High-resolution dynamical downscaling for regional climate projection in Central Asia based on bias-corrected multiple GCMs

2021 ◽  
Author(s):  
Yuan Qiu ◽  
Jinming Feng ◽  
Zhongwei Yan ◽  
Jun Wang ◽  
Zhen Li
Keyword(s):  
High Resolution ◽  
Central Asia ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Climate Projection ◽  
Regional Climate Projection

scholarly journals Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22° resolution over the CORDEX Central Asia domain

2021 ◽  
Vol 14 (3) ◽  
pp. 1267-1293
Author(s):  
Sara Top ◽  
Lola Kotova ◽  
Lesley De Cruz ◽  
Svetlana Aniskevich ◽  
Leonid Bobylev ◽  
...  
Keyword(s):  
High Resolution ◽  
Central Asia ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Maximum Temperature ◽  
The Tibetan Plateau ◽  
Climate Information ◽  
Climate Data

Abstract. To allow for climate impact studies on human and natural systems, high-resolution climate information is needed. Over some parts of the world plenty of regional climate simulations have been carried out, while in other regions hardly any high-resolution climate information is available. The CORDEX Central Asia domain is one of these regions, and this article describes the evaluation for two regional climate models (RCMs), REMO and ALARO-0, that were run for the first time at a horizontal resolution of 0.22∘ (25 km) over this region. The output of the ERA-Interim-driven RCMs is compared with different observational datasets over the 1980–2017 period. REMO scores better for temperature, whereas the ALARO-0 model prevails for precipitation. Studying specific subregions provides deeper insight into the strengths and weaknesses of both RCMs over the CAS-CORDEX domain. For example, ALARO-0 has difficulties in simulating the temperature over the northern part of the domain, particularly when snow cover is present, while REMO poorly simulates the annual cycle of precipitation over the Tibetan Plateau. The evaluation of minimum and maximum temperature demonstrates that both models underestimate the daily temperature range. This study aims to evaluate whether REMO and ALARO-0 provide reliable climate information over the CAS-CORDEX domain for impact modeling and environmental assessment applications. Depending on the evaluated season and variable, it is demonstrated that the produced climate data can be used in several subregions, e.g., temperature and precipitation over western Central Asia in autumn. At the same time, a bias adjustment is required for regions where significant biases have been identified.

Regional Dynamical Downscaling

2020 ◽  
Author(s):  
Filippo Giorgi
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Added Value ◽  
Climate Information ◽  
Atmospheric Models ◽  
Future Directions ◽  
Climate Change Research ◽  
Climate Downscaling

Dynamical downscaling has been used for about 30 years to produce high-resolution climate information for studies of regional climate processes and for the production of climate information usable for vulnerability, impact assessment and adaptation studies. Three dynamical downscaling tools are available in the literature: high-resolution global atmospheric models (HIRGCMs), variable resolution global atmospheric models (VARGCMs), and regional climate models (RCMs). These techniques share their basic principles, but have different underlying assumptions, advantages and limitations. They have undergone a tremendous growth in the last decades, especially RCMs, to the point that they are considered fundamental tools in climate change research. Major intercomparison programs have been implemented over the years, culminating in the Coordinated Regional climate Downscaling EXperiment (CORDEX), an international program aimed at producing fine scale regional climate information based on multi-model and multi-technique approaches. These intercomparison projects have lead to an increasing understanding of fundamental issues in climate downscaling and in the potential of downscaling techniques to provide actionable climate change information. Yet some open issues remain, most notably that of the added value of downscaling, which are the focus of substantial current research. One of the primary future directions in dynamical downscaling is the development of fully coupled regional earth system models including multiple components, such as the atmosphere, the oceans, the biosphere and the chemosphere. Within this context, dynamical downscaling models offer optimal testbeds to incorporate the human component in a fully interactive way. Another main future research direction is the transition to models running at convection-permitting scales, order of 1–3 km, for climate applications. This is a major modeling step which will require substantial development in research and infrastructure, and will allow the description of local scale processes and phenomena within the climate change context. Especially in view of these future directions, climate downscaling will increasingly constitute a fundamental interface between the climate modeling and end-user communities in support of climate service activities.

scholarly journals A case study of possible future summer convective precipitation over the UK and Europe from a regional climate projection

2017 ◽  
Vol 38 (5) ◽  
pp. 2314-2324 ◽  
Author(s):  
Alan M. Gadian ◽  
Alan M. Blyth ◽  
Cindy L. Bruyere ◽  
Ralph R. Burton ◽  
James M. Done ◽  
...  
Keyword(s):  
Regional Climate ◽  
Climate Projection ◽  
Convective Precipitation ◽  
Regional Climate Projection ◽  
The Uk

scholarly journals Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22° resolution over the CORDEX Central Asia domain

2020 ◽  
Author(s):  
Sara Top ◽  
Lola Kotova ◽  
Lesley De Cruz ◽  
Svetlana Aniskevich ◽  
Leonid Bobylev ◽  
...  
Keyword(s):  
High Resolution ◽  
Central Asia ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Maximum Temperature ◽  
Climate Projections ◽  
Climate Information ◽  
Climate Data

Abstract. To allow for climate impact studies on human and natural systems high-resolution climate information is needed. Over some parts of the world plenty of regional climate simulations have been carried out, while in other regions hardly any high-resolution climate information is available. This publication aims at addressing one of these regional gaps by presenting an evaluation study for two regional climate models (RCMs) (REMO and ALARO-0) at a horizontal resolution of 0.22° (25 km) over Central Asia. The output of the ERA-Interim driven RCMs is compared with different observational datasets over the 1980–2017 period. The choice of the observational dataset has an impact on the scores but in general one can conclude that both models reproduce reasonably well the spatial patterns for temperature and precipitation. The evaluation of minimum and maximum temperature demonstrates that both models underestimate the daily temperature range. More detailed studies of the annual cycle over subregions should be carried out to reveal whether this is due to an incorrect simulation in cloud cover, atmospheric circulation or heat and moisture fluxes. In general, the REMO model scores better for temperature whereas the ALARO-0 model prevails for precipitation. This publication demonstrates that the REMO and ALARO-0 RCMs can be used to perform climate projections over Central Asia and that the produced climate data can be applied in impact modelling.

scholarly journals Streamflow Data from Small Basins: A Challenging Test to High-Resolution Regional Climate Modeling

2011 ◽  
Vol 12 (5) ◽  
pp. 900-912 ◽  
Author(s):  
Kerstin Stahl ◽  
Lena M. Tallaksen ◽  
Lukas Gudmundsson ◽  
Jens H. Christensen
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Temporal Dynamics ◽  
Model Simulation ◽  
Regional Climate ◽  
Regional Scale ◽  
Climate Simulation ◽  
Change Scenario

Abstract Land surface models and large-scale hydrological models provide the basis for studying impacts of climate and anthropogenic changes on continental- to regional-scale hydrology. Hence, there is a need for comparison and validation of simulated characteristics of spatial and temporal dynamics with independent observations. This study introduces a novel validation framework that relates to common hydrological design measures. The framework is tested by comparing anomalies of runoff from a high-resolution climate-model simulation for Europe with a large number of streamflow observations from small near-natural basins. The regional climate simulation was performed as a “poor man’s reanalysis,” involving a dynamical downscaling of the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) with the Danish “HIRHAM5” model. For 19 different anomaly levels, two indices evaluate the temporal agreement (i.e., the occurrence and frequency of dry and wet events based on daily anomalies), whereas two other indices compare the interannual variability and trends based on annual anomalies. Benchmarks on each index facilitated a comparison across indices, anomaly levels, and basins. The lowest agreement of observed and simulated anomalies was found for dry anomalies. Weak to moderately wet anomalies agreed best, but agreement dropped again for the wettest anomalies. The results could guide the decision on thresholds if this regional climate model were used for the assessment of climate change scenario impacts on flood and drought statistics. Indices vary across Europe, but a gradient with decreasing correspondence between observed and simulated runoff characteristics from west to east, from lower to higher elevations, and from fast to slowly responding basins can be distinguished. The suggested indices can easily be adapted to other study areas and model types to assist in assessing the reliability of predictions of hydrological change.

scholarly journals VHR-REA_IT Dataset: Very High Resolution Dynamical Downscaling of ERA5 Reanalysis over Italy by COSMO-CLM

Data ◽  
2021 ◽  
Vol 6 (8) ◽  
pp. 88
Author(s):  
Mario Raffa ◽  
Alfredo Reder ◽  
Gian Franco Marras ◽  
Marco Mancini ◽  
Gabriella Scipione ◽  
...  
Keyword(s):  
High Resolution ◽  
Applied Research ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Climatological Data ◽  
Recent Climate ◽  
Very High ◽  
Italian Territory

This work presents a new dataset for recent climate developed within the Highlander project by dynamically downscaling ERA5 reanalysis, originally available at ≃31 km horizontal resolution, to ≃2.2 km resolution (i.e., convection permitting scale). Dynamical downscaling was conducted through the COSMO Regional Climate Model (RCM). The temporal resolution of output is hourly (like for ERA5). Runs cover the whole Italian territory (and neighboring areas according to the necessary computation boundary) to provide a very detailed (in terms of space–time resolution) and comprehensive (in terms of meteorological fields) dataset of climatological data for at least the last 30 years (01/1989-12/2020). These types of datasets can be used for (applied) research and downstream services (e.g., for decision support systems).

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