IPCC Climate Zones (from the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories)

温室气体 环境科学 气候变化 气候学 地质学 海洋学
作者
Matthew Lewis
出处
期刊:CERN European Organization for Nuclear Research - Zenodo
标识
DOI:10.5281/zenodo.7303807
摘要

Description These data (re)create spatial data for the 2019 IPCC Climate Zones, shown in Figure 3A.5.1 of Chapter 3: Consistent Representation of Lands in Volume 4: Agriculture, Forestry and Other Land Use of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. I recreated these data because I could not readily identify the data in a spatial format online, a problem which has previously been noted by ESDAC, who produced a spatial version of Figure 3A.5.1 from the original 2006 guidelines. Resolution: 0.5 arc degree CRS: lon/lat WGS 84 If you use these data please ensure you also cite the IPCC - Calvo Buendia, E et al. (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. IPCC, Switzerland. Methods The data were derived using the classification scheme shown in Figure 3A.5.2 based on the gridded Climate Research Unit (CRU) Time Series (TS) monthly climate data (Harris et al., 2014) for the period from 1985 to 2015 following the methods described in Annex 3A.5 Default climate and soil classifications of the above Chapter. All data were processed in R version 4.2.1, with the packages elevatr (v0.4.2), lubridate (v1.8.0), magrittr (v2.0.3), and terra (v1.6-7) attached. The full session info is included as a .txt file. As these methods are not exhaustively described in the Annex, the following assumptions were made: CRU TS3.25 was used as the most recently published data (published on 2017-09-22) that could have been incorporated into the Refinement. Other possibilities include CRU TS3.24 (which are the first data to include 2015), or CRU TS4.00 or CRU TS4.01 (both of which were published in parallel to 3.24 and 3.25). These data were all investigated, and CRU TS3.25 produced results that were the most visually similar to the published Figure 3A.5.1 (though non-identical). As the methods did not mention a preferred elevation data source, the elevatr R package was used to obtain data at zoom level 2 (approx resolution of 0.15 arc degree), that was then resampled to match the 0.5-degree resolution of the CRU data. These data originally come from the ETOPO1 global relief model. Known discrepancies The distribution of Tropical Wet and Tropical Moist in South America does not exactly match the original data. There are small discrepancies in Tropical Montane classifications (likely arising from the use of a different elevation layer). These are most noticeable in, but not restricted to, Africa. The classification of Boreal Dry, Polar Dry, and Polar Moist in northern Russia and (to a lesser extent) in northern Canada does not exactly match the original data. There are a small number of Cool Temperate Dry pixels in the UK, and Warm Temperate Dry pixels around Brittany which do not occur in the original data. Disclaimer I am not affiliated with the IPCC in any way, I just needed spatial data of the Climate Zones, and could not readily identify any online. This is a problem which has previously been noted by ESDAC, who produced a spatial version of Figure 3A.5.1 from the original 2006 guidelines. File description README.html - ~this description file. IPCC_Climate_Zones_ts_3.25.tif - the output Climate Zones map at 0.5-arc degree resolution based on the CRU TS3.25 data. IPCC_Climate_Zones_colour_map.clr - a colour map file to render the output map with the same colours as in the IPCC 2019 Refinement figure. IPCC_Climate_Zones_ts_3.25.png - an image file of the output Climate Zones map. ipcc_climate_zones_2019.R - the script used to produce these data. session_info.txt - the R session info.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
Dean发布了新的文献求助10
1秒前
tonyfountain完成签到,获得积分10
1秒前
今后应助chem采纳,获得10
1秒前
1秒前
开朗的慕儿完成签到,获得积分10
2秒前
上官从菡完成签到,获得积分10
2秒前
XYNW发布了新的文献求助10
3秒前
马亚飞完成签到,获得积分10
3秒前
xu完成签到,获得积分10
4秒前
LL完成签到,获得积分10
4秒前
5秒前
MQ_sun发布了新的文献求助10
5秒前
大胆寒风发布了新的文献求助10
5秒前
5秒前
doc.level完成签到,获得积分10
5秒前
5秒前
Norman发布了新的文献求助10
5秒前
5秒前
米里迷路完成签到,获得积分10
6秒前
汤壳西姆完成签到,获得积分10
6秒前
6秒前
旺旺完成签到,获得积分10
6秒前
7秒前
汉字完成签到,获得积分10
7秒前
科研通AI6应助HK采纳,获得10
8秒前
9秒前
何燕姿完成签到 ,获得积分10
9秒前
LiHN123完成签到,获得积分10
10秒前
10秒前
罗明明发布了新的文献求助10
10秒前
11发布了新的文献求助10
10秒前
二十六画生完成签到,获得积分10
11秒前
11秒前
11秒前
十三应助LiLy采纳,获得30
11秒前
Richard完成签到,获得积分10
11秒前
chenqiumu应助HIT_C采纳,获得30
11秒前
yu完成签到,获得积分10
11秒前
FashionBoy应助骑猪看唱本采纳,获得10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Fermented Coffee Market 2000
Methoden des Rechts 600
Constitutional and Administrative Law 500
PARLOC2001: The update of loss containment data for offshore pipelines 500
Critical Thinking: Tools for Taking Charge of Your Learning and Your Life 4th Edition 500
Vertebrate Palaeontology, 5th Edition 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5283704
求助须知:如何正确求助?哪些是违规求助? 4437469
关于积分的说明 13813675
捐赠科研通 4318220
什么是DOI,文献DOI怎么找? 2370348
邀请新用户注册赠送积分活动 1365683
关于科研通互助平台的介绍 1329143