Melting of snow and ice

Transcription

1 Glacier meteorology Surface energy balance How does ice and snow melt? Where does the energy come from? How to model melt? Melting of snow and ice Ice and snow melt at 0 C (but not necessarily at air temperature >= 0 C) Depends on energy balance which is controlled by meteorological conditions properties of the surface

2 Summary: Properties of snow and ice Surface temperature can not exceed 0 C - stable stratification in melt season - glacier wind (katabatic wind) - max surface vapor pressure 611 Pa - max longwave outgoing radiation = 316 Wm 2 Transmission of short wave radiation down to 10 m for ice and 1 m for snow - important for subsurface melting High and variable albedo Warming of snow/ice First, snow/ ice needs to be warmed to melting point Second, melt can occur Snow temp Cold content 1 g water refreezes 160 grams of snow will be warmed by 1 K Depth Cold content = energy needed to bring the snow / ice to 0 C. Ground heat flux

3 SURFACE ENERGY BALANCE Qatm = QM + QG Energy flux atmosphere to glacier surface Energy available for melting Change in internal energy (heating / cooling of the ice or snow)

4 Energy balance Q N Net radiation ATMOSPHERE Q H sensible heat flux Q L latent heat flux Q G ground heat flux (heat flux in the ice/snow) Q R sensible heat supplied by rain G Global radiation α albedo L longwave incoming radiation L longwave outgoing radiation G R L L Precipitation Sensible heat flux & latent heat flux Wind GLACIER Conduction (snow & ice) MELTING GLOBAL RADIATION or shortwave incoming radiation Top of atmosphere radiation solar constant = amount of incoming solar electromagnetic radiation per unit area, measured on the outer surface of Earth's atmosphere, in a plane perpendicular to the rays. roughly 1366 W/m2, fluctuates by about 7% during a year W/m2 to 1321 W/m2 in early July varying distance from the sun the average incoming solar radiation is one fourth the solar constant or ~342 W/m².

5 GLOBAL RADIATION or shortwave incoming radiation Direct & diffuse only diffuse Wavelength: µm 2 components: Direct / diffuse component: Scattering by air molecules scattering and absorption by liquid and solid particles Selective absorption by water vapour and ozone Direct solar radiation I 0 = solar constant=1368 Wm -2 cos (angle of incidence θ) R= Earth-Sun radius (m=mean) Ψ= atmospheric transmissivity P= atmospheric pressure (0=at sea level) β= slope angle, φ sun Φ slope =solar and slope azimuth angle θ zenith, Z Strong spatial variation Controlling factors: - site characteristics: slope, aspect, solar geometry - atmosphere: transmissivity (cloudiness, pollutants...) I increases with - decreasing angle of incidence - increasing transmissivity (affected by volcanoes, pollution, clouds) - increasing elevation (decreasing mass, less shading, multiple reflection)

6 Spatial variation of potential solar direct radiation (clear-sky conditions) Topographic shading averaged over melt season Potential direct radiation The large spatial variability of the direct component of global radiation in complex topography is responsible for much of the spatial variability in observed melt Modelled direct and diffuse radiation on Storglaciaren, Jun 7 Sep 17, Wm2 Clear-sky days= D approx. 15% of global radiation, Overcast days 100% D controlled by - atmospheric conditions (clouds) - spatially: albedo, skyview factor, V Less variable spatially than direct radiation

7 Extrapolation of global radiation Ratio is small under cloudy conditions Ratio is large under clear-sky conditions Ratio is proxy for cloudiness and assumed to be the same across glacier Albedo ATMOSPHERE Precipitation R L Sensible heat flux & latent heat flux G L Wind GLACIER Conduction (snow & ice) MELTING

8 ALBEDO = average reflectivity over the spectrum µm = ratio between reflected and incoming solar radiation Typical values: new snow old snow glacier ice soil, dark 0.1 grass 0.2 rain forest 0.15 Large wavelength dependency Large variability in space and time Key variable in glacier melt modelling Ice albedo less variable than snow albedo, but often modified by sediment and debris cover Hourly discharge

9 CONTROLS ON GLACIER ALBEDO Surface properties Grain size (large grain size decreases albedo) Water content (water increases grain size decreases albedo) Impurity content Surface roughness Crystal orientation/structure Incident shortwave radiation Cloudiness ( increase since clouds preferentially absorb near-infrared radiation higher fraction of visible light which has higher reflectivity); effect enhanced by multiple reflection, increase up to 15% effect is small over ice surfaces Zenith angle ( increase when sun is low, due to Mie scattering properties of the grains) Jonsell et al., 2003, J. Glac. How to model snow albedo? Radiative transfer models including effects of grain size (most important control) and atmospheric controls large data requirements, not practicable for operational purposes Empirical relationships Aging curve approach: function of time after snowfall (Corps of Engineers, 1956) variants include temperature, snow depth b, k = coefficients α 0 =minimum snow albedo

10 Snow albedo parameterisations 1) U.S. Army Corps of Engineers (1956) 2) Brock et al. (2000) function snow age n and temperature (through k) Snow albedo is computed as a function of accumulated maximum daily temperature since snowfall Daily albedo Pelliciotti et al., J. Glaciol No diurnal variation Slope effect albedo Parallel-levelled instrument Horizontally levelled diurnal variation Albedo Time (hrs) Jonsell et al, 2003, J.Glaciol., 164

11 Cryoconite holes Longwave incoming radiation Wavelengths 4-120µm Emitted by atmosphere (water vapour, CO2, ozone) Function of air temperature and humidity (cloudiness) High values compared to shortwave radiation Longwave rad. balance < 0, when fog ca 0 W/m2 Spatial variation: Topographic effects: - reduced by obscured sky - enhanced by radiation from slopes and air inbetween Climate change: Temp increase or more cloudiness more L L R L acts day & night G L =εeffσt4 glacier ATMOSPHERE Precipitation Sensible heat flux & latent heat flux L Wind GLACIER Conduction (snow & ice) MELTING

12 The longwave incoming radiation is the largest contribution to melt (~ 70%) L =ε eff σt 4 About 70 % of the longwave incoming radiation originates from within the first 100m of the atmosphere Variations of screen-level temperatures can be regarded as representative of this boundary layer PARAMETERISATION OF LONG-WAVE INCOMING RADIATION L =Fε clear-sky σt 4 =ε eff σt 4 ε eff =effective emissivity T=air temperature n= cloud fraction (0-1) e=vapour pressure clear-sky term (cs) overcast term (oc) ε cs =clear-sky emissivity ε oc =overcase emissivity L = clear (T,e) F σ T 4 INPUT air temperature (T) vapour pressure (e) (air humidity) Cloudiness (n) (can e.g. be parameterized as function of global radiation and top of atmosphere radiation)

13 Longwave outgoing radiation L =εσt 4 +(1-ε)L L = W m -2 σ = 5.67x10-8 W m -2 K -4 Longwave reflectance of snow: < 0.05 Emissivity ε > 0.95 Often assumed ε =1 Assume black body radiation -> ε=1

14 Radiation messages Net radiation is negative during clear-sky nights: low atmospheric emissivity low incoming longwave radiation cooling of the air Net radiation is higher during cloudy nights (high atmospheric emissivity high incoming longwave radiation warming of the air Longwave incoming radiation (ca. 300 W/m2) much larger than shortwave incoming radiation ( W/m2), but less variation TURBULENT HEAT FLUXES Precipitation R L Sensible heat flux & latent heat flux G L Wind GLACIER Conduction (snow & ice) MELTING

15 Turbulent heat fluxes Driven by temperature and moisture gradients between air and surface and by turbulence as mechanism of vertical air exchange Turbulent heat fluxes = Ability to transfer x gradient of relevant property Eddy diffusivity Turbulent heat fluxes Driven by temperature and moisture gradients between air and surface and by turbulence as mechanism of vertical air exchange Sensible heat flux Function of temperature gradient Function of wind speed Latent heat flux ( the energy released or absorbed during a change of state) Function of vapour pressure gradient Function of wind speed Fluxes also affected by Surface roughness Atmospheric stability

16 Sensible heat flux Turbulent heat fluxes Temperature difference Latent heat flux wind speed Exchange coefficient Wind speed Exchange coefficient is function of surface roughness and stability function (empirical expressions to define stability functions) Humidity difference Bulk aerodynamic method Sublimation To melt 1 kg snow/ice requires J kg -1 Latent heat of fusion To sublimate 1 kg of snow requires J kg -1 Latent heat of sublimation (8x L f!!!)

17 Latent heat flux Positive vapour gradient Condensation To melt 1 kg snow/ice requires J kg-1 = Latent heat of fusion Negative vapour gradient Sublimation To sublimate 1 kg snow/ice requires J kg-1 = Latent heat of sublimation Typical for during dry periods in the outer tropics Sublimation occurs Ls = 8*Lf 8x less ablation than under wet conditions for same energy input

18 Sensible heat flux by rain Tr = rain temperature Ts = surface temperature R = rain fall rate ρ= Density of water Cp=Specific heat of water A 10 mm/day at 10 C on melting surface provides 2.4 Wm-2 Negligible compared to W/m2 net radiation averaged over longer periods But rainfall has indirect effects: changes albedo, mechanical removal of snow An intellectual break

19 wind speed & direction 1) Temp radiation components (S, S, L, L ) temperature humidity sensible heat flux latent heat flux rain heat flux (longwave incoming radiation) 2) Humidity latent heat flux (longwave incoming radiation) 3) Wind speed sensible heat flux latent heat flux 4) Global radiation Photo: T. Schuler, Austonna Temporal variation of energy balance components

20 Energy partitioning (%) Glacier Q N Q H Q L Q G Q M Aletschgletscher, Switzerland Hintereisferner, Austria Peytoglacier, Canada Storglaciären, Sweden Melt energy weather patterns day-to-day variability in melt is often determined by the turbulent fluxes Net radiation Sensible heat Latent heat Q M = Q N +Q H +Q L +

21 Summary (Part I) Ice and snow melt are determined by the energy balance Do not necessarily melt at air temperature >= 0 C Snow/ice temperature must be raised to 0 C before melting can occur (2 steps: warming, melting) Fixed maximum surface temperature (0 C) under melting conditions: constant L = 316 Wm 2, surface vapour pressure = 611 Pa, leads to condensation stable stratification (inversion), glacier wind Often net radiation dominant source of energy, longwave radiation largest source (often the double the amount of shortwave incoming) Variations from day to day often determined by variations in turbulent heat fluxes Spatial variations in energy balance determined by shortwave incoming radiation Energy by rain generally very small direction of vapour pressure gradient important sublimation reduces energy available for melt significantly How to model melt? 1. Physically based energy-balance models: each of the relevant energy fluxes at the glacier surface is computed from physically based calculations using direct measurements of the necessary meteorological variables 2. Temperature-index or degree-day models: melt is calculated from an empirical formula as a function of air temperature alone

22 Melt modelling Model type Spatial discretization Mass balance models 0-Dim elevation bands fully distributed Temp-index regression Temp-index or simplified energy balance Increasing model sophistication Energy balance

23 Temperature-index melt models Assume a relationship between air temperature and melt: M=f(T), M=f(T+) Relationship melt - air temperature Data by R. Braithwaite Temperature-index melt models Assume a relationship between air temperature and melt: M=f(T), M=f(T+) Positive degree-day sum PDD = ΣT+ Relationship melt degree-day sum

24 Physical basis of temp-index models Air temperature directly affects several components of the surface energy balance Longwave incoming rad Sensible heat flux Latent heat flux L =εσt 4 f(t) f(e(t)) L is the largest contribution to melt (~ 70%) (Ohmura, 2001, Physical basis of temperatureindex models) Case studies (Sicart et al., 2008, JGR): Correlation between energy fluxes and air tempe L has low variability compared to other fluxes L is poorly correlated to air temperature when cloud variations dominate its variability (usual in mountains) Degree-day factors [mm/day/k] Typical values Snow ~3-5 mm/d/k Snow Ice ~5-10 mm/d/k Ice Aletschgletscher, Switzerland 5.3 John Evans Glacier, Canada Alfotbreen, Norway Storglaciaren, Sweden Dokriani Glacier, Himalaya Yala Glacier, Himalaya Glacier AX Thule Ramp, Greenland 12, 7.0 Camp IV-EGIG, Greenland 18.6 GIMES profile, Greenland 8.7 Qamanarssup sermia, M = f ice/snow * T

25 Degree-day factors [mm/day/k] M = DDF ice/snow * T + Spatial and diurnal variation Derived from energy balance modeling Hock, 1999, J.Glaciol. SPATIAL VARIABILITY OF DEGREE-DAY FACTORS Calculation of degree-day factors for various points on the Greenland ice sheet with an atmospheric and snow model (thesis Filip Lefebre) snow ice

26 Performance of degree-day model Melt = DDFice/snow * T+ Model captures seasonal variations but not diurnal melt fluctuations

27 Modified temperature-index model Including potential direct solar radiation Hock 1999, J. Glaciol Classical degree-day factor M = DDFice/snow * T+ Including pot. direct radiation M = (MF + aice/snow*dir) * T+ Model introduces a spatial variation in melt factors a diurnal variation in melt factors

28 Simulated cumulative melt Summer 1994 Model comparison

29 Gornergletscher outburst floods Huss et al., 2007, J. Glaciol. Photo: Shin Sugiyama Extended temperature-index models including other data than temperature Degree-day model M = DDF ice/snow * T + Extended temperature-index model including radiation M = a * R + melt factor * T Shortwave bal Net radiation Energy balance model Gradual transition from degree-day models to energy balance-type expressions by increasing the number of climate input variables

30 Simplified energy balance model Oerlemans (2001) M = a * R + melt factor * T M = (1-α)G+c 0 +c 1 T Shortwave radiation balance Longwave balance and turbulent fluxes Gradual transition from degree-day models to energy balance-type expressions by increasing the number of climate input variables Distributed temp-index model by Pelliciotti et al, 2005, J.Glaciol. Temperature Albedo Incoming shortwave radiation Computed as function of accumulated maximum daily temperature since snowfall Brock Brock et et al. al. (2000) (2000) Computed as function of daily temperature range Model only requires air temperature Global radiation and albedo parameterized Pellicciotti et al, 2005, J. Glaciology

31 Spatial patterns of hourly melt rate (mm w.e. h-1) Haut d Arolla Glacier 27 August July Melt is function of Global radiation, and thus topography (in particular shading) Surface properties and particularly albedo Temperature extrapolation With courtesy of Francesca Pellicciotti Pellicciotti et al, 2005, J. Glaciology Temperature-index versus energy balance Shortcomings Advantages Temperature index Wide availability of Temp-data Easy interpolation and forecasting Good model performance Computational simplicity Empirical, not physically based DDF vary, works on average conditions Does not work in tropics Model parameter stability under different climate conditions? Energy balance Physical based describe physical processes more adequately Projections more reliable Large data requirements (often not available)

32 Runoff peak: melt or subglacial drainage event? Energy balance on Storglaciären Wrong conclusion if temperature taken as sole index, Energy balance needed to solve problem Net radiation Sensible heat Latent heat

33 SUMMARY Both temp-index and energy balance models are useful tools, choice depends on data availability Awareness of limitations Need for more approaches of intermediate complexity and moderate data input Both temp-index and energy balance models need calibration (parameter tuning) Literature Energy balance: Hock, R., Glacier melt: A review on processes and their modelling. Progress in Physical Geography 29(3), Temperature-index methods: Hock, R., Temperature index melt modelling in mountain regions. Journal of Hydrology 282(1-4), doi: / S (03)