Retrieval of Snow Water Equivalent from Nimbus-7. SMMR Data: Effect of Land-Cover Categories and. Weather Conditions. (Invited Paper). Abstract-The effect ...
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IEEE JOURNAL OF OCEANIC ENGINEERING, VOL. OE-9, NO. 5 , DECEMBER 1984
Retrieval of Snow Water Equivalent from Nimbus-7 SMMR Data: Effect of Land-Cover Categories and Weather Conditions (Invited Paper) Abstract-The effect of thefourmajorsurface types in w a n d (forests,boglands,farmlands, and water (ice))onthemicrowave brightness temperature of snow-covered areas is investigated. Nimbus-7 ScanningMultichannelMicrowaveRadiometer ( S m ) d a h are employedto derive theresponse of eachsurfacetype. An algorithmto SMMR d a b is retrieve the water equivaknt of snow cover from Nimbus-7 tested in different dry snow conditions.
I. INTRODUCTION HE NIMBUS-7 satellite carries a Scanning Multichannel TMicrowave Radiometer (SMMR) that is used to map the brightness temperature of Earth. The frequencies are 6.6, 10.7, 18.0, 21 .O, and 37.0 GHz. Ateach frequency, both horizontally and vertically polarized microwave radiation are measured. The conical scan covers a swath width of 780 km with a local incidence angle of 50”. The surface resolution varies from 151 X 97 k m 2 at 6.6 GHz to 27 X 18 km’at 37 GHz. More technical information aboutNimbus-7andthe SMMR is provided in the Nimbus-7 User’s Guide [ 11. Nimbus-7 SMMRdata have provedto be a valuable tool for remote sensing of snow. Snow is important to hydrology, agriculture, weather, and climate. In order to increase the accuracy of forecasts in these fields, high-qualitysnow information is needed. It has been concluded that this need may be met bestin the future using remote-sensing techniques in combinationwithconventionalsnow-surveyingmethods [a-
Microwave remote sensing has some advantages that make it particularly useful for snow mapping. The first advantage of using microwaves insteadof optical or infrared waves is their capability to penetrate dry snow. This offers achance to measure the depth and water equivalent of dry snow cover. The second advantage relates to the capability of microwaves to penetrate clouds. There are several atmospheric transmission “windows” in the visible, infrared, andmicrowave regions available for satellite observations of ground. Only microwavescanbeusedundercloudy conditions. Cloud attenuation in the microwave region, especially in the lower frequency range, is orders of magnitudesmallerthanthe attenuation in the visible and infrared regions. This is important for snow mapping whichrequires successive observations in order to monitor the changes in the snow depth and Manuscript received March 2, 1984; revised July 3, 1984. The author is with the Radio Laboratory, Helsinki University of Technology. 02150 Espoo, Finland.
water equivalent. The number of clear days in Finland varies from 20 to 70 per year. The physical basis of passive microwave remote sensingof snow is volume scattering by snow,particles. The microwave brightness temperature ofsnow-covered terrain hasbeen found to decrease with increasing snow thickness in prairie areas [3]. The decrease is a result of volume scattering by snow particles and has been observed for dry snow only. This relationship has been employed to derive the water equivalent of snow cover on a global basis using Nimbus-7 SMMR data [41. The effect of surface type on the brightnesstemperature has been investigated previously to some degree. By subtracting the influence of trees, a linear inverse relationshipbetween the residual brightness temperature at 37 GHz andthe thickness of snow cover up to 80 cm has been obtained [SI. Forested areas have been found to lower the difference between the brightness temperatures at 18 and 37 GHz compared to the values observed for areas witha substantial fraction of farmland, bogland, or water [6]. The first satellite-derived snow water equivalentmaps of Finland have beenproducedusing an algorithm that accounts for different surface types [7]. The algorithm included four constants, the values of which were determined through trial and error. In this paper, the effect of the four major surface types in Finland-forests, boglands, water(ice-covered lakes and rivers), andfarmlands-on the brightness temperature of snow-covered areas is investigatedandthemicrowaveresponse ofeach surface type is derived. Nimbus-7 SMMRdata at 18 and 37 GHz (horizontal polarization) for February and March 1979 are employed. The effect of the thermal history of snowon the microwaveresponseofsnow-coveredareasis examined for thetwo extremes of dry snow conditions,namely before and after a major melting-refreezing process. Two institutions in Finland report snow-related data. The water equivalent of snow cover is measured manually by the Hydrological Office of the National Board of Waters in about 160 locations twice amonth. The Meteorological Institute reports the following data every day: the temperature of air several times a day (40 inland locations), the daily precipitation(40 locations), the number of sunshine hours (25 locations), and the temperature of ground at depths of 20, 50 and 100 cm (8 locations). All measurements reported by the Hydrological Office are made on land. Usually the water equivalent of snow cover is
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HALLIKAINEN:RETRIEVAL OF SNOW WATER EQUNALENT FROM NIMBUS7 DATA
substantially smaller on lakes than on land. This is mainly due to the formation of snow ice. Since no data concerning the snow cover on lakes are available, the true value for the microwave response of snow upon ice-covered lakes cannot be derived in this study.
II. WATER EQUIVALENT ALGORITHM Kiinzi et al. tested seven different algorithms to retrieve the
Est i n a t o d (TIIH-T~H)Dw:
1 c-1OK 2 -lOK 0 -6K
snow depth and snow water equivalent from Nimbus-7 S " R data [4]. The algorithms employed either a single SMMR
channel or the difference between the results from two channels. Both vertical and horizontal polarization were included. The algorithms were tested against groundtruth data for Finland, Alberta, Canada, and Southern Russia. The highest overall linear correlation coefficient R Z = 0.73 was obtained using the difference between the brightness temperatures at 18 and 37 GHz for horizontal polarization, denoted here by T I ~H T37~. Fig. 1. Difference in the brightness temperature between 18 and 37 GHz for Using T18~- T37H, the linear correlation coefficients for snow-free terrain in Finland (Nibus-7 S " R data for November 1979, horizontal polarization, look angle 50"). 0.56, Finland, Alberta, Canada, andSouthernRussiawere 0.71, and 0.66, respectively. An obvious reason for the low and value for Finland is the presence of a variety of surface types In (l), W , is the water equivalent of snow cover, and T18H T37H are the brightness temperatures at 18 GHz and 37 GHz, in Finland, as compared with the more homogeneous areas in respectively. The values of T1SH - T37H for snow-free terrain Alberta Canada, and Southern Russia. The effect ofmixed surface types to the brightness temperature of snow-covered were obtained for each area from the Nimbus-7 SMMR data terrain has been studied to some extent previously [6]. It was for early and mid-November 1978. The total AT response from eachresolution cell on the found that forests mask partly the microwave emission from ground can be divided into a summation of responses from the the ground. About two thirds of Finland is covered by forests, four major surface types consisting mainly of pine andspruce. One fourth is boglands, whichmayvary from wet sparsely forested areas to open AT(Wq)=fFoATFo(w q > +fBATB(weq) wetlands. Boglandsare located mostly inCentral and Northern +fWATw(Weq)+fFATF(weq). (2) Finland. In SoutheasternFinland, lakes cover about one fourth of the area. Farmlands are located in Southern Finland. They In (2), f is the surface-type fraction within the resolutioncell, cover 7 percent of the total area. and Fo, B, W , and F refer to forest, bogland, water, and At the present, the effect ofvegetationcanopieson the farmland, respectively. The fractions of boglands, waterbrightness temperature of terrain istheoretically notwell covered areas, and farmlands are available from recently known. Therefore, SMMR data before the first snow fall in digitized surface-type mapsofFinland [8]. Forests are late 1978 were used to check for this effect. Days without any assumed to cover the rest of each resolution cell in Southern precipitation were selected and values for TlgH - T3,, were and Central Finland obtained for each area shortly before the first snow fall. It was found that TIsH- T37H varies from about - 12 K in the Lake f F o = 1- ( . f . . + f W + f F ) . (3) District to + 8 K on the West Coast (fraction of forested areas In fact, f F o from(3) includes also urban areas, roads, and small), as illustrated in Fig. 1. On the coast, overlapping waste lands but their effect is neglected. In Northern Finland, footprints including land and sea were not used. No values the land gradually changes into tundra for the northernmost could be obtained for northernmost Finland, because it was part. Hence, (3) does not hold there. The change is compenalready covered with snow. It is obvious from Fig. 1 thatT I g H sated in the algorithm by increasing the AT response of - T37Hfor each area before the first snowfallshouldbe forested areas in Northern Finland, as discussed in Section m. included in the algorithm as a reference value from which the The value of AT( W& for each resolutioncell (60 x 60 k m 2 change in T18~- T37~iS observed. for both 18 and37GHzin this study) is obtainedfrom Consequently, the algorithm to retrieve the water equivalent Nimbus-7SMMR data. Iftheindividualresponseofeach of dry snow cover is the following. The algorithm employs the major surface type is known, the water equivalent can be difference in the brightness temperature between 18 and 37 solved from (2). The water equivalent from (2) is unambiguGHz for snow-covered terrain (horizontal polarization), com- ous as far as the individual responses are unambiguous. pared with the corresponding value before the first snow fall: III. EFFECT OF SURFACE TYPES AND THERMAL HISTORY OF SNOW AT(weq)= [Tl8H( - T37H(Weq)l
weq= o)].
- [ TMH( w q = 0)- T37~(
(1)
Using Nimbus-7 S " R data, the algorithm from (2) was applied to two cases, namely February 15-21, 1979, and
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March 17, 1979. The ATresponse of the major surface types was optimized using the least-squares method
TABLE I OFTIMIZED AT RESPONSES TO SNOW WATER EQUIVALENT (4) FOR THE MAJOR SURFACE TYPES (14 TESTAREAS, FEBRUARY 15-21 AND MARCH
17,1979)
N
[ATi,,Obs(Weq)- AT,,pred(Weq)l2=lnhimum. i= 1
.
(4)
Response AT/ W, Surface Type
Wwl
In (4), the predicted value ATi,preafor each resolution cell (N Forest 0.185 Bogland = 86 in Finland) was calculated as asummationofthe 0.35 Farmland 0.37 individual responses withthesurface-typefraction as a Water 0.49 weighting function. February 15-21 and March 17 represent the two extremes in dry snow conditions within the period covered by the Nimbus7 SMMR data. The long cold period in January and February Biweekly Snow Woter Equlvolent(Finnish Hydroprevented the accumulatedsnow from going through the logicolOffice] and Doily Precipttation [Finnish melting-refreezing process. Therefore, the snow density was Meteorological Institute] -2.m lowand the particle size small in the wholecountryon February 15-21, 1979. SMMR data from several passes were averaged to decrease the scatter. For March 17, SMMR data from only two passes were used. This was due to a warm period that lasted in Southern FinlanduntilMarch15. No Nimbus-7SMMR data were available beyondMarch 17, 1979. The length of the warm period in March varied from 16 1 16 1 16 1 16 two days in Northern Finland to ten days in Southern Finland. )ecernber Jonuory Februory March Obviously, this caused the snow density and particle size to Dote 11978 - 7 9 ) increase at least in Southern Finland. The ground truth was Fig. 2. Manually measured snow waterequivalentat four locations in obtained from water equivalent maps, compiled by the Finland in 1978-1979. Hydrological Office. Maps describing the situation on February 16 and March 16, 1979 were used. The average value of Look Angle 500 Horizontal Polarization W, was 90 mm on February 16 and 110 mm on March 16. Density of Snow 0.3 tjcm3 The development of the water equivalentof snow cover at four Boundary -- Plane Bottom Rouah.RMS 0.3 meteorological stations in Finland is shown in Fig. 2. Theoretical calculations for the brightness temperature of snow-covered terrain were made to estimate the magnitude of the A T response as a function of water equivalent. Since the effect of vegetationcanopies to the brightness temperature was not considered, the calculations correspond to the situation for snow-covered farmlands. The theoretical model treats the I I snow cover as a layer of spherical Rayleigh scatterers with a 0 1M 200 3w rough bottom [9]. As illustrated in Fig. 3, the theoretical T I g H Water Equivalent (mml - T 3 7 depends ~ strongly on both water equivalent and snow Fig. 3. Theoretical brightness temperature difference between 18 and37 GHz for snow-covered terrain (horizontal polarization) as a function of particle diameter. The results suggest that T I w - T37H snow water equivalent, with snow particlediameter d as a parameter. saturates around W, = 100 mm, depending on snow particle diameter. Since both the snow particle sizeandthewater equivalent of snow cover usually increase with time, the AT the Hydrological Office) in Fig. 4. In order to check for local response in practice does not follow any of the curves with a variations, Finland was divided into three regions. Especially fixed snow particle diameter d in Fig. 3. Rather, it may start for March 17, there is no clear trend in the A T values. This by following the curve for d = 0.5 mm for small values of means thatthe water equivalent cannot be determinedfiom.AT W, and finally reachthe curve for d = 1.25 mm after several without accounting for the effect of surface types. melting-refreezing processes. The optimized AT responsesofmajor surface types for The initial valuesfor the optimization process were obtained February 15-21, 1979, are linear and do not show any local using 14 test areas for the two dates. The responses shown in variations or saturation, as illustrated in Fig. 5. The values are Table I were obtained from (4) with N = 14. Using these slightly lower than the initial values in Table I. A comparison initial values, the responses were optimizedseparately for between the observed andcalculated water equivalent values is February 15-21 and March 17, 1979. For each surface type, shown in Fig. 6. The linear correlation coefficient is R 2 = the response as a function of water equivalent was allowedto 0.70. be either linear or piecewise linear (with slight saturation). For March 17, the optimized ATvalues are shown in Fig. 7 The observed A T values for the two dates are shown as a and a comparison between the observed and predicted water function of the observed water equivalent values (compiledby equivalentvaluesin Fig. 8. The optimizedresponses for E
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HALLIKAINEN: RETRIEVAL OF SNOW WATER EQUIVALENT FROM NIMBUS7 DATA
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Fig. 5 . Optimized AT response to snow water equivalentfor major surface types (February 15-21, 1979).
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Fig. 7. Optimized AT response to snow water equivalent for major surface types (March 17, 1979) in (a) Southern Finland, (b) Central Finland, and (c) Northern Finland.
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8. Comparison of calculated and observedwaterequivalentvalues. Linear correlation coefficient R Z = 0.76 (March 17, 1979).
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IEEE JOURNAL OF OCEANIC ENGINEERING, VOL. OE-9, NO. 5 , DECEMBER 1984
Southern Finland are considerably higher than for Northern percent smaller than in Southern Finland.According to Finland. This is believed to be due to different snow particle theoretical calculations, this corresponds to a difference of sizes, causedby the difference in the lengthof the warm about 0.15 m in the snow particle diameter. period in early March. The linear correlation coefficient for f ) The values for the linear correlation coefficient, R 2 = 0.70 for February 15-21 and R Z = 0.76 for March 17, are March 17 is R 2 = 0.76. The optimized response for farmland inFigs. 5 and 7 canbe close to the overall value of R 2 = 0.73 reported by. Kiinzief compared withthe theoretical curves in Fig. 3. The agreement al. for Finland, Alberta, Canada, andSouthernRussia [4]. is good, when the theoretical results for asnow particle Therefore, the effect of the surfaceaver nonhomogeneity in diameter of 0.8 to 0.9 mm are used. This is a common value in Finland could be removed by using the present algorithm. g) The accuracy ofsatellite-derivedwater equivalent values Finland. the The effect of the inaccuracy of (3) in Northern Finland was can be increased substantiallywithinformationabout compensated for by increasing the response for forested areas. efficient snow particle size. This could be obtained with an Starting from latitude 64’, the response was increased linearly additional radiometer onboard a satellite, operating ata until, at latitude 68”, it was equal to that of boglands. The frequency higher than 37 GHz. The accuracy can also be correction was made for both February 15-21 and March 17, increased by adjusting the magnitude of satellite-derived valuesusing W, valuesmeasuredmanually at selected 1979. locations in Finland. CONCLUSIONS REFERENCES A snow water equivalent algorithm that accounts for the presence of various surface types was discussed. The alC. R. Madrid, Ed., The Nimbus-7 User’s Guide. Greenbelt, M D : NASA Goddard Space Flight Center, 1978. gorithm was applied to two cases that represent the extremes in A. Rango and B. Hartline, Eds., Plan of Research for Snowpack dry snow conditions within the period covered by the NimbusProperties Remote Sensing-(PRS)2;Recommendations of the 7 SMMR data, namely February 15-21 and March 17, 1979. Snowpack Propertie Working Group. Greenbelt, MD, NASA Goddard Space Flight Center, 1982. For February 15-2 1, most ofthe snow accumulatedso far had A. Rango et al., “The utilization of spaceborne microwave radiometers never gone through a melting-refreezing process. The length for monitoring snowpackproperties,” Nordic Hydrology, vol. 10, p p . of the warm period in early March varied from two days in 25-40, 1979. K.Kiinzi, S. Pat&and H. Rott, “Snow-coverparametersretrieved Northern Finland to about ten days in Southern Finland. The from Nimbus-7 scanning multichannel microwave radiometer (SMMR) microwave response of each major surface type-forest, data,” IEEE Trans. Geosci. Remote Sensing, vol. GE-20, pp. 452bogland, farmland, and water-was optimized separately for 467, 1982. D. K. Hall, J. L. Foster, and A. T. C. Chang,“Measurementand the two cases, allowing local variations. The results suggest modeling of microwave emission from forested snowfields in Michithe following conclusions. gan,” Nordic Hydrology, vol. 13, pp. 129-138, 1982. a) The AT response to snow water equivalent isconsideraM. Tiuri and M. Hallikainen, “Microwave emissioncharacteristics of snow-mvered Earth surfaces measured byNimbus-7 satellite,” in bly lower for forests than for other surface types. This can be Proc. l l t h Eur. Microwave ConJ (Amsterdam, The Netherlands), expected because forests mask partly the emission from the Sept. 1981. ground and snow. M. Tiuri and A. Sihvola, “Remote sensing of snow depth by passive microwave satellite observations,” in Digert 1982 Znt. Geoscience b) The AT responses for farmland and bogland are practiand Remote Sensing Symp. (IGARSS’82) (Munich), June 1982. cally the same. The response for boglands represents an M. Hallikainen, M. C. Dobson, and S. Moezzi, “Influence of surface average value. In fact, the local response may vary practically type on the brighmess temperature of snow-covered terrain,” in Proc. URSI Commission F/ESA Symp. Wave Propagation and Remote from that for forests (sparsely forested boglands) to that for Sensing (Louvain-la-Neuve,Belgium), June 9-15, 1983, pp. 273water (open wetlands). 279. c) The AT response of water-covered (ice-covered) areas is A. K. Fung and H. 3. Fmm, “Emission from a Rayleigh layer with irregular boundaries,” J. Quant. Spectrosc. Radiat. Transfer, vol. highest. Since W, is always measured on landbythe 26, pp. 397-409, 1981. Hydrological Office, whereas W, on lake ice may be 30-50 percent of that on land, the optimized AT response for watercovered areas is not the true value. The response gives the value that applies to land. In order to compare the satelliteMartti T. IIallikainen (”83) was born in derived W, values with those measured by the Hydrological Savonlinna,Finland, on January 29, 1946. He Office, this procedure was necessary. received the degrees of Diploma Engineer (MA.) d)Aslight saturation in the AT response wasfound to andDoctorofTechnology in 1971, and1980, respectively, both inelechid engineering from the occur for all surface types around W, = 100 mm depending HelsinkiUniversity of Technology, Espoo, Finon the snow particle size. This is in agreementwith the land. theoretical calculations. From 1Wl to 1974 and 1975 to 1981, he was a Research and Teaching Assistant with the Helsinki e) The thermal history of snow cover has an influence on University of Technology. In 1974-1975, he was a the AT response of all surface types. For March 17, three Fulbrighc Grantee at -&e University of Texas, separate sets of response parameters were needed, obviously Austin. From 1981 to 1983, he was a Visiting Scientist at the University of because of the difference in the length of the preceding warm Kansas Center for Research, Inc. Since 1984, he has been with the Helsinki University of Technology. His interests include microwave remote sensing period in the south-north direction. For March 17, the and dielectric measurementsof natural media. Dr. Hallikainen is thesecretary response of each surface type in Northern Finland is about30 of the Finnish National Committee ofURSI.
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