Summary

 

Contributing author

Darrel Jenerette

Summary

Temperature is an intensive state variable of a material related to energy content through mass specific functions. Gradients in temperature generate flows of energy. Temperature changes are caused by altered net storage of energy resulting from absorbed and emitted sensible heat fluxes (energy exchange that involves a temperature change), latent heat fluxes (energy exchange that involves evaporation or transpiration of water without a temperature change), and conduction of heat to the atmosphere. Temperature and the energy budget of organisms or components of the land surface are measured primarily because of interest in micro- and macro-biological influences on organismal water relations, and the physiological, phenological, and life-cycle sensitivities of organisms to their environment.

Leaf scale

Temperature

Thermocouple
Leaf temperature can be measured directly via a thermocouple attached to the leaf. Generally the thermocouple is attached to the shaded side of a leaf and a gas permeable fixative such as medical tape is used to connect the thermocouple to the leaf (Tarnopolsky and Seginer 1999). Measurement with a thermocouple is also commonly used as part of a leaf photosynthesis system where a thermocouple within the leaf cuvette is in contact with the leaf and contributes to calculating stomatal conductance.

Infrared thermometer
A second approach uses an IR sensor to obtain a spot measurement of surface temperature. The approach is based on the detection of infrared energy radiating from objects in a sensors field of view (Blad and Rosenberg 1976).

Thermal imaging
An extension of the single value infrared thermometer is thermal imaging, which uses a microbolometer to measure temperatures across an array of sensors with common pixel resolutions ranging between 320X240 and 640×512 (Hartz et al. 2006, Leuzinger et al. 2010).

Transpiration

Transpiration of the leaf is directly measured using a leaf porometer or as part of a leaf photosynthesis system. Applications of micrometeorological and leaf temperature measurements also provide indirect approaches to measure transpiration (Leinonen et al. 2006).

Albedo, Absorbance, Transmittance

All of these terms are commonly measured using a spectrophotometer (for example CI-710 Miniature Leaf Spectrometer) or integrating sphere (e.g. Idle and Proctor 1983). These methods can be either broad spectrum or over specific wavelengths according to sensor and light source limitations.

Plant canopy to whole ecosystem scale

Energy Balance

Energy balance at the plant canopy or whole ecosystem scales is typically measured through a combination of radiometers, heat flux sensors, with eddy-covariance estimates of latent heat exchanges. Typical instrument configurations include a 4-component net radiometer measuring up- and down-welling long and short-wave radiation. A ground heat flux plate and soil temperature probes will measure heat flux into the ground. A coupled fast response (e.g. 10 hz) 3-dimensional anemometer and water vapor gas analyzer will be used to compute the eddy-covariance derived evaporative flux. Together this suite of instruments can generally achieve within 70% closure of the energy balance at 30 minute scales and higher closure at longer-time intervals (Twine et al. 2000). The approach is now applied across nearly all biomes and many sites have data records extending past 10 years (Baldocchi et al. 2001). Several reviews of the general approach have been compiled (Baldocchi et al. 1988, Goulden et al. 1996, Baldocchi 2003).

Bowen ratio

Whole ecosystem transpiration can also be estimated by calculating the Bowen ratio (Bowen 1926; Malek and Bingham, 1993), where the Bowen ratio is defined as the ratio of sensible and latent heat fluxes. This approach requires measurements of net radiation, storage heat flux including ground heat flux. Historically, measurements at two heights have been required of air temperature and water vapor pressure (Shi et al. 2008), although recent theoretical and measurement advances have also provided a single height approach (Anderson and Goulden 2009).

Sap-flux transpiration

Whole plant transpiration can be measured as sap-flux based on gradients of heat in sensors placed through plant xylem (Granier 1987, Bush et al. 2010).

Thermal mapping / remote sensing

Landscape and regional thermal imaging can be achieved through handheld cameras or remotely sensed imagery on board satellite or aircraft. Satellite data commonly used include Landsat (http://landsat.gsfc.nasa.gov/) and MODIS (http://modis.gsfc.nasa.gov/) sensors. A common airborne system available through NASA is MASTER (http://masterweb.jpl.nasa.gov/). These approaches are commonly combined with in-situ measurements to estimate whole ecosystem evaporation (Glenn et al. 2007).

Modeling energy budget

Energy balance and temperature are commonly modeled for whole ecosystem, canopy, and individual leaves. A broad range of approaches are derived from mechanistic based Penman-Monteith models or more empirical Priestley-Taylor models (Stannard 1993). Models linking Penman-Monteith-type models and canopy temperature approaches have recently been extended to work with modern thermal imaging instruments (Blonquist et al. 2009, Kustas and Anderson 2009).

Literature references

Anderson, R. G. and M. L. Goulden. 2009. A mobile platform to constrain regional estimates of evapotranspiration. Agricultural and Forest Meteorology 149:771-782.

Baldocchi, D., E. Falge, L. H. Gu, R. Olson, D. Hollinger, S. Running, P. Anthoni, C. Bernhofer, K. Davis, R. Evans, J. Fuentes, A. Goldstein, G. Katul, B. Law, X. H. Lee, Y. Malhi, T. Meyers, W. Munger, W. Oechel, K. T. P. U, K. Pilegaard, H. P. Schmid, R. Valentini, S. Verma, T. Vesala, K. Wilson, and S. Wofsy. 2001. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bulletin of the American Meteorological Society 82:2415-2434.

Baldocchi, D. D. 2003. Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future. Global Change Biology 9:479-492.

Baldocchi, D. D., B. B. Hicks, and T. P. Meyers. 1988. Measuring Biosphere-Atmosphere Exchanges of Biologically Related Gases with Micrometeorological Methods. Ecology 69:1331-1340.

Blad, B. L. and N. J. Rosenberg. 1976. Measurement of crop temperature by leaf thermocouple, infrared thermometry and remotely sensed thermal imagery. Agronomy Journal 68:635-641.

Blonquist, J. M., J. M. Norman, and B. Bugbee. 2009. Automated measurement of canopy stomatal conductance based on infrared temperature. Agricultural and Forest Meteorology 149:1931-1945.

Bush, S. E., K. R. Hultine, J. S. Sperry, and J. R. Ehleringer. 2010. Calibration of thermal dissipation sap flow probes for ring- and diffuse-porous trees. Tree Physiology 30:1545-1554.

Glenn, E. P., A. R. Huete, P. L. Nagler, K. K. Hirschboeck, and P. Brown. 2007. Integrating remote sensing and ground methods to estimate evapotranspiration. Critical Reviews in Plant Sciences 26:139-168.

Goulden, M. L., J. W. Munger, S. M. Fan, B. C. Daube, and S. C. Wofsy. 1996. Measurements of carbon sequestration by long-term eddy covariance: Methods and a critical evaluation of accuracy. Global Change Biology 2:169-182.

Granier, A. 1987. Evaluation of transpiration in a Douglas-Fir stand by means of sap flow measurements. Tree Physiology 3:309-319.

Hartz, D. A., L. Prashad, B. C. Hedquist, J. Golden, and A. J. Brazel. 2006. Linking satellite images and hand-held infrared thermography to observed neighborhood climate conditions. Remote Sensing of Environment 104:190-200.

Kustas, W. and M. Anderson. 2009. Advances in thermal infrared remote sensing for land surface modeling. Agricultural and Forest Meteorology 149:2071-2081.

Leinonen, I., O. M. Grant, C. P. P. Tagliavia, M. M. Chaves, and H. G. Jones. 2006. Estimating stomatal conductance with thermal imagery. Plant Cell and Environment 29:1508-1518.

Leuzinger, S., R. Vogt, and C. Korner. 2010. Tree surface temperature in an urban environment. Agricultural and Forest Meteorology 150:56-62.

Shi, T. T., D. X. Guan, J. B. Wu, A. Z. Wang, C. J. Jin, and S. J. Han. 2008. Comparison of methods for estimating evapotranspiration rate of dry forest canopy: Eddy covariance, Bowen ratio energy balance, and Penman-Monteith equation. Journal of Geophysical Research-Atmospheres 113.

Stannard, D. I. 1993. Comparison of Penman-Monteith, Shuttleworth-Wallace, and Modified Priestley-Taylor Evapotranspiration Models for Wildland Vegetation in Semiarid Rangeland. Water Resources Research 29:1379-1392.

Tarnopolsky, M. and I. Seginer. 1999. Leaf temperature error from heat conduction along thermocouple wires. Agricultural and Forest Meteorology 93:185-194.