Angular anisotropy of satellite observations of land surface temperature

Vinnikov, Konstantin Y.; Yu, Yunyue; Goldberg, Mitchell D.; Tarpley, Dan; Romanov, Peter; László, István; Chen, Ming

doi:10.1029/2012gl054059

Cited by 80 publications

(67 citation statements)

References 20 publications

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“…Thermal anisotropy refers to the angular variation of TIR radiation. This effect is stronger during daytime and can make the LST of the same target to vary more than 2-4 • C when viewed by different directions [47,48]. Thermal anisotropy is known to influence the comparison of LST data [1,48,49] and for this reason it is important to adopt compensation strategies when comparing LST data from different sources, as is this case.…”

Section: Research Objective and Experimental Setupmentioning

confidence: 99%

“…Hence, following this approach, even though it adds an additional source of statistical noise, makes the performed analysis more straightforward. Another important issue that can influence the analysis of LST data is thermal anisotropy [47,48]. Thermal anisotropy refers to the angular variation of TIR radiation.…”

Section: Research Objective and Experimental Setupmentioning

confidence: 99%

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Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels

et al. 2016

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Abstract:The downscaling of geostationary diurnal thermal data can ease the lack of land surface temperature (LST) datasets that combine high spatial and temporal resolution. However, the downscaling of diurnal LST data is more demanding than single scenes. This is because the spatiotemporal interrelationships of the original LST data have to be preserved and accurately reproduced by the downscaled LST (DLST) data. To that end, LST disaggregation kernels/predictors that provide information about the spatial distribution of LST during different times of a day can prove especially useful. Such LST predictors are the LST Annual Cycle Parameters (ACPs). In this work, multitemporal ACPs are employed for downscaling daytime and nighttime~4 km geostationary LST from SEVIRI (Spinning Enhanced Visible and Infrared Imager) down to 1 km. The overall goal is to assess if the use of the ACPs can improve the estimation of the diurnal range of DLST (daytime DLST minus nighttime DLST). The evaluation is performed by comparing the DLST diurnal range maps with reference data from MODIS (Moderate Imaging Spectroradiometer) and also with data retrieved from a modified version of the TsHARP (Thermal Sharpening) algorithm. The results suggest that the ACPs increase the downscaling performance, improve the estimation of diurnal DLST range and produce more accurate spatial patterns.

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Section: Research Objective and Experimental Setupmentioning

confidence: 99%

Section: Research Objective and Experimental Setupmentioning

confidence: 99%

Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels

et al. 2016

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“…The experimental data showed that the differences between nadir and off-nadir values of directional temperature are of considerable magnitude and, as such, cannot be ignored [76]. Angular correction of satellite retrieved LST must be applied before LST data can be compiled into a long-term data set, assimilated into weather prediction models or used in climate research [77]. The accuracy of MODIS products may be affected by errors in land surface emissivity.…”

Section: The Emphasis Of the View Angle In Temporal Compositionmentioning

confidence: 99%

Impact of MODIS Quality Control on Temporally Aggregated Urban Surface Temperature and Long-Term Surface Urban Heat Island Intensity

Gawuć

Strużewska

2016

Remote Sensing

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Surface Urban Heat Island (SUHI) is a phenomenon of high spatial and temporal variability. However, studies that investigate urban land surface temperature (LST) observed in different seasons frequently utilize a single satellite measurement and do not incorporate temporal composites. Temporally aggregated data increase clear sky coverage, which is important in many aspects of urban climatology. However, it is critical to account for possible errors and quality of the data that are utilized. The objective of this paper is to analyze the impact of MODIS Quality Control (QC) and the view angle on temporally aggregated urban surface temperature and long-term SUHI intensity. To achieve this, a weighted arithmetic mean was utilized whose weights were based on the view angle of satellite observation and the MODIS QC flags; namely, LST retrieval errors and emissivity errors. In order to investigate the impact of the MODIS QC on long-term LST composites, five exponential powers were applied to weights during the temporal aggregation process, resulting in five thresholds of best quality pixel promotion. It was found that there are significant differences between temporal composites that take into account the MODIS QC and the view angle and those that do not (obtained by means of a simple arithmetic mean with no weights applied), in terms of spatial distribution and density distribution of urban and rural LST. The differences were more distinctive in spring or daytime cases than in autumn or nighttime cases. The impact of the MODIS QC and the view angle on temporal composites was highest in the city center. Ten SUHI indicators were utilized. It was found that the impact on long-term SUHI intensity is weaker than on the spatial pattern of LST and that SUHI indicators are inconsistent.

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“…Section 4 focuses only on SatCORPS SST results because the validation and angular corrections differ from those used for LST. Validation of the LST and application of the theoretical model developed by Vinnikov et al (2012) comprise the main topics of Sect. 5.…”

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confidence: 99%

“…5. Coefficients for the Vinnikov et al (2012) model were determined empirically from near-simultaneous measurements covering a limited viewing range from a small collection of sites. Because those sites represent varied surface and climate types, the resulting coefficients could potentially serve as an effective initial step in the process of correcting LST for angular dependency.…”

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confidence: 99%

Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections

et al. 2017

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Abstract. Surface skin temperature (T s ) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve T s over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of T s over the diurnal cycle in non-polar regions, while polar T s retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed T s , along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly T s observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived T s data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, T s validation with established references is essential, as is proper evaluation of T s sensitivity to atmospheric correction source.This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based T s product that is derived using a single-channel technique. The resulting clearsky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve satellite LST retrievals. Application of the anisotropic correction yields reduced mean bias and improved precision of GOES-13 LST relative to independent Moderateresolution Imaging Spectroradiometer (MYD11_L2) LST and Atmospheric Radiation Measurement Program ground station measurements. It also significantly reduces intersatellite differences between LSTs retrieved simultaneously from two different imagers. The implementation of these universal corrections into the SatCORPS product can yield significant improvement in near-global-scale, near-realtime, satellite-based LST measurements. The immediate availability and broad coverage of these skin temperature observations should prove valuable to modelers and climate researchers looking for improved forecasts and better understanding of the global climate model.

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Angular anisotropy of satellite observations of land surface temperature

Cited by 80 publications

References 20 publications

Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels

Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels

Impact of MODIS Quality Control on Temporally Aggregated Urban Surface Temperature and Long-Term Surface Urban Heat Island Intensity

Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections

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