Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model

Gao, Xuejie; Shi, Ying; Giorgi, Filippo

doi:10.1080/16742834.2016.1172938

Cited by 116 publications

(87 citation statements)

References 30 publications

(31 reference statements)

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“…These improvements have been demonstrated to be much conducive to the model's simulation of frozen ground conditions (Koven et al, ; Lawrence et al, ). The model has been widely employed to study soil water and heat processes and permafrost dynamics (Gao et al, ; Guo & Wang, ; Lawrence et al, ; Luo et al, ; Wang et al, ).…”

Section: Data Model Experimental Design and Methodsmentioning

confidence: 99%

Simulation of Changes in the Near‐Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

Guo

Wang

et al. 2018

JGR Atmospheres

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Change in the near‐surface soil freeze/thaw cycle is critical for assessments of hydrological activity, ecosystems, and climate change. Previous studies investigated the near‐surface soil freeze/thaw cycle change mostly based on in situ observations and satellite monitoring. Here numerical simulation method is tested to estimate the long‐term change in the near‐surface soil freeze/thaw cycle in response to recent climate warming for its application to predictions. Four simulations are performed at 0.5° × 0.5° resolution from 1979 to 2009 using the Community Land Model version 4.5, each driven by one of the four atmospheric forcing data sets (i.e., one default Climate Research Unit‐National Centers for Environmental Prediction [CRUNCEP] and three newly developed Modern Era Retrospective‐Analysis for Research and Applications, Climate Forecast System Reanalysis, and European Centre for Medium‐Range Weather Forecasts Reanalysis Interim). The observations from 299 weather stations in both Russia and China are employed to validate the simulated results. The results show that all simulations reasonably reproduce the observed variations in the ground temperature, the freeze start and end dates, and the freeze duration (the correlation coefficients range from 0.47 to 0.99, and the Nash‐Sutcliffe efficiencies range from 0.19 to 0.98). Part of the simulations also exactly simulate the trends of the ground temperature, the freeze start and end dates, and the freeze duration. Of the four simulations, the results from the simulation using the CRUNCEP data set show the best overall agreement with the in situ observations, indicating that the CRUNCEP data set could be preferentially considered as the basic atmospheric forcing data set for future prediction. The simulated area‐averaged annual freeze duration shortened by 8.03 days on average from 1979 to 2009, with an uncertainty (one standard deviation) of 0.67 days caused by the different atmospheric forcing data sets. These results address the performance of numerical model in simulating the long‐term changes in the near‐surface soil freeze/thaw cycle and the role of different atmospheric forcing data sets in the simulation, which are useful for the prediction of future freeze/thaw dynamics.

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Section: Data Model Experimental Design and Methodsmentioning

confidence: 99%

Simulation of Changes in the Near‐Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

Guo

Wang

et al. 2018

JGR Atmospheres

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“…Little differences in the projected future changes are evident at 25 or 50 km resolutions, but both show differences compared to the driving GCM change patterns. In addition, for regional climate modeling, many physical parameterization schemes including convective scheme parameterization Gao et al 2016), cloud microphysics parameterizations, and aerosol emission factors and their interactions are also important, especially for precipitation. Therefore, sensitivity experiments making use of the optimized parameters of convection scheme and/or different combinations of various model parameterizations are desirable to identify the best-performing model configuration Gao et al 2016).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…The model is run at its default configuration of 18 vertical sigma layers with two different horizontal resolutions, 50 and 25 km (hereafter referred to as HdR_50km and HdR_25km, respectively). Based on the performance of different convective schemes in RegCM4.4 experiments over China (Gao et al 2016), here we choose the land surface scheme CLM3.5 (Oleson et al 2008) and the convection scheme of Emanuel (Emanuel 1991). Other model physics include computations employing the non-local formulation of Holtslag et al (1990) for planetary boundary layer, resolvable scale precipitation scheme of Pal et al (2000), and the atmospheric radiative transfer scheme from the NCAR community climate model CCM3 (Kiehl et al 1998).…”

Section: Model Experimental Design and Introduction Of Climate Extrementioning

confidence: 99%

Role of resolution in regional climate change projections over China

2017

Self Cite

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This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

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“…On the other hand, CMIP5 global climate models (GCMs) show some limitations in simulating regional climate due to their relatively coarse resolutions (Giorgi et al, 2009). Regional climate models (RCMs) with higher resolutions are demonstrated to outperform global models on the regional scale (Lee and Hong 2014;Wu et al, 2015a;Gao et al, 2012Gao et al, , 2017. Thus, this study aims to project changes in the haze pollution potential in China from the AEC perspective, based on the downscaling simulations of the regional climate model RegCM4 under the RCP4.5 scenario.…”

Section: Introductionmentioning

confidence: 99%

“…The model has the horizontal resolution of 25 km and 18 vertical sigma layers with the top at 50 hPa. Based on the study of Gao et al (2016Gao et al ( , 2017, we selected a suite of physical parameterization schemes suitable for the simulation of the Chinese climate, including the Emanuel convection scheme (Emanuel, 1991), the radiation package of the CCM3 model for atmospheric radiative transfer (Kiehl et al, 1998), the non-local formulation of Holtslag (Holtslag et al, 1990) for the planetary boundary layer, the SUBEX parameterization for large-scale precipitation (Pal et al, 2000), and the CLM3.5 for land surface process (Oleson et al, 2008). The land cover data were updated based on the vegetation atlas of China (Han et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Projected changes in haze pollution potential in China: an ensemble of regional climate model simulations

Han

Zhou

et al. 2017

Atmos. Chem. Phys.

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Abstract. Based on the dynamic downscaling by the regional climate model RegCM4 from three CMIP5 global models under the historical and the RCP4.5 simulations, this article evaluated the performance of the RegCM4 downscaling simulations on the air environment carrying capacity (AEC) and weak ventilation days (WVDs) in China, which are applied to measure haze pollution potential. Their changes during the middle and the end of the 21st century were also projected. The evaluations show that the RegCM4 downscaling simulations can generally capture the observed features of the AEC and WVD distributions over the period 1986-2005. The projections indicate that the annual AEC tends to decrease and the annual WVDs tend to increase over almost the whole country except central China, concurrent with greater change by the late 21st century than by the middle of the 21st century. It suggests that annual haze pollution potential would be enlarged under the RCP4.5 scenario compared to the present. For seasonal change in the four main economic zones of China, it is projected consistently that there would be a higher probability of haze pollution risk over the Beijing-Tianjin-Hebei (BTH) region and the Yangtze River Delta (YRD) region in winter and over the Pearl River Delta (PRD) region in spring and summer in the context of the warming scenario. Over Northeast China (NEC), future climate change might reduce the AEC or increase the WVDs throughout the whole year, which favours the occurrence of haze pollution and thus the haze pollution risk would be aggravated. The relative contribution of different components related to the AEC change further indicates that changes in the boundary layer depth and the wind speed play leading roles in the AEC change over the BTH and NEC regions. In addition to those two factors, the precipitation change also exerts important impacts on the AEC change over the YRD and PRD zones.

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Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model

Cited by 116 publications

References 30 publications

Simulation of Changes in the Near‐Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

Simulation of Changes in the Near‐Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

Role of resolution in regional climate change projections over China

Projected changes in haze pollution potential in China: an ensemble of regional climate model simulations

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