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Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains
Satellite-derived land surface temperature (skin temperature) provides invaluable information for data-sparse high elevation and Arctic regions. However, the relationship between satellite-derived clear-sky skin temperature and various downscaled air temperature products for snow covered sub-Arctic...
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Published in: | Remote sensing of environment 2017-02, Vol.189, p.14-24 |
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description | Satellite-derived land surface temperature (skin temperature) provides invaluable information for data-sparse high elevation and Arctic regions. However, the relationship between satellite-derived clear-sky skin temperature and various downscaled air temperature products for snow covered sub-Arctic alpine regions remain poorly understood, such that trend analysis or air temperature product integration is difficult. We compared monthly average air temperatures from two independent downscaled temperature products to MODIS Land Surface Temperature (LST) and air temperature at nine meteorological stations situated above tree-line in the southwest Yukon, Canada, between May and August 2008 for a full range of snow cover fractions. We found that both downscaled products generally agreed with LST for the low elevation, snow-free, vegetation classes. However, a systematic cold bias in Average LST emerged for snow fractions greater than approximately 40%, and this bias increased in magnitude as snow cover increased. In these situations the downscaled air temperatures were 5–7°C warmer than Average LST for snow fractions of >90%, and this pattern was largely independent of the number of measurements of LST within a month. Maximum LST was similar to average air temperatures for high snow fractions, but Minimum LST was colder by 10°C or more for all snow fractions. Consequently, the average of Maximum and Minimum LST produces the cold bias, compared to air temperature, for high snow cover fractions. Air temperature measured at nine meteorological monitoring stations located between elevations of 1408–2690m, on land cover classes Barren, Sparsely Vegetated or Permanent Snow and Ice, confirmed the cold bias results when incorporating Minimum LST in monthly averages. For snow fractions of |
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•The LST down-scaled air temperature relationship depends on snow cover.•Minimum LST tracks average air temperature for all snow cover fractions.•Maximum LST converges with average air temperature for large snow cover fractions.•Integration of LST with downscaled air temperature requires including snow cover.</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2016.11.009</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>Air temperature ; Bias ; Cloud cover ; Cryosphere ; Downscaled NARR ; Elevation ; Land surface temperature ; MODIS ; MODIS LST ; SNAP ; Snow ; Snow cover ; Stations</subject><ispartof>Remote sensing of environment, 2017-02, Vol.189, p.14-24</ispartof><rights>2016 Elsevier Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-b97bac3201f7c409590f96737672ff172db9f1fe73457eae243859c31304d0af3</citedby><cites>FETCH-LOGICAL-c331t-b97bac3201f7c409590f96737672ff172db9f1fe73457eae243859c31304d0af3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Williamson, Scott N.</creatorcontrib><creatorcontrib>Hik, David S.</creatorcontrib><creatorcontrib>Gamon, John A.</creatorcontrib><creatorcontrib>Jarosch, Alexander H.</creatorcontrib><creatorcontrib>Anslow, Faron S.</creatorcontrib><creatorcontrib>Clarke, Garry K.C.</creatorcontrib><creatorcontrib>Scott Rupp, T.</creatorcontrib><title>Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains</title><title>Remote sensing of environment</title><description>Satellite-derived land surface temperature (skin temperature) provides invaluable information for data-sparse high elevation and Arctic regions. However, the relationship between satellite-derived clear-sky skin temperature and various downscaled air temperature products for snow covered sub-Arctic alpine regions remain poorly understood, such that trend analysis or air temperature product integration is difficult. We compared monthly average air temperatures from two independent downscaled temperature products to MODIS Land Surface Temperature (LST) and air temperature at nine meteorological stations situated above tree-line in the southwest Yukon, Canada, between May and August 2008 for a full range of snow cover fractions. We found that both downscaled products generally agreed with LST for the low elevation, snow-free, vegetation classes. However, a systematic cold bias in Average LST emerged for snow fractions greater than approximately 40%, and this bias increased in magnitude as snow cover increased. In these situations the downscaled air temperatures were 5–7°C warmer than Average LST for snow fractions of >90%, and this pattern was largely independent of the number of measurements of LST within a month. Maximum LST was similar to average air temperatures for high snow fractions, but Minimum LST was colder by 10°C or more for all snow fractions. Consequently, the average of Maximum and Minimum LST produces the cold bias, compared to air temperature, for high snow cover fractions. Air temperature measured at nine meteorological monitoring stations located between elevations of 1408–2690m, on land cover classes Barren, Sparsely Vegetated or Permanent Snow and Ice, confirmed the cold bias results when incorporating Minimum LST in monthly averages. For snow fractions of <40% the RMSE for all of the temperature products was <2.5°C when compared to station air temperature and all biases were positive and <2.0°C. For snow fractions of >40%, the average LST bias became strongly negative at −4.5°C, and the RMSE increased to 6.1°C, whereas the downscaled products bias and RMSE were similar to those from snow fractions of <40%. A weak warm bias for all the temperature products occurred for small snow fractions over non-forested land cover classes. Downscaled air temperature fields show physically real differences from Average LST in spring and summer, caused by snow cover and the interplay of Maximum and Minimum LST. These findings indicate that the integration of MODIS LST with downscaled air temperature products or local air temperature requires the incorporation of snow cover.
•The LST down-scaled air temperature relationship depends on snow cover.•Minimum LST tracks average air temperature for all snow cover fractions.•Maximum LST converges with average air temperature for large snow cover fractions.•Integration of LST with downscaled air temperature requires including snow cover.</description><subject>Air temperature</subject><subject>Bias</subject><subject>Cloud cover</subject><subject>Cryosphere</subject><subject>Downscaled NARR</subject><subject>Elevation</subject><subject>Land surface temperature</subject><subject>MODIS</subject><subject>MODIS LST</subject><subject>SNAP</subject><subject>Snow</subject><subject>Snow cover</subject><subject>Stations</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqNkUFv2zAMhYWhA5Zm_QG96biLPdGyIws7BWm7BciQQ9KzIMvUoiCWM0nukH9fBdl52IkE8T0Sj4-QR2AlMFh8PZYhYlnltgQoGZMfyAxaIQsmWH1HZozxuqirRnwi9zEeGYOmFTAjl905OP-Lat_TOA0DBjqMPh1OF_pz-7Te0c1uT12kzh8woE953jkdsadmHM465CaNVLtAEw5nDDpNATNNox__ZOYNr0icumIZTHImb5980s7Hz-Sj1aeID3_rnLy-PO9XP4rN9vt6tdwUhnNIRSdFpw3PzqwwNZONZFYuBBcLUVkLouo7acGi4HUjUGNV87aRhgNndc-05XPy5bb3HMbfE8akBhcNnk7a4zhFBW3L8neAN_-BNrLJbL4xJ3BDTRhjDGhV_uOgw0UBU9dE1FHlRNQ1EQWgciJZ8-2mwWz3zWFQ0Tj0BnsX0CTVj-4f6nc0hJQB</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Williamson, Scott N.</creator><creator>Hik, David S.</creator><creator>Gamon, John A.</creator><creator>Jarosch, Alexander H.</creator><creator>Anslow, Faron S.</creator><creator>Clarke, Garry K.C.</creator><creator>Scott Rupp, T.</creator><general>Elsevier Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7TG</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20170201</creationdate><title>Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains</title><author>Williamson, Scott N. ; Hik, David S. ; Gamon, John A. ; Jarosch, Alexander H. ; Anslow, Faron S. ; Clarke, Garry K.C. ; Scott Rupp, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-b97bac3201f7c409590f96737672ff172db9f1fe73457eae243859c31304d0af3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Air temperature</topic><topic>Bias</topic><topic>Cloud cover</topic><topic>Cryosphere</topic><topic>Downscaled NARR</topic><topic>Elevation</topic><topic>Land surface temperature</topic><topic>MODIS</topic><topic>MODIS LST</topic><topic>SNAP</topic><topic>Snow</topic><topic>Snow cover</topic><topic>Stations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Williamson, Scott N.</creatorcontrib><creatorcontrib>Hik, David S.</creatorcontrib><creatorcontrib>Gamon, John A.</creatorcontrib><creatorcontrib>Jarosch, Alexander H.</creatorcontrib><creatorcontrib>Anslow, Faron S.</creatorcontrib><creatorcontrib>Clarke, Garry K.C.</creatorcontrib><creatorcontrib>Scott Rupp, T.</creatorcontrib><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Williamson, Scott N.</au><au>Hik, David S.</au><au>Gamon, John A.</au><au>Jarosch, Alexander H.</au><au>Anslow, Faron S.</au><au>Clarke, Garry K.C.</au><au>Scott Rupp, T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains</atitle><jtitle>Remote sensing of environment</jtitle><date>2017-02-01</date><risdate>2017</risdate><volume>189</volume><spage>14</spage><epage>24</epage><pages>14-24</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>Satellite-derived land surface temperature (skin temperature) provides invaluable information for data-sparse high elevation and Arctic regions. However, the relationship between satellite-derived clear-sky skin temperature and various downscaled air temperature products for snow covered sub-Arctic alpine regions remain poorly understood, such that trend analysis or air temperature product integration is difficult. We compared monthly average air temperatures from two independent downscaled temperature products to MODIS Land Surface Temperature (LST) and air temperature at nine meteorological stations situated above tree-line in the southwest Yukon, Canada, between May and August 2008 for a full range of snow cover fractions. We found that both downscaled products generally agreed with LST for the low elevation, snow-free, vegetation classes. However, a systematic cold bias in Average LST emerged for snow fractions greater than approximately 40%, and this bias increased in magnitude as snow cover increased. In these situations the downscaled air temperatures were 5–7°C warmer than Average LST for snow fractions of >90%, and this pattern was largely independent of the number of measurements of LST within a month. Maximum LST was similar to average air temperatures for high snow fractions, but Minimum LST was colder by 10°C or more for all snow fractions. Consequently, the average of Maximum and Minimum LST produces the cold bias, compared to air temperature, for high snow cover fractions. Air temperature measured at nine meteorological monitoring stations located between elevations of 1408–2690m, on land cover classes Barren, Sparsely Vegetated or Permanent Snow and Ice, confirmed the cold bias results when incorporating Minimum LST in monthly averages. For snow fractions of <40% the RMSE for all of the temperature products was <2.5°C when compared to station air temperature and all biases were positive and <2.0°C. For snow fractions of >40%, the average LST bias became strongly negative at −4.5°C, and the RMSE increased to 6.1°C, whereas the downscaled products bias and RMSE were similar to those from snow fractions of <40%. A weak warm bias for all the temperature products occurred for small snow fractions over non-forested land cover classes. Downscaled air temperature fields show physically real differences from Average LST in spring and summer, caused by snow cover and the interplay of Maximum and Minimum LST. These findings indicate that the integration of MODIS LST with downscaled air temperature products or local air temperature requires the incorporation of snow cover.
•The LST down-scaled air temperature relationship depends on snow cover.•Minimum LST tracks average air temperature for all snow cover fractions.•Maximum LST converges with average air temperature for large snow cover fractions.•Integration of LST with downscaled air temperature requires including snow cover.</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2016.11.009</doi><tpages>11</tpages></addata></record> |
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subjects | Air temperature Bias Cloud cover Cryosphere Downscaled NARR Elevation Land surface temperature MODIS MODIS LST SNAP Snow Snow cover Stations |
title | Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains |
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