I’m trying to divide an OMI L3 HCHO by OMI HCHO L3 NO2 averaged over a certain period of time. Given that I’ve now managed to average NO2, and I already could average HCHO, the only remaining issue is that the HCHO product is the only OMI L3 to come with a resolution of 0.1 by 0.1. Since the OMI NO2 L3 product has a resolution of 0.25 by 0.25 don’t I need to regrid the HCHO to a 0.25 by 0.25 grid to do an accurate division?
If so how would I go about doing this?
Here’s my code for merging HCHO L3 products. I tried to regrid in the operations stage but it didn’t work as lat and long are already set at 0.1 by 0.1. Perhaps if I define lat and long myself as you showed me how to do for NO2 this would work?
import coda import harp import numpy from os import listdir #Local variables productlist =  Folder = r'/Users/varsha.rao/Downloads/OMI_HCHO/' OutFolder = r'/Users/varsha.rao/Downloads/' #Function for listing files def list_files1(directory, extension): return (f for f in listdir(directory) if f.endswith('.' + extension)) #Adding files to a list FileList = list_files1(Folder, "nc") for File in FileList: InFile = Folder + File pf = coda.open(InFile) try: latitude = coda.fetch(pf, '/Latitude') longitude = coda.fetch(pf, '/Longitude') hcho = coda.fetch(pf, '/key_science_data/column_amount') finally: coda.close(pf) product = harp.Product() product.latitude = harp.Variable(latitude, ["latitude"]) product.latitude.unit = "degree_north" product.longitude = harp.Variable(longitude, ["longitude"]) product.longitude.unit = "degree_east" product.hcho_column_number_density = harp.Variable(hcho, ["latitude", "longitude"]) product.hcho_column_number_density.unit = "molec/cm2" productlist.append(product) average = harp.execute_operations(productlist, post_operations="bin();squash(time, (latitude,longitude))") OutFile = OutFolder + File[19:23] + File [24:26] + ".nc" harp.export_product(average, OutFile)