Spatial and Temporal Variability of Potential Evaporation across North American Forests

Abstract

Given the widespread ecological implications that would accompany any significant change in evaporative demand of the atmosphere, this study investigated spatial and temporal variation in several accepted expressions of potential evaporation (PE). The study focussed on forest regions of North America, with 1 km-resolution spatial coverage and a monthly time step, from 1951-2014. We considered Penman's model (E Pen ), the Priestley-Taylor model (E PT ), 'reference' rates based on the Penman-Monteith model for grasslands (E RG ), and reference rates for forests that are moderately coupled (E RFu ) and well coupled (E RFc ) to the atmosphere. To give context to the models, we also considered a statistical fit (E PanFit ) to measurements of pan evaporation (E Pan ). We documented how each model compared with E Pan , differences in attribution of variance in PE to specific driving factors, mean spatial patterns, and time trends from 1951-2014. The models did not agree strongly on the sensitivity to underlying drivers, zonal variation of PE, or on the magnitude of trends from 1951-2014. Sensitivity to vapour pressure deficit (D a ) differed among models, being absent from E PT and strongest in E RFc . Time trends in reference rates derived from the Penman-Monteith equation were highly sensitive to how aerodynamic conductance was set. To the extent that E PanFit accurately reflects the sensitivity of PE to D a over land surfaces, future trends in PE based on the Priestley-Taylor model may underestimate increasing evaporative demand, while reference rates for forests, that assume strong canopy-atmosphere coupling in the Penman-Monteith model, may overestimate increasing evaporative demand. The resulting historical database, covering the spectrum of different models of PE applied in modern studies, can serve to further investigate biosphere-hydroclimate relationships across North America.

Mapped Hydroclimatology of Evapotranspiration and Drainage Runoff Using SMAP Brightness Temperature Observations and Precipitation Information

“…Similarly, parts of the Michigan Upper Peninsula and Northeast United States also show low values, which is due to increased number of waterbodies within SMAP pixels—These regions are excluded in further analysis. Nonetheless, the spatial pattern and distribution of 3‐year averaged from high in the southwest to lower in the Midwest as well as its dynamics range (~3–12 mm/day) is consistent with recent multidecade warm‐season Penman, Priestley‐Taylor, and pan‐evaporation analysis by (Hember et al, ). Other regional patterns for are also observed, such as lower values near the Mississippi embayment (<3 mm/day) as well as larger values (>10 mm/day) in the southeast.…”

The Uncertainty of Penman‐Monteith Method and the Energy Balance Closure Problem

“…However, results from the Mekong Basin demonstrated that sunshine duration hours were the dominant factor contributing to ET 0 (B Li et al, 2015), while wind speed and RH were the most and least sensitive climatic factors for ET 0 in Malaysia, respectively (Askari et al, 2015). Similar to these results, a study of North American forests also showed that aerodynamic conditions were highly sensitive to ET 0 and that the PM model may overestimate the increase in evaporative demand (Hember et al, 2017). In China, a study based on the national average found that the most sensitive factor for ET 0 was the actual vapor pressure, followed by the daily maximum temperature and global radiation .…”

Tree Ring Reconstructions of Stemwood Biomass Indicate Increases in the Growth Rate of Black Spruce Trees Across Boreal Forests of Canada

“…Warm‐season soil water content was calculated from a monthly surface water balance model (Hember et al, ; Hember, Kurz, & Coops, ). The model followed previous implementations of Thornthwaite's initial approach (Willmott et al, ), only replacing the temperature‐based model of actual evapotranspiration with the Penman‐Monteith equation for forest canopies with moderate atmosphere‐canopy coupling (Hember, Coops, & Spittlehouse, ). Values for each tree were derived from the nearest cell within a 1‐km grid.…”