北美当前和预测的气候数据（CMIP6 ）

举报
此星光明 发表于 2023/06/04 07:03:13 2023/06/04
【摘要】 ​北美当前和预测的气候数据（CMIP6 ）¶开发大气-海洋环流模型 (AOGCM) 是为了在广泛的时间尺度上模拟气候变率，并且经常在耦合模拟和数据同化模式下进行测试。 您可以在此处阅读有关 AOGCM 和 CMIP6 的更多信息。 此页面上的数据集由 AdaptWest 开发，该项目由 Wilburforce 基金会资助，旨在为气候适应规划开发信息资源。前言 – 床长人工智能教程数据是使用 ...

​

北美当前和预测的气候数据（CMIP6 ）¶
开发大气-海洋环流模型 (AOGCM) 是为了在广泛的时间尺度上模拟气候变率，并且经常在耦合模拟和数据同化模式下进行测试。 您可以在此处阅读有关 AOGCM 和 CMIP6 的更多信息。 此页面上的数据集由 AdaptWest 开发，该项目由 Wilburforce 基金会资助，旨在为气候适应规划开发信息资源。前言 – 床长人工智能教程

数据是使用 ClimateNA 软件生成的。CMIP6: the next generation of climate models explained - Carbon Brief ClimateNA 使用来自 PRISM 和 WorldClim 的当前气候数据，并缩减了耦合模型比对项目第 6 阶段 (CMIP6) 数据库中对应于第六次 IPCC 评估报告的未来预测数据。

集合预测是来自 13 个 CMIP5 模型（下表）的平均预测，这些模型被选为代表类似 AOGCM 的所有主要集群。 除了集合预测之外，还提供了代表较大集合的 9 个单独的 AOGCM（下表）的数据。 选择了九个单独的模型来代表所有主要的类似 AOGCM 集群。 使用更广泛的 13 个 AOGCM 集来创建集合数据。 与单个 AOGCM 的预测相比，此处还提供了更大范围的时间段和情景的集合预测。

AOGCM Ensemble Models AOGCM Individual Models
ACCESS-ESM1-5 ACCESS-ESM1-5
BCC-CSM2-MR
CNRM-ESM2-1 CNRM-ESM2-1
CanESM5
EC-Earth3 EC-Earth3
GFDL-ESM4 GFDL-ESM4
GISS-E2-1-G GISS-E2-1-G
INM-CM5-0
IPSL-CM6A-LR
MIROC6 MIROC6
MPI-ESM1-2-HR MPI-ESM1-2-HR
MRI-ESM2-0 MRI-ESM2-0
UKESM1-0-LL UKESM1-0-LL



Data citation

AdaptWest Project. 2022. Gridded current and projected climate data for North America at 1km resolution,
generated using the ClimateNA v7.30 software (T. Wang et al., 2022). Available at adaptwest.databasin.org.

Paper citation

You can read the paper here and cite as as below

AdaptWest Project. 2022. Gridded current and projected climate data for North America at 1km resolution, generated using the ClimateNA v7.30 software (T. Wang et al., 2022). Available at adaptwest.databasin.org.
For further information and citation refer to:

Wang, T., A. Hamann, D. Spittlehouse, C. Carroll. 2016. Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America. PLoS One 11(6): e0156720 https://doi.org/10.1371/journal.pone.0156720

Mahony, C.R., T. Wang, A. Hamann, and A.J. Cannon. 2022. A global climate model ensemble for downscaled monthly climate normals over North America. International Journal of Climatology. 1-21. https://doi.org/10.1002/joc.7566

The current climatic variables included in the datasets for climate normals, AOGCM models and AOGCM ensemble model are listed below

Monthly Variables Description
tmin minimum temperature for a given month (°C)
tmax maximum temperature for a given month (°C)
tave mean temperature for a given month (°C)
ppt total precipitation for a given month (mm)


Earth Engine Snippet Climate variables

var climate_models_ppt = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Models_ppt");
var climate_models_tave = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Models_tave");
var climate_models_tmax = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Models_tmax");
var climate_models_tmin = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Models_tmin");
var climate_normals_ppt = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Normals_ppt");
var climate_normals_tave = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Normals_tave");
var climate_normals_tmax = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Normals_tmax");
var climate_normals_tmin = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Normals_tmin");
var aogcm_ensemble_ppt = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/AOGCM-ensemble_ppt");
var aogcm_ensemble_tave = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/AOGCM-ensemble_tave");
var aogcm_ensemble_tmax = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/AOGCM-ensemble_tmax");
var aogcm_ensemble_tmin = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/AOGCM-ensemble_tmin");

Sample Code: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:weather-climate/CMIP6-CURRENT-FUTURE-SCENARIOS

 Google Earth Engine v7.3 的后期处理¶
所有 9 个单独的 AOGCM 模型都添加到与每个气候变量相关的集合中，并命名为 Climate-Models_（变量名称）。 合奏模型与气候平均值一起被摄取。
AOGCM 系综模型和单个模型都有日期范围和排放情景类型 emission_scenario，开始和结束日期作为属性添加。
由于 Climate-Models-(Variable Name) 集合由 9 个单独的模型组成，另一个元数据字段被添加到这些集合中，即 model 以按模型名称过滤。
由于所有气候变量都是每月的，因此将一个名为 month 的额外元数据添加到气候平均值、合奏和单个模型集合中，以便根据需要进一步分割数据。
模型的版本号和 20 年和 30 年月度变量的周期现在包含在元数据中。

​


Earth Engine Snippet Bioclimatic variables

var climate_models_bioclim = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Models_bioclim");
var aogcm_ensemble_bioclim = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/AOGCM-ensemble_bioclim");
var climate_normals_bioclim = ee.ImageCollection("projects/sat-io/open-datasets/CMIP6-scenarios-NA/Climate-Normals_bioclim");

Sample Code: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:weather-climate/CMIP6-CURRENT-FUTURE-BIOCLIMATIC

There are a total of 33 bioclimatic variables included for the collections and models , the reference table is included below and you can filter using the metadata property bioclim_variable and the property names from the table.

Bioclimatic Variables Description
MAT mean annual temperature (°C)
MWMT mean temperature of the warmest month (°C)
MCMT mean temperature of the coldest month (°C)
TD difference between MCMT and MWMT, as a measure of continentality (°C)
MAP mean annual precipitation (mm)
MSP mean summer (May to Sep) precipitation (mm)
AHM annual heat moisture index, calculated as (MAT+10)/(MAP/1000)
SHM summer heat moisture index, calculated as MWMT/(MSP/1000)
DD_0 degree-days below 0°C (chilling degree days)
DD5 degree-days above 5°C (growing degree days)
DD_18 degree-days below 18°C
DD18 degree-days above 18°C
NFFD the number of frost-free days
FFP frost-free period
bFFP the julian date on which the frost-free period begins
eFFP the julian date on which the frost-free period ends
PAS precipitation as snow (mm)
EMT extreme minimum temperature over 30 years
EXT extreme maximum temperature over 30 years
Eref Hargreave's reference evaporation
CMD Hargreave's climatic moisture index
MAR mean annual solar radiation (MJ m-2 d-1) (excludes areas south of US and some high-latitude areas)
RH mean annual relative humidity (%)
CMI Hogg’s climate moisture index (mm)
DD1040 (10<DD<40) degree-days above 10°C and below 40°C
Tave_wt winter (December to February) mean temperature (°C)
Tave_sp spring (March to May) mean temperature (°C)
Tave_sm summer (June to August) mean temperature (°C)
Tave_at autumn (September to November) mean temperature (°C)
PPT_wt winter (December to February) precipitation (mm)
PPT_sp spring (March to May) precipitation (mm)
PPT_sm summer (June to August) precipitation (mm)
PPT_at autumn (September to November) precipitation (mm)
PPT_at autumn (September to November) precipitation (mm)

已知的问题：¶
由于两国 PRISM 数据之间的边缘匹配问题，沿美国/加拿大边界出现了一些降水值的不连续性。

年平均太阳辐射 (MAR) 数据是临时数据，计划在即将发布的 ClimateNA 软件中进行修订。

License

These datasets are made available under the CC BY 4.0 Attribution 4.0 International license. This license allows users to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator.

Changelog

  • Updated to v7.3
  • Added 20 year periods apart from 30 year periods

Data Website: You can download the data and description here

Explore the data in R-Shiny apps here

Created by: AdaptWest Project, Wang, T., A. Hamann, D. Spittlehouse, C. Carroll

Curated in GEE by: Samapriya Roy

Keywords: climate change, global circulation models, gridded climate data, north america,emission scenarios,climate variables

Last updated: 2023-03-24


 

​

【版权声明】本文为华为云社区用户原创内容，转载时必须标注文章的来源（华为云社区）、文章链接、文章作者等基本信息， 否则作者和本社区有权追究责任。如果您发现本社区中有涉嫌抄袭的内容，欢迎发送邮件进行举报，并提供相关证据，一经查实，本社区将立刻删除涉嫌侵权内容，举报邮箱： cloudbbs@huaweicloud.com
Astro流程应用 Astro Flow 云端实践 云计算 数据库 机器学习
  • 点赞
  • 收藏
  • 关注作者

评论（0）

0/1000
抱歉，系统识别当前为高风险访问，暂不支持该操作

全部回复

上滑加载中

设置昵称

在此一键设置昵称，即可参与社区互动！

*长度不超过10个汉字或20个英文字符，设置后3个月内不可修改。

*长度不超过10个汉字或20个英文字符，设置后3个月内不可修改。

确认 取消

加入云驻计划，成为创作者

  • 华为云周边好礼
  • 免费体验产品
  • 特殊身份标识
  • 线下官方门票
  • 内部专家零距离
  • 与10000+优质创作者共同成长
立即加入