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

The Tibetan Plateau has been undergoing accelerated warming over recent decades, and is considered an indicator for broader global warming phenomena. However, our understanding of warming rates with elevation in complex mountain regions is incomplete. The most serious concern is the lack of high-quality near-surface air temperature (Tair) datasets in these areas. To address this knowledge gap, we developed an automated mapping framework for the estimation of seamless daily minimum and maximum Land Surface Temperatures (LSTs) for the Tibetan Plateau from the existing MODIS LST products for a long period of time (i.e., 2002–present). Specific machine learning methods were developed and linked with target-oriented validation and then applied to convert LST to Tair. Spatial variables in retrieving Tair, such as solar radiation and vegetation indices, were used in estimation of Tair, whereas MODIS LST products were mainly focused on temporal variation in surface air temperature. We validated our process using independent Tair products, revealing more reliable estimates on Tair; the R2 and RMSE at monthly scales generally fell in the range of 0.9–0.95 and 1–2 °C. Using these continuous and consistent Tair datasets, we found temperature increases in the elevation range between 2000–3000 m and 4000–5000 m, whereas the elevation interval at 6000–7000 m exhibits a cooling trend. The developed datasets, findings and methodology contribute to global studies on accelerated warming.

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Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

Journal of Applied Meteorology and Climatology ◽

10.1175/jam2561.1 ◽

2007 ◽

Vol 46 (10) ◽

pp. 1587-1605 ◽

Cited By ~ 37

Author(s):

J-F. Miao ◽

D. Chen ◽

K. Borne

Keyword(s):

Soil Moisture ◽

Air Temperature ◽

Land Surface ◽

Model Performance ◽

Surface Air Temperature ◽

Near Surface ◽

Surface Models ◽

Urban Heat ◽

Soil Moisture Initialization ◽

Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

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Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-7665-2015 ◽

2015 ◽

Vol 12 (8) ◽

pp. 7665-7687 ◽

Cited By ~ 2

Author(s):

C. L. Pérez Díaz ◽

T. Lakhankar ◽

P. Romanov ◽

J. Muñoz ◽

R. Khanbilvardi ◽

...

Keyword(s):

Surface Temperature ◽

Skin Temperature ◽

Air Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Hydrological Cycle ◽

Critical Role ◽

Surface Air Temperature ◽

Balance Model ◽

Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

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Quantifying the Congruence between Air and Land Surface Temperatures for Various Climatic and Elevation Zones of Western Himalaya

Remote Sensing ◽

10.3390/rs11242889 ◽

2019 ◽

Vol 11 (24) ◽

pp. 2889 ◽

Cited By ~ 3

Author(s):

Shaktiman Singh ◽

Anshuman Bhardwaj ◽

Atar Singh ◽

Lydia Sam ◽

Mayank Shekhar ◽

...

Keyword(s):

Air Temperature ◽

Land Surface ◽

Extreme Environments ◽

Western Himalaya ◽

In Situ Monitoring ◽

Lapse Rate ◽

Similar Data ◽

Surface Temperatures ◽

Land Surface Temperatures

The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (Ta) observations require intense logistic and financial investments, making it sparse and fragmented particularly in remote and extreme environments. The temperatures in Himalaya are controlled by a complex system driven by topography, seasons, and cryosphere which further makes it difficult to record or predict its spatial heterogeneity. In this regard, finding a way to fill the observational spatiotemporal gaps in data becomes more crucial. Here, we show the comparison of Ta recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (Ts) recorded by Moderate Resolution Imagining Spectroradiometer (MODIS) Aqua and Terra satellites in cloud-free conditions. We found remarkable seasonal and spatial trends in the Ta vs. Ts relationship: (i) Ts are strongly correlated with Ta (R2 = 0.77, root mean square difference (RMSD) = 5.9 °C, n = 11,101 at daily scale and R2 = 0.80, RMSD = 5.7 °C, n = 3552 at 8-day scale); (ii) in general, the RMSD is lower for the winter months in comparison to summer months for all the stations, (iii) the RMSD is directly proportional to the elevations; (iv) the RMSD is inversely proportional to the annual precipitation. Our results demonstrate the statistically strong and previously unreported Ta vs. Ts relationship and spatial and seasonal variations in its intensity at daily resolution for the Western Himalaya. We anticipate that our results will provide the scientists in Himalaya or similar data-deficient extreme environments with an option to use freely available remotely observed Ts products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting Ta by Ts as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived Ts in place of discrete in situ Ta extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.

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Estimating mean air temperature using MODIS day and night land surface temperatures

Theoretical and Applied Climatology ◽

10.1007/s00704-013-1033-7 ◽

2013 ◽

Vol 118 (1-2) ◽

pp. 81-92 ◽

Cited By ~ 21

Author(s):

Hao Sun ◽

Yunhao Chen ◽

Adu Gong ◽

Xiang Zhao ◽

Wenfeng Zhan ◽

...

Keyword(s):

Air Temperature ◽

Land Surface ◽

Surface Temperatures ◽

Land Surface Temperatures

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Mapping of Daily Mean Air Temperature in Agricultural Regions Using Daytime and Nighttime Land Surface Temperatures Derived from TERRA and AQUA MODIS Data

Remote Sensing ◽

10.3390/rs70708728 ◽

2015 ◽

Vol 7 (7) ◽

pp. 8728-8756 ◽

Cited By ~ 32

Author(s):

Ran Huang ◽

Chao Zhang ◽

Jianxi Huang ◽

Dehai Zhu ◽

Limin Wang ◽

...

Keyword(s):

Air Temperature ◽

Land Surface ◽

Modis Data ◽

Surface Temperatures ◽

Land Surface Temperatures ◽

Agricultural Regions

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Recent Trends in Land Surface Temperature on the Tibetan Plateau

Journal of Climate ◽

10.1175/jcli3811.1 ◽

2006 ◽

Vol 19 (12) ◽

pp. 2995-3003 ◽

Cited By ~ 29

Author(s):

Yuichiro Oku ◽

Hirohiko Ishikawa ◽

Shigenori Haginoya ◽

Yaoming Ma

Keyword(s):

Tibetan Plateau ◽

Surface Temperature ◽

Air Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Precipitation Amount ◽

Surface Air Temperature ◽

The Tibetan Plateau ◽

Near Surface ◽

Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

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Study on Urban Thermal Environment based on Diurnal Temperature Range

10.5194/egusphere-egu2020-12971 ◽

2020 ◽

Author(s):

Zheng Guo ◽

Miaomiao Cheng

Keyword(s):

Surface Temperature ◽

Air Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Thermal Environment ◽

Surface Air Temperature ◽

Heat Island ◽

Near Surface ◽

Diurnal Range ◽

Urban Thermal Environment

Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter, which is a very important factor in the field of the urban thermal environmental. Nowadays, the research of urban thermal environment mainly focused on surface heat island and canopy heat island.Based on analysis of the current status of city thermal environment. Firstly, a method was proposed to obtain near surface air temperature diurnal range in this study, difference of land surface temperature between day and night were introduced into the improved temperature vegetation index feature space based on remote sensing data. Secondly, compared with the district administrative division, we analyzed the spatial and temporal distribution characteristics of the diurnal range of land surface temperature and near surface air temperature.The conclusions of this study are as follows:1 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing were fluctuating upward. The rising trend of the near surface air temperature diurnal range was more significant than land surface temperature diurnal range. In addition, the rise and decline of land surface temperature and near surface air temperature diurnal range in different districts were different. In the six city districts, the land surface temperature and near surface air temperature diurnal range in the six areas of the city were mainly downward. The decline trend of near surface air temperature diurnal range was more significant than land surface temperature diurnal range.2 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing with similar characteristics in spatial distribution, with higher distribution land surface temperature and near surface air temperature diurnal range in urban area and with lower distribution of land surface temperature and near surface air temperature diurnal range in the Northwest Mountainous area and the area of Miyun reservoir.

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