Critical importance of tree and non-tree vegetation for African precipitation

Supporting data and material with the following manuscript:

"Critical importance of tree and non-tree vegetation for African precipitation"

Authors:

Te Wierik, S.A. (1,2,4) Keune, J. (3) Miralles, D. (3),Gupta, J. (2), Artzy-Randrup, Y.A (1), Cammeraat, L.H. (1), 

van Loon, E.E. (1)

1 Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, the Netherlands 

2 Governance and Inclusive Development, University of Amsterdam, Amsterdam, the Netherlands 

3 Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium

4 Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, PO Box 60 12 03, 14412 Potsdam, Germany

Last update: 03-07-2024

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DATA 

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1. FLEXPART_output_all Folder containing the precipitation source regions, differentiating between short and tall vegetation, for individual watersheds (NetCDF-file)

Output files (_ALLPBL_biascor-attr_linear_hybrid_monthly_1981-2019_E2P_and_T2P_all.nc) correspond with individual watershed numbers (see below).

Files represent output of moisture tracking framework from Keune et al., 2022. 

2. major_watersheds Folder containing shapefile of the major African watersheds from hydroSHEDS  (major_watersheds.shp)

3. masks Folder containing:

- Mask for all major African watersheds (1 degree) (mask_all_1x1_sum.nc) 

- Mask representing 1) forest loss hotspot region and 2) all cells with > 30% forest loss (1 degree) (mask_forest_loss.nc)

- Mask representing 1) grass,- range- and cropland loss hotspot regions and 2) all cells with >30% grass-, range- and cropland loss (1 degree) (mask_croppasture_loss.nc).

4. grid_area.nc Surface area (m2) of individual gridcells from a 1x1 degree global grid

5. T_tall_short_mean_annual_1981-2019_1deg.nc GLEAM-Hybrid monthly total T and E data, global, 1 degree.

6. vegetation-cover_1deg_monthly_1980-2019.nc MODIS derived vegetation cover fractions of short and tall vegetation and barren soil from MeASURES.

Original data (0.05 degree) is resampled to 1 degree. 

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CODE AND ENVIRONMENT

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Short_tall_Tp_Africa.py Python code to analyze the moisture sources over individual watersheds

Short_tall.yml Necessary environment to run Short-tall_Tp_Africa.py. Make sure the environment is imported and activated before running the script.

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OUTPUT

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1. Figure 1

t_volumetric.png 1d. Mean annual TP flow from trees (km3 year-1)

t_normalized.png 1f. Mean annual TP flux from trees (mm year-1)

h_volumetric.png 1e. Mean annual TP flow from non-tree vegetation (km3 year-1)

h_volumetric.png 1g. Mean annual TP flux from non-tree vegetation (mm year-1)

2. Supplementary Figure 2

extent_t Contributing source regions of P from trees over the African continent using Tmin (mean annual TP > 0.5 mm yr-1).

extent_h Contributing source regions of P from non-tree vegetation over the African continent using Tmin (mean annual TP > 0.5 mm yr-1)

3. Supporting data

0.5pshed_output_allwatersheds CSV file containing output data from all individual watersheds: mean annual contribution of short and tall vegetation (km3/year and mm/year); associated surface area (km2); relative contribution to precipitation from short and tall vegetation (%); relative contribution to dry and wet season precipitation from tall and short vegeation (%) 

0.5pshed_continental_sum_output.csv CSV file containing output data of aggregated means at continental level: mean annual contribution of short and tall vegetation to precipitation over Africa (mm/year and km3/year); associated surface area (km2).

0.5pshed_hotspot_contributions.csv CSV file containing output data of LULC hotspot contributions to precipitation from all individual watersheds: volumetric contribution from hotspot regions (km3); surface area of the hotspot regions (km2); mean annual precipitation (km3/year) and mean annual precipitation from T (km3/year)

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WATERSHED NUMBER REFERENCES:

1 Lake Chad

2 Nile

3 Rift Valley

4 Congo

5 Niger

6 Volta

7 Africa, West Coast

8 Africa, North West Coast

9 Mediterranean South Coast

10 Africa, Red Sea - Gulf of Aden Coast

11 Shebelli - Juba

12 Africa, East Central Coast

13 Madasgacar

14 Zambezi

15 Africa, Indian Ocean Coast

16 Limpopo

17 South Africa, South Coast

18 South Africa, West Coast

19 Orange

20 Africa, South Interior

21 Namibia, Coast

22 Angola, Coast

23 Gulf of Guinea

24 Senegal

25 Africa, North Interior

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REFERENCES & DATA SOURCES

- Keune, J., Schumacher, D.L., and Miralles, D.G. (2022) A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models. Geosci. Model Dev., 15, 1875–1898, 2022 https://doi.org/10.5194/gmd-15-1875-2022

- te Wierik, S.A., Keune, J., Miralles, D.G., Gupta, J., Artzy-Randrup, Y.A., Gimeno, L., Nieto, R., Cammeraat L.H. (2022) The Contribution of Transpiration to Precipitation Over African Watersheds. Water Resources Research, 58, e2021WR031721. https://doi. org/10.1029/2021WR031721

• MEaSUREs vegetation continuous fields (VCF), Yearly, Global, 0.05 degree (https://cmr.earthdata.nasa.gov/search/concepts/C1452975608-LPDAAC_ECS.html; https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MCD12Q1#bands)

• HydroSHEDS data is available via https://data.apps.fao.org/catalog/dataset/7707086d-af3c-41cc-8aa5-323d8609b2d1;

• ERA-Interim data is available via https://apps.ecmwf.int/datasets/.

• GLEAM data is available via https://www.gleam.eu/; 

• MSWEP data is available via http://www.gloh2o.org/. 

• OAFlux data is available from https://oaflux.whoi.edu/data-access/.