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Evaluation of CAMEL over the Taklimakan Desert Using Field Observations

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  • Yufen Ma

    (Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
    National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
    Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi 830002, China
    Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China)

  • Wei Han

    (China Meteorological Administration Earth System Modeling and Prediction Centre (CEMC), Beijing 100081, China
    The State Key Laboratory of Severe Weather (LaSW), China Meteorological Administration, Beijing 100081, China)

  • Zhenglong Li

    (Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • E. Eva Borbas

    (Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • Ali Mamtimin

    (Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
    National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
    Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi 830002, China
    Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China)

  • Yongqiang Liu

    (College of Resource and Environmental Sciences, Xinjiang University, Urumqi 830049, China)

Abstract

Infrared (IR) land surface emissivity (LSE) plays an important role in numerical weather prediction (NWP) models through the satellite radiance assimilation. However, due to the large uncertainties in LSE over the desert, many land-surface sensitive channels of satellite IR sensors are not assimilated. This calls for further assessments of the quality of satellite-retrieved LSE in these desert regions. A set of LSE observations were made from field experiments conducted on 16–18 October 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference values to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL) data. Analysis of these data shows four main results. First, the CAMEL datasets appear to sufficiently capture the spatial variations in LSE from the oasis to the hinterland of the TD (this is especially the case in the quartz reststrahlen band). From site 1 at the southern edge of the Taklimakan Desert to site 10 at the northern edge, the measured LSE and the corresponding CAMEL observation in the quartz reststrahlen band first decrease and reach their minimum around sites 4–6 in the hinterland of the Taklimakan Desert. Then, the LSE increases gradually and finally reaches its maximum at site 10, which has a clay ground surface, showing that the LSE is higher at the edges of the desert and lower in the center. Second, the CAMEL values at 11.3 μm have a zonal distribution characterized by a northeast–southwest strike, though such an artifact might have been introduced by ASTER LSE data during the merging process that created the CAMEL dataset. Third, the unrealistic variation of the original EOBS can be filtered out with useful signals, as identified by the first six principal components of the PCA conducted on the laboratory-measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL results correlate well with the measured LSE at the 10 observation sites, with the observed LSE being slightly smaller than the CAMEL values in general.

Suggested Citation

  • Yufen Ma & Wei Han & Zhenglong Li & E. Eva Borbas & Ali Mamtimin & Yongqiang Liu, 2023. "Evaluation of CAMEL over the Taklimakan Desert Using Field Observations," Land, MDPI, vol. 12(6), pages 1-21, June.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1232-:d:1171746
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    References listed on IDEAS

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    1. Michele Torresani & Guido Masiello & Nadia Vendrame & Giacomo Gerosa & Marco Falocchi & Enrico Tomelleri & Carmine Serio & Duccio Rocchini & Dino Zardi, 2022. "Correlation Analysis of Evapotranspiration, Emissivity Contrast and Water Deficit Indices: A Case Study in Four Eddy Covariance Sites in Italy with Different Environmental Habitats," Land, MDPI, vol. 11(11), pages 1-16, October.
    2. Peter Bauer & Alan Thorpe & Gilbert Brunet, 2015. "The quiet revolution of numerical weather prediction," Nature, Nature, vol. 525(7567), pages 47-55, September.
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