low pass filter data to remove high-frequency content from the original signal given precipidation data and datetime in matlab

To low pass filter precipitation data in Matlab, you can use the Butterworth filter. Here is an example code:

main.m
% Load precipitation data
load('precip_data.mat') % assuming data is stored in a file

% Define filter parameters
fs = 24; % sampling frequency in hours
fc = 0.1; % cutoff frequency for the filter

% Compute normalized cutoff frequency
Wn = fc / (fs/2);

% Compute filter coefficients using a Butterworth filter of order n
n = 4; % filter order
[b,a] = butter(n,Wn,'low');

% Filter the precipitation data
precip_filtered = filtfilt(b,a,precip_data);

% Plot the original and filtered data
figure;
plot(datetime,precip_data,'b',datetime,precip_filtered,'r');
legend('Original','Filtered');
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In this code, we first load the precipitation data from a file (assuming it is stored in a variable called precip_data). We then define the filter parameters, including the sampling frequency (fs) and the cutoff frequency (fc). For a low pass filter, the cutoff frequency should be set to a value that is less than the frequency of the high-frequency content you want to remove.

Next, we compute the normalized cutoff frequency (Wn) as the ratio between the cutoff frequency and half the sampling frequency. We then use the butter function to compute the filter coefficients (b and a) for a Butterworth filter of the desired order (n) and normalized cutoff frequency.

Finally, we use the filtfilt function to apply the filter to the precipitation data. This function implements zero-phase filtering, which means it applies the filter both forwards and backwards in time to eliminate phase shift. We then plot both the original and filtered data using the plot function.