Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains

Williamson, Scott; Hik, David S.; Gamon, John A.; Jarosch, Alexander H.; Anslow, F. S.; Clarke, Garry K. C.; Rupp, T. Scott

doi:10.1016/j.rse.2016.11.009

Cited by 34 publications

(40 citation statements)

References 35 publications

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“…Hall et al 2012), to monitor melt events on the ice sheet (Hall et al, 2013), and as input for surface mass balance or snowpack modeling (Fréville et al, 2014;Shamir and Georgakakos, 2014;Navari et al, 2016). A number of validation studies present results acquired over various time scales and in different locations to 130 determine the accuracy of the MODIS surface temperature products in the cryosphere (Hall et al, 2004(Hall et al, , 2008Koenig and Hall, 2010;Westermann et al, 2012;Hachem et al, 2012;Shuman et al, 2014;Østby et al, 2014;Shamir and Georgakakos, 2014;Hall et al, 2015;Williamson et al, 2017). validation studies and is discussed in further detail in the discussion section.…”

Section: Remote Sensing Of Surface Temperaturementioning

confidence: 99%

Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

Adolph

Albert

Hall

2017

Preprint

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10As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures, but in remote locations where few ground-based measurements exist, such as on the Greenland Ice Sheet, temperatures over large areas are assessed using remote sensing techniques. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow 15 surface (referred to as "skin" temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June through 18July 2015, near Summit Station in Greenland to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, thermochrons, and thermocouples; 2 m air temperature measured by a NOAA meteorological station; and a MODerate-resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our 20 data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in-situ, and this finding may account for apparent biases in previous surface temperature studies of MODIS products that used 2 m air temperature for validation. This inversion is present during summer months when incoming solar radiation and wind speed are both low. As compared to our in-situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface-temperature standard product has an RMSE of 1.0°C, spanning a range of temperatures from -35°C to -5°C. For our 25 study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below -20°C where other studies found a significant cold bias. The apparent "cold bias" present in others' comparison of 2 m air temperature and MODIS surface temperature is perhaps a result of the nearsurface temperature inversion that our data demonstrate. Further investigation of how in-situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below -35°C) is warranted to determine if this cold bias does indeed exist. 30The Cryosphere Discuss., https://doi

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Section: Remote Sensing Of Surface Temperaturementioning

confidence: 99%

Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

Adolph

Albert

Hall

2017

Preprint

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“…Therefore, there are challenges in converting LST to a realistic measure of air temperature at high elevations (Pepin et al, ). Well‐known issues include contamination by cloud cover (Zhang, Zhang, Ye, et al, ; Zhang, Zhang, Zhang, et al, ), the influence of ephemeral snow cover (Shamir & Georgakakos, ; Williamson et al, ), the role of vegetation in increasing latent heat at the expense of sensible heat (Vancutsem et al, ), and timing and spatial differences between the two measurements (point vs pixel).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, there are challenges in converting LST to a realistic measure of air temperature at high elevations (Pepin et al, 2016). Well-known issues include contamination by cloud cover (Zhang, Zhang, Ye, et al, 2016;, the influence of ephemeral snow cover (Shamir & Georgakakos, 2014;Williamson et al, 2017), the role of vegetation in increasing latent heat at the expense of sensible heat (Vancutsem et al, 2010), and timing and spatial differences between the two measurements (point vs pixel). This paper develops a new statistical model to predict the difference between LST and T air at 87 Chinese Meteorological Administration stations on the Tibetan plateau and uses the model to correct LST to more precisely represent air temperature.…”

Section: Introductionmentioning

confidence: 99%

An Examination of Temperature Trends at High Elevations Across the Tibetan Plateau: The Use of MODIS LST to Understand Patterns of Elevation‐Dependent Warming

et al. 2019

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Research has revealed systematic changes in warming rates with elevation (EDW) in mountain regions. However, weather stations on the Tibetan plateau are mostly located at lower elevations (3,000‐4,000 m) and are nonexistent above 5,000 m, leaving critical temperature changes unknown. Satellite LST (Land Surface Temperature) can fill this gap but needs calibrating against in situ air temperatures (Tair). We develop a novel statistical model to convert LST to Tair, developed at 87 high‐elevation Chinese Meteorological Administration stations. Tair (daily maximum/minimum temperatures) is compared with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua LST (1330 and 0130 local time) for 8‐day composites during 2002‐2017. Typically, 80‐95% of the difference between LST and Tair (ΔT) is explained using predictors including LST diurnal range, morning heating/nighttime cooling rates, the number of cloud free days/nights, and season (solar angle). LST is corrected to more closely represent Tair by subtracting modeled ΔT. We validate the model using an AWS on Zhadang Glacier (5800 m). Trend analysis at the 87 stations (2002‐2017) shows corrected LST trends to be similar to original Tair trends. To examine regional contrasts in EDW patterns, elevation profiles of corrected LST trends are derived for three ranges (Qilian Mountains, NyenchenTanglha, and Himalaya). There is limited EDW in the Qilian mountains. Maximum warming is observed around 4,500‐5,500 m in NyenchenTanglha, consistent with snowline retreat. In common with other studies, there is stabilization of warming at very high elevations in the Himalaya, including absolute cooling above 6,000 m, but data there are compromised by frequent cloud.

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“…A number of validation studies present results acquired over various timescales and in different locations to determine the accuracy of the MODIS surface temperature products in the cryosphere (Hall et al, 2004(Hall et al, , 2008Koenig and Hall, 2010;Westermann et al, 2012;Hachem et al, 2012;Shuman et al, 2014;Østby et al, 2014;Shamir and Georgakakos, 2014;Williamson et al, 2017). Table 1 provides summary statistics related to the results of many of these validation studies and is discussed in further detail in the discussion section.…”

Section: Introductionmentioning

confidence: 99%

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

2018

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Abstract. As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as "skin" temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 • C and a mean bias of −0.4 • C, spanning a range of temperatures from −35 to −5 • C (RMSE = 1.6 • C and mean bias = −0.7 • C prior to cloud masking). For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below −20 • C, where other studies found a significant cold bias. We show that the apparent cold bias present in other comparisons of 2 m air temperature and MODIS surface temperature may be a result of the near-surface temperature inversion. Further investigation of how in situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below −35 • C) is warranted to determine whether a cold bias exists for those temperatures.

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Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains

Cited by 34 publications

References 35 publications

Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

An Examination of Temperature Trends at High Elevations Across the Tibetan Plateau: The Use of MODIS LST to Understand Patterns of Elevation‐Dependent Warming

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

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