Dynamical downscaling of CMIP5 global circulation models over CORDEX-Africa with COSMO-CLM: evaluation over the present climate and analysis of the added value

Dosio, Alessandro; Panitz, Hans-Jürgen; Schubert-Frisius, Martina; Lüthi, Daniel

doi:10.1007/s00382-014-2262-x

Cited by 215 publications

(217 citation statements)

References 52 publications

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“…Smaller-scale regional studies and models are invaluable and continue to be developed for the Southern Ocean (e.g., Pinkerton et al, 2010;Smith et al, 2014;Graham et al, 2016), and IPCC model projections may be considered as boundary forcing for downscaled, regional or local fields. Regional climate downscaling is a growing field of research, with CORDEX providing an example (Dosio et al, 2014;Katragkou , 2015), although this needs to be carefully applied with an appreciation of its strengths and weaknesses (Grose et al, 2012;Corney et al, 2013).…”

Section: Key Challenges and Recommendationsmentioning

confidence: 99%

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

et al. 2017

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Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality) we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer), there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

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Section: Key Challenges and Recommendationsmentioning

confidence: 99%

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

et al. 2017

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“…Although RCMs are capable of adding value to the forcing global climate models, there is a limit to what can be corrected by the downscaling of imperfect driving conditions [14]. For example, a study by [23] over the CORDEX Africa domain investigated the ability of CCLM to improve (or not) the GCMs' results using the added value score (−1 ≤ AV ≤ 1) [53] (using a similar set of GCMs used in this study). This study found out that precipitation intensity is not always better reproduced by the RCM, despite some improvements like correction of the GCMs' wet bias, satisfactorily reproducing the bimodal distribution of the annual cycle.…”

Section: Comparison Between Observed and Simulated Extremesmentioning

confidence: 99%

“…Thus, the 1989-2008 common period has been chosen for both RCMs. For GCM-driven runs, RCA4 has been driven by eight CGCMs, while CCLM has been driven by four of the same GCMs used in RCA4 simulations [21,23]. In this study, RCM runs with the four common driving GCMs (i.e., MPI-ESM-LR, HadGEM2-ES, CNRM-CM5 and EC-EARTH (Table 2) -2100 under two emission scenarios (i.e., RCP4.5 and RCP8.5).…”

Section: Model Datamentioning

confidence: 99%

Precipitation Extremes in Dynamically Downscaled Climate Scenarios over the Greater Horn of Africa

et al. 2018

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This study first assesses the performance of regional climate models in the Coordinated Regional Climate Downscaling Experiment (CORDEX) in reproducing observed extreme precipitation indices over the Greater Horn of Africa (GHA) region during 1989-2005. The study then assesses projected changes in these extremes during 2069-2098 compared to 1976-2005. The Regional Climate Model (RCM) simulations are made using two RCMs, with large-scale forcing from four CMIP5 Global limate Models(GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5). We found that RCM simulations have reasonably captured observed patterns of moderate precipitation extreme indices (MPEI). Pattern correlation coefficients between simulated and observed MPEI exceed 0.5 for all except the Simple Daily Intensity Index (SDII). However, significant overestimations or underestimations exist over localized areas in the region. Projected changes in Total annual Precipitation (PRCPTOT) and the annual number of heavy (>10 mm) and very heavy (>20 mm) precipitation days by 2069-2098 show a general north-south pattern, with decreases over the southern half and increases over the northern half of the GHA. These changes are often greatest over parts of Somalia, Eritrea, the Ethiopian highlands and southern Tanzania. Maximum one-and five-day precipitation totals over a year and SDII (ratio of PRCPTOT to rainy days) are projected to increase over a majority of the GHA, including areas where PRCPTOT is projected to decrease, suggesting fewer, but heavier rainy days in the future. Changes in the annual sum of daily precipitation above the 95th and 99th percentiles are statistically significant over a few locations, with the largest projected decrease/increase over Eritrea and northwestern Sudan/Somalia. Projected changes in Consecutive Dry Days (CDD) suggest longer periods of dryness over the majority of the GHA, except the central portions covering northern Uganda, southern South Sudan, southeastern Ethiopia and Somalia. Substantial increases in CDD are located over southern Tanzania and the Ethiopian highlands. The magnitude and the spatial extent of statistically-significant changes in all MPEI increase from RCP4.5 to RCP8.5, and the separation between positive and negative changes becomes clearer under RCP8.5.

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“…Duffy et al 2006;Feser 2006;Sotillo et al 2006;Buonomo et al 2007;Sanchez-Gomez et al 2009;Prömmel et al 2010;Di Luca et al 2012;Kendon et al 2012;Cardoso et al 2013;Chan et al 2013;Pearson et al 2015Torma et al 2015, which affects the fidelity of spatial analysis of added value or wholly precludes it. Winterfeldt and Weisse (2009) and Vautard et al (2013) apply few relative metrics only for individual locations, and Winterfeldt et al (2011) and Dosio et al (2015) on a gridpoint basis.…”

Section: Introductionmentioning

confidence: 99%

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

Ivanov

Warrach‐Sagi

Wulfmeyer

2017

Theor Appl Climatol

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A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as 'field' or 'global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 • grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

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Dynamical downscaling of CMIP5 global circulation models over CORDEX-Africa with COSMO-CLM: evaluation over the present climate and analysis of the added value

Cited by 215 publications

References 52 publications

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Precipitation Extremes in Dynamically Downscaled Climate Scenarios over the Greater Horn of Africa

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

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