Regional climate simulations at kilometer-scale with RegCM4: Evaluation of precipitation and future projections

2020 ◽  
Author(s):  
Paolo Stocchi ◽  
Emanuela Pichelli ◽  
Erika Coppola ◽  
Jose Abraham Torres Alvarez ◽  
Filippo Giorgi
Keyword(s):  
Global Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Historical Period ◽  
Climate Projections ◽  
Model Errors ◽  
Grid Spacing ◽  
Climate Simulations ◽  
Near Future ◽  
Far Future

<p>The recent increase in climate modeling activities at convection permitting scales (grid spacing under 4 km) has strongly been motivated by the increased computer capacities in the last years with the aim to reduce the model errors associated with parameterized convection and a more detailed representation of present and future regional climate. Some Regional climate projects addressing on convection permitting modeling simulations and projections have been recently implemented to make more robust conclusions on the added value of convection permitting simulation to future climate projections. Here, we present convection resolving climate simulations performed in the framework the European Climate Prediction System (EUCP) project, using the non-hydrostatic version of the RegCM model. The RegCM simulations have a grid spacing of 3 km, over three different regions (Pan-Alpine, Central Europe, and South-East Europe). These simulations were driven by initial and boundary conditions built from intermediate 12 km simulations driven by the global climate model (GCM) HadGEM2-ES. We considered three time slices each one of them covering a 10-year period, the historical (1996-2005), the near future (2041-2050) and the far future (2090-2099) under the RCP8.5 scenario. The high resolutions (3 km) simulations, over the historical period, are evaluated through comparison with available observations data sets (including in-situ and satellite-based observation of precipitation) and coarse resolution (12 km) simulation is used as benchmark. The kilometer-scale RegCM4.7 scenario (RCP8.5) simulations, driven by HadGEM2-ES, near future (2041-2050) and the far future (2090-2099), are also analyzed and presented, focusing on the future change in terms of mean precipitation, precipitation intensity and frequency and heavy precipitation on daily and hourly timescales in different seasons.</p>

scholarly journals WRF Sensitivity for Seasonal Climate Simulations of Precipitation Fields on the CORDEX South America Domain

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 107
Author(s):  
Helber Barros Gomes ◽  
Maria Cristina Lemos da Silva ◽  
Henrique de Melo Jorge Barbosa ◽  
Tércio Ambrizzi ◽  
Hakki Baltaci ◽  
...  
Keyword(s):  
South America ◽  
Numerical Models ◽  
Regional Climate ◽  
Wrf Model ◽  
Added Value ◽  
Climate Projections ◽  
South American ◽  
Climate Forecasting ◽  
Climate Simulations ◽  
Simulated Precipitation

Dynamic numerical models of the atmosphere are the main tools used for weather and climate forecasting as well as climate projections. Thus, this work evaluated the systematic errors and areas with large uncertainties in precipitation over the South American continent (SAC) based on regional climate simulations with the weather research and forecasting (WRF) model. Ten simulations using different convective, radiation, and microphysical schemes, and an ensemble mean among them, were performed with a resolution of 50 km, covering the CORDEX-South America domain. First, the seasonal precipitation variability and its differences were discussed. Then, its annual cycle was investigated through nine sub-domains on the SAC (AMZN, AMZS, NEBN, NEBS, SE, SURU, CHAC, PEQU, and TOTL). The Taylor Diagrams were used to assess the sensitivity of the model to different parameterizations and its ability to reproduce the simulated precipitation patterns. The results showed that the WRF simulations were better than the ERA-interim (ERAI) reanalysis when compared to the TRMM, showing the added value of dynamic downscaling. For all sub-domains the best result was obtained with the ensemble compared to the satellite TRMM. The largest errors were observed in the SURU and CHAC regions, and with the greatest dispersion of members during the rainy season. On the other hand, the best results were found in the AMZS, NEBS, and TOTL regions.

scholarly journals Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble.

2020 ◽  
Author(s):  
Erika Coppola ◽  
Keyword(s):  
Regional Climate ◽  
Congo Basin ◽  
Added Value ◽  
Climate Projections ◽  
Hazard Indices ◽  
Future Time ◽  
Climate Services ◽  
North East ◽  
The Impact ◽  
Far Future

<p>Under the CORDEX umbrella the CORDEX-CORE initiative has been developed that was able to produce an ensemble of two RCMs at 0.22° resolution downscaling 3 GCMs for each of the 9 CORDEX domains for two climate scenarios the RCP2.6 and the RCP8.5. The CORDEX-CORE and the CMIP5 driving ensemble together with the most recently produced CMIP6 ensemble has been analyzed and several temperature, heat, wet and dry hazard indicators have been computed for the present day and mid and far future time slices.</p><p>As a results CORDEX-CORE shows a better validation for several hazard indices due to the higher spatial resolution. For the far future time slice the 3 ensembles project an increase for all the temperature and heat indices under the RCC8.5 scenario. The highest values are always shown by the CMIP6 ensemble except that for Tx>35 °C for which CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected by the regional ensemble over la Plata basin in South America , over the Congo basin in Africa, in east North America, north east Europe , India and Indochina, notably the regions where a better validation is obtained, whereas the global ensembles show quite small or not existent signal. Compound hazard hotspots based on heat and drought indicators have been identified in Central America, in the Amazon region, in the Mediterranean, South Africa, India and Australia since in all these regions a linear relation is shown by the heatwave and drought change signal. Although still limited the CORDEX-CORE initiative was able to produce high resolution climate projections with a quasi global coverage. This can be seen as a first step to foster collaboration among the global and regional climate community. The existence of the first of this kind ensemble together with the previous CORDEX 0.44 ensembles and the global ensemble is very valuable for climate impact assessment studies since can provide information on the mean and extreme regional climate projections but also more robust quantification on the model spread. All being an added value for the impact and climate services communities.</p>

scholarly journals Climate Projections for South America: RegCM3 Driven by HadCM3 and ECHAM5

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Michelle Simões Reboita ◽  
Rosmeri Porfírio da Rocha ◽  
Cássia Gabriele Dias ◽  
Rita Yuri Ynoue
Keyword(s):  
South America ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Projections ◽  
South American ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Precipitation Increase ◽  
Near Future ◽  
Far Future

This study shows climate projections of air temperature and precipitation over South America (SA) from the Regional Climate Model version 3 (RegCM3) nested in ECHAM5 and HadCM3 global models. The projections consider the A1B scenario from Intergovernmental Panel on Climate Change (IPCC) and three time-slices: present (1960–1990), near- (2010–2040), and far-future (2070–2100) climates. In the future, RegCM3 projections indicate general warming throughout all SA and seasons, which is more pronounced in the far-future period. In this late period the RegCM3 projections indicate that the negative trend of precipitation over northern SA is also higher. In addition, a precipitation increase over southeastern SA is projected, mainly during summer and spring. The lifecycle of the South American monsoon (SAM) was also investigated in the present and future climates. In the near-future, the projections show a slight delay (one pentad) of the beginning of the rainy season, resulting in a small reduction of the SAM length. In the far-future, there is no agreement between projections related to the SAM features.

UKCP: Understanding uncertainty in future changes in precipitation extremes at convection-permitting scale

2020 ◽  
Author(s):  
Giorgia Fosser ◽  
Elizabeth Kendon ◽  
Steven Chan ◽  
David Stephenson
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Climate Change Projections ◽  
Convective Processes ◽  
Climate Simulations ◽  
The Uk

<p>Convection-permitting models (CPMs) provide a better representation of sub-daily precipitation statistics and convective processes, both on climate and NWP time scales, mainly thanks to the possibility to switch off the parameterisation of convection. The improved realism of these models gives us greater confidence in their ability to project future changes in short-duration precipitation extremes.</p><p>The first 12-member ensemble of convection-permitting climate simulations over the UK was completed within the latest updates to the UK Climate Projections (UKCP). The 20-year long CPM simulations for present-day and end of century periods are nested in an ensemble of regional climate model (RCM) simulations over Europe driven by a global climate model ensemble. In the driving ensembles, uncertain parameters in the model physics are varied within plausible bounds to sample uncertainty. Although no perturbations are applied directly to the CPMs, this project allow us to provide a first-ever estimate of uncertainty at convection-permitting scale and thus provide UK risk assessment studies with more reliable climate change projections at local and hourly scales.</p><p>Here we will present results looking at the uncertainty in future changes in hourly precipitation extremes across the CPM ensemble, and how this differs from the driving RCM ensemble.</p>

Realised added value in dynamical downscaling of Australian climate change

2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Future Climate ◽  
Added Value ◽  
Climate Projections ◽  
Eastern Australia ◽  
Australian Alps ◽  
Future Climate Projections

<p>Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, ‘realised added value’, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.</p>

scholarly journals Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R<sup>2</sup>D<sup>2</sup>) bias correction

2018 ◽  
Vol 22 (6) ◽  
pp. 3175-3196 ◽  
Author(s):  
Mathieu Vrac
Keyword(s):  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Grid Cell ◽  
Dependence Structure ◽  
Historical Period ◽  
Temporal Properties ◽  
Temperature And Precipitation ◽  
Climate Simulations ◽  
Site Dependence

Abstract. Climate simulations often suffer from statistical biases with respect to observations or reanalyses. It is therefore common to correct (or adjust) those simulations before using them as inputs into impact models. However, most bias correction (BC) methods are univariate and so do not account for the statistical dependences linking the different locations and/or physical variables of interest. In addition, they are often deterministic, and stochasticity is frequently needed to investigate climate uncertainty and to add constrained randomness to climate simulations that do not possess a realistic variability. This study presents a multivariate method of rank resampling for distributions and dependences (R2D2) bias correction allowing one to adjust not only the univariate distributions but also their inter-variable and inter-site dependence structures. Moreover, the proposed R2D2 method provides some stochasticity since it can generate as many multivariate corrected outputs as the number of statistical dimensions (i.e., number of grid cell  ×  number of climate variables) of the simulations to be corrected. It is based on an assumption of stability in time of the dependence structure – making it possible to deal with a high number of statistical dimensions – that lets the climate model drive the temporal properties and their changes in time. R2D2 is applied on temperature and precipitation reanalysis time series with respect to high-resolution reference data over the southeast of France (1506 grid cell). Bivariate, 1506-dimensional and 3012-dimensional versions of R2D2 are tested over a historical period and compared to a univariate BC. How the different BC methods behave in a climate change context is also illustrated with an application to regional climate simulations over the 2071–2100 period. The results indicate that the 1d-BC basically reproduces the climate model multivariate properties, 2d-R2D2 is only satisfying in the inter-variable context, 1506d-R2D2 strongly improves inter-site properties and 3012d-R2D2 is able to account for both. Applications of the proposed R2D2 method to various climate datasets are relevant for many impact studies. The perspectives of improvements are numerous, such as introducing stochasticity in the dependence itself, questioning its stability assumption, and accounting for temporal properties adjustment while including more physics in the adjustment procedures.

scholarly journals Precipitation over southern Africa: Is there consensus among GCMs, RCMs and observational data?

2021 ◽  
Author(s):  
Maria Chara Karypidou ◽  
Eleni Katragkou ◽  
Stefan Pieter Sobolowski
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
Regional Climate ◽  
Coupled Model ◽  
Added Value ◽  
Rain Gauges ◽  
Climate Simulations ◽  
Observational Uncertainty ◽  
Direct Contrast ◽  
Improved Performance

Abstract. The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modelling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behaviour of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (Oct–Mar), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP5 ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensemble exhibited improved performance compared to its forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher resolution regional climate simulations. The CMIP6 ensemble displayed a similar behaviour to CMIP5, however reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angolan Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic process that take place. Improvements in observational networks (both in-situ and satellite), as well as continued advancements in high-resolution modelling will be critical, in order to develop a robust assessment of climate change for southern Africa.

The CORDEX‐Australasia ensemble: evaluation and future projections

2021 ◽  
Author(s):  
Jason Evans ◽  
Giovanni Di Virgilio ◽  
Annette Hirsch ◽  
Peter Hoffmann ◽  
Armelle Reca Remedio ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Current Status ◽  
Climate Projections ◽  
Good Representation ◽  
Future Projections ◽  
Recent Climate ◽  
Climate Downscaling

&lt;p&gt;The World Climate Research Programme (WCRP) has an international initiative called the COordinated Regional climate Downscaling EXperiment (CORDEX). The goal of the initiative is to provide regionally downscaled climate projections for most land regions of the globe, as a compliment to the global climate model projections performed within the Coupled Model Intercomparison Projects (CMIP). CORDEX includes data from both dynamical and statistical downscaling. It is anticipated that the CORDEX dataset will provide a link to the impacts and adaptation community through its better resolution and regional focus. Participation in CORDEX is open and any researchers performing climate downscaling are encourage to engage with the initiative. Here I present the current status, &lt;span&gt;evaluation and future projections&lt;/span&gt; for the CORDEX-AustralAsia &lt;span&gt;ensemble&lt;/span&gt;.&lt;/p&gt;&lt;p&gt;The CORDEX-Australasia ensemble is the largest regional climate projection ensemble ever created for the region. It is a 20-member ensemble made by 6 regional climate models downscaling 11 global climate models. Overall the ensemble produces a good representation of recent climate. Consistent biases within the ensemble include an underestimation of the diurnal temperature range and an underestimation of precipitation across much of southern Australia. Under a high emissions scenario projected temperature changes by the end of the twenty-first century reach ~ 5 K in the interior of Australia with smaller increases found toward the coast. Projected precipitation changes are towards drying, particularly in the most populated areas of the southwest and southeast of the continent. The projected precipitation change is very seasonal with summer projected to see little change leaning toward an increase. These results provide a foundation enabling future studies of regional climate changes, climate change impacts, and adaptation options for Australia.&lt;/p&gt;

scholarly journals Changes in the characteristics of ‘wet’ and ‘dry’ Red Sea Trough over the Eastern Mediterranean in CMIP5 climate projections

2020 ◽  
Vol 143 (1-2) ◽  
pp. 781-794
Author(s):  
Assaf Hochman ◽  
Dorita Rostkier-Edelstein ◽  
Pavel Kunin ◽  
Joaquim G. Pinto
Keyword(s):  
Water Resources ◽  
Red Sea ◽  
Forest Fires ◽  
Eastern Mediterranean ◽  
Regional Climate ◽  
Mitigation Strategies ◽  
Cmip5 Models ◽  
Historical Period ◽  
Climate Projections ◽  
Synoptic Classification

AbstractThe Eastern Mediterranean resides on the border between the temperate and semi-arid and arid climate zones, and is thus influenced by both mid-latitude and sub-tropical weather systems. Precipitation and extreme weather in this region are mainly associated with either Cyprus Lows or the “wet” Red Sea Troughs. Current regional climate projections indicate that the region may become warmer and drier in future decades. Here, we analyze the influence of enhanced greenhouse gas forcing on the climatological properties of the ‘wet’ and ‘dry’ Red Sea Trough (WRST & DRST, respectively). With this aim, a regional synoptic classification and a downscaling algorithm based on past analogs are applied to eighteen rain stations over the main ground water basins in Israel. The algorithms are applied to the NCEP/NCAR reanalysis data for 1986–2005 and to eight CMIP5 model simulations for the historical (1986–2005) and end of the century (2081–2100) climate conditions according to the RCP8.5 scenario. For the historical period, the CMIP5 models are largely able to represent the characteristics of the Red Sea Trough. Based on the multi-model mean, significant changes are found for WRST and DRST for the late XXI Century. First, an increase in the meridional pressure gradient is found for both the WRST and the DRST, implying stronger horizontal winds. Furthermore, a significant decrease in the occurrence of the WRST (− 20%) and a significant increase in the frequency of the DRST (+ 19%) are identified. Accordingly, the persistence of the WRST decreases (− 9%), while for DRST increases (+ 9%). The decline in the frequency of WRST occurs primarily in the transition seasons, while the increase for DRST is found throughout the wet season. In total, the daily rainfall associated with the WRST system is projected to significantly decline (− 37%) by the end of the XXI century. These results document the projected changes in a dominant synoptic system in this area, which can facilitate a better estimation of the arising challenges, e.g., related to shortage of water resources and associated political unrest, reduced agricultural potential, and increased air pollution and forest fires. Such a pathway can ultimately foster novel mitigation strategies for water resources management and regional climate change adaptation.

scholarly journals Downscaling Atmosphere-Ocean Global Climate Model Precipitation Simulations over Africa Using Bias-Corrected Lateral and Lower Boundary Conditions

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 493 ◽  
Author(s):  
Leonard Druyan ◽  
Matthew Fulakeza
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Lower Boundary ◽  
Climate Projections ◽  
African Easterly Jet ◽  
Modèle Simulation ◽  
Goddard Institute ◽  
Bias Corrections

A prequel study showed that dynamic downscaling using a regional climate model (RCM) over Africa improved the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM: ModelE) simulation of June–September rainfall patterns over Africa. The current study applies bias corrections to the lateral and lower boundary data from the AOGCM driving the RCM, based on the comparison of a 30-year simulation to the actual climate. The analysis examines the horizontal pattern of June–September total accumulated precipitation, the time versus latitude evolution of zonal mean West Africa (WA) precipitation (showing monsoon onset timing), and the latitude versus altitude cross-section of zonal winds over WA (showing the African Easterly Jet and the Tropical Easterly Jet). The study shows that correcting for excessively warm AOGCM Atlantic sea-surface temperatures (SSTs) improves the simulation of key features, whereas applying 30-year mean bias corrections to atmospheric variables driving the RCM at the lateral boundaries does not improve the RCM simulations. We suggest that AOGCM climate projections for Africa should benefit from downscaling by nesting an RCM that has demonstrated skill in simulating African climate, driven with bias-corrected SST.

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