https://www.wcrp-climate.org/etccdi

气候变化指数
背景
气候界普遍认为，极端气候事件的频率或严重程度的任何变化都会对自然和社会产生深远的影响。因此，分析极端事件非常重要。极端气候变化的监测，检测和归因通常需要每日分辨率数据。但是，全局完整且易于获得的全分辨率日常数据集的编译，提供和更新是一项非常困难的任务。这部分是因为并非所有国家气象和水文气象服务（NMHS）都有能力或授权自由分发他们收集的每日数据。因此，ET及其前身CCl / CLIVAR气候变化检测工作组（WG）一直在协调国际上的发展，计算和分析一系列指数，以便个人，国家和地区能够以完全相同的方式计算指数，使其分析能够无缝地融入全球图景中（Karl等，1999，Peterson和共同作者2001） 。希望参与这项工作将使所有有关各方，包括指数提供者，能够从目前无法获得更广泛空间覆盖的改进的变化监测中受益。

具体发现文献：https://www.sciencedirect.com/science/article/pii/S1040618214002043?via%3Dihub

https://doi.org/10.1016/j.quaint.2014.03.060

降水相关指数

http://etccdi.pacificclimate.org/software.shtml

1. Rx1day, Monthly maximum 1-day precipitation:

   Let RR_ij be the daily precipitation amount on day i in period j. The maximum 1-day value for period j are:

   Rx1day_j = max (RR_ij)

2. Rx5day, Monthly maximum consecutive 5-day precipitation:

   Let RR_kj be the precipitation amount for the 5-day interval ending _k, period j. Then maximum 5-day values for period j are:

   Rx5day_j = max (RR_kj)

3. SDII Simple pricipitation intensity index: Let RR_wj be the daily precipitation amount on wet days, w (RR ≥ 1mm) in period j. If Wrepresents number of wet days in j, then:

   

4. R10mm Annual count of days when PRCP≥ 10mm: Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where:

   RR_ij ≥ 10mm

5. R20mm Annual count of days when PRCP≥ 20mm: Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where:

   RR_ij ≥ 20mm

6. Rnnmm Annual count of days when PRCP≥ nnmm, nn is a user defined threshold: Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where:

   RR_ij ≥ nnmm

7. CDD. Maximum length of dry spell, maximum number of consecutive days with RR < 1mm: Let RR_ij be the daily precipitation amount on day iin period j. Count the largest number of consecutive days where:

   RR_ij < 1mm

8. CWD. Maximum length of wet spell, maximum number of consecutive days with RR ≥ 1mm: Let RR_ij be the daily precipitation amount on day iin period j. Count the largest number of consecutive days where:

   RR_ij ≥ 1mm

9. R95pTOT. Annual total PRCP when RR > 95p. Let RR_wj be the daily precipitation amount on a wet day w (RR ≥ 1.0mm) in period i and let RR_wn95 be the 95^th percentile of precipitation on wet days in the 1961-1990 period. If W represents the number of wet days in the period, then:

10. R99pTOT. Annual total PRCP when RR > 99p: Let RR_wj be the daily precipitation amount on a wet day w (RR ≥ 1.0mm) in period i and let RR_wn99 be the 99^th percentile of precipitation on wet days in the 1961-1990 period. If W represents the number of wet days in the period, then:

11. PRCPTOT. Annual total precipitation in wet days: Let RR_ij be the daily precipitation amount on day i in period j. If I represents the number of days in j, then

References

• Karl, T.R., N. Nicholls, and A. Ghazi, 1999: CLIVAR/GCOS/WMO workshop on indices and indicators for climate extremes: Workshop summary. Climatic Change, 42, 3-7.
• Peterson, T.C., and Coauthors: Report on the Activities of the Working Group on Climate Change Detection and Related Rapporteurs 1998-2001. WMO, Rep. WCDMP-47, WMO-TD 1071, Geneve, Switzerland, 143pp.

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github 程序

• pacificclimate/climdex.pcic

  Routines to compute ETCCDI Climdex indices
  GPL-3.0 license
  R

• ECCC-CDAS/RClimDex

  Simple R package for ETCCDI/CRD climate change indices calculations

  LGPL-2.1 license
  R

• Peter-Gibson/ETCCDI_cdo

  python code that uses cdo operators to calculate ETCCDI indices

• SantanderMetGroup/climate4R.climdex

  A climate4R package for calculation of the ETCCDIcore climate indices (part of the climate4R bundle)

  R

M. Iturbide, J. Bedia, S. Herrera, J. Baño-Medina, J. Fernández, M.D. Frías, R. Manzanas, D. San-Martín, E. Cimadevilla, A.S. Cofiño and JM Gutiérrez (2019) The R-based climate4R open framework for reproducible climate data access and post-processing. Environmental Modelling & Software, 111, 42-54. DOI: /10.1016/j.envsoft.2018.09.009

https://github.com/SantanderMetGroup/notebooks

直接数据的下载：
http://etccdi.pacificclimate.org/data.shtml

The extreme precipitation indices used can be divided into two types (Liu et al., 2013; Wang et al., 2013a,b,c). One is precipitation indices, including PRCPTOT, R95p, R99p, RX1 day, RX5 day and SDII. The other type is the number of days of precipitation, including R10 mm, R20 mm, R25 mm, CDD and CWD

具体定义查询climdex-indices

http://climate-modelling.canada.ca/climatemodeldata/climdex/

Sillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013b: Climate extremes indices in the CMIP5 multi-model ensemble. Part 2: Future projections. J. Geophys. Res., [doi:10.1002/jgrd.50188](http://dx.doi.org/10.1002/jgrd.50188 "Links to websites not under the control of the Government of Canada, including those to our social media accounts, are provided solely for the convenience of our website visitors. We are not responsible for the accuracy, currency or reliability of the content of such websites. The Government of Canada does not offer any guarantee in that regard and is not responsible for the information found through these links, nor does it endorse the sites and their content.

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Table 1. Core Set of 27 Extreme Indices Recommended by the ETCCDI. The Index R1mm Marked With * is Defined by ETCCDI for a User Specified Threshold Which is Set to 1 mm for This Study

The indices are defined and described in detail in Klein Tank et al. [2009] and Zhang et al. [2011]. The indices fall roughly into four categories: (1) absolute indices, which describe, for instance, the hottest or coldest day of a year, or the annual maximum 1 day or 5 day precipitation rates; (2) threshold indices, which count the number of days when a fixed temperature or precipitation threshold is exceeded, for instance, frost days or tropical nights; (3) duration indices, which describe the length of wet and dry spells, or warm and cold spells; and (4) percentile‐based threshold indices, which describe the exceedance rates above or below a threshold which is defined as the 10^th or 90^th percentile derived from the 1961–1990 base period. The latter are referred to as percentile indices in the following. The complete set of 27 indices is summarized in Table 1.

Label	Index Name	Index Definition	Units
TN10p	Cold nights	Let TNij be the daily minimum temperature on day i in period j and let TNin10 be the calendar day 10th percentile centered on a 5 day window. The percentage of days in a year is determined where TNij < TNin10	%
TX10p	Cold days	Let TXij be the daily maximum temperature on day i in period j and let TXin10 be the calendar day 10th percentile centered on a 5 day window. The percentage of days is determined where TXij < TXin10	%
TN90p	Warm nights	Let TNij be the daily minimum temperature on day i in period j and let TNin90 be the calendar day 90th percentile centered on a 5 day window. The percentage of days is determined where TNij > TNin90	%
TX90p	Warm days	Let TXij be the daily maximum temperature on day i in period j and let TXin90 be the calendar day 90th percentile centered on a 5 day window. The percentage of days is determined where TXij > TXin90	%
WSDI	Warm spell duration	Let TXij be the daily maximum temperature on day i in period j and let TXin90 be the calendar day 90th percentile centered on a 5 day window for the base period 1961–1990. Then the number of days per period is summed where, in intervals of at least 6 consecutive days: TXij > TXin90	days
CSDI	Cold spell duration	Let TNij be the daily minimum temperature on day i in period j and let TNin10 be the calendar day 10th percentile centered on a 5 day window for the base period 1961–1990. Then the number of days per period is summed where, in intervals of at least 6 consecutive days: TNij < TNin10	days
TXx	Max TX	Let TXx be the daily maximum temperatures in month k, period j. The maximum daily maximum temperature each month is then: TXxkj = max(TXxkj)	°C
TXn	Min TX	Let TXn be the daily maximum temperature in month k, period j. The minimum daily maximum temperature each month is then: TXnkj = min(TXnkj)	°C
TNx	Max TN	Let TNx be the daily minimum temperatures in month k, period j. The maximum daily minimum temperature each month is then: TNxkj = max(TNxkj)	°C
TNn	Min TN	Let TNn be the daily minimum temperature in month k, period j. The minimum daily minimum temperature each month is then: TNnkj = min(TNnkj)	°C
FD	Frost days	Let TN be the daily minimum temperature on day i in period j. Count the number of days where TNij < 0°C	days
ID	Ice days	Let TX be the daily maximum temperature on day i in period j. Count the number of days where TXij < 0°C	days
SU	Summer days	Let TX be the daily maximum temperature on day i in period j. Count the number of days where TXij > 25°C	days
TR	Tropical nights	Let TN be the daily minimum temperature on day i in period j. Count the number of days where TNij > 20°C	days
GSL	Growing season length	Let T be the mean temperature ((TN + TX)/2) on day i in period j. Count the number of days between the first occurrence of at least 6 consecutive days with T > 5°C and the first occurrence after 1st July (NH) or 1st January (SH) of at least 6 consecutive days with Tij < 5°C	days
DTR	Diurnal temperature range	Let TN and TX be the daily minimum and maximum temperature respectively on day I in period j. If I represents the number of days in j, then: DTRj = [图片上传失败...(image-fbdc26-1561518921414)](TXij – TNij)/ I	°C
RX1day	Max 1 day precipitation	Let PRij be the daily precipitation amount on day i in period j. The maximum 1 day value for period j are: RX1dayj = max (PRij)	mm
RX5day	Max 5 day precipitation	Let PRkj be the precipitation amount for the 5 day interval ending k, period j. Then maximum 5 day values for period j are: RX5dayj = max (PRkj)	mm
SDII	Simple daily intensity	Let PRwj be the daily precipitation amount on wet days, PR > = 1 mm in period j. If W represents number of wet days in j, then: SDIIj = ([图片上传失败...(image-663a6c-1561518921414)] PRwj) / W	mm
R1mm*	Number of wet days	Let PRij be the daily precipitation amount on day i in period j. Count the number of days where PRij > 1 mm	days
R10mm	Heavy precipitation days	Let PRij be the daily precipitation amount on day i in period j. Count the number of days where PRij > 10 mm	days
R20mm	Very heavy precipitation days	Let PRij be the daily precipitation amount on day i in period j. Count the number of days where PRij > 20 mm	days
CDD	Consecutive dry days	Let PRij be the daily precipitation amount on day i in period j. Count the largest number of consecutive days where PRij < 1 mm	days
CWD	Consecutive wet days	Let PRij be the daily precipitation amount on day i in period j. Count the largest number of consecutive days where PRij > 1 mm	days
R95p	Very wet days	Let PRwj be the daily precipitation amount on a wet day w (PR > = 1 mm) in period i and let PRwn95 be the 95th percentile of precipitation on wet days in the 1961–1990 period. If W represents the number of wet days in the period, then: R95pj = [图片上传失败...(image-e960d3-1561518921413)] PRwj, where PRwj > PRwn95	mm
R99p	Extremely wet days	Let PRwj be the daily precipitation amount on a wet day w (PR > = 1 mm) in period i and let PRwn99 be the 95th percentile of precipitation on wet days in the 1961–1990 period. If W represents the number of wet days in the period, then: R99pj = [图片上传失败...(image-ad69e8-1561518921413)] PRwj, where PRwj > PRwn99	mm
PRCPTOT	Total wet‐day precipitation	Let PRij be the daily precipitation amount on day i in period j. If I represents the number of days in j, then: PRCPTOTj = [图片上传失败...(image-c85055-1561518921412)] PRij	mm

https://github.com/scivision/FClimDex