Prospects of microwave remote sensing for snow hydrology

Transcription

1 Hydrologie Applications of Space Technology (Proceedings of the Cocoa Beach Workshop, Florida, August 1985). IAHS Publ. no. 160,1986. Prospects of microwave remote sensing for snow hydrology HELMUT ROTT Institute of Meteorology s Geophysics, University of Innsbruck, Austria Abstract Emission and backscattering characteristics of snow-covered terrain in the microwave region are briefly reviewed. The capabilities of past and present spaceborne microwave sensors in regard to snow cover monitoring are summarized. An outlook is given on the capabilities of microwave sensors on future satellites in respect to snow hydrology. Specifications are provided for an optimum microwave system for snow cover monitoring based on a multichannel imaging microwave radiometer and on a synthetic aperture radar system. Introduction Efficient monitoring of the snow cover is possible by use of satellite remote sensing methods, which are able to provide improved temporal and spatial coverage. For operational use in hydrology microwave techniques are very promising because microwaves are able to penetrate clouds and therefore to provide data on the snow cover in regular time intervals. Another advantage is the possibility to detect the depth and water equivalent of dry snow because of the penetration capability. However, while visible and infrared satellite data on the snow cover are in regular use for modelling and forecasting snowmelt runoff, the applications of microwave data in snow hydrology are still very limited. This is partly due to the experimental character of the relevant satellite missions and partly due to the system specifications which have not been optimum for snow applications. Recognizing the needs for improved snow cover monitoring in hydrology and water management, the capabilities of previous and present satellite microwave systems are reviewed and possibilities for improvements are discussed in this paper. The snow cover parameters of main interest for hydrology are the areal extent, the water equivalent, and the liquid water content (or at least qualitative information on the melting condition). The requirements of spatial resolution and temporal repetition rate cover a wide range depending on basin size and type and on the application (Herschy et al., 1985). Typical repetition rates are between 1 and 7 days, typical numbers for the spatial resolution are between 100 m and 1 km. Microwave Interaction with Snow Â" simplified illustration of microwave emission and scattering processes from snow covered ground is shown in Figure 1, neglecting atmospheric effects and multiple scattering. The measured brightness temperature may include contributions from the snow layer and from the underlying ground. The radiation emitted or reflected at the soil surface is absorbed and scattered in the snowpack in dependence of the wavelength and of the dielectric properties. A radar beam incident on snow covered terrain is scattered at the air/snow boundary, in the snow volume, and at the snow/ground boundary. For the interpretation of microwave emission and scattering it is essential to consider the magnitude of the different contributions which is 215

2 216 Helmut Rott dependent on the transmittance of the snowpack decribed by the penetration depth 6. For a uniform medium 6 is related to the extinction coefficient k By: 6 = 1/k where k is" given by* the absorption coefficient k a and the scattering coefficient k g : k g = k & + k g. E mission Scatter ing ML >k y? Snow Ground FIG.l Simplified illustration of emission and backscattering from snow-covered ground. T - brightness temperature of the snow-ground medium. T - emission at the ground surface. T - reflection at the ground surface. T s - emission due to volume scattering. 3 T - optical thickness of the snow layer. Scattering contributions : I - from the air/snow interface. s I (t) - volume scattering of the transmitted beam. v I* - from the snow/ground interface. I v (g) - volume scattering of I*. g I - I* after transmission through the snowpack. In case of wet snow the simplification k ~ k is possible at microwave frequencies because the absorption losses are significantly larger than the scattering losses. Due to the high dielectric losses 6 of wet snow is in the order of one wavelength only so that the soil contribution is of no

3 Microwave remote sensing for snow hydrology 217 relevance. This results in the following typical signatures of wet snow: The brightness temperature is comparatively high because wet snow radiates almost like a black body. The backscattering coefficient is low (apart from angles near specular reflection). For dry snow the penetration depth is 2 to 3 orders of magnitude larger than for wet snow. At 40 GHz (A =0.75 cm) 6 is less than 1 m, at 10 GHz (X = 3.0 cm) S is about 10 m. 6 is ^reduced by layering and inhomogeneities in the^snowpack. Backscatrering from a dry snowpack is insignificantly in the L- to X-band range ( < 11 GHz) where existing airborne and spaceborne SAR systems are operating. The contribution from the ground surface is dominating in the backscattering signal. Volume scattering effects are strongly increasing with frequency and at frequencies Ï 15 to 20 GHz backscattering and emission from a dry snow volume are significant. For mapping of snow-covered areas the discrimination against snowfree surfaces is of importance. This is illustrated in the Figures 2 and 3 showing typical microwave emission and backscattering signatures of snow-covered and snow-free ground at incidence angles 6 = 50 in dependence of frequency. The variability of natural targets may result in considerable scattering around the plotted curves. Considering the emission, dry soil and wet snow show little variation with the frequency and reveal similar brightness temperatures T,. For wet soil the T, -values are significantly lower and show an increase with frequency. For dry snow T, is decreasing with increasing frequency; the decrease depends on the thickness and density of the scattering snow layer and on the size of the scattering particles. The frequency-dependence of T,, which is derived from measurements at two or more frequencies > 15 GHz, enables clear discrimination of dry snow and can be related to the water equivalent of the snow layer. The backscattering coefficient o shows an increase with frequency 300 T b CK) ^ -" ss" **»" ^ Frequency (GHz) FIG.2 Typical values of the brightness temperatures at horizontal polarization and at an incidence angle of 50 for: (1) dry soil, (2) wet snow, (3) dry snow of different depth, (4) very wet soil.

4 218 Helmut Rott o cr CdB) Frequency CGHz) FIG.3 Typical values of the backscattering coefficient 0 at 50 incidence angle (parallel polarizations) for: (1) rough soil surfaces, (2) dry snow including different soil contributions, (3) smooth soil, (4) wet snow. for snow covered as well as for snow-free ground. Bare soil surfaces cover a wide range of o -values, depending on surface roughness and wetness. For frequencies s 10 GHz backscattering from soil covered with dry snow is clearly dominated from the soil contribution. At higher frequencies the increase of a is stronger for dry snow than for other targets. This might offer a possibility for dry snow mapping, but presently not sufficient experimental data are available on this problem. For a of wet snow considerable variability is found according to wetness, grain size, and surface roughness (Màtzler and Schanda, 1984), but a is usually lower than for most other surfaces with the exception of water and swamps. The discrimination between wet snow and snow-free ground is optimum in the 8 to 15 GHz range and at incidence angles S 25, at low frequencies smooth soil and wet snow surfaces may reveal similar a -values. Snow Mapping with Spaceborne Microwave Sensors Several active and passive microwave sensors with capabilities for snow and ice mapping have been operating on board of satellites. The active sensors (synthetic aperture radar, SAR, systems) operated on Seasat (from July to October 1978) and on Space Shuttle Flights (Shuttle Imaging Radar-A, -B). The technical characteristcs of these systems were far from the optimum for snow applications. The sensors operated in the L-band at 1.28 GHz (23.5 cm wavelength) in hh polarizations. The image resulotion was 25 m (4 looks) for Seasat and 40 m (6 looks) for SIR-A. For SIR-B the azimuth resolution was 25 m (4 looks), while the range resolution varied between 17 m and 58 m in dependence of the antenna look angle. Main differences in the SAR images resulted from the antenna look angle: 20 (off nadir) for Seasat SAR, 47 for SIR-A and selectable between 15 and 60 for SIR-B. A considerable number of scenes on glaciers has been acquired by the spaceborne SAR systems. Investigations of these data clearly demonstrated the significance for glaciological applications; some information of

5 Microwave remote sensing for snow hydrology 219 relevance for seasonal snow cover mapping was also obtained (Rott, 1984a, b). The wet snow surfaces on the glaciers revealed low backscattering values, but for a variety of snow-free surfaces (e.g. meadows, alluvial deposits, soil) similar values were observed. This shows that L-band frequencies are not suitable for snow mapping even in case of wet snow; dry snow cover is transparent at these frequencies. Information for the selection of the antenna look angle could also be derived. For application in mountain areas look angles around 50 degrees are favourable, strong geometric distortions limit the usefulness of SAR data at low incidence angles. More relevant information for the definition of a snow monitoring system was gained from an airborne SAR experiment mentioned in the next paragraph. The passive microwave imagers which have been operating on satellites revealed better capabilities for snow mapping than the radar systems. The best sensor for snow mapping hitherto has been the Scanning Multichannel Microwave Radiometer (SMMR) which was launched on Nimbus-7 in October 1978 and is still operating in As for any passive microwave system, a major drawback of SMMR is the limited spatial resolution which is determined by the antenna aperture. SMMR operates at five frequencies (6.6, 10.7, 18.0, 21.0, 37.0 GHz) in horizontal and vertical polarization and covers a swath of 780 km under an earth incidence angle of about 50 ; for full global coverage 3 days of SMMR operation are required. For snow, mapping the 18 GHz and 37 GHz channels are utilized, for which standard data (brightness temperatures) are produced for 60 x 60 km 2 cells (18 GHz) and 30 x 30 km 2 cells (37 GHz). This resolution is adequate for large scale climatology and for snow mapping in large drainage basins (> 10 5 km 2 ). Algorithms have been developed for mapping the areal extent and the water equivalent of dry snow. The onset of snowmelt and melting-refreezing snow can also be detected (Kùnzi et al., 1982). An empirical relation was derived between the SMMR brightness temperatures (the differences between the 18 GHz and 37 GHz channels) and snow water equivalent for test sites in Canada, Finland, and Southern Russia. The algorithm for the determination of the snow water equivalent was improved by Hallikainen (1984) who investigated the effects of major surface types in Finland on the brightness temperature of snow-covered areas. Forests, for example, mask partly the microwave emission from ground and snow so that different coefficients are used for the calculation of snow water equivalent from the SMMR data. An improvement for water equivalent determination can also be expected by including information on grain size, because microwave emission is dependent also on the size of the scattering particles. In the different investigations linear correlation coefficients of about R 2 = 0.75 were found between SMMR-derived and observed water equivalent. The SMMR algorithm can be applied only for water equivalent values i 150 mm, because of the limited penetration depth at 37 GHz. Definition of a Snow Cover Monitoring System The specification of a microwave system for snow cover monitoring was based on the following sources: the analyses of spaceborne microwave data from active and passive sensors (summarized in the previous paragraph), emission and backscatter measurements reported in the literature, an airborne SAR experiment on snow mapping, simulations of SAR image products. Systematic measurements on microwave emission and scattering from snow have been reported from the Institute of Applied Physics of the University of Berne (Mâtzler et al., 1980; Mâtzler et al., 1982; Mâtzler and Schanda, 1984) and from the University of Kansas Research Center (Stiles

6 220 Helmut Rott and Ulaby, 1980; Ulaby and Stiles, 1980a, b). However, only few backscatter measurements have been carried out at higher microwave frequencies (K-band). Detailed passive microwave measurements on snow have been reported also from the Helsinki Technical University (Tiuri and Schultz, 1980). While the conclusions from the spaceborne SAR experiments regarding snow hydrology were rather limited, an airborne experiment over an Alpine test site could provide more relevant data. During the European SAR-580 Experiment,conducted in June and July 1981 by the European Space Agency and by the Joint Research Centre of the European Communities, partly snow covered test sites in the Swiss (Mâtzler and Schanda, 1984) and Austrian Alps (Rott, 1984a; Rott and Domik, 1984) were surveyed with an airborne SAR operating in the X- (at 9.4 GHz) and L- bands (at 1.3 GHz) resp. in the X- and C- (at 5.3 GHz) bands. The experiments showed very clearly that melting snow cover can be mapped with X-band and C-band SAR. For parallel polarizations (hh or vv) discrimination of snow is possible at surface incidence angles between about 25 and 80 degrees (from the normal to the surface), while at cross polarizations snow mapping is possible also at angles < 25. However, due to the high power requirements the use of cross polarizations may not be practicable for spaceborne systems. Detailed specifications of a spaceborne SAR system for snow mapping were elaborated in a study for the European Space Agency (Rott et al., 1985). The study included a review of theory and experiments on backscattering from snow, the analysis of airborne and spaceborne SAR data, and a simulation task. The simulations considered effects of the antenna look angle, spatial resolution, and signal to noise ratio. The investigations resulted in the definition of a SAR sensor for wet snow cover monitoring: Frequency Polarizations Incidence angle Spatial resolution Range of Radiometric resolution Radiometric accuracy Image localisation Swath width Data turnaround X-band hh or vv 40 to 50 degrees 15 to 20 m, 1 look -25 db to 0 db 3 db for 15 m x 15 m 1 db (mean) 200 m km 6 h - 24 h (off nadir) (at -25 db) The simulations clearly indicated that spatial resolutions of at least 20 m are required in complex terrain because for snow mapping averaging over a number of pixels is necessary to reduce the speckle effect. Due to the required repetition rate for snow mapping, which is in the order of a few days, significant improvements over present SAR capabilities in regard to areal coverage are required. Even with two spacecrafts the temporal requirements cannot be met in case of narrow swath radars. Therefore wide swath systems would be necessary, where high resolution images can be selected for subareas in order to reduce the data rate. Compared to radar systems, microwave radiometers have the advantage of wide areal coverage and significantly lower data rates. However, for hydrological applications major improvements of spatial resolution over existing spaceborne radiometers are required. For passive microwave remote sensing of snow an imaging radiometer of the SMMR-type with constant earth incidence angle of about 50 and swath width of about 1000 km appears useful. The radiometer should include at least the following frequencies, dual polarization would be

7 Microwave remote sensing for snow hydrology 221 useful: one frequency in the 15 to 20 GHz range, one freqency in the 35 to 40 GHz range, one frequency at about 90 GHz. Improved determination of snow water equivalent and information on the metamorphic state can be expected if 3 frequencies below 40 GHz (at about 15 GHz, 25 GHz, 38 GHz) are employed. The 90 GHz frequency is of interest for mapping snow extent because better spatial resolution can be achieved than at lower frequencies. However, dense clouds and precipitation mask the surface signals in this channel, while at frequencies 40 GHz snow mapping is possible under almost all weather conditions. Spatial resolutions of at least 10 km should be achieved in the 20 to 40 GHz range, and 5 km for the 90 GHz channel. These requirements appear realistic when the present sensors are considered. Further improvements are highly desirable and should be possible by the development of aperture synthesis techniques. Snow Monitoring Capabilities of Future Spaceborne Microwave Systems During the next decade microwave remote sensing will gain a leading position withing earth observation. A variety of active and passive microwave systems are planned, but the prospects for hydrological applications are not too optimistic. Apart from short-term missions on Space Shuttle Flights the launch of SAR systems is planned for 1989 and 1990 on the following satellites: the ESA Remote Sensing Satellite (ERS-1), the Japanese Earth Observation Satellite (J-ERS-1), and the Canadian RADARSAT. The specifications of the SAR systems of ERS-1 (Joyce et al., 1984) and J-ERS-1 (Fukai et al., 1984) are not favorable for snow mapping. The ERS-1 SAR is designed for ocean and sea ice applications and will operate in the C-band (at 5.3 GHz), the swath width will be 80 km and the incidence angle at the swath's center will be 23 off nadir. At this angle ambiguities exist in the radar return of wet snow and other surfaces; moreover, the use in hilly and mountainous areas will be restricted due to strong geometric distortions. Also the foreseen radiometric sensitivity of -18 db may not be sufficient for the low return signal of wet snow. The SAR system of J-ERS-1 will operate in the L-band which according to the backscattering properties is not useful for snow mapping. The swath width will be 75 km, the incidence angle 33. RADARSAT will be dedicated to ice mapping, coastal zone surveys, and various land applications. The system has not yet been finally approved; it will operate in the C-band, provide a spatial resolution of 25 m and should be able to provide images within a ground range distance of about 500 km (20 to about 45 incidence angle). Because of the wide coverage this system could be of interest for snow cover monitoring. Regarding the passive microwave systems the prospects for snow monitoring are better. The main restrictions of these sensors result from the spatial resolution; the data dissemmination problem has also to be solved. In 1986 a scanning microwave radiometer, the Special Sensor Microwave/Imager (SSM/I) will be launched on the US Air Force DMSP satellite, a similar system is foreseen for the US-Navy N-ROSS (Navy Remote Sensing System) in The 19.35, 37 and 85.5 GHz channels of SSM/I are of interest for snow mapping, the spatial resolutions of the channels will be approximately 50 km, 25 km, and 15 km respectively. The swath width of 1400 km provides twice daily coverage at higher latitudes, so that the system is of considerable interest for large scale snow mapping. However, since DMSP and N-ROSS are military satellites, it is unlikely

8 222 Helmut Rott that hydrological users in various countries can rely on these data for operational programmes. A real operational passive microwave system, the advanced microwave sounder unit (AMSU) is planned for the next generation of the NOAA satellites to be in operation after about 1990 (Staelin, 1984). Though AMSU is designed for atmospheric sounding, some of the channels are also of interest for earth surface observations. AMSU will probably consist of two sub-systems: AMSU-A with 15 channels between 23 and 90 GHz and about 50 km footprint size and AMSU-B with 5 channels between 90 GHz and 183 GHz and about 15 km footprint size. For snow mapping two channels below 40 GHz and a window channel at about 90 GHz could be applied. The improved resolution of the AMSU-B 90 GHz channel is of interest for snow mapping, however, the final decision on the incorporation of AMSU-B in the NOAA system has not yet been made. Conclusions Microwave sensors offer unique capabilities for snow cover monitoring. However, the technical and operational characteristics of existing and planned microwave systems up to the early 1990's are aiming at other applications and the prospects for use in snow hydrology are not promising. Moreover, for the operational use long-term continuity of data acquisition and fast data delivery are of vital importance. In view of the potential of satellite systems for monitoring not only the snow cover, but also other hydrological elements, a satellite system dedicated to hydrology and water management would be highly desirable (Herschy et al., 1985). For such a system a multispectral imaging microwave radiometer is certainly a prime candidate, which can be used for monitoring extent and water equivalent of dry snow, precipitation, cloud liquid water content, and soil moisture. The spatial resolution of the sensor should be at least in the order of 5 to 10 km, and further improvements are desirable. SAR systems would be required for supplementing the radiometers for wet snow cover mapping and for applications in complex terrain where the spatial resolution of passive sensors may not be sufficient. The capabilities of SAR for wet snow monitoring are known, the possibilities for dry snow mapping are only speculative and certainly major changes of existing SAR systems, in particular in regard to the sensing frequencies, would be required. But also a system for mapping the wet snow cover with sufficient temporal and spatial resolution could be valuable, because for snowmelt runoff the boundaries of the snow areas during the melting season are of high interest and these should be detectable with X-band SAR. References Fukai, M., et al., 1984, Some test results of synthetic aparture radar transmitter and receiver: Proc. IGARSS'84, ESA SP-215, p Hallikainen, M.T., 1984, Retrieval of snow water equivalent from Nimbus-7 SMMR d^ta : effect of land-cover categories and weather conditions: IEEE J. of Oceanic Eng., Vol. OE-9(5), p Herschy, R.W., Barrett, E.C. Roozekrans, J.N., 1985, Remote Sensing in Hydrology and Water Management: Final Report, EARSeL WG10, European Space Agency, Paris, 225 p. Joyce, H., Cox, R.P., Sawyer, F.G., 1984, The active microwave instrument for ERS-1, Proc. IGARSS'89, ESA SP-215, p Kùnzi, K., Patil, S., Rott, H., 1982, Snow cover parameters retrieved from Nimbus-7 Scanning Multichannel Microwave radiometer (SMMR) data, IEEE Trans. Geosc. Rem. Sens., Vo. GE-20, p Mâtzler, C, Schanda, E., Hofer, R., Good, W., 1980, Microwave

9 Microwave remote sensing for snow hydrology 223 signatures of the natural snow cover at Weissfluhjoch. Microwave Rem. Sens, of Snowpack Properties, NASA Conf. Publ. 2153, p Mâtzler, C, Schanda, E., Good, W., 1982, Towards the definition of optimum sensor specifications for microwave remote sensing of snow. IEEE Trans. Geosc. Rem. Sens., GE-20, p Mâtzler, C, Schanda, E., 1984, Snow mapping with active microwave sensors. Int. J. Remote Sens., 5(2), p Rott, H., 1984a, The analysis of backscattering properties from SAR data of mountain regions, IEEE J. of Oceanic Eng., Special Issue on Microwave Signatures of the Sea, Sea Ice, and Snow, Vol. OE-9(5), p Rott, H., 1984b, Synthetic aperture radar capabilities for snow and glacier monitoring, Advances in Space Research, 4(11), p Rott, H., Domik G., 1984, The SAR experiment on snow and glaciers at the Austrian test site, Final Report of the European SAR-580 Campaign, JRC, Ispra, Italy, in press. Rott, H., Domik, G., Mâtzler, C., Miller, H., 1985, Study on use and characteristics of SAR for land snow and ice applications, Final Report to ES A, Mitteilungen des Instituts fur Météorologie und Geophysik, Universitât Innsbruck, Nr. 1 (1985). Staelin, D.H., 1984, Passive microwave remote sensing of the atmosphere, Proc. IGARSS'84, ESA SP-215, p Stiles, W.H., Ulaby, F.T., 1980, Radar observations of snowpacks. Microwave Remote Sensing of Snowpack Properties, NASA Conf. Publ. 2153, p Ulaby, F.T., Stiles, W.H., 1980a, The active and passive microwave response to snow paramters, 2, water equivalent of dry snow, J. Geophys. Res., 85(G1), p ~~ Ulaby, F.T., Stiles, W.H., 1980b, Microwave radiometer observations of snowpacks, Microwave Remote Sensing of Snowpack Properties, NASA Conf. Publ. 2153, p Tiuri, M., Schultz, H., 1980, Theoretical and experimental studies of microwave radiation from a natural snow field, Microwave Remote Sensing of Snowpack Properties, NASA Conf. Publ. 2153, p

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