Received: 07 May 2022 – Discussion started: 11 May 2022
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.
P6L8: What is the format of skewed normal distribution? Please express the distribution. Why do you choose distribution? Is that common for PET? If yes, include the references. Otherwise, statistical test must be performed to ensure the distribution. Is it possible that noise ratio can be negative? If not, other distribution must do better job such as gamma.
There is no full equation that explains the stochastic simulation model of PET including sine +noise+annual variability. Each element is explained in separate sections. Combined model description must be provided.
The overall comparison between hPET and stoPET is not acceptable since the hPET was employed to build the stoPET model. Naive or other stochasitc model must be used for comparison.
Double cycle of seasonal variability shown in Africa of A4 (Figure9) does not seem perform good. Please describe the potential reasons.
Explanation of the program and data must be provided. Provide specific steps to download the data.
Fig12: stoPET is the stochastic simulation model. One might have wrong implication that the model was not performed good. Separate panels can be used instead of overlapping.
For example of Method 1 and 2, isn’t it better with different user-defined-changes at each year. This reviewer suggest that the authors reasonably set up the scenario to change the annual variation.
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.
stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly...
