Representative climate projections for the North Sea and Baltic Sea

Author(s):  
Christian Dieterich ◽  
Matthias Gröger ◽  
Anders Höglund ◽  
Renate A. I. Wilcke ◽  
H. E. Markus Meier

<p>Robust estimations of uncertainty for climate projections on the regional scale are highly needed but are still challenging. Regional climate projections rely on downscaling global climate scenarios. Typically, a number of different global climate models are downscaled to assess the inherent model uncertainty. The more models, the more robust the estimate of model uncertainty. However, this strategy is time consuming and so ensembles of regional projections are usually smaller than ensembles of global projections which can lead to an underestimation of regional uncertainty. With an increasing number of available global projections regional downscaling becomes increasingly expensive. We use a regional ensemble of coupled atmosphere-ice-ocean scenarios and a ensemble of ocean-ecosystem scenarios for the Baltic Sea to explore the effect of model selection on the representation of model uncertainty. Using a number of climate indices to characterize the regional system we apply a model selection that is representative of the original ensemble in terms of ensemble spread. We use existing algorithms to generate orthogonal patterns of climate change for the Baltic Sea. A small number of patterns is used to represent the climate change and its uncertainty in physical and biogeochemical parameters of the Baltic Sea. We show that climate change signals in atmosphere, ocean and ecosystem are coherent and that atmospheric or oceanic indices can be used to select global climate models for an ensemble of representative regional ecosystem scenarios for the Baltic Sea. Since the atmospheric climate in the regional climate model is close to its representation in the global climate model that latter can be used to perform an initial model selection.</p>

2021 ◽  
Author(s):  
Ole B. Christensen ◽  
Erik Kjellström ◽  
Christian Dieterich ◽  
Matthias Gröger ◽  
H. E. Markus Meier

Abstract. The Baltic Sea Region is very sensitive to climate change; it is a region with spatially varying climate and diverse ecosystems, but also under pressure due to high population in large parts of the area. Climate change impacts could easily exacerbate other anthropogenic stressors such as biodiversity stress from society and eutrophication of the Baltic Sea considerably. Therefore, there has been a focus on estimations of future climate change and its impacts in recent research. In this review paper, we will concentrate on a presentation of recent climate projections from both atmosphere-only and coupled atmosphere-ocean regional climate models. The recent regional climate model projections strengthen the picture from previous assessments. This includes a strong warming, in particular in the north in winter. Precipitation is projected to increase in the whole region apart from the southern half during summer. Consequently, the new results lend more credibility to estimates of uncertainties and robust features of future climate change. Furthermore, the larger number of scenarios gives opportunities to better address impacts of mitigation measures. The coupled atmosphere-ocean model locally modifies the climate change signal relative to that in the stand-alone atmosphere regional climate model. Differences are largest in areas where the coupled system arrives at different sea-surface temperatures and sea-ice conditions.


2019 ◽  
Vol 6 ◽  
Author(s):  
Sofia Saraiva ◽  
H. E. Markus Meier ◽  
Helén Andersson ◽  
Anders Höglund ◽  
Christian Dieterich ◽  
...  

2016 ◽  
Vol 11 (2) ◽  
pp. 670-678 ◽  
Author(s):  
N. S Vithlani ◽  
H. D Rank

For the future projections Global climate models (GCMs) enable development of climate projections and relate greenhouse gas forcing to future potential climate states. When focusing it on smaller scales it exhibit some limitations to overcome this problem, regional climate models (RCMs) and other downscaling methods have been developed. To ensure statistics of the downscaled output matched the corresponding statistics of the observed data, bias correction was used. Quantify future changes of climate extremes were analyzed, based on these downscaled data from two RCMs grid points. Subset of indices and models, results of bias corrected model output and raw for the present day climate were compared with observation, which demonstrated that bias correction is important for RCM outputs. Bias correction directed agreements of extreme climate indices for future climate it does not correct for lag inverse autocorrelation and fraction of wet and dry days. But, it was observed that adjusting both the biases in the mean and variability, relatively simple non-linear correction, leads to better reproduction of observed extreme daily and multi-daily precipitation amounts. Due to climate change temperature and precipitation will increased day by day.


Author(s):  
Ole Bøssing Christensen ◽  
Erik Kjellström

The ecosystems and the societies of the Baltic Sea region are quite sensitive to fluctuations in climate, and therefore it is expected that anthropogenic climate change will affect the region considerably. With numerical climate models, a large amount of projections of meteorological variables affected by anthropogenic climate change have been performed in the Baltic Sea region for periods reaching the end of this century.Existing global and regional climate model studies suggest that:• The future Baltic climate will get warmer, mostly so in winter. Changes increase with time or increasing emissions of greenhouse gases. There is a large spread between different models, but they all project warming. In the northern part of the region, temperature change will be higher than the global average warming.• Daily minimum temperatures will increase more than average temperature, particularly in winter.• Future average precipitation amounts will be larger than today. The relative increase is largest in winter. In summer, increases in the far north and decreases in the south are seen in most simulations. In the intermediate region, the sign of change is uncertain.• Precipitation extremes are expected to increase, though with a higher degree of uncertainty in magnitude compared to projected changes in temperature extremes.• Future changes in wind speed are highly dependent on changes in the large-scale circulation simulated by global climate models (GCMs). The results do not all agree, and it is not possible to assess whether there will be a general increase or decrease in wind speed in the future.• Only very small high-altitude mountain areas in a few simulations are projected to experience a reduction in winter snow amount of less than 50%. The southern half of the Baltic Sea region is projected to experience significant reductions in snow amount, with median reductions of around 75%.


2018 ◽  
Vol 56 (6) ◽  
pp. 732
Author(s):  
Anh Thi Van Vu ◽  
Thuc Tran ◽  
Minh Truong Ha ◽  
Lanh Thi Minh Pham

A top-down approach begins with Global Climate Models (GCMs) is a common method for assessing climate change impacts on water resources in river basins. To overcome the coarse resolution of GCMs, dynamic downscaling by regional climate models (RCMs) with bias-correction procedures is utilized with the aim to reflect the meteorological features at the river basin scale. However, the results still entail large uncertainties. This paper examines the ability to capture the observed baseline temperature and precipitation (1986-2005) in the Ba River Basin from GCM outputs, RCM outputs, bias-corrected GCM outputs and bias-corrected RCM outputs by analyzing statistical indicators between historical simulations and observed data in 4 temperature and 6 rainfall stations. Bias-corrected results of both GCM and RCM have significantly smaller errors compared to the unbias-corrected ones. The uncertainty of future climate projection for the mid and late 21th century of the bias-corrected GCMs and RCMs are evaluated. It is found that there is still uncertainty in projected results. A concept of “Decision-Scaling” which combines top-down and bottom-up approaches is proposed to assess the climate change impacts on hydrological system to take into account uncertainties of climate projections by models.


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