High‐Resolution Climate Projections for the Northeastern United States Using Dynamical Downscaling at Convection‐Permitting Scales

Kömürcü, Müge; Emanuel, Kerry; Huber, Matthew; Acosta, R. P.

doi:10.1029/2018ea000426

Cited by 29 publications

(27 citation statements)

References 66 publications

(87 reference statements)

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“…ere is a tradeoff to be considered between using 6-GCM-Ensemble and CNRM-CM5-2. Although 6-GCM-Ensemble is 15.63% more accurate, using the averages of 6 GCMs will involve ∼6 times more amount of data than using a single GCM and hence will require more time and computational resources, particularly for complex applications of these models, e.g., the use of GCM outputs as inputs for mesoscale models for dynamical downscaling in order to obtain climate simulations and projections at high resolution [28][29][30][31]. Advances in Meteorology…”

Section: Discussionmentioning

confidence: 99%

Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

Kamworapan

Surussavadee

2019

Advances in Meteorology

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This study evaluates the performances of all forty different global climate models (GCMs) that participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for simulating climatological temperature and precipitation for Southeast Asia. Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. The results show that the performances of different GCMs vary greatly. CNRM-CM5-2 performs best among the 40 GCMs, where its total error is 3.25 times less than that of GCM performing worst. The performance of CNRM-CM5-2 is compared with those of the ensemble average of all 40 GCMs (40-GCM-Ensemble) and the ensemble average of the 6 best GCMs (6-GCM-Ensemble) for four categories, i.e., temperature only, precipitation only, land only, and sea only. While 40-GCM-Ensemble performs best for temperature, 6-GCM-Ensemble performs best for precipitation. 6-GCM-Ensemble performs best for temperature and precipitation simulations over sea, whereas CNRM-CM5-2 performs best over land. Overall results show that 6-GCM-Ensemble performs best and is followed by CNRM-CM5-2 and 40-GCM-Ensemble, respectively. The total errors of 6-GCM-Ensemble, CNRM-CM5-2, and 40-GCM-Ensemble are 11.84, 13.69, and 14.09, respectively. 6-GCM-Ensemble and CNRM-CM5-2 agree well with observations and can provide useful climate simulations for Southeast Asia. This suggests the use of 6-GCM-Ensemble and CNRM-CM5-2 for climate studies and projections for Southeast Asia.

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Section: Discussionmentioning

confidence: 99%

Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

Kamworapan

Surussavadee

2019

Advances in Meteorology

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“…The Coupled Model Intercomparison Project (CMIP) is a model comparison plan that collects data from models and simulates recent and long-term projections. Global scale models can also be applied at the regional scale through dynamic downscaling or statistical downscaling methods [46]. Recent research has presented methods to downscale global assumptions and estimates, focusing on quantifying input metrics [47].…”

Section: Methods Outlinementioning

confidence: 99%

Building Regional Sustainable Development Scenarios with the SSP Framework

Shi

Cui

2019

Sustainability

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Climate change is having an increasing effect on human society and ecosystems. The United Nations has established 17 sustainable development goals, one of which is to cope with climate change. How to scientifically explore uncertainties and hazards brought about by climate change in the future is crucial. The new Intergovernmental Panel on Climate Change (IPCC) has proposed shared socioeconomic pathways (SSPs) to project climate change scenarios. SSP has been analyzed globally, but how regions and nations respond to the global climate change and mitigation policies is seldom explored, which do not meet the demand for regional environmental assessment and social sustainable development. Therefore, in this paper, we reviewed and discussed how SSPs were applied to regions, and this can be summarized into four main categories: (1) integrated assessment model (IAM) scenario analysis, (2) SSPs-RCPs-SPAs framework scenario analysis, (3) downscaling global impact assessment model, and (4) regional impact assessment model simulation. The study provides alternative ways to project land use, water resource, energy, and ecosystem service in regions, which can carry out related policies and actions to address climate change in advance and help achieve sustainable development.

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“…The dynamical downscaling is based on the methodology used in Komurcu et al (2018) [22]: We use bias-corrected Community Earth System Model (CESM) v1.0 projections under RCP 8.5 [24,25] as initial and boundary conditions in the Weather Research and Forecasting Model (WRF) v3.6.1 [26] with three nested domains of 36, 12 and 4 km horizontal resolution ( Figure 1) with 40 vertical atmospheric levels. WRF has been extensively used for weather forecasting and atmospheric research as well as for dynamical downscaling of climate reanalyses and climate projections to study historical climate and future climate change (e.g., [22,[27][28][29]). Similar to Komurcu et al (2018) [22], we perform convection-permitting simulations, meaning that we use convection parameterization (Kain-Fritsch (K-F) [30]) only in domains 1 and 2 and no convection parametrization is used in domain 3.…”

Section: Regional Climate Model Configurationmentioning

confidence: 99%

“…Removing convection parameterization is a distinctive feature of our simulations that, to our knowledge, none of the regional climate modeling studies focusing on climate change in KSA and the AP have previously taken advantage of. A discussion of advantages of removing convection parameterization in regional climate models is provided in [22]. Due to the substantial computational resources required to perform regional climate simulations at convection-permitting scales (e.g., [22]), we are only able to downscale a single ESM under a high-impact emission scenario and simulate two months that fall within the dry-hot and wet seasons across KSA [23]: August and November, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…A discussion of advantages of removing convection parameterization in regional climate models is provided in [22]. Due to the substantial computational resources required to perform regional climate simulations at convection-permitting scales (e.g., [22]), we are only able to downscale a single ESM under a high-impact emission scenario and simulate two months that fall within the dry-hot and wet seasons across KSA [23]: August and November, respectively. These months have also historically been shown to contain the most frequent and intense heat and precipitation events in the region, respectively (e.g., [1]).…”

Section: Introductionmentioning

confidence: 99%

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Mid-Century Changes in the Mean and Extreme Climate in the Kingdom of Saudi Arabia and Implications for Water Harvesting and Climate Adaptation

et al. 2020

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The Kingdom of Saudi Arabia (KSA) is a water-scarce region with a dry, desert climate, yet flood-producing precipitation events and heat extremes lead to loss of life and damages to local infrastructure, property and economy. Due to its distinctive natural and man-made spatial features (e.g., coastal features, wadis, agricultural areas) studying changes in the mean climate and extreme events requires higher-resolution climate projections than those available from the current generation of Earth System Models. Here, a high-resolution convection-permitting regional climate model is used to downscale the middle of the 21st century (2041–2050) climate projections of the Community Earth System Model (CESM) under representative concentration pathway (RCP) 8.5 and for a historical time period (2008–2017) focusing on two months (August and November) within KSA’s dry-hot and wet seasons, where extreme events have historically been observed more frequently. Downscaling of climate reanalysis is also performed for the historical time period (2008–2017) to evaluate the downscaling methodology. An increase in the intensity and frequency of precipitation events is found in August by mid-century, particularly along the mountainous western coast of KSA, suggesting potential for water harvesting. Conversely, the northern flank of the Empty Quarter experiences a noticeable reduction in mean and extreme precipitation rates during the wet season. Increasing August heat index is found to particularly make regional habitability difficult in Jeddah by mid-century.

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High‐Resolution Climate Projections for the Northeastern United States Using Dynamical Downscaling at Convection‐Permitting Scales

Cited by 29 publications

References 66 publications

Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

Building Regional Sustainable Development Scenarios with the SSP Framework

Mid-Century Changes in the Mean and Extreme Climate in the Kingdom of Saudi Arabia and Implications for Water Harvesting and Climate Adaptation

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