co2usa_salt_lake_city_background_to_netCDF.m

% clear all
% close all
set(0,'DefaultFigureWindowStyle','docked')

%% netCDF creation documentation

% Following the Climate Forecasting conventions for netCDF files documented here:
% http://cfconventions.org/
% http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.html
% 
% Also following the Attribute Convention for Data Discovery version 1.3
% https://wiki.esipfed.org/Attribute_Convention_for_Data_Discovery_1-3
% 
% Variables must have a standard_name, a long_name, or both.
% A standard_name is the name used to identify the physical quantity. A standard name contains no whitespace and is case sensitive.
% A long_name has an ad hoc, human readable format.
% A comment can be used to add further detail, but is not required.
% 
% Time and date formating follow this convention:
% https://www.edf.org/health/data-standards-date-and-timestamp-guidelines
% 
% Data will be archived at the ORNL DAAC:
% https://daac.ornl.gov/PI/
% 

%% Creation date

% date_created: The date on which this version of the data was created. Recommended. 
date_created_now = datetime(now,'ConvertFrom','datenum','TimeZone','America/Denver'); date_created_now.TimeZone = 'UTC';
date_created_str = datestr(date_created_now,'yyyy-mm-ddThh:MM:ssZ');

% date_issued: The date on which this data (including all modifications) was formally issued (i.e., made available to a wider audience). Suggested.
date_issued_now = datestr(now,'yyyy-mm-dd');
date_issued = datetime(2021,02,22);
date_issued_str = datestr(date_issued,'yyyy-mm-ddThh:MM:ssZ');

% Working folders
if ~exist('currentFolder','var'); currentFolder = pwd; end
if ~exist('readFolder','var'); readFolder = fullfile(currentFolder(1:regexp(currentFolder,'gcloud.utah.edu')+14),'data','co2-usa','data_input'); end
if ~exist('writeFolder','var');  writeFolder = fullfile(currentFolder(1:regexp(currentFolder,'gcloud.utah.edu')+14),'data','co2-usa','synthesis_output'); end

%% City & provider information:

city = 'salt_lake_city';
city_long_name = 'Salt Lake City';
city_url = 'https://air.utah.edu/';

i = 1;
provider(i).name = 'John C. Lin';
provider(i).address1 = 'Department of Atmospheric Sciences';
provider(i).address2 = '135 S 1460 E, room 819';
provider(i).address3 = 'Salt Lake City, UT 84112';
provider(i).country = 'United States';
provider(i).city = city_long_name;
provider(i).affiliation = 'University of Utah';
provider(i).email = 'John.Lin@utah.edu';
provider(i).orcid = 'https://orcid.org/0000-0003-2794-184X';
provider(i).parameter = 'Provider has contributed measurements for: ';
i = 2;
provider(i).name = 'David R. Bowling';
provider(i).address1 = 'School of Biological Sciences';
provider(i).address2 = '257 S. 1400 E.';
provider(i).address3 = 'Salt Lake City, UT 84112';
provider(i).country = 'United States';
provider(i).city = city_long_name;
provider(i).affiliation = 'University of Utah';
provider(i).email = 'David.Bowling@utah.edu';
provider(i).orcid = 'https://orcid.org/0000-0002-3864-4042';
provider(i).parameter = 'Provider has contributed measurements for: ';

%% Site meta data

clear site % start fresh
site.reference = 'Mitchell, Logan E., John C. Lin, David R. Bowling, Diane E. Pataki, Courtenay Strong, Andrew J. Schauer, Ryan Bares, et al. Long-Term Urban Carbon Dioxide Observations Reveal Spatial and Temporal Dynamics Related to Urban Characteristics and Growth. Proceedings of the National Academy of Sciences 115, no. 12 (March 20, 2018): 2912–17. https://doi.org/10.1073/pnas.1702393115.';

site.groups = {}; % List of the site "code_species_inletHt"
site.species = {}; % List of the "species"
site.codes = {}; % List of the site "codes"
site.date_issued = date_issued;
site.date_issued_str = datestr(site.date_issued,'yyyy-mm-ddThh:MM:ssZ');
site.date_created_str = date_created_str;

i = 1;
site.codes{1,i} = 'background';

site.(site.codes{i}).code = upper(site.codes{i});
site.(site.codes{i}).name = 'background';
site.(site.codes{i}).long_name = 'background';

site.(site.codes{i}).country = 'United States';
site.(site.codes{i}).time_zone = 'America/Denver';
site.(site.codes{i}).inlet_height_long_name = {'background'};
site.(site.codes{i}).inlet_height = {0};
site.(site.codes{i}).species = {'co2'};
site.(site.codes{i}).species_standard_name = {'carbon_dioxide'};
site.(site.codes{i}).species_units = {'micromol mol-1'};
site.(site.codes{i}).species_units_long_name = {'ppm'};
site.(site.codes{i}).instrument = {'modeled'};
site.(site.codes{i}).calibration_scale = {'WMO CO2 X2007'};
site.(site.codes{i}).in_lat = 40.7607;
site.(site.codes{i}).in_lon = -111.8911;
site.(site.codes{i}).in_elevation = 1301;
site.(site.codes{i}).date_issued = date_issued;
site.(site.codes{i}).date_issued_str = date_issued_str;

sp = 1; sptxt = site.(site.codes{i}).species{sp};
inlet = 1; intxt = site.(site.codes{i}).inlet_height_long_name{inlet};

site.groups = [site.groups; {[sptxt,'_',site.(site.codes{i}).name]}];
site.species = [site.species; {sptxt}];

load(fullfile(currentFolder(1:regexp(currentFolder,'gcloud.utah.edu')+14),'code','SLC CO2','Data','data_background.mat'))

% Note: the CO2-USA data set has data set to the floored hour, but CT has
% time stamps on the half hour.  This sets all of the CT data to be on the
% hour, then interpolates to find the correct concentration at the new
% times.  Lastly, it removes any duplicates (from times when there was a
% HDP & CT data point with the same hour)

mask = strcmp(bg.source,'CT2019B'); % mask for CT data
bg2 = bg;
bg2.dtUTC(mask).Minute = 0; % Set CT minute to 0

bg2.co2(mask) = interp1(datenum(bg.dtUTC),bg.co2,datenum(bg2.dtUTC(mask))); % Interpolates CT data

[~,ia,~] = unique(bg2.dtUTC); % Finds duplicates

bg2.dtUTC = bg2.dtUTC(ia); % Removes duplicates
bg2.co2 = bg2.co2(ia); % Removes duplicates
bg2.source = bg2.source(ia); % Removes duplicates

% figure(100);clf; hold on
% plot(bg.dtUTC,bg.co2,'.')
% plot(bg2.dtUTC,bg2.co2,'.')
% hold off

bg = bg2;

site.(site.codes{i}).([sptxt,'_',intxt]) = bg.co2; % species mixing ratio
site.(site.codes{i}).([sptxt,'_',intxt,'_time']) = datetime(bg.dtUTC,'ConvertFrom','datenum'); ...

% Note: The first several years of BG come from CarbonTracker which has values on the half hour. This floors the hour.
site.(site.codes{i}).([sptxt,'_',intxt,'_time']).Minute = 0; 

% Removes the leading and trailing NaNs
data_range_ind = find(site.(site.codes{i}).([sptxt,'_',intxt])~=-9999.0,1,'first'):find(site.(site.codes{i}).([sptxt,'_',intxt])~=-9999.0,1,'last');
site.(site.codes{i}).([sptxt,'_',intxt]) = site.(site.codes{i}).([sptxt,'_',intxt])(data_range_ind);
site.(site.codes{i}).([sptxt,'_',intxt,'_time']) = site.(site.codes{i}).([sptxt,'_',intxt,'_time'])(data_range_ind);
clear data_range_ind

site.(site.codes{i}).([sptxt,'_',intxt,'_std']) = ones(length(site.(site.codes{i}).([sptxt,'_',intxt])),1)*-9999.0;
site.(site.codes{i}).([sptxt,'_',intxt,'_unc']) = ones(length(site.(site.codes{i}).([sptxt,'_',intxt])),1)*-9999.0;
site.(site.codes{i}).([sptxt,'_',intxt,'_n']) = ones(length(site.(site.codes{i}).([sptxt,'_',intxt])),1)*-9999.0;
site.(site.codes{i}).([sptxt,'_',intxt,'_lat']) = repmat(site.(site.codes{i}).in_lat,length(site.(site.codes{i}).([sptxt,'_',intxt])),1);
site.(site.codes{i}).([sptxt,'_',intxt,'_lon']) = repmat(site.(site.codes{i}).in_lon,length(site.(site.codes{i}).([sptxt,'_',intxt])),1);
site.(site.codes{i}).([sptxt,'_',intxt,'_elevation']) = repmat(site.(site.codes{i}).in_elevation,length(site.(site.codes{i}).([sptxt,'_',intxt])),1);
site.(site.codes{i}).([sptxt,'_',intxt,'_inlet_height']) = ones(length(site.(site.codes{i}).([sptxt,'_',intxt])),1)*-9999.0;

site.date_issued = date_issued; % This date will be updated with the most recent date in the files below.
site.date_issued_str = datestr(site.date_issued,'yyyy-mm-ddThh:MM:ssZ');

fprintf('---- %-6s complete ----\n\n',site.codes{i})

%% Temporary code to truncate all sites to Dec 31, 2019 for the 4/21 ORNL DAAC archive

for i = 1:length(site.codes)
    for sp = 1:length(site.(site.codes{i}).species) % only doing CO2 for now.
        sptxt = site.(site.codes{i}).species{sp};
        for inlet = 1:length(site.(site.codes{i}).inlet_height_long_name)
            intxt = site.(site.codes{i}).inlet_height_long_name{inlet};
            mask = site.(site.codes{i}).([sptxt,'_',intxt,'_time'])<datetime(2020,1,1); % Mask for data before 2020-01-01
            fields = {'','_std','_n','_unc','_time','_lat','_lon','_elevation','_inlet_height'};
            for j = 1:length(fields)
                site.(site.codes{i}).([sptxt,'_',intxt,fields{j}]) = site.(site.codes{i}).([sptxt,'_',intxt,fields{j}])(mask); % Apply the mask
            end
        end
    end
end

%% Identify the netCDF files to create based on species.
site.unique_species = unique(site.species);
site.species_list = [];
for species_ind = 1:length(site.unique_species)
    site.species_list = [site.species_list, site.unique_species{species_ind},' '];
end
site.species_list = strip(site.species_list); % Removes the last space

for j = 1:length(site.species)
    if strcmp(site.species{j,1},'co2')
        site.species_standard_name{j,1} = 'carbon dioxide';
    elseif strcmp(site.species{j,1},'ch4')
        site.species_standard_name{j,1} = 'methane';
    elseif strcmp(site.species{j,1},'co')
        site.species_standard_name{j,1} = 'carbon monoxide';
    end
end

%% Creating the netCDF file

fprintf('Now creating the netCDF files.\n')
eval('co2usa_create_netCDF')