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Surveys in Geophysics

, Volume 35, Issue 3, pp 785–812 | Cite as

Global Snow Mass Measurements and the Effect of Stratigraphic Detail on Inversion of Microwave Brightness Temperatures

  • Mark Richardson
  • Ian Davenport
  • Robert Gurney
Article

Abstract

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as snow water equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions, but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment and the Helsinki University of Technology microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 and 37 GHz vertically polarised microwaves are consistent with advanced microwave scanning radiometer-earth observing system and special sensor microwave imager retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10-cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method, then it is equivalent to ±13 mm SWE (7 % of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.

Keywords

Snow mass Snow grain size Remote sensing Microwave radiometry Hydrology 

Notes

Acknowledgments

MR is funded by National Environment Research Council studentship F3275903, and ID is a member of the National Centre for Earth Observation.

References

  1. Anderson E (1976) A point energy and mass balance model of a snow cover. Office of Hydrology, National Weather Service, Silver SpringGoogle Scholar
  2. Andreadis K, Liang D, Tsang L, Lettenmaier D, Josberger E (2008) Characterization of errors in a coupled snow hydrology–microwave emission model. J Hydrometeor 9:149–164CrossRefGoogle Scholar
  3. Armstrong R, Brodzik M (2000) Validation of passive microwave snow algorithms. Proc IGARSS 2000(4):1561–1563Google Scholar
  4. Armstrong R, Brodzik M, Knowles K, Savoie M (2005) Global monthly EASE-grid snow water equivalent climatology. Boulder, Colorado USA: National Snow and Ice Data Center, URL http://nsidc.org/data/docs/daac/nsidc0271_ease_grid_swe_climatology.gd.html
  5. Barnett TP, Adam J, Lettenmaier DP (2005) Potential impacts of a warming climate on water availability in snow-dominated regions. Nature 438:303–309CrossRefGoogle Scholar
  6. Best M, Pryor M, Clark D, Rooney G, Essery R, Ménard C et al (2011) The joint UK (JULES) land environment simulator, model description—Part 1: energy and water fluxes. Geosci Model Dev 4:677–699CrossRefGoogle Scholar
  7. Betts A, Köhler M, Zhang Y (2009) Comparison of river basin hydrometeorology in ERA-Interim and ERA-40 reanalyses with observations. J Geophys Res 114Google Scholar
  8. Brasnett B (1999) A global analysis of snow depth for numerical weather prediction. J Appl Meteorol 38:726–740CrossRefGoogle Scholar
  9. Brown RD, Mote PW (2009) The response of northern hemisphere snow cover to a changing climate. J Clim 22:2124–2145CrossRefGoogle Scholar
  10. Brown R, Brasnett B, Robinson D (2003) Gridded North American monthly snow depth and snow water equivalent for GCM evaluation. Atmos Ocean 41(1):1–14CrossRefGoogle Scholar
  11. Brucker L, Royer A, Picard G, Langlois A, Fily M (2011) Hourly simulations of the microwave brightness temperature of seasonal snow in Quebec, Canada, using a coupled snow evolution–emission model. Remote Sens Environ 115:1966–1977CrossRefGoogle Scholar
  12. Brun E, David P, Sudul M, Brunot G (1992) A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting. J Glaciol 38(128):13–22Google Scholar
  13. Budyko M (1958) The heat balance of the Earth’s surface. Department of Commerce, Weather BureauGoogle Scholar
  14. Carroll T, Cline D, Fall G, Nilsson A, Li L, Rost A (2001) NOHRSC operations and the simulation of snow cover properties for the coterminous U.S. 69th Annual Meeting of the Western Snow Conference. Sun Valley, Idaho USAGoogle Scholar
  15. Chang A, Hall J, Foster D (1987) Nimbus7 SMMR derived global snow cover parameters. Ann Glaciol 9(9):39–44Google Scholar
  16. Chang A, Kelly R, Josberger E, Armstrong R, Foster J, Mognard N (2005) Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the Northern Great Plains. J Hydrometeor 6:20–33CrossRefGoogle Scholar
  17. Clifford D (2010) Global estimates of snow water equivalent from passive microwave instruments: history, challenges and future developments. Int J Remote Sens 31(14):3707–3726CrossRefGoogle Scholar
  18. Cline D, Elder K, Davis B, Hardy J, Liston GE, Imel D et al (2002) Overview of the NASA cold land processes field experiment (CLPX-2002). SPIE Proceedings, HangzhouGoogle Scholar
  19. Davenport I, Sandells M, Gurney R (2012) The effects of variation in snow properties on passive microwave snow mass estimation. Remote Sens Environ 118:168–175CrossRefGoogle Scholar
  20. De Lannoy G, Reichle R, Houster P, Arsenault K, Verhoest N, Pauwels V (2010) Satellite-scale snow water equivalent assimilation into a high-resolution land surface model. J Hydrometeor 11:352–369CrossRefGoogle Scholar
  21. Dechant C, Moradkhani H (2011) Radiance data assimilation for operational snow and streamflow forecasting. Adv Water Resour 34(3):351–364CrossRefGoogle Scholar
  22. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J Royal Meteorol Soc 137:553–597CrossRefGoogle Scholar
  23. Derksen C, Sturm M, Listen G, Holmgren J, Huntington H, Silis A et al (2009) Northwest Territories and Nunavut snow characteristics from a subarctic traverse: implications for passive microwave remote sensing. J Hydrometeorol 10:448–463CrossRefGoogle Scholar
  24. Dominé F, Shepson P (2002) Air-snow interactions and atmospheric chemistry. Science 297:1506–1510CrossRefGoogle Scholar
  25. Dong J, Walker J, Houser P, Sun C (2007) Scanning multichannel microwave radiometer snow water equivalent assimilation. J Geophys Res 112:D07108Google Scholar
  26. Drusch M, Vasiljevic D, Viterbo P (2004) ECMWF’s global snow analysis: assessment and revision based on satellite observations. J Appl Meteorol 43:1282–1294CrossRefGoogle Scholar
  27. Durand M, Margulis S (2006) Feasibility test of multifrequency radiometric data assimilation to estimate snow water equivalent. J Hydrometeor 7:443–457CrossRefGoogle Scholar
  28. Durand E, Kim E, Margulis S (2008) Quantifying uncertainty in modelling snow microwave radiance for a mountain snowpack at the point-scale, including stratigraphic effects. IEEE Trans Geosci Remote Sens 46:1753–1767CrossRefGoogle Scholar
  29. Durand M, Kim E, Margulus S (2009). Radiance assimilation shows promise for snowpack characterization. Geophys Res Lett 29(2)Google Scholar
  30. Durand M, Kim E, Margulis S, Molotch N (2011) A first-order characterization of errors from neglecting stratigraphy in forward and inverse passive microwave modelling of snow. IEEE Geosci Remote Sens Lett 8:730–734CrossRefGoogle Scholar
  31. Dutra E, Balsamo G, Viterbo P, Miranda P, Beljaars A, Schär C et al (2010) An improved snow scheme for the ECMWF land surface model: description and offline validation. J Hydrometeorol 11:899–916CrossRefGoogle Scholar
  32. Dye D (2002) Variability and trends in the annual snow-cover cycle in Northern Hemisphere land areas, 1972–2000. Hydrol Proc 16(15):3065–3077CrossRefGoogle Scholar
  33. Dyer J, Mote T (2006) Spatial variability and trends in observed snow depth over North America. Geophys Res Lett 33(16)Google Scholar
  34. Finnish Meteorological Institute. Globsnow Project Description (2012) http://www.globsnow.info/snow_workshop_2012/presentations/GlobSnow_Fact_Sheet_EuropeanSatelliteSnowMonitoringActivities.pdf. Accessed 8th Aug, 2013
  35. Flanner M, Shell K, Barlage M, Perovich D, Tschudi M (2011) Radiative forcing and albedo feedback from the Northern Hemisphere cryosphere between 1979 and 2008. Nat Geosci 4:151–155CrossRefGoogle Scholar
  36. Foster J, Sun C, Walker J, Kelly R, Chang A, Dong J et al (2005) Quantifying the uncertainty in passive microwave snow water equivalent observations. Remote Sens Environ 94:187–203CrossRefGoogle Scholar
  37. Frappart F, Ramillien G, Biancamaria S, Mognard N, Cazenave A (2006) Evolution of high-latitude snow mass derived from the GRACE gravimetry mission (2002–2004). Geophys Res Lett 33Google Scholar
  38. Frei A, Miller J, Robinson D (2003) Improved simulations of snow extent in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2). J Geophys Res 108Google Scholar
  39. Grenfell T, Warren S (1999) Representation of a nonspherical ice particle by a collection of independent spheres for scattering and absorption of radiation. J Geophys Res 104(D24):31697–31709CrossRefGoogle Scholar
  40. Grippa M, Mognard N, Le Toan T (2005) Comparison between the interannual variability of snow parameters derived from SSM/I and the Ob river discharge. Remote Sens Environ 98:35–44CrossRefGoogle Scholar
  41. Hall D, Riggs G (2007) Accuracy assessment of the MODIS snow products. Hydrol Proc 21:1534–1547CrossRefGoogle Scholar
  42. Hall DK, Sturm M, Benson C, Chang AT, Foster JL, Garbeil H et al (1991) Passive microwave remote and in situ measurements of arctic [sic] and subarctic snow covers in Alaska. Remote Sens Environ 38(3):161–172CrossRefGoogle Scholar
  43. Hallikainen M (1989) Microwave radiometry of snow. Adv Space Res 9(1):267–275CrossRefGoogle Scholar
  44. Hancock S, Baxter R, Evans J, Huntley B (2013) Evaluating global snow water equivalent products for testing land surface models. Remote Sens Environ 128:107–117CrossRefGoogle Scholar
  45. Haran T (2003) CLPX-Satellite: MODIS radiances, reflectances, snow cover and related grids. MOD10A2. Boulder, Colorado USA: NSIDC: National Snow and Ice Data CenterGoogle Scholar
  46. Khan V, Holko L (2009) Snow cover characteristics in the Aral Sea Basin from different data sources and their relation with river runoff. J Marine Syst 76:254–262CrossRefGoogle Scholar
  47. Kitaev L, Kislov A, Krenke A, Razuzaev V, Martuganov R, Konstantinov I (2002) The snow cover characteristics of northern Eurasia and their relationship to climatic parameters. Boreal Environ Res 7:437–445Google Scholar
  48. Koskinen J, Pulliainen J, Hallikainen M (1997) The use of ERS-1 SAR data in snow melt monitoring. IEEE Trans Geosci and Remote Sens 35:601–610CrossRefGoogle Scholar
  49. Lemmetyinen J, Pulliainen J, Rees A, Kontu A, Qiu Y, Derksen C (2010) Multiple-layer adaption of HUT snow emission model: comparison with experimental data. IEEE Trans Geosci Remote Sens 48:2781–2794CrossRefGoogle Scholar
  50. Liu G (2004) Approximation of single scattering properties of ice and snow particles for high microwave frequencies. J Atmospheric Sci 61:2441–2456CrossRefGoogle Scholar
  51. Macke A, Mueller J, Raschke E (1996) Single scattering properties of atmospheric ice crystals. J Atmospheric Sci 53(19):2813–2825CrossRefGoogle Scholar
  52. Mätzler C (2000) A simple snowpack/cloud reflectance and transmittance model from microwave to ultraviolet: the ice-lamella pack. J Glaciol 46(152):20–24CrossRefGoogle Scholar
  53. Mätzler C (2002) Relation between grain-size and correlation length of snow. J Glaciol 48:166–461CrossRefGoogle Scholar
  54. Mie G (1908) Beiträge zur Optik trüber Medien, speziell kolloidaler Metallösungen. Ann Phys 330(3):377–445Google Scholar
  55. Nilsson A (2003) Qscat CLPX data. //ftp.nohrsc.nws.gov/staff/nilsson/qscat/. Accessed 15 April 2013Google Scholar
  56. Niu G-Y, et al. (2007). Retrieving snow mass from GRACE terrestrial water storage change with a land surface model. Geophys Res Lett 34Google Scholar
  57. Onogi K, Tsutsui J, Koide H, Sakamoto M, Kobayashi S, Hatsushika H et al (2007) The JRA-25 reanalysis. J Meteorol Soc Jpn 85(3):369–432CrossRefGoogle Scholar
  58. Painter T, Bryant A, Skiles S (2012). Radiative forcing by light absorbing impurities in snow from MODIS surface reflectance data. Geophys Res Lett 39Google Scholar
  59. Picard G, Brucker L, Fily M, Gallée H, Krinner G (2009) Modeling time series of microwave brightness temperature in Antarctica. J Glaciol 55(191):537–551CrossRefGoogle Scholar
  60. Pulliainen J (2006) Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations. Remote Sens Environ 101:257–269CrossRefGoogle Scholar
  61. Pulliainen J, Grandell J, Hallikainen M (1999) HUT snow emission model and its applicability to snow water equivalent retrieval. IEEE Trans Geosci Rem Sens 37(3):1378–1390CrossRefGoogle Scholar
  62. Ramsay B (1998) The interactive multisensor snow and ice mapping system. Hydrol Process 12:1537–1546CrossRefGoogle Scholar
  63. Rawlins M, Fanestock M, Frolking S, Vörösmarty CJ (2007) On the evaluation of snow water equivalent estimates over the terrestrial Arctic drainage basin. Hydrol Process 21(12):1616–1623Google Scholar
  64. Rawlins M, Steele M, Holland M, Adam J, Cherry J, Francis J et al (2010) Analysis of the Arctic system for freshwater cycle intensification: observations and expectations. J Clim 23:5715–5737CrossRefGoogle Scholar
  65. Rienecker M, Suarez M, Gelaro R, Todling R, Bacmeister J, Liu E et al (2010) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24:3624–3648CrossRefGoogle Scholar
  66. Rittger K, Painter T, Dozier J (2013) Assessment of methods for mapping snow cover from MODIS. Adv in Water Resour 51:367–380CrossRefGoogle Scholar
  67. Roesch A (2006) Evaluation of surface albedo and snow cover in AR4 coupled climate models. J Geophys Res 111Google Scholar
  68. Saha S, Moorthi S, Pan H-L, Wang J, Nadiga S, Tripp P et al (2010) The NCEP climate forecast system reanalysis. Bull Amer Meteorol Soc 91:1015–1057CrossRefGoogle Scholar
  69. Salzmann N, Mearns L (2012) Assessing the performance of multiple regional climate model simulations for seasonal mountain snow in the upper Colorado River Basin. J Hydrometeorol 13:539–556CrossRefGoogle Scholar
  70. Skiles S, Painter T, Deems J, Bryant A, Landry C (2012) Dust radiative forcing in snow of the Upper Colorado River Basin: 2. Interannual variability in radiative forcing and snowmelt rates, Water Resour Res 48Google Scholar
  71. Smith C, Guttman L (1953) Measurement of internal boundaries in three-dimensional structures by random sectioning. Trans AIME 5:81–87Google Scholar
  72. Sun C, Walker J, Houser P (2004) A methodology for snow data assimilation in a land surface model. J Geophys Res 109:D08108Google Scholar
  73. Takala M, Luojus K, Pulliainen J, Derksen C, Lemmetyinen J, Kärnä J-P et al (2011) Estimating northern hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer data and ground-based measurements. Remote Sens of Environ 115:3517–3529CrossRefGoogle Scholar
  74. Tedesco M, Pulliainen J, Takala M, Hallikainen M, Pampaloni P (2004a) Artificial neural network-based techniques for the retrieval of SWE and snow depth from SSM/I data. Remote Sens of Environ 90:76–85CrossRefGoogle Scholar
  75. Tedesco M, Kelly R, Foster J, Chang A (2004b) AMSR-E/Aqua daily L3 global snow water equivalent EASE-Grids V002. updated daily. Boulder, Colorado USA: National Snow and Ice Data Center. URL http://nsidc.org/data/ae_dysno
  76. Teschl E, Randeu W, Teschl R (2010) Microwave scattering from ice crystals: how much parameters can differ from equal volume spheres. Adv in Geosci 25:127–133CrossRefGoogle Scholar
  77. Toure A, Goita K, Royer A, Kim E, Durand M, Margulis S et al (2011) A case study of using a multilayered thermodynamical snow model for radiance assimilation. IEEE Trans on Geosci and Remote Sens 49(8):2828–2837CrossRefGoogle Scholar
  78. Uppala S, Kållberg P, Simmons A, Andrae U, Da Costa Bechtold V, Fiorino M et al (2005) The ERA-40 re-analysis. Q J of the Royal Meteorol Soc 131(612):2961–3012CrossRefGoogle Scholar
  79. Wiesmann A, Mätzler C (1999) Microwave emission model of layered snowpacks. Remote Sens of Environ 70(3):307–316CrossRefGoogle Scholar
  80. Wiesmann A, Fierz C, Mätzler C (2000) Simulation of microwave emission from physically modeled snowpacks. Ann of Glaciol 31(1):397–405CrossRefGoogle Scholar
  81. Yang D, Zhao Y, Armstrong R, Robinson D, Brodzik, M-J (2007). Streamflow response to seasonal snow cover mass changes over large Siberian watersheds. J Geophys Res Earth Surf 112Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Mark Richardson
    • 1
    • 2
  • Ian Davenport
    • 1
  • Robert Gurney
    • 1
  1. 1.Department of MeteorologyUniversity of ReadingReadingUK
  2. 2.ESSC, Harry Pitt Building, 3 Earley GateUniversity of ReadingReadingUK

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