A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
<p>Near-surface air temperature (<span class="inline-formula"><i>T</i><sub>a</sub></span>) is a key variable in global climate studies. A global gridded dataset of daily maximum and minimum <span class="inline-formula"><i>T<...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-12-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/14/5637/2022/essd-14-5637-2022.pdf |
| _version_ | 1811195642950713344 |
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| author | T. Zhang Y. Zhou K. Zhao Z. Zhu G. Chen J. Hu L. Wang |
| author_facet | T. Zhang Y. Zhou K. Zhao Z. Zhu G. Chen J. Hu L. Wang |
| author_sort | T. Zhang |
| collection | DOAJ |
| description | <p>Near-surface air temperature (<span class="inline-formula"><i>T</i><sub>a</sub></span>) is a key variable in global climate
studies. A global gridded dataset of daily maximum and minimum <span class="inline-formula"><i>T</i><sub>a</sub></span> (<span class="inline-formula"><i>T</i><sub>max</sub></span> and <span class="inline-formula"><i>T</i><sub>min</sub></span>) is particularly valuable and critically needed in
the scientific and policy communities but is still not available. In this paper, we developed a global dataset of daily <span class="inline-formula"><i>T</i><sub>max</sub></span> and <span class="inline-formula"><i>T</i><sub>min</sub></span>
at 1 <span class="inline-formula">km</span> resolution over land across 50<span class="inline-formula"><sup>∘</sup></span> S–79<span class="inline-formula"><sup>∘</sup></span> N from 2003 to 2020 through the combined use of ground-station-based
<span class="inline-formula"><i>T</i><sub>a</sub></span> measurements and satellite observations (i.e., digital elevation model and land surface temperature) via a state-of-the-art
statistical method named Spatially Varying Coefficient Models with Sign Preservation (SVCM-SP). The root mean square errors in our estimates ranged
from 1.20 to 2.44 <span class="inline-formula"><sup>∘</sup>C</span> for <span class="inline-formula"><i>T</i><sub>max</sub></span> and 1.69 to 2.39 <span class="inline-formula"><sup>∘</sup>C</span> for <span class="inline-formula"><i>T</i><sub>min</sub></span>. We found that the accuracies were affected
primarily by land cover types, elevation ranges, and climate backgrounds. Our dataset correctly represents a negative relationship between
<span class="inline-formula"><i>T</i><sub>a</sub></span> and elevation and a positive relationship between <span class="inline-formula"><i>T</i><sub>a</sub></span> and land surface temperature; it captured spatial and temporal
patterns of <span class="inline-formula"><i>T</i><sub>a</sub></span> realistically. This global 1 <span class="inline-formula">km</span> gridded daily <span class="inline-formula"><i>T</i><sub>max</sub></span> and <span class="inline-formula"><i>T</i><sub>min</sub></span> dataset is the first of its kind, and we
expect it to be of great value to global studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting. The data have
been published by Iowa State University at <a href="https://doi.org/10.25380/iastate.c.6005185">https://doi.org/10.25380/iastate.c.6005185</a> (Zhang and Zhou, 2022).</p> |
| first_indexed | 2024-04-12T00:46:33Z |
| format | Article |
| id | doaj.art-da73a899ce9a4c3497451a72abd3944b |
| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-04-12T00:46:33Z |
| publishDate | 2022-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj.art-da73a899ce9a4c3497451a72abd3944b2022-12-22T03:54:52ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162022-12-01145637564910.5194/essd-14-5637-2022A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)T. Zhang0Y. Zhou1K. Zhao2Z. Zhu3G. Chen4J. Hu5L. Wang6Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USADepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USASchool of Environment and Natural Resources, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USADepartment of Statistics, Iowa State University, Ames, IA 50011, USALaboratory for Remote Sensing and Environmental Change (LRSEC), Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USADepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USADepartment of Statistics, George Mason University, Fairfax, VA 22030, USA<p>Near-surface air temperature (<span class="inline-formula"><i>T</i><sub>a</sub></span>) is a key variable in global climate studies. A global gridded dataset of daily maximum and minimum <span class="inline-formula"><i>T</i><sub>a</sub></span> (<span class="inline-formula"><i>T</i><sub>max</sub></span> and <span class="inline-formula"><i>T</i><sub>min</sub></span>) is particularly valuable and critically needed in the scientific and policy communities but is still not available. In this paper, we developed a global dataset of daily <span class="inline-formula"><i>T</i><sub>max</sub></span> and <span class="inline-formula"><i>T</i><sub>min</sub></span> at 1 <span class="inline-formula">km</span> resolution over land across 50<span class="inline-formula"><sup>∘</sup></span> S–79<span class="inline-formula"><sup>∘</sup></span> N from 2003 to 2020 through the combined use of ground-station-based <span class="inline-formula"><i>T</i><sub>a</sub></span> measurements and satellite observations (i.e., digital elevation model and land surface temperature) via a state-of-the-art statistical method named Spatially Varying Coefficient Models with Sign Preservation (SVCM-SP). The root mean square errors in our estimates ranged from 1.20 to 2.44 <span class="inline-formula"><sup>∘</sup>C</span> for <span class="inline-formula"><i>T</i><sub>max</sub></span> and 1.69 to 2.39 <span class="inline-formula"><sup>∘</sup>C</span> for <span class="inline-formula"><i>T</i><sub>min</sub></span>. We found that the accuracies were affected primarily by land cover types, elevation ranges, and climate backgrounds. Our dataset correctly represents a negative relationship between <span class="inline-formula"><i>T</i><sub>a</sub></span> and elevation and a positive relationship between <span class="inline-formula"><i>T</i><sub>a</sub></span> and land surface temperature; it captured spatial and temporal patterns of <span class="inline-formula"><i>T</i><sub>a</sub></span> realistically. This global 1 <span class="inline-formula">km</span> gridded daily <span class="inline-formula"><i>T</i><sub>max</sub></span> and <span class="inline-formula"><i>T</i><sub>min</sub></span> dataset is the first of its kind, and we expect it to be of great value to global studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting. The data have been published by Iowa State University at <a href="https://doi.org/10.25380/iastate.c.6005185">https://doi.org/10.25380/iastate.c.6005185</a> (Zhang and Zhou, 2022).</p>https://essd.copernicus.org/articles/14/5637/2022/essd-14-5637-2022.pdf |
| spellingShingle | T. Zhang Y. Zhou K. Zhao Z. Zhu G. Chen J. Hu L. Wang A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020) Earth System Science Data |
| title | A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020) |
| title_full | A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020) |
| title_fullStr | A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020) |
| title_full_unstemmed | A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020) |
| title_short | A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020) |
| title_sort | global dataset of daily maximum and minimum near surface air temperature at 1 thinsp km resolution over land 2003 2020 |
| url | https://essd.copernicus.org/articles/14/5637/2022/essd-14-5637-2022.pdf |
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