Indian Journal of Radio & Space PhysicsVol. 12, October 1983, pp. 141-149

Microwave Remote Sensing with Bhaskara-I & II Satellites

P N PATHAK, P S DESAI & T A HARIHARAN

Meteorology Division, Space Applications Centre (ISRO), Ahmedabad 380053

Received 22 April 1983

The .nain scientific applications of the satellite microwave radiometer (SAMIR) systems flown onboard the two Indiansatellites Bhaskara-I and II are reviewed. After a brief resume of the fundamental ideas on microwave remote sensing togetherwith a short summary on the historical development of microwave remote sensing from space, the main characteristics of thetwo SAMIR systems are described and results on their in-orbit performance presented. The scientific applications of the datafrom the two SAMIR systems are then reviewed in two broad areas-meteorology and oceanography.

1 IntroductionRemote probing of the earth's atmosphere and

ocean surface using electromagnetic radiation in themicrowave region, has long been recognized as apowerful tool for meteorological and oceanographicapplications. The technological advances in theperformance of radiometers, scatterometers, alti-meters, radars, etc. have widened considerably thescope of these applications to include earth resourcessurveys.

Significant efforts are being made in the country inthe development and utilization of microwave remotesensing techniques. India's two experimental satellitesfor earth observation (SEO-I and II, later namedBhaskara-I and II), carried onboard, passivemicrowave radiometer systems called SAMIR (satellitemicrowave radiometer). This paper attempts to reviewthe several exploratory scientific investigations thathave been made using the SAMIR data from the twoBhaskara satellites. The present review considers thework carried out till the end of February 1983. Insection 2, the fundamental ideas on microwave remotesensing are briefly discussed together with a shorthistorical background on microwave radiometry fromspace. Section 3 gives details regarding the Bhaskarasatellites and their onboard SAMIR systems, followedby a brief account of the in-orbit performance ofSAMIR through an analysis of temperature sensitivityand spatial resolution. In section 4, the scientificapplications of the SAMIR data are discussed indifferent sub-sections depending on the specificdisciplines such as meteorology, oceanography, etc.Finally, an attempt has been made to project the futurescope of the work taking into account the experiencegained from the SAMIR systems onboard the twoBhaskara satellites.

2 Fundamental Ideas on Microwave Remote SensingMicrowave remote sensing is based on the

measurement of thermal emission from earth in themicrowave range of the electromagnetic spectrum. Thethermal energy B radiated by a perfect black-body atabsolute temperature 1\oK) is given by the well-knownPlank's law for black-body radiation, viz.

2hv3B - --.-:::----::-----:-=c----c=

- c2[exp(hvkT)-I]w 1m2 /ster/Hz ... (1)

where

h Planck's universal constantv Frequency of the emitted radiationk Boltzmann constantc velocity of light

At microwave frequencies (1-300 GHz) hv~ T andconsequently Eq. (1) reduces to a simple form

B=2k2TJc •.. (2)

where Jc is the wavelength of the emitted radiation.Thus, at microwave frequencies the thermal radiationis directly proportional to the physical temperature ofthe emitting body; this relation is known as theRayleigh-Jeans approximation.

A real object, in general, is not perfectly 'black' andits 'efficiency' of emission is described by a parametercalled emissivity, s ,such that the net radiated energy is stimes the black-body value. The radiated energy is thenproportional to the product c Twhlch is referred to asthe brightness temperature TB• Thus, for a real object.Eq. (2) can be written as

2kB='2cT

A

2kor B= Jc2TB ... (3)

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INDIAN J RADIO & SPACE PHYS. VOL. 12,OCTOBER 1983

The microwave radiation emitted by a target area onearth is generally referred to as the scene brightnesstemperature. However, the radiation arriving at aspaceborne sensor is called the apparent brightnesstemperature, which is different from the scenebrightness temperature due to modifications in-troduced by the intervening atmosphere.Mathematically, the brightness temperature T,Iv) atfrequency v observed by a spaceborne microwaveradiometer is given byT atv) = r"[t:,Ts + (1 - t:s)TSkY] + Tatm" ... (4)

whereTv Transmittance at frequency vt:s Surface emissivityT, Physical temperature of the surfacer., Sky temperatureTatm Atmospheric brightness temperature

It can be seen from Eq. (4) that the microwaveradiation reaching a spaceborne sensor is composed ofthe following.(i) The radiation emitted by the earth's surface andattenuated by the intervening atmsophere.

(ii) Reflection of the down-welling emission of sky andatmosphere by the surface and subsequent attenuationby the atmopshere.

(iii) Upwelling radiation by the atmosphere.Changes in the observed brightness temperature

could be thus basically due to one or more factors suchas changes in emissivity t:s and physical temperature ofthe surface or due to changes in the atmosphericconstituents which would, in turn, affect Tskyand Tatm·

Fortunately, the microwave absorption spectrum of theearth's atmosphere provides a number of resonanceabsorption lines due to atmospheric constituents likewater-vapour (22.235 GHz, 183 GHz), oxygen (centrednear 60 GHz), etc. Measurement of brightnesstemperature at these resonance absorption frequenciesas well as in the window regions allow us to determineseveral atmospheric as well as surface geophysicalparameters. Differential sensitivities of the netbrightness temperature at different frequencies,polarizations and look-angles to several surface andatmospheric parameters allow us to use the multi-frequency approach of remote sensing technique. Fig. 1shows the sensitivities of the radiometer brightnesstemperature measurements to different parameters asfunctions of frequency. These curves are based onphysical models of ocean and atmosphere microwaveemission as reviewed by Wilheit 1.2. It is important tonote here that atmospheric parameters such as watervapour and liquid water can be determined only overoceans. This is due to the fact that against the cool

142

- ..- SALINITYSEA

-.- SEA SURFACE TEMP SURFACE---- WINO SPEED-- WATER VAPOUR,-LIQUID WATER.-l ATMOSPHERE

11(X-----\ I.

J / \f' J .·XXl 40 50 60

''''''F REQUENCY.GHz-.-.-1

Fig. I-Normalized sensitivity of brightness temperature (TB) tovarious geophysical parameters (Pi) as a function of frequency(schematic) [Arrows indicate the three SAMIR frequencies 19, 22

and 31 GHz (adapted from Wilheit2).]

radiative background of ocean (s ::::;0.4),the warmradiative temperature of atmospheric water provides agood contrast, whereas against the warm radiativebackground of land surfaces (t::::::0.9) the atmosphericwater does not give such a contrast. Since microwaveradiation can penetrate most clouds, the space-bornemicrowave radiometers have all-weather capability toa certain extent.

Ha ving discussed the fundamental ideas onmicrowave remote sensing, we shall now give a briefhistorical background of microwave remote sensingfrom space. Various workers 3 - 5 have written excellentreviews on this subject. Observation of atmospherethrough ground-based microwave radiometers wasfirst initiated by Dicke et al.6. The first space-bornemicrowave radiometer was, however, not used forremote sensing of earth's atmosphere but was usedonboard the Mariner-2 spacecraft to observe theplanet Venus during December 1962 (Ref. 7). The firstapplication of microwave radiometry from space forremote sensing of earth was attempted in Sep. 1968with the launch of Soviet satellite Cosmos-243 whichmeasured the microwave radiation from earth at 3.5,8.8, 22.2 and 37.5 GHz and the measurements wereused to estimate atmospheric water vapour, liquidwater and sea-surface temperatures". Thereafter.several American and Soviet satellites carryingmicrowave radiometers have been launched and, as aresult, the basic feasibility has been demonstrated forderiving several meteorological and geophysicalparameters through microwave remote sensing fromspace. Table 1 gives some pertinent data on thedifferent passive microwave sensors flown so faronboard different spacecrafts and their geophysicalapplications.

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 applicationslaunch acronym GHz spatial

(see foot- resolution Atmosphere Surfacenote) element

km1968 COSMOS-243 } 3.5, 8.8, 13 Water vapour Sea-surface1970 COSMOS-384 22.2,37 and liquid temperature,

water content sea-iceconcentration

1972 NIMBUS-5 ESMR" 19.3 25 Rain rate Sea-iceconcentration

NEMS· 22.2, 31.4, 200 Temperature Ice classi-53.6, 54.9, profile, water fication,

58.8 vapour and liquid snow coverwater content

1973 SKYLAB S-193 13.9 16 Wind, precipatationS-194 1.4 115 Soil moisture

1975 NIMBUS-6 ESMR" 37 20 x 43 Same as NIMBUS-5 Same as NIMBUS-5SCAMS' 22.2, 31.6, 175 Temperature

52.8, 53.8, profile55.4

1978 SEASAT SMMRd 6.6,10.7, 18 x 28 Water Sea-surfaceNIMBUS 18,21,37 22 x 35 vapour and temperature.

liquid windwater content speed,

sea ice-concentration

a: Electrically Scanning Microwave Radiometer; b: Nimbus-E Microwave Spectrometerc: Scanning Microwave Spectrometer; d: Scanning Multichannel Microwave Radiometer.

3 Microwave Radiometer Systems OnboardBhaskara-I and II Satellites

Both Bhaskara-I and II satellites were launched" innear circular orbits at average altitude of about 530 kmand inclination of about 51°. In this orbit the period ofthe satellite is about 95 min and the longitudinal shift ofthe orbit is about 2S per day towards west. Both theBhaskara satellites are spin-stabilized with onboardcontrol systems for spin-rate and spin-axis orientation.The satellites employ passive thermal control systemswhich could control the onboard environmentaltemperatures within a range of 0-40°C.

The SAMIR systems on board both Bhaskarasatellites were Dicke-type receivers in superheterodynemode. Calla et al" - 11 have given detailed technicaldescription of the SAMIR systems. Table 2 gives themain characteristics of the SAMIR systems onboardthe two Bhaskaras. The essential differences betweenthe two SAMIR systems are as follows.

(i) Instead of two 19-GHz channels and one at 22GHz in Bhaskara-I, the Bhaskara-Il SAMIR systemhas three separate channels at 19,22 and 31 GHz. Thethird channel at 31 G Hz was incorporated to

* Launch dates: Bhaskara-I: 7 June 1979.Bhaskara-Il: 20 Nov. 1981.

differentiate liquid water from water vapour (seeFig. 1).

(ii) In the case of Bhaskara-I SAMIR system the two19 GHz channels had their footprints of 150 kmdiameter slightly offset symmetrically on the two sidesofthe subsatellite track and the 22 GHz channel had itsfootprint of 230 km along the subsatellite track slightlyoverlapping the other two footprints. In Bhaskara-IIthe three radiometers .have a common footprint of 125km diameter. For atmospheric and oceanographicstudies the identical view geometry of Bhaskara-llSAMIR is superior. Also, the view-angles are same forall three radiometers in Bhaskara II unlike inBhaskara-I.

Both the Bhaskara spacecrafts were designed tooperate the SAMIR system in two distinct modescalled the Normal and Alternate modes. In the Normalmode the spin-axis of the spacecraft was maintainedperpendicular to the orbital plane and consequentlyduring each spin the SAMIR observations were takenalong the satellite ground trace at different view-angleswith respect to nadir direction. In the Alternate mode.the spin-axis of the satellite was aligned along a tangentto the orbital plane at certain latitude andconsequently the SAM]R radiometers could scanacross the satellite ground trace at a number of angular

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INDIAN J RADIO & SPACE PHYS, VOL. 12,OCTOBER 1983

System parameter

Table 2-Characteristics of the SAMIR Systems Onboard Bhaskara-I & II

Bhaskara-Iradiometers

Bhaskara -IIradiometers

R-I R-2 R-3 R-I R-2 R-3

Frequency (GHz) 19.1 19.6 22.235 31.4 19.35 22.235RF bandwidth (MHz) 250 250 250 250 250 250Integration time (ms) 350 350 470 300 300 300RMS temperature sensitivity ~nK) 1 I 1 1 I ISystem noise figure (dB) 6.5 6.5 7.5 8.5 6.5 7.5Spatial resolution (km) 150 150 230 125 125 125.•. ~ ~-.View angles with respect to nadir ±2.8', ±5.6', ±2.8', ±11.2, ±2K, ±5.6, 180 (zenith)(normal mode) 1800(zenith) 1800(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 spin-rate of Bhaskara is nominally controlled between 6 and8 rpm. Fig. 2 shows the two modes of SAMIRoperations for Bhaskara-II.

The original SAMIR data transmitted by theBhaskara satellite, along with other information, werein raw form of counts from 0-127 representing voltages.Before these data can be used for any analysis it isnecessary to convert the same to the correspondingbrightness temperatures by using the calibrationcurves generated in the laboratory prior to launch. Inaddition, it is also essential to provide earth-location tothe SAMIR observations. Both these aspects, i.e.calibration and earth-location of the SAMIR data weretaken care of by the Data Product Group of theBhaskara Project. The final SAMIR Data Productafter all the necessary preprocessing gives values ofbrightness temperature at different view-angles and thecorresponding beam-centre positions in terms oflatitude and longitude as well as time of dataacquisition and other spacecraft system information.

It may be noted that both the SAMIR systems werealso designed to measure the zenith cold skytemperature of ~ 3°K with a view to use thismeasurement for the purpose of onboard calibration.However, in the case of Bhaskara-I SAMIR, themeasurement on zenith sky temperature was notpossible due to some problem and therefore only theprelaunch calibration curves were used. In the case ofBhaskara-II SAMIR, the zenith temperature could bemeasured and was, therefore, used for the purpose ofcalibration along with the prelaunch calibrationcurves. (Further refinements in the calibrationprocedure were also made by taking into accountonboard horn losses and other factors).

The in-orbit performance of both the SAMIRsystems has been studied by examining thetemperature sensitivity (temperature resolution) over

144

(01

BHASKARA - II SAMIRNORMAl MODE OPERATION

(bl

BHASKARA -II SAMIRALTERNATE MODE OPERATION

/

R1"31" GHzR2-19-35 GHz

R3-22·23S 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 amicrowave radiometer is defined as the rmsfluctuations in the brightness temperature when theinput scene temperature is constant. In terms of itsdesign parameters, AT for a Dicke-type microwaveradiometer is given by 1 2

where

PATHAK et al.: MICROWAVE REMOTE SENSING WITH BHASKARA-I & II SATELLITES

TR Noise temperature of the receiverTA Antenna temperatureB Predetection bandwidth of the receiverT Integration time

The total noise TN of the system is given by

TN= TR+ TA

=(F -1)To+ TA

where F is the noise figure of the receiver and To is theonboard reference temperature. For the SAMIRsystems the noise figure values lie in the range of 6-8 dBand To usually varies between 280 and 290 K over longperiods. Thus, the factor (F -1) To dominates over TAwhich varies only between 150 and 250 K. Thetemperature sensitivity !1T, therefore, becomes largelya function of To only. This can be understood by notingthat an increase in the reference temperature wouldintroduce more thermal noise in the system therebyaffecting !1T.

The normal mode SAMIR data over long periodsfrom both the satellites ha ve been statistically analyzedand it is found that, as expected from theoreticalconsiderations, !1T is significantly affected by To (seeFig. 3). For low reference temperatures (To<280 K),!1T:::::.1 K consistent with the design specifications butfor To> 290 K, !1Tcan become 2 K or worse!". It maybe noted here that the observed degradation of !J. Tisonly a transient effect (i.e. there is no permanentdamage to the system) and with the decrease in To, !1Tagain improves. The above analysis has shown thatboth the SAMIR systems have performed welI as perexpectation over long periods of in-orbit operation.

In order to estimate the in-orbit spatial resolution ofSAMIR, a simple analytical method has beendeveloped. In this method the falI in brightnesstemperature at a land/sea boundary is simulated fordifferent assumed values of spatial resolution elements.The simulated values of the brightness temperatures arethen compared with the observed values and theeffective in-orbit spatial resolution is decided on thebasis of best-fit. It has been found that for cloudless andrelatively dry conditions and after applying necessarycorrection for the effect of atmospheric water vapour,the above method gives a reasonable estimate of thespatial resolution which is in good agreement with theexpected value.

4 Scientific Applications of SAMIR DataSince the SAMIR systems make passive microwave

observations at basicalIy two or three frequencies-19and 22 GHz (Bhaskara-I) and 19.22 and 31 GHz(Bhaskara II)-some limited applications using

BHASKARA-I SAMIR PERIOD' JUNE 1979- JAN 1980JI,INE -AUG 1980

2·5 19 GHz 22 GHzR= 0·83 . R = 0-89

•2'() •

'"..

r-' 1·5<l ••. ......

1·0 .(0)..

270 280 290 300 270 280 290 J:)()

To,K

BHASKARA-II SAMIR PERIOD NOV 1981- JUNE 1982

31 GHz 19 GHz U GHzR = 0.83 R.O·85 R = 0-86

2·5

..

(b)

21\0 290 XlO280 290 XlO280 290 J:)()To' K

Fig. 3-Scatter plots between temperature sensitivity l!T andonboard reference temperature To for: (a) Bhaskara-I SAMIR, 19and 22 GHz radiometers; and (b) Bhaskara-Il SAMIR, 19,22 and 31GHz radiometers (R indicates correlation coefficient. Least-square-

fit line for each scatter plot is shown.)

normal mode SAMIR data have been possible inmeteorology and oceanography. A few of these studiesha ve been earlier reviewed by Desai 13 andHariharan!". In this section, we briefly review theseapplication studies under two major sub-headings-meteorological and oceanographic applications. In allsuch studies, it is extremely important that a large data-base of ground truth be available for the purpose ofvalidation. In the case of Bhaskar-I, it was a fortunatecircumstance that a large amount of in situmeasurements both for meteorological and oceanog-raphic applications were readily available from theMONEX-79 data-base. However, in the case ofBhaskar-Il, a very meagre data base is available andtherefore, recourse had to be taken for conductingspecial compaigns to colIect ground truth.

4.1 Meteorological Applications

In these studies total water vapour and liquid watercontents of the atmosphere over oceans have beenestimated using the data from both the SAMIRsystems onboard the two Bhaskars satellites. Attempthas also been made to estimate oceanic rainfall rateusing the 19 GHz SAMIR data.

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INDIAN J RADIO & SPACE PHYS. VOL. 12, OCTOBER 1983

In order to estimate atmospheric water vappourcontent, two distinct approaches have been considered.In the first approach, called 'statistical' and initiallysuggested by Grody'", the expected microwavebrightness temperature over ocean is simulated for astatistically representative set of atmospheres for theregion of interest and a regression is then performedbetween the geophysical parameter (water vapour) andthe simulated brightness temperature. The resultingregression equation is then later used independently toderive atmospheric water vapour over ocean by usingthe observed microwave brightness temperature. Thesecond approach is known as 'empirical' where aregression analysis is effected between the actualobserved data on brightness temperature and the near-coincident in situ observations on the geophysicalparameter of interest. The Bhaskara-I SAMIR data at19 and 22 GHz have been used to derive water vapourcontent using both these approaches 16-18 and theresults 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 asystematic trend between the two methods, whichcould be possibly due to instrumental biases betweenSAMIR and radiosonde measurements as well as dueto uncertainties in the water vapour absorption modelused in the 'statistical' method. Judging from the rmserrors obtained by both the methods it can be safelyconcluded that with the 19 and 22 GHz SAMIR data ofBhaskara-I, atmospheric water vapour content overocean has been estimated to an accuracy of - 4mm.

A slightly different approach in the statisticalmethod has also been attempted 19, wherein simulatedatmospheres are used and transmittances due tooxygen, water vapour and liquid water are analyzed todetermine total water vapour and liquid watercontents.

For Bhaskara-II SAMIR data, 3-frequency (19, 22and 31 GHz) regression equations were derivedthrough 'statistical' method. Using a set of suchregression equations atmospheric water vapour valueswere derived from the SAMIR data of orbit 985 (24Jan.1982). After applying some consistency checks toensure that the water vapour values derived throughdifferent regression equations agree among themselves,the final results were found to be in agreement withcoastal and island radiosonde data as well as withlimited NOAA satellite water vapour data 13. A moredetailed comparison is planned using substantialamount of SAMIR-derived water vapour data andNOAA satellite water vapour data in the near future.

Atmospheric liquid water content from Bhaskara-Iand II SAMIR data has been estimated using the'statistical' method only since in situ data on integratedliquid water content are not easily available. However,

146

&Or-~--------------------------------,(0)

v= -O-l>26+1·013XCORRELATION CDEFFICIENT=O·B3RMS DEVIATION-0·58 9. cm-2

RMS ERROR- 0;~6 9. cm-2

x~ctu;::oJ>;::ct

~5{)N

'Eudoa::)oQ.

~ffit.-Oia::E~

x•

3·0L..- -L --L ..L.-.J

6·0.--------------------------------------,

':'Eu

x x•

(b)v= 1·518+0'6799 xCORRELATION COEFFICIENT=0'83RMS OEVIATION=0·299.cm2

RMS ERROR=0·249.cm2

xx

xxx

3·0l-. --L --'- L......J

3·0 4·0 5-0

RADIOSONDE WATER VAPOUR, g. cm2

Fig. 4-Comparison of water vapour derived from Bhaskara-ISAMIR (19,22 GHz) data with in situ radiosonde data: (a) statistical

method (b) empirical method

&0

it has been verified that liquid water content valuesobtained from SAMIR data are in a reasonable rangeas expected from meteorological conditions 18.

Estimation of rainfall rate over ocean using 19 GHzSAMIR data has also been attempted 20. This involvessimulation of brightness temperature for a rainingatmosphere where additional factors such as(i)microwave absorption due to rain which is basicallydependent on the drop-size distribution and rain-rate(scattering effects which are prominent only for rain-rates above 20 mmjhr are neglected) and (ii) cloud-baseheights, cloud-top heights and liquid water density inthe clouds. Since quantitative information on thesecloud parameters are not readily available, sometypical representative range of values for tropicalraining atmosphere have been used and simulationshave been carried out. The results give a rather largerange of rainfall rate for a given value of 19 GHz .brightness temperature. Rainfall rate estimate can be

PATHAK et af.: MICROWAVE REMOTE SENSING WITH BHASKARA-I & II SATELLITES

made more definitive only if quantitative informationon the above mentioned cloud parameters areavailable.

Due to the coarse spatial resolution of SAMIR andthe disparity between sea and land emissivities, onelimitation 'hindering full use of SAMIR data overoceans is that data within about 200 km of coast are'land-contaminated' and hence not directly usable withregressions based upon sea-surface emissivity modes.However, for many meteorological applications, e.g.rainfall comparison with coastal radars, etc. such near-coast data would be worth using if some method to doso could be found. In the course of examining theresponse of SAMIR to a tropical cyclone (Bay ofBengal, December 1981), a simple method has beendeveloped+':!". The land-sea cross-over (fall ofbrightness temperature) in the 19 GHz channel wasexamined for a pass which went over the cyclone whenit had reached very close to the coast. While no distinctpeak was noticed (unlike the behaviour expected, hadthe cyclone been in the open ocean), the cross-over wasseen to be much slower than the normal ones in thatregion. By taking the difference between the cross-overvalues of this pass with respect to another pass in thesame. area on a 'quiet' day, the peaking behaviour wasidentified and the excess brightness temperature due tothe cyclone was estimated to be as high as 60 K at thepeak which can be related to the cyclone parameter likeprecipitation, cloud-liquid water content as well as sea-surface winds and roughness.

4.2 Oceanographic Applications

In this sub-section we discuss the potentialapplication of SAMIR data for deriving sea-surfacewind speed which is an important oceanographicparameter. This potential application is based on thefact that sea-surface emissivity (which is an importantphysical parameter related to microwave emissionfrom sea) is.a function of several factors such as salinity,sea-surface temperature as well as sea-surface windspeed. Earlier studies21.22 have shown that forfrequencies beyond ~4 GHz, sea-surface emissivity ispractically insensitive to salinity changes. Similarly,beyond the frequency range 4-6 GHz, effects due totemperature changes are negligible+' (see Fig. 1). Itturns out that for the SAMIR frequencies (19,22 and 31GHz), the sea-surface emissivity is almost independentof changes in both salinity and temperature butincreases with sea-surface wind speed. The changes inemissivity due to wind speed come about through sea-surface roughness as well as foam-cover andwhitecaps+'.

Since the brightness temperature observed by aspace-borne microwave radiometer depends both onsurface (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 thepast, several workers+" - 26 have developed statisticalregression models based on theoretical simulation aswell as empirical relationships between sea-surfacewind speed and microwave brightness temperature.For the case of Bhaskar-I SAMIR, an empiricalapproach was adopted and the observed brightnesstemperatures at 19 G Hz near nadir were correlatedwith sea-surface wind speed as observed by nearbyMONEX research ships and at coastal stations!", Thebasic assumption made' here was that during the fewdays considered the meteorological conditions do notchange significantly so as to affect the brightnesstemperature. The above analysis, although based on ameagre amount of data, did show a fairly closerelationship between sea-surface wind speed and 19GHz brightness temperature observed by SAMIRonboard Bhaskara-I.

Statistical inversion technique has also been appliedto this problem. For a variety of atmospheric profilesand sea-surface wind conditions observed duringMONEX-1979 and using an empirical relationshipbetween sea-surface wind speed and emissivity+",brightness temperatures at 19, 22 and 31 GHz weresimulated and regression models were developed torelate the observed brightness temperature with sea-surface wind speeds. Several types of regressionequations-linear as well as nonlinear-with two orthree-frequency combinations were tried out. Theseregression equations were then used to derive sea-surface wind speeds from the actual SAMI Robservations and the wind speeds, so derived, werecompared with the available in situ measurements.Care was taken to ensure that the SAMIR footprintover sea does not cover any portion of coast or island,since this would contaminate the brightnesstemperature due to high emissivity ofland surface. As aresult of this exercise it was found that the followinglinear relationship connecting wind speed (SW) with19 and 22 GHz brightness temperature (TB) and havingan rms accuracy of ~ 2.7 m/sec gives fairly consistentresults.

SW= -14.43 -0.1187TB(19)+0.1833TB(22) m/sec

Using the above regression equation with Bhaskara-I SAMIR data during July 1979, wind speeds werederived at a few locations in the Bay of Bengal whereMONEX research ships were stationed. The SAMIR-derived wind speeds were then compared with the insitu measurements of the MONEX ships. (The spatialseparation between ship's position and SAMIRobservation position was limited to 250 km from theconsideration of the SAMIR footprint size as well aspersistence of wind over that distance, whereas the time

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INDIAN J RADIO & SPACE PHYS. VOL. 12. OCTOBER 1983

8

7

• r------------------,• MONE)( SHIPS 1979BHASKARA-I

o R V GAVESHAN I 1982BHASKARA-II

~III 4

4 5 6 7 8 9

SW (SHIP),m/sec

Fig. 5-Comparison of sea-surface wind speed (SW) derived fromSAMIR data (19. 22 GHz) of Bhaskara-I and II with in situ ship data

interval between the SAMIR and in situ measurementwas kept within 2.5 hr.). The results of these comparisonsare shown by a scatter plot in Fig. 5. In Fig. 5, a fewdata points are also included which relate to Bhaskara-II SAMIR data validation compaign+? conducted inJune 1982 where the in situ sea-truth measurementswere made on the ship R V Gaveshani in the ArabianSea concurrent with Bhaskara-II orbital passes.Although the total number of data points is quitelimited, a definite relationship seems to be indicated.Further analysis with better statistics and larger rangeof observed windspeeds would be quite fruitful to testthe validity of the regression model over wider range ofwind speeds and meteorological conditions.

5 Concluding RemarksThe application studies in meteorology and

oceanography carried out with Bhaskara SAMIR datahave been reviewed. In view of the fact that bothBhaskara satellites were essentially experimentalremote sensing satellites, with the demonstration of thefeasibility for the application of SAMIR data inmeteorology and oceanography, the full potential ofthe Bhaskara SAMIR seems to have been well realized.Through these studies we have learnt the basictechnique of handling and interpreting passivemicrowave observation from space. In addition.statistical inversion techniques and formulation ofradiative transfer models have been learnt andmethodologies have been established for retrieval ofgeophysical parameters. Among the differentgeophysical parameters that have been derived fromSAMIR data, atmospheric water vapour content overocean and sea-surface wind speed are the only twoparameters for which validation could be done with thehelp of some in situ data. However, it is most importantto validate such satellite-derived parameters with a

148

much larger data-base of in situ measurements overdifferent periods, in order to have large range ofvariation of the geophysical parameter. Foratmospheric liquid water content derived throughSAMIR data, no in situ measurements of cloud-liquidwater content are available whereas for the rainfall rateestimated over ocean, the situation at present iscomplex due to uncertainties in the input cloud modelparameters. In future, one can use information fromother sources (such as infra-red sounders onboardoperational meteorological satellites) on cloud heightsand work out better models for rainfall rate estimates.

To extend the scope of future microwave remotesensing, additional frequencies suitable for remotesensing of sea-surface temperature and atmospherictemperature profiles may also be incorporated.Meanwhile it may also be worthwhile to carry out a fewfeasibility studies with field/aircraft experiments usingsuitable passive microwave sensors for the de-termination of soil moisture and detection of oil spillsover ocean.

AcknowledgementThe authors would like to express their deep sense of

appreciation to Prof. E V Chitnis, Director, SpaceApplications Centre (SAC) and Prof. P 0 Bhavsar,Chairman, Remote Sensing Area, SAC for their keeninterest in the various aspects related to BhaskaraSAMIR utilization. They would also like toacknowledge Shri 0 P N Calla, Principal Scientist,SAMIR payload, and his team of dedicated engineersfor their hard work and perseverance which resulted inthe successful in-orbit performance of SAMI R. Finally,the authors acknowledge the Data Product Group atSAC for providing the SAMIR data in easily usableform. The SAMIR Data Validation Campaign duringJune 1982 was conducted using the ship R V Gaveshanifor which the authors thank the Director, NationalInstitute of Oceanography, Panjim, Goa. The authorsare thankful to their colleagues Dr S M Bhandari, DrAbhijit Sarkar and Shri B S Gohil for usefuldiscussions during the preparation of the presentreview.

References1 Wilheit T T. Boundary Laver Meteorol (Netherlands). 13 (1977)

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