Preprints
https://doi.org/10.5194/gmd-2022-128
https://doi.org/10.5194/gmd-2022-128
Submitted as: model description paper
11 May 2022
Submitted as: model description paper | 11 May 2022

stoPET v1.0: A stochastic potential evapotranspiration generator for simulation of climate change impacts

Dagmawi Teklu Asfaw1, Michael Bliss Singer2,3,4, Rafael Rosolem5,6, David MacLeod1, Mark Cuthbert2,7, Edisson Quichimbo Miguitama2, Manuel F. Rios Gaona2, and Katerina Michaelides1,4,6 Dagmawi Teklu Asfaw et al.
  • 1School of Geographical Sciences, University of Bristol, Bristol, UK
  • 2School of Earth and Environmental Sciences, Cardiff University, Cardiff, UK
  • 3Water Research Institute, Cardiff University, Cardiff, UK
  • 4Earth Research Institute, University of California Santa Barbara, Santa Barbara, USA
  • 5Department of Civil Engineering, University of Bristol, UK
  • 6Cabot Institute for the Environment, University of Bristol, Bristol, UK
  • 7School of Civil and Environmental Engineering, The University of New South Wales (UNSW), Sydney, Australia

Abstract. Potential evapotranspiration (PET) represents the evaporative demand in the atmosphere for the removal of water from the land and is an essential variable for understanding and modelling land-atmosphere interactions. Weather generators are often used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. Here we develop a stochastic PET generator, stoPET, by leveraging a recently published global dataset of hourly PET at 0.1° resolution (hPET). stoPET is designed to simulate realistic time series of PET that capture the diurnal and seasonal variability of hPET and to support the simulation of various scenarios of climate change. The parsimonious model is based on a sine function fitted to the monthly average diurnal cycle of hPET, producing parameters that are then used to generate synthetic series of hourly PET at any 0.1° land surface point between 55° N and 55° S. stoPET also incorporates three methods to account for potential future changes in atmospheric evaporative demand to rising global temperature. These include 1) user-defined percentage increase of annual PET; 2) a step change in PET based on a unit increase in temperature, and 3) extrapolation of the historical trend in hPET into the future. We evaluated stoPET at a regional scale and at twelve locations spanning arid and humid climatic regions around the globe. stoPET generates PET distributions that are statistically similar to hPET, capturing its diurnal/seasonal dynamics, indicating that stoPET produces physically plausible diurnal and seasonal PET variability. We provide examples of how stoPET can generate large ensembles of PET for future climate scenario analysis in sectors like agriculture and water resources, with minimal computational demand.

Journal article(s) based on this preprint

Dagmawi Teklu Asfaw et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-128', Anonymous Referee #1, 12 May 2022
    • AC1: 'Reply on RC1', Dagmawi Asfaw, 25 May 2022
      • RC3: 'Reply on AC1', Taesam Lee, 07 Jun 2022
  • RC2: 'Comment on gmd-2022-128', Anonymous Referee #2, 06 Jun 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Dagmawi Asfaw on behalf of the Authors (08 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Reject (11 Jul 2022) by Charles Onyutha
ED: Referee Nomination & Report Request started (05 Aug 2022) by Min-Hui Lo
RR by Taesam Lee (12 Aug 2022)
RR by Anonymous Referee #3 (17 Aug 2022)
ED: Reconsider after major revisions (30 Aug 2022) by Min-Hui Lo
AR by Dagmawi Asfaw on behalf of the Authors (13 Nov 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (23 Nov 2022) by Min-Hui Lo
RR by Anonymous Referee #3 (08 Dec 2022)
ED: Publish subject to minor revisions (review by editor) (09 Dec 2022) by Min-Hui Lo
AR by Dagmawi Asfaw on behalf of the Authors (16 Dec 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (02 Jan 2023) by Min-Hui Lo

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-128', Anonymous Referee #1, 12 May 2022
    • AC1: 'Reply on RC1', Dagmawi Asfaw, 25 May 2022
      • RC3: 'Reply on AC1', Taesam Lee, 07 Jun 2022
  • RC2: 'Comment on gmd-2022-128', Anonymous Referee #2, 06 Jun 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Dagmawi Asfaw on behalf of the Authors (08 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Reject (11 Jul 2022) by Charles Onyutha
ED: Referee Nomination & Report Request started (05 Aug 2022) by Min-Hui Lo
RR by Taesam Lee (12 Aug 2022)
RR by Anonymous Referee #3 (17 Aug 2022)
ED: Reconsider after major revisions (30 Aug 2022) by Min-Hui Lo
AR by Dagmawi Asfaw on behalf of the Authors (13 Nov 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (23 Nov 2022) by Min-Hui Lo
RR by Anonymous Referee #3 (08 Dec 2022)
ED: Publish subject to minor revisions (review by editor) (09 Dec 2022) by Min-Hui Lo
AR by Dagmawi Asfaw on behalf of the Authors (16 Dec 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (02 Jan 2023) by Min-Hui Lo

Journal article(s) based on this preprint

Dagmawi Teklu Asfaw et al.

Dagmawi Teklu Asfaw et al.

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Short summary
stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.