用降水、比湿和温度计算相对湿度(nc版、python)
有时收集到的气象数据为比湿，但模型中需要的输入为相对湿度，我们可以利用降水、比湿和温度进行换算。
转换公式：https://earthscience.stackexchange.com/questions/2360/how-do-i-convert-specific-humidity-to-relative-humidity
讯享网
比湿转换为相对湿度
def shum_switch_rhum(temp,shum,pres): ''' 利用比湿（specific humidity）计算相对湿度 :param temp: 气温，K :param shum: 比湿 :param pres: 气压，Pa :return: rhum，% ''' rhum = 0.236 * pres * shum * np.exp((17.67 * (temp - 273.16))/(temp - 29.65)) (-1) print(rhum) return rhum 讯享网
如果你的数据是nc的，那么你可以尝试用下面的函数进行批量计算
讯享网import xarray as xr import os import datetime import numpy as np import pandas as pd def Search_File(dirname,suffix): ''' This function can search all files with the specified suffix in this dir. :param dirname: string, the path need to be searched :param suffix: string, the specified suffix need to be seached :return: filter_list: list, the path list need to be searched. ''' filter = [suffix] # 设置过滤后的文件类型 当然可以设置多个类型 filter_list = [] for maindir, subdir, file_name_list in os.walk(dirname): #print(maindir) #当前主目录 for filename in file_name_list: apath = os.path.join(maindir, filename)#合并成一个完整路径 portion = os.path.splitext(apath) ext = portion[1] # 获取文件后缀 [0]获取的是除了文件名以外的内容 if ext in filter: newname = portion[0] + suffix filter_list.append((newname,portion[0].split("\\")[-1])) # print(filter_list) return filter_list def batch_shum_to_rhum(pres_path,shum_path,temp_path,output_path,start_year,end_year): ''' 可以利用降水、比湿和温度计算相对湿度，注意数据单位 :param pres_path: :param shum_path: :param temp_path: :param output_path: :return: ''' # 批量比湿和相对湿度换算 # 导入数据，压力、比湿以及温度，注意单位 pres_path_list = Search_File(pres_path,".nc") pres_list = [read_nc_data(path[0]) for path in pres_path_list] pres = xr.combine_nested(pres_list,concat_dim="time") temp_path_list = Search_File(temp_path,".nc") temp_list = [read_nc_data(path[0]) for path in temp_path_list] temp = xr.combine_nested(temp_list,concat_dim="time") shum_path_list = Search_File(shum_path, ".nc") shum_list = [read_nc_data(path[0]) for path in shum_path_list] shum = xr.combine_nested(shum_list, concat_dim="time") acc = xr.merge([shum,temp,pres]) rhum_data = shum_switch_rhum(acc["temp"].values,acc["shum"].values,acc["pres"].values) rhum = xr.Dataset({
"rhum": (["time", "lat", "lon"], rhum_data)}, coords=acc.coords, attrs={
"long_name": "relative humidity", "units": "%"}) years = list(range(start_year, end_year + 1)) for year in years: # 输入年月数据比较方便！！！ out = rhum.sel(time=rhum["time.year"] == year) out.to_netcdf("{}/rhum_{}.nc".format(output_path,year)) print(out)
版权声明：本文内容由互联网用户自发贡献，该文观点仅代表作者本人。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容，请联系我们，一经查实，本站将立刻删除。
如需转载请保留出处：https://51itzy.com/kjqy/36436.html