Microwave Remote Sensing with Bhaskara-I

Transcription

1 Indian Journal of Radio & Space Physics Vol. 12, October 1983, pp Microwave Remote Sensing with Bhaskara-I & II Satellites P N PATHAK, P S DESAI & T A HARIHARAN Meteorology Division, Space Applications Centre (ISRO), Ahmedabad Received 22 April 1983 The.nain scientific applications of the satellite microwave radiometer (SAMIR) systems flown onboard the two Indian satellites Bhaskara-I and II are reviewed. After a brief resume of the fundamental ideas on microwave remote sensing together with a short summary on the historical development of microwave remote sensing from space, the main characteristics of the two SAMIR systems are described and results on their in-orbit performance presented. The scientific applications of the data from the two SAMIR systems are then reviewed in two broad areas-meteorology and oceanography. 1 Introduction Remote probing of the earth's atmosphere and ocean surface using electromagnetic radiation in the microwave region, has long been recognized as a powerful tool for meteorological and oceanographic applications. The technological advances in the performance of radiometers, scatterometers, altimeters, radars, etc. have widened considerably the scope of these applications to include earth resources surveys. Significant efforts are being made in the country in the development and utilization of microwave remote sensing techniques. India's two eperimental satellites for earth observation (SEO-I and II, later named Bhaskara-I and II), carried onboard, passive microwave radiometer systems called SAMIR (satellite microwave radiometer). This paper attempts to review the several eploratory scientific investigations that have been made using the SAMIR data from the two Bhaskara satellites. The present review considers the work carried out till the end of February In section 2, the fundamental ideas on microwave remote sensing are briefly discussed together with a short historical background on microwave radiometry from space. Section 3 gives details regarding the Bhaskara satellites and their onboard SAMIR systems, followed by a brief account of the in-orbit performance of SAMIR through an analysis of temperature sensitivity and spatial resolution. In section 4, the scientific applications of the SAMIR data are discussed in different sub-sections depending on the specific disciplines such as meteorology, oceanography, etc. Finally, an attempt has been made to project the future scope of the work taking into account the eperience gained from the SAMIR systems onboard the two Bhaskara satellites. 2 Fundamental Ideas on Microwave Remote Sensing Microwave remote sensing is based on the measurement of thermal emission from earth in the microwave range of the electromagnetic spectrum. The thermal energy B radiated by a perfect black-body at absolute temperature 1\oK) is given by the well-known Plank's law for black-body radiation, viz. 2hv 3 B :::----::-----:-=c----c= - c 2 [ep(hvkt)-i] where w 1m2 /ster/hz... (1) h Planck's universal constant v Frequency of the emitted radiation k Boltzmann constant c velocity of light At microwave frequencies (1-300 GHz) hv~ T and consequently Eq. (1) reduces to a simple form B=2k 2T Jc.. (2) where Jc is the wavelength of the emitted radiation. Thus, at microwave frequencies the thermal radiation is directly proportional to the physical temperature of the emitting body; this relation is known as the Rayleigh-Jeans approimation. A real object, in general, is not perfectly 'black' and its 'efficiency' of emission is described by a parameter called emissivity, s,such that the net radiated energy is s times the black-body value. The radiated energy is then proportional to the product c Twhlch is referred to as the brightness temperature T B Thus, for a real object. Eq. (2) can be written as 2k B='2cT A 2k or B= Jc2TB... (3) 141

2 INDIAN J RADIO & SPACE PHYS. VOL. 12,OCTOBER 1983 The microwave radiation emitted by a target area on earth is generally referred to as the scene brightness temperature. However, the radiation arriving at a spaceborne sensor is called the apparent brightness temperature, which is different from the scene brightness temperature due to modifications introduced by the intervening atmosphere. Mathematically, the brightness temperature T,Iv) at frequency v observed by a spaceborne microwave radiometer is given by T atv) = r"[t:,ts + (1 - t:s)t SkY ] + T atm "... (4) where Tv Transmittance at frequency v t:s Surface emissivity T, Physical temperature of the surface r., Sky temperature T atm Atmospheric brightness temperature It can be seen from Eq. (4) that the microwave radiation reaching a space borne sensor is composed of the following. (i) The radiation emitted by the earth's surface and attenuated by the intervening atmsophere. (ii) Reflection of the down-welling emission of sky and atmosphere by the surface and subsequent attenuation by the atmopshere. (iii) Upwelling radiation by the atmosphere. Changes in the observed brightness temperature could be thus basically due to one or more factors such as changes in emissivity t:s and physical temperature of the surface or due to changes in the atmospheric constituents which would, in turn, affect Tskyand T atm Fortunately, the microwave absorption spectrum of the earth's atmosphere provides a number of resonance absorption lines due to atmospheric constituents like water-vapour ( GHz, 183 GHz), oygen (centred near 60 GHz), etc. Measurement of brightness temperature at these resonance absorption frequencies as well as in the window regions allow us to determine several atmospheric as well as surface geophysical parameters. Differential sensitivities of the net brightness temperature at different frequencies, polarizations and look-angles to several surface and atmospheric parameters allow us to use the multifrequency approach of remote sensing technique. Fig. 1 shows the sensitivities of the radiometer brightness temperature measurements to different parameters as functions of frequency. These curves are based on physical models of ocean and atmosphere microwave emission as reviewed by Wilheit 1.2. It is important to note here that atmospheric parameters such as water vapour and liquid water can be determined only over oceans. This is due to the fact that against the cool -..- SALINITY -.- SEA SURFACE TEMP SEA SURFACE ---- WINO SPEED -- WATER VAPOUR, -LIQUID WATER.-l ATMOSPHERE 11(X----- \ I. J / \ f' J X. Xl ''''''F -. REQUENCY. -. GHz Fig. I-Normalized sensitivity of brightness temperature (T B ) to various geophysical parameters (Pi) as a function of frequency (schematic) [Arrows indicate the three SAMIR frequencies 19, 22 and 31 GHz (adapted from Wilheit 2 ).] radiative background of ocean (s::::;0.4),the warm radiative temperature of atmospheric water provides a good contrast, whereas against the warm radiative background of land surfaces (t::::::0.9) the atmospheric water does not give such a contrast. Since microwave radiation can penetrate most clouds, the space-borne microwave radiometers have all-weather capability to a certain etent. Ha ving discussed the fundamental ideas on microwave remote sensing, we shall now give a brief historical background of microwave remote sensing from space. Various workers 3-5 have written ecellent reviews on this subject. Observation of atmosphere through ground-based microwave radiometers was first initiated by Dicke et al. 6. The first space-borne microwave radiometer was, however, not used for remote sensing of earth's atmosphere but was used onboard the Mariner-2 spacecraft to observe the planet Venus during December 1962 (Ref. 7). The first application of microwave radiometry from space for remote sensing of earth was attempted in Sep with the launch of Soviet satellite Cosmos-243 which measured the microwave radiation from earth at 3.5, 8.8, 22.2 and 37.5 GHz and the measurements were used to estimate atmospheric water vapour, liquid water and sea-surface temperatures". Thereafter. several American and Soviet satellites carrying microwave radiometers have been launched and, as a result, the basic feasibility has been demonstrated for deriving several meteorological and geophysical parameters through microwave remote sensing from space. Table 1 gives some pertinent data on the different passive microwave sensors flown so far onboard different spacecrafts and their geophysical applications. 142

3 PATHAK et al.: MICROWAVE REMOTE SENSING WITH BHASKARA-I & II SATELLITES Table I-Passive Microwave Radiometers Flown on Different Spacecrafts and Their Geophysical Applications (Adapted from Staelin") Year of Spacecraft Instrument Frequency Smallest Geophysical applications launch acronym GHz spatial (see foot- resolution Atmosphere Surface note) element km 1968 COSMOS-243 } 3.5, 8.8, 13 Water vapour Sea-surface 1970 COSMOS ,37 and liquid temperature, water content sea-ice concentration 1972 NIMBUS-5 ESMR" Rain rate Sea-ice concentration NEMS 22.2, 31.4, 200 Temperature Ice classi- 53.6, 54.9, profile, water fication, 58.8 vapour and liquid snow cover water content 1973 SKYLAB S Wind, precipatation S Soil moisture 1975 NIMBUS-6 ESMR" Same as NIMBUS-5 Same as NIMBUS-5 SCAMS' 22.2, 31.6, 175 Temperature 52.8, 53.8, profile SEASAT SMMR d 6.6,10.7, Water Sea-surface NIMBUS 18,21, vapour and temperature. liquid wind water content speed, sea iceconcentration a: Electrically Scanning Microwave Radiometer; b: Nimbus-E Microwave Spectrometer c: Scanning Microwave Spectrometer; d: Scanning Multichannel Microwave Radiometer. 3 Microwave Radiometer Systems Onboard Bhaskara-I and II Satellites Both Bhaskara-I and II satellites were launched" in near circular orbits at average altitude of about 530 km and inclination of about 51. In this orbit the period of the satellite is about 95 min and the longitudinal shift of the orbit is about 2S per day towards west. Both the Bhaskara satellites are spin-stabilized with onboard control systems for spin-rate and spin-ais orientation. The satellites employ passive thermal control systems which could control the on board environmental temperatures within a range of 0-40 C. The SAMIR systems on board both Bhaskara satellites were Dicke-type receivers in superheterodyne mode. Calla et al" - 11 have given detailed technical description of the SAMIR systems. Table 2 gives the main characteristics of the SAMIR systems onboard the two Bhaskaras. The essential differences between the two SAMIR systems are as follows. (i) Instead of two 19-GHz channels and one at 22 GHz in Bhaskara-I, the Bhaskara-Il SAMIR system has three separate channels at 19,22 and 31 GHz. The third channel at 31 G Hz was incorporated to * Launch dates: Bhaskara-I: 7 June Bhaskara-Il: 20 Nov differentiate liquid water from water vapour (see Fig. 1). (ii) In the case of Bhaskara-I SAMIR system the two 19 GHz channels had their footprints of 150 km diameter slightly offset symmetrically on the two sides ofthe subsatellite track and the 22 GHz channel had its footprint of 230 km along the subsatellite track slightly overlapping the other two footprints. In Bhaskara-II the three radiometers.have a common footprint of 125 km diameter. For atmospheric and oceanographic studies the identical view geometry of Bhaskara-ll SAMIR is superior. Also, the view-angles are same for all three radiometers in Bhaskara II unlike in Bhaskara-I. Both the Bhaskara spacecrafts were designed to operate the SAMIR system in two distinct modes called the Normal and Alternate modes. In the Normal mode the spin-ais of the spacecraft was maintained perpendicular to the orbital plane and consequently during each spin the SAMIR observations were taken along the satellite ground trace at different view-angles with respect to nadir direction. In the Alternate mode. the spin-ais of the satellite was aligned along a tangent to the orbital plane at certain latitude and consequently the SAM]R radiometers could scan across the satellite ground trace at a number of angular 143

4 INDIAN J RADIO & SPACE PHYS, VOL. 12,OCTOBER 1983 System parameter Table 2-Characteristics of the SAMIR Systems Onboard Bhaskara-I & II Bhaskara-I radiometers Bhaskara -II radiometers R-I R-2 R-3 R-I R-2 R-3 Frequency (GHz) RF bandwidth (MHz) Integration time (ms) RMS temperature sensitivity ~nk) 1 I 1 1 I I System noise figure (db) Spatial resolution (km) ~ ~-. View angles with respect to nadir ±2.8', ±5.6', ±2.8', ±11.2, ±2K, ±5.6, 180 (zenith) (normal mode) 180 (zenith) (zenith),..-- " View angles with respect to nadir ±2.8, ±8.4, ±14.0, ±19.6, ±25.2, ±30.8, ±36.4 (alternate mode) positions (see Table 2). For both these modes, the spinrate of Bhaskara is nominally controlled between 6 and 8 rpm. Fig. 2 shows the two modes of SAMIR operations for Bhaskara-II. The original SAMIR data transmitted by the Bhaskara satellite, along with other information, were in raw form of counts from representing voltages. Before these data can be used for any analysis it is necessary to convert the same to the corresponding brightness temperatures by using the calibration curves generated in the laboratory prior to launch. In addition, it is also essential to provide earth-location to the SAMIR observations. Both these aspects, i.e. calibration and earth-location of the SAMIR data were taken care of by the Data Product Group of the Bhaskara Project. The final SAMIR Data Product after all the necessary preprocessing gives values of brightness temperature at different view-angles and the corresponding beam-centre positions in terms of latitude and longitude as well as time of data acquisition and other spacecraft system information. It may be noted that both the SAMIR systems were also designed to measure the zenith cold sky temperature of ~ 3 K with a view to use this measurement for the purpose of onboard calibration. However, in the case of Bhaskara-I SAMIR, the measurement on zenith sky temperature was not possible due to some problem and therefore only the prelaunch calibration curves were used. In the case of Bhaskara-II SAMIR, the zenith temperature could be measured and was, therefore, used for the purpose of calibration along with the prelaunch calibration curves. (Further refinements in the calibration procedure were also made by taking into account onboard horn losses and other factors). The in-orbit performance of both the SAMIR systems has been studied by eamining the temperature sensitivity (temperature resolution) over (bl (01 BHASKARA - II SAMIR NORMAl MODE OPERATION BHASKARA -II SAMIR ALTERNATE MODE OPERATION / R1"31" GHz R GHz R S GHz Fig. 2- Two possible modes ofsamir operations (Bhaskara-Il): (a) normal mode operation; and (b) alternate mode operation different periods. The temperature sensitivity AT of a microwave radiometer is defined as the rms fluctuations in the brightness temperature when the input scene temperature is constant. In terms of its design parameters, AT for a Dicke-type microwave radiometer is given by

5 PATHAK et al.: MICROWAVE REMOTE SENSING WITH BHASKARA-I & II SATELLITES where TR Noise temperature of the receiver TA Antenna temperature B Predetection bandwidth of the receiver T Integration time The total noise TN of the system is given by TN= T R + TA =(F -1)To+ TA where F is the noise figure of the receiver and To is the onboard reference temperature. For the SAMIR systems the noise figure values lie in the range of 6-8 db and To usually varies between 280 and 290 K over long periods. Thus, the factor (F -1) To dominates over TA which varies only between 150 and 250 K. The temperature sensitivity!1t, therefore, becomes largely a function of To only. This can be understood by noting that an increase in the reference temperature would introduce more thermal noise in the system thereby affecting!1t. The normal mode SAMIR data over long periods from both the satellites ha ve been statistically analyzed and it is found that, as epected from theoretical considerations,!1t is significantly affected by To (see Fig. 3). For low reference temperatures (To<280 K),!1T:::::. 1 K consistent with the design specifications but for To> 290 K,!1Tcan become 2 K or worse!". It may be noted here that the observed degradation of!j. Tis only a transient effect (i.e. there is no permanent damage to the system) and with the decrease in To,!1T again improves. The above analysis has shown that both the SAMIR systems have performed weli as per epectation over long periods of in-orbit operation. In order to estimate the in-orbit spatial resolution of SAMIR, a simple analytical method has been developed. In this method the fali in brightness temperature at a land/sea boundary is simulated for different assumed values of spatial resolution elements. The simulated values of the brightness temperatures are then compared with the observed values and the effective in-orbit spatial resolution is decided on the basis of best-fit. It has been found that for cloudless and relatively dry conditions and after applying necessary correction for the effect of atmospheric water vapour, the above method gives a reasonable estimate of the spatial resolution which is in good agreement with the epected value. 4 Scientific Applications of SAMIR Data Since the SAMIR systems make passive microwave observations at basicaliy two or three frequencies-19 and 22 GHz (Bhaskara-I) and and 31 GHz (Bhaskara II)-some limited applications using BHASKARA-I SAMIR PERIOD' JUNE JAN 1980 JI,INE -AUG GHz 22 GHz R= R = '().. '" r-' 1 5 <l (0) J:)() To,K BHASKARA-II SAMIR PERIOD NOV JUNE GHz 19 GHz U GHz R = 0.83 R.O 85 R = \0 290 XlO XlO J:)() To' K Fig. 3-Scatter plots between temperature sensitivity l!t and onboard reference temperature To for: (a) Bhaskara-I SAMIR, 19 and 22 GHz radiometers; and (b) Bhaskara-Il SAMIR, 19,22 and 31 GHz radiometers (R indicates correlation coefficient. Least-squarefit line for each scatter plot is shown.) normal mode SAMIR data have been possible in meteorology and oceanography. A few of these studies ha ve been earlier reviewed by Desai 13 and Hariharan!". In this section, we briefly review these application studies under two major sub-headingsmeteorological and oceanographic applications. In all such studies, it is etremely important that a large database of ground truth be available for the purpose of validation. In the case of Bhaskar-I, it was a fortunate circumstance that a large amount of in situ measurements both for meteorological and oceanographic applications were readily available from the MONEX-79 data-base. However, in the case of Bhaskar-Il, a very meagre data base is available and therefore, recourse had to be taken for conducting special compaigns to coliect ground truth. 4.1 Meteorological Applications In these studies total water vapour and liquid water contents of the atmosphere over oceans have been estimated using the data from both the SAMIR systems onboard the two Bhaskars satellites. Attempt has also been made to estimate oceanic rainfall rate using the 19 GHz SAMIR data. (b) 145

6 INDIAN J RADIO & SPACE PHYS. VOL. 12, OCTOBER 1983 In order to estimate atmospheric water vappour content, two distinct approaches have been considered. In the first approach, called 'statistical' and initially suggested by Grody'", the epected microwave brightness temperature over ocean is simulated for a statistically representative set of atmospheres for the region of interest and a regression is then performed between the geophysical parameter (water vapour) and the simulated brightness temperature. The resulting regression equation is then later used independently to derive atmospheric water vapour over ocean by using the observed microwave brightness temperature. The second approach is known as 'empirical' where a regression analysis is effected between the actual observed data on brightness temperature and the nearcoincident in situ observations on the geophysical parameter of interest. The Bhaskara-I SAMIR data at 19 and 22 GHz have been used to derive water vapour content using both these approaches and the results are shown in Fig. 4. It can be seen from Figs. 4(a)-4(b) that both the methods give acceptable results. However, there seems to be a relative bias and a systematic trend between the two methods, which could be possibly due to instrumental biases between SAMIR and radiosonde measurements as well as due to uncertainties in the water vapour absorption model used in the 'statistical' method. Judging from the rms errors obtained by both the methods it can be safely concluded that with the 19 and 22 GHz SAMIR data of Bhaskara-I, atmospheric water vapour content over ocean has been estimated to an accuracy of - 4mm. A slightly different approach in the statistical method has also been attempted 19, wherein simulated atmospheres are used and transmittances due to oygen, water vapour and liquid water are analyzed to determine total water vapour and liquid water contents. For Bhaskara-II SAMIR data, 3-frequency (19, 22 and 31 GHz) regression equations were derived through 'statistical' method. Using a set of such regression equations atmospheric water vapour values were derived from the SAMIR data of orbit 985 (24Jan. 1982). After applying some consistency checks to ensure that the water vapour values derived through different regression equations agree among themselves, the final results were found to be in agreement with coastal and island radiosonde data as well as with limited NOAA satellite water vapour data 13. A more detailed comparison is planned using substantial amount of SAMIR-derived water vapour data and NOAA satellite water vapour data in the near future. Atmospheric liquid water content from Bhaskara-I and II SAMIR data has been estimated using the 'statistical' method only since in situ data on integrated liquid water content are not easily available. However, ~ ct u ;:: oj> ;:: ct ~5{) N 'E u do a: :) ':'E u &Or-~ , oq. ~ ffit.-o i a: :E ~ (0) v= -O-l> X CORRELATION CDEFFICIENT=O B3 RMS DEVIATION cm- 2 RMS ERROR- 0;~6 9. cm L..- -L --L..L.-.J , (b) v= '6799 CORRELATION COEFFICIENT=0'83 RMS OEVIATION=0 299.cm2 RMS ERROR=0 249.cm2 3 0l-. --L --'- L...J RADIOSONDE WATER VAPOUR, g. cm 2 Fig. 4-Comparison of water vapour derived from Bhaskara-I SAMIR (19,22 GHz) data with in situ radiosonde data: (a) statistical method (b) empirical method it has been verified that liquid water content values obtained from SAMIR data are in a reasonable range as epected from meteorological conditions 18. Estimation of rainfall rate over ocean using 19 GHz SAMIR data has also been attempted 20. This involves simulation of brightness temperature for a raining atmosphere where additional factors such as(i) microwave absorption due to rain which is basically dependent on the drop-size distribution and rain-rate (scattering effects which are prominent only for rainrates above 20 mmjhr are neglected) and (ii) cloud-base heights, cloud-top heights and liquid water density in the clouds. Since quantitative information on these cloud parameters are not readily available, some typical representative range of values for tropical raining atmosphere have been used and simulations have been carried out. The results give a rather large range of rainfall rate for a given value of 19 GHz. brightness temperature. Rainfall rate estimate can be &0 146

7 PATHAK et af.: MICROWAVE REMOTE SENSING WITH BHASKARA-I & II SATELLITES made more definitive only if quantitative information on the above mentioned cloud parameters are available. Due to the coarse spatial resolution of SAMIR and the disparity between sea and land emissivities, one limitation 'hindering full use of SAMIR data over oceans is that data within about 200 km of coast are 'land-contaminated' and hence not directly usable with regressions based upon sea-surface emissivity modes. However, for many meteorological applications, e.g. rainfall comparison with coastal radars, etc. such nearcoast data would be worth using if some method to do so could be found. In the course of eamining the response of SAMIR to a tropical cyclone (Bay of Bengal, December 1981), a simple method has been developed+':!". The land-sea cross-over (fall of brightness temperature) in the 19 GHz channel was eamined for a pass which went over the cyclone when it had reached very close to the coast. While no distinct peak was noticed (unlike the behaviour epected, had the cyclone been in the open ocean), the cross-over was seen to be much slower than the normal ones in that region. By taking the difference between the cross-over values of this pass with respect to another pass in the same. area on a 'quiet' day, the peaking behaviour was identified and the ecess brightness temperature due to the cyclone was estimated to be as high as 60 K at the peak which can be related to the cyclone parameter like precipitation, cloud-liquid water content as well as seasurface winds and roughness. 4.2 Oceanographic Applications In this sub-section we discuss the potential application of SAMIR data for deriving sea-surface wind speed which is an important oceanographic parameter. This potential application is based on the fact that sea-surface emissivity (which is an important physical parameter related to microwave emission from sea) is.a function of several factors such as salinity, sea-surface temperature as well as sea-surface wind speed. Earlier studies have shown that for frequencies beyond ~4 GHz, sea-surface emissivity is practically insensitive to salinity changes. Similarly, beyond the frequency range 4-6 GHz, effects due to temperature changes are negligible+' (see Fig. 1). It turns out that for the SAMIR frequencies (19,22 and 31 GHz), the sea-surface emissivity is almost independent of changes in both salinity and temperature but increases with sea-surface wind speed. The changes in emissivity due to wind speed come about through seasurface roughness as well as foam-cover and whitecaps+'. Since the brightness temperature observed by a space-borne microwave radiometer depends both on surface (i.e. wind) as well as atmospheric effects, in order to derive wind speed from the microwave data, the atmospheric effect should be first eliminated. In the past, several workers+" - 26 have developed statistical regression models based on theoretical simulation as well as empirical relationships between sea-surface wind speed and microwave brightness temperature. For the case of Bhaskar-I SAMIR, an empirical approach was adopted and the observed brightness temperatures at 19 G Hz near nadir were correlated with sea-surface wind speed as observed by nearby MONEX research ships and at coastal stations!", The basic assumption made' here was that during the few days considered the meteorological conditions do not change significantly so as to affect the brightness temperature. The above analysis, although based on a meagre amount of data, did show a fairly close relationship between sea-surface wind speed and 19 GHz brightness temperature observed by SAMIR onboard Bhaskara-I. Statistical inversion technique has also been applied to this problem. For a variety of atmospheric profiles and sea-surface wind conditions observed during MONEX-1979 and using an empirical relationship between sea-surface wind speed and emissivity+", brightness temperatures at 19, 22 and 31 GHz were simulated and regression models were developed to relate the observed brightness temperature with seasurface wind speeds. Several types of regression equations-linear as well as nonlinear-with two or three-frequency combinations were tried out. These regression equations were then used to derive seasurface wind speeds from the actual SAMI R observations and the wind speeds, so derived, were compared with the available in situ measurements. Care was taken to ensure that the SAMIR footprint over sea does not cover any portion of coast or island, since this would contaminate the brightness temperature due to high emissivity ofland surface. As a result of this eercise it was found that the following linear relationship connecting wind speed (SW) with 19 and 22 GHz brightness temperature (T B ) and having an rms accuracy of ~ 2.7 m/sec gives fairly consistent results. SW= T B (19) T B (22) m/sec Using the above regression equation with Bhaskara- I SAMIR data during July 1979, wind speeds were derived at a few locations in the Bay of Bengal where MONEX research ships were stationed. The SAMIRderived wind speeds were then compared with the in situ measurements of the MONEX ships. (The spatial separation between ship's position and SAMIR observation position was limited to 250 km from the consideration of the SAMIR footprint size as well as persistence of wind over that distance, whereas the time 147

8 INDIAN J RADIO & SPACE PHYS. VOL. 12. OCTOBER ~ III 4 r , MONE)( SHIPS 1979 BHASKARA-I o R V GAVESHAN I 1982 BHASKARA-II SW (SHIP),m/sec Fig. 5-Comparison of sea-surface wind speed (SW) derived from SAMIR data ( GHz) of Bhaskara-I and II with in situ ship data interval between the SAMIR and in situ measurement was kept within 2.5 hr.). The results of these comparisons are shown by a scatter plot in Fig. 5. In Fig. 5, a few data points are also included which relate to Bhaskara- II SAMIR data validation compaign+? conducted in June 1982 where the in situ sea-truth measurements were made on the ship R V Gaveshani in the Arabian Sea concurrent with Bhaskara-II orbital passes. Although the total number of data points is quite limited, a definite relationship seems to be indicated. Further analysis with better statistics and larger range of observed windspeeds would be quite fruitful to test the validity of the regression model over wider range of wind speeds and meteorological conditions. 5 Concluding Remarks The application studies in meteorology and oceanography carried out with Bhaskara SAMIR data have been reviewed. In view of the fact that both Bhaskara satellites were essentially eperimental remote sensing satellites, with the demonstration of the feasibility for the application of SAMIR data in meteorology and oceanography, the full potential of the Bhaskara SAMIR seems to have been well realized. Through these studies we have learnt the basic technique of handling and interpreting passive microwave observation from space. In addition. statistical inversion techniques and formulation of radiative transfer models have been learnt and methodologies have been established for retrieval of geophysical parameters. Among the different geophysical parameters that have been derived from SAMIR data, atmospheric water vapour content over ocean and sea-surface wind speed are the only two parameters for which validation could be done with the help of some in situ data. However, it is most important to validate such satellite-derived parameters with a much larger data-base of in situ measurements over different periods, in order to have large range of variation of the geophysical parameter. For atmospheric liquid water content derived through SAMIR data, no in situ measurements of cloud-liquid water content are available whereas for the rainfall rate estimated over ocean, the situation at present is comple due to uncertainties in the input cloud model parameters. In future, one can use information from other sources (such as infra-red sounders onboard operational meteorological satellites) on cloud heights and work out better models for rainfall rate estimates. To etend the scope of future microwave remote sensing, additional frequencies suitable for remote sensing of sea-surface temperature and atmospheric temperature profiles may also be incorporated. Meanwhile it may also be worthwhile to carry out a few feasibility studies with field/aircraft eperiments using suitable passive microwave sensors for the determination of soil moisture and detection of oil spills over ocean. Acknowledgement The authors would like to epress their deep sense of appreciation to Prof. E V Chitnis, Director, Space Applications Centre (SAC) and Prof. P 0 Bhavsar, Chairman, Remote Sensing Area, SAC for their keen interest in the various aspects related to Bhaskara SAMIR utilization. They would also like to acknowledge Shri 0 P N Calla, Principal Scientist, SAMIR payload, and his team of dedicated engineers for their hard work and perseverance which resulted in the successful in-orbit performance of SAMI R. Finally, the authors acknowledge the Data Product Group at SAC for providing the SAMIR data in easily usable form. The SAMIR Data Validation Campaign during June 1982 was conducted using the ship R V Gaveshani for which the authors thank the Director, National Institute of Oceanography, Panjim, Goa. The authors are thankful to their colleagues Dr S M Bhandari, Dr Abhijit Sarkar and Shri B S Gohil for useful discussions during the preparation of the present review. References 1 Wilheit T T. Boundary Laver Meteorol (Netherlands). 13 (1977) Wilheit T T, Chang A T C & Milman A S, Boundary Layer Meteorol (Netherlands), 18 (1980) Staelin D H. Proc IEEE (USA), 57 (1969) Staelin D H. IEEE Trans Antennas & Propag (USA). 29 (1981) Njoku E G. Proc IEEE (USA). 70 (1982) Dicke R H, Beringer R, Kyhl R C & Vane A B. Phys Rev (USA). 70 (1946) Barath FT. Barrett A H, Copeland J. Jones D E & Lilley A E. AstronJ (USA). 69 (1964)

9 PATHAK et al.: MICROWAVE REMOTE SENSING WITH BHASKARA-I & II SATELLITES 8 Basharinov A E, Gurvich A S, Yogrov S T, Kurskaya A A, Matveyev D T & Shutko A M, Space Research XI (Akademie-Verlag, Berlin), Calla OP N, Raju G, Rana S S & Balasubramanian S,ilnst Elect Telecommun Eng (India), 25 (1979) Calla 0 P N, Raju G, Rana S S & Balasubramanian S,J I nst Elect Telecommun Eng (India), 26 (1980) 243. II Calla 0 P N, Raju G, Rana S S & Balasubramanian S,J Inst Elect Telecommun Eng (India), 28 (1982) Kraus J D, Radio astronomy (McGraw Hill, New York), Desai P S, Scientific applications of Bhaskar a SA MtR - A review, Presented at the,national Space Science Symposium, 3-6 Feb. 1982, Bangalore (unpublished). 14 Hariharan T A, Proceedings of the Indo-Soviet symposium on space science, Feb. 1983, Bangalore (unpublished). 15 Grody N C, IEEE Trans Antennas & Propag (USA), 24 ( Pandey P C, Gohil B S & Sharma A K, Proc Indian Acad Sci (Earth & Planetary Sci), 89 (1980) Pandey PC, Sharma A K & Gohil B S, Proc Indian Acad Sci (Earth & Planetary Sci), 90 (1981) Pandey PC,Gohil B S& Sharma A K, Mausam(lndia),32(1981) Gohil B S, Hariharan T A, Pandey PC & Sharma A K, lnt J Remote Sens (USA), 3 (1982) Gohil B S, Sharma A K & Pandey PC, I SRO tech rep ISRO- TR , ISRO Headquarters, Bangalore, 1981, unpublished. 21 Hollinger J P, Naval Research Laboratory rep. No , 1973, unpublished. 22 Litman V & Nicholas J, NASA Reference Publication No , unpublished. 23 Williams G F (Jr), J Geophys Res (USA). 74 (1969) Hollinger J P, J Geophys Res (USA), 75 (1970) Nordberg W, Conaway J, Ross D B & Wilheit T T,J Atmos Sci (USA), 28 (1971) Wilheit T T (Jr) & Fowler M G, IEEE Trans Antennas & Propag (USA), 2S (1977) Pandey r c. Gohil B S & Sharma A K. Mahasagar (India). 13 (1980) Wisler M M & Hollinger J P, N RL memorandum rep 3661, unpublished. 29 Bhandari S M, Desai P S, Pathak P N, Raju G, Rana S S & Sarkar A, Report on SAMIR Data Validation Campaign- June 1982, Internal tech re,p, Space Applications Centre (/SRO), Ahmedabad, 1982, unpublished. 149