scholarly journals Assessment of the performance of CMIP5 and CORDEX-SA models over the drought-prone Bundelkhand region, India

2020 ◽  
Vol 11 (S1) ◽  
pp. 133-144 ◽  
Author(s):  
Ankur Vishwakarma ◽  
Mahendra Kumar Choudhary ◽  
Mrityunjay Singh Chauhan

Abstract The present study evaluates the reliability of the latest generation five best general circulation models (GCMs) under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their corresponding regional climate models (RCMs) of Coordinated Regional Climate Downscaling Experiment (CORDEX) for the Bundelkhand region in central India. The study is performed on a microscale due to frequent drought events and more climate susceptibility in the study region. Observed daily precipitation data of 35 years (1971–2005) from the Indian Meteorological Department (IMD) have been chosen to check the performance of the models. Bilinear interpolation has been adopted to prepare all the data to obtain them on a common grid platform at a half-degree (0.5° × 0.5°) resolution. The data of the models have been bias-corrected using quantile mapping. Uncertainty of the models has been assessed using Nash–Sutcliffe efficiency (NSE), coefficient of determination (r2) and a modified method known as skill score (SS). The study concluded that the bias-corrected GCMs played a better role than the CORDEX RCMs for the Bundelkhand region. Earth System Model, ESM-2M of the Geophysical Fluid Dynamics Laboratory (GFDL) has shown better accuracy than all the CORDEX RCMs and their driving GCMs for the study region.

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1032 ◽  
Author(s):  
Ariel Wang ◽  
Francina Dominguez ◽  
Arthur Schmidt

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.


2006 ◽  
Vol 19 (21) ◽  
pp. 5637-5651 ◽  
Author(s):  
Willem P. Sijp ◽  
Michael Bates ◽  
Matthew H. England

Abstract Convective overturning arising from static instability during winter is thought to play a crucial role in the formation of North Atlantic Deep Water (NADW). In ocean general circulation models (OGCMs), a strong reduction in convective penetration depth arises when horizontal diffusion (HD) is replaced by Gent and McWilliams (GM) mixing to model the effect of mesoscale eddies on tracer advection. In areas of sinking, the role of vertical tracer transport due to convection is largely replaced by the vertical component of isopycnal diffusion along sloping isopycnals. Here, the effect of this change in tracer transport physics on the stability of NADW formation under freshwater (FW) perturbations of the North Atlantic (NA) in a coupled model is examined. It is found that there is a significantly increased stability of NADW to FW input when GM is used in spite of GM experiments exhibiting consistently weaker NADW formation rates in unperturbed steady states. It is also found that there is a significant increase in NADW stability upon the introduction of isopycnal diffusion in the absence of GM. This indicates that isopycnal diffusion of tracer rather than isopycnal thickness diffusion is responsible for the increased NADW stability observed in the GM run. This result is robust with respect to the choice of isopycnal diffusion coefficient. Also, the NADW behavior in the isopycnal run, which includes a fixed background horizontal diffusivity, demonstrates that HD is not responsible in itself for reducing NADW stability when simple horizontal diffusion is used. Our results suggest that care should be taken when interpreting the results of coarse grid models with regard to NADW sensitivity to FW anomalies, regardless of the choice of mixing scheme.


2021 ◽  
Author(s):  
Thibault Lemaitre-Basset ◽  
Ludovic Oudin ◽  
Guillaume Thirel ◽  
Lila Collet

Abstract. The increasing air temperature in a changing climate will impact actual evaporation and have consequences for water resources management in energy-limited regions. In many hydrological models, evaporation is assessed by a preliminary computation of potential evaporation (PE) representing the evaporative demand of the atmosphere. Therefore, in impact studies the quantification of uncertainties related to PE estimation, which can arise from different sources, is crucial. Indeed, a myriad of PE formulations exist and the uncertainties related to climate variables cascade into PE computation. So far, no consensus has emerged on the main source of uncertainty in the PE modelling chain for hydrological studies. In this study, we address this issue by setting up a multi-model and multi-scenario approach. We used seven different PE formulations and a set of 30 climate projections to calculate changes in PE. To estimate the uncertainties related to each step of the PE calculation process (namely Representative Concentration Pathways, General Circulation Models, Regional Climate Models and PE formulations), an analysis of variance decomposition (ANOVA) was used. Results show that PE would increase across France by the end of the century, from +40 to +130 mm/year. In ascending order, uncertainty contributions by the end of the century are explained by: PE formulations (below 10 %), then RCPs (above 20 %), RCMs (30–40 %) and GCMs (30–40 %). Finally, all PE formulations show similar future trends since climatic variables are co-dependent to temperature. While no PE formulation stands out from the others, in hydrological impact studies the Penman-Monteith formulation may be preferred as it is representative of the PE formulations ensemble mean and allows accounting for climate and environmental drivers co-evolution.


1997 ◽  
Vol 25 ◽  
pp. 400-406 ◽  
Author(s):  
Martin Beniston ◽  
Wilfried Haeberli ◽  
Martin Hoelzle ◽  
Alan Taylor

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.


Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 723 ◽  
Author(s):  
Erzsébet Kristóf ◽  
Zoltán Barcza ◽  
Roland Hollós ◽  
Judit Bartholy ◽  
Rita Pongrácz

Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises.


Author(s):  
Antero Ollila

The research article of Gillett et al. was published in Nature Climate Change (NCC) in March 2021. The objective of the NCC study was to simulate human-induced forcings to warming by applying 13 CMIP6 (Coupled Model Intercomparison Project Phase 6) climate models. NCC did not accept the author’s remarks as a “Matters arising” article. The purpose of this article is to detail the original three remarks and one additional remark: 1) the discrepancy between the graphs and reported numerical values, 2) the forcings of aerosols and clouds, 3) the positive water feedback, and 4) the calculation basis of the Paris agreement. The most important finding is that General Circulation Models (GCMs) used in simulations omit the significant shortwave anomaly from 2001 to 2019, which causes a temperature error of 0.3°C according to climate change physics of Gillett et al. For the year 2019, this error is 0.8°C showing the magnitude of shortwave anomaly impact. The main reason for this error turns out to be the positive water feedback generally applied in climate models. The scientific basis of the Paris climate agreement is faulty for the same reason.


2021 ◽  
Author(s):  
Abraham Torres-Alavez ◽  
Fred Kucharski ◽  
Erika Coppola ◽  
Lorena Castro

<p>Using high-spatial-resolution regional simulations from the global program, Coordinated Regional Climate Downscaling Experiment-Coordinated Output for Regional Evaluations (CORDEX-CORE), we examine the capability of regional climate models (RCMs) to represent the El Niño–Southern Oscillation (ENSO) precipitation and surface air temperature teleconnections during boreal winter (December-February). This study uses CORDEX-CORE simulations for the period 1975-2004 with two RCMs, the RegCM4 and REMO, driven by three General Circulation Models (GCMs) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5). The RCM simulations were run at a 25-km grid spacing over Africa, Central and North America, South Asia and South America.</p><p>The teleconnection patterns are calculated in the reanalysis data (observations), and these results are compared to those of the ensemble and individual simulations of both the GCM and RCM. Linear regression is used to calculate the teleconnection patterns and a permutation test is applied to calculate the statistical significance of the regression coefficients. Results show that overall, the ENSO signal from the GCMs is preserved in the ensemble and the individual RCM simulations over most of the regions analyzed. These reproduced most of the observed regional responses to ENSO forcing and showing teleconnection signals statistically significant at the 95% level. Furthermore, in some cases, the ensemble and individual simulations of RCMs improve the spatial pattern and the amplitude of the ENSO precipitation response of the GCMs, particularly over southern Africa, the Arabian-Asian region, and the region composed of Mexico and the southern United States. These results show the potential value of the GCM-RCM downscaling systems not only in the context of climate change research but also for seasonal to annual prediction.</p>


2018 ◽  
Vol 31 (22) ◽  
pp. 9151-9173 ◽  
Author(s):  
Richard Davy

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.


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