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      Downscaling NLDAS-2 daily maximum air temperatures using MODIS land surface temperatures

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      1 , * , 1 , 2
      PLoS ONE
      Public Library of Science

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          Abstract

          We have developed and applied a relatively simple disaggregation scheme that uses spatial patterns of Land Surface Temperature (LST) from MODIS warm-season composites to improve the spatial characterization of daily maximum and minimum air temperatures. This down-scaling model produces qualitatively reasonable 1 km daily maximum and minimum air temperature estimates that reflect urban and coastal features. In a 5-city validation, the model was shown to provide improved daily maximum air temperature estimates in the three coastal cities, compared to 12 km NLDAS-2 (North American Land Data Assimilation System). Down-scaled maximum temperature estimates for the other two (non-coastal) cities were marginally worse than the original NLDAS-2 temperatures. For daily minimum temperatures, the scheme produces spatial fields that qualitatively capture geographic features, but quantitative validation shows the down-scaling model performance to be very similar to the original NLDAS-2 minimum temperatures. Thus, we limit the discussion in this paper to daily maximum temperatures. Overall, errors in the down-scaled maximum air temperatures are comparable to errors in down-scaled LST obtained in previous studies. The advantage of this approach is that it produces estimates of daily maximum air temperatures, which is more relevant than LST in applications such as public health. The resulting 1 km daily maximum air temperatures have great potential utility for applications such as public health, energy demand, and surface energy balance analyses. The method may not perform as well in conditions of strong temperature advection. Application of the model also may be problematic in areas having extreme changes in elevation.

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          Most cited references34

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          A generalized split-window algorithm for retrieving land-surface temperature from space

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            Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong

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              Estimating subpixel surface temperatures and energy fluxes from the vegetation index–radiometric temperature relationship

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Funding acquisitionRole: InvestigationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 January 2020
                2020
                : 15
                : 1
                : e0227480
                Affiliations
                [1 ] Universities Space Research Association, NASA Marshall Space Flight Center, Huntsville, AL, United States of America
                [2 ] New York State Department of Health & University at Albany- State University of New York, Albany, NY, United States of America
                George Mason University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-0439-3206
                http://orcid.org/0000-0003-4725-2515
                Article
                PONE-D-19-08782
                10.1371/journal.pone.0227480
                6964900
                31945081
                85356bd0-87a7-47fb-b196-d17bb7267469
                © 2020 Crosson et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 March 2019
                : 19 December 2019
                Page count
                Figures: 3, Tables: 1, Pages: 13
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100014573, Earth Sciences Division;
                Award ID: U38EH000942
                Award Recipient :
                This project is funded by NASA ROSES 2013: NNX15AN77G -Using Remote Sensing and Environmental Data to Quantify Social Vulnerabilities to Heat Stress and Strengthen Environmental Public Health Tracking and Heat Mitigation Efforts; supported by CDC’s National Environmental Public Health Tracking Program, Federal Award Number U38EH000942. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Public and Occupational Health
                Earth Sciences
                Geography
                Geographic Areas
                Urban Areas
                Physical Sciences
                Materials Science
                Material Properties
                Surface Properties
                Surface Temperature
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Physical Sciences
                Physics
                Condensed Matter Physics
                Surface Energy
                Engineering and Technology
                Remote Sensing
                Earth Sciences
                Engineering and Technology
                Equipment
                Optical Equipment
                Prisms
                Custom metadata
                The down-scaled products presented in this paper and an executable for running the down-scaling model developed by the authors are available from the New York State Environmental Public Health tracking program by contacting tabassum.insafhealth.ny.gov or epht@ 123456health.ny.gov . The native NLDAS-2 and MODIS data used in the creation of the down-scaled products are available from the respective data depositories at https://disc.gsfc.nasa.gov/ and https://earthdata.nasa.gov/.

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