scholarly journals Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods

2012 ◽  
Vol 16 (9) ◽  
pp. 3383-3390 ◽  
Author(s):  
L. Gudmundsson ◽  
J. B. Bremnes ◽  
J. E. Haugen ◽  
T. Engen-Skaugen
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Local Scale ◽  
Technical Note ◽  
Post Processing ◽  
Real World Application ◽  
Systematic Biases ◽  
The Impact ◽  
Selection Of

Abstract. The impact of climate change on water resources is usually assessed at the local scale. However, regional climate models (RCMs) are known to exhibit systematic biases in precipitation. Hence, RCM simulations need to be post-processed in order to produce reliable estimates of local scale climate. Popular post-processing approaches are based on statistical transformations, which attempt to adjust the distribution of modelled data such that it closely resembles the observed climatology. However, the diversity of suggested methods renders the selection of optimal techniques difficult and therefore there is a need for clarification. In this paper, statistical transformations for post-processing RCM output are reviewed and classified into (1) distribution derived transformations, (2) parametric transformations and (3) nonparametric transformations, each differing with respect to their underlying assumptions. A real world application, using observations of 82 precipitation stations in Norway, showed that nonparametric transformations have the highest skill in systematically reducing biases in RCM precipitation.

scholarly journals Technical Note: Downscaling RCM precipitation to the station scale using quantile mapping – a comparison of methods

2012 ◽  
Vol 9 (5) ◽  
pp. 6185-6201 ◽  
Author(s):  
L. Gudmundsson ◽  
J. B. Bremnes ◽  
J. E. Haugen ◽  
T. Engen Skaugen
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Local Scale ◽  
Technical Note ◽  
Quantile Mapping ◽  
Real World Application ◽  
Systematic Biases ◽  
The Impact ◽  
Selection Of

Abstract. The impact of climate change on water resources is usually assessed at the local scale. However, regional climate models (RCM) are known to exhibit systematic biases in precipitation. Hence, RCM simulations need to be post-processed in order to produce reliable estimators of local scale climate. A popular post-processing approach is quantile mapping (QM), which is designed to adjust the distribution of modeled data, such that it matches observed climatologies. However, the diversity of suggested QM methods renders the selection of optimal techniques difficult and hence there is a need for clarification. In this paper, QM methods are reviewed and classified into: (1) distribution derived transformations, (2) parametric transformations and (3) nonparametric transformations; each differing with respect to their underlying assumptions. A real world application, using observations of 82 precipitation stations in Norway, showed that nonparametric transformations have the highest skill in systematically reducing biases in RCM precipitation.

Hydrological simulations in the Rhine basin

2005 ◽  
Vol 51 (5) ◽  
pp. 1-4
Author(s):  
B. van den Hurk ◽  
J. Beersma ◽  
G. Lenderink
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Rhine River ◽  
Rhine Basin ◽  
The Impact ◽  
Selection Of

Simulations with regional climate models (RCMs), carried out for the Rhine basin, have been analyzed in the context of implications of the possible future discharge of the Rhine river. In a first analysis, the runoff generated by the RCMs is compared to observations, in order to detect the way the RCMs treat anomalies in precipitation in their land surface component. A second analysis is devoted to the frequency distribution of area averaged precipitation, and the impact of selection of various driving global climate models.

Evaluating the effect of climate change on snow load on structures

2019 ◽  
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi ◽  
Francesca Marsili
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Extremes ◽  
Regional Climate Models ◽  
Extreme Weather Events ◽  
Uncertainty Range ◽  
Greenhouse Gasses ◽  
Weather Events ◽  
The Impact

<p>As consequence of global warming extreme weather events might become more frequent and severe across the globe. The evaluation of the impact of climate change on extremes is then a crucial issue for the resilience of infrastructures and buildings and is a key challenge for adaptation planning. In this paper, a suitable procedure for the estimation of future trends of climatic actions is presented starting from the output of regional climate models and taking into account the uncertainty in the model itself. In particular, the influence of climate change on ground snow loads is discussed in detail and the typical uncertainty range is determined applying an innovative algorithm for weather generation. Considering different greenhouse gasses emission scenarios, some results are presented for the Italian Mediterranean region proving the ability of the method to define factors of change for climate extremes also allowing a sound estimate of the uncertainty range associated with different models.</p>

NUKLEUS - User-relevant and applicable kilometer-scale climate information for Germany

2021 ◽  
Author(s):  
Kevin Sieck ◽  
Bente Tiedje ◽  
Hendrik Feldmann ◽  
Joaquim Pinto
Keyword(s):  
Climate Models ◽  
Local Scale ◽  
Easy Access ◽  
Climate Information ◽  
Post Processing ◽  
Last Mile ◽  
Wide Range ◽  
Impact Modelling ◽  
The Impact ◽  
Impact Models

&lt;p&gt;Given the current developments in climate science it becomes more a more feasible to provide climate information at the kilometer-scale from convection-permitting climate simulations. This progress will enable many users to directly feed high-resolution climate information into their impact-models for climate impact studies at the local scale. Examples include urban heat stress at street level or the design of drainage systems for future precipitation extremes. Within the RegIKlim (Regional information for action on climate change) consortium, the NUKLEUS (Actionable local climate information for Germany) project will not only provide climate information at the local scale, but also to co-develop interfaces between climate and impact models, in order to fulfil the needs of the impact modelling community as good as possible. Within the RegIKlim consortium, the impact modelling community is organised in six &amp;#8220;model regions&amp;#8221; across Germany, which cover a wide range of geographical and socio-economic conditions.&lt;/p&gt;&lt;p&gt;For the NUKLEUS project, the baseline will be the latest generation of EURO-CORDEX downscaled CMIP6 simulations, which will be further refined to roughly 3&amp;#160;km horizontal resolution and 30-year time-slices for Germany with convection-permitting climate models (ICON CLM, COSMO-CLM, REMO-NH) and statistical-dynamical downscaling approaches. A detailed analysis on the performance of the multi-model mini-ensemble is planned to assess the quality of the provided data. At the interface to the users, we will follow three different approaches to provide usable climate information at the kilometer-scale. One is to provide easy-access to data and post-processing opportunities using the FREVA system. FREVA offers various access-levels from shell to web-based, which serves different levels of user-expertise. In addition, it provides a transparent way of post-processing data by workflow sharing mechanisms. The second one is to develop appropriate additional downscaling methods for the &amp;#8220;last mile&amp;#8221; where needed. For this &amp;#8220;last mile&amp;#8221;, we will apply dynamical and statistical methods such as urban climate models and/or weather generators. With the third approach we explicitly aim at integrating a collected user-feedback into the regional modelling systems used within NUKLEUS. Specifically, we intend to identify and incorporate data processing that is best done during the simulation permanently into the models. Examples are wind speeds at rotor heights of windmills or high frequency precipitation sums. NUKLEUS is a contribution to the German research program RegIKlim funded by the Federal Ministry of Education and Research (BMBF).&lt;/p&gt;

Changes in extreme surface solar radiation in EURO-CORDEX Regional Climate Models

2021 ◽  
Author(s):  
Blanka Bartok
Keyword(s):  
Climate Change ◽  
Power Generation ◽  
Solar Radiation ◽  
Solar Energy ◽  
Electricity Generation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Surface Solar Radiation ◽  
The Impact

&lt;p&gt;As solar energy share is showing a significant growth in the European electricity generation system, assessments regarding long-term variation of this variable related to climate change are becoming more and more relevant for this sector. Several studies analysed the impact of climate change on the solar energy sector in Europe (Jerez et al, 2015) finding light impact (-14%; +2%) in terms of mean surface solar radiation. The present study focuses on extreme values, namely on the distribution of low surface solar radiation (overcast situation) and high surface solar radiation (clear sky situation), since the frequencies of these situations have high impact on electricity generation.&lt;/p&gt;&lt;p&gt;The study considers 11 high-resolution (0.11 deg) bias-corrected climate projections from the EURO-CORDEX ensemble with 5 Global Climate Models (GCMs) downscaled by 6 Regional Climate Models (RCMs).&lt;/p&gt;&lt;p&gt;Changes in extreme surface solar radiation frequencies show different regional patterns over Europe.&lt;/p&gt;&lt;p&gt;The study also includes a case study determining the changes in solar power generation induced by the extreme situations.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Jerez et al (2015): The impact of climate change on photovoltaic power generation in Europe, Nature Communications 6(1):10014, 10.1038/ncomms10014&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals The impact of RCM formulation and resolution on simulated precipitation in Africa

2019 ◽  
Author(s):  
Minchao Wu ◽  
Grigory Nikulin ◽  
Erik Kjellström ◽  
Danijel Belušić ◽  
Colin Jones ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Added Value ◽  
Primary Control ◽  
Model Formulation ◽  
Simulated Precipitation ◽  
Mean Climate ◽  
The Impact

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs – SMHI-RCA4 and HCLIM38-ALADIN are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100 and 200 km. Additionally to the two RCMs, two different configurations of the same RCA4 are used. Contrasting different RCMs, configurations and resolutions it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle is completely controlled by model formulation (convection scheme) while its amplitude is a function of resolution. Although higher resolution in many cases leads to smaller biases in the time mean climate, the impact of higher resolution is mixed. An improvement in one region/season (e.g. reduction of dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). The experiments confirm a pronounced and well known impact of higher resolution – a more realistic distribution of daily precipitation. Even if the time-mean climate is not always greatly sensitive to resolution, what the time-mean climate is made up of, higher order statistics, is sensitive. Therefore, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and in general cannot be considered as an added value of downscaling.

scholarly journals The Impact of Climate Change on Material Degradation Criteria in Heritage over Iran: Regional Climate Model Evaluation

2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Salt Crystallization ◽  
Climate Modelling ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
The Impact

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.

scholarly journals Chilling accumulation in fruit trees in Spain under climate change

2019 ◽  
Vol 19 (5) ◽  
pp. 1087-1103 ◽  
Author(s):  
Alfredo Rodríguez ◽  
David Pérez-López ◽  
Enrique Sánchez ◽  
Ana Centeno ◽  
Iñigo Gómara ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Fruit Trees ◽  
Calculation Model ◽  
Cold Temperatures ◽  
Tree Crops ◽  
Chilling Requirements ◽  
The Impact

Abstract. Growing trees are quite vulnerable to cold temperatures. To minimise the effect of these cold temperatures, they stop their growth over the coldest months of the year, a state called dormancy. In particular, endodormancy requires accumulating chilling temperatures to finish this sort of dormancy. The accumulation of cool temperatures according to specific rules is called chilling accumulation, and each tree species and variety has specific chilling requirements for correct plant development. Under global warming, it is expected that the fulfilment of the chilling requirements to break dormancy in fruit trees could be compromised. In this study, the impact of climate change on the chilling accumulation over peninsular Spain and the Balearic Islands was assessed. For this purpose, bias-adjusted results of 10 regional climate models (RCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5 were used as inputs of four different models for calculating chilling accumulation, and the results for each model were individually compared for the 2021–2050 and 2071–2100 future periods under both RCPs. These results project a generalised reduction in chilling accumulation regardless of the RCP, future period or chilling calculation model used, with higher reductions for the 2071–2100 period and the RCP8.5 scenario. The projected winter chill decrease may threaten the viability of some tree crops and varieties in some areas where the crop is currently grown, but also shows scope for varieties with lower chilling requirements. The results are relevant for planning future tree plantations under climate change, supporting adaptation of spatial distribution of tree crops and varieties in Spain.

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