The more extreme nature of U.S. warm season climate in the recent observational record and two “well‐performing” dynamically downscaled CMIP3 models

Chang, Hsin I.; Castro, Christopher L.; Carrillo, Carlos M.; Domínguez, Francina

doi:10.1002/2015jd023333

Cited by 22 publications

(21 citation statements)

References 78 publications

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“…We also repeated the dynamical downscaling of an atmospheric reanalysis originally described in [62] with the modified KF CPS. Similar to the NWP-type simulations of NAME IOP2, use of the modified KF CPS yields results that compare better with observed precipitation, alleviating well-known positive biases in the regional model-simulated rainfall over the SMO, for example as described in [21].…”

Section: Summary and Discussionmentioning

confidence: 99%

“…In addition to the simulation of NAME IOP-2, we also repeat the dynamical downscaling of the NCEP-NCAR Reanalysis with WRF as recently described in [62] but with the modified KF CPS for continuous 60-year period 1950-2010. This regional climate model (RCM) simulation encompasses a domain of the contiguous U.S. and Mexico at a grid spacing of 35 km.…”

Section: Regional Climate Model Simulationmentioning

confidence: 99%

“…As described earlier in the methods section, the dynamical downscaling of the NCEP-NCAR reanalysis for the period 1950-2010 described in [62] is repeated with use of the modified KF CPS. This RCM simulation is categorized as type 2 dynamical downscaling, from the classification of [57], in which the initial conditions within the regional model are forgotten and lateral boundary forcing may be considered from a retrospective atmospheric reanalysis, as a "perfect" representation of the observed atmosphere.…”

Section: Value Added In a Regional Climate Modeling Experimentsmentioning

confidence: 99%

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Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

et al. 2018

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Abstract:A commonly noted problem in the simulation of warm season convection in the North American monsoon region has been the inability of atmospheric models at the meso-β scales (10 s to 100 s of kilometers) to simulate organized convection, principally mesoscale convective systems. With the use of convective parameterization, high precipitation biases in model simulations are typically observed over the peaks of mountain ranges. To address this issue, the Kain-Fritsch (KF) cumulus parameterization scheme has been modified with new diagnostic equations to compute the updraft velocity, the convective available potential energy closure assumption, and the convective trigger function. The scheme has been adapted for use in the Weather Research and Forecasting (WRF). A numerical weather prediction-type simulation is conducted for the North American Monsoon Experiment Intensive Observing Period 2 and a regional climate simulation is performed, by dynamically downscaling. In both of these applications, there are notable improvements in the WRF model-simulated precipitation due to the better representation of organized, propagating convection. The use of the modified KF scheme for atmospheric model simulations may provide a more computationally economical alternative to improve the representation of organized convection, as compared to convective-permitting simulations at the kilometer scale or a super-parameterization approach.

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Section: Summary and Discussionmentioning

confidence: 99%

Section: Regional Climate Model Simulationmentioning

confidence: 99%

Section: Value Added In a Regional Climate Modeling Experimentsmentioning

confidence: 99%

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Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

et al. 2018

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“…There are few studies in Mexico that have evaluated empirical–statistical ensembles of GCMs at regional scale (e.g., Montero‐Martínez and Pérez‐López, ; Cavazos and Arriaga‐Ramirez, ; Magaña et al ., ; Cook and Seager, ; Torres‐Alavez et al ., ). Few others have used dynamical downscaling (Diro et al ., ; Bukovsky et al ., ; ; Fuentes‐Franco et al ., ; ; Chang et al ., ; Cerezo‐Mota et al ., ) to better understand present climate and its future changes. In Central America and the Caribbean region there are also examples of empirical–statistical (e.g., Hidalgo et al ., ; Jones et al ., ) and dynamical (e.g., Karmalkar et al ., ; Martínez‐Castro et al ., ) downscaling studies.…”

Section: Introductionmentioning

confidence: 99%

Climate change projections from Coupled Model Intercomparison Project phase 5 multi‐model weighted ensembles for Mexico, the North American monsoon, and the mid‐summer drought region

Colorado-Ruiz

Cavazos

Salinas

et al. 2018

Intl Journal of Climatology

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Two versions of the “reliability ensemble averaging” (REA and REA Xu) method and an unweighted mean were used to generate multi‐model ensembles of 14 general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) for a baseline (1971–2000) period and future scenarios (RCP4.5 and RCP8.5) for the 21st century. To test the consistency of the REA ensembles at different scales, one ensemble was area‐averaged at regional scale and two were obtained at 50‐km gridpoints. Climatic metrics of temperature and precipitation during the baseline period served to evaluate the performance of the GCMs and the ensembles in the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. The metrics of the three REA ensembles are very similar among them in each region and show a better performance than the unweighted multi‐model ensemble (U‐MME). The majority of the GCMs overestimate winter precipitation in the NAM and fail to retract the end of the monsoon in autumn; REA ensembles reduce this overestimation. All ensembles capture well the MSD's double peak of rainfall, but underestimate summer precipitation. According to all ensembles, temperature increases of 1.5–2 °C in the two regions may be reached between 2035 and 2055 relative to the baseline, and by 2070–2099 temperature (precipitation) in Mexico may increase (decrease) between 2° C (5%) and 5.8 °C (10%) in the RCP4.5 and RCP8.5 scenarios, respectively. Annual changes of precipitation show a north (positive) and south of 35°N (negative) pattern. The largest impacts are expected during summer with a possible decrease of ~13% (up to −1.5 mm/day), especially in southern Mexico, Central America, and the Caribbean, while autumn precipitation may slightly increase. Future projections from the REA Xu (by gridpoint) ensemble show spatial patterns similar to the U‐MME, but with more regional detail, which could be an added value for regional climate impact studies.

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“…During this time of year, "billion-dollar disaster events" as defined in the National Centers for Environmental Information database, caused by severe weather, heat waves and drought, wildfire, and flooding are likely to become more extreme in an anthropogenically driven warming global climate (Meehl et al, 2000;Min et al, 2011). Changes in global precipitation in recent observational records generally validate the hypothesis "wet gets wetter, dry gets drier" (Hsu et al, 2011;Wang et al, 2012;Chang et al, 2015). The idea basically suggests increasing precipitation when it is climatologically preferred to occur (e.g., near-equatorial regions) and decreasing it where it is not (e.g., subtropical land areas).…”

Section: Introductionmentioning

confidence: 88%

Credibility of Convection-Permitting Modeling to Improve Seasonal Precipitation Forecasting in the Southwestern United States

et al. 2019

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Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a subdaily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.

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The more extreme nature of U.S. warm season climate in the recent observational record and two “well‐performing” dynamically downscaled CMIP3 models

Cited by 22 publications

References 78 publications

Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

Climate change projections from Coupled Model Intercomparison Project phase 5 multi‐model weighted ensembles for Mexico, the North American monsoon, and the mid‐summer drought region

Credibility of Convection-Permitting Modeling to Improve Seasonal Precipitation Forecasting in the Southwestern United States

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