Project Deliverables (Updated periodically)



  • D2.1 Report on historical trends in climate/water (Task 2.1)
  • D2.2 Report on socio-economic, demographic and population trends in HAD (Task 2.2)
  • D2.3 Report on links between land use change and climate (Task 2.2)
  • D2.4 Report on future climate scenarios in HAD (Task 2.3)


  • D3.1 CUWALID model for water and food insecurity in drylands (Task 3.1)
  • D3.2 Report on modeled HAD water/food derived from seasonal forecasts (Task 3.2)
  • D3.3 Report on trends in historical HAD water/food using CUWALID (Task 3.1)
  • D3.4 Report on long-term projections of water/food in HAD for climate services (Task 3.3)
  • D3.5 WajihaCast mobile phone app for water/food forecasts to end-users (Task 3.4)
  • D3.6 Report on WajihaCast app design, development, implementation (Task 3.4)


  • D4.1 Expanded climate/water data networks throughout HAD (Task 4.3)
  • D4.2 Increased capacity to produce media content on climate adaptation (Kenya) (Task 4.1)
  • D4.3 Regional extension workshops on WajihaCast and climate change (Task 4.2)
  • D4.4 Training workshops for ICPAC staff on CUWALID (Task 4.2)
  • D4.5 Report on machine-learning methods of forecasting (Task 4.3)
  • D4.6 Inclusion of CUWALID-based forecasts in GHACOF, IFRAH, and FEWS NET (Task 4.3)
  • D4.7 Technical workshops on CUWALID for stakeholders (Task 4.2)
  • D4.8 Report on future-proof climate adaptation/reslience policy framework (Task 4.4)
  • D4.9 Regional and international policy engagement workshops (Task 4.4)






Academic Peer Review Publications Generated by DOWN2EARTH

Student and postdoc work denoted by *.

16) *Rigby, J. M., & Preist, C. (2023). Towards User-Centred Climate Services: the Role of Human-Computer Interaction. Paper presented at the Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, Hamburg, Germany. doi:10.1145/3544548.3580663. pdf

15) *Koppa, A., *Keune, J., *MacLeod, D.A., Singer, M.B., Nietod, R., Gimeno, L., Michaelides, K., Rosolem, R., Otieno, G., Tadege, A., Miralles, D.G. (In Review); A Lagrangian analysis of the sources of rainfall over the Horn of Africa Drylands

14) *MacLeod, D.A., *Quichimbo, E.A., Michaelides, K., *Asfaw, D.T., Rosolem, R., Cuthbert, M.O., Otenyo, E., Segele, Z., *Rigby, J.M., Otieno, G., Hassaballah, K., Tadege, A., Singer, M.B. (2023); Translating seasonal climate forecasts into water balance forecasts for decision making, PLOS Climate, 2(3):e0000138, doi:10.1371/journal.pclm.0000138. pdf

13) Streefkerk, I. N., de Bruijn, J., Haer, T., Van Loon, A. F., Quichimbo, E. A., Wens, M., et al. (2023). A coupled agent-based model to analyse human-drought feedbacks for agropastoralists in dryland regions, Frontiers in Water, 4, doi:10.3389/frwa.2022.1037971. pdf

12) *Asfaw, D.T., Singer, M.B., Rosolem, R., Cuthbert, M.O., *Quichimbo, E.A., *MacLeod, D.A., *Rios Gaona, M.F., Michaelides, K. (2023); StoPET v1.0: A stochastic potential evapotranspiration generator for simulation of climate change impacts, Geoscientific Model Development, 16(2), 557-571, doi:10.5194/gmd-16-557-2023. pdf

11) *Deman, V.M.H., *Koppa, A., Waegeman, W., *MacLeod, D.A., Singer, M.B., Miralles, D.G. (2022); Seasonal prediction of Horn of Africa long rains using machine learning: The pitfalls of preselecting correlated predictors, Frontiers in Water, Vol. 4, doi:10.3389/frwa.2022.1053020. pdf

10) *Adloff, M., Singer, M.B., *MacLeod, D.A., Michaelides, K., *Mehrnegar, N., Hansford, E., Funk, C., Mitchell, D. (2022); Sustained water storage in East African drylands dominated by seasonal rainfall extremes, Geophysical Research Letters, 49(21):e2022GL099299, doi:10.1029/2022GL099299. pdf.

9) *Rigby, J.M., Yohannis, A., Preist, C., Singer, M.B., Waema, T., Wausi, A., Michaelides, K. (2022); Climate services for the Greater Horn of Africa: Interviews exploring practitioner perspectives from Kenya and beyond, Climate and Development, 1-13, doi:10.1080/17565529.2022.2074350. pdf.

8) *Koppa, A., Rains, D., Hulsman, P., Poyatos, R., & Miralles, D. G. (2022). A deep learning-based hybrid model of global terrestrial evaporation, Nature Communications, 13(1), 1912, doi:10.1038/s41467-022-29543-7. pdf

7) *Quichimbo, E.A., Singer, M.B., Michaelides, K., Hobley, D., Rosolem, R., Cuthbert, M.O. (2021). DRYP 1.0: A parsimonious hydrological model of DRYland Partitioning of the water balance, Geoscientific Model Development, doi:10.5194/gmd-2021-137. pdf

6) *MacLeod, D., Kniveton, D.R., Todd, M.C. (2021). Playing the long game: Anticipatory action based on seasonal forecasts, Climate Risk Management, 34, 100375, doi:10.1016/j.crm.2021.100375. pdf

5) *Kolstad, E.W., *Macleod, D., Demissie, T.D. (2021). Drivers of subseasonal forecast errors of the East African short rains, Geophysical Research Letters, 48(14), p.e2021GL093292, doi:10.1029/2021GL093292. pdf

4) *Hari, V., Dharmasthala, S., *Koppa, A., Karmakar, S., Kumar, R. (2021). Climate hazards are threatening vulnerable migrants in Indian megacities - Comment, Nature Climate Change, 11, 636–638, doi:10.1038/s41558-021-01105-7. pdf

3) *Koppa, A., Alam, S., Miralles, D.G., & Gebremichael, M. (2021). Budyko-based long-term water and energy balance closure in global watersheds from Earth observations, Water Resources Research, 57, e2020WR028658, doi:10.1029/2020WR028658. pdf

2) *Schrieks, T., Botzen, W.J.W., Wens, M., Haer, T., Aerts, J.C.J.H. (2021). Integrating behavioral theories in agent-based models for agricultural drought risk assessments, Frontiers in Water, 3, doi:10.3389/frwa.2021.686329. pdf

1) Singer, M.B., *Asfaw, D.T., Rosolem, R., Cuthbert, M.O., *Quichimbo, A., Miralles, D.G., MacLeod, D., Michaelides, K. (2021). Hourly potential evapotranspiration at 0.1˚ grid resolution for the global land surface from 1981-present, Scientific Data, 8(224), doi:10.1038/s41597-021-01003-9. pdf

New Datasets Generated by DOWN2EARTH

New Models Generated by DOWN2EARTH

Academic Non-Peer Review Publications

Other Project Outputs

An EU Horizon 2020 Project funded under grant agreement No 869550