source: TOOLS/CMIP6_FORCING/SOLAR/CMIP6_historical_6bands.m @ 3381

Last change on this file since 3381 was 3381, checked in by jgipsl, 4 years ago

Initial version of scripts to create solar forcings.

O Boucher

File size: 12.1 KB
Line 
1% MATLAB run script to integrate spectral solar irradiance (SSI) data
2% recommended and provided by SPARC/SOLARIS-HEPPA for use in CMIP6 to
3% spectral bands of any desired resolution (according to
4% radiation/photolysis scheme of employed (chemistry) climate model)
5%
6% Author: Tim Kruschke (tkruschke[at]geomar.de)
7% Last modified: 02 May 2016 (compliance with solarforcing_*_*_3.1.nc)
8%
9% Description:
10%    1. reading data from netcdf-file as provided by SPARC/SOLARIS-HEPPA
11%    2. reading definitions of spectral bands (user-specified by creating an
12%       ascii-textfile according to specific formatting, as described below)
13%    3. calling MATLAB-function "regrid_ssi" (provided with this run script as
14%       part of a joint zip-archive) to integrate SSI over specified bands
15%    4. writing new netcdf-file with same structure and attributes as original
16%       (input) file, but only with (unchanged) total solar irradiance
17%       (TSI), SSI integrated over spectral bands specified by user, and
18%       irradiance fraction (of TSI) in respective band (plus
19%       necessary/related dimensions/variables time, wlen, wlenbinsize)
20%
21% Formatting of ascii-textfile, containing definitions of spectral bands:
22%    NO HEADER LINES, NO UNITS, NO CHARACTER DELIMITERS
23%    It's as simple as this:
24%    - one line per spectral band
25%    - each line contains two floating point numbers: lower and upper edge
26%      of respective spectral band (in nanometers!!!), separated by
27%      blank space(s) or tabulator(s)
28%    See example_spectral_bands.dat (provided with this run script as
29%    part of a joint zip-archive) as an example.
30%--------------------------------------------------------------------------
31
32%  execute with run CMIP6.m
33
34%% User-defined paths and filenames
35
36% path to directory of input data; adapt to your file structure
37dir_in=['.'];
38
39% path to directory of output data; adapt to your file structure if desired
40% to differ from input directory
41dir_out=dir_in;
42
43% filename of ascii-textfile (to be placed in dir_in) containing
44% definitions of spectral bands (see explanations in script header);
45% adapt to name of your band definition file
46%filename_spectral_bands='example_spectral_bands.dat';
47filename_spectral_bands='example_spectral_bands_6_SSI_FRAC=1.dat';
48%filename_spectral_bands='example_spectral_bands_2_SSI_FRAC=1.dat';
49
50% filename of original data file, provided by SPARC/SOLARIS-HEPPA (to be
51% placed in dir_in); adapt to respective file that is to be considered
52%filename_in='solarforcing_ref_mon_3.1.nc';
53filename_in='solarforcing_ref_day_3.1.nc';
54
55% lines 53-54 only used to match input and output filenames
56% ATTENTION: works only on unix platforms; if run on other platforms,
57% delete/comment following two lines and enter complete filename_out in
58% l. 59
59[~,filename_in_base]=unix(['basename ' dir_in filesep filename_in ' .nc']);
60filename_in_base=strcat(filename_in_base);
61
62% filename of new file to be created, containing SSI data in spectral
63% resolutiuon as desired by the user; adapt to whatever name you like if
64% not desired to match input filename
65%filename_out=[filename_in_base '_SSI_regridded.nc'];
66filename_out=[filename_in_base '_SSI_regridded_6_TSI_anomaly.nc'];
67
68%% Usually, nothing should be edited below this line!!!!!!!!!!!!!!!!!!!!!!!
69
70ncid_in=netcdf.open([dir_in filesep filename_in],'NOWRITE');
71ncid_out=netcdf.create(strcat([dir_out filesep filename_out]),'CLOBBER'); % existing files are overwritten
72
73% adapting title of original file
74nc_title=netcdf.getAtt(ncid_in,-1,'title');
75nc_title=['Spectral solar irradiance (SSI) of ' nc_title ', converted to custom spectral resolution'];
76netcdf.putAtt(ncid_out,-1,'title',nc_title);
77
78%% time stamp
79netcdf.putAtt(ncid_out,-1,'creation_date',datestr(now)); % creates a time stamp, though not compliant with ISO 8601
80%c% You can use the following lines (commented out) instead to generate a
81%c% time stamp compliant to ISO 8601; change last digits according to
82%c% your time zone in this case (currently +02:00 for CEST)
83%     create_date_vec=datevec(now);
84%     create_date_str=cell(1,6);
85%     for id=1:6;
86%         if create_date_vec(id)<10;
87%             create_date_str{1,id}=['0' num2str(round(create_date_vec(id)))];
88%         else
89%             create_date_str{1,id}=num2str(round(create_date_vec(id)));
90%         end
91%     end
92%     netcdf.putAtt(ncid_out,-1,'creation_date',[create_date_str{1,1} '-' create_date_str{1,2} '-' ...
93%         create_date_str{1,3} 'T' create_date_str{1,4} ':' create_date_str{1,5} ':' create_date_str{1,6} '+02:00'])
94%%
95
96% copy global attributes to new file
97netcdf.copyAtt(ncid_in,-1,'institution',ncid_out,-1)
98netcdf.copyAtt(ncid_in,-1,'institution_id',ncid_out,-1)
99netcdf.copyAtt(ncid_in,-1,'activity_id',ncid_out,-1)
100netcdf.copyAtt(ncid_in,-1,'comment',ncid_out,-1)
101netcdf.copyAtt(ncid_in,-1,'time_coverage_start',ncid_out,-1)
102netcdf.copyAtt(ncid_in,-1,'time_coverage_end',ncid_out,-1)
103netcdf.copyAtt(ncid_in,-1,'frequency',ncid_out,-1)
104netcdf.copyAtt(ncid_in,-1,'source',ncid_out,-1)
105netcdf.copyAtt(ncid_in,-1,'source_id',ncid_out,-1)
106netcdf.copyAtt(ncid_in,-1,'realm',ncid_out,-1)
107netcdf.copyAtt(ncid_in,-1,'further_info_url',ncid_out,-1)
108netcdf.copyAtt(ncid_in,-1,'metadata_url',ncid_out,-1)
109netcdf.copyAtt(ncid_in,-1,'contributor_name',ncid_out,-1)
110netcdf.copyAtt(ncid_in,-1,'references',ncid_out,-1)
111netcdf.copyAtt(ncid_in,-1,'Conventions',ncid_out,-1)
112netcdf.putAtt(ncid_out,-1,'history',['Original SSI data from file ' filename_in ' integrated ' ...
113    'over spectral bands as defined in file ' filename_spectral_bands ' ' ...
114    'by MATLAB run script CMIP6_SSI_convert_resolution_run.m, using function regrid_ssi.m']);
115
116% reading SSI-related variables from CMIP6 input file
117wvl_in_ID=netcdf.inqVarID(ncid_in,'wlen');
118wvl_edges_in_ID=netcdf.inqVarID(ncid_in,'wlen_bnds');
119bw_in_ID=netcdf.inqVarID(ncid_in,'wlenbinsize');
120time_in_ID=netcdf.inqVarID(ncid_in,'time');
121time_bnds_in_ID=netcdf.inqVarID(ncid_in,'time_bnds');
122year_in_ID=netcdf.inqVarID(ncid_in,'calyear');
123month_in_ID=netcdf.inqVarID(ncid_in,'calmonth');
124day_in_ID=netcdf.inqVarID(ncid_in,'calday');
125tsi_in_ID=netcdf.inqVarID(ncid_in,'tsi');
126ssi_in_ID=netcdf.inqVarID(ncid_in,'ssi');
127
128wvl_in=netcdf.getVar(ncid_in,wvl_in_ID);
129wvl_edges_in=(netcdf.getVar(ncid_in,wvl_edges_in_ID))';
130bw_in=netcdf.getVar(ncid_in,bw_in_ID);
131ssi_in=netcdf.getVar(ncid_in,ssi_in_ID);
132tsi_in=netcdf.getVar(ncid_in,tsi_in_ID);
133time_in=netcdf.getVar(ncid_in,time_in_ID);
134time_bnds_in=netcdf.getVar(ncid_in,time_bnds_in_ID);
135year_in=netcdf.getVar(ncid_in,year_in_ID);
136month_in=netcdf.getVar(ncid_in,month_in_ID);
137day_in=netcdf.getVar(ncid_in,day_in_ID);
138
139% read user specified definitions of spectral bands
140fid=fopen([dir_in filesep filename_spectral_bands]);
141tmp=textscan(fid,'%f %f');
142fclose(fid);
143wvl_edges_out=tmp{1,1};
144wvl_edges_out(:,2)=tmp{1,2};
145clear tmp
146
147% calculation of output central wave lengths
148wvl_out=sum(wvl_edges_out,2)/2;
149
150% calculation of output bin width
151bw_out=wvl_edges_out(:,2)-wvl_edges_out(:,1);
152
153% check for consistency of output bin definitions
154if min(bw_out)<0;
155    error(['Error: For at least one spectral band, the specified upper edge \n' ...
156        '(right column) in your input file ' filename_in '\n ' ...
157        'is smaller than the respective lower edge (left column).'])
158end
159
160% check for spectral coverage of input data with respect to desired output
161% bins
162if min(wvl_edges_out(:,1))<min(wvl_edges_in(:,1)) || max(wvl_edges_out(:,2))>max(wvl_edges_in(:,2));
163    warning(['You are extrapolating into spectral ranges not covered by the input spectrum! ' ...
164        'This routine supports this by linearly extrapolating based on change between last two bins. ' ...
165        'However, this might be physically inappropriate!']);
166end
167
168% Integration of SSI data for each specified spectral band
169% (regrid_ssi.m calculates weighted means of SSI per nm, this is multiplied by binwidth)
170ssi_out=bsxfun(@times,regrid_ssi(ssi_in,wvl_edges_in,wvl_edges_out),bw_out);
171
172% Calculation of solar irradiance fraction (compared to total solar
173% irradiance) in each band
174ssi_frac_out=bsxfun(@rdivide,ssi_out,tsi_in');
175
176% Calculation the average value of tsi
177avtsi=mean(tsi_in)
178disp (avtsi)
179
180%Calculate the anomaly of tsi
181antsi(:,1)=tsi_in(:,1)-avtsi
182
183disp (antsi)
184
185format longEng
186disp (avtsi)
187
188% writing data (including dimensions) to output file
189  % dimension definitions
190time_dimID=netcdf.defDim(ncid_out,'time',0);
191wvl_dimID=netcdf.defDim(ncid_out,'wlen',length(wvl_out));
192bounds_dimID=netcdf.defDim(ncid_out,'nbd',2);
193
194  % variable definitions
195time_out_ID=netcdf.defVar(ncid_out,'time','double',time_dimID);
196time_bnds_out_ID=netcdf.defVar(ncid_out,'time_bnds','double',[bounds_dimID time_dimID]);
197wvl_out_ID=netcdf.defVar(ncid_out,'wlen','double',wvl_dimID);
198wvl_edges_out_ID=netcdf.defVar(ncid_out,'wlen_bnds','double',[wvl_dimID bounds_dimID]);
199bw_out_ID=netcdf.defVar(ncid_out,'wlenbinsize','double',wvl_dimID);
200year_out_ID=netcdf.defVar(ncid_out,'calyear','double',time_dimID);
201month_out_ID=netcdf.defVar(ncid_out,'calmonth','double',time_dimID);
202day_out_ID=netcdf.defVar(ncid_out,'calday','double',time_dimID);
203tsi_out_ID=netcdf.defVar(ncid_out,'tsi','float',time_dimID);
204antsi_out_ID=netcdf.defVar(ncid_out,'antsi','float',time_dimID);
205ssi_out_ID=netcdf.defVar(ncid_out,'ssi','float',[wvl_dimID time_dimID]);
206ssi_frac_out_ID=netcdf.defVar(ncid_out,'ssi_frac','float',[wvl_dimID time_dimID]);
207
208  % copy variable attributes from input to output file
209netcdf.copyAtt(ncid_in,time_in_ID,'axis',ncid_out,time_out_ID)
210netcdf.copyAtt(ncid_in,time_in_ID,'long_name',ncid_out,time_out_ID)
211netcdf.copyAtt(ncid_in,time_in_ID,'standard_name',ncid_out,time_out_ID)
212netcdf.copyAtt(ncid_in,time_in_ID,'units',ncid_out,time_out_ID)
213netcdf.copyAtt(ncid_in,time_in_ID,'calendar',ncid_out,time_out_ID)
214netcdf.copyAtt(ncid_in,time_in_ID,'_CoordinateAxisType',ncid_out,time_out_ID)
215netcdf.copyAtt(ncid_in,time_in_ID,'bounds',ncid_out,time_out_ID)
216
217netcdf.copyAtt(ncid_in,time_bnds_in_ID,'long_name',ncid_out,time_bnds_out_ID)
218netcdf.copyAtt(ncid_in,time_bnds_in_ID,'units',ncid_out,time_bnds_out_ID)
219
220netcdf.copyAtt(ncid_in,wvl_in_ID,'standard_name',ncid_out,wvl_out_ID)
221netcdf.copyAtt(ncid_in,wvl_in_ID,'long_name',ncid_out,wvl_out_ID)
222netcdf.copyAtt(ncid_in,wvl_in_ID,'units',ncid_out,wvl_out_ID)
223netcdf.copyAtt(ncid_in,wvl_in_ID,'bounds',ncid_out,wvl_out_ID)
224
225netcdf.copyAtt(ncid_out,wvl_edges_in_ID,'long_name',ncid_out,wvl_edges_out_ID)
226netcdf.copyAtt(ncid_out,wvl_edges_in_ID,'units',ncid_out,wvl_edges_out_ID)
227
228netcdf.copyAtt(ncid_in,bw_in_ID,'long_name',ncid_out,bw_out_ID)
229netcdf.copyAtt(ncid_in,bw_in_ID,'units',ncid_out,bw_out_ID)
230
231netcdf.copyAtt(ncid_in,year_in_ID,'long_name',ncid_out,year_out_ID)
232
233netcdf.copyAtt(ncid_in,month_in_ID,'long_name',ncid_out,month_out_ID)
234
235netcdf.copyAtt(ncid_in,day_in_ID,'long_name',ncid_out,day_out_ID)
236
237netcdf.copyAtt(ncid_in,tsi_in_ID,'standard_name',ncid_out,tsi_out_ID)
238netcdf.copyAtt(ncid_in,tsi_in_ID,'long_name',ncid_out,tsi_out_ID)
239netcdf.copyAtt(ncid_in,tsi_in_ID,'units',ncid_out,tsi_out_ID)
240netcdf.copyAtt(ncid_in,tsi_in_ID,'cell_methods',ncid_out,tsi_out_ID)
241
242netcdf.putAtt(ncid_out,antsi_out_ID,'standard_name','total solar_irradiance anomaly')
243netcdf.putAtt(ncid_out,antsi_out_ID,'long_name','reconstructed total solar irradiance anomaly at 1 AU')
244netcdf.putAtt(ncid_out,antsi_out_ID,'units','W m^-2')
245
246netcdf.putAtt(ncid_out,ssi_out_ID,'long_name','reconstructed solar irradiance at 1 AU within respective bands')
247netcdf.putAtt(ncid_out,ssi_out_ID,'units','W m^-2')
248
249netcdf.putAtt(ncid_out,ssi_frac_out_ID,'long_name','reconstructed fraction of total solar irradiance at 1 AU within respective bands')
250netcdf.putAtt(ncid_out,ssi_frac_out_ID,'units','1')
251
252netcdf.close(ncid_in);
253netcdf.endDef(ncid_out);
254
255netcdf.putVar(ncid_out,time_out_ID,0,length(time_in),time_in)
256netcdf.putVar(ncid_out,time_bnds_out_ID,time_bnds_in)
257netcdf.putVar(ncid_out,wvl_out_ID,wvl_out)
258netcdf.putVar(ncid_out,wvl_edges_out_ID,wvl_edges_out)
259netcdf.putVar(ncid_out,bw_out_ID,bw_out)
260netcdf.putVar(ncid_out,year_out_ID,year_in)
261netcdf.putVar(ncid_out,month_out_ID,month_in)
262netcdf.putVar(ncid_out,day_out_ID,day_in)
263netcdf.putVar(ncid_out,tsi_out_ID,tsi_in)
264netcdf.putVar(ncid_out,antsi_out_ID,antsi)
265netcdf.putVar(ncid_out,ssi_out_ID,ssi_out)
266netcdf.putVar(ncid_out,ssi_frac_out_ID,ssi_frac_out)
267
268netcdf.sync(ncid_out);
269netcdf.close(ncid_out);
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