A5066470371- Hydrology and Watershed Management Studies
- Climate variability and models
- Meteorological Phenomena and Simulations
- Hydrology and Drought Analysis
- Cryospheric studies and observations
- demographic modeling and climate adaptation
- Flood Risk Assessment and Management
- Hydrological Forecasting Using AI
- Physics and Engineering Research Articles
- Atmospheric and Environmental Gas Dynamics
- Climate change and permafrost
- Water resources management and optimization
- Geophysics and Gravity Measurements
- Climate change impacts on agriculture
- Climate Change Policy and Economics
- Peatlands and Wetlands Ecology
- Soil and Water Nutrient Dynamics
- Plant Water Relations and Carbon Dynamics
- Advanced Mathematical Modeling in Engineering
- Water-Energy-Food Nexus Studies
- Environmental and Agricultural Sciences
- Aquatic and Environmental Studies
- Fire effects on ecosystems
- Hydrology and Sediment Transport Processes
- Landslides and related hazards
Swedish Meteorological and Hydrological Institute
2015-2024
ETH Zurich
2008-2013
Key Points ANOVA method applied to climate‐impact modeling Detailed assessment of changes in water balance quantities due climate change Interactions uncertainty sources
VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.). Here we describe the participating methods and first results from experiment, using “perfect” reanalysis (and reanalysis‐driven regional model (RCM)) predictors assess intrinsic performance of precipitation temperatures over a set 86 stations representative main climatic regions in...
The influence of uncertainties in gridded observational reference data on regional climate model (RCM) evaluation is quantified a pan‐European scale. Three different sets are considered: the coarse‐resolved E‐OBS set, compilation high‐resolution products (HR) and European‐scale MESAN reanalysis. Five ERA‐Interim‐driven RCM experiments EURO‐CORDEX initiative evaluated against each these references over eight European sub‐regions considering range performance metrics for mean daily temperature...
Abstract. The annual cycle of temperature and precipitation changes as projected by climate models is fundamental interest in impact studies. Its estimation, however, impaired natural variability. Using a simple form the delta change method, we show that on regional scales relevant for hydrological models, are prone to sampling artefacts. For at station locations, these artefacts may have amplitudes comparable signal itself. Therefore, should be filtered when generating scenarios. We test...
Abstract Recent technological advances in representation of processes numerical climate models have led to skillful predictions, which can consequently increase the confidence hydrological predictions and usability hydroclimatic services. Given that many water‐related stakeholders are affected by seasonal variations, there is a need manage such variations their advantage through better understanding drivers influence predictability. Here we analyze forecasts streamflow volumes across about...
The spatial dependence of meteorological variables is crucial for many impacts, example, droughts, floods, river flows, energy demand, and crop yield. There thus a need to understand how well it represented in downscaling (DS) products. Within the COST Action VALUE, we have conducted comprehensive analysis variability output over 40 different DS methods perfect predictor setup. evaluated against daily precipitation temperature observations period 1979–2008 at 86 sites across Europe 53...
To meet the European Union's 2050 climate neutrality target, future electricity generation is expected to largely rely on variable renewable energy (VRE). VRE supply, being dependant weather, susceptible changing conditions. Based spatiotemporally explicit data under a Paris-proof scenario and comprehensive conversion model, this study assesses projected changes of supply from perspective average production, production variability, spatiotemporal complementarity, risk concurrent droughts....
The study is carried out for Mumbai (18°58′30″ N, 72°49′33″ E). Future projections provided by general circulation models (GCMs) suggest the probability of occurrence intense rainfall will change in future. However, GCM data generally need to be downscaled and bias-corrected impact studies. Although domains covered Regional Climate Models (RCMs) are increasing, statistical downscaling results main alternative many regions. We applied a Distribution-based Scaling (DBS) procedure, with...
Abstract. As the risk of a forest fire is largely influenced by weather, evaluating its tendency under changing climate becomes important for management and decision making. Currently, biases in models make it difficult to realistically estimate future consequent impact on risk. A distribution-based scaling (DBS) approach was developed as post-processing tool that intends correct systematic modelling outputs. In this study, we used two projections, one driven historical reanalysis (ERA40)...
Abstract Climate change is expected to affect the hydrological cycle, with considerable impacts on water resources. Climate-induced changes in hydrology of Rhine River (Europe) are major importance for riparian countries, as most important European waterway, serves a freshwater supply source, and prone floods droughts. Here regional climate model data from Ensemble-Based Predictions Changes their Impacts (ENSEMBLES) project used drive Precipitation–Runoff–Evapotranspiration–Hydrotope...
In this paper, the ability of two joint bias correction algorithms to adjust biases in daily mean temperature and precipitation is compared against univariate quantile mapping methods when constructing projections from years 1981–2010 early (2011–2040) late (2061–2090) 21st century periods. Using both climate model simulations corresponding hydrological as proxies for future a pseudo-reality framework, these are inter-compared cross-validation manner order assess what extent more...
The impact of climate change on the hydro-climatology Indian subcontinent is investigated by comparing statistics current and projected future fluxes resulting from three RCP scenarios (RCP2.6, RCP4.5, RCP8.5). Climate projections CORDEX-South Asia framework have been bias-corrected using Distribution-Based Scaling (DBS) method used to force HYPE hydrological model generate evapotranspiration, runoff, soil moisture deficit, snow depth, applied irrigation water soil. We also assess changes in...
Uncertainties in hydro-climatic projections are (in part) related to various components of the production chain. An ensemble numerous is usually considered characterize overall uncertainty; however practice a small set scenario combinations constructed provide users with subset that manageable for decision-making. Since unavoidably uncertain, and multiple typically informationally redundant considerable extent, it would be helpful identify an representative large model ensemble. Here...
Hydrological forecasting is one of the most essential tasks in operational hydrology; however, predictions are usually subject to several sources uncertainty (both epistemic and aleatory). These uncertainties can be due to, for example, inadequacies model structure and/or parameters, forcing data, initial conditions updating procedures. Here, we analyse medium-scale (10 days) hydrological forecasts across 71 selected indicator stations Sweden aim identify typical production chain ways reduce...
Abstract. Bias adjustment is the practice of statistically transforming climate model data in order to reduce systematic deviations from a reference set, typically some sort observations. There are numerous proposed methodologies perform adjustments – ranging simple scaling approaches advanced multi-variate distribution-based mapping. In practice, actual bias method small step application, and most processing handles reading, writing, linking different sets. These practical steps become...
Lack of suitable observational data makes bias correction high space and time resolution regional climate models (RCM) problematic. We present a method to construct pseudo-observational precipitation bymerging large scale constrained RCMreanalysis downscaling simulation with coarse observations. The constraint synchronizes the inner domain solution driving reanalysis model, such that simulated weather is similar observations on monthly scale. Monthly biases for each single month are...
The next generation of climate services needs not only tailoring to specific user but provide, in addition, access key information a usable way that satisfies the different users’ profiles; especially web-based services. Here, we present outcomes from developing such new interactive prototype. service provides data for robust analysis underpin decision-making when planning measures compensate impact. goal is facilitate communication on between modelling communities and adaptation or...
Abstract. The annual cycle of temperature and precipitation changes as projected by climate models is fundamental interest in impact studies. Its estimation, however, impaired natural variability. Using a simple form the delta change method, we show that on regional scales relevant for hydrological models, are prone to sampling artefacts. For at station locations, these artefacts may have amplitudes comparable signal itself. Therefore, should be filtered when generating scenarios. We test...
Coupled glacio-hydrological models have recently become a valuable method for predicting the hydrological response of catchments in mountainous regions under changing climate. While focus mostly on processes non-glacierized part catchment with relatively simple glacier representation, latest generation standalone (global) tend to describe more accurately by using new global datasets and explicitly modeling ice-flow dynamics. Yet, authors' knowledge, existing catchment-scale coupled either do...