Harmonisation

.gitignore

@@ -1,12 +1,30 @@
+# Output plots
+*.pdf
+
 # Processed data
 data/national/ceds/processed
 data/national/gfed/processed
 data/national/gfed-bb4cmip/processed
+data/global/adam-et-al-2024/processed
+data/global/edgar/processed/
+data/global/gcb/processed
+data/global/velders-et-al-2022/processed/
+data/global/wmo-2022/processed
 data/combined-processed-output
+data/global-composite
+
+# Raw WMO data
+data/global/wmo-2022/data_raw
+
+# EDGAR data
+data/global/edgar/data_raw/
 
 # RCMIP data
 data/global/rcmip/data_raw
 
+# GCB raw data
+data/global/gcb/data_raw
+
 # CEDS data
 data/national/ceds/data_raw
 

data/global/adam-et-al-2024/data_raw/HFC-23_Global_annual_emissions.csv

@@ -0,0 +1,62 @@
+# Global annual emissions for HFC-23
+# Outputs from AGAGE 12-box model
+# Time stamps are the centre of the averaging period
+#            ||90-30N| 30-0N| 0-30S | 30-90S
+#            ||=============================
+# 1000-500hPa|| Box0 | Box1 | Box2  | Box3
+#  500-200hPa|| Box4 | Box5 | Box6  | Box7
+#  200-   hPa|| Box8 | Box9 | Box10 | Box11
+# Contact Matt Rigby or Luke Western (University of Bristol)
+# [email protected]/[email protected]
+# File created 2024-02-12 14:24:10.839835+00:00
+# Units: Gg/yr
+Year,Month,Decimal_date,Global_annual_emissions,Global_annual_emissions_1-sigma
+1975,6,1975.46,3.3082381022962006,0.9783583998800276
+1976,6,1976.46,3.412108853553091,1.1920795413621776
+1977,6,1977.46,3.6542986657185987,1.1675173798851615
+1978,6,1978.46,4.055111559383712,1.0500178334971184
+1979,6,1979.46,4.216507724685216,0.9573601350210964
+1980,6,1980.46,4.3261330935472495,0.9416762796963863
+1981,6,1981.46,4.227156807146147,0.899283826576965
+1982,6,1982.46,3.834191418686187,0.9065827719459081
+1983,6,1983.46,4.656061392177526,0.9586185322863234
+1984,6,1984.46,5.090458271193384,0.8692295602085965
+1985,6,1985.46,5.350316483906609,0.8494280517555504
+1986,6,1986.46,5.7479251719451545,0.8573542430396427
+1987,6,1987.46,5.794054187638121,0.8278671083460137
+1988,6,1988.46,6.748611281315206,0.8330146381055876
+1989,6,1989.46,7.618529880341374,0.8604183181649075
+1990,6,1990.46,7.082930135477382,0.8294217921927168
+1991,6,1991.46,6.619382252408158,0.8518339351973709
+1992,6,1992.46,7.2788473124675335,0.8207619866400576
+1993,6,1993.46,8.188958959406902,0.8020050274215419
+1994,6,1994.46,8.177011135188787,0.8085693031591361
+1995,6,1995.46,9.088606061045377,0.8109785535012753
+1996,6,1996.46,9.520253967726967,0.8314454478187091
+1997,6,1997.46,10.100806056679165,0.8314476215021896
+1998,6,1998.46,10.42264981740719,0.7671522971499976
+1999,6,1999.46,10.348867029978964,0.8064610668983494
+2000,6,2000.46,11.064797997100351,0.8884679319803815
+2001,6,2001.46,8.939704475878814,0.8574240863213126
+2002,6,2002.46,9.46819793866396,0.8554461895471467
+2003,6,2003.46,9.637622482754454,0.8606079273538187
+2004,6,2004.46,11.866019158721869,0.8757073162380118
+2005,6,2005.46,12.652068493728821,0.8672572218560374
+2006,6,2006.46,14.336407780532454,0.8865562476484358
+2007,6,2007.46,11.611248947209765,0.8359125762498057
+2008,6,2008.46,11.45835028503325,0.6308386844128152
+2009,6,2009.46,9.59748778636138,0.5630194265141016
+2010,6,2010.46,10.52849805758974,0.5964640914139149
+2011,6,2011.46,11.728609157340069,0.6115274290185482
+2012,6,2012.46,12.919691799546976,0.6340449827646341
+2013,6,2013.46,13.923964302794822,0.652588179698151
+2014,6,2014.46,14.435299277869296,0.6905524908523142
+2015,6,2015.46,12.873910864335862,0.6370848043270962
+2016,6,2016.46,12.786738245751446,0.6562897041216607
+2017,6,2017.46,15.123098674685131,0.7198020100101903
+2018,6,2018.46,16.832849727946375,0.73345354496374
+2019,6,2019.46,17.311924936295306,0.7584004353710423
+2020,6,2020.46,16.50514026193276,0.755355605623176
+2021,6,2021.46,15.533804205481097,0.7596433598791492
+2022,6,2022.46,13.954471607853897,0.7664611734140768
+2023,6,2023.46,14.051843086776302,0.9477747363753392

data/global/adam-et-al-2024/data_raw/README.md

@@ -0,0 +1,4 @@
+# Adam et al. 2024 data
+
+Paper: https://doi.org/10.1038/s43247-024-01946-y
+Data supplied by the authors directly.

data/global/velders-et-al-2022/data_raw/README.md

@@ -0,0 +1,4 @@
+Data provided by Guus Velders ([email protected]), Nov. 29, 2024.
+
+This is a temporary solution.
+We will use the Zenodo record when it is updated.

data/global/velders-et-al-2022/data_raw/README.txt

@@ -0,0 +1,13 @@
+Data accompanying the article
+
+"Projections of hydrofluorocarbon (HFC) emissions and the resulting global warming based on recent trends in observed
+abundances and current policies" by
+
+Guus J.M. Velders, John S. Daniel, Stephen A. Montzka, Isaac Vimont, Matthew Rigby, Paul B. Krummel, Jens Muhle,
+Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, and Dickon Young
+
+Output files of the scenario model for the Kigali Amendment (data in t/yr or tCO2-eq/yr)
+   - KGL2021_constrProdEmis_ObsAgage_2500_OECD-SSP5.dat:  upper range
+   - Data extended to 2500 by keeping the GDP and population constant past 2100
+
+Guus Velders ([email protected]), Nov. 29, 2024

data/global/wmo-2022/data_raw/C2F6/outputs/C2F6_Global_annual_emissions.csv

@@ -0,0 +1,62 @@
+# Global annual emissions for C2F6
+# Outputs from AGAGE 12-box model
+# Time stamps are the centre of the averaging period
+#            ||90-30N| 30-0N| 0-30S | 30-90S
+#            ||=============================
+# 1000-500hPa|| Box0 | Box1 | Box2  | Box3
+#  500-200hPa|| Box4 | Box5 | Box6  | Box7
+#  200-   hPa|| Box8 | Box9 | Box10 | Box11
+# Contact Matt Rigby or Luke Western (University of Bristol)
+# [email protected]/[email protected]
+# File created 2022-05-06 13:57:04.510860+00:00
+# Units: Gg/yr
+Year,Month,Decimal_date,Global_annual_emissions,Global_annual_emissions_1-sigma
+1973,6,1973.46,2.0079454531542074,0.2147636836757873
+1974,6,1974.46,2.06195325203483,0.19472037347828922
+1975,6,1975.46,1.8979078807368006,0.19273444474993745
+1976,6,1976.46,1.830444820630274,0.21858787053373865
+1977,6,1977.46,1.8940150735651813,0.19414344068139341
+1978,6,1978.46,1.966874770236488,0.21248342896081746
+1979,6,1979.46,2.0349533887230007,0.2384128693778127
+1980,6,1980.46,2.0622560700147337,0.22132260411116855
+1981,6,1981.46,1.893829099749067,0.20994528786198624
+1982,6,1982.46,1.6349034648043952,0.2160120448766821
+1983,6,1983.46,1.7313384089547503,0.21373119782491354
+1984,6,1984.46,2.266643877579255,0.23323396594863205
+1985,6,1985.46,2.3111345601743167,0.2158281246236931
+1986,6,1986.46,2.2426380348194566,0.2155943101115059
+1987,6,1987.46,2.0917832822617446,0.21895079391810188
+1988,6,1988.46,2.151259271466081,0.2183837396888249
+1989,6,1989.46,2.2700923147831875,0.22506645514557735
+1990,6,1990.46,2.299541445538168,0.2181625908067751
+1991,6,1991.46,2.3098490267598204,0.21752875840309469
+1992,6,1992.46,2.106891382558718,0.21364803947403047
+1993,6,1993.46,2.102876606977528,0.21187460641188385
+1994,6,1994.46,2.079866865940978,0.21355630635518702
+1995,6,1995.46,2.2865638574440306,0.2129887297351558
+1996,6,1996.46,2.591237829378663,0.2148005861256201
+1997,6,1997.46,2.925239322380899,0.20407486612791897
+1998,6,1998.46,2.957889384961916,0.2090814019899756
+1999,6,1999.46,3.0514272588947553,0.20871109143734046
+2000,6,2000.46,3.102689945987825,0.2216620972703224
+2001,6,2001.46,2.8690536138370724,0.2029512779952538
+2002,6,2002.46,2.8517185759003127,0.20310131020208028
+2003,6,2003.46,2.6629576036186786,0.1863288068314249
+2004,6,2004.46,2.3989333845876217,0.16440684838385813
+2005,6,2005.46,2.238795891971414,0.15934356197453414
+2006,6,2006.46,2.3015381449268517,0.1502794064899895
+2007,6,2007.46,2.318492396593854,0.14326019744336865
+2008,6,2008.46,2.0762184843864833,0.14720374294607805
+2009,6,2009.46,1.8570969198323544,0.1451074874458068
+2010,6,2010.46,1.9757946555097197,0.14419604442605832
+2011,6,2011.46,1.94415200227046,0.14523805704535342
+2012,6,2012.46,1.9079333239879899,0.13308757378407907
+2013,6,2013.46,1.9373561059909539,0.13238380172411768
+2014,6,2014.46,1.9465674803031694,0.1278600018676643
+2015,6,2015.46,1.9677858836596582,0.13299912112743487
+2016,6,2016.46,2.1389154431359017,0.13622997189197536
+2017,6,2017.46,2.2674909334704263,0.14162107433942348
+2018,6,2018.46,2.2119538875579834,0.13869458997583145
+2019,6,2019.46,2.2036141167563446,0.13613941082841757
+2020,6,2020.46,2.1686617929881904,0.13875398679766335
+2021,6,2021.46,2.2563987648752435,0.1924415060909131

data/global/wmo-2022/data_raw/CF4/outputs/CF4_Global_annual_emissions.csv

@@ -0,0 +1,62 @@
+# Global annual emissions for CF4
+# Outputs from AGAGE 12-box model
+# Time stamps are the centre of the averaging period
+#            ||90-30N| 30-0N| 0-30S | 30-90S
+#            ||=============================
+# 1000-500hPa|| Box0 | Box1 | Box2  | Box3
+#  500-200hPa|| Box4 | Box5 | Box6  | Box7
+#  200-   hPa|| Box8 | Box9 | Box10 | Box11
+# Contact Matt Rigby or Luke Western (University of Bristol)
+# [email protected]/[email protected]
+# File created 2022-05-06 13:57:02.711846+00:00
+# Units: Gg/yr
+Year,Month,Decimal_date,Global_annual_emissions,Global_annual_emissions_1-sigma
+1973,6,1973.46,17.92716025637551,1.3066894867349428
+1974,6,1974.46,18.653299439212248,1.3232037098693277
+1975,6,1975.46,17.18894418769766,1.261566932898014
+1976,6,1976.46,16.87643898417258,1.3201816864548468
+1977,6,1977.46,17.72383592630971,1.278778476522782
+1978,6,1978.46,18.163972717206263,1.3243146129503862
+1979,6,1979.46,18.762477044600306,1.2889222242124694
+1980,6,1980.46,18.262045708069788,1.3630679595929562
+1981,6,1981.46,17.515370015672943,1.2699010657152385
+1982,6,1982.46,15.921252459825107,1.2602857810057837
+1983,6,1983.46,16.001548136731085,1.3134593263224519
+1984,6,1984.46,17.118331830614785,1.355401643945485
+1985,6,1985.46,16.41348270000749,1.2714070976356713
+1986,6,1986.46,15.593639697452891,1.2522506186701279
+1987,6,1987.46,15.960189522649218,1.3018384753625203
+1988,6,1988.46,16.11119723111036,1.2242669578796552
+1989,6,1989.46,16.386421786472216,1.2695082639969362
+1990,6,1990.46,15.5480897171484,1.2359964278252153
+1991,6,1991.46,15.53706864579676,1.2258813890989837
+1992,6,1992.46,13.226407159206437,1.1912038919241847
+1993,6,1993.46,12.45592769420326,1.1844928586805183
+1994,6,1994.46,11.445083718663897,1.1866800396981767
+1995,6,1995.46,11.498757947441016,1.1448568300789324
+1996,6,1996.46,11.4355742090501,1.1952200144825766
+1997,6,1997.46,11.316001369740775,1.113781232533771
+1998,6,1998.46,11.125525874544266,1.2000834341482407
+1999,6,1999.46,11.070059449618213,1.165116720974689
+2000,6,2000.46,10.982572045119708,1.1725861397320938
+2001,6,2001.46,10.373885287856213,1.1321219648835332
+2002,6,2002.46,10.43503109249973,1.1123411459166683
+2003,6,2003.46,10.997460116931789,1.0314430440642788
+2004,6,2004.46,10.989421585356716,0.988448047437027
+2005,6,2005.46,10.746792821111343,0.9014935116566809
+2006,6,2006.46,10.950571202478505,0.8297420079751083
+2007,6,2007.46,10.912631867280977,0.8136918973778051
+2008,6,2008.46,10.240715819685489,0.7883416207045977
+2009,6,2009.46,9.6453176650851,0.8226950962575802
+2010,6,2010.46,10.219736763929701,0.8074741200112729
+2011,6,2011.46,10.964861573084887,0.8295164052346766
+2012,6,2012.46,11.174480376199154,0.8381134894239762
+2013,6,2013.46,11.124941193445876,0.8020950058381047
+2014,6,2014.46,11.250069575206522,0.8412603125730236
+2015,6,2015.46,11.975292599558498,0.8859332290027491
+2016,6,2016.46,12.947901930554805,0.8945874709797956
+2017,6,2017.46,13.910992392142996,0.8649547529305697
+2018,6,2018.46,14.339609082955414,0.8990556244649821
+2019,6,2019.46,14.443486311623142,0.9334746935741339
+2020,6,2020.46,14.541187658098986,1.0549431621710736
+2021,6,2021.46,14.733364481344163,1.37469073930619

data/global/wmo-2022/data_raw/README.md

@@ -0,0 +1,3 @@
+Data from [the 2022 WMO Ozone Assessment](https://csl.noaa.gov/assessments/ozone/2022/).
+
+Provided by the authors.

data/scenarios/data_raw/.gitignore

@@ -0,0 +1,2 @@
+# Ignore the download scenarios, they should be grabbed from the database
+*__scenarios-scenariomip__*.csv

data/scenarios/data_raw/README.md

@@ -0,0 +1,27 @@
+Scenario data can be downloaded from IIASA's resources here:
+https://data.ece.iiasa.ac.at/ssp-submission.
+
+Downloading the data can be done with the following commands.
+(if you're not on a unix-based system,
+create a virtual environment using whatever environment manager you like
+then remove `venv/bin/` from all the commands below).
+
+```sh
+# Install pyam-iamc
+python3 -m venv venv
+venv/bin/pip install --upgrade pip wheel
+venv/bin/pip install pyam-iamc tqdm
+```
+
+Login with ixmp4
+
+```sh
+# Note that this saves your login on your machine in plain text, be careful.
+venv/bin/ixmp4 login <your-username>
+```
+
+Then, download the data
+
+```sh
+venv/bin/python download-database.py
+```

data/scenarios/data_raw/download-database.py

@@ -0,0 +1,31 @@
+import datetime as dt
+from pathlib import Path
+
+import pyam
+import tqdm
+
+OUT_DIR = Path(__file__).parents[0]
+
+time_id = dt.datetime.now().strftime("%Y%m%d-%H%M%S")
+
+# Establish connection to the legacy pyam platform 'ssp-submission'
+pyam.iiasa.Connection("ssp_submission")
+conn_ssp = pyam.iiasa.Connection("ssp_submission")
+props = conn_ssp.properties().reset_index()
+
+# Retrieve the desired scenarios' emissions
+# (download everything; loop over model-scenario combinations to not blow up RAM)
+for model, scenario in tqdm.tqdm(
+    zip(props["model"], props["scenario"]), total=len(props["model"]), desc="Model-scenario combinations"
+):
+    print(f"Grabbing {model=} {scenario=}")
+    df = pyam.read_iiasa("ssp_submission", model=model, scenario=scenario, variable="Emissions|*")
+    if df.empty:
+        print(f"No data for {model=} {scenario=}")
+        continue
+
+    # Write out the scenario data
+    output_filename = f"{time_id}__scenarios-scenariomip__{model}__{scenario}.csv".replace("/", "_").replace(" ", "-")
+    output_file = OUT_DIR / output_filename
+    df.to_csv(output_file)
+    print(f"Data for {model} {scenario} has been written to {output_file}")

gcages/pyproject.toml

@@ -8,7 +8,14 @@ authors = [
 license = { text = "placeholder" }
 requires-python = ">=3.9"
 dependencies = [
+    # TODO: add min pins here
+    "aneris-iamc>=0.3.0",
+    "loguru",
+    "openscm-units",
     "pandas",
+    "scipy",
+    "tqdm",
+    "typer",
 ]
 readme = "README.md"
 classifiers = [

notebooks/0101_CEDS-prepare.py

@@ -26,6 +26,7 @@
     CEDS_EXPECTED_NUMBER_OF_REGION_VARIABLE_PAIRS_IN_GLOBAL_HARMONIZATION,
     CEDS_PROCESSING_ID,
     DATA_ROOT,
+    HISTORY_SCENARIO_NAME,
 )
 from emissions_harmonization_historical.units import assert_units_match_wishes
 
@@ -157,6 +158,10 @@
 # add global
 ceds = add_global(ceds)
 
+# %%
+# Rename NMVOC
+ceds = ceds.rename(index=lambda v: v.replace("NMVOC", "VOC"))
+
 # %%
 ceds_reformatted = ceds.rename_axis(index={"em": "variable", "country": "region"})
 ceds_reformatted
@@ -165,7 +170,7 @@
 # rename to IAMC-style variable names including standard index order
 ceds_reformatted_iamc = (
     ceds_reformatted.pix.format(variable="Emissions|{variable}|{sector}", drop=True)
-    .pix.assign(model="History", scenario=f"CEDSv{ceds_release}")
+    .pix.assign(scenario=HISTORY_SCENARIO_NAME, model=f"CEDSv{ceds_release}")
     .reorder_levels(["model", "scenario", "region", "variable", "unit"])
 ).sort_values(by=["region", "variable"])
 ceds_reformatted_iamc