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MATLAB|
Calculation Method for Single Point Extreme Precipitation Index
Author: Li Zhi, Eighth Galaxy
Email: [email protected]
}
1
Rx1day
The maximum daily precipitation, which is straightforward and can be solved using the max() function.
2
Rx5day
The maximum precipitation over 5 consecutive days, which includes several conditions: 1) 5 consecutive days; 2) maximum value. The maximum value does not need explanation. When calculating the 5-day consecutive precipitation, it is important to ensure that the precipitation amount for all 5 days is not zero. Since this 5-day period is a sliding window, care must be taken to break the sliding window at zero values and NaN.
Thus, we introduce the movsum() function for calculation.
3
SDII
The daily precipitation intensity on wet days (daily precipitation > 1mm). This index first limits daily precipitation to greater than 1mm, and then calculates the precipitation intensity. Precipitation intensity = cumulative precipitation / cumulative precipitation time.
4
R10
The number of days with precipitation ≥ 10mm.
5
R20
The number of days with precipitation ≥ 20mm.
6
R95p
This is defined as the number of days with precipitation greater than the 95th percentile precipitation. I honestly did not understand this, but the percentile must use the prctile() function. So I checked the literature.
https://www.sciencedirect.com/science/article/pii/S1674927823001533
7
R99p
Similarly.
8
R98pTOT
The percentage of total precipitation on very wet days. After reading, I still did not understand, so I checked again:
9
R99pTOT
Similarly.
10
CDD and CWD
This is slightly more complex. It requires the use of the find(), diff(), and max() functions in combination.
Complete Code
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 60001534531401522175846117523591223];Rx1day = max(pr);
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 60001534531401522175846117523591223];% Here we convert data, changing 0 values to NaN, so that sliding calculations do not recognize non-precipitation days. pr(pr==0) = nan;M = movsum(pr,5,'Endpoints','discard');Rx5day = max(M);
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 600101534531401522175846117523591223];% Calculate simple daily precipitation intensity indexthresholdP = 1;wetDays = pr(pr > thresholdP);SDII = sum(wetDays) / length(wetDays);
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 600101534531401522175846117523591223];% Calculate the number of heavy precipitation daysthresholdP = 10;wetDays = pr(pr >= thresholdP);R10 = length(wetDays);
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 600101534531401522175846117523591223];% Calculate the number of extreme precipitation daysthresholdP = 20;wetDays = pr(pr >= thresholdP);R20 = length(wetDays);
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 3111111111111401522175461132165526255496223];% First filter daily precipitation greater than 1thresholdP = 1;wetDays = pr(pr > thresholdP);% Calculate 95th percentile precipitationR95pthresholdP = prctile(wetDays, 95);R95p = length(pr(pr >= R95pthresholdP));
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 3111111111111401522175461132165526255496223];% First filter daily precipitation greater than 1thresholdP = 1;wetDays = pr(pr > thresholdP);% Calculate 99th percentile precipitationR99pthresholdP = prctile(wetDays, 99);R99p = length(pr(pr >= R99pthresholdP));
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 3111111111111401522175461132165526255496223];% First filter daily precipitation greater than 1thresholdP = 1;wetDays = pr(pr > thresholdP);% Calculate 95th percentile precipitationR95pthresholdP = prctile(wetDays, 95);R95p = length(pr(pr >= R95pthresholdP));% Calculate the proportion of total precipitation for 95th percentileAmount95 = sum(pr(pr >= R95pthresholdP));R95pTOT = Amount95 / sum(pr);
clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 3111111111111401522175461132165526255496223];% First filter daily precipitation greater than 1thresholdP = 1;wetDays = pr(pr > thresholdP);% Calculate 99th percentile precipitationR99pthresholdP = prctile(wetDays, 99);R99p = length(pr(pr >= R99pthresholdP));% Calculate the proportion of total precipitation for 99th percentileAmount99 = sum(pr(pr >= R99pthresholdP));R99pTOT = Amount99 / sum(pr);
clear;clc% Assume single point precipitation is pr, data does not contain missing values. pr = [4500.10.20.30.512345600.10.3 ];% Calculate consecutive dry daysthresholdP = 1;drySpells = diff(find([1, pr<thresholdP, 1]));CDD = max(drySpells) - 1;wetSpells = diff(find([1, pr>=thresholdP, 1]));CWD = max(drySpells) - 1;END
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Article edited by: Eighth Galaxy – Xinyue