Diurnal Air Temperature Modeling Based on the Land Surface Temperature
Abstract
:1. Introduction
2. The Study Area
3. Data
- Ground based weather data: Ta data from 77 weather stations with three-hour time intervals were obtained from 1 January 2000 to 22 March 2017 from I.R. of the Iran Meteorological Organization (IRIMO). Along with air temperature, sky condition, and wind speed data are also available.
- Elevation data: ASTER-DEM with 30 m spatial resolution was obtained from NASA Reverb website.
- Land cover map: Land cover type of the fifth category from MODIS land cover products with 500 m spatial resolution (MCD12Q1) was downloaded from NASA Reverb website.
4. Methodology
4.1. Air Temperature DTC Model
4.2. LST DTC Model
4.3. Construction from LST DTC
5. Results
5.1. Estimation of the Air DTC Model Based on LST DTC Parameters
5.2. Accuracy of the Air DTC Model from Regressions
6. Discussion
7. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Parton, W.J.; Logan, J.A. A model for diurnal variation in soil and air temperature. Agric. Meteorol. 1981, 23, 205–216. [Google Scholar] [CrossRef]
- Gázquez, F.; Calaforra, J.M.; Fernández-Cortés, Á. Flash flood events recorded by air temperature changes in caves: A case study in Covadura Cave (Se Spain). J. Hydrol. 2016, 541, 136–145. [Google Scholar] [CrossRef]
- Bunker, A.; Wildenhain, J.; Vandenbergh, A.; Henschke, N.; Rocklöv, J.; Hajat, S.; Sauerborn, R. Effects of air temperature on climate-sensitive mortality and morbidity outcomes in the elderly; a systematic review and meta-analysis of epidemiological evidence. EBioMedicine 2016, 6, 258–268. [Google Scholar] [CrossRef] [PubMed]
- Deser, C.; Terray, L.; Phillips, A.S. Forced and internal components of winter air temperature trends over North America during the past 50 years: Mechanisms and implications. J. Clim. 2016, 29, 2237–2258. [Google Scholar] [CrossRef]
- Slini, T.; Papakostas, K. 30 years air temperature data analysis in Athens and Thessaloniki, Greece. In Energy, Transportation and Global Warming; Springer: Berlin, Germany, 2016; pp. 21–33. [Google Scholar]
- Sun, Y.-J.; Wang, J.-F.; Zhang, R.-H.; Gillies, R.; Xue, Y.; Bo, Y.-C. Air temperature retrieval from remote sensing data based on thermodynamics. Theor. Appl. Climatol. 2005, 80, 37–48. [Google Scholar] [CrossRef]
- Prince, S.D.; Goetz, S.J.; Dubayah, R.; Czajkowski, K.; Thawley, M. Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using advanced very high-resolution radiometer satellite observations: Comparison with field observations. J. Hydrol. 1998, 212, 230–249. [Google Scholar] [CrossRef]
- Zakšek, K.; Schroedter-Homscheidt, M. Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments. ISPRS J. Photogramm. Remote Sens. 2009, 64, 414–421. [Google Scholar] [CrossRef]
- Prihodko, L.; Goward, S.N. Estimation of air temperature from remotely sensed surface observations. Remote Sens. Environ. 1997, 60, 335–346. [Google Scholar] [CrossRef]
- Stisen, S.; Sandholt, I.; Nørgaard, A.; Fensholt, R.; Eklundh, L. Estimation of diurnal air temperature using MSG SEVIRI data in West Africa. Remote Sens. Environ. 2007, 110, 262–274. [Google Scholar] [CrossRef]
- Nieto, H.; Sandholt, I.; Aguado, I.; Chuvieco, E.; Stisen, S. Air temperature estimation with MSG-SEVIRI data: Calibration and validation of the TVX algorithm for the IBERIAN PENINSULA. Remote Sens. Environ. 2011, 115, 107–116. [Google Scholar] [CrossRef]
- Zhu, W.; Lű, A.; Jia, S. Estimation of daily maximum and minimum air temperature using MODIS land surface temperature products. Remote Sens. Environ. 2013, 130, 62–73. [Google Scholar] [CrossRef]
- Goetz, S.; Prince, S.D. Modelling terrestrial carbon exchange and storage: Evidence and implications of functional convergence in light-use efficiency. Adv. Ecol. Res. 1999, 28, 57–92. [Google Scholar]
- Florio, E.; Lele, S.; Chi Chang, Y.; Sterner, R.; Glass, G. Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature: A statistical approach. Int. J. Remote Sens. 2004, 25, 2979–2994. [Google Scholar] [CrossRef]
- Sandholt, I.; Rasmussen, K.; Andersen, J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sens. Environ. 2002, 79, 213–224. [Google Scholar] [CrossRef]
- Mostovoy, G.V.; King, R.L.; Reddy, K.R.; Kakani, V.G.; Filippova, M.G. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of MISSISSIPPI. GIsci. Remote Sens. 2006, 43, 78–110. [Google Scholar] [CrossRef]
- Vancutsem, C.; Ceccato, P.; Dinku, T.; Connor, S.J. Evaluation of modis land surface temperature data to estimate air temperature in different ecosystems over Africa. Remote Sens. Environ. 2010, 114, 449–465. [Google Scholar] [CrossRef]
- Benali, A.; Carvalho, A.; Nunes, J.; Carvalhais, N.; Santos, A. Estimating air surface temperature in Portugal using MODIS LST data. Remote Sens. Environ. 2012, 124, 108–121. [Google Scholar] [CrossRef]
- Zhu, W.; Lű, A.; Jia, S.; Yan, J.; Mahmood, R. Retrievals of all-weather daytime air temperature from modis products. Remote Sens. Environ. 2017, 189, 152–163. [Google Scholar] [CrossRef]
- Cresswell, M.; Morse, A.; Thomson, M.; Connor, S. Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model. Int. J. Remote Sens. 1999, 20, 1125–1132. [Google Scholar] [CrossRef]
- Emamifar, S.; Rahimikhoob, A.; Noroozi, A.A. Daily mean air temperature estimation from MODIS land surface temperature products based on M5 model tree. Int. J. Climatol. 2013, 33, 3174–3181. [Google Scholar] [CrossRef]
- Fu, G.; Shen, Z.; Zhang, X.; Shi, P.; Zhang, Y.; Wu, J. Estimating air temperature of an alpine meadow on the northern tibetan plateau using MODIS land surface temperature. Acta Ecol. Sin. 2011, 31, 8–13. [Google Scholar] [CrossRef]
- Jang, J.-D.; Viau, A.; Anctil, F. Neural network estimation of air temperatures from AVHRR data. Int. J. Remote Sens. 2004, 25, 4541–4554. [Google Scholar] [CrossRef]
- Kim, D.-Y.; Han, K.-S. Remotely sensed retrieval of midday air temperature considering atmospheric and surface moisture conditions. Int. J. Remote Sens. 2013, 34, 247–263. [Google Scholar] [CrossRef]
- Lin, S.; Moore, N.J.; Messina, J.P.; DeVisser, M.H.; Wu, J. Evaluation of estimating daily maximum and minimum air temperature with modis data in east africa. Int. J. Appl. Earth Obs. Geoinf. 2012, 18, 128–140. [Google Scholar] [CrossRef]
- Moser, G.; De Martino, M.; Serpico, S.B. Estimation of air surface temperature from remote sensing images and pixelwise modeling of the estimation uncertainty through support vector machines. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 2015, 8, 332–349. [Google Scholar] [CrossRef]
- Vogt, J.V.; Viau, A.A.; Paquet, F. Mapping regional air temperature fields using satellite-derived surface skin temperatures. Int. J. Climatol. 1997, 17, 1559–1579. [Google Scholar] [CrossRef]
- Xu, Y.; Qin, Z.; Shen, Y. Study on the estimation of near-surface air temperature from MODIS data by statistical methods. Int. J. Remote Sens. 2012, 33, 7629–7643. [Google Scholar] [CrossRef]
- Yan, H.; Zhang, J.; Hou, Y.; He, Y. Estimation of air temperature from MODIS data in east China. Int. J. Remote Sens. 2009, 30, 6261–6275. [Google Scholar] [CrossRef]
- Zhang, W.; Huang, Y.; Yu, Y.; Sun, W. Empirical models for estimating daily maximum, minimum and mean air temperatures with MODIS land surface temperatures. Int. J. Remote Sens. 2011, 32, 9415–9440. [Google Scholar] [CrossRef]
- Xu, Y.; Knudby, A.; Ho, H.C. Estimating daily maximum air temperature from MODIS in British Columbia, Canada. Int. J. Remote Sens. 2014, 35, 8108–8121. [Google Scholar] [CrossRef]
- Duan, S.-B.; Li, Z.-L.; Wang, N.; Wu, H.; Tang, B.-H. Evaluation of six land-surface diurnal temperature cycle models using clear-sky in situ and satellite data. Remote Sens. Environ. 2012, 124, 15–25. [Google Scholar] [CrossRef]
- Jin, M.; Dickinson, R.E. Interpolation of surface radiative temperature measured from polar orbiting satellites to a diurnal cycle: 1. without clouds. J. Geophys. Res. Atmos. 1999, 104, 2105–2116. [Google Scholar] [CrossRef]
- Sun, D.; Pinker, R.T.; Kafatos, M. Diurnal temperature range over the United States: A satellite view. Geophys. Res. Lett. 2006, 33. [Google Scholar] [CrossRef]
- Alavipanah, S.K.; Weng, Q.; Gholamnia, M.; Khandan, R. An analysis of the discrepancies between MODIS and INSAT-3D LSTS in high temperatures. Remote Sens. 2017, 9, 347. [Google Scholar] [CrossRef]
- Inamdar, A.K.; French, A.; Hook, S.; Vaughan, G.; Luckett, W. Land surface temperature retrieval at high spatial and temporal resolutions over the southwestern United States. J. Geophys. Res. Atmos. 2008, 113. [Google Scholar] [CrossRef]
- EPSA. INSAT-3D Algorithm Theoretical Basis Document; Space Applications Centre, Government of India: Ahmedabad, India, 2015.
- Duffie, J.A.; Beckman, W.A. Solar Engineering of Thermal Processes; Wiley: New York, NY, USA, 1980. [Google Scholar]
- ELAGIB, N.A.; ALVI, S.H.; MANSELL, M.G. Day-length and extraterrestrial radiation for Sudan: A comparative study. Int. Sol. Energy 1999, 20, 93–109. [Google Scholar] [CrossRef]
- Göttsche, F.-M.; Olesen, F.S. Modelling of diurnal cycles of brightness temperature extracted from Meteosat data. Remote Sens. Environ. 2001, 76, 337–348. [Google Scholar] [CrossRef]
- Schädlich, S.; Göttsche, F.; Olesen, F.-S. Influence of land surface parameters and atmosphere on METEOSAT brightness temperatures and generation of land surface temperature maps by temporally and spatially interpolating atmospheric correction. Remote Sens. Environ. 2001, 75, 39–46. [Google Scholar] [CrossRef]
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gholamnia, M.; Alavipanah, S.K.; Darvishi Boloorani, A.; Hamzeh, S.; Kiavarz, M. Diurnal Air Temperature Modeling Based on the Land Surface Temperature. Remote Sens. 2017, 9, 915. https://doi.org/10.3390/rs9090915
Gholamnia M, Alavipanah SK, Darvishi Boloorani A, Hamzeh S, Kiavarz M. Diurnal Air Temperature Modeling Based on the Land Surface Temperature. Remote Sensing. 2017; 9(9):915. https://doi.org/10.3390/rs9090915
Chicago/Turabian StyleGholamnia, Mehdi, Seyed Kazem Alavipanah, Ali Darvishi Boloorani, Saeid Hamzeh, and Majid Kiavarz. 2017. "Diurnal Air Temperature Modeling Based on the Land Surface Temperature" Remote Sensing 9, no. 9: 915. https://doi.org/10.3390/rs9090915