tuned to well represent present day climatologies rather than accurately simulate climate change. More research is necessary about how the regional climate sensitivity (e.g. the models’ response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared to uncoupled ones.


2021 ◽  
Vol 12 (3) ◽  
pp. 939-973
Author(s):  
Matthias Gröger ◽  
Christian Dieterich ◽  
Jari Haapala ◽  
Ha Thi Minh Ho-Hagemann ◽  
Stefan Hagemann ◽  
...  

Abstract. Nonlinear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross-compartmental feedback loops in the Earth system. These feedbacks are less well represented in the traditional stand-alone atmosphere and ocean models on which many of today's regional climate assessments rely (e.g., EURO-CORDEX, NOSCCA and BACC II). This has promoted the development of regional climate models for the Baltic Sea region by coupling different compartments of the Earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed on the region by prescribed boundary conditions and, thus, permit more degrees of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress on model systems that allow two-way communication between atmosphere and ocean models; models for the land surface, including the terrestrial biosphere; and wave models at the air–sea interface and hydrology models for water cycle closure. However, several processes that have mostly been realized by one-way coupling to date, such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g., aerosols), are not considered here. In contrast to uncoupled stand-alone models, coupled Earth system models can modify mean near-surface air temperatures locally by up to several degrees compared with their stand-alone atmospheric counterparts using prescribed surface boundary conditions. The representation of small-scale oceanic processes, such as vertical mixing and sea-ice dynamics, appears essential to accurately resolve the air–sea heat exchange over the Baltic Sea, and these parameters can only be provided by online coupled high-resolution ocean models. In addition, the coupling of wave models at the ocean–atmosphere interface allows for a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large-scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land-use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes such as heavy precipitation, storms, or tropical nights (defined as nights where the daily minimum temperature does not fall below 20 ∘C), and these parameters appear to be sensitive to coupling. For the present-day climate, many coupled atmosphere–ocean and atmosphere–land surface models have demonstrated the added value of single climate variables, in particular when low-quality boundary data were used in the respective stand-alone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models to close the water cycle remains problematic, as the accuracy of precipitation provided by atmosphere models is, in most cases, insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments. Many regional stand-alone ocean and atmosphere models are tuned to suitably represent present-day climatologies rather than to accurately simulate climate change. Therefore, more research is required into how the regional climate sensitivity (e.g., the models' response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared with uncoupled ones.


2021 ◽  
Author(s):  
C. Dutheil ◽  
H. E. M. Meier ◽  
M. Gröger ◽  
F. Börgel

AbstractThe Baltic Sea is one of the fastest-warming semi-enclosed seas in the world over the last decades, yielding critical consequences on physical and biogeochemical conditions and on marine ecosystems. Although long-term trends in sea surface temperature (SST) have long been attributed to trends in air temperature, there are however, strong seasonal and sub-basin scale heterogeneities of similar magnitude than the average trend which are not fully explained. Here, using reconstructed atmospheric forcing fields for the period 1850–2008, oceanic climate simulations were performed and analyzed to identify areas of homogenous SST trends using spatial clustering. Our results show that the Baltic Sea can be divided into five different areas of homogeneous SST trends: the Bothnian Bay, the Bothnian Sea, the eastern and western Baltic proper, and the southwestern Baltic Sea. A classification tree and sensitivity experiments were carried out to analyze the main drivers behind the trends. While ice cover explains the seasonal north/south warming contrast, the changes in surface winds and air-sea temperature anomalies (along with changes in upwelling frequencies and heat fluxes) explain the SST trends differences between the sub-basins of the southern part of the Baltic Sea. To investigate future warming trends climate simulations were performed for the period 1976–2099 using two RCP scenarios. It was found that the seasonal north/south gradient of SST trends should be reduced in the future due to the vanishing of sea ice, while changes in the frequency of upwelling and heat fluxes explained the lower future east/west gradient of SST trend in fall. Finally, an ensemble of 48 climate change simulations has revealed that for a given RCP scenario the atmospheric forcing is the main source of uncertainty. Our results are useful to better understand the historical and future changes of SST in the Baltic Sea, but also in terms of marine ecosystem and public management, and could thus be used for planning sustainable coastal development.


2021 ◽  
Author(s):  
Vladimir S. Kostsov ◽  
Anke Kniffka ◽  
Dmitry V. Ionov

Abstract. Liquid water path (LWP) is one of the most important cloud parameters. The knowledge on LWP is critical for many studies including global and regional climate modelling, weather forecasting, modelling of hydrological cycle and interactions between different components of the climate system: the atmosphere, the hydrosphere, and the land surface. Satellite observations by the SEVIRI and AVHRR instruments have already provided the evidences of the systematic difference between the LWP values derived over the land surface and over the Baltic Sea and major lakes in Northern Europe during both cold and warm seasons. The goal of the present study is to analyse the phenomenon of the LWP horizontal inhomogeneities in the vicinity of various water bodies in Northern Europe making focus on the temporal and spatial variation of LWP. The objects of investigation are water bodies and water areas located in Northern Europe which are different in size and other characteristics: Gulf of Finland, Gulf of Riga, the Neva River bay, lakes Ladoga, Onega, Peipus, Pihkva, Ilmen, and Saimaa. The input data are the LWP values of pure liquid-phase clouds derived from the space-borne observations by the SEVIRI instrument in 2011–2017 during daytime. The study revealed that in general the mean values of the land-sea LWP gradient are positive during all seasons (larger values over land, smaller values over water surface). However, the negative gradients were also detected over several relatively small water bodies during cold (winter) season. The important finding is the positive trend of the land-sea LWP gradient detected within the time period 2011–2017. The analysis of intra-seasonal features revealed special conditions on the territory of the Gulf of Finland where in June and July large and moderate positive LWP gradients prevail over negative ones while in August positive and negative gradients are much smaller (in terms of absolute values) and occur with equal frequency. This result can lead to the conclusion about possible common physical mechanisms that drive the land-sea LWP difference in the Baltic Sea region at small distances from the coastline. The diurnal cycle of the LWP land-sea gradient has been detected in June and July while there was no evidence for it in August. For several specific cases, atmospheric parameters over the mesoscale domain comprising Gulf of Finland and several lakes have been simulated with the numerical model ICON in limited area and weather prediction mode. These simulations have clearly demonstrated the LWP land-sea gradient and have pointed out less stability of the atmosphere over land surfaces.


Author(s):  
Erik Kjellström ◽  
Ole Bøssing Christensen

Regional climate models (RCMs) are commonly used to provide detailed regional to local information for climate change assessments, impact studies, and work on climate change adaptation. The Baltic Sea region is well suited for RCM evaluation due to its complexity and good availability of observations. Evaluation of RCM performance over the Baltic Sea region suggests that: • Given appropriate boundary conditions, RCMs can reproduce many aspects of the climate in the Baltic Sea region. • High resolution improves the ability of RCMs to simulate significant processes in a realistic way. • When forced by global climate models (GCMs) with errors in their representation of the large-scale atmospheric circulation and/or sea surface conditions, performance of RCMs deteriorates. • Compared to GCMs, RCMs can add value on the regional scale, related to both the atmosphere and other parts of the climate system, such as the Baltic Sea, if appropriate coupled regional model systems are used. Future directions for regional climate modeling in the Baltic Sea region would involve testing and applying even more high-resolution, convection permitting, models to generally better represent climate features like heavy precipitation extremes. Also, phenomena more specific to the Baltic Sea region are expected to benefit from higher resolution (these include, for example, convective snowbands over the sea in winter). Continued work on better describing the fully coupled regional climate system involving the atmosphere and its interaction with the sea surface and land areas is also foreseen as beneficial. In this respect, atmospheric aerosols are important components that deserve more attention.


2019 ◽  
Author(s):  
Christian Dieterich ◽  
Matthias Gröger ◽  
Lars Arneborg ◽  
Helén C. Andersson

Abstract. An ensemble of regional climate change scenarios for the Baltic Sea is validated and analyzed with respect to extreme sea levels (ESLs) in the recent past. The ERA40 reanalysis and five Coupled Model Intercomparison Project Phase 5 (CMIP5) global general circulation models (GCMs) have been downscaled with the coupled atmosphere-ice-ocean model RCA4-NEMO. Validation of 100-year return levels against observational estimates along the Swedish coast shows that the model estimates are within the 95 % confidence limits for most stations, except those on the west coast. The ensemble mean 100-year return levels turns out to be the best estimator with biases of less than 10 cm. The ensemble spread includes the 100-year return levels based on observations. A series of sensitivity studies explores how the choice of different parameterizations, open boundary conditions and atmospheric forcing affects the estimates of 100-year return levels. A small ensemble of different regional climate models (RCMs) forced with ERA40 shows the highest uncertainty in ESLs in the southwestern Baltic Sea and in the northeastern part of the Bothnian Bay. Also the Skagerrak, Gulf of Finland and Gulf of Riga are sensitive to the choice of the RCM. A second ensemble of one RCM forced with different GCMs uncovers a lower sensitivity of ESLs against the variance introduced by different GCMs. The uncertainty in the estimates of 100-year return levels introduced by GCMs ranges from 20 cm to 40 cm at different stations. It is of similar size as the 95 % confidence limits of 100-year return levels from observational records.


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