World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Near–surface Air Temperature and Snow Skin Temperature Comparison from Crest-safe Station Data with Modis Land Surface Temperature Data : Volume 12, Issue 8 (10/08/2015)

By Pérez Díaz, C. L.

Click here to view

Book Id: WPLBN0004012434
Format Type: PDF Article :
File Size: Pages 23
Reproduction Date: 2015

Title: Near–surface Air Temperature and Snow Skin Temperature Comparison from Crest-safe Station Data with Modis Land Surface Temperature Data : Volume 12, Issue 8 (10/08/2015)  
Author: Pérez Díaz, C. L.
Volume: Vol. 12, Issue 8
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Yu, Y., Muñoz, J., Lakhankar, T., Romanov, P., Pérez Díaz, C. L., & Khanbilvardi, R. (2015). Near–surface Air Temperature and Snow Skin Temperature Comparison from Crest-safe Station Data with Modis Land Surface Temperature Data : Volume 12, Issue 8 (10/08/2015). Retrieved from http://hawaiilibrary.net/


Description
Description: National Oceanic and Atmospheric Administration-Cooperative Remote Sensing Science and Technology (NOAA-CREST) Center, The City College of New York, New York, NY 10031, USA. 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.


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

Excerpt
Benali, A., Carvalho, A. C., Nunes, J. P., Carvalhais, N., and Santos, A.: Estimating air surface temperature in Portugal using MODIS LST data, Remote Sens. Environ., 124, 108–121, 2012.; Chen, C., Lakhankar, T., Romanov, P., Helfrich, S., Powell, A., and Khanbilvardi, R.: Validation of NOAA-Interactive Multisensor Snow and Ice Mapping System (IMS) by comparison with ground-based measurements over continental United States, Remote Sens., 4, 1134–1145, doi:10.3390/rs4051134, 2012.; Crosson, W. L., Al-Hamdan, M. Z., Hemmings, S. N. J., and Wade, G. M.: A daily merged MODIS Aqua–Terra land surface temperature data set for the conterminous United States, Remote Sens. Environ., 119, 315–324, doi:10.1016/j.rse.2011.12.019, 2012.; Dominé, F. and Shepson, P. B.: Air-snow interactions and atmospheric chemistry, Science, 297, 1506–1510, doi:10.1126/science.1074610, 2002.; Dong, J. and Peters-Lidard, C.: On the relationship between temperature and MODIS snow cover retrieval errors in the western U.S., IEEE J. Sel. Top. Appl., 3, 132–140, 2010.; Fu, G., Shen, Z., Zhang, X., Shi, P., Zhang, Y., and Wu, J.: Estimating air temperature of an alpine meadow on the Northern Tibetan Plateau using MODIS land surface temperature, Acta Ecol. Sin., 31, 8–13, 2011.; Hachem, S., Duguay, C. R., and Allard, M.: Comparison of MODIS-derived land surface temperatures with ground surface and air temperature measurements in continuous permafrost terrain, The Cryosphere, 6, 51–69, doi:10.5194/tc-6-51-2012, 2012.; Hall, D. K., Riggs, G. A., Salomonson, V. V., DiGirolamo, N. E., and Bayr, K. J.: MODIS snow-cover products, Remote Sens. Environ., 83, 181–194, 2002.; Lakhankar, T. Y., Muñoz, J., Romanov, P., Powell, A. M., Krakauer, N. Y., Rossow, W. B., and Khanbilvardi, R. M.: CREST-Snow Field Experiment: analysis of snowpack properties using multi-frequency microwave remote sensing data, Hydrol. Earth Syst. Sci., 17, 783–793, doi:10.5194/hess-17-783-2013, 2013.; Li, Z.-L., Tang, B.-H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., and Sobrino, J. A.: Satellite-derived land surface temperature: current status and perspectives, Remote Sens. Environ., 131, 14–37, doi:10.1016/j.rse.2012.12.008, 2013.; Muñoz, J.: Microwave Snow Emission Model Using a Long-Term Field Experiment, The City College of New York, unpublished thesis dissertation, 2014.; Shuman, C., Hall, D., DiGirolamo, N., Mefford, T., and Schnaubelt, M.: Comparison of near-surface air temperatures and MODIS ice-surface temperatures at Summit, Greenland (2008–2013), J. Appl. Meteorol. Climatol., 53, 2171–2180, 2013.; Tang, Q., Gao, H., Lu, H., and Lettenmaier, D. P.: Remote sensing: hydrology, Prog. Phys. Geog., 33, 490–509, 2009.; Vancutsem, C., Ceccato, P., Dinku, T., and Connor, S. J.: Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa, Remote Sens. Environ., 114, 449–465, 2010.; Walsh, J. E., Jasperson, W. H., and Ross, B.: Influences of snow cover and soil moisture on monthly air temperature, Mon. Weather Rev., 113, 756–768, doi:2.0.CO;2>10.1175/1520-0493(1985)113<0756:IOSCAS>2.0.CO;2, 1985.; Wan, Z., Zhang, Y., Zhang, Q., and Li, Z.-L.: Quality assessment and validation of the MODIS global land surface temperature, Int. J. Remote Sens., 25, 261–274, doi:10.1080/0143116031000116417, 2004.; Yang, W., Tan, B., Huang, D., Rautiainen, M., Shabanov, N. V., Wang, Y., Privette, J. L., Huemmrich, K.

 

Click To View

Additional Books


  • Hydrogeios: a Semi-distributed Gis-based... (by )
  • Investigation of Groundwater-surface Wat... (by )
  • Influence of Cracking Clays on Satellite... (by )
  • A Journey of a Thousand Miles Begins wit... (by )
  • River Flow Forecasting with Artificial N... (by )
  • Screening of Sustainable Groundwater Sou... (by )
  • Spatial Moments of Catchment Rainfall: R... (by )
  • Data Assimilation in Integrated Hydrolog... (by )
  • Detecting the Influence of Land Use Chan... (by )
  • Accounting for Dependencies in Regionali... (by )
  • Confirmation of Acru Model Results for A... (by )
  • Qualitative Soil Moisture Assessment in ... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from Hawaii eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.