Description and evaluation of the <scp>E</scp>arth <scp>S</scp>ystem <scp>R</scp>egional <scp>C</scp>limate <scp>M</scp>odel (<scp>R</scp>eg <scp>CM‐ES</scp>)

Sitz, Lina Elisabet; Sante, Fabio Di; Farneti, Riccardo; Fuentes‐Franco, Ramón; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Cossarini, Gianpiero; Giorgi, Filippo

doi:10.1002/2017ms000933

Cited by 45 publications

(50 citation statements)

References 110 publications

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“…In particular, the fine resolution of RCMs aims to improve the simulation of regional circulations especially in areas characterized by complex terrain and the spatial representation and variability of precipitation, temperature, and climate extremes (e.g., Nikulin et al, 2012;Bukovsky et al, 2013;Giorgi and Gutowski Jr, 2015). Regionally coupled atmosphere-ocean models over the CORDEX-CAM (Central America, Caribbean, and Mexico) domain have also shown improvements by including air-sea interactions leading to better representation of key circulation patterns, such as the Intertropical Convergence Zone (ITCZ) and reduction of precipitation biases in both land and oceans, and in coastal regions (e.g., Li and Misra, 2014;Sitz et al, 2017;Cabos et al, 2019). Table 1 shows some examples of dynamical and empirical statistical downscaling studies carried out in different parts of the CORDEX-CAM domain with the objective of understanding regional climate phenomena, their future changes, and the sensitivity of RCMs to different parameterizations, grid spacing or ocean-atmosphere couplings.…”

Section: Introductionmentioning

confidence: 99%

Climatic trends and regional climate models intercomparison over the CORDEX‐CAM (Central America, Caribbean, and Mexico) domain

Cavazos

Luna‐Niño

Cerezo‐Mota

et al. 2019

Intl Journal of Climatology

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An intercomparison of three regional climate models (RCMs) (PRECIS‐HadRM3P, RCA4, and RegCM4) was performed over the Coordinated Regional Dynamical Experiment (CORDEX)—Central America, Caribbean, and Mexico (CAM) domain to determine their ability to reproduce observed temperature and precipitation trends during 1980–2010. Particular emphasis was given to the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. The three RCMs show negative (positive) temperature (precipitation) biases over the mountains, where observations have more problems due to poor data coverage. Observations from the Climate Research Unit (CRU) and ERA‐Interim show a generalized warming over the domain. The most significant warming trend (≥0.34°C/decade) is observed in the NAM, which is moderately captured by the three RCMs, but with less intensity; each decade from 1970 to 2016 has become warmer than the previous ones, especially during the summer (mean and extremes); this warming appears partially related to the positive Atlantic Multidecadal Oscillation (+AMO). CRU, GPCP, and CHIRPS show significant decreases of precipitation (less than −15%/decade) in parts of the southwest United States and northwestern Mexico, including the NAM, and a positive trend (5–10%/decade) in June–September in eastern Mexico, the MSD region, and northern South America, but longer trends (1950–2017) are not statistically significant. RCMs are able to moderately simulate some of the recent trends, especially in winter. In spite of their mean biases, the RCMs are able to adequately simulate inter‐annual and seasonal variations. Wet (warm) periods in regions affected by the MSD are significantly correlated with the +AMO and La Niña events (+AMO and El Niño). Summer precipitation trends from GPCP show opposite signs to those of CRU and CHIRPS over the Mexican coasts of the southern Gulf of Mexico, the Yucatan Peninsula, and Cuba, possibly due to data limitations and differences in grid resolutions.

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Section: Introductionmentioning

confidence: 99%

Climatic trends and regional climate models intercomparison over the CORDEX‐CAM (Central America, Caribbean, and Mexico) domain

Cavazos

Luna‐Niño

Cerezo‐Mota

et al. 2019

Intl Journal of Climatology

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“…The HD model [52] with a resolution of 0.5 • has already been used for many years in both the global Earth System Models (ESMs) such as MPI-ESM [53], ECHAM5/MPIOM [54,55] and in the regional ESMs, e.g., ROM [56], RegCM-ES [57], and REMO-MPIOM [58].…”

Section: Hydrological Discharge Model Hdmentioning

confidence: 99%

Internal Model Variability of the Regional Coupled System Model GCOAST-AHOI

et al. 2020

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Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September–31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions.

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“…For RCSMs, a few setups exists where a discharge model is included, but its resolution is rarely higher than 0.5 • . Examples comprise the HD model (Hagemann and Dümenil, 1998) at 0.5 • (Elizalde, 2011;Sein et al, 2015;Sitz et al, 2017), TRIP (Oki and Sud, 1998) at 0.5 • (Dell'Aquila et al, 2012;Sevault et al, 2014) and LARSIM (Bremicker, 2000) at 1/6 • over Northern Europe (Lorenz and Jacob, 2014). Several studies exists where a RCM was coupled to a very-high resolution regional HM but currently these studies cover only short periods or relatively small catchments/areas (e.g., Mauser and Bach, 2009;Larsen et al, 2014;Shrestha et al, 2014;Senatore et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

High Resolution Discharge Simulations Over Europe and the Baltic Sea Catchment

2020

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Regional coupled system models require a high-resolution discharge component to couple their atmosphere/land components to the ocean component and to adequately resolve smaller catchments and the day-today variability of discharge. As the currently coupled discharge models usually do not fulfill this requirement, we improved a well-established discharge model, the Hydrological Discharge (HD) model, to be globally applicable at 5 Min. resolution. As the first coupled high-resolution discharge simulations are planned over Europe and the Baltic Sea catchment, we focus on the respective regions in the present study. As no river specific parameter adjustments were conducted and since the HD model parameters depend on globally available gridded characteristics, the model is, in principle, applicable for climate change studies and over ungauged catchments. For the validation of the 5 Min. HD (HD5) model, we force it with prescribed fields of surface and subsurface runoff. As no large-scale observations of these variables exist, they need to be calculated by a land surface scheme or hydrology model using observed or re-analyzed meteorological data. In order to pay regard to uncertainties introduced by these calculations, three different methods and datasets were used to derive the required fields of surface and subsurface runoff for the forcing of the HD5 model. However, the evaluation of the model performance itself is hampered by biases in these fields as they impose an upper limit on the accuracy of simulated discharge. 10-years simulations (2000-2009) show that for many European rivers, where daily discharge observations were available for comparison, the HD5 model captures the main discharge characteristics reasonably well. Deficiencies of the simulated discharge could often be traced back to deficits in the various forcing datasets. As direct anthropogenic impact on the discharge, such as by regulation or dams, is not regarded in the HD model, those effects can generally not be simulated. Thus, discharges for many heavily regulated rivers in Scandinavia or for the rivers Volga and Don are not well represented by the model. The comparison of the three sets of simulated discharges indicates that the HD5 model is suitable to evaluate the terrestrial hydrological cycle of climate models or land surface models, especially with regard to the separation of throughfall (rain or snow melt) into surface and subsurface runoff.

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Description and evaluation of the Earth System Regional Climate Model (Reg CM‐ES)

Cited by 45 publications

References 110 publications

Climatic trends and regional climate models intercomparison over the CORDEX‐CAM (Central America, Caribbean, and Mexico) domain

Climatic trends and regional climate models intercomparison over the CORDEX‐CAM (Central America, Caribbean, and Mexico) domain

Internal Model Variability of the Regional Coupled System Model GCOAST-AHOI

High Resolution Discharge Simulations Over Europe and the Baltic Sea Catchment

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