MATLAB | Calculation Method for Single Point Extreme Precipitation Index

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MATLAB|

Calculation Method for Single Point Extreme Precipitation Index

Author: Galaxy Eight – Li Zhi

Email: [email protected]

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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 intensity of precipitation on wet days (daily precipitation > 1mm), this index first limits daily precipitation to be 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, which I honestly do not understand, 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 combination of the find(), diff(), and max() functions.

Complete Code

clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 6 0 0 0 15 3 4 5 31 40 15 22 17 58 46 11 75 2 3 5 9 12 23];Rx1day = max(pr);clear;clc% Assume single point precipitation is pr, data contains missing values. pr = [4 NaN 6 0 0 0 15 3 4 5 31 40 15 22 17 58 46 11 75 2 3 5 9 12 23];% Here we convert the data, changing 0 values to NaN, to facilitate sliding calculations without recognizing 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 6 0 0 10 15 3 4 5 31 40 15 22 17 58 46 11 75 2 3 5 9 12 23];% 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 6 0 0 10 15 3 4 5 31 40 15 22 17 58 46 11 75 2 3 5 9 12 23];% 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 6 0 0 10 15 3 4 5 31 40 15 22 17 58 46 11 75 2 3 5 9 12 23];% 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 31 1 1 1 1 11 1 1 1 1 1 40 15 22 17 5 46 11 3 2 1 65 52 62 55 49 62 23];% 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 31 1 1 1 1 11 1 1 1 1 1 40 15 22 17 5 46 11 3 2 1 65 52 62 55 49 62 23];% 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 31 1 1 1 1 11 1 1 1 1 1 40 15 22 17 5 46 11 3 2 1 65 52 62 55 49 62 23];% 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 31 1 1 1 1 11 1 1 1 1 1 40 15 22 17 5 46 11 3 2 1 65 52 62 55 49 62 23];% 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 contains no missing values. pr = [4 5 0 0.1 0.2 0.3 0.5 1 2 3 4 56 0 0.1 0.3 ];% 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;

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This article was edited by Galaxy Eight – Xinyue