Explosive Cyclones in the CORDEX-CORE projections for Southern Hemisphere domains

2021 ◽  
Author(s):  
Michelle Reboita ◽  
Natália Machado Crespo ◽  
Marco Reale ◽  
José Abraham Torres ◽  
Rosmeri Porfírio da Rocha
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Time Range ◽  
Austral Winter ◽  
Sam Domain ◽  
Explosive Cyclones ◽  
Short Time

<p>Explosive cyclones (ECs) are extratropical systems, often associated with extreme events,  which experience a fast deepening (~24 hPa/24 h) over a relatively short time range. Here, we analyze changes in the austral winter characteristics of ECs in three domains (Africa-AFR, Australia-AUS and South America-SAM) as projected by Regional Climate Model (RegCM4) under RCP8.5 emission scenario in the CORDEX-CORE framework. RegCM4 was nested in three global climate models (GCMs) from CMIP5 (HadGEM2-ES, MPI-ESM-MR and NorESM-1M) and executed with 25 km of grid spacing. The cyclone database was obtained with the application of an automatic detection and tracking scheme to the 6-hourly mean sea level pressure fields. Extratropical cyclones with explosive features are then selected using the Sanders and Gyakum criterium. Following IPCC recommendation, we analyze the reference 1995–2014 period and the end-of-century 2080–2099 period. ECs represent ~13-17% of the total number of cyclones in ERA-Interim reanalysis during the austral winter, while the simulation ensembles, in general, underestimate this value. While in the AFR domain GCMs ensemble represents better the percentage of ECs compared to ERA-Interim, in AUS and SAM domains RegCM4 has a better performance than GCMs. The percentage of ECs compared to the  total number of cyclones in each domain is projected to increase, with higher positive trends for the SAM domain (7.4% in GCMs and 5.6% in RegCM4) than  AFR (3.3% in GCMs and 3.9% in RegCM4) and AUS (3.9% in GCMs and 1.7% in RegCM4). Compared to the present climate, ECs in the future will be stronger and faster but with a shorter lifetime.</p>

scholarly journals Spatio-temporal trends of hydrological components: the case of the Tafna basin (northwestern Algeria)

2021 ◽  
Author(s):  
Amina Mami ◽  
Djilali Yebdri ◽  
Sabine Sauvage ◽  
Mélanie Raimonet ◽  
José Miguel
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Assessment Tool ◽  
Global Climate ◽  
Swat Model ◽  
Regional Climate ◽  
Temporal Trends ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
The Future

Abstract Climate change is expected to increase in the future in the Mediterranean region, including Algeria. The Tafna basin, vulnerable to drought, is one of the most important catchments ensuring water self-sufficiency in northwestern Algeria. The objective of this study is to estimate the evolution of hydrological components of the Tafna basin, throughout 2020–2099, comparing to the period 1981–2000. The SWAT model (Soil and Water Assessment Tool), calibrated and validated on the Tafna basin with good Nash at the outlet 0.82, is applied to analyze the spatial and temporal evolution of hydrological components, over the basin throughout 2020–2099. The application is produced using a precipitation and temperature minimum/maximum of an ensemble of climate model outputs obtained from a combination of eight global climate models and two regional climate models of Coordinated Regional Climate Downscaling Experiment project. The results of this study show that the decrease of precipitation in January, on average −25%, ranged between −5% and −44% in the future. This diminution affects all of the water components and fluxes of a watershed, namely, in descending order of impact: the river discharge causing a decrease −36%, the soil water available −31%, the evapotranspiration −30%, and the lateral flow −29%.

scholarly journals Comparison of Statistical and Dynamic Downscaling Techniques in Generating High-Resolution Temperatures in China from CMIP5 GCMs

2020 ◽  
Vol 59 (2) ◽  
pp. 207-235 ◽  
Author(s):  
Lei Zhang ◽  
YinLong Xu ◽  
ChunChun Meng ◽  
XinHua Li ◽  
Huan Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
The Tibetan Plateau ◽  
Dynamic Downscaling

AbstractIn aiming for better access to climate change information and for providing climate service, it is important to obtain reliable high-resolution temperature simulations. Systematic comparisons are still deficient between statistical and dynamic downscaling techniques because of their inherent unavoidable uncertainties. In this paper, 20 global climate models (GCMs) and one regional climate model [Providing Regional Climates to Impact Studies (PRECIS)] are employed to evaluate their capabilities in reproducing average trends of mean temperature (Tm), maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), and extreme events represented by frost days (FD) and heat-wave days (HD) across China. It is shown generally that bias of temperatures from GCMs relative to observations is over ±1°C across more than one-half of mainland China. PRECIS demonstrates better representation of temperatures (except for HD) relative to GCMs. There is relatively better performance in Huanghuai, Jianghuai, Jianghan, south Yangzi River, and South China, whereas estimation is not as good in Xinjiang, the eastern part of northwest China, and the Tibetan Plateau. Bias-correction spatial disaggregation is used to downscale GCMs outputs, and bias correction is applied for PRECIS outputs, which demonstrate better improvement to a bias within ±0.2°C for Tm, Tmax, Tmin, and DTR and ±2 days for FD and HD. Furthermore, such improvement is also verified by the evidence of increased spatial correlation coefficient and symmetrical uncertainty, decreased root-mean-square error, and lower standard deviation for reproductions. It is seen from comprehensive ranking metrics that different downscaled models show the most improvement across different climatic regions, implying that optional ensembles of models should be adopted to provide sufficient high-quality climate information.

scholarly journals Climate Change Impact Assessment for Aji Basin Using Statistical Downscaling and Bias Correction of Climate Model Outputs

2016 ◽  
Vol 11 (2) ◽  
pp. 670-678 ◽  
Author(s):  
N. S Vithlani ◽  
H. D Rank
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Climate Extremes ◽  
Global Climate Models ◽  
Climate Indices ◽  
Climate Projections

For the future projections Global climate models (GCMs) enable development of climate projections and relate greenhouse gas forcing to future potential climate states. When focusing it on smaller scales it exhibit some limitations to overcome this problem, regional climate models (RCMs) and other downscaling methods have been developed. To ensure statistics of the downscaled output matched the corresponding statistics of the observed data, bias correction was used. Quantify future changes of climate extremes were analyzed, based on these downscaled data from two RCMs grid points. Subset of indices and models, results of bias corrected model output and raw for the present day climate were compared with observation, which demonstrated that bias correction is important for RCM outputs. Bias correction directed agreements of extreme climate indices for future climate it does not correct for lag inverse autocorrelation and fraction of wet and dry days. But, it was observed that adjusting both the biases in the mean and variability, relatively simple non-linear correction, leads to better reproduction of observed extreme daily and multi-daily precipitation amounts. Due to climate change temperature and precipitation will increased day by day.

scholarly journals Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

2021 ◽  
Author(s):  
Guillaume Evin ◽  
Samuel Somot ◽  
Benoit Hingray
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Uncertainty Assessment ◽  
Global Climate Models ◽  
Climate Projections ◽  
Total Uncertainty ◽  
Near Surface

Abstract. Large Multiscenarios Multimodel Ensembles (MMEs) of regional climate model (RCM) experiments driven by Global Climate Models (GCM) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse Scenario-GCM-RCM matrices, these large ensembles are however very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest ensemble ever produced for regional projections in Europe. This analysis provides i) the most up-to-date and balanced estimates of mean changes for near-surface temperature and precipitation in Europe, ii) the total uncertainty of projections and its partition as a function of time, and iii) the list of the most important contributors to the model uncertainty. For changes of total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in Central-Eastern Europe for instance, the difference between balanced and direct estimates are up to 0.8 °C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

scholarly journals New Tendencies in Global Climate Change and Their Effects on the Climate of Hungary

Hadmérnök ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. 99-107
Author(s):  
László Földi ◽  
László Halász
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Lower Atmosphere ◽  
The Earth

Defining the term of climate, we investigate the role of natural causes and effects of human activities in climate change. The temperature of the Earth is determined by the balance between the amount of radiation energy received from the Sun and that emitted from the surface of the Earth towards the outer space. Greenhouse gases in the atmosphere, including water vapor, carbon dioxide, methane and nitrous oxides, act to make the surface much warmer, because they absorb and emit heat energy in all directions (including downwards), keeping Earth’s surface and lower atmosphere warm. The primary cause of climate change is the burning of fossil fuels, such as oil and coal, which emits greenhouse gases into the atmosphere – primarily carbon dioxide. We give a review about the activity of the Intergovernmental Panel on Climate Change and the United Nations Climate Change Conferences. Shortly investigate the different global climate models and some regional climate models. Finally discuss the results of regional climate model simulations for the Carpathian Basin.

Precipitation Associated with Cyclogenetic Hotspot Regions in the Extratropical Southern Hemisphere: CORDEX-CORE Projections

2020 ◽  
Author(s):  
Michelle Reboita ◽  
Marco Reale ◽  
Rosmeri da Rocha ◽  
Graziano Giuliani ◽  
Erika Coppola ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Winter Season ◽  
Coupled Model ◽  
Global Climate Models ◽  
Precipitation Intensity ◽  
Southeastern Australia

<p>Projections of the precipitation associated with cyclones in the main cyclogenetic regions of the Extratropical Southern Hemisphere domains (Africa - AFR, Australia - AUS and South America - SAM) are here analyzed during the winter season (JJA). The projections were obtained with the Regional Climate Model version 4 (RegCM4) nested in three global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5) under the Representative Concentration Pathway 8.5. RegCM4 simulations were executed with horizontal grid spacing of 25 km and for the period 1979-2100. As reference period, we consider the interval 1995-2014 and as future climate, the period 2080-2099. Cyclones are identified using an algorithm based on the neighbor nearest approach applied to 6 hourly mean sea level pressure (SLP) fields. In SAM and AUS domains, two hotspot regions for cyclogenesis are selected while for AFR only one is considered. First, in each hotspot region, the cyclogeneses are identified and, then, the mean precipitation from the previous day (day<sub>-1</sub>) to the day after (day<sub>+1</sub>) of these processes is calculated. A general negative trend in the cyclone's frequency is projected for the period 2080-2099. However, for the same period, it is projected an increase of precipitation intensity for AFR domain, mainly near the southwestern coast of the continent. In AUS the increase is observed between southeastern Australia and New Zeland, and over north New Zealand. For SAM there is an expansion of the area with a maximum precipitation intensity close to southern Brazil and Uruguay and to the east of 60<sup>o</sup>W near 40<sup>o</sup>S. Summarizing, the precipitation associated with individual cyclones will increase on average in the future (for example 30% in the SAM domain), being the storms less frequent but more intense.</p>

scholarly journals Regional climate change projections from NA-CORDEX and their relation to climate sensitivity

2020 ◽  
Vol 162 (2) ◽  
pp. 645-665
Author(s):  
Melissa S. Bukovsky ◽  
Linda O. Mearns
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Full Range ◽  
Regional Scale ◽  
Global Climate Models ◽  
Continental Scale

Abstract The climate sensitivity of global climate models (GCMs) strongly influences projected climate change due to increased atmospheric carbon dioxide. Reasonably, the climate sensitivity of a GCM may be expected to affect dynamically downscaled projections. However, there has been little examination of the effect of the climate sensitivity of GCMs on regional climate model (RCM) ensembles. Therefore, we present projections of temperature and precipitation from the ensemble of projections produced as a part of the North American branch of the international Coordinated Regional Downscaling Experiment (NA-CORDEX) in the context of their relationship to the climate sensitivity of their parent GCMs. NA-CORDEX simulations were produced at 50-km and 25-km resolutions with multiple RCMs which downscaled multiple GCMs that spanned nearly the full range of climate sensitivity available in the CMIP5 archive. We show that climate sensitivity is a very important source of spread in the NA-CORDEX ensemble, particularly for temperature. Temperature projections correlate with driving GCM climate sensitivity annually and seasonally across North America not only at a continental scale but also at a local-to-regional scale. Importantly, the spread in temperature projections would be reduced if only low, mid, or high climate sensitivity simulations were considered, or if only the ensemble mean were considered. Precipitation projections correlate with climate sensitivity, but only at a continental scale during the cold season, due to the increasing influence of other processes at finer scales. Additionally, it is shown that the RCMs do alter the projection space sampled by their driving GCMs.

Numerical simulations of precipitation and streamflow in current climate and future projections to drainage areas of Brazilian hydroelectric plants

2020 ◽  
Vol 79 (3) ◽  
pp. 219-241
Author(s):  
W Luiz Silva ◽  
MEP Maceira ◽  
OC Rotunno Filho
Keyword(s):  
Climate Models ◽  
Hydrological Model ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Future Projections ◽  
Hydroelectric Plants

Hydroelectric sources are a major contributor to power generation in Brazil. The constant evaluation of climate change impacts is relevant for guiding Brazilian energy policy. This research presents a methodological framework composed of the calibration of a hydrological model and verification of a climate model in the ‘present’ climate (1961-1990), in addition to future scenarios (2011-2100) of precipitation and streamflow for 4 hydroelectric plants in Brazil. For future projections, data from the Eta regional climate model (20 km horizontal resolution) nested within the HadGEM2-ES and MIROC5 global climate models were used. Monthly linear bias correction was applied to the simulations. Future projections were based on IPCC RCP4.5 and 8.5 scenarios. The SMAP hydrological model was adopted on a monthly scale with the addition of a translation parameter that examines the level of dependence of the present streamflow on the previous month's streamflow. The climate and hydrological models satisfactorily capture the distribution of precipitation and streamflow in different Brazilian regions, and effectively represent seasonal variability. Future projections point to a reduction in rainfall and natural streamflow in central-northern Brazil and a slight increase in the southern region. These scenarios should be carefully considered and require constant improvement and research since there are uncertainties associated with atmospheric dynamics and the hydrological cycle.

Transient Future Climate over the Western United States Using a Regional Climate Model

2005 ◽  
Vol 9 (11) ◽  
pp. 1-21 ◽  
Author(s):  
Mark A. Snyder ◽  
Lisa C. Sloan
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Snow Accumulation ◽  
Global Climate Models ◽  
Coupled Gcm ◽  
Fully Coupled

Abstract Regional climate models (RCMs) have improved our understanding of the effects of global climate change on specific regions. The need for realistic forcing has led to the use of fully coupled global climate models (GCMs) to produce boundary conditions for RCMs. The advantages of using fully coupled GCM output is that the global-scale interactions of all components of the climate system (ocean, sea ice, land surface, and atmosphere) are considered. This study uses an RCM, driven by a fully coupled GCM, to examine the climate of a region centered over California for the time periods 1980–99 and 2080–99. Statistically significant increases in mean monthly temperatures by up to 7°C are found for the entire state. Large changes in precipitation occur in northern California in February (increase of up to 4 mm day−1 or 30%) and March (decrease of up to 3 mm day−1 or 25%). However, in most months, precipitation changes between the cases were not statistically significant. Statistically significant decreases in snow accumulation of over 100 mm (50%) occur in some months. Temperature increases lead to decreases in snow accumulation that impact the hydrologic budget by shifting spring and summer runoff into the winter months, reinforcing results of other studies that used different models and driving conditions.

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