High Resolution Climate Modelling with the CCLM Regional Model for Europe and Africa

2014 ◽  
pp. 561-574 ◽  
Author(s):  
H.-J. Panitz ◽  
G. Schädler ◽  
M. Breil ◽  
S. Mieruch ◽  
H. Feldmann ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Model ◽  
Climate Modelling

scholarly journals A high-resolution downscaled CMIP6 projections dataset of essential surface climate variables over the globe coherent with the ERA5-Land reanalysis for climate change impact assessments

2021 ◽  
Author(s):  
Thomas Noël ◽  
Harilaos Loukos ◽  
Dimitri Defrance
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Models ◽  
Mapping Method ◽  
Cumulative Distribution ◽  
Climate Projections ◽  
Climate Modelling ◽  
Temperature And Precipitation ◽  
Surface Climate ◽  
Emissions Scenarios

A high-resolution climate projections dataset is obtained by statistically downscaling climate projections from the CMIP6 experiment using the ERA5-Land reanalysis from the Copernicus Climate Change Service. This global dataset has a spatial resolution of 0.1°x 0.1°, comprises 5 climate models and includes two surface daily variables at monthly resolution: air temperature and precipitation. Two greenhouse gas emissions scenarios are available: one with mitigation policy (SSP126) and one without mitigation (SSP585). The downscaling method is a Quantile Mapping method (QM) called the Cumulative Distribution Function transform (CDF-t) method that was first used for wind values and is now referenced in dozens of peer-reviewed publications. The data processing includes quality control of metadata according to the climate modelling community standards and value checking for outlier detection.

scholarly journals Tracking cyclones in regional model data: the future of Mediterranean storms

2005 ◽  
Vol 2 ◽  
pp. 13-19 ◽  
Author(s):  
M. Muskulus ◽  
D. Jacob
Keyword(s):  
Regional Climate ◽  
Regional Model ◽  
Climate Modelling ◽  
High Resolution Data ◽  
International Panel ◽  
The Future ◽  
Precipitation Estimates ◽  
Emissions Scenarios ◽  
The Mediterranean ◽  
Ipcc Sres

Abstract. With the advent of regional climate modelling, there are high-resolution data available for regional climatological change studies. Automatic tracking of cyclones in these datasets encounters problems with high spatial resolution due to cyclone substructure. Watershed segmentation, a technique from image analysis, has been used to obtain estimates for the spatial extent of cyclones, enabling better tracking and precipitation analysis. In this study we have used data from a 0.5° Regional Model (REMO) climatological model run for the period from 1961-2099, following the International Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) B2 forcing. The resulting hourly mean sea level pressure (MSLP) fields have been analysed for cyclone numbers and tracks in the Mediterranean region. According to the results, the total number of cyclones in the Mediterranean seems to be increasing in the future, in spite of a general decrease of the numbers of stronger systems. In Summer, the increase in each gridbox seems to be proportional to the total number of cyclones in that box, whereas in Winter there is a slight proportional decrease. As concerns track properties and precipitation estimates along tracks, no significant change could be detected.

Climate Evaluation of a High-Resolution Regional Model over the Canary Current Upwelling System

2019 ◽  
pp. 240-252
Author(s):  
Ruben Vazquez ◽  
Ivan Parras-Berrocal ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Rafael Mañanes ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Model ◽  
Upwelling System

scholarly journals Evaluation of a Unique Approach to High-Resolution Climate Modelling using the Model for Prediction Across Scales (MPAS) version 5.1

2019 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
General Circulation Models ◽  
Climate Modelling ◽  
Northern Hemispheric

Abstract. We present multi-seasonal simulations representative of present-day and future thermodynamic environments using the global Model for Prediction Across Scales-Atmosphere (MPAS) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select ten simulation years with varying phases of El Niño-Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analysed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most of Northern Hemispheric basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemispheric phenomena, and, more generally, the utility of MPAS for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals Quantifying pollution inflow and outflow over East Asia in spring with regional and global models

2010 ◽  
Vol 10 (9) ◽  
pp. 4221-4239 ◽  
Author(s):  
M. Lin ◽  
T. Holloway ◽  
G. R. Carmichael ◽  
A. M. Fiore
Keyword(s):  
Boundary Layer ◽  
Air Pollution ◽  
High Resolution ◽  
Boundary Conditions ◽  
East Asia ◽  
Large Scale ◽  
Regional Model ◽  
Global Model ◽  
Global Models ◽  
High Resolution Models

Abstract. Understanding the exchange processes between the atmospheric boundary layer and the free troposphere is crucial for estimating hemispheric transport of air pollution. Most studies of hemispheric air pollution transport have taken a large-scale perspective using global chemical transport models with fairly coarse spatial and temporal resolutions. In support of United Nations Task Force on Hemispheric Transport of Air Pollution (TF HTAP; www.htap.org), this study employs two high-resolution atmospheric chemistry models (WRF-Chem and CMAQ; 36×36 km) driven with chemical boundary conditions from a global model (MOZART; 1.9×1.9°) to examine the role of fine-scale transport and chemistry processes in controlling pollution export and import over the Asian continent in spring (March 2001). Our analysis indicates the importance of rapid venting through deep convection that develops along the leading edge of frontal system convergence bands, which are not adequately resolved in either of two global models compared with TRACE-P aircraft observations during a frontal event. Both regional model simulations and observations show that frontal outflows of CO, O3 and PAN can extend to the upper troposphere (6–9 km). Pollution plumes in the global MOZART model are typically diluted and insufficiently lofted to higher altitudes where they can undergo more efficient transport in stronger winds. We use sensitivity simulations that perturb chemical boundary conditions in the CMAQ regional model to estimate that the O3 production over East Asia (EA) driven by PAN decomposition contributes 20% of the spatial averaged total O3 response to European (EU) emission perturbations in March, and occasionally contributes approximately 50% of the total O3 response in subsiding plumes at mountain observatories (at approximately 2 km altitude). The response to decomposing PAN of EU origin is strongly affected by the O3 formation chemical regimes, which vary with the model chemical mechanism and NOx/VOC emissions. Our high-resolution models demonstrate a large spatial variability (by up to a factor of 6) in the response of local O3 to 20% reductions in EU anthropogenic O3 precursor emissions. The response in the highly populated Asian megacities is 40–50% lower in our high-resolution models than the global model, suggesting that the source-receptor relationships inferred from the global coarse-resolution models likely overestimate health impacts associated with intercontinental O3 transport. Our results highlight the important roles of rapid convective transport, orographic forcing, urban photochemistry and heterogeneous boundary layer processes in controlling intercontinental transport; these processes may not be well resolved in the large-scale models.

Revealing snow cover dynamics in the Hindu Kush Himalaya over the past decades

2020 ◽  
Author(s):  
Kathrin Naegeli ◽  
Carlo Marin ◽  
Valentina Premier ◽  
Gabriele Schwaizer ◽  
Martin Stengel ◽  
...  
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Satellite Data ◽  
Weather Forecast ◽  
Short Wave ◽  
Climate Modelling ◽  
Snow Cover Area ◽  
Hindu Kush ◽  
Spatio Temporal ◽  
Area Percentage

<p>Knowledge about the snow cover distribution is of high importance for climate studies, weather forecast, hydrological investigations, irrigation or tourism, respectively. The Hindu Kush Himalayan (HKH) region covers almost 3.5 million km<sup>2</sup> and extends over eight different countries. The region is known as ‘water tower’ as it contains the largest volume of ice and snow outside of the polar ice sheets and it is the source of Asia’s largest rivers. These rivers provide ecosystem services, the basis for livelihoods and most importantly living water for drinking, irrigation, energy production and industry for two billion people, a fourth of the world’s population, living in the mountains and downstream.</p><p>The spatio-temporal variability of snow cover in the HKH is high and studies reported average snow-covered area percentage of 10–18%, with greater variability in winter (21–42%) than in summer (2–4%). However, no study systematically investigated snow cover metrics, such as snow cover area percentage (SCA), snow cover duration (SCD) or snow cover onset (SCOD) and melt-out day (SCMD), for the entire region so far. Here, we thus present unique in-sights of regional and sub-regional snow cover dynamics for the HKH based on almost four decades, an exceptionally long and in view of the climate modelling community valuable timeseries, of satellite data obtained within the ESA CCI+ Snow project.</p><p>Our results are based on Advanced Very High Resolution Radiometer (AVHRR) data, collected onboard the polar orbiting satellites NOAA-7 to -19, providing daily, global imagery at a spatial resolution of 5 km. Calibrated and geocoded reflectance data and a consistent cloud mask pre-processed and provided by the ESA Cloud_cci project as global 0.05° composites are used. The retrieval of snow extent considers the high reflectance of snow in the visible spectra and the low reflectance values in the short-wave infrared expressed in the Normalized Difference Snow Index (NDSI). Additional thresholds related to topography and land cover are included to derive the fractional snow cover of every pixel. A temporal gap-filling was applied to mitigate the influence of clouds. Reference snow maps from high-resolution optical satellite data as well as in-situ station data were used to validate the time series.</p>

Using PRIMAVERA high-resolution global climate models for European windstorm risk assessment in present and future climates for the (re)insurance industry

2020 ◽  
Author(s):  
Julia Lockwood ◽  
Erika Palin ◽  
Galina Guentchev ◽  
Malcolm Roberts
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Insurance Industry ◽  
Global Climate ◽  
Storm Track ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Business And Society ◽  
High Resolution Models

<p>PRIMAVERA is a European Union Horizon2020 project about creating a new generation of advanced and well-evaluated high-resolution global climate models, for the benefit of governments, business and society in general. The project has been engaging with several sectors, including finance, transport, and energy, to understand the extent to which any improved process understanding arising from high-resolution global climate modelling can – in turn – help with using climate model output to address user needs.</p><p>In this talk we will outline our work for the finance and (re)insurance industries.  Following consultation with members of the industry, we are using PRIMAVERA climate models to generate a European windstorm event set for use in catastrophe modelling and risk analysis.  The event set is generated from five different climate models, each run at a selection of resolutions ranging from 18-140km, covering the period 1950-2050, giving approximately 1700 years of climate model data in total.  High-resolution climate models tend to have reduced biases in storm track position (which is too zonal in low-resolution climate models) and windstorm intensity.  We will compare the properties of the windstorm footprints and associated risk across the different models and resolutions, to assess whether the high-resolution models lead to improved estimation of European windstorm risk.  We will also compare windstorm risk in present and future climates, to see if a consistent picture emerges between models.  Finally we will address the question of whether the event sets from each PRIMAVERA model can be combined to form a multi-model event set ensemble covering thousands of years of windstorm data.</p>

scholarly journals Extreme Events Representation in CMCC-CM2 High and Very-High Resolution General Circulation Models

2021 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Daniele Peano ◽  
Silvio Gualdi ◽  
Alessio Bellucci ◽  
Tomas Lovato ◽  
...  
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Horizontal Resolution ◽  
Historical Period ◽  
Climate Modelling ◽  
Temperature And Precipitation ◽  
Very High

Abstract. The recent advancements in climate modelling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the CMCC-CM2 model used here, adopt the highest horizontal resolutions available within the last family of the global coupled climate models de¬veloped at CMCC to participate in the CMIP6 effort. The main aim of this study is to document the ability of the CMCC-CM2 models in representing the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations (ERA5 Reanalysis and CHIRPS observations). For a more detailed evaluation we investigate both 6 hourly and daily time series for the definition of the extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The very-high resolution version (¼ degree horizontal resolution) of the atmospheric model provides better results than the high resolution one (one degree), not only in terms of means but also in terms of extreme events of temperature defined at daily and 6-hourly frequency. This is also the case of average precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

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