A spatiotemporal analysis of the relationship between near‐surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series

Good, Elizabeth; Ghent, Darren; Bulgin, Claire E.; Remedios, J. J.

doi:10.1002/2017jd026880

Cited by 131 publications

(93 citation statements)

References 92 publications

(176 reference statements)

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“…Our result is also consistent with the study by Good et al (2017), who showed the stronger coupling between global surface and air temperature at their minima. They attributed the weaker daytime coupling of the two temperatures to the influence of insolation.…”

Section: Discussionsupporting

confidence: 94%

Do Surface and Air Temperatures Contain Similar Imprints of Evaporative Conditions?

Panwar

Kleidon

Renner

2019

Geophysical Research Letters

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Generally, surface and air temperatures seem closely related but we show that they respond differently to evaporative conditions. We evaluate the temperature increase in response to solar radiation for different evaporative fractions, using observations from the Southern Great Plains. The warming rate of air temperature decreases only by 1.7 × 10−3 K/(W m−2) from dry to moist conditions compared to a stronger reduction by 14 × 10−3 K/(W m−2) for surface temperature. The weaker response of air temperature to evaporative fraction is explained by the larger growth of boundary layer on drier days, which suppresses the warming of air. Estimates based on this explanation reproduce the warming rate of air temperature in observations. Our results show that diurnal variations of surface temperatures contain imprints of evapotranspiration while air temperatures do not. These findings appear important to be considered when using, analyzing, or interpreting temperature data in studies dealing with climate change, hydrology, or land‐atmosphere interactions.

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Section: Discussionsupporting

confidence: 94%

Do Surface and Air Temperatures Contain Similar Imprints of Evaporative Conditions?

Panwar

Kleidon

Renner

2019

Geophysical Research Letters

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“…Generally, the magnitude of nighttime T surf and T air is very close (differing by <5°C), regardless of land-cover type (Good et al 2017). Generally, the magnitude of nighttime T surf and T air is very close (differing by <5°C), regardless of land-cover type (Good et al 2017).…”

Section: Introductionmentioning

confidence: 96%

“…However, relationships among these factors are not straightforward (Good 2016, Good et al 2017, Jin and Dickinson 2010, Lee et al 2011, Mildrexler et al 2011. Differences between T surf and T air may be driven by land cover (especially, vegetation cover and surface roughness) and atmospheric properties (e.g., cloud cover, water vapor content, and surface boundary layer processes), in addition to factors such as soil moisture, elevation, net radiation, and latitude.…”

Section: Introductionmentioning

confidence: 99%

“…Differences between T surf and T air may be driven by land cover (especially, vegetation cover and surface roughness) and atmospheric properties (e.g., cloud cover, water vapor content, and surface boundary layer processes), in addition to factors such as soil moisture, elevation, net radiation, and latitude. However, relationships among these factors are not straightforward (Good 2016, Good et al 2017, Jin and Dickinson 2010, Lee et al 2011, Mildrexler et al 2011.…”

Section: Introductionmentioning

confidence: 99%

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Thermal imaging in plant and ecosystem ecology: applications and challenges

et al. 2019

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Temperature is a primary environmental control on ecological systems and processes at a range of spatial and temporal scales. The surface temperature of organisms is often more relevant for ecological processes than air temperature, which is much more commonly measured. Surface temperature influences-and is influenced by-a range of biological, physical, and chemical processes, providing a unique view of temperature effects on ecosystem function. Furthermore, surface temperatures vary markedly over a range of temporal and spatial scales and may diverge from air temperature by 40°C or more. Surface temperature measurements have been challenging due to sensor and computational limitations but are now feasible at high spatial and temporal resolutions using thermal imaging. Thus, significant advances in our understanding of plant and ecosystem thermal regimes and their functional consequences are now possible. Thermal measurements may be used to address many ecological questions, such as the thermal controls on plant and ecosystem metabolism and the impact of heat waves and drought. Further advances in this area will require interdisciplinary collaborations among practitioners in fields ranging from physiology to ecosystem ecology to remote sensing and geospatial analysis. In this overview, we demonstrate the feasibility, utility, and potential of thermal imaging for measuring vegetation surface temperatures across a range of scales and from measurement, analysis, and synthesis perspectives.

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“…The differences between ATSR‐2 and AATSR in the Arctic is around 1 K (Ghent et al, ). Future work should include harmonization to reduce differences between the sensors, following studies such as Good et al (), Merchant et al (), and Merchant et al (). As noted in sections and , land sea masking and sea ice masking are different between the SST L2P and GT LST data sets providing the input T s for AAST.…”

Section: Discussionmentioning

confidence: 99%

Toward a Combined Surface Temperature Data Set for the Arctic From the Along‐Track Scanning Radiometers

et al. 2019

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Surface temperature data sets for, or including, the Arctic have been derived from various thermal infrared sensors. However, a combined, all surface temperature data set for the Arctic has not been generated previously. Here we present the first combined land, ocean, and ice surface temperature data set for the Arctic produced from Along‐Track Scanning Radiometer ‐ 2 and the Advanced Along‐Track Scanning Radiometer satellite sensors: the Along‐Track Scanning Radiometer Arctic combined Surface Temperature data set. Separate products, produced independently for each sensor and containing quantified uncertainties, together cover the period August 1995 to April 2012. Product validation, utilizing a more extensive in situ database than previous studies, shows that Along‐Track Scanning Radiometer Arctic combined Surface Temperature surface temperatures generally agree with in situ data and are similar to previous validation of input surface temperature retrievals. Biases range from −1.74 to 0.23 K over open ocean, sea ice, snow over land, and the Greenland ice sheet with higher variability over snow/ice. However, there are noticeable outliers in the validation results, particularly over Arctic land in boreal summer for Along‐Track Scanning Radiometer ‐ 2, which are likely due to cloud contamination resulting from a climatologically static snow field being used for that sensor. This study suggests that the Along‐Track Scanning Radiometer Arctic combined Surface Temperature data set presented here is a useful tool for assessment of models in the Arctic. Further work would have clear benefits including improvements to snow cover and cloud clearing to achieve a fully consistently processed, climate quality combined surface temperature data set for the Arctic region.

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A spatiotemporal analysis of the relationship between near‐surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series

Cited by 131 publications

References 92 publications

Do Surface and Air Temperatures Contain Similar Imprints of Evaporative Conditions?

Do Surface and Air Temperatures Contain Similar Imprints of Evaporative Conditions?

Thermal imaging in plant and ecosystem ecology: applications and challenges

Toward a Combined Surface Temperature Data Set for the Arctic From the Along‐Track Scanning Radiometers

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