Development of Consistent Global Long-Term Records of Atmospheric Evaporative Demand
Evapotranspiration (ET) can be considered as the linchpin climate variable because it forms the link between the water, energy and carbon cycles at the Earth s surface. Understanding the evolution of ET is a key factor in climate change, playing a central role in the potential acceleration of the water cycle, providing land-atmosphere feedbacks, and modulating extreme events such as droughts and heatwaves. Controls on terrestrial ET are particularly complicated and are constrained by surface radiation, the atmospheric boundary layer, and the state of the vegetation-soil system. Accurately modeling terrestrial evapotranspiration processes is fundamental to understanding past changes in climate, and climate predictions and projections. ET is driven by atmospheric demand (radiative and aerodynamic controls) and surface limitations (environmental and ecophysical controls). Much of the uncertainty in ET derives from uncertainties in atmospheric evaporative demand, often referred to as potential evapotranspiration (PET). This quantifies the combined effects of available radiation for evaporation and the ability of the atmosphere to accept evaporated water. Multiple studies have documented regional changes in the components of PET, and have shown that changes in pan evaporation, a measurement proxy for PET, have been driven by changes in solar radiation, vapor pressure deficit and wind speed. However, global, long-term estimates of PET and its trends are very uncertain because of the lack of observations. Yet this is crucial for understanding the potential for acceleration of the hydrological cycle and its extremes, the role of temperature as a presumed forcing of change, and the robustness of projected future changes from climate models.
The goal of this proposal is to develop an ESDR for PET, including the supporting surface meteorological and radiation data. It may appear that an ESDR for PET is rather limited, given that an ESDR for actual ET is more directly relevant to a range of science problems, but this proposal shows the importance of providing a consistent, long-term, global dataset for PET as a necessary first step towards a consistent global ET dataset and the challenges of doing this. The project will provide a 1982-2008 (and potentially longer) dataset of land atmospheric evaporative demand at 3-hour, 0.25-degree resolution. Additionally, the project will develop long-term and consistent estimates of the ancillary data sets of near surface meteorology and radiation, needed to calculate the global variation in PET, including its uncertainties. We will use a suite of existing and newly reprocessed observational and remote sensing datasets of radiation and meteorology to determine the uncertainties in long-term trends in forcing variables of PET. Uncertainties will be derived from detailed analysis of the consistency of remote sensing products and how they replicate in-situ data trends. These will be merged with empirical estimates and reanalysis data to form consistent records of forcing variables.
The proposed PET ESDR addresses NASA’s goal of developing long-term, consistent Earth System Data Records that can drive advancements in understanding the climate system by taking a prerequisite step towards improved understanding of the role of ET in a changing climate and thus making progress towards better prediction of climate change and particularly extreme events. The work contributes exactly to the MEaSURES call by developing a PET ESDR that integrates across satellite products and merges with available in-situ observations. The work is well aligned with the recommended GCOS Essential Climate Variables for the near surface atmosphere and is essential for subsequent derivation of ET, closure of the terrestrial water and energy budgets, and improved land surface ECVs. Furthermore, the ESDR will contribute to evaluation of impacts related to humidity, radiation and wind and for design of renewable energy systems.
Justin Sheffield - PI, Princeton University
Page Last Updated: May 2, 2019 at 12:02 PM EDT