ppcpy.io.readMeteo

Classes

Meteo	% LOADMETEOR read meteorological data.
MeteoNcCloudnet	TODO for now only one filename define preferred model

class ppcpy.io.readMeteo.Meteo(meteorDataSource, meteo_folder, meteo_file)

% LOADMETEOR read meteorological data. % % USAGE: % [temp, pres, relh, wins, wind, meteorAttri] = loadMeteor(mTime, asl) % % INPUTS: % mTime: array % query time. % asl: array % height above sea level. (m) % % KEYWORDS: % meteorDataSource: str % meteorological data type. % e.g., ‘gdas1’(default), ‘standard_atmosphere’, ‘websonde’, ‘radiosonde’, ‘nc_cloudnet’ % gdas1Site: str % the GDAS1 site for the current campaign. % meteo_folder: str % the main folder of the GDAS1 profiles (or the cloudnet profiles). % radiosondeSitenum: integer % site number, which can be found in % doc/radiosonde-station-list.txt. % radiosondeFolder: str % the folder of the sonding files. % radiosondeType: integer % file type of the radiosonde file. % 1: radiosonde file for MOSAiC (default) % 2: radiosonde file for MUA % flagReadLess: logical % flag to determine whether access meteorological data by certain time % interval. (default: false) % method: char % Interpolation method. (default: ‘nearest’) % isUseLatestGDAS: logical % whether to search the latest available GDAS profile (default: false). % % OUTPUTS: % temp: matrix (time * height) % temperature for each range bin. [°C] % pres: matrix (time * height) % pressure for each range bin. [hPa] % relh: matrix (time * height) % relative humidity for each range bin. [%] % wins: matrix (time * height) % wind speed. (m/s) % meteorAttri: struct % dataSource: cell % The data source used in the data processing for each cloud-free group. % URL: cell % The data file info for each cloud-free group. % datetime: array % datetime label for the meteorlogical data. % % HISTORY: % - 2021-05-22: first edition by Zhenping % % .. Authors: - zhenping@tropos.de

load(times, heights)

load the data and resample to 15 minute intervals

get_mean_profiles(time_slice)

get the mean meteorological profiles

class ppcpy.io.readMeteo.MeteoNcCloudnet(basepath, filepattern)

TODO for now only one filename define preferred model

find_path_for_time(time)

load(time, height_grid)

not quite sure on the interface yet ` met.load(data_cube.retrievals_highres['time'][0]) met.load(datetime.datetime.timestamp(datetime.datetime.strptime(data_cube.date, '%Y%m%d'))) `

Recipie:

• load

• select variables?

• rename?

• regrid from (time, level) to (time, lidar heights)

clarify the above ground above sea level issues