1. How Do Forests, Agriculture and Residential Neighborhoods Interact with Climate? Andrew Ouimette, Lucie Lepine, Mary Martin, Scott Ollinger Earth Systems Research Center, University of New Hampshire, Durham, NH 03824, USA andrew.ouimette@unh.edu, lucie.lepine@unh.edu, mary.martin@unh.edu, scott.ollinger@unh.edu Latent and sensible heat Eddy Flux Systems “Sweating” Greenhouse Gases Longwave Radiation Albedo “Breathing”“Reflectivity” Latent and sensible heatAlbedoGas exchange Remote Sensing Examples of remotely sensed estimates of land surface temperature (LST), latent heat flux (evapotranspiration) and albedo in southern NH. While these estimates represent single snapshots in time, they allow for spatially explicit estimates and comparisons. 0 60 oCoC Using eddy flux measurements and remote sensing to understand land-climate interactions under future change scenarios As part of the NH EPSCoR Ecosystems and Society project, we are interested in understanding land use/land cover interactions with climate so that we may better assess climate conditions in NH under future change scenarios. The land surface interacts with the atmosphere primarily through movement of greenhouse gases (e.g. CO 2 ) and energy (e.g. light, heat), and these gas and energy fluxes vary by land use/land cover type. In the simplest terms, these fluxes can be thought of as breathing (respiring CO 2 ), reflecting (albedo), and sweating (evapotranspiration). Using the eddy covariance method and biometeorological sensors, we will measure CO 2 fluxes, evapotranspiration, and albedo over four land cover types that broadly represent the NH landscape: forest, field/pasture, corn/agriculture, residential/paved. Understanding how these greenhouse gas and energy fluxes vary over different land cover types will help us better assess the impacts that changes in land use will have on the local and global climate. Abstract Land-Climate Interactions Gas exchange Examples How can we measure these interactions over a mixed landscape? Albedo is the ratio of incoming to reflected shortwave solar energy, with values ranging between 1 (100% reflectivity) and 0 (100% absorbance). Certain “greenhouse” gases in the atmosphere behave similar to the glass in a greenhouse, trapping (longwave) heat radiating from the Earth’s surface. Eddy flux systems use the eddy covariance method to measure covariance of H 2 O and CO 2 concentrations and vertical wind speed in eddies over the land surface, and allow for measurements of greenhouse gas fluxes and sensible heat and latent heat (e.g. evaporative water loss). A suite of meteorological, solar radiation, soil and canopy sensors will help interpret these flux data, and fill in data gaps: Net radiometer for incoming and outgoing shortwave and longwave radiation PAR sensor for incoming photosynthetically-active radiation Soil temperature and humidity probes Air temperature and humidity sensor Rain gauge tipping bucket With complete eddy flux systems that include biometeorological sensors, we will measure CO 2 fluxes, evapotranspiration, and albedo over four land cover types that broadly represent the NH landscape. Remote sensing data will be used to calibrate and validate measurements from the eddy flux systems and assess variability in surface energy fluxes across different regions of the state. Relevance The eddy flux systems and data they capture will also provide opportunities for undergraduate and graduate research projects, as well as middle and high school science and technology projects and internships. ~ ~ ~ ~ ~ ~ Examples of CO 2 & water density and heat fluxes measured with eddy flux systems in a grassland over the course of a day in spring. Note the release of water and uptake of CO 2 during daylight hours. Thompson Farm, Durham, NH Kingman Farm, Madbury, NH Moore Fields, Durham, NH West Edge Parking Lot, Durham, NH Data derived from the eddy flux systems have direct relevance to the EPSCoR Ecosystems & Society project, as they will be used not only by terrestrial and hydrologic modeling groups, but also to assess climate and future land-use scenarios. By understanding how each component of the landscape contributes to the surface energy budget, we will be better able to estimate climate forcing under various land-use scenarios. This knowledge will help inform decisions about future land use. Estimates such as LST, latent heat flux, and albedo derived from remote sensing data over southern NH, the Lakes region, and the North Country will allow us to: Assess the variability of energy fluxes of each land use type across a latitudinal gradient Estimate surface energy fluxes across the whole state by calibrating remotely sensed estimates of latent heat flux and albedo with those measured by eddy covariance Provide data (e.g. foliar nitrogen, latent heat flux) necessary to more accurately model greenhouse gas fluxes across the state LST derived from Landsat 5 thermal band (August 2011) Latent heat flux derived from Landsat 5 estimated LST and NDVI band using equation from Wang et al. 2007 (August 2011) Surface albedo calculated from airborne imaging spectrometer data (AVIRIS) (July 2009) W m -2 100 0 0 30 Albedo Latent heat releases absorbed energy through evaporation and does not lead to an increase in local temperature. Sensible heat is energy released that results in warmer surface temperatures that we can feel or “sense” (e.g. urban heat islands).