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Empirical Analysis of the Influence of Forest Extent on Annual and Seasonal Surface Temperatures for the Continental United States
Citation:
WICKHAM, J. D., T. G. WADE, AND K. H. Riitters. Empirical Analysis of the Influence of Forest Extent on Annual and Seasonal Surface Temperatures for the Continental United States. Global Ecology and Biogeography. Wiley InterScience, Silver Spring, MD, 22:620-629, (2013).
Impact/Purpose:
Albedo and transpiration are two competing biophysical factors that influence the degree to which forests warm or cool surface air temperatures. Forest albedo tends to be low (Hollinger 2010), making forests comparatively dark objects that absorb incoming solar radiation and then re‐radiate it to the atmosphere, warming surface air temperatures. Transpiration is a counteracting radiative force that cools and moistens the atmosphere. The relative influences of albedo and transpiration change along a gradient from the equator to the poles (Bonan 2008a). In tropical forests, evaporative cooling from transpiration is greater than sensible warming. The relative influences of albedo and transpiration are reversed in boreal regions, where sensible warming from a low albedo is greater than the cooling effect of transpiration. The gradient of net cooling in tropical forests to net warming in boreal forests is ultimately driven by sun angle and seasonality. Transpiration is essentially a year‐round process in the tropics, but is only seasonally active at higher latitudes. Conversion of the sun's energy to sensible heat is not counteracted by the cooling effects of transpiration when forests are seasonally dormant. The relative roles of albedo and transpiration in temperate forests are less clear (Bonan 2008a, Jackson et al. 2008). Most modeling studies show that removal of temperate forest cools surface air temperatures, although there are a few studies that show that removal of temperate forest warms surface air temperatures (Table 1). These findings are based on comparisons of climate model outputs for different land cover scenarios, with the main difference being that forest in one scenario (e.g., historical) is replaced by agriculture in the other scenario (e.g., current ). Model outputs that show cooler surface air temperatures when forest is replaced with agriculture are attributed to higher surface albedo and less frictional resistance to transpiration and momentum transfer in croplands (Bonan 1997). The model results showing that the removal of temperate forest cools surface air temperature conflicts with many field‐based studies. Matlack (1993) and Chen et al. (1993) found that temperate US forest ‐ surface temperature relationships US forrest-surface temperature relationships.
Description:
Most scenario‐based climate modeling studies indicate that replacing temperate forest with cropland will promote cooling by reducing surface air temperatures. These results are inconsistent with fieldbased microclimate studies that have found that forests are cooler, wetter, and less windy than surrounding fields. In this study, we use temperature and land‐cover data to examine empirical relationships between the proportion of forest and surface air temperature for the continental United States. Land cover is derived from the National Land Cover Database (NLCD 2001), and surface temperature is derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) data. Our results are inconsistent with the scenario‐based climate modeling studies. Surface air temperatures declined as the proportion of forest increased. The inverse relationship between forest and surface air temperature was found for the spring, summer, and fall seasons, and annually. We also found an inverse relationship between forest and surface air temperature for winter up to latitudes between 35°N to 40°N. The forest‐surface temperature relationship was also scale dependent in that spatially extensive forests produced cooler temperatures than forests that were dominant only locally. We attribute the inconsistency between our results and the scenario‐based climate modeling studies to the uncertainty in estimates of albedo and the coarse resolution land‐cover data used in the scenario‐based climate modeling studies.