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RegCM4区域气候模式21世纪中国气候变化集合预估数据集 Datasets of RegCM4 ensemble climate change projections

[发布日期: 2022-01-20 浏览量 1405]

文献引用】Citation: Gao XJ, Wu J, Shi Y, et al. Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations [J]. Atmospheric and Oceanic Science Letters, 2018, 11(04): 291-299. doi: 10.1080/ 16742834.2018.1471578.

【数据下载,请联系 Contact for download: wangjun@mail.iap.ac.cn

【数据制作方法】Method

      所进行的试验中采用的区域气候模式(RCM),为国际理论物理中心的RegCM4 (Giorgi et al., 2012),模拟区域为联合区域气候降尺度协同试验第二阶段东亚(CORDEX Phase II East Asia)的推荐区域,覆盖整个中国及其周边的东亚地区。模式的水平分辨率为25 km,模式垂直方向是18层,层顶高度为10 hPa,模式的参数设置按照Gao et al. (2016, 2017),并根据韩振宇等 (2015) 更新了中国土地覆盖数据,以更好地描述下垫面植被状况。

      RegCM4所需的初始和侧边界条件由CMIP5全球气候模式HadGEM2-ES, MPI-ESM-MR, NorESM1-M和EC-EARTH, CSIRO-Mk3.6的模拟结果提供。模拟包括了当前观测到的温室气体浓度时段(1968−2005)以及在RCP2.6(仅有前3个模式的驱动结果),RCP4.5和RCP8.5情景下未来的时段(2006−2099)。Gao et al. (2018) 基于该数据,分析了气候变化对中国未来热舒适度的影响。RegCM4输出数据使用双线性方法,插值到了0.25°×0.25°(经纬度)格点上。

      The RCM employed is the International Center for Theoretical Physics (ICTP) Regional Climate Model version 4 (RegCM4, Giorgi et al., 2012). The domain used is the Coordinated Regional Climate Downscaling Experiment (CORDEX) Phase II East Asia domain, covering whole of China and its surrounding East Asia areas. The model is run at 25 km gird spacing, with its standard configuration of 18 vertical sigma layers with a model top at 10 hPa. Configuration of the model follows Gao et al. (2016, 2017), with land cover data over China was updated as reported by Han et al. (2015) to better represent the realistic vegetation.

      The initial and lateral boundary conditions needed to drive RegCM4 are derived from the CMIP5 models of HadGEM2-ES, MPI-ESM-MR, NorESM1-M, and EC-EARTH, CSIRO-Mk3.6. The simulations covers the period 1968−2005 for the present day with observed greenhouse gas concentrations, and 2006−2099 for future under RCP2.6 (the former three models only), RCP4.5, RCP8.5 pathways. Analysis of future changes in thermal comfort conditions have been conducted based on the set of simulations by Gao et al. (2018).

      The RegCM4 outputs are bilinearly interpolated to the regular grids of 0.25°×0.25° (latitude-longitude).

【数据简介】Data description

  区域范围 Region:69.75-140.25°E,14.75-55.25°N

  格点数 Grids: 283(东西方向 west-east)×163(南北方向 north-south)

  水平分辨率 Horizontal resolution: 0.25°×0.25° (经-纬度 latitude-longitude)

  时间分辨率 Time scale: 日平均 daily mean

  时间段 Preiod: 1980年1月1日~2098年12月31日  January 1, 1980–December 31, 2098

  模式日历(各全球模式及其驱动下RegCM4的日历) Model calendar (for GCMs and thus the driven RegCM4): 

       CSIRO-Mk3-6-0 and NorESM1-M: 365d/yr; EC-EARTH and MPI-ESM-MR: 365d/yr (366 for leap years); HadGEM2-ES: 360d/yr (30d/month)

  要素 Variables: 平均气温、降水量、最高气温、最低气温 daily mean temperature, precipitation, daily maximum and minimum temperatures

  温室气体排放情景 Emission scenario:RCP2.6(仅3个模拟 three simulations only), RCP4.5, RCP8.5

【文件名和变量说明】File names and variables

◆文件名 Format of file names: 数据文件名格式为:A_day_B_historical_1981-2005.nc,A_day_B_C_2006-2098.nc

          A为要素代码,B为模式名称,C为排放情景  A for variables, B for model names, C for emission scenarios

◆要素名称: Variable names

            tas: 平均气温 mean temperature (°C)

            pr: 降水量 precipitation (kg/m2s=mm/s,mm by×24×3600)

            tasmax: 日最高气温 daily maximum temperature (°C)

            tasmin: 日最低气温 daily minimum temperature (°C)

【项目资助】Funding

中国科学院战略性先导科技专项(A类)“东南亚国家气候与水资源变化”(编号:XDA20060401)和国家重点研发计划项目“中国北方地区极端气候的变化及成因研究”(编号:2016YFA0600704)共同资助

Jointly supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA2006040102) and National Key Research and Development Program (Grant No. 2016YFA0600704)

【主要参考文献】References

韩振宇, 高学杰, 石英, 等. 中国高精度土地覆盖数据在RegCM4/CLM模式中的引入及其对区域气候模拟影响的分析 [J]. 冰川冻土, 2015, 37(04): 857-866. Han ZY, Gao XJ, Shi Y, et al. Development of Chinese high resolution land cover data for the RegCM4/CLM and its impact on regional climate simulation [J]. Journal of Glaciology and Geocryology, 2015, 37(4): 857-866.

Gao XJ, Shi Y, Giorgi F. Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model [J]. Atmospheric and Oceanic Science Letters, 2016, 9(4): 246-254. doi: 10.1080/16742834.2016.1172938.

Gao XJ, Shi Y, Han ZY, et al. Performance of RegCM4 over major river basins in China [J]. Advances in Atmospheric Sciences, 2017, 34(4): 441-455. doi: 10.1007/s00376-016-6179-7.

Giorgi F, Coppola E, Solmon F, et al. RegCM4: model description and preliminary tests over multiple CORDEX domains [J]. Climate Research, 2012, 52(1): 7-29. doi:10.3354/cr01018.