Severe cloud contamination of MODIS Land Surface Temperatures over an Arctic ice cap, Svalbard

Østby, Torbjørn Ims; Schuler, Thomas; Westermann, Sebastian

doi:10.1016/j.rse.2013.11.005

Cited by 70 publications

(81 citation statements)

References 44 publications

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“…2b also shows a comparison of monthly averages of all available MODIS LST measurements, i.e., without filling the gaps in the time series with ERA-Interim reanalysis air temperatures. Here, a significantly larger cold bias of up to 3 • C is found for all months except July, which is in line with validation studies from Svalbard which demonstrate a similar cold bias during the winter moths Østby et al, 2014). In July, the average of all MODIS LST measurements is significantly warmer than the observations.…”

Section: Comparison To In Situ Datasupporting

confidence: 90%

“…Validation studies have revealed a significant cold bias of long-term averages derived from MODIS LST in Arctic regions Østby et al, 2014), which is attributed to the overrepresentation of clear-sky situations and deficiencies in the cloud detection during polar night conditions (Liu et al, 2004). The same bias is found for Samoylov Island (Fig.…”

Section: Surface Temperaturementioning

confidence: 54%

“…This finding is corroborated by the sensitivity analysis (Table 3) which showcases the importance of a sound representation of ground thermal properties, in particular in and just below the active layer, for correct modeling of ground temperatures. These differences are at least partly related to stratigraphy-dependent thermal offsets between average ground surface and ground temperatures caused by seasonal changes of subsurface thermal conductivities due to freezing and thawing (Osterkamp and Romanovsky, 1999).…”

Section: The Modeled Ground Thermal Regimementioning

confidence: 99%

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Transient modeling of the ground thermal conditions using satellite data in the Lena River delta, Siberia

et al. 2017

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Abstract. Permafrost is a sensitive element of the cryosphere, but operational monitoring of the ground thermal conditions on large spatial scales is still lacking. Here, we demonstrate a remote-sensing-based scheme that is capable of estimating the transient evolution of ground temperatures and active layer thickness by means of the ground thermal model CryoGrid 2. The scheme is applied to an area of approximately 16 000 km 2 in the Lena River delta (LRD) in NE Siberia for a period of 14 years. The forcing data sets at 1 km spatial and weekly temporal resolution are synthesized from satellite products and fields of meteorological variables from the ERA-Interim reanalysis. To assign spatially distributed ground thermal properties, a stratigraphic classification based on geomorphological observations and mapping is constructed, which accounts for the large-scale patterns of sediment types, ground ice and surface properties in the Lena River delta.A comparison of the model forcing to in situ measurements on Samoylov Island in the southern part of the study area yields an acceptable agreement for the purpose of ground thermal modeling, for surface temperature, snow depth, and timing of the onset and termination of the winter snow cover. The model results are compared to observations of ground temperatures and thaw depths at nine sites in the Lena River delta, suggesting that thaw depths are in most cases reproduced to within 0.1 m or less and multi-year averages of ground temperatures within 1-2 • C. Comparison of monthly average temperatures at depths of 2-3 m in five boreholes yielded an RMSE of 1

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Section: Comparison To In Situ Datasupporting

confidence: 90%

Section: Surface Temperaturementioning

confidence: 54%

Section: The Modeled Ground Thermal Regimementioning

confidence: 99%

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Transient modeling of the ground thermal conditions using satellite data in the Lena River delta, Siberia

et al. 2017

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“…The colder MODIS LST may be related to the inherent association of MODIS measurements with clear-sky conditions. Previous studies have noted the seasonality of MODIS LST errors in Arctic environments with a slight warm bias during summer and a strong cold bias in winter (Langer et al, 2010;Østby et al, 2014;Westermann et al, 2011;Westermann et al, 2012). In summer, net radiation is higher under clear skies and warms the surface more than under overcast conditions.…”

Section: Uncertainties and Errors Of Modis Lst Evaluationmentioning

confidence: 96%

Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes

Muster

Langer

Abnizova

et al. 2015

Remote Sensing of Environment

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The accelerated warming of the Arctic climate may alter the local and regional surface energy balances, for which changing land surface temperatures (LSTs) are a key indicator. Modeling current and anticipated changes in the surface energy balance requires an understanding of the spatio-temporal interactions between LSTs and land cover, both of which can be monitored globally by measurements from space. This paper investigates the accuracy of the MODIS LST/Emissivity Daily L3 Global 1 km V005 product and its spatio-temporal sensitivity to land surface properties in a Canadian High Arctic permafrost landscape. The land cover ranged from fully vegetated wet sedge tundra to barren rock. MODIS LSTs were compared with in situ radiometer measurements from wet tundra areas collected over a 2-year period from July 2008 to July 2010 including both summer and winter conditions. The accuracy of the MODIS LSTs was −1.1°C with a root mean square error of 3.9°C over the entire observation period. Agreement was lowest during the freeze-back periods where MODIS LST showed a cold bias likely due to the overrepresentation of clear-sky conditions. A multi-year analysis of LST spatial anomalies, i.e., the difference between MODIS LSTs and the MODIS LST regional mean, revealed a robust spatiotemporal pattern. Highest variability in LST anomalies was found during freeze-up and thaw periods as well as for open water surface in early summer due to the presence or absence of snow or ice. The summer anomaly pattern was similar for all three years despite strong differences in precipitation, air temperature and net radiation. Summer periods with regional mean LSTs above 5.0°C showed the greatest spatial diversity with four distinct 2.0°C classes. Summer anomalies ranged from −4.5°C to 2.6°C with an average standard deviation of 1.8°C. Dry ridge areas heated up the most, while wetland areas and dry areas of sparsely vegetated bedrock with a high albedo remained coolest. The observed summer LST anomalies can be used as a baseline against which to evaluate both past and future changes in land surface properties that relate to the surface energy balance. Summer anomaly classes mainly reflected a combination of albedo and surface wetness. The potential to use this tool to monitor surface drying and wetting in the Arctic should therefore be further explored. A multi-sensor approach combining thermal satellite measurements with optical and radar imagery promises to be an effective tool for a dynamic, process-based ecosystem monitoring scheme.

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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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Severe cloud contamination of MODIS Land Surface Temperatures over an Arctic ice cap, Svalbard

Cited by 70 publications

References 44 publications

Transient modeling of the ground thermal conditions using satellite data in the Lena River delta, Siberia

Transient modeling of the ground thermal conditions using satellite data in the Lena River delta, Siberia

Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes

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

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