A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests

Most global temperature analyses are based on station air temperatures. This study presents a global analysis of the relationship between remotely sensed annual maximum LST (LSTmax) from the Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and the corresponding site-based maximum air temperature (Tamax) for every World Meteorological Organization station on Earth. The relationship is analyzed for different land cover types. We observed a strong positive correlation between LSTmax and Tamax. As temperature increases, LSTmax increases faster than Tamax and captures additional information on the concentration of thermal energy at the Earth\u27s surface, and biophysical controls on surface temperature, such as surface roughness and transpirational cooling. For hot conditions and in nonforested cover types, LST is more closely coupled to the radiative and thermodynamic characteristics of the Earth than the air temperature (Tair). Barren areas, shrublands, grasslands, savannas, and croplands have LSTmax values between 10°C and 20°C hotter than the corresponding Tamax at higher temperatures. Forest cover types are the exception with a near 1:1 relationship between LSTmax and Tamax across the temperature range and 38°C as the approximate upper limit of LSTmax with the exception of subtropical deciduous forest types where LSTmax occurs after canopy senescence. The study shows a complex interaction between land cover and surface energy balances. This global, semiautomated annual analysis could provide a new, unique, monitoring metric for integrating land cover change and energy balance changes

Satellite Finds Highest Land Skin Temperatures on Earth

The location of the hottest spot on Earth has undoubtedly been an interesting curiosity for centuries. Even with the advent of the instrumental temperature record around the year 1850, the location of the hottest spot on Earth has continued to be the subject of debate and controversy. In 1913, the weather station at Furnace Creek in Death Valley National Park, California, measured an air temperature of 56.7°C (134.1°F) and claimed the title of “hottest place on Earth.” Nine years later in El Azizia, Libya, an air temperature of 57.8°C (136°F) was recorded on land owned by an Italian farmer and the title of the “hottest place on Earth” moved from the United States to Libya. The 1922 air temperature measurement from El Azizia has never been surpassed. In reality, finding the hottest spot on Earth based on scattered site-based air temperature measurements is a limited approach due to the poor spatial coverage of the instruments where measurements are taken compared with Earth’s expansive barren deserts where the hottest conditions occur. The World Meteorological Organization (WMO) has approximately 11,119 weather stations on Earth’s land surface collecting surface temperature observations (ftp://ftp.ncdc.noaa.gov/pub/data/gsod/2010). When compared to the 144.68 million km2 of land surface, that’s one station every 13,012 km2. The Earth’s hot deserts, such as the Sahara, the Gobi, the Sonoran, and the Lut, are climatically harsh and so remote that access for routine measurements and maintenance of a weather station is impractical. The majority of Earth’s potentially hottest spots are simply not being directly measured by ground-based instruments. Satellites provide a continuous view of Earth’s surface, allowing equal observation of the most remote areas and the most accessible. However, satellites do not measure the near-surface air temperature; instead they measure the radiometric surface temperature, or skin temperature, a different physical parameter

A forest vulnerability index based on drought and high temperatures

Increasing forest stress and tree mortality has been directly linked to combinations of drought and high temperatures. The climatic changes expected during the next decades – large increases in mean temperature, increased heat waves, and significant long-term regional drying in the western USA – will likely increase chronic forest stress and mortality. The aim of this research is to develop and apply a new forest vulnerability index (FVI) associated with drought and high temperatures across the Pacific Northwest region (PNW; Oregon and Washington) of the USA during the MODIS Aqua era (since 2003). Our technique incorporates the alterations to canopy water and energy exchange processes caused by drought and high temperatures with spatially continuous MODIS land surface temperature (LST) and evapotranspiration (ET), and with Parameter-elevation Relationships on Independent Slopes Model (PRISM) precipitation (P) data.With P and ET, we calculate a monthly water balance variable for each individual pixel normalized by forest type group (FTG), and then difference the water balance with the corresponding normalized monthly mean LST to calculate a monthly forest stress index (FSI). We then extract the pixel-specific (800-mresolution) statistically significant temporal trends of the FSI from 2003 to 2012 by month (April to October). The FVI is the slope of the monthly FSI across years, such that there is a FVI for each month. Statistically significant positive slopes indicate interannual increases in stress leading to expected forest vulnerability (positive FVI) for a given month. Positive FVI values were concentrated in the months of August and September, with peak vulnerability occurring at different times for different FTGs. Overall, increased vulnerability rates were the highest in drier FTGs such as Ponderosa Pine, Juniper, and Lodgepole Pine. Western Larch and Fir/Spruce/Mountain Hemlock groups occupy moister sites but also had relatively high proportion of positive FVI values. The Douglas-fir group had the second largest total area of increased vulnerability due to its large areal extent in the study area. Based on an analysis using imagery viewed in Google Earth, we confirm that areas with increased vulnerability are associated with greater amounts of stress and mortality. The FVI is a new way to conceptualize and monitor forest vulnerability based on first-order principles and has the potential to be generalized to other geographical areas

Satellite Monitoring of Earth’s Surface Temperature : Effects of Land Cover, Disturbance, and a Changing Climate

The Earth’s surface is experiencing unprecedented change. Humanity’s growing population, expanding land-use footprint, and increasing global emissions of atmospheric greenhouse gases affect a vast number of species on Earth and the functioning of virtually all ecosystems. Given the vital interactions and feedbacks between the Earth’s land surface and climate, measurements that link surface conditions and climate can provide crucial information on biospheric change. Land surface temperature (LST) is one of the most important parameters in the physical processes of surface energy and water balances at local through global scales. Interactions between the land surface and the atmosphere and the resulting exchanges of energy and water have a substantial impact on climate. This dissertation presents new methodologies developed using satellite-derived LST in conjunction with other biophysical datasets to monitor, quantify, map and understand critical Earth system changes from global to ecoregional scales.It has long been known that temperature is one of the key environmental controls and stressors to which an organism may be subjected. Its influence is fundamental, ranging from controls on chemical reactions that drive key processes on Earth, such as photosynthesis and respiration, to its role in defining large-scale species distributions and biome patterns. Climatological data can be developed for two kinds of surface temperatures: near-surface air temperature and the skin temperature, or LST. Although correlated with air temperature, LST differs from air temperature in its physical meaning, magnitude, and measurement techniques. LST can be estimated from measurements of thermal radiance coming from the land surface, retrieved from satellite, and mapped globally. In vegetated areas, satellite-derived LST measures the canopy surface temperature, and is more closely connected to the biophysical characteristics of the land surface, such as the land cover type, vegetation density, and water and energy fluxes of a specific area. LST provides important insights into high temperature extremes associated with droughts and heat waves, and the thermal tolerances and exposures for species and ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST product is measured across every 1-km2 pixel of the Earth’s surface. This is an important distinction from air temperature measurements from weather stations that have an inequitable global distribution including few stations across remote areas of the Earth’s surface, and cannot give detailed spatial patterns.We describe a new global change indicator based on an annual global measure of the Earth’s maximum land surface temperature (LSTmax) and demonstrate its value to examine critical Earth system functions (Chapter 2). LSTmax provides a unique integrated measure of the ecosystems thermal condition that is especially powerful at minimizing synoptic and seasonal variability and highlighting changes associated with extreme climatic events and significant land cover changes. We questioned whether maximum thermal anomalies could be indicative of heat waves and droughts, a melting cryosphere, and tropical forest disturbance from 2003 to 2014. The 1-km2 LSTmax anomalies detected complex spatial patterns associated with heat waves and droughts across the Earth’s surface, peaking in 2010 and 2012 with 5% (16%) of the Earth’s surface experiencing anomalies greater than 4°C (2°C). Our findings show that entire biomes are experiencing shifts in their maximum surface temperature distributions in association with extreme climatic events and large-scale land surface changes. These directional shifts in components of the Earth’s integrated LSTmax histograms are associated with melting of ice sheets, severe droughts in tropical rainforests, and with the incremental effects of forest loss in tropical forests. We conclude that with continued warming, the Earth’s integrated maximum temperatures will 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.In a regional assessment responding to the acute concern about increasing forest stress and tree mortality and its direct link to combinations of drought and high temperatures (Chapter 3), we developed and applied a new forest vulnerability index (FVI) that identifies when and where forests have been experiencing increasingly high surface temperatures and greater growing season water deficits across the Pacific Northwest region (PNW: Oregon and Washington) of the USA during the MODIS Aqua era (since 2003). Our technique incorporates the alterations to canopy water and energy exchange processes caused by drought and high temperatures with MODIS LST and evapotranspiration (ET) data, and with Parameter-elevation Relationships on Independent Slopes Model (PRISM) precipitation (P) data. The FVI’s monthly assessment over the growing season revealed a possible trajectory toward more extreme conditions indicated by a trend toward cooler and wetter conditions in the spring, followed by a rapid transition to widespread warmer and drier trends in August and September. Area of increased vulnerability was concentrated in the months of August and September, with peak vulnerability occurring at separate times for different forest types. Overall, increased vulnerability rates were highest in drier forest type groups, such as Ponderosa Pine, Juniper, and Lodgepole Pine. Western Larch and Fir Spruce Mountain Hemlock groups occupy moister sites but also had relatively high proportion of increased vulnerability. The Douglas-fir group had the second largest total area of increased vulnerability due to its large areal extent in the study area. Based on an analysis using imagery viewed in Google Earth, we found that areas with increased vulnerability are associated with greater amounts of visible health decline and mortality. The FVI is a new way to conceptualize and monitor forest vulnerability based on first-order principles and has the potential to be generalized to other geographical areas.In Chapter 4 we utilize the FVI and its intermediary datasets on canopy energy and water exchange trends to investigate the Swiss needle cast (SNC) epidemic in the Oregon Coast Range. SNC is caused by an ascomycete fungus endemic to the PNW, and is having important consequences on the region’s coastal Douglas-fir forests. Seasonal changes in temperature and or precipitation regimes, such as we detected in Chapter 3 of this dissertation, have the potential to shift conditions in favor of pathogens, resulting in widespread epidemics. Foliar fungi diseases such as SNC are thought to be especially responsive to climate changes. Previous research has verified that spring and early summer leaf wetness is a key factor in SNC disease epidemiology. In this study, we investigate the relationship between climatic trends detected during the spring and early summer months (May – August) along the Pacific Coast of Oregon from 2003 to 2012, and the distribution of forests with visible symptoms of SNC in 2012. Our objectives were to: 1) Calculate the relationship between LST and water balance (WB) trends and pixel-level presence absence of SNC symptoms. 2) Compare the relationship between private and public forest lands to make inferences about the effects of forestry practices on forest vulnerability to SNC intensification. We find evidence that recent short-term directional climate changes may have contributed to the recent increases in SNC symptoms in Douglas-fir forests, and that this influence was stronger on private lands. The LST trends had greater explanatory power than WB trends, and the interactions between monthly LST trends increased the explanatory power of LST, whereas this effect was minimal for WB. The trends of the May and August LST together explained 7% of the deviance in SNC symptom distribution on private land, and 2% on public land. When combined with proximity to coast (strongest explanatory variable), May and August LST explained 14% of the deviance in SNC symptom expression on private land, and 8.7% on public land. Adding the WB factor did not improve the deviance explained in presence of SNC symptoms. This study indicates that early spring and mid-summer LST contains valuable information on leaf wetness, possibly contrasting both early season wetness and late season dryness, both of which are important to the epidemiology of SNC.The results from this dissertation highlight the immense value of the LST measurement in tracking critical changes in the Earth system. While questions remain regarding upper temperature thresholds that may trigger biome shifts or widespread forest die-offs, our results help to fill the knowledge gap about how these temperature changes are impacting the Earth’s ecosystems. The methodologies and tools developed here offer new and important opportunities for long-term monitoring that will continue to increase our understanding of these key land surface-climate interactions.Keywords: stress, forest vulnerability index, heat waves, annual maximum LST, Aqua MODIS Land surface temperature, climate change, evapotranspiration, Swiss needle cast, cryosphere melt, global change indicator, tropical forest drought, water defici

A New Satellite-Based Methodology for Continental-Scale Disturbance Detection

The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land–surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance

Thermal Anomalies Detect Critical Global Land Surface Changes

Measurements that link surface conditions and climate can provide critical information on important biospheric changes occurring in the Earth system. As the direct driving force of energy and water fluxes at the surface–atmosphere interface, land surface temperature (LST) provides information on physical processes of land-cover change and energy-balance changes that air temperature cannot provide. Annual maximum LST (LSTmax) is especially powerful at minimizing synoptic and seasonal variability and highlighting changes associated with extreme climatic events and significant land-cover changes. The authors investigate whether maximum thermal anomalies from satellite observations could detect heat waves and droughts, a melting cryosphere, and disturbances in the tropical forest from 2003 to 2014. The 1-km2 LSTmax anomalies peaked in 2010 when 20% of the global land area experienced anomalies of greater than 1 standard deviation and over 4% of the global land area was subject to positive anomalies exceeding 2 standard deviations. Positive LSTmax anomalies display complex spatial patterns associated with heat waves and droughts across the global land area. The findings presented herein show that entire biomes are experiencing shifts in their LSTmax distributions driven by extreme climatic events and large-scale land surface changes, such as melting of ice sheets, severe droughts, and the incremental effects of forest loss in tropical forests. As climate warming and land-cover changes continue, it is likely that Earth’s maximum surface temperatures will experience greater and more frequent directional shifts, increasing the possibility that critical thresholds in Earth’s ecosystems and climate system will be surpassed, resulting in profound and irreversible changes

Strategic reserves in Oregon’s forests for biodiversity, water, and carbon to mitigate and adapt to climate change

Creating strategic forest reserves is essential for stemming the loss of biodiversity and contributing to climate mitigation and adaptation. Meeting preservation targets of 30% protection by 2030, and 50% by 2050 would lead to greater protection of animal taxa and tree species habitat, carbon stocks and accumulation, and forests that are important sources of drinking water. Here, we develop a regional framework to specifically identify at a fine resolution (30 m) high priority forestlands for preservation in Oregon, USA. We include a resilience metric that represents connectivity and topographic diversity, and identify areas within each ecoregion that are ranked high priority for carbon, biodiversity, resilience and drinking water. Oregon has less than 10% of its forestlands protected at the highest levels, yet its temperate forests are among those with the highest carbon densities in the world. Reserves for surface drinking water sources and forest habitat for birds, mammals, amphibians, and reptiles could increase to 50–70% protection at the highest levels by 2050. Protected aboveground biomass carbon could triple to 635 teragrams of carbon by 2050. The ownership of the high preservation priority lands for carbon and biodiversity is primarily federal (67% by 2050) followed by private (28% by 2050), with much less in the other ownerships. Forest reserves could be established on federal lands through executive action, regulation and rule-making, while private landowners could be incentivized to store more carbon, limit harvest in certain areas and transfer ownership to land trusts. Protecting mature and old forests on federal lands fulfills an urgent need for protection and provides a low-cost way to simultaneously meet national and international goals. This study provides a flexible, dynamic framework for identifying areas that are high priority to protect for climate mitigation and adaptation at regional and sub-regional scales

Observations and assessment of forest carbon dynamics following disturbance in North America

Disturbance processes of various types substantially modify ecosystem carbon dynamics both temporally and spatially, and constitute a fundamental part of larger landscape-level dynamics. Forests typically lose carbon for several years to several decades following severe disturbance, but our understanding of the duration and dynamics of post-disturbance forest carbon fluxes remains limited. Here we capitalize on a recent North American Carbon Program disturbance synthesis to discuss techniques and future work needed to better understand carbon dynamics after forest disturbance. Specifically, this paper addresses three topics: (1) the history, spatial distribution, and characteristics of different types of disturbance (in particular fire, insects, and harvest) in North America; (2) the integrated measurements and experimental designs required to quantify forest carbon dynamics in the years and decades after disturbance, as presented in a series of case studies; and (3) a synthesis of the greatest uncertainties spanning these studies, as well as the utility of multiple types of observations (independent but mutually constraining data) in understanding their dynamics. The case studies—in the southeast U.S., central boreal Canada, U.S. Rocky Mountains, and Pacific Northwest—explore how different measurements can be used to constrain and understand carbon dynamics in regrowing forests, with the most important measurements summarized for each disturbance type. We identify disturbance severity and history as key but highly uncertain factors driving post-disturbance carbon source-sink dynamics across all disturbance types. We suggest that imaginative, integrative analyses using multiple lines of evidence, increased measurement capabilities, shared models and online data sets, and innovative numerical algorithms hold promise for improved understanding and prediction of carbon dynamics in disturbance-prone forests