Regional Climate Model Evaluation System powered by Apache Open Climate Workbench v1.3.0: an enabling tool for facilitating regional climate studies

Lee, Huikyo; Goodman, A.; McGibbney, L. J.; Waliser, Duane E.; Kim, Jinwon; Loikith, Paul C.; Gibson, Peter B.; Massoud, Elias

doi:10.5194/gmd-11-4435-2018

Cited by 18 publications

(15 citation statements)

References 43 publications

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“…For example, if the model spread is large enough, then the expected change, as reported by a multi-model ensemble mean, may not be meaningful. Different models can present very different results, and the spread of the multi-model ensemble can inform the significance of the future change results [79,80]. To this end, we show in Figure 10 the spread of the multi-model ensemble for the CMIP5 simulations of AR frequency and mean daily precipitation for the historical (blue), RCP8.5 (red), and the projected differences (green), presented as latitudinal averages.…”

Section: Statistical Significance Of Expected Changesmentioning

confidence: 99%

Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)

Massoud

Guan

et al. 2020

Water

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This study investigates the historical climatology and future projected change of atmospheric rivers (ARs) and precipitation for the Middle East and North Africa (MENA) region. We use a suite of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5, historical and RCP8.5 scenarios) and other observations to estimate AR frequency and mean daily precipitation. Despite its arid-to-semi-arid climate, parts of the MENA region experience strong ARs, which contribute a large fraction of the annual precipitation, such as in the mountainous areas of Turkey and Iran. This study shows that by the end of this century, AR frequency is projected to increase (~20–40%) for the North Africa and Mediterranean areas (including any region with higher latitudes than 35 N). However, for these regions, mean daily precipitation (i.e., regardless of the presence of ARs) is projected to decrease (~15–30%). For the rest of the MENA region, including the Arabian Peninsula and the Horn of Africa, minor changes in AR frequency (±10%) are expected, yet mean precipitation is projected to increase (~50%) for these regions. Overall, the projected sign of change in AR frequency is opposite to the projected sign of change in mean daily precipitation for most areas within the MENA region.

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Section: Statistical Significance Of Expected Changesmentioning

confidence: 99%

Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)

Massoud

Guan

et al. 2020

Water

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“…Massoud et al 2019bMassoud et al , 2020, as well as to characterize uncertainty inherent in the climate system due to internal variability (e.g., Kay et al 2015). These ensembles provide an important resource for examining and evaluating the models that cause uncertainties in future climate projections (Lee et al 2018). Often, when creating multimodel averages, projections of the future from each model are considered to be equally likely, without accounting for model skill or for the fact that some models are very similar to other models in the archive, which could lead to a biased weighting (Collins et al 2013;Espinoza et al 2018;Massoud et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States

Massoud

Lee

Gibson

et al. 2020

Journal of Hydrometeorology

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This study utilizes Bayesian Model Averaging (BMA) as a framework to constrain the spread of uncertainty in climate projections of precipitation over the contiguous United States (CONUS). We use a subset of historical model simulations and future model projections (RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We evaluate the representation of five precipitation summary metrics in the historical simulations using observations from the NASA Tropical Rainfall Measuring Mission (TRMM) satellites. The summary metrics include mean, annual and interannual variability, and maximum and minimum extremes of precipitation. The estimated model average produced with BMA is shown to have higher accuracy in simulating mean rainfall than the ensemble mean (RMSE of 0.49 for BMA vs 0.65 for ensemble mean), and a more constrained spread of uncertainty with roughly a third of the total uncertainty than is produced with the multi-model ensemble. The results show that, by the end of the century, the mean daily rainfall is projected to increase for most of the East Coast and the Northwest, may decrease in the Southern US, and with little change expected for the Southwest. For extremes, the wettest year on record is projected to become wetter for the majority of CONUS and the driest year to become drier. We show that BMA offers a framework to more accurately estimate and to constrain the spread of uncertainties of future climate, such as precipitation changes over CONUS.

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“…The inclusion of this simple diagnostic in the Earth System Model eValuation Tool-ESMValTool (Eyring et al, 2016) and Regional Climate Model Evaluation System-RCMES (Lee et al, 2018) will be very useful for intercomparison of the rainfall variability over different TRB regions in the CMIP6 and CORDEX models. Practical application of the TRB indices can be very wide and includes (a) describing precipitation climatologies in the tropics and sub-tropics, (b) estimating observational uncertainties, (c) evaluating global and regional climate models and (d) assessing projected changes in tropical precipitation.…”

Section: Discussionmentioning

confidence: 99%

A simple set of indices describing the Tropical Rain Belt over central and southern Africa

Nikulin

2019

Atmospheric Science Letters

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Understanding the variability of the Tropical Rain Belt (TRB) in Africa is a challenging task due to complex interactions among global, regional and local drivers of rainfall. A simple method that provides a set of three indices describing large‐scale spatial–temporal characteristics of the TRB over central and southern Africa is introduced. The method is based on approximation of a meridional cross‐section of monthly mean precipitation by the Gaussian function. The three parameters of the Gaussian function correspond to the three TRB indices, namely: intensity, location and width. It is shown how the TRB indices can be used for describing the climatology of the TRB, for estimating observational uncertainties, and for evaluating the ERA‐Interim and ERA5 reanalyses against observations. Simplicity and flexibility of the method allow using the TRB indices for a wide range of applications, including evaluation of climate models and assessment of projected climate change in tropical rainfall.

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Regional Climate Model Evaluation System powered by Apache Open Climate Workbench v1.3.0: an enabling tool for facilitating regional climate studies

Cited by 18 publications

References 43 publications

Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)

Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)

Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States

A simple set of indices describing the Tropical Rain Belt over central and southern Africa

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