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Climate and land-use changes are pushing ecosystems toward critical thresholds of profound change and new ways are needed to monitor and understand these impacts, especially with metrics that are relevant and communicable to society, land managers, and decision-makers. Land surface temperature (LST) is a fundamental aspect of climate and biology, affecting organisms and ecosystems from local to global scales. We applied a new global change indicator based on an annual measure of Earth's maximum land surface temperatures (LSTmax) and demonstrate its value to examine critical functions of the Earth system.

Our results show that large areas of Earth's land surface are experiencing anomalously extreme maximum temperatures in association with large-scale extreme climatic events and land-use change. These rising extreme maximum temperatures affect virtually every ecosystem on the planet, including ice sheets and tropical forests that play major roles in regulating the biosphere.

In an analysis of 1-[km.sup.2] LST data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Aqua satellite, we characterized a fundamental aspect of Earth's surface-climate system, the LSTmax distribution. The multimodality in distributions is reflective of ecosphere patterns and the low interannual variability reflects the robustness of LSTmax against the many intra- and interannual variations and fluctuations in LST. We hypothesized that shifts in LSTmax distributions might hence serve as a proxy for more deeply rooted shifts in Earth system properties that could indicate drifts of ecosystems and biomes toward thresholds of profound change.

High temperature extremes were detected from 2003 to 2014 across the global land area and coincided with heat waves, droughts, and related disruptions with important consequences to ecosystems and to human society. Entire biomes experienced shifts in their LSTmax distributions driven by extreme climatic events and large-scale land surface changes, such as ice melt, severe droughts, and with the incremental effects of forest loss in tropical forests. Maximum temperature spikes were associated with widespread melt of the Greenland ice sheet in 2012, and with the 2005 and 2010 droughts that had severe effects on the Amazon and Congo rain forests.

Our research shows the immense value of a single, unique measurement in tracking critical changes in the Earth system. With continued warming, Earth's LSTmax will likely experience greater and more frequent directional shifts, increasing the likelihood that critical thresholds will be surpassed resulting in regional-scale transitions that are tipping points in the global climate system. Our focus on changing thermal regimes has the potential to detect the shifts of ecosystems toward thresholds of profound change and our global, semiautomated annual analysis is easily repeatable for continuous monitoring of the entire land surface of Earth.--David J. Mildrexler (Oregon State University), M. Zhao, W. B. Cohen, S. W. Running, X. P. Song, and M. O. Jones, "Thermal anomalies detect critical global land surface changes," in the February Journal of Applied Meteorology and Climatology.

Caption: Spatially continuous global map of the I-[km.sup.2] LSTmax from 2003 to 2014. The highest LSTs (in red and orange) are found in Earth's deserts and arid shrublands. Grasslands and savannas (in light orange and light blue) transition into the cooler LSTs of forests (in blue). Dark blue areas are predominantly covered with year-round ice and include some high-elevation mountain ranges.

Caption: Earth's maximum temperature profile (MODIS LST). The global maximum thermal signature of Earth's land surface from 2003 to 2014 captures the unique influence of different land-cover types on the expression of LSTmax. Tracking shifts in the distribution of these annual histograms provides a new integrated measure of surface energy balance components and land-cover change, and a different means to monitor biospheric change. The area under the annual density curves sums to I.
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Author:Mildrexler, David J.
Publication:Bulletin of the American Meteorological Society
Geographic Code:1USA
Date:Apr 1, 2018
Next Article:Tropical Cyclone Structure Forecasts in a Hi-Res Version of the GFDL fvGFS Model.

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