• Adegoke, J. O., R. Pielke, and A. M. Carleton, 2007: Observational and modeling studies of the impacts of agriculture-related land use change on planetary boundary layer processes in the central US. Agric. For. Meteor., 142, 203215, doi:10.1016/j.agrformet.2006.07.013.

    • Search Google Scholar
    • Export Citation
  • Alex, Z. C., and J. Behari, 1998: Laboratory evaluation of emissivity of soils. Int. J. Remote Sens., 19, 13351340, doi:10.1080/014311698215478.

    • Search Google Scholar
    • Export Citation
  • Brown, J. F., and M. S. Pervez, 2014: Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture. Agric. Syst., 127, 2840, doi:10.1016/j.agsy.2014.01.004.

    • Search Google Scholar
    • Export Citation
  • Cierniewski, J., A. Karnieli, C. Kaźmierowski, and J. Ceglarek, 2014: A tool for predicting diurnal soil albedo variation in Poland and Israel. EARSeL eProc., 13, 3640, doi:10.12760/02-2014-1-07.

    • Search Google Scholar
    • Export Citation
  • Davey, C. A., R. A. Pielke Sr., and K. P. Gallo, 2006: Differences between near-surface equivalent temperature and temperature trends for the eastern United States: Equivalent temperature as an alternative measure of heat content. Global Planet. Change, 54, 1932, doi:10.1016/j.gloplacha.2005.11.002.

    • Search Google Scholar
    • Export Citation
  • Diamond, H. J., and Coauthors, 2013: U.S. Climate Reference Network after one decade of operations status and assessment. Bull. Amer. Meteor. Soc., 94, 485498, doi:10.1175/BAMS-D-12-00170.1.

    • Search Google Scholar
    • Export Citation
  • Dobos, E., 2006: Albedo. Encyclopedia of Soil Science, R. Lal, Ed., CRC Press, 64–66.

  • Döll, P., and S. Siebert, 2002: Global modeling of irrigation water requirements. Water Resour. Res., 38, doi:10.1029/2001WR000355.

  • Evett, S. R., 2000: Energy and water balances at soil–plant–atmosphere interfaces. Handbook of Soil Science, M. E. Sumner, Ed., CRC Press, A129–A182.

  • Fall, S., D. Niyogi, A. Gluhovsky, R. A. Pielke, E. Kalnay, and G. Rochon, 2010: Impacts of land use land cover on temperature trends over the continental United States: Assessment using the North American Regional Reanalysis. Int. J. Climatol., 30, 19801993, doi:10.1002/joc.1996.

    • Search Google Scholar
    • Export Citation
  • Gaffen, D. J., and R. J. Ross, 1999: Climatology and trends of U.S. surface humidity and temperature. J. Climate, 12, 811828, doi:10.1175/1520-0442(1999)012<0811:CATOUS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Geiger, R., R. H. Aron, and P. Todhunter, 2009: The Climate near the Ground. Rowman and Littlefield, 584 pp.

  • Gollehon, N., and W. Quinby, 2006: Irrigation resources and water costs. Agricultural Resources and Environmental Indicators, Economic Research Service/USDA, 24–32.

  • Hargreaves, G. H., and R. G. Allen, 2003: History and evaluation of Hargreaves evapotranspiration equation. J. Irrig. Drain. Eng., 129, 5363, doi:10.1061/(ASCE)0733-9437(2003)129:1(53).

    • Search Google Scholar
    • Export Citation
  • Hulley, G., S. Hook, and C. Hughes, 2012: MODIS MOD21 land surface temperature and emissivity Algorithm Theoretical Basis Document. Jet Propulsion Laboratory, California Institute of Technology, JPL Publ. 12–17, 102 pp. [Available online at http://emissivity.jpl.nasa.gov/downloads/examples/documents/MOD21_LSTE_ATBD_Hulley_v2.0_20121116_pmbv1.pdf.]

  • Jacob, F., F. Petitcolin, T. Schmugge, E. Vermote, A. French, and K. Ogawa, 2004: Comparison of land surface emissivity and radiometric temperature derived from MODIS and ASTER sensors. Remote Sens. Environ., 90, 137152, doi:10.1016/j.rse.2003.11.015.

    • Search Google Scholar
    • Export Citation
  • Kimes, D. S., P. J. Sellers, and W. W. Newcomb, 1987: Hemispherical reflectance variations of vegetation canopies and implications for global and regional energy budget studies. J. Climate Appl. Meteor., 26, 959972, doi:10.1175/1520-0450(1987)026<0959:HRVOVC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lehmann, J., and D. Coumou, 2015: The influence of mid-latitude storm tracks on hot, cold, dry and wet extremes. Sci. Rep., 5, 17491, doi:10.1038/srep17491.

    • Search Google Scholar
    • Export Citation
  • Mira, M., M. Weiss, F. Baret, D. Courault, O. Hagolle, B. Gallego-Elvira, and A. Olioso, 2015: The MODIS (collection V006) BRDF/albedo product MCD43D: Temporal course evaluated over agricultural landscape. Remote Sens. Environ., 170, 216228, doi:10.1016/j.rse.2015.09.021.

    • Search Google Scholar
    • Export Citation
  • Moore, B., A. Coleman, M. Wigmosta, R. Skaggs, and E. Venteris, 2015: A high spatiotemporal assessment of consumptive water use and water scarcity in the conterminous United States. Water Resour. Manage., 29, 51855200, doi:10.1007/s11269-015-1112-x.

    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., Sr., and Coauthors, 2011: Land use/land cover changes and climate: Modeling analysis and observational evidence. Wiley Interdiscip. Rev.: Climate Change, 2, 828850, doi:10.1002/wcc.144.

    • Search Google Scholar
    • Export Citation
  • Pinty, B., M. Taberner, V. R. Haemmerle, S. R. Paradise, E. Vermote, M. M. Verstraete, N. Gobron, and J.-L. Widlowski, 2011: Global-scale comparison of MISR and MODIS land surface albedos. J. Climate, 24, 732749, doi:10.1175/2010JCLI3709.1.

    • Search Google Scholar
    • Export Citation
  • Rees, W. G., 2001: Physical Principles of Remote Sensing. 2nd ed. Cambridge University Press, 343 pp.

  • Sacks, W. J., B. I. Cook, N. Buenning, S. Levis, and J. H. Helkowski, 2009: Effects of global irrigation on the near-surface climate. Climate Dyn., 33, 159175, doi:10.1007/s00382-008-0445-z.

    • Search Google Scholar
    • Export Citation
  • Schaaf, C. B., and Coauthors, 2002: First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sens. Environ., 83, 135148, doi:10.1016/S0034-4257(02)00091-3.

    • Search Google Scholar
    • Export Citation
  • Sellers, P., and Coauthors, 1995: Remote sensing of the land surface for studies of global change: Models—algorithms—experiments. Remote Sens. Environ., 51, 326, doi:10.1016/0034-4257(94)00061-Q.

    • Search Google Scholar
    • Export Citation
  • Shukla, S., A. Steinemann, S. F. Iacobellis, and D. R. Cayan, 2015: Annual drought in California: Association with monthly precipitation and climate phases. J. Appl. Meteor. Climatol., 54, 22732281, doi:10.1175/JAMC-D-15-0167.1.

    • Search Google Scholar
    • Export Citation
  • Simes, R. J., 1986: An improved Bonferroni procedure for multiple tests of significance. Biometrika, 73, 751754, doi:10.1093/biomet/73.3.751.

    • Search Google Scholar
    • Export Citation
  • Steduto, P., T. C. Hsiao, D. Raes, and E. Fereres, 2012: Crop yield response to water. Food and Agriculture Organization of the United Nations, 505 pp. [Available online at http://www.fao.org/docrep/016/i2800e/i2800e.pdf.]

  • Sun, B. M., C. B. Baker, T. R. Karl, and M. D. Gifford, 2005: A comparative study of ASOS and USCRN temperature measurements. J. Atmos. Oceanic Technol., 22, 679686, doi:10.1175/JTECH1752.1.

    • Search Google Scholar
    • Export Citation
  • Taberner, M., B. Pinty, Y. Govaerts, S. Liang, M. Verstraete, N. Gobron, and J. L. Widlowski, 2010: Comparison of MISR and MODIS land surface albedos: Methodology. J. Geophys. Res., 115, D05101, doi:10.1029/2009JD012665.

    • Search Google Scholar
    • Export Citation
  • Trepanier, J. C., M. J. Roberts, and B. D. Keim, 2015: Trends and spatial variability in dry spells across the south-central United States. J. Appl. Meteor. Climatol., 54, 22612272, doi:10.1175/JAMC-D-14-0319.1.

    • Search Google Scholar
    • Export Citation
  • Wan, Z., 2008: New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote Sens. Environ., 112, 5974, doi:10.1016/j.rse.2006.06.026.

    • Search Google Scholar
    • Export Citation
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Quantifying the Roles of Changing Albedo, Emissivity, and Energy Partitioning in the Impact of Irrigation on Atmospheric Heat Content

S. C. PryorDepartment of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York

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R. C. SullivanDepartment of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York

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T. WrightAntorcha, LLC, Logan, Utah

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Abstract

Introduction of irrigated agriculture changes the partitioning of the surface energy flux between sensible and latent heat (H vs LE) and alters the albedo α and emissivity ε. In the absence of changes in the radiation components of the surface energy balance, the change in the Bowen ratio due to irrigation typically suppresses the local air temperature T but increases the total near-surface atmospheric heat content (as measured using equivalent potential temperature θe). While the effect of irrigation on surface energy partitioning due to enhanced surface and subsurface water availability has long been acknowledged, the roles of associated changes in ε and α have received less attention, and the scales and magnitudes of these effects remain uncertain. A new methodology designed for application to in situ and remote sensing data is presented and used to demonstrate that the net impact of irrigation on T and θe is strongly dependent on the regional climate, land cover in surrounding areas, and the amount of irrigation in the upwind fetch. The results suggest that the impact of the radiative forcing terms on net available energy is not negligible and may amplify or offset the impact from changed energy partitioning on T and θe depending on the specific regional climate and land cover.

Corresponding author address: S. C. Pryor, Department of Earth and Atmospheric Sciences, Bradfield Hall, Cornell University, Ithaca, NY 14853. E-mail: sp2279@cornell.edu.

Abstract

Introduction of irrigated agriculture changes the partitioning of the surface energy flux between sensible and latent heat (H vs LE) and alters the albedo α and emissivity ε. In the absence of changes in the radiation components of the surface energy balance, the change in the Bowen ratio due to irrigation typically suppresses the local air temperature T but increases the total near-surface atmospheric heat content (as measured using equivalent potential temperature θe). While the effect of irrigation on surface energy partitioning due to enhanced surface and subsurface water availability has long been acknowledged, the roles of associated changes in ε and α have received less attention, and the scales and magnitudes of these effects remain uncertain. A new methodology designed for application to in situ and remote sensing data is presented and used to demonstrate that the net impact of irrigation on T and θe is strongly dependent on the regional climate, land cover in surrounding areas, and the amount of irrigation in the upwind fetch. The results suggest that the impact of the radiative forcing terms on net available energy is not negligible and may amplify or offset the impact from changed energy partitioning on T and θe depending on the specific regional climate and land cover.

Corresponding author address: S. C. Pryor, Department of Earth and Atmospheric Sciences, Bradfield Hall, Cornell University, Ithaca, NY 14853. E-mail: sp2279@cornell.edu.
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