Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

2021 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Data ◽  
Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2°C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.</p>

Urban-rural contrasts and extreme weather conditions in regional climate change projections across spatial and temporal scales

2020 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Climate Projections ◽  
Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2°C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales. </p>

Distribution-based scaling to improve usability of regional climate model projections for hydrological climate change impacts studies

2010 ◽  
Vol 41 (3-4) ◽  
pp. 211-229 ◽  
Author(s):  
Wei Yang ◽  
Johan Andréasson ◽  
L. Phil Graham ◽  
Jonas Olsson ◽  
Jörgen Rosberg ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Impact Studies ◽  
Emissions Scenarios ◽  
Precipitation And Temperature

As climate change could have considerable influence on hydrology and corresponding water management, appropriate climate change inputs should be used for assessing future impacts. Although the performance of regional climate models (RCMs) has improved over time, systematic model biases still constrain the direct use of RCM output for hydrological impact studies. To address this, a distribution-based scaling (DBS) approach was developed that adjusts precipitation and temperature from RCMs to better reflect observations. Statistical properties, such as daily mean, standard deviation, distribution and frequency of precipitation days, were much improved for control periods compared to direct RCM output. DBS-adjusted precipitation and temperature from two IPCC Special Report on Emissions Scenarios (SRESA1B) transient climate projections were used as inputs to the HBV hydrological model for several river basins in Sweden for the period 1961–2100. Hydrological results using DBS were compared to results with the widely-used delta change (DC) approach for impact studies. The general signal of a warmer and wetter climate was obtained using both approaches, but use of DBS identified differences between the two projections that were not seen with DC. The DBS approach is thought to better preserve the future variability produced by the RCM, improving usability for climate change impact studies.

scholarly journals Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change?

2017 ◽  
Vol 98 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
Nikolina Ban ◽  
Nigel M. Roberts ◽  
Hayley J. Fowler ◽  
Malcolm J. Roberts ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Convective Storms ◽  
Wide Range

Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.

scholarly journals Impacts of climate change on temperature, precipitation and hydrology in Finland – studies using bias corrected Regional Climate Model data

2015 ◽  
Vol 12 (3) ◽  
pp. 2657-2706 ◽  
Author(s):  
T. Olsson ◽  
J. Jakkila ◽  
N. Veijalainen ◽  
L. Backman ◽  
J. Kaurola ◽  
...  
Keyword(s):  
Climate Change ◽  
Seasonal Changes ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Catchment Scale ◽  
Temperature And Precipitation

Abstract. Assessment of climate change impacts on climate and hydrology on catchment scale requires reliable information about the average values and climate fluctuations of the past, present and future. Regional Climate Models (RCMs) used in impact studies often produce biased time series of meteorological variables. In this study bias correction of RCM temperature and precipitation for Finland is carried out using different versions of distribution based scaling (DBS) method. The DBS adjusted RCM data is used as input of a hydrological model to simulate changes in discharges in four study catchments in different parts of Finland. The annual mean discharges and seasonal variation simulated with the DBS adjusted temperature and precipitation data are sufficiently close to observed discharges in the control period (1961–2000) and produce more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data. Furthermore, with most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data during 1961–2100. However, if the biases in the mean or the SD of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections. The DBS method influences especially the projected seasonal changes in discharges and the use of uncorrected data can produce unrealistic seasonal discharges and changes. The projected changes in annual mean discharges are moderate or small, but seasonal distribution of discharges will change significantly.

scholarly journals Assessment of potential hydrological climate change impacts in Kastoria basin (Western Macedonia, Greece) using EUROCORDEX regional climate models

2021 ◽  
Keyword(s):  
Climate Change ◽  
Groundwater Level ◽  
Climate Models ◽  
Regional Climate ◽  
Substantial Reduction ◽  
Regional Climate Models ◽  
Water Yield ◽  
Climate Projections ◽  
Climate Data ◽  
Northern Greece

<p>The Mediterranean region is expected to present reduced availability of water resources due to climate change. This study aims to assess the potential hydrological responses to climate change in the Kastoria basin (Western Macedonia, Northern Greece) for the period 2019-2078. Climate projections from eight regional climate models from EURO-CORDEX were bias-adjusted using the linear scaling method. The bias-adjusted climate data were used to force the FeFLOW hydro-logical model to predict the discharge of the Kastoria aquifer towards lake Orestiada along with the projected groundwater level distribution. Precipitation (temperature) shows a tendency to decrease (increase) mainly in late spring to early autumn while increase (decrease) in the other sea-sons. Moreover, results indicate a significant increase in temperature and a slight decrease in precipitation towards 2078, while the predicted groundwater level of Kastoria aquifer will reduce slightly. However, the future hydrological behavior of the basin indicates a substantial reduction by approximately 15% of total water yield towards the end of the century.</p>

Supporting users to implement uncertainty of climate change information in adaptation studies

2020 ◽  
Author(s):  
Gabriella Zsebeházi ◽  
Beatrix Bán
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Web Portals ◽  
Climate Data ◽  
Adaptation Studies ◽  
Climate Services ◽  
Model Simulations

&lt;p&gt;There is a growing need to develop climate services both at national and international level, to bridge the gap between the providers and the end-users of climate information. Several national climate services are aiming to serve the local users&amp;#8217; needs by creating web portals. Thanks to this trend, the number of available climate data (both measured and modelled) is rapidly growing and often there is not any personal contact between the users and the climate scientists via the web portals. Therefore, it is important to make this service usable and informative and train the potential users about the nature, strengths and limits of climate data.&lt;/p&gt;&lt;p&gt;Within the framework of a national funded project (KlimAdat), the regional climate model projections of the Hungarian Meteorological Service are extended and a representative climate database is developed. Regular workshops are organised, where we get hands-on information about the requirements and give training about climate modelling in exchange. One of the most discussed issue during the workshops is tackling with uncertainty information of climate projections in climate change adaptation studies. The future changes are quantified in probabilistic form, applying ensemble technique, i.e. several climate model simulations prepared with different global and regional climate models and anthropogenic scenarios are evaluated simultaneously.&lt;/p&gt;&lt;p&gt;In order to help the users orienting through the mushrooming climate projections, a user guide is prepared. Topics are e.g. how to select model simulations, how to take into account model validation results and what is the difference between signal and noise. The guideline is based on 24 simulations of the 12-km resolution Euro-CORDEX regional climate models, driven by the RCP4.5 and RCP8.5 scenarios. Two target groups are distinguished based on the required level of post-processing climate data: 1) climate impact modellers, who need large amount of raw or bias corrected data to drive their own impact model; 2) decision makers and planners, who need heavily processed but lightweight data. The purpose of our guideline is to provide insight into the customized methodologies used at the Hungarian Meteorological Service for fulfilling users&amp;#8217; needs.&lt;/p&gt;

Assessment of climate change impacts in a semi-arid watershed in Iran using regional climate models

2014 ◽  
Vol 6 (1) ◽  
pp. 161-180 ◽  
Author(s):  
Hamid R. Solaymani ◽  
A. K. Gosain
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Assessment Tool ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Water Yield ◽  
Climate Data ◽  
Water Shortages ◽  
Semi Arid

This paper aims to summarize in detail the results of the climate models under various scenarios by temporal and spatial analysis in the semi-arid Karkheh Basin (KB) in Iran, which is likely to experience water shortages. The PRECIS and REMO models, under A2, B2 and A1B scenarios, have been chosen as regional climate models (RCMs). These regional climate models indicate an overall warming in future in KB under various scenarios. The increase in temperature in the dry months (June, July and August) is greater than the increase in the wet months (January, February, March and April). In order to perform climate change impact assessment on water resources, the Arc-SWAT 9.3 model was used in the study area. SWAT (Soil and Water Assessment Tool) model results have been obtained using present and future climate data. There is an overall reduction in the water yield (WYLD) over the whole of the KB. The deficit of WYLD is considerable over the months of April to September throughout KB due to the increase in average temperature and decrease in precipitation under various emission scenarios. Statistical properties in box-and-whisker plots have been used to gain further understanding relevant to uncertainty analysis in climate change impacts. Evaluation of uncertainty has shown the highest uncertain condition under B2.

scholarly journals Impacts of climate change on temperature, precipitation and hydrology in Finland – studies using bias corrected Regional Climate Model data

2015 ◽  
Vol 19 (7) ◽  
pp. 3217-3238 ◽  
Author(s):  
T. Olsson ◽  
J. Jakkila ◽  
N. Veijalainen ◽  
L. Backman ◽  
J. Kaurola ◽  
...  
Keyword(s):  
Climate Change ◽  
Seasonal Changes ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Catchment Scale ◽  
Temperature And Precipitation

Abstract. Assessment of climate change impacts on climate and hydrology on catchment scale requires reliable information about the average values and climate fluctuations of the past, present and future. Regional climate models (RCMs) used in impact studies often produce biased time series of meteorological variables. In this study bias correction (BC) of RCM temperature and precipitation for Finland is carried out using different versions of the distribution based scaling (DBS) method. The DBS-adjusted RCM data are used as input of a hydrological model to simulate changes in discharges of four study catchments in different parts of Finland. The annual mean discharges and seasonal variation simulated with the DBS-adjusted temperature and precipitation data are sufficiently close to observed discharges in the control period 1961–2000 and produce more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data. Furthermore, with most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data during 1961–2100. However, if the biases in the mean or the standard deviation of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections. The DBS method influences especially the projected seasonal changes in discharges and the use of uncorrected data can produce unrealistic seasonal discharges and changes. The projected changes in annual mean discharges are moderate or small, but seasonal distribution of discharges will change significantly.

scholarly journals On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff

2013 ◽  
Vol 17 (3) ◽  
pp. 1189-1204 ◽  
Author(s):  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
S. Ricard ◽  
J. A. Velázquez ◽  
J. Schmid ◽  
...  
Keyword(s):  
Climate Change ◽  
River Runoff ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Hydrological Models

Abstract. In climate change impact research, the assessment of future river runoff as well as the catchment-scale water balance is impeded by different sources of modeling uncertainty. Some research has already been done in order to quantify the uncertainty of climate projections originating from the climate models and the downscaling techniques, as well as from the internal variability evaluated from climate model member ensembles. Yet, the use of hydrological models adds another layer of uncertainty. Within the QBic3 project (Québec–Bavarian International Collaboration on Climate Change), the relative contributions to the overall uncertainty from the whole model chain (from global climate models to water management models) are investigated using an ensemble of multiple climate and hydrological models. Although there are many options to downscale global climate projections to the regional scale, recent impact studies tend to use regional climate models (RCMs). One reason for that is that the physical coherence between atmospheric and land-surface variables is preserved. The coherence between temperature and precipitation is of particular interest in hydrology. However, the regional climate model outputs often are biased compared to the observed climatology of a given region. Therefore, biases in those outputs are often corrected to facilitate the reproduction of historic runoff conditions when used in hydrological models, even if those corrections alter the relationship between temperature and precipitation. So, as bias correction may affect the consistency between RCM output variables, the use of correction techniques and even the use of (biased) climate model data itself is sometimes disputed among scientists. For these reasons, the effect of bias correction on simulated runoff regimes and the relative change in selected runoff indicators is explored. If it affects the conclusion of climate change analysis in hydrology, we should consider it as a source of uncertainty. If not, the application of bias correction methods is either unnecessary to obtain the change signal in hydro-climatic projections, or safe to use for the production of present and future river runoff scenarios as it does not alter the change signal. The results of the present paper highlight the analysis of daily runoff simulated with four different hydrological models in two natural-flow catchments, driven by different regional climate models for a reference and a future period. As expected, bias correction of climate model outputs is important for the reproduction of the runoff regime of the past, regardless of the hydrological model used. Then again, its impact on the relative change of flow indicators between reference and future periods is weak for most indicators, with the exception of the timing of the spring flood peak. Still, our results indicate that the impact of bias correction on runoff indicators increases with bias in the climate simulations.

scholarly journals Estimation of Climate-Change Impacts on the Urban Heat Load Using an Urban Climate Model and Regional Climate Projections

2011 ◽  
Vol 50 (1) ◽  
pp. 167-184 ◽  
Author(s):  
Barbara Früh ◽  
Paul Becker ◽  
Thomas Deutschländer ◽  
Johann-Dirk Hessel ◽  
Meinolf Kossmann ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Load ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Urban Climate ◽  
Regional Climate Models ◽  
Annual Number ◽  
Climate Projections ◽  
Urban Heat

Abstract A pragmatic approach to estimate the impact of climate change on the urban environment, here called the cuboid method, is presented. This method allows one to simulate the urban heat load and the frequency of air temperature threshold exceedances using only eight microscale urban climate simulations for each relevant wind direction and time series of daily meteorological parameters either from observations or regional climate projections. Eight representative simulations are designed to encompass all major potential urban heat-stress conditions. From these representative simulations, the urban-heat-load conditions in any weather situation are derived by interpolation. The presented approach is applied to study possible future heat load in Frankfurt, Germany, using the high-resolution Microscale Urban Climate Model in three dimensions (MUKLIMO_3). To estimate future changes in heat-load-related climate indices in Frankfurt, climate projections from the regional climate models Max Planck Institute Regional Model (REMO), Climate Limited-Area Model (CLM), Wetterlagen-basierte Regionalisierungsmethode (WETTREG), and Statistical Regional Model (STAR) are used. These regional climate models are driven by the “ECHAM5” general circulation model and Intergovernmental Panel on Climate Change emission scenario A1B. For the mean annual number of days with a maximum daily temperature exceeding 25°C, a comparison between the cuboid method results from observed and projected regional climate time series of the period 1971–2000 shows good agreement, except for CLM for which a clear underestimation is found. On the basis of the 90% significance level of all four regional climate models, the mean annual number of days with a maximum daily temperature exceeding 25°C in Frankfurt is expected to increase by 5–32 days for 2021–50 as compared with 1971–2000.

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