Sven Kotlarski

21st century climate change in the European Alps—A review☆

Reliable estimates of future climate change in the Alps are relevant for large parts of the European society. At the same time, the complex Alpine region poses considerable challenges to climate models, which translate to uncertainties in the climate projections. Against this background, the present study reviews the state-of-knowledge about 21st century climate change in the Alps based on existing literature and additional analyses. In particular, it explicitly considers the reliability and uncertainty of climate projections. Results show that besides Alpine temperatures, also precipitation, global radiation, relative humidity, and closely related impacts like floods, droughts, snow cover, and natural hazards will be affected by global warming. Under the A1B emission scenario, about 0.25 °C warming per decade until the mid of the 21st century and accelerated 0.36 °C warming per decade in the second half of the century is expected. Warming will probably be associated with changes in the seasonality of precipitation, global radiation, and relative humidity, and more intense precipitation extremes and flooding potential in the colder part of the year. The conditions of currently record breaking warm or hot winter or summer seasons, respectively, may become normal at the end of the 21st century, and there is indication for droughts to become more severe in the future. Snow cover is expected to drastically decrease below 1500-2000 m and natural hazards related to glacier and permafrost retreat are expected to become more frequent. Such changes in climatic parameters and related quantities will have considerable impact on ecosystems and society and will challenge their adaptive capabilities.

VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUEs main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

Calculating distributed glacier mass balance for the Swiss Alps from regional climate model output: A methodical description and interpretation of the results

[1] This study aims at giving a methodical description of the use of gridded output from a regional climate model (RCM) for the calculation of glacier mass balance distribution for the perimeter of the Swiss Alps. The mass balance model runs at daily steps and 100 m spatial resolution, while the regional model (REMO) RCM provides daily grids (� 18 km resolution) of dynamically downscaled reanalysis data. A combination of interpolation techniques and simple subgrid parameterizations is applied to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation, and precipitation. Interpolation schemes are a key element and thus we test different interpolators. For validation, computed mass balances are compared to stake measurements and time series (1979–2003) of observed mass balance. The meteorological input fields are compared to measurements at weather stations. The applied inverse distance weighting introduces systematic biases due to spatial autocorrelation, whereas thin plate splines preserve the characteristics of the RCM output. While summer melt at point locations on several glaciers is well reproduced by the model, accumulation is mostly underestimated. These systematic shifts are correlated to biases of the meteorological input fields. Time series of mass balance obtained from the model run agree well with observed time series. We conclude that the gap in spatial resolution is not a major drawback, given that interpolators and parameterizations are selected upon detailed considerations. Biases in RCM precipitation are a major source for the observed underestimations in mass balance and have to be corrected prior to operational use of the presented approach.

Exploring Perturbed Physics Ensembles in a Regional Climate Model

AbstractPerturbed physics ensembles (PPEs) have been widely used to assess climate model uncertainties and have provided new estimates of climate sensitivity and parametric uncertainty in state-of-the-art climate models. So far, mainly global climate models were used to generate PPEs, and little work has been conducted with regional climate models. This paper discusses the parameter uncertainty in two PPEs of a regional climate model driven by reanalysis data for the present climate over Europe. The uncertainty is evaluated for the variables of 2-m temperature, precipitation, and total cloud cover, with a focus on the annual cycle, interannual variability, and selected extremes.The authors show that the simulated spread of the PPEs encompasses the observations at a regional scale in terms of the annual cycle and the interannual variability, provided observational uncertainty is taken into account. To rank the PPEs a new skill metric is proposed, which takes into account observational uncertainty and natur...

The impact of climate change on photovoltaic power generation in Europe

Ambitious climate change mitigation plans call for a significant increase in the use of renewables, which could, however, make the supply system more vulnerable to climate variability and changes. Here we evaluate climate change impacts on solar photovoltaic (PV) power in Europe using the recent EURO-CORDEX ensemble of high-resolution climate projections together with a PV power production model and assuming a well-developed European PV power fleet. Results indicate that the alteration of solar PV supply by the end of this century compared with the estimations made under current climate conditions should be in the range (−14%;+2%), with the largest decreases in Northern countries. Temporal stability of power generation does not appear as strongly affected in future climate scenarios either, even showing a slight positive trend in Southern countries. Therefore, despite small decreases in production expected in some parts of Europe, climate change is unlikely to threaten the European PV sector.

Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part I: Climate Model Evaluation

A coupling interface between the regional climate model REMO and a distributed glacier mass balance model is presented in a series of two papers. The first part describes and evaluates the reanalysis-driven regional climate simulation that is used to force a mass balance model for two glaciers of the Swiss mass balance network. The detailed validation of near-surface air temperature, precipitation, and global radiation for the European Alps shows that the basic spatial and temporal patterns of all three parameters are reproduced by REMO. Compared to the Climatic Research Unit (CRU) dataset, the Alpine mean temperature is underestimated by 0.348C. Annual precipitation shows a positive bias of 17% (30%) with respect to the uncorrected gridded ALP-IMP (CRU) dataset. A number of important and systematic model biases arise in high-elevation regions, namely, a negative temperature bias in winter, a bias of seasonal precipitation (positive or negative, depending on gridbox altitude and season), and an underestimation of springtime and overestimation of summertime global radiation. These can be expected to have a strong effect on the simulated glacier mass balance. It is recommended to account for these shortcomings by applying correction procedures before using the RCM output for subsequent mass balance modeling. Despite the obvious model deficiencies in high-elevation regions, the new interface broadens the scope of application of glacier mass balance models and will allow for a straightforward assessment of future climate change impacts.

Response of Karakoram-Himalayan glaciers to climate variability and climatic change: A regional climate model assessment

The Karakoram and the Himalayan mountain range accommodate a large number of glaciers and are the major source of several perennial rivers downstream. To interactively describe to response of glaciers to climate change, a glacier parameterization scheme has been developed and implemented into the regional climate model REMO. The scheme simulates the mass balance as well as changes of the areal extent of glaciers on a subgrid scale. The parameterization scheme is for the first time applied to the region. A regional glacier inventory is compiled and is used to initialize glacier area and volume. Over the highly complex and data sparse region, the simulated mass balance largely agrees with observations including the positive Karakoram anomaly. The simulated equilibrium line altitude is well captured although a systematic underestimation is apparent. REMO simulates the glacier-climate interaction reasonably well; it has clear potential to be used for future climate assessments.

Climate change impacts on the power generation potential of a European mid-century wind farms scenario

Wind energy resource is subject to changes in climate. To investigate the impacts of climate change on future European wind power generation potential, we analyze a multi-model ensemble of the most recent EURO-CORDEX regional climate simulations at the 12 km grid resolution. We developed a mid-century wind power plant scenario to focus the impact assessment on relevant locations for future wind power industry. We found that, under two greenhouse gas concentration scenarios, changes in the annual energy yield of the future European wind farms fleet as a whole will remain within ±5% across the 21st century. At country to local scales, wind farm yields will undergo changes up to 15% in magnitude, according to the large majority of models, but smaller than 5% in magnitude for most regions and models. The southern fleets such as the Iberian and Italian fleets are likely to be the most affected. With regard to variability, changes are essentially small or poorly significant from subdaily to interannual time scales.

Does Quantile Mapping of Simulated Precipitation Correct for Biases in Transition Probabilities and Spell Lengths

AbstractClimate impact studies constitute the basis for the formulation of adaptation strategies. Usually such assessments apply statistically postprocessed output of climate model projections to force impact models. Increasingly, time series with daily resolution are used, which require high consistency, for instance with respect to transition probabilities (TPs) between wet and dry days and spell durations. However, both climate models and commonly applied statistical tools have considerable uncertainties and drawbacks. This paper compares the ability of 1) raw regional climate model (RCM) output, 2) bias-corrected RCM output, and 3) a conventional weather generator (WG) that has been calibrated to match observed TPs to simulate the sequence of dry, wet, and very wet days at a set of long-term weather stations across Switzerland. The study finds systematic biases in TPs and spell lengths for raw RCM output, but a substantial improvement after bias correction using the deterministic quantile mapping tech...

Separating climate change signals into thermodynamic, lapse-rate and circulation effects: theory and application to the European summer climate

Climate models robustly project a strong overall summer warming across Europe showing a characteristic north-south gradient with enhanced warming and drying in southern Europe. However, the processes that are responsible for this pattern are not fully understood. We here employ an extended surrogate or pseudo-warming approach to disentangle the contribution of different mechanisms to this response pattern. The basic idea of the surrogate technique is to use a regional climate model and apply a large-scale warming to the lateral boundary conditions of a present-day reference simulation, while maintaining the relative humidity (and thus implicitly increasing the specific moisture content). In comparison to previous studies, our approach includes two important extensions: first, different vertical warming profiles are applied in order to separate the effects of a mean warming from lapse-rate effects. Second, a twin-design is used, in which the climate change signals are not only added to present-day conditions, but also subtracted from a scenario experiment. We demonstrate that these extensions provide an elegant way to separate the full climate change signal into contributions from large-scale thermodynamic (TD), lapse-rate (LR), and circulation and other remaining effects (CO). The latter in particular include changes in land-ocean contrast and spatial variations of the SST warming patterns. We find that the TD effect yields a large-scale warming across Europe with no distinct latitudinal gradient. The LR effect, which is quantified for the first time in our study, leads to a stronger warming and some drying in southern Europe. It explains about 50 % of the warming amplification over the Iberian Peninsula, thus demonstrating the important role of lapse-rate changes. The effect is linked to an extending Hadley circulation. The CO effect as inherited from the driving GCM is shown to further amplify the north-south temperature change gradient. In terms of mean summer precipitation the TD effect leads to a significant overall increase in precipitation all across Europe, which is compensated and regionally reversed by the LR and CO effects in particular in southern Europe.