## Search Keywords and Engines

"hydrophobic coatings"
"nakajima hashimoto thin solid films"
"preparation of hard super hydrophobic visible light"
"takai lake louise composites snow"
"simple hydrophobic film"

Scholar's Portal
"Composites: Design for performance"

Science Direct
"Recent Studies on Super-Hydrophobic Films"

## Part I: Developing Hydrophobic Thin Film Coatings

Schondelmaier, D., Cramm, S., Klingeler, R., Morenzin, J., Zilkens, Ch., Eberhardt, W., Orientation and Self-Assembly of Hydrophobic Fluoroalkylsilanes, Langmuir, Vol. 18, Issue 16, 6242-6245, (2002)

Tag: water-repellent, FAS, film stability and thickness

The film stability and thickness of self-arranging FAS monolayers was investigated. Hydrophobic surfaces can be created by inducing surface roughness, or by reducing surface free energy. When both are combined super-hydrophobic surfaces are created, where water is able to "roll" off the surface. In rolling off the surface, the water can drag dirt from it, thereby self-cleaning. To preserve the underlying microstructure of the surface, precise control of film thickness, orientation and stability of the molecules are necessary. An analysis of the thickness and the orientation of a self-assembled coating of FAS on various substrates obtained by X-ray photoelectron spectroscopy and X-ray absorption near edge spectroscopy measurements, are presented. A strong bond between the first monolayer of ip-coated FAS molecules and the substrate was observed, with the molecular axis predominantly perpendicular to the surface, even within the microchannels of an Al2O3 membrane. Further layers can be applied weakly by dip-coating, and removed easily by rinsing in water or ethanol.

Tadanaga, K., Katata, N., Minami, T., Super-Water-Repellent Al2O3 Coating Films with High Transparency, Journal of the American Ceramic Society, Vol. 80, Issue 4, 1040-1042, (1997)

Tag: transparent, super-water-repellent coating, Al2O3

This paper investigates the synthesis of transparent, super-water-repellent coatings. By the sol-gel method, porous Al2O3 coatings were produced with roughness less than 50 nm, then heat treated. An uneven, 20-50 nm flowerlike Al2O3 structure was produced by immersing the film in boiling water. To yield low surface energies and water-repellency, Heptadecafluorodecyltrimethylsilane (a FAS) was coated on the Al2O3 film, then again heat treated. Water contact angles of 165 degrees, and a transmittance of visible light greater than 92% were achieved. The roughness of the alumina was too small to scatter light, however it was utilized along with chemical modification by FAS, to yield a super-hydrophobic transparent glass coating.

Zhang, X., Jarn, M., Peltonen, J., Pore, V., Vuorinen, T., Levanen, E., Mantyla, T., Analysis of roughness parameters to specify superhydrophobic antireflective boehmite films made by the sol-gel process, Journal of the European Ceramic Society 28, 2177-2181, (2008).

Tag: Snow and PV, super-hyrdophobic, antireflective

In this paper, superhydrophobic antireflective boehmite (AlOOH) films were made with different optical transmittances by varying the heat-treatment temperatures and the film thicknesses. A set of roughness parameters was determined to characterize the superhydrophobic property and the antireflective property. The aim is not only to identify the superhydrophobic property but also to specify the antireflective property by the roughness parameters. The superhydrophobic antireflective boehmite films were made from aluminum tri-sec-butoxide, isopropyl alcohol, ethyl acetoacetate and (heptadecafluoro-1,1,2,2-tetrahydrodecyl) trimethoxy-silane. Two different sols were produced and spun coated on glass slides. By varying the heat-treatment temperatures and the film thicknesses the superhydrophobic and antireflective properties were tuned. Three slides with sol-A were produced and heat treated at 100C, 300C and 500C. Contact angles were 103, 152, 152 degrees respectively will optical transmittance of all three greater than that of reference glass (92-96%). Two slides with sol-B coatings were treated at 300C. They both produced contact angles of 154 degrees and excellent optical transmittance. B1-300 yielded 95-96% transmittance over the whole wavelength range.

Scmidt, D., Coburn, C., Dekoven, B., Potter, G., Meyers, G. & Fischer, D., Water-based non-stick hydrophobic coatings,Nature 368, 39 - 41, (03 March 1994).

Tag: reactive perfluoroalkyl polymeric surfactants

This article investigates the suitability of RPPS as non-stick coatings when cross linked and cured with reactive ionic functionalities such as carboxylate and phenate. They found an effective an effective crosslinking approach was to react ammonium-carboxylate functional RPPS with a poly-IPO based crosslinking agent. Solutions with both compounds were stable until applied to the surface and loss of ammonia and solvent, then amide-ester crosslinks were formed. Various RPPS' were prepared by copolymerizing acrylate or methylacrylate esters of fluoroalkyl alcohols with carboxylic acid functional vinyl monomers. Crosslinking of final film was varied by controlling the initial mole ratios of carboxylate to oxazoline in poly-IPO when reacted with RPPS. The wettability of these films was compared using tilt angle measurements (more sensitive than theta c)....

Ma, Y., Cao, X., Feng, X., Ma, Y., Zou, H., Fabrication of super-hydrophobic film from PMMA with intrinsic water contact angle below 90 degrees

Tag: hydrophobic surfaces without low surface energy materials, polymer modification, selective solvent treatment

A super-hydrophobic film was created without the surface modification of low surface energy materials such as fluorides by synthesizing a polystyrene (PS)-PMMA film and treating with warm cyclohexane. The mixture of PMMA and PS was dissolved in THF to 5 wt%, then films were spin-cast to glass slides. Finally, the coatings were exposed to warm cyclohexane. The spin-cast films were initially transparent, but turned translucent following cyclohexane exposure, indicating the possible formation of micro-structures in the film by removal of PS. CAs with water as high as 154 degrees were reported.

Nakajima, A., Saiki, C., Hashimoto, K., & Wantanabe T., Processing of roughened silica film by coagulated colloidal silica for super-hydrophobic coating,Journal of Materials Science Letters 20, 1975-1977, (2001).

Tag: super-hydrophobic surfaces

This article discusses the production of two different silica films coagulated with collodial silica suitable for super-hydrophobic coatings. Tetraethyl orthosilicate (TEOS) and 36% hydrochloric acid solution were mixed with ethanol and stirred for 19 hours, then collodial silica were added. Two different silicas were employed: methanol-based collodial silica (MA-ST), and methylethylketone-based (MEK-ST). Pyrex plates were spin coated five times to produce ~500nm silica films. Next, an ethanolic solution of heptadecafluorodecyltrimethoxysilane was hydrolyzed by water. This silane solution was then evaporated and deposited on the silica films, producing hydrophobic coatings on glass plates. MEK-based collodial silica yielded lower degrees of sliding at all water drop masses. The transmission of 500nm light through the MEK-based coating was approximately 90%.

Nakajima, A., Abe, K., Hashimoto, K., Watanabe, T., Preparation of hard super-hydrophobic films with visible light transmission,Thin Solid Films 376, Issues 1-2, 140-143, (2000).

Tag: surface roughness, fluoroalkylsilanes

This article investigates super-hydrophobic coatings (contact angles greater that 150 degrees) due to the inhibition of snow sticking or water resistance. Surface roughness is necessary for hydrophobicity, but it induces scattering of light. In order to satisfy both hydrophobicity and light transmission, precise control of surface roughness is thus required. This requirement was achieved by the utilization of a sublimable compound and a fluoroalkylsilane coating.

Nakajima, A., Abe, K., Hashimoto, K., Watanabe, T., Invited Review Recent Studies on Super-Hydrophobic Films, Chemical Monthly 132, 31-41 (2001).

Tag: review article

Nakajima, A., Design of a transparent hydrophobic coating, Journal of the Ceramic Society of Japan 112 [10], 533-540, (2004).

Tag: review article

## Part II: Snow Loss, Dynamics and PV Array Effects

E. Andenæs, B. P. Jelle, K. Ramlo, T. Kolås, J. Selj, and S. E. Foss, “The influence of snow and ice coverage on the energy generation from photovoltaic solar cells,” https://www.sciencedirect.com/science/article/pii/S0038092X17309581 Solar Energy, vol. 159, pp. 318–328, Jan. 2018.

• Examines properties of snow with respect to reflectance (albedo) and spectral transmittance
• Examines common transmittance profile
• Snow loads and snowmelt risk assessment carried out
• Common challenges relating to snow and effects on material as well as architecture checked

D. Ryberg and J. Freeman, “Integration Validation and Application of a PV Snow Coverage Model in SAM,” . 2015. https://www.researchgate.net/profile/David_Ryberg2/publication/293605963_Integration_Validation_and_Application_of_a_PV_Snow_Coverage_Model_in_SAM/links/56b9bc0208ae39ea99072536.pdf

• builds on and integrates Marion's model into NREL's System Advisor Model (SAM)
• model is effective for reducing estimation errors for PV arrays
• estimates average snow loss in United States using the new functionality in SAM together with historical data set

B. Marion, R. Schaefer, H. Caine, and G. Sanchez, “Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations,” https://www.sciencedirect.com/science/article/pii/S0038092X13003034 Solar Energy, vol. 97, pp. 112–121, Nov. 2013.

• Measures energy losses due to snow for these areas for winter periods in two year
• Result shows 90% monthly energy loss due to snow, representing up to 12% annual energy loss
• Introduces new model and method for energy losses using variable factors such snow depth, irradiance and air temperature relationship, PV tilt angle and extent of snow coverage that affect PV power production
• Compares result of measured with modelled energy losses

R. W. Andrews, A. Pollard, and J. M. Pearce, “The effects of snowfall on solar photovoltaic performance,” https://www.sciencedirect.com/science/article/pii/S0038092X13000790 Solar Energy, vol. 92, pp. 84–97, Jun. 2013.

• Discusses effect of snow on PV performance using multi-angle and multi-technological approach
• Introduces a novel methodology for measuring snow losses on 5 minutes time series resolution
• develops new method for probability distribution of snow precipitation
• Results show snow loss dependencies on albedo, tilt angle and technology system typology deployed
• Improvement of system performance is contingent on proper snow loss assessment

R. W. Andrews and J. M. Pearce, “Prediction of energy effects on photovoltaic systems due to snowfall events,” in 2012 38th IEEE Photovoltaic Specialists Conference, 2012, pp. 003386–003391.

• Provides snow fall effects identification method
• Recommends a model for prediction of snow effects using meteorological time series
• Model validated with data from two existing large PV plants greater than 8 MW
• Daily and average snow effect was predicted for plants with low tilt angle

E. Lorenz, D. Heinemann, and C. Kurz, “Local and regional photovoltaic power prediction for large scale grid integration: Assessment of a new algorithm for snow detection,” https://onlinelibrary.wiley.com/doi/full/10.1002/pip.1224 Progress in Photovoltaics: Research and Applications, vol. 20, no. 6, pp. 760–769, 2012.

• Resolution of hourly weather forecast for a 2-day period deployed as a basic approach to predicting regional PV power
• Presents new and enhanced features of the regional power forecasting system of the Oldenburg University and the Meteocontrol GmBH
• New PV power prediction approach improves on existing overestimation of power production during snow cover
• Forecast for 1-year period was carried out
• Results show reduced root mean square error (rmse), from 4.9% to 3.9% and 5.7% to 4.6% for intra-day and day-ahead forecasts respectively
• Using proposed algorithm for snow prediction provides greatest reduced rmse in January

L. Powers, J. Newmiller, and T. Townsend, “Measuring and modeling the effect of snow on photovoltaic system performance,” https://files.zotero.net/16659715101/Powers%20et%20al.%20-%202010%20-%20Measuring%20and%20modeling%20the%20effect%20of%20snow%20on%20photo.pdf in 2010 35th IEEE Photovoltaic Specialists Conference, 2010, pp. 000973–000978.

• Provided a side by side PV test bed installed in California
• Gauges energy loss for different and most common tilt angles
• test result presented for a particular winter period

Ross, Michael., [http://www.rerinfo.ca/documents/trPVSnowandRime.pdf Snow and Ice Accumulation on Photovoltaic Arrays:

An Assessment of the TN Conseil Passive Melting Technology], Division Report EDRL 95-68 (TR), (1995)

A very comprehensive study into the effects of snow on PV performance. This study was performed with the focus of validating a new snow removal technology aimed at reducing snow losses in remote northern sites. It includes a excellent reveiw of snow types, accumulation methods and physical properties, and a full thermal model of a panel which was used to predict melt times for the panels. This model requires further validation in order to be universally applied, but handles well the many variables associated with the melting of snow from a panel.

D. Thevenard, K. Haddad Ground reflectivity in the context of building energy simulation, 2005---- Nabeil

A great overview of snow albedo and specularity. Done in the context of buildings simulations. -Includes models for specular albedo on sloped suefaces -Did a preliminary analysis and found that the snowfall can increase array performance by ~2.63% -For a building, can decrease heating load by 10.9% in a year

Use as reference for snow albedo numbers and correlations

---K.Hosokawa & T.Tomabechi, A study on the optimal installation of PhotoVoltaic systems in snowfall areas ---- Nabeil

they found 90 degrees to be the optimal angle for a system that was located at a similar latitude to us (actually slightly south). I think that it is hard to make any hard conclusions, however as they are mising a siginificant chunk of data for their system. Also, the author seems to confuse power and energy in some of the graphs. Its also interesing that his measured values for albedo on a vertical plane as a fraction of total global irradiation are close to those that I predicted theoretically in the report (25% predicted, 30% measured by the paper) however, they never explained how they measured this, so it is a bit dubious.

I do have a problem with the insolation vs. power (or energy?) curves, as they are very non linear, levelling off at at around 400w/m^2. This means that those panels that are operating near the optimal angle in the summer time do not have the abillity to correctly utilizse the greater insolation at these times, which means that the losses of the 90 degree panel will not be as great in the summer time (becasue the optimal panels are not operating well either) According to PV syst you should be loosing close to 45% of your summertime yeild and 32% of your wintertime yield at an agle of 90 degrees, which is not shown in the collected data. It can be seen that they never reached their rated yeild of 70W, even at 1200w/m^2

## Spectral effects

• Isc mismatch calculated from Isc at standard AM 1.5 and Isc for arbitrary spectrum E(lambda) extrapolated to 1000W/m^2, assuming spectral response is not effected by point of operation
• This mistatch can be large for a-Si (Possiblity that the spectrum for albedo reflection from old snow can cause poor performance in a:si due to albedo?)
• Used CM11 diffuse and global and a filtered glass to measure 'redness index' of the light
• Modules were stabalized by degredation for six months
• Fill factor showed a large amount of scatter in the low ranges of Isc, it is not at all constant across the range
• Scatter could also be due to environmental issues, eg. Snow
• Fill factor cannot be correlated to panel temperature
• Correlates to spectrum as the reason for the difference in fill factor, could also have to do with level of irradiance, as all diffuse are low irradiance and clear are high irradiance
• the diffuse data comes primarily at times of lower irradiance, so the same correlation could be shown between low and high irradiance. There is an interesting bit about scatter in the mid ranges of this curve, which might suggest some advantage of a bluer spectrum in this region, but there was no statistical analysis to back this up.

• A:si work better in summer: possibly becasue of heat soaking and their low stabilized efficiencies
• C:si work better in winter because tehre is no Staebler-Wronski effect
• Experimental setup used a spectroradiometer
• Modules remained at OC, worst case for stability, and were subjected to the AM1.0 spectrum while exposed to different temperatures.
• Isc, Voc, Tcell measured hourly
• 200h total time illuminated, 8h on 16h off
• Kratos solar simulater
• Winter, 20C summer, 70C
• Samples were annealed at 150C for 4h in dark to ensure they were at the same conditions.
• Data from an outdoors test site (panels tested on an indoors I-V tester) showed seasonal fluctuations, degredation over the winter and recovery in the summer caused by the Staebler-Wronsky effect.
• small defects may be annealed overnight, but are quickly re-created meaning that there is an overall degredation with time.
• 1h at 150C or 1000h at 50C to completely anneal a panel
• Shift in the solar spectrum towards red in the winter due to the higher AM, could lead towards lower efficiencies
• Pyranometer readings should be taken at periods of similar spectral distribution for comparsion, as the spectrum and therefore the response of the panel will sift between diffusivity, and AM through zenith angle
• Therefore, synthetic day algorithm should take into account both diffuse ratio and zenith angle when calculating synthetic days.
• Humidity is also a concern, as it effects the spectral distribution
• The seasonal effect likely has some effect from the annealing of defects, but more likely is due to shifts in solar wavelengths over time

• IEC 90891 can be used to transform outdoor data to STC
• seasonal ocilations can be due to spectral effects due to teh nearrower bandgap and anneling of the SWE
• Stabalization depends on operating conditions
• Experimental set-up 3 panels on a multitracer at 45 deg
• part was used on a tracker to eliminate AOI effects
• AM correction for pressure can be found in refs 12,13
• Efficiency corrected to AM1.5 as per refs 12-14, using a spectral mismatch factor
• IEC 60891 translation equations used to correct output to 25C
• 16 has a temperature threshold above which module improvment occurs
• Shows that panels can degrade in outdoors conditions

7-10 speak about factors effecting ground level radiation Used simulation to veiw the effects of turbicity, water vapour and AM on cell output for a:si is effected more by turbicity A:si is not effected by water vapour, as this effects things in wavelengths above its response a:si decreases with increasing AM, whereas crystalline increases with AM nice graph of spectral response

• study showing the effect of spectral variations with time, cloud cover etc. using a full year of spectral data
• Done in the UK, similar climactic conditions, inclined at 52 degrees
• argues that the seasonal variation can be related to spectral effects, not annealing phenomenon
• spectroradiometer, which scans over 2 minute intervals and has collected data for 5 years
• read 8 for PV measurements
• uses the Useful Fraction whihc is total irradiance within the spectrally responsive range to total irradiance (a:si 300-780 nm)
• Could be improved by utilizing an integrated value, weighted by the spectral response of the cell
• UF is a measure of teh "blueness" of the light, high UF could correlate to mainly diffuse, or incident with low air mass
• standard AM1.5 has a UF of 0.604
• in london, the UF is higher than average, its northern location has a high AM (up to 3.96) however is also cloudy 80% of the time, which shifts towards blue, increasing the UF
• spectral variations can lead to a summertime underestimation of 6-8% and a windtertime overestimation of 8%
• yearly effects may be masked, as they are generally an inverse with ambient temperatures, an effect which can actually cause positive temperature coefficients in the practical performance of these *devices
• by correcting for spectral effects, this can be reversed
• contains a good graph of useful irradiation

• 10 minute obervations over 30 months
• Hirata and Tani [9] did a study with 6 pyranometer filters, investigating teh difference between a-si and c-si devices
• Fabero and Chenlo used Isc to find the effects on a-si vs c-si
• Instrument can measure spectrum up to 1700nm
• system and spectrometer mounted at 52 degrees
• 10W/m2 or less are ignored
• non-linearity with respect to the response of multijunction a-si cells to spectral indluences
• spectral effects form both air mass and clearness index
• [14] talks about the effects of cloud cover
• In the summer, useful fraction increases in the morning and afternoon, as the radiaiton shifts from beam to diffuse
• In the winter, useful fraction decreases in the morning and afternoon
• The useful fraction is lower in the wintertime, which correlates with findings in { Seasonal variations in amorphous silicon solar module outputs and thin film characteristics}
• Cloudy days give a higher useful fraction for a-Si
• Useful fraction for a-si~0.6 in summer, 0.5-0.65 in winter

8Good graph of seasonal variation of useful fraction

## Global insolation modelling

• Generated models to predict the performance of PV arrays throughout canada.
• Used insolation data, mean precipitiation as an analoge to snow cover
• Multiple angles and tracking were consitered
• Large scale prediciotns are made based upon interpolation schemes, specific solar radiation models and satellite models
• Used thin plate smoothing sline algorithms, used by Hutchinson (1984) in australia
• Data collected from the CERES CD, containts global, direct, diffuse on horizontal and 31 tilted planes and a FTS plane
• after 1993 the data became lower quality with the introduction of automatic weather observing
• uses MAC2 (Davies) to estimate houlry radiation on horizontal , 5% error (McKay and Morris, 1985)
• Hay model used for tilted plane90 deg l-15 l+15
• optimal angles in Photovoltaic Systems Design
• Manual” Natural Resources Canada, 1991 or on the NASA SSE website
• Poissant et al. 2003 talk about factors effecting PV performance
• Has a graph showing PV angle optimization

## previous snow studies

Barriers to implementation of PV in japan because of presumed issues with snow cover

Many flat roofs in the area, making it more difficult to integrate PV

Describes the development of a wall mounted PV/Thermal panel

estimation of 10% loss due to snowfall at and angle of 31 degrees, however a 20% is expected for flush mounted panels. 60 degrees are quite small.

actual installation was at 80 degrees, because of architectural consraints

made 6 variations of the PV hybrid wallboards, measured the IV curve using loading device and multiplecers, recorded only MPP

measured the temperature output of the air passing over the panels

the amorphous were bad because of condensation,

efficiencies based on projected wall areas, not installed panel capacity

thermal outputs at 28C, 37C which provide about hald the daily heating requirements of a well insulated house (60MJ/day)

1. Janssen, E., Nixon, D., De Bruyn, S., Amdurski, G. and Hilaire, L.S., Long-term Impacts of Tilt Angle and Mounting Style on Photovoltaic System Snow Losses. https://www.researchgate.net/profile/Erik_Janssen/publication/333488852_Long-term_Impacts_of_Tilt_Angle_and_Mounting_Style_on_Photovoltaic_System_Snow_Losses/links/5cf02b054585153c3da793d3/Long-term-Impacts-of-Tilt-Angle-and-Mounting-Style-on-Photovoltaic-System-Snow-Losses.pdf

## Albedo effects

Excellent resource

errors associated with measurement of albedo, van den Broeke et al., 2004

theretical determinatns of spectal albedo a(lambda) made by wiscombe and warren

scattering is defined by absorbtion efficiency, scattering efficiency, and asymmetry factor, scattering is assumed to happen as spheres

in ice, scattering at ics-bubble boundaries

albedo can be dramatically effected by the inclusion of soot, dust is about 200 times less absorbent

we will be measuring spectrally integrated albedo

spectral albedo is 1 ish in UV and <0.4 in the infared region

grains increaseing decrease the likelyhood of a photon hittign an air-ice boundary and thus reduces albedo

soot decreaes albedo in the UV region

azimuth angle increases albedo because of increases in scattering near the top layer, and because snow grains are smaller at the top. there is a gerater increase in the IR region for albedo.

albedo for light in the bandgap of a:si is neary 1, lower abledos will be caused by a decreased reflection in the snortwave IR region

water increased effective grain size

diffuse radiaiotn effective zenith angle of 50 degrees

cloud cover reduces the IR radiation and increases UV and visible becasue of reflection

as the zenith angle decreases, diffuse fraction increases as diffuse decreases slower than direct

--1. Warren SG. Optical properties of snow. Rev. Geophys. ;20(1):PP. 67-89.; Shows albedo properties of snow in the solar (300-500-nm) and thermal infared (5000-40000nm) ranges

Bidirectional Refelction Distribution Function says how light is reflected from snow surface

albedo is the integral of the BRDF over all reflection angles

diffuse albedo is for hemispherically isotropic

spectrally integrated abledo(as) is measured by radiometers, which is in trun effected by teh spectrum of incoming light

spectral emissivity depends on emission angle and is equal to absorbtivity or coalbedo by Krichoff's law (siegel and Howell)

reflective coefficient in solar spectrum should be taken from WWI paper (1400nm-2800nm)

solar albedo shown to increase with zenith angle by Hubley, Lijequist, Russin, Bryazin and Kptev,Korff et al. and Carroll and Fitch

cloud cover normally increases albedo due to spectral shift, of 5%-10%

snow ageing is covered by holmgren, Grengell and Maykut, Grengell et al (1981)

excellent graph of albedo vs. wavelength

graph of albedo vs grain size for various wavelengths albedo is effected by grain size becasue refraction happens at ice/air interface, and absorbtion happens when travelling through ice. tehrefore larger grains means more travel through ice and fewer boundaries. 50 um new to 1mm old. dependance on density is likely a dependance on grain size

Impurities can decrease albedo, soot in quantities of 0.15ppm can decrease by >10%

trasmission through snow at a maximum of 460nm, where ki is its minimum

most of the absorbtion is in the near IR, however heat will be rejected more at teh surface because the ks is larger. therefore, the heat maximum in a snowpack can be some ways down in the snowpack.

albedo dependance on angle, the shallower the angle the scattering will occur closer to teh surface, also becomes asymmetric and forward scattered

there is some hysterysis between the morning and afternoon, likely due to teh melting of fine snow at the top of the snowpack over the day.

effect of cloud cover: changes zenith angle to effectively 50, usually increased spectrally integrated snow albedo, as clouds absorb IR

bidirectional reflectance function: the albedo is forward scattered with increasing solar zenith angle. Lots of good formulae for averaging solar flux over an azmuth

Infared emissivity of ~99% emmisivity=1-absorbtivity

graphs of emmisivity are there

snow temperature can be measured from its emmisivity, snow depth as well

Good reference for practical snow Albedo measurments, includes apparatus for albedo measurement as well as measurement of snow grain size.

wiscombe and warren are the guys who know most about optical properties

melting in spring because of increase of shortwave irradiance, increases density which decreases albedo

highly reflevtive to UV radiaion, causing snow blindness

snow can increase erythermal irradiance by up to 60%

uses albedometers which are sensitive in the 250-390 nm range

must account for azimuthal errors in albedo measurements

usedUV Biometer model 501, ventilated

also used a multichannel radiometer to measure UV albedo at various wavelengths

PAR is 400-700nm, same as a:si maybe use a PAR sensor to more accurately predict a:Si yeilds

talks about the calibration of the pyranometers for zenith angle, laboratory calibration was carried out but consitered unsatisfactory due to higher zentih angle

grain size was measured using sampes of snow on ascreen with mm-grid

noticed an albedo decrease right after midday, assumed to be the accumulation of liquid water in the snowpack, which then re freeezes or flows deeper into teh snowpack later in the day, causing the albedo to rebound.

also, daily variaitions causign a decreae in albedo between the morning and afternoon, possibly due to the accumulation of hoar-frost

grain size ahs a large effect on the level of albedo

global snow classes are defined in strum et al. ,1995

Reference for above article

--1. Choudhury BJ, Chang ATC. The albedo of snow for partially cloudy skies. Boundary-Layer Meteorol 1981;20(3):371-389.;

Reference for above article

--1. Meinander O, Kontu A, Lakkala K, Heikkilä A, Ylianttila L, Toikka M. Diurnal variations in the UV albedo of arctic snow. Atmos. Chem. Phys. 2008;8(21):6551-6563.; Good reference for practical snow Albedo measurments, includes apparatus for albedo measurement as well as measurement of snow grain size.

Graph of daily albedo shwoing zenith angle effects

## Optimal angles

optimal angle as a function of clearness index

Mathematical models for finding it.

## Spectral distribution modelling programs

--MODTRANS

Computationally heavy simulations package which is consitered to be a reference for these measurements


--SBDART

  Lightweight simulations package capable of simulating cloudy sky information


-SMARTS2

 Developed my NREL and used to generate ASTM AM1.5 standard spectra. Currently only performs calculations for clear sky phenomena.


--LBLRTM

 Developed by ARM, it is a line-by line radiative transfer model


--[Streamer]

  Based on the DISTORT code, can handle multiple cloud layers


--[Modtran5]

  Developed by U.S air force, extensively validated spectral modelling code.


--RRTM

 The rapid radiative transfer model (RRTM) is a validated, correlated k-distribution band model for the calculation of longwave and shortwave atmospheric radiative fluxes and heating rates. The Rapid Radiative Transfer Model for GCMs is an accelerated version of RRTM that provides improved efficiency with minimal loss of accuracy for application to general circulation models.

Page data
Authors Rob Andrews, Tyler, Adewale Aremu Adesanya 2009 CC-BY-SA-4.0 695 No main image Rob Andrews, Tyler, Adewale Aremu Adesanya (2009). "Snow effects on PV Lit review". Appropedia. Retrieved September 25, 2022.
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