• Anderson, J. R., , Hardy E. E. , , Roach J. T. , , and Witmer R. E. , 1976: A land use and land cover classification system for use with remote sensor data. U.S. Geological Survey Professional Paper 964, 28 pp.

    • Crossref
    • Export Citation
  • Belward, A. S., , Estes J. E. , , and Kline K. D. , 1999: The IGBP-DIS global 1-km land-cover data set DISCover: A project overview. Photogram. Eng. Remote Sens, 65 , 10131020.

    • Search Google Scholar
    • Export Citation
  • Chandler, L., , and Tippets D. W. , cited. 2000: NASA satellite data used operationally to help combat fires in the west. NASA News Archive. [Available online at http://earthobservatory.nasa.gov/Newsroom/NasaNews/2000/200009124019.html.].

  • Chen, F., , and Dudhia J. , 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129 , 569585.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cihlar, J., 1997: GCOS/GTOS plan for terrestrial climate related observations: Version 2. GCOS Rep. 32, World Meteorological Organization, 130 pp.

  • Colle, B. A., , Westrick K. J. , , and Mass C. F. , 1999: Evaluation of MM5 and Eta-10 precipitation forecasts over the Pacific Northwest during the cool season. Wea. Forecasting, 14 , 137154.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colle, B. A., , Mass C. F. , , and Westrick K. W. , 2000: MM5 precipitation verification over the Pacific Northwest during the 1997–1999 cool seasons. Wea. Forecasting, 15 , 730744.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crawford, T. M., , Stensrud D. J. , , Mora F. , , Merchant J. W. , , and Wetzel P. J. , 2001: Value of incorporating satellite-derived land cover data in MM5/PLACE for simulating surface temperatures. J. Hydrometeor., 2 , 453468.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crook, N. A., 1996: Sensitivity of moist convection forced by boundary layer processes to low-level thermodynamic fields. Mon. Wea. Rev., 124 , 17671785.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dickinson, R. E., , and Henderson-Sellers A. , 1988: Modeling tropical deforestation: A study of GCM land-parameterization. Quart. J. Roy. Meteor. Soc., 114 , 439462.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46 , 30773107.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1993: A nonhydrostatic version of the Penn State–NCAR mesoscale model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev., 121 , 14931513.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedl, M. A., and Coauthors, 2002: Global land cover from MODIS: Algorithms and early results. Remote Sens. Environ., 83 , 287302.

  • Grell, G. A., , Dudhia J. , , and Stauffer D. R. , 1995: A description of the fifth generation Penn State/NCAR mesoscale model (MM5). NCAR Tech. Note NCAR/TN-398+STR, 138 pp.

  • Hansen, M. C., , DeFries R. S. , , Townshend J. R. G. , , Sohlberg R. , , Dimiceli C. , , and Carroll M. , 2002: Towards an operational MODIS continuous field of percent tree cover algorithm: Examples using AVHRR and MODIS data. Remote Sens. Environ., 83 , 304320.

    • Search Google Scholar
    • Export Citation
  • Hong, S-Y., , and Pan H-L. , 1996: Non-local boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124 , 23222339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Justice, C. O., , Townshend J. R. G. , , Vermote E. F. , , Masuoka E. , , Wolfe R. E. , , Saleous N. , , Roy D. P. , , and Morisette J. T. , 2002: An overview of MODIS land data processing and product status. Remote Sens. Environ., 83 , 315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J. S., , and Fritsch J. M. , 1992: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165–170.

    • Crossref
    • Export Citation
  • Kurkowski, N. P., , and Stensrud D. J. , 2003: Assesment of implementing satellite-derived land cover data in the Eta Model. Wea. Forecasting, 18 , 404416.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loveland, T. R., , and Belward A. S. , 1997: The IGBP-DIS global 1-km land cover data set, DISCover: First results. Int. J. Remote Sens., 18 , 32913295.

    • Search Google Scholar
    • Export Citation
  • Miller, D. A., , and White R. A. , 1998: A conterminous United States multilayer soil characteristics data set for regional climate and hydrology modeling. Earth Interactions, 2 .[Available online at http://EarthInteractions.org.].

    • Search Google Scholar
    • Export Citation
  • Nobre, C. A., , Sellers P. J. , , and Shukla J. , 1991: Amazonian deforestation and regional climate change. J. Climate, 4 , 957988.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pan, Z., , Takle E. , , Segal M. , , and Arritt R. , 1999: Simulation of potential impacts of man-made land use changes on U.S. summer climate under various synoptic regimes. J. Geophys. Res., 104 , 65156528.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., 2001: Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev. Geophys., 39 , 151177.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., , Marland G. , , Betts R. A. , , Chase T. N. , , Eastman J. L. , , Niles J. O. , , Niyogi D. S. , , and Running S. W. , 2002: The influence of land-use change and landscape dynamics on the climate system: Relevance to climate-change policy beyond the radiative effect of greenhouse gases. Philos. Trans. Roy. Soc. London, A360 , 17051719.

    • Search Google Scholar
    • Export Citation
  • Pineda, N., , Jorba O. , , Jorge J. , , and Baldasano J. M. , 2004: Using NOAA AVHRR and SPOT VGT data to estimate surface parameters: Application to a mesoscale meteorological model. Int. J. Remote Sens., 25 , 129143.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scepan, J., 1999: Thematic validataion of high-resolution global land-cover data sets. Photogram. Eng. Remote Sens., 65 , 10511060.

  • Schaaf, C. B., and Coauthors, 2002: First operational BRDF, albedo and nadir reflectance products from MODIS. Remote Sens. Environ., 83 , 135148.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Segal, M., , Pan Z. , , Turner R. W. , , and Takle E. S. , 1998: On the potential impact of irrigated areas in North America on summer rainfall caused by large-scale systems. J. Appl. Meteor., 37 , 325331.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sen, O. L., , Wang Y. , , and Wang B. , 2004: Impact of Indochina deforestation on the East Asian summer monsoon. J. Climate, 17 , 13661380.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Strahler, A., , Muchoney D. , , Borak J. , , Friedl M. , , Gopal S. , , Lambin E. , , and Moody A. , cited. 1999: MODIS land cover product algorithm theoretical basis document (ATBD). Version 5. [Available online at http://modis.gsfc.nasa.gov/data/atbd/atbd_mod12.pdf.].

  • Tao, W-K., , and Simpson J. , 1993: The Goddard cumulus ensemble model. Part I: Model description. Terr. Atmos. Oceanic Sci., 4 , 3572.

  • Thompson, E. H., , Gutro R. , , and Bettwy M. , cited. 2004: Land cover changes affect U.S. summer climate. NASA News Archive. [Available online at http://earthobservatory.nasa.gov/Newsroom/NasaNews/2004/2004032416710.html.].

  • Townshend, J. R. G., , and Justice C. O. , 1998: Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations. Int. J. Remote Sens., 9 , 187236.

    • Search Google Scholar
    • Export Citation
  • Vermote, E. F., , El Saleous N. , , and Justice C. O. , 2002: Atmospheric correction of MODIS data in the visible to middle infrared: First results. Remote Sens. Environ., 83 , 97111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Z., , Zeng X. , , and Barlage M. , 2004: Using MODIS BRDF and albedo data to evaluate global model land surface albedo. J. Hydrometeor., 5 , 314.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wei, X., , Hahmann A. N. , , Dickinson R. E. , , Yang Z-L. , , Zeng X. , , Schaudt K. J. , , Schaaf C. B. , , and Strugnell N. , 2001: Comparison of albedos computed by land surface models and evolution against remotely sensed data. J. Geophys. Res., 106 , 2068720702.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wetzel, P. J., , and Chang J-T. , 1988: Evapotranspiration from non-uniform surfaces: A first approach for short-term numerical weather prediction. Mon. Wea. Rev., 116 , 600621.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., 1996: The impact of desertification in the Mongolian and the inner Mongolian grassland on the regional climate. J. Climate, 9 , 21732189.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yucel, I., , Shuttleworth W. J. , , Gao X. , , and Sorooshian S. , 2003: Short-term performance of MM5 with cloud-cover assimilation from satellite observations. Mon. Wea. Rev., 131 , 17971810.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, L., and Coauthors, 2003: Comparison of seasonal and spatial variations of albedos from Moderate-Resolution Imaging Spectroradiometer (MODIS) and common land model. J. Geophys. Res., 108 .4488, doi:10.1029/2002JD003326.

    • Search Google Scholar
    • Export Citation
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Effects of Implementing MODIS Land Cover and Albedo in MM5 at Two Contrasting U.S. Regions

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  • 1 Physics Department, Center for Atmospheric Sciences, Hampton University, Hampton, Virginia
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Abstract

This study implements a new land-cover classification and surface albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and investigates its effects on regional near-surface atmospheric state variables as well as the planetary boundary layer evolution for two dissimilar U.S. regions. Surface parameter datasets are determined by translating the 17-category MODIS classes into the U.S. Geological Survey (USGS) and Simple Biosphere (SiB) categories available for use in MM5. Changes in land-cover specification or associated parameters affected surface wind, temperature, and humidity fields, which, in turn, resulted in perceivable alterations in the evolving structure of the planetary boundary layer. Inclusion of the MODIS albedo into the simulations enhanced these impacts further. Area-averaged comparisons with ground measurements showed remarkable improvements in near-surface temperature and humidity at both study areas when MM5 is initialized with MODIS land-cover and albedo data. Influence of both MODIS surface datasets is more significant at a semiarid location in the southwest of the United States than it is in a humid location in the mid-Atlantic region. Intense summertime surface heating at the semiarid location creates favorable conditions for strong land surface forcing. For example, when the simulations include MODIS land cover and MODIS albedo, respective error reduction rates were 6% and 11% in temperature and 2% and 2.5% in humidity in the southwest of the United States. Error reduction rates in near-surface atmospheric fields are considered important in the design of mesoscale weather simulations.

Corresponding author address: Ismail Yucel, Center for Atmospheric Sciences, Hampton University, Hampton, VA 23668. Email: ismail.yucel@hamptonu.edu

Abstract

This study implements a new land-cover classification and surface albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and investigates its effects on regional near-surface atmospheric state variables as well as the planetary boundary layer evolution for two dissimilar U.S. regions. Surface parameter datasets are determined by translating the 17-category MODIS classes into the U.S. Geological Survey (USGS) and Simple Biosphere (SiB) categories available for use in MM5. Changes in land-cover specification or associated parameters affected surface wind, temperature, and humidity fields, which, in turn, resulted in perceivable alterations in the evolving structure of the planetary boundary layer. Inclusion of the MODIS albedo into the simulations enhanced these impacts further. Area-averaged comparisons with ground measurements showed remarkable improvements in near-surface temperature and humidity at both study areas when MM5 is initialized with MODIS land-cover and albedo data. Influence of both MODIS surface datasets is more significant at a semiarid location in the southwest of the United States than it is in a humid location in the mid-Atlantic region. Intense summertime surface heating at the semiarid location creates favorable conditions for strong land surface forcing. For example, when the simulations include MODIS land cover and MODIS albedo, respective error reduction rates were 6% and 11% in temperature and 2% and 2.5% in humidity in the southwest of the United States. Error reduction rates in near-surface atmospheric fields are considered important in the design of mesoscale weather simulations.

Corresponding author address: Ismail Yucel, Center for Atmospheric Sciences, Hampton University, Hampton, VA 23668. Email: ismail.yucel@hamptonu.edu

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