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

2019 ◽  
Vol 11 (24) ◽  
pp. 2889 ◽  
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.

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

2013 ◽  
Vol 118 (1-2) ◽  
pp. 81-92 ◽  
Author(s):  
Hao Sun ◽  
Yunhao Chen ◽  
Adu Gong ◽  
Xiang Zhao ◽  
Wenfeng Zhan ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Surface Temperatures ◽  
Land Surface Temperatures

scholarly journals Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica

2014 ◽  
Vol 8 (1) ◽  
pp. 55-84 ◽  
Author(s):  
H. Fréville ◽  
E. Brun ◽  
G. Picard ◽  
N. Tatarinova ◽  
L. Arnaud ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Data Set ◽  
Warm Bias ◽  
Clear Sky ◽  
Surface Temperatures ◽  
Stable Conditions ◽  
Land Surface Temperatures ◽  
Sky Conditions

Abstract. MODIS land surface temperatures in Antarctica were processed in order to produce a gridded data set at 25 km resolution, spanning the period 2000–2011 at an hourly time-step. The AQUA and TERRA orbits and MODIS swath width, combined with frequent clear-sky conditions, lead to very high availability of quality-controlled observations: on average, hourly data are available 14 h per day at the grid points around the South Pole and more than 9 over a large area of the Antarctic Plateau. Processed MODIS land surface temperatures, referred to hereinafter as MODIS Ts, were compared with in situ hourly measurements of surface temperature collected over the entire year 2009 by 7 stations from the BSRN and AWS networks. In spite of an occasional failure in the detection of clouds, MODIS Ts exhibit a good performance, with a bias ranging from −1.8 to 0.1 °C and errors ranging from 2.2 to 4.8 °C root mean square at the 5 stations located on the plateau. These results show that MODIS Ts can be used as a precise and accurate reference to test other surface temperature data sets. Here, we evaluate the performance of surface temperature in the ERA-Interim reanalysis. During conditions detected as cloud-free by MODIS, ERA-Interim shows a widespread warm bias in Antarctica in every season, ranging from +3 to +6 °C on the plateau. This confirms a recent study which showed that the largest discrepancies in 2 m air temperature between ERA-Interim and the HadCRUT4 data set occur in Antarctica. A comparison with in situ surface temperature shows that this bias is not strictly limited to clear-sky conditions. A detailed comparison with stand-alone simulations by the Crocus snowpack model, forced by ERA-Interim, and with the ERA-Interim/land simulations, shows that the warm bias may be due primarily to an overestimation of the surface turbulent fluxes in very stable conditions. Numerical experiments with Crocus show this is likely due to an overestimation of the surface exchange coefficients under very stable conditions.

scholarly journals Evaluation of “all weather” microwave-derived land surface temperatures with in situ CEOP measurements

2011 ◽  
Vol 116 (D23) ◽  
pp. n/a-n/a ◽  
Author(s):  
J. Catherinot ◽  
C. Prigent ◽  
R. Maurer ◽  
F. Papa ◽  
C. Jiménez ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Temperatures ◽  
Land Surface Temperatures

scholarly journals Assessment of High Resolution Air Temperature Fields at Rocky Mountain National Park by Combining Scarce Point Measurements with Elevation and Remote Sensing Data

2020 ◽  
Vol 13 (1) ◽  
pp. 113
Author(s):  
Antonio-Juan Collados-Lara ◽  
Steven R. Fassnacht ◽  
Eulogio Pardo-Igúzquiza ◽  
David Pulido-Velazquez
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Air Temperature ◽  
Land Surface ◽  
National Park ◽  
Rocky Mountain ◽  
Rocky Mountain National Park ◽  
Temperature Fields ◽  
Lapse Rate ◽  
Validation Experiment

There is necessity of considering air temperature to simulate the hydrology and management within water resources systems. In many cases, a big issue is considering the scarcity of data due to poor accessibility and limited funds. This paper proposes a methodology to obtain high resolution air temperature fields by combining scarce point measurements with elevation data and land surface temperature (LST) data from remote sensing. The available station data (SNOTEL stations) are sparse at Rocky Mountain National Park, necessitating the inclusion of correlated and well-sampled variables to assess the spatial variability of air temperature. Different geostatistical approaches and weighted solutions thereof were employed to obtain air temperature fields. These estimates were compared with two relatively direct solutions, the LST (MODIS) and a lapse rate-based interpolation technique. The methodology was evaluated using data from different seasons. The performance of the techniques was assessed through a cross validation experiment. In both cases, the weighted kriging with external drift solution (considering LST and elevation) showed the best results, with a mean squared error of 3.7 and 3.6 °C2 for the application and validation, respectively.

Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh

2020 ◽  
Vol 18 ◽  
pp. 100314 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Md. Shahinoor Rahman ◽  
Abdullah-Al- Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Muhaiminul Islam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Surface Temperatures ◽  
Land Surface Temperatures
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