Contrasting snow and ice albedos derived from MODIS, Landsat ETM+ and airborne data from Langjökull, Iceland

Surface albedo is a key parameter in the energy balance of glaciers and ice sheets because it controls the shortwave radiation budget, which is often the dominant term of a glacier's surface energy balance. Monitoring surface albedo is a key application of remote sensing and achieving consistency between instruments is crucial to accurate assessment of changing albedo. Here we take advantage of a high resolution (5 m) airborne multispectral dataset that was collected over Langjokull, Iceland in 2007, and compare it with near contemporaneous ETM+ and MODIS imagery. All three radiance datasets are converted to reflectance by applying commonly used atmospheric correction schemes: 6S and FLAASH. These are used to derive broadband albedos. We first assess the similarity of albedo values produced by different atmospheric correction schemes for the same instrument, then contrast results from different instruments. In this way we are able to evaluate the consistency of the available atmospheric correction algorithms and to consider the impacts of different spatial resolutions. We observe that FLAASH leads to the derivation of surface albedos greater than when 6S is used. Albedo is shown to be highly variable at small spatial scales. This leads to consistent differences associated with specific facies types between different resolution instruments, in part attributable to different surface bi-directional reflectance distribution functions. Uncertainties, however, still exist in this analysis as no correction for variable bi-directional reflectance distribution functions could be implemented for the ETM+ and airborne datasets.

[1]  W. G. Rees,et al.  Combining airborne lidar and Landsat ETM+ data with photoclinometry to produce a digital elevation model for Langjökull, Iceland , 2013 .

[2]  J. Oerlemans,et al.  Narrowband-to-broadband albedo conversion for glacier ice and snow: equations based on modeling and ranges of validity of the equations , 2004 .

[3]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[4]  Lin Wang,et al.  A new cross-track radiometric correction method (VRadCor) for airborne hyperspectral image of operational modular imaging spectrometer(OMIS) , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[5]  W. Paterson,et al.  The Physics of Glaciers Ed. 4 , 2010 .

[6]  C. Reijmer,et al.  Anisotropy of the Reflected Radiation Field Over Melting Glacier Ice , 1998 .

[7]  S. P. Anderson,et al.  Glaciers Dominate Eustatic Sea-Level Rise in the 21st Century , 2007, Science.

[8]  G. Flowers,et al.  Spatial and Temporal Transferability of a Distributed Energy-Balance Glacier Melt Model , 2011 .

[9]  C. Justice,et al.  Atmospheric correction of MODIS data in the visible to middle infrared: first results , 2002 .

[10]  X. Fettweis,et al.  Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model , 2012 .

[11]  T. Berntsen,et al.  A Comparison between Simulated and Observed Surface Energy Balance at the Svalbard Archipelago , 2015 .

[12]  Shunlin Liang,et al.  Mapping daily snow/ice shortwave broadband albedo from Moderate Resolution Imaging Spectroradiometer (MODIS): The improved direct retrieval algorithm and validation with Greenland in situ measurement , 2005 .

[13]  Teemu Hakala,et al.  Hemispherical-directional reflectance factor measurements of snow on the Greenland Ice Sheet during the Radiation, Snow Characteristics and Albedo at Summit (RASCALS) campaign , 2014 .

[14]  Warren B. Cohen,et al.  Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery☆ , 1997 .

[15]  A. S. Mahiny,et al.  A comparison of four common atmospheric correction methods , 2007 .

[16]  J. Foster,et al.  Comparison of in situ and Landsat derived reflectance of Alaskan glaciers , 1989 .

[17]  Nigel P. Fox,et al.  Characterisation of the HDRF (as a proxy for BRDF) of snow surfaces at Dome C, Antarctica, for the inter-calibration and inter-comparison of satellite optical data , 2015 .

[18]  Yuichi Shimamura,et al.  Evaluation of a useful method to identify snow‐covered areas under vegetation – comparisons among a newly proposed snow index, normalized difference snow index, and visible reflectance , 2006 .

[19]  J. Hagen,et al.  On the Net Mass Balance of the Glaciers and Ice Caps in Svalbard, Norwegian Arctic , 2003 .

[20]  Alan H. Strahler,et al.  An algorithm for the retrieval of albedo from space using semiempirical BRDF models , 2000, IEEE Trans. Geosci. Remote. Sens..

[21]  G. Miller,et al.  Glacier fluctuation and inferred climatology of Langjökull ice cap through the Little Ice Age , 2007 .

[22]  W. Greuell,et al.  Anisotropic reflection by melting glacier ice : Measurements and parametrizations in Landsat TM bands 2 and 4 , 1999 .

[23]  A. Arendt Approaches to Modelling the Surface Albedo of a High Arctic Glacier , 1999 .

[24]  J. Privette,et al.  Estimating spectral albedo and nadir reflectance through inversion of simple BRDF models with AVHRR/MODIS‐like data , 1997 .

[25]  R. Hill,et al.  Mapping tree species in temperate deciduous woodland using time‐series multi‐spectral data , 2010 .

[26]  J. McDonnell,et al.  Topographic controls on the chemistry of subsurface stormflow , 2001 .

[27]  Crystal B. Schaaf,et al.  Accuracy assessment of the MODIS 16-day albedo product for snow: comparisons with Greenland in situ measurements , 2005 .

[28]  E. Källén,et al.  Vertical structure of recent Arctic warming , 2008, Nature.

[29]  Marika M. Holland,et al.  Perspectives on the Arctic's Shrinking Sea-Ice Cover , 2007, Science.

[30]  Johannes Oerlemans,et al.  Narrowband-to-broadband albedo conversion for glacier ice and snow based on aircraft and near-surface measurements , 2002 .

[31]  P. Reinartz,et al.  Mosaicking of optical remote sensing imagery , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[32]  D. Scott Munro,et al.  Visible and near-infrared reflectivity during the ablation period on Peyto Glacier, Alberta, Canada , 1996, Journal of Glaciology.

[33]  Liu Da-zhao Atmospheric correction of MODIS data over case Π waters at the Pearl River Estuary , 2010 .

[34]  Wouter H. Knap,et al.  The Surface Albedo Of The Vatnajökull Ice Cap, Iceland: A Comparison Between Satellite-Derived And Ground-Based Measurements , 1999 .

[35]  Yves Durand,et al.  Variational assimilation of albedo in a snowpack model and reconstruction of the spatial mass-balance distribution of an alpine glacier , 2012, Journal of Glaciology.

[36]  T. Painter,et al.  Reflectance quantities in optical remote sensing - definitions and case studies , 2006 .

[37]  H. Björnsson,et al.  Comparison of energy balance and degree–day models of summer ablation on the Langjökull ice cap, SW-Iceland , 2009, Jökull.

[38]  P. Holmlund,et al.  The Mass Balance of Circum-Arctic Glaciers and Recent Climate Change , 1997, Quaternary Research.

[39]  S. Warren,et al.  A Model for the Spectral Albedo of Snow. II: Snow Containing Atmospheric Aerosols , 1980 .

[40]  Masamu Aniya,et al.  The use of satellite and airborne imagery to inventory outlet glaciers of the Southern Patagonia Icefield, South America , 1996 .

[41]  Libo Wang,et al.  Snow and ice facies variability and ice layer formation on Canadian Arctic ice caps, 1999–2005 , 2009 .

[42]  C. Tucker,et al.  NASA’s Global Orthorectified Landsat Data Set , 2004 .

[43]  F. Pellicciotti,et al.  A study of the energy balance and melt regime on Juncal Norte Glacier, semi‐arid Andes of central Chile, using melt models of different complexity , 2008 .

[44]  Jack Kohler,et al.  Topographic controls on the surface energy balance of a high Arctic valley glacier , 2006 .

[45]  Neil S. Arnold,et al.  Modelling seasonal and spatial variations in the surface energy balance of Haut Glacier d’Arolla, Switzerland , 2000, Annals of Glaciology.

[46]  Crystal B. Schaaf,et al.  Re-evaluation of MODIS MCD43 Greenland albedo accuracy and trends , 2013 .

[47]  R. Hock,et al.  Regionally differentiated contribution of mountain glaciers and ice caps to future sea-level rise , 2011 .

[48]  Martin Funk,et al.  An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier d'Arolla, Switzerland , 2005 .

[49]  Didier Tanré,et al.  Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview , 1997, IEEE Trans. Geosci. Remote. Sens..

[50]  P. Reinartz,et al.  Radiometric normalization of optical remote sensing imagery , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[51]  X. Fettweis,et al.  Greenland ice sheet albedo feedback: thermodynamics and atmospheric drivers , 2012 .

[52]  J. Roujean,et al.  A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data , 1992 .

[53]  Roy G. Grainger,et al.  Reconciling satellite‐derived atmospheric properties with fine‐resolution land imagery: Insights for atmospheric correction , 2011 .

[54]  E. Vermote,et al.  Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II. Homogeneous Lambertian and anisotropic surfaces. , 2007, Applied optics.

[55]  Self-similarity in glacier surface characteristics , 2003, Journal of Glaciology.

[56]  Alan H. Strahler,et al.  Validation of the MODIS bidirectional reflectance distribution function and albedo retrievals using combined observations from the aqua and terra platforms , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[57]  James C. Storey,et al.  Four years of Landsat-7 on-orbit geometric calibration and performance , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[58]  Christophe Kinnard,et al.  Albedo over rough snow and ice surfaces , 2014 .

[59]  Regine Hock,et al.  A distributed surface energy-balance model for complex topography and its application to Storglaciären, Sweden , 2005, Journal of Glaciology.

[60]  Johannes Oerlemans,et al.  Model study of the spatial distribution of the energy and mass balance of Morteratschgletscher, Switzerland , 2002, Journal of Glaciology.

[61]  Doreen S. Boyd,et al.  Remote sensing in physical geography: a twenty-first-century perspective , 2009 .

[62]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[63]  S. Warren,et al.  A Model for the Spectral Albedo of Snow. I: Pure Snow , 1980 .

[64]  David P. Miller,et al.  Status of atmospheric correction using a MODTRAN4-based algorithm , 2000, SPIE Defense + Commercial Sensing.

[65]  Xavier Fettweis,et al.  The role of albedo and accumulation in the 2010 melting record in Greenland , 2011 .

[66]  Daniel Mandl,et al.  High-speed atmospheric correction for spectral image processing , 2012, Defense + Commercial Sensing.

[67]  J. Oerlemans,et al.  The residual method for determination of the turbulent exchange coefficient applied to automatic weather station data from Iceland, Switzerland and West Greenland , 2005, Annals of Glaciology.

[68]  Wouter H. Knap,et al.  Comparison of Landsat TM-derived and ground-based albedos of Haut Glacier d'Arolla, Switzerland , 1999 .

[69]  J. Kohler,et al.  Modeling the surface mass balance of a high Arctic glacier using the ERA‐40 reanalysis , 2010 .

[70]  M. F. Meier,et al.  Remote sensing of snow and ice. , 1980 .

[71]  Andreas Kääb,et al.  Rapid disintegration of Alpine glaciers observed with satellite data , 2004 .