Air flow influences on local climate: comparison of a regional climate model with observations over the United Kingdom

Midlatitude western coastal regions are recognized as being important for the global energy cycle, marine and terrestrial biodiversity, and regional economies. &#160;These coastal regions exhibit a rich range of weather and climate phenomena, including persistent stratocumulus clouds, sea-breeze circulations, coastally-trapped Kelvin waves, and wind-driven upwelling. During the summer season, when impacts from transient synoptic systems are relatively reduced, the local climate is governed by a complex set of interactions among the atmosphere, land, and ocean.&#160; This complexity has so far inhibited basic understanding of the drivers of western coastal climate, climate variability, and climate change.As a way of simplifying the system, we have developed a hierarchical regional climate model experimental framework focused on the western United States. We modify the International Centre for Theoretical Physics RegCM4 to use steady-state initial, lateral, and top-of-model boundary conditions: average July insolation (no diurnal cycle) and average meteorological state (winds, temperature, humidity, surface pressure).&#160; This July Base State simulation rapidly reaches a steady state solution that closely resembles the observed mean climate and the mean climate achieved using RegCM4 in a standard reanalysis-driven configuration.&#160; It is particularly notable that the near-coastal stratocumulus field is spatially similar to the satellite-observed stratocumulus field during arbitrary July days: including gaps in stratocumulus coverage downwind of capes. We run similar Base State simulations for the other calendar months and find that these simulations mimic the annual cycle. &#160;This suggests that the summer coastal stratocumulus field results from the steady-state response of the marine boundary layer to summertime climatological forcing; if true for the real world, this would imply that stratocumulus cloud fraction, within a given month, is temporally modulated by deviations from the summer base state (e.g., transient synoptic disturbances that interrupt the cloud field).&#160; We describe modifications to this simplified experimental framework aimed at understanding the factors that govern stratocumulus cloud fraction and its variability.

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Impact of different and time-varying land cover data sets in a regional climate model on regional and local climate over Europe

10.5194/egusphere-egu2020-631 ◽

2020 ◽

Author(s):

Mingyue Zhang ◽

Jürgen Helmert ◽

Merja Tölle

Keyword(s):

Land Cover ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Data Sets ◽

Time Varying ◽

Data Set ◽

Local Climate ◽

Land Cover Data ◽

Simulation Results

According to IPCC, Land use and Land Cover (LC) changes have a key role to adapt and mitigate future climate change aiming to stabilize temperature rise up to 2&#176;C. Land surface change at regional scale is associated to global climate change, such as global warming. It influences the earth&#8217;s water and energy cycles via influences on the heat, moisture and momentum transfer, and on the chemical composition of the atmosphere. These effects show variations due to different LC types, and due to their spatial and temporal resolutions. &#160;Thus, we incorporate a new time-varying land cover data set based on ESACCI into the regional climate model COSMO-CLM(v5.0). Further, the impact on the regional and local climate is compared to the standard operational LC data of GLC2000 and GlobCover 2009. Convection-permitting simulations with the three land cover data sets are performed at 0.0275&#176; horizontal resolution over Europe for the time period from 1992 to 2015.Overall, the simulation results show comparable agreement to observations. However, the simulation results based on GLC2000 and GlobCover 2009 (with 23 LC types) LC data sets show a fluctuation of 0.5K in temperature and 5% of precipitation. Even though the LC is classified into the same types, the difference in LC distribution and fraction leads to variations in climate simulation results. Using all of the 37 LC types of the ESACCI-LC data set show noticeable differences in distribution of temperature and precipitation compared to the simulations with GLC2000 and GlobCover 2009. Especially in forest areas, slight differences of the plant cover type (e.g. Evergreen or Deciduous) could result in up to 10% differences (increase or decrease) in temperature and precipitation over the simulation domain. Our results demonstrate how LC changes as well as different land cover type effect regional climate. There is need for proper and time-varying land cover data sets for regional climate model studies. The approach of including ESACCI-LC data set into regional climate model simulations also improved the external data generation system.We anticipate this research to be a starting point for involving time-varying LC data sets into regional climate models. Furthermore, it will give us a possibility to quantify the effect of time-varying LC data on regional climate accurately.Acknowledgement:1: Computational resources were made available by the German Climate Computing Center (DKRZ) through support from the Federal Ministry of Education and Research in Germany (BMBF). We acknowledge the funding of the German Research Foundation (DFG) through grant NR. 401857120.2: Appreciation for the support of J&#252;rg Luterbacher and Eva Nowatzki.&#160;

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Impacts of different RCP scenarios on ALADIN-Climate regional climate model projections over Hungary

10.5194/egusphere-egu2020-15871 ◽

2020 ◽

Author(s):

Beatrix Bán ◽

Gabriella Zsebeházi

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Horizontal Resolution ◽

Observation Data ◽

Rcp Scenarios ◽

Local Climate ◽

Temperature And Precipitation ◽

Local Climate Change ◽

Primary Basis

The KlimAdat national project was started in 2016 to create a complex database of detailed meteorological information aiming to support local climate change impact studies in different sectors, adaptation strategies and related decision making. Besides observation data its primary basis will be ALADIN-Climate and REMO regional climate model simulations achieved by the Hungarian Meteorological Service and this set of projections will be extended by members of the Euro-CORDEX ensemble in order to quantify the projection uncertainties.&#160; This study is focusing on analysis of the ALADIN-Climate model projections driven with RCP4.5 and RCP8.5 scenarios. Firstly, the CNRM-CM5 global model outputs were downscaled to 50 km horizontal resolution over the EURO-CORDEX domain with ALADIN-Climate Version 5.2. Then using these &#160;results as lateral boundary conditions, 10 km experiments were prepared on a domain covering Central and South-Eastern Europe. The presentation aims to introduce the behaviour of these simulations achieved by different scenarios and at different spatial resolution from the aspect of temperature and precipitation change over Hungary. Special attention will be put on the differences in extreme indices. Finally, our 10 km resolution simulations are compared with EURO-CORDEX results to specify their place in a larger ensemble.

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Future response of precipitation extremes over the Nordic region in a convection-permitting regional climate model

10.5194/egusphere-egu2020-9167 ◽

2020 ◽

Author(s):

Petter Lind ◽

Danijel Belušić ◽

Erik Kjellström ◽

Fuxing Wang ◽

Erika Toivonen ◽

...

Keyword(s):

High Resolution ◽

Regional Climate Model ◽

Boundary Data ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Precipitation Extremes ◽

Grid Spacing ◽

Local Climate ◽

Nordic Region

There is an increased need for more detailed climate information from impact researchers, stakeholders and policy makers for regional-to-local climate change assessments. In order to design relevant and informative planning strategies on these scales it is important to have reliable climate data and information on high spatial O(1km) and temporal (daily to sub-daily) scales. Such high-resolution data is also beneficial for climate impact modellers as input to their models, e.g. hydrological or urban models that operate on regional to local scales. It has been established that regional climate models (RCMs) provide added value compared to coarser global climate models (GCMs) or re-analysis (e.g. ERA-Interim). However, RCMs with standard spatial resolution O(10 &#8722; 50km) still suffer from inadequacies in representing important regional-to-local climate phenomena and characteristics, both from the implied &#8221;smoothening&#8221; effect within each grid cell which limits the representation of fine scale surface forcings, and the need to parameterize small-scale processes like atmospheric convection. The latter particularly invokes uncertainties in future climate responses of short-duration precipitation extremes such as flash-floods. Here, we compare 20-year simulations with a very high resolution (3 km grid spacing) convection permitting regional climate model (CPRCM) with a standard high-resolution (12 km grid spacing) convection parameterized RCM and their abilities to simulate the climate characteristics of the Nordic region in Europe, with particular focus on precipitation extremes. The study covers both recent past (with boundary data from ERA-Interim and the EC-Earth GCM) and the end of the 21st century (boundary data from EC-Earth using the RCP8.5 radiative forcing scenario). The high model grid resolution combined with the extensive simulated time period which enables assessment on climatological time scales makes this study one of very few for this region.

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Realism of Rainfall in a Very High-Resolution Regional Climate Model

Journal of Climate ◽

10.1175/jcli-d-11-00562.1 ◽

2012 ◽

Vol 25 (17) ◽

pp. 5791-5806 ◽

Cited By ~ 232

Author(s):

Elizabeth J. Kendon ◽

Nigel M. Roberts ◽

Catherine A. Senior ◽

Malcolm J. Roberts

Keyword(s):

United Kingdom ◽

High Resolution ◽

Regional Climate Model ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Heavy Rain ◽

Spatial Extent ◽

Hourly Rainfall ◽

Very High

Abstract The realistic representation of rainfall on the local scale in climate models remains a key challenge. Realism encompasses the full spatial and temporal structure of rainfall, and is a key indicator of model skill in representing the underlying processes. In particular, if rainfall is more realistic in a climate model, there is greater confidence in its projections of future change. In this study, the realism of rainfall in a very high-resolution (1.5 km) regional climate model (RCM) is compared to a coarser-resolution 12-km RCM. This is the first time a convection-permitting model has been run for an extended period (1989–2008) over a region of the United Kingdom, allowing the characteristics of rainfall to be evaluated in a climatological sense. In particular, the duration and spatial extent of hourly rainfall across the southern United Kingdom is examined, with a key focus on heavy rainfall. Rainfall in the 1.5-km RCM is found to be much more realistic than in the 12-km RCM. In the 12-km RCM, heavy rain events are not heavy enough, and tend to be too persistent and widespread. While the 1.5-km model does have a tendency for heavy rain to be too intense, it still gives a much better representation of its duration and spatial extent. Long-standing problems in climate models, such as the tendency for too much persistent light rain and errors in the diurnal cycle, are also considerably reduced in the 1.5-km RCM. Biases in the 12-km RCM appear to be linked to deficiencies in the representation of convection.

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GCM Model Selection Procedure for Downscaling

10.5194/egusphere-egu21-5153 ◽

2021 ◽

Author(s):

Carolyne Pickler ◽

Thomas Mölg

Keyword(s):

Surface Temperature ◽

Regional Climate Model ◽

East Africa ◽

Spatial Resolution ◽

General Circulation ◽

Climate Model ◽

Regional Climate ◽

Selection Procedure ◽

Reanalysis Data ◽

Local Climate

Downscaling has been widely used in studies of regional and/or local climate as it yields greater spatial resolution than general circulation models (GCM) can provide. &#160;It can approached in two distinct ways: 1) Statistical and 2) Dynamical. &#160;Statistical downscaling utilizes mathematical relationships between large-scale and regional/local climate to transform GCM or reanalysis data to a higher spatial resolution. &#160;Dynamical downscaling comprises forcing the lateral boundaries of a regional climate model with reanalysis or GCM data. &#160;However, there is no set technique to select said GCM(s).A comprehensive yet easily applicable selection procedure was created to address this. &#160;Using reanalysis data and/or observational data, the space-time climatic anomalies and the mean state of the climate are evaluated for the region of interest. &#160;East Africa was utilized as a case study and GISS-E2-H r6i1p3 was found to perform the strongest. &#160;This procedure cannot, however, tell whether the models can reproduce the key processes of the region. &#160;To examine this, the ability of the models to simulate the Indian Ocean Dipole were evaluated. &#160;It was found that higher ranked models were better able to capture it than lower ranked ones. &#160;Furthermore, to ensure that a higher ranked model yielded a better downscaling simulation, three 10-year regional climate model simulations over East Africa were undertaken, where they were respectively forced by the highest ranked GCM (GISS-E2-H r6i1p3), the lowest ranked GCM (IPSL-CM5A-LR r4i1p1) and the MERRA-2 reanalysis product. &#160;The simulated surface temperature and precipitation for Equatorial East Africa were compared with a gridded observational dataset (CRU TS 4.04). &#160;Results showed that the higher ranked GCM produced a better downscaled simulation than the lower ranked one, a result that was more evident for surface temperature than precipitation.

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REMOLAND: New high-resolution surface boundary data for the regional climate model REMO and their impacts

10.5194/egusphere-egu2020-3005 ◽

2020 ◽

Author(s):

Katrin Ziegler ◽

Felix Pollinger ◽

Daniel Abel ◽

Heiko Paeth

Keyword(s):

High Resolution ◽

Regional Climate Model ◽

Land Surface ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Data Sets ◽

Surface Boundary ◽

Local Climate

In cooperation with the Climate Service Center Germany (GERICS) we want to improve the land surface module in the regional climate model REMO. Due to the need of high-resolution regional climate models to get information about local climate change, new data and new processes have to be integrated in these models. Based on the REMO2015 version and focusing on EUR-CORDEX region we included and compared five different high-resolution topographic data sets. To improve the thermal and hydrological processes in the model&#8217;s soil we also tested three new soil data sets with a much higher spatial resolution and with new parameters for a new soil parameterization.

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