Abstract
Accurate estimates of long-term land surface temperature (Ts) and near-surface air temperature (Ta) at finer spatio-temporal resolutions are crucial for surface energy budget studies, for environmental applications, for land surface model data assimilation, and for climate change assessment and its associated impacts. The Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Aqua satellite provide a unique opportunity to estimate both temperatures twice daily at the global scale. In this study, differences between Ta and Ts were assessed locally over regions of North America from 2009 to 2013 using ground-based observations covering a wide range of geographical, topographical, and land cover types. The differences between Ta and Ts during non-precipitating conditions are generally 2–3 times larger than precipitating conditions. However, these differences show noticeable diurnal and seasonal variations. The differences between Ta and Ts were also investigated at the global scale using the AIRS estimates under clear-sky conditions for the period 2003–2015. The tropical regions showed about 5–20 °C warmer Ts than Ta during the day-time, whereas opposite characteristics (about 2–5 °C cooler Ts than Ta) are found over most parts of the globe during the night-time. Additionally, Ts estimates from the AIRS and the MODIS sensors were inter-compared. Although large-scale features of Ts were essentially similar for both sensors, considerable differences in magnitudes were observed (> 6 °C over mountainous regions). Finally, Ta and Ts estimates from the AIRS and MODIS sensors were validated against ground-based observations for the period of 2009–2013. The error characteristics notably varied with ground stations and no clear evidence of their dependency on land cover types or elevation was detected. However, the MODIS-derived Ts estimates generally showed larger biases and higher errors compared to the AIRS-derived estimates. The biases and errors increased steadily when the spatial resolution of the MODIS estimates changed from finer to coarser. These results suggest that representativeness error should be properly accounted for when validating satellite-based temperature estimates with point observations.
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References
Ayanlade A (2016) Seasonality in the daytime and night-time intensity of land surface temperature in a tropical city area. Sci Total Environ 557–558:415–424. https://doi.org/10.1016/j.scitotenv.2016.03.027
Bell JE, Palecki MA, Baker CB, Collins WG, Lawrimore JH, Leeper RD, Hall ME, Kochendorfer J, Meyers TP, Wilson T, Diamond HJ (2013) U.S. Climate Reference Network soil moisture and temperature observations. J Hydrometeorol 14:977–988. https://doi.org/10.1175/JHM-D-12-0146.1
Bechtel B (2015) A new global climatology of annual land surface temperature. Remote Sens 7(3):2850–2870. https://doi.org/10.3390/rs70302850
Blackwell WJ (2012) Neural network Jacobian analysis for high-resolution profiling of the atmosphere. EURASIP J Adv Signal Process 71:1–11. https://doi.org/10.1186/1687-6180-2012-71
Boylan P, Wang J, Cohn SA, Fetzer E, Maddy ES, Wong S (2015) Validation of AIRS version 6 temperature profiles and surface-based inversions over Antarctica using Concordiasi dropsonde data. J Geophys Res - Atmos 120:992–1007. https://doi.org/10.1002/2014JD022551
Broxton PD, Zeng X, Sulla-Menashe D, Troch PA (2014) A global land cover climatology using MODIS data. J Appl Meteorol Climatol 53:1593–1605. https://doi.org/10.1175/JAMC-D-13-0270.1
Cheval S, Dumitrescu A (2017) Rapid daily and sub-daily temperature variations in an urban environment. Clim Res 73:233–246. https://doi.org/10.3354/cr01481
Diamond HJ, Karl TR, Palecki MA, Baker CB, Bell JE, Leeper RD, Easterling DR, Lawrimore JH, Meyers TP, Helfert MR, Goodge G, Thorne PW (2013) U.S. Climate Reference Network after one decade of operations: status and assessment. Bull Amer Meteorol Soc 94:489–498. https://doi.org/10.1175/BAMS-D-12-00170.1
Didari S, Norouzi H, Zand-Parsa S, Khanbilvardi R (2017) Estimation of daily minimum land surface air temperature using MODIS data in southern Iran. Theor Appl Climatol 130:1149–1161. https://doi.org/10.1007/s00704-016-1945-0
Fabrizi R, Bonafoni S, Biondi R (2010) Satellite and ground-based sensors for the urban heat island analysis in the city of Rome. Remote Sens 2(5):1400–1415. https://doi.org/10.3390/rs2051400
Gallo K, Hale R, Tarpley D, Yu Y (2011) Evaluation of the relationship between air and land surface temperature under clear- and cloudy-sky conditions. J Appl Meteorol Climatol 50:767–775. https://doi.org/10.1175/2010JAMC2460.1
Good EJ (2016) An in situ-based analysis of the relationship between land surface “skin” and screen-level air temperatures. J Geophys Res - Atmos 121:8801–8819. https://doi.org/10.1002/2016JD025318
Houser PR, De Lannoy GJ, Walker JP (2010) Land surface data assimilation. In: Lahoz W, Khattatov B, Menard R (eds) Data assimilation. Springer, Berlin, Heidelberg, pp 549–597. https://doi.org/10.1007/978-3-540-74703-1_21.
Jang K, Kang S, Kimball JS, Hong SY (2014) Retrievals of all-weather daily air temperature using MODIS and AMSR-E data. Remote Sens 6(9):8387–8404. https://doi.org/10.3390/rs6098387
Kang H-J, Yoo J-M, Jeong M-J, Won Y-I (2015) Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only. Atmos Meas Tech 8:4025–4041. https://doi.org/10.5194/amt-8-4025-2015
Lee Y-R, Yoo J-M, Jeong M-J, Won Y-I, Hearty T, Shin D-B (2013) Comparison between MODIS and AIRS/AMSU satellite-derived surface skin temperatures. Atmos Meas Tech 6:445–455. https://doi.org/10.5194/amt-6-455-2013.
Liu W, Chen S, Jiang H, Wang C, Li D (2017) Spatiotemporal analysis of MODIS land surface temperature with in situ meteorological observations and ERA-interim reanalysis: the option of model calibration. IEEE J Selected Topics Appl Earth Obs Remote Sens 10:1357–1371. https://doi.org/10.1109/JSTARS.2016.2645859
Mazdiyasni O, AghaKouchak A (2015) Substantial increase in concurrent droughts and heatwaves in the United States. Proc Nat Acad Sci 112:11484–11489. https://doi.org/10.1073/pnas.1422945112
Moncet J-L, Liang P, Lipton AE, Galantowicz JF, Prigent C (2011) Discrepancies between MODIS and ISCCP land surface temperature products analyzed with microwave measurements. J Geophys Res 116:D21105. https://doi.org/10.1029/2010JD015432.
Noi PT, Kappas M, Degener J (2016) Estimating daily maximum and minimum land air surface temperature using MODIS land surface temperature data and ground truth data in northern Vietnam. Remote Sens 8(12):1002. https://doi.org/10.3390/rs8121002
Norouzi H, Temimi M, Rossow W, Pearl C, Azarderakhsh M, Khanbilvardi R (2011) The sensitivity of land surface emissivity estimates from AMSR-E at C and X bands to surface properties. Hydrol Earth Syst Sci 15:3577–3589. https://doi.org/10.5194/hess-15-3577-2011
Norouzi H, Temimi M, AghaKouchak A, Azarderakhsh M, Khanbilvardi R, Shields G, Tesfagiorgis K (2015) Inferring land surface parameters from the diurnal variability of microwave and infrared temperatures. Phys Chem Earth 83–84:28–35. https://doi.org/10.1016/j.pce.2015.01.007
Oyler JW, Dobrowski SZ, Holden ZA, Running SW (2016) Remotely sensed land skin temperature as a spatial predictor of air temperature across the conterminous United States. J Appl Meteorol Climatol 55:1441–1457. https://doi.org/10.1175/JAMC-D-15-0276.1
Parkinson CL (2013) Summarizing the first ten years of NASA’s Aqua mission. IEEE J Selected Topics Appl Earth Obs Remote Sens 6:1179–1188. https://doi.org/10.1109/JSTARS.2013.2239608
Prakash S, Norouzi H, Azarderakhsh M, Blake R, Tesfagiorgis K (2016) Global land surface emissivity estimation from AMSR2 observations. IEEE Geosci Remote Sens Lett 13:1270–1274. https://doi.org/10.1109/LGRS.2016.2581140
Prakash S, Norouzi H, Azarderakhsh M, Blake R, Khanbilvardi R (2017) Potential of satellite-based land emissivity estimates for the detection of high-latitude freeze and thaw states. Geophys Res Lett 44:2336–2342. https://doi.org/10.1002/2017GL072560
Prakash S, Norouzi H, Azarderakhsh M, Blake R, Prigent C, Khanbilvardi R (2018) Estimation of consistent global microwave land surface emissivity from AMSR-E and AMSR2 observations. J Appl Meteorol Climatol 57:907–919. https://doi.org/10.1175/JAMC-D-17-0213.1
Prigent C, Jimenez C, Aires F (2016) Towards all weather, long record, and real-time land surface temperature retrievals from microwave satellite observations. J Geophys Res - Atmos 121:5699–5717. https://doi.org/10.1002/2015JD024402
Rahmstorf S, Foster G, Cahill N (2017) Global temperature evolution: recent trends and some pitfalls. Environ Res Lett 12:054001. https://doi.org/10.1088/1748-9326/aa6825
Ramamurthy P, Sangobanwo M (2016) Inter-annual variability in urban heat island intensity over 10 major cities in the United States. Sustainable Cities and Society 26:65–75. https://doi.org/10.1016/j.scs.2016.05.012
Ruzmaikin A, Aumann HH, Lee J, Susskind J (2017) Diurnal cycle variability of surface temperature inferred from AIRS data. J Geophys Res - Atmos 122:10928–20938. https://doi.org/10.1002/2016JD026265
Shati F, Prakash S, Norouzi H, Blake R (2018) Assessment of differences between near-surface air and soil temperatures for reliable detection of high-latitude freeze and thaw states. Cold Reg Sci Technol 145:86–92. https://doi.org/10.1016/j.coldregions.2017.10.007
Sheng Y, Liu X, Yang X, Xin Q, Deng C, Li X (2017) Quantifying the spatial and temporal relationship between air and land surface temperatures of different land-cover types in southeastern China. Int J Remote Sens 38:1114–1136. https://doi.org/10.1080/01431161.2017.1280629
Stephens GL, L’Ecuyer T (2015) The Earth’s energy balance. Atmos Res 166:195–203. https://doi.org/10.1016/j.atmosres.2015.06.024
Susskind J, Blaisdell JM, Iredell L (2014) Improved methodology for surface and atmospheric soundings, error estimates, and quality control procedures: the atmospheric infrared sounder science team version-6 retrieval algorithm. J Appl Remote Sens 8:084994. https://doi.org/10.1117/1.JRS.8.084994
Urban M, Eberle J, Huttich C, Schmullius C, Herold M (2013) Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the Pan-Arctic scale. Remote Sens 5:2348–2367. https://doi.org/10.3390/rs5052348
Wan Z (2014) New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote Sens Environ 140:36–45. https://doi.org/10.1016/j.rse.2013.08.027
Yang YZ, Cai WH, Yang J (2017) Evaluation of MODIS land surface temperature data to estimate near-surface air temperature in Northeast China. Remote Sens 9(5):410. https://doi.org/10.3390/rs9050410
Zhou C, Wang K (2016) Land surface temperature over global deserts: mean, variability, and trends. J Geophys Res - Atmos 121:14344–14357. https://doi.org/10.1002/2016JD025410
Acknowledgements
The authors would like to thank the editor and anonymous reviewers for their constructive comments. The statements contained within the manuscript are not the opinions of the funding agency or the US government; they reflect the authors’ opinions only. MODIS/Aqua land surface temperature data obtained from NASA EOSDID LP DAAC (https://lpdaac.usgs.gov/), Aqua/AIRS data products obtained from the GES DISC (https://disc.gsfc.nasa.gov/), USCRN observations obtained from the NOAA National Centers for Environmental Information (https://www.ncdc.noaa.gov/crn/), and MODIS-based 0.5 km global land cover climatology obtained from the USGS Land Cover Institute (https://landcover.usgs.gov/) are thankfully acknowledged.
Funding
This study was supported by the National Science Foundation (NSF) Research Experiences for Undergraduates (REU) under Grant 1560050 and by the Center for Remote Sensing and Earth System Sciences at the New York City College of Technology. This study was also partially supported by the Department of Defense Army Research Office under Grant W911NF–15–1–0070 and by NASA under Grant NNH15ZDA001N.
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Prakash, S., Shati, F., Norouzi, H. et al. Observed differences between near-surface air and skin temperatures using satellite and ground-based data. Theor Appl Climatol 137, 587–600 (2019). https://doi.org/10.1007/s00704-018-2623-1
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DOI: https://doi.org/10.1007/s00704-018-2623-1