Indian Journal of Radio & Space PhysicsVol. 24, October 1995; pp. 245-254

Satellite-borne microwave radiometry for atmospheric studies

PCPandey

Space Applications Centre (ISRO); Ahmedabad 380 053

Satellite microwave radiometry research contributions mainly in the field of atmospheric sciencesand ocean-air interaction studies done in India using data from Indian as well as foreign satellitesare reviewed. Geophysical parameters such as precipitable water, cloud liquid water content, windspeed, sea surface temperature, precipitation, temperature profile and.humidity profiles can now beobtained from microwave radiometers with useful accuracy required for weather forecasting, climatestudies and physicaloceanographyapplications.

1 IntroductionThe launch of satellite about three decades ago

and the subsequent developments in the field ofcomputer technology, data transmission, data pro-cessing and archival has given a new dimension toour ability to observe our mother planet earth.The global perspective obtained from the space isunique. Techniques other than space-based alsohave an important role to play in studying andmonitoring our planet. A recent emphasis in thefield of modem earth science is to understand theearth as an integrated system for climate predic-tion. The complexity of the earth as a geophysicalsystem with land, oceans, atmosphere and cryos-phere as its components arises due to the fact thatprocesses on different time and space scales arepresent in the climate components and the differ-ent components interact among themselves. Itsenvironment can be monitored only by satelliteson a global scale. Observations are the backboneof all branches of science and there are greatchallenges in the interpretation of data from thesehigh tech sensors which work in the various por-tions of the electromagnetic spectrum. There arevarious international programmes such as GARP,WCRP, WOCE, TOGA, IGBP, etc. to understandvarious components of our climate systems. Ef-forts made by NASA, USA and currently beingmade by many other countries such as India, Ja-pan, Europe, etc. are playing a major role in earthobservation programme. India's IRSIINSAT-seriesof satellites are an example which are providingdata for monitoring O1,)rnatural resources andweather. These sensors operate in visible/Ik re-gion of electromagnetic (EM) spectrum. The otherregion which has been exploited for remote sens-ing applications is microwaves. The microwaveregion is characterized by much higher transpar-

ency of the atmosphere compared with high ab-sorption properties of the infrared. Not only isthe absorption weaker than in the infrared, butthe effect of scattering is also weaker at theselonger wavelengths. For this reason microwave re-gion is of great value in making observations fromspace of not only the atmosphere but also thesurface .. The gap in EM spectrum is being filledby technological developments such as mm andsub-mm limb sounders being developed by Wa-ters ' at Jet Propulsion Laboratory, USA, which isright at the forefront of technological achievementworldwide.

India entered into space oceanography and at-mospheric sciences with the launch of first Bhas-kara mission in 1979 with a two-channel satellitemicrowave radiometer (SAMIR). This was laterfollowed by an improved mission Bhaskara-IIlaunched in 1981 with a three-channel microwaveradiometer. The first scientific results are report-ed elsewhere+'. The mission provided unique op-portunity to scientists and engineers to learnabout the instruments and the science whichformed the basis in India for advanced researchin this field. Data from sensors such as SMMRonboard SEASAT and NIMBUS-7 and SSWIonboard DMSP, and MSU onboard NOAA oper-ational satellites have also been used in variousapplications".

2 Space-borne microwave radiometerMost radiometers to date that have been flown

on satellites were of Dicke-type except SSM/Iwhich was a total power radiometer. Functionallya microwave radiometer consists of three basicelements: (1) an antenna and associated scanningmechanism to collect radiation from a specifiedbeam pointing direction, (2) a receiver which de-

246 INDIAN J RADIO & SPACE PHYS, OcrOBER 1995

A )t @> 0 [J 0

B 'j T~ @> [Z] [1] 0

cTREF~ L ~

oM--------'L:.. TA

- - - - - - - - - - - ---I ,I,IB-[DJ

- - __ I

-[§::>- Amplifier (Gain G)

{]]- Integrator (Integration time 1')

ill Power or square La w det ector

Fig. I-Block diagram showing the basic principles of radiometer designs (a) The ideal receiver, (b) Total powerradiometer, (c) Dicke radiometer, and (d) Noise injection radiometer.

tects and amplifies the collected radiation within aspecified frequency band, and (3) a data handlingsystem which performs digitizing, multiplexing,and formatting function on the received data aswell as on other calibration and house-keepingdata. Bhaskara SAMIR and SEASAT-SMMRwere of Dicke-type radiometers. Figure 1 showsthe block diagram of different types of radiome-ters described in detail by Ulaby et al.'

The total power radiometer suffers from thestability problems because of gain variations ofRF amplifiers and noise introduced in the system.In 1946, Dicke" found a wayout of largely solvingthe stability problems in radiometers. By using theradiometer not to measure directly the antennatemperature, but rather the difference betweenthis and some known reference temperature, the

sensmvity of measurements to gain and noisetemperature instabilities is greatly reduced. Theswitching frequency (Fs) is normally 1 kHz. Be-fore integration the signal is multiplied by + 1when the switch is at TA and by - 1 when it is atTR, resulting in the subtraction of the signals bythe integrator. For one half of the switching peri-od, the output is

VI = C ( TA+ TN) G

and for the other half,

V2 = - C ( TR + TN) G

... (1)

... (2)

provided that F, is so rapid that TA, TN' and G(where G is the gain of the receiver) 'can be re-garded as constants over the period and that theperiod is much shorter than the integration time.

PANDEY: SATELLITE-BORNE MICROWAVE RADIOMETRY FOR ATMOSPHERIC STUDIES 247

The parameter c is a constant which includes de-rector constant, Boltzmann constant and pre-de-tection bandwidth multiplied together. The outputof the radiometer is found as

VOU!= VI + V2 = c( TA + TN) G- c( TR + TN) G=c(TA-TR)G ... (3)

It is seen that TN is eliminated while G is stillpresent although with less weight. Now G is mul-tiplied by the difference between TA and TRwhere TR is reasonably chosen to be in the samerange as TA, while in total power radiometer case,G was multiplied by the 'sum of TA and ratherlarge TN. A price has to be paid, however, for im-munity to instabilities. As only half of the mea-surement time is spent on the antenna signal, thesensitivity is poorer than total power radiometer.For a Dicke radiometer, the sensitivity is given by

2T.11T= rn-=

yBT... (4)

where T. is the radiometer system noise (K), Bthe pre-detection bandwidth (Hz), and T the post-detection integration time (s). The overall noisetemperature is the sum of the antenna tempera-ture TA and the receiver noise temperature TR,that is

... (5)

Therefore the maximum sensitivity (i.e. smallest11T) is obtained by three factors-by increasingsystem bandwidth, increasing the integration time,and reducing the system temperature. A trade offis made depending upon the interference and sa-tellite motion on Band T respectively.

The calibration procedure establishes a rela-tionship between output (voltages and counts) andinput antenna temperatures. Normally a hot(300 K), a cold (100 K) and sky temperatures areused as calibrators. The instrument is calibratedon ground and also during the flight.

3 Theoretical basis for measurement3.1 Radiative transfer physics

The basic function of a passive microwave sen-sor is to measure the intensity and in some casespolarizations of radiation within the beam of theantenna and within certain frequency bands. For anon-scattering atmosphere in local thermodynam-ic equilibrium and using Rayleigh-Jeans approx-imations, the brightness temperature (Tb) ob-served by a downward looking radiometer at the

top of the atmosphere (pressure assumed to bezero) is given in pressure coordinate as

[

P' aT+ (1- EJ T,.{Ps - 0) T(p)_V (p-+ p.) dpo Op

... (6)

where s, is the surface emissivity, T. the surfacetemperature, and Tv the atmospheric transmit-tance function. The pointing direction of the ar-row indicates the direction of the emission, e.g.ip, -+ 0) means transmittance from surface tospace. OT/Op are called the weighting functionsand are indicative of widths of the atmosphericlayer contributing maximum to the measured radi-ance.

From the standpoint of atmospheric remotesensing, the information we seek is contained inthe second term of right hand side of Eq. (6)which may be regarded as a signal term. The firstterm is a surface-dependent term and may there-fore be regarded as a noise term. If TJps -+ 0) - 0,the first and third terms become negligible inmagnitude. This condition is achieved throughfrequency selection procedure using optimizationtechniques 7. If on the other hand, the satellite-borne radiometers are intended to provide infor-mation about the surface, the frequency should bechosen so that atmospheric transmittanceTv(Ps -+ 0) - 1 and Tb approaches surface bright-ness temperature values. The contribution of thesecond term should be kept minimum.

3.2 Surface emission modellingThe geophysical parameters, namely, sea sur-

face temperature (SST) and salinity (effective forfrequencies less than 3 GHz) enter through emis-sivity term directly into radiative transfer Eq. (6).The presence of wind speed creates surfaceroughness and foams over oceanic surface andchanges emissivity. An empirical emissivity modeldeveloped by Pandey and Kakar" has been usedin Eq. (6).

3.3 Attenuation and emission by atmospheric gasesThe interaction of microwave radiation with at-

mospheric gases is both of resonant and nonreso-nant types. The resonant types are mainly due torotational levels and in some cases due to vibra-tional levels, whereas nonresonant interactions de-pend upon the bulk properties of the gas.

248 INDIAN J RADIO & SPACE PHYS, OcrOBER 1995

A number of molecules exhibit microwavespectral lines, the most prominent ones in atmos-phere being water vapour and oxygen. Water va-pour has rotational spectral line at 22.235 GHzand 183.35 GHz. Oxygen has a series of rotation-al spectral lines which combine into a band with apeak near 60 GHz and a single line at118.75 GHz. Because oxygen is homogeneouslymixed in the atmosphere, the emission near itsspectral line is used to sound the temperatureprofile. Ozone too has a number of absorptionlines below 100 GHz, but they are weak com-pared to water vapour and oxygen lines. In thevalley regions, absorption results from the farwings of water vapour and oxygen lines as well asfrom nonresonant interactions. Clouds and rainsare other sources of absorption of microwave ra-diation which are modelled. An excellent sourceis Waters? for various absorption models of theatmospheric gases.

4 Retrieval theory and techniquesThe radiative transfer model given by Eq. (6),

which is governed by the laws of physics, is a re-lationship of the type T b = f(P), where T b is avector containing antenna temperatures at a num-ber of frequencies and polarization and P is avector of physical parameters influencing themeasurements. A retrieval method should readP= g(T h)' In order to find the function g, severalmethods have been proposed, some of them aredescribed below:

It is possible to recast the physical model givenby Eq. (6) in the form

Th= w·pwhich relates a measurable vector Tb of order nto an unknown vector p of order m (usually m islarger than n) through a known weighting matrixW which is the derivative of brightness tempera-ture with parameters. In practice, we cannot mea-sure the true Tb exactly because of experimentalerrors which may include measurement errorsand modelling errors. Let us denote the observedbrightness as To, where

... (8)

where E is the error vector. The first requirementthat usually needs to be satisfied to invert Eq. (8)is for the number of measurements, n, to be atleast equal to or greater than the number of un-knowns, m.

Most satellite-based retrievals have been doneusing statistical approach and radiative transferphysics. We seek a solution that is linearly related

with observations through a prediction matrix D,i.e.

P'=D'T' o ... (9)

where prime denotes departure from their meanvalues and D is given by

... (10)

which is obtained by minimizing the expected va-lue of the variance of the error in the estimate.The parameter E refers to the expectation valueand the superscript T refers to the transpose. Forthis reason the method is also termed as mini-mum variance method.

The prediction matrix D can be estimated en-tirely from the simultaneous experimental observ-ations of P and To' This requires large statisticsand is completely devoid of physics. We used ra-diative transfer model and climatological database of the geophysical variables to calculate ma-trix D.

Pandey and KakarlO proposed the concept ofusing a subset of channels for the retrieval prob-lems. The subset selection is accomplished by amethod known as Regressions by Leaps andBounds procedure, well known in statistical litera-ture. The technique has a unique capability ofproviding diagnostic and quality control featureson the retrieval, not provided by other methods.The technique has been successfully applied tothe SEASAT-SMMR data analysis 10 and channeloptimization problems 7 such as in TOPEX exper-iment for atmospheric correction.

5 Some examples of scientific resultsOnce the measurement physics is understood

and the theoretical basis and retrieval algorithmdeveloped, the next step is to evaluate and valid-ate the retrievals and set error bars on the retrie-vals. These steps are essential for any meaningfulsatellite data interpretation.

An r.m.s. error in the range 0.2-0.4 g/cm? inwater vapour retrieval was obtained based on li-mited in situ comparisons using MONEX'79 da-ta. Proper utilization of satellite data demands pe-riodic compaigns to evaluate performance of thesensor and retrievals. Figure 2 shows the latitudi-nal variation of total precipitable water over Indi-an oceans. These are sample results, details aregiven elsewhere II .

In addition to the physical methods used forBhaskara data analysis, empirical methods havealso extensively been used in the analysis by Pa-thak and Gautarri'? and Pathak 13. Raina and

PANDEY: SATELLITE-BORNE MICROWAVE RADIOMETRY FOR ATMOSPHERIC STUDIES 249

•....E--'!01

0:IIJ

!;i 7.0~IIJ 6.5 -\-j~ 6.0«!= 5.5Q.

~ 5.0.0:Q. 4.5

~ 4.0«ffi 3.5>« 3.0

5S 0

25 MAY TO 25 JUN E 1982

r?~~, .r/ \1-·~-I ),

I \

I-~ --1----,I I

: 23NOV.1981 TO31 JAN.t982

5N tQN 15N 20N 25NLATITUDE (deg)

Fig. 2-Latitudinal variation of SAMIR-derived precipitablewater.

ghosh 14 have studied water vapour distributionusing Bhaskara data over the Indian subcontinentusing simplifying assumptions of emissivity var-iations of land and compared their results withupward looking radiometer measurements. Bhan-dari et al.15 described the details of the data vali-dation compaign in the Arabian sea. Pandey",Hariharan and Pandey" and Pathak et al:" havereviewed the work done on Bhaskara. Differentaspects of SAMIR data utilization are also de-scribed in a workshop report":

Possibility of wind speed estimation from Bhas-kara SAMIR has also been demonstrated by Pan-dey et al.'? and Viswambharan et al.20 They ob-tained satisfactory results of wind speed whencompared with ship-based measurements undercertain meteorological conditions. Correlation ofBhaskara SAMIR data with sea surface waveheight was also studied by Venkateswara Rao etal.21

The analysis of SEASAT-SMMR data using theretrieval concept proposed by Pandey andKakar '? are given in references+". From multi-spectral measurements, wind speed, precipitablewater and SST were retrieved with an accuracy of± 1.5 m/s, ± 0.4 g/cm- and ± 1.5 K, respectively.Global maps of these quantities on a 10-day basisand monthly basis have also been produced. Thishas been done after proper evaluation and valida-tion of individual retrievals. These satellite-de-rived products are ideally suited for studies relat-ing to climate and its variability. Passive micro-wave radiometers are unique in this respect dueto coarser spatial resolutions.

Values of precipitable water derived from mic-rowave sensors have been used to correct the alti-

0·60.-------------------------~

E 0'4 0

0·50

cot; 0-30,..QI......8 0·20QI

CIa 0'10a:

.'

0-0 0 •..•..•..~......., ...•..•.....•..•..•.•..•....•..•.~ •.•..•..••.•..•..•'-"-'~~~0.00 20·0 40·0 60·0 80·0

Precipite ble wet e r (m m )Fig. 3-Scatter plot between precipitable water and altimeter

range correction.

6CHANNELS: 18 V, 21V 2r.m .s.ERROR O· 40 g/cmDATA POINTS = 62

N

Ev~ 5

cr:::l 4oa,~ 3a:wt-

~ 2

~ 1~III O~ __~ __~ ___L__-J L___~ __~

01234567RADIO~ONDE WATERVAPOUR(g/cm2)

Fig. 4-Comparison of SEASAT-SMMR derived precipitablewater with that of nearby radiosonde data for the month of

September 1978.

meter data"', Figure 3 shows the scatter plot be-tween precipitable water and range correction.

Figure 4 shows the comparison of SMMR de-rived precipitable water with that of nearby radio-sonde giving an r.m.s. error of 0.4 g/cm? based onthe algorithm of Pandey". The mean monthly dis-tribution of precipitable water over the entire glo-bal oceanic regions was also obtained and is de-picted in Fig. 5.

Figure 6 shows the comparison of retrievedwind speed with ship-borne measurements ob-tained during JASIN in the North Atlantic. Theship's observations were corrected for boundary

250 INDIAN J RADIO & SPACE PHYS, OCTOBER 1995

5EA5AT-5MMR MEAN PRECIPITABLE WATER(g/Cnf> 7 -1& JULY 1978

Fig. 5-Global SMMR moisture field for the period 7-18 July1978.

20·0.-------------------------~CHANNELS 10 H, 18 V(J: ',5 m/s

DATA POINTS :134BIAS: -0·16 m/s~18'0

Eoww 12·0o,III

oZ~ 8·0

i ;-

LINE OF PERFECT AGREEMENT

O.O~--~----~~--~~~~~~0·0 4.0 8·0 12·0 , 6' 0 20·0

IN SITU WIND SPEED(m/s)

Fig. 6-SMMR wind speed comparison with JASIN measure-ments.

layer effects using a surface layer parametrizationmodel developed at JPL. It gave an accuracy of± 1.5 mis, better than that provided by algorithmused for routine processing at JPU2.

Figure 7 is a global map of wind speed on amonthly basis obtained by Pandey". The authorhas also compared it with global field obtainedscatterometer and altimeter onboard SEASAT.Although there is in general a good agreement be-tween different fields, there are some discrepan-cies requiring further research.

Figure 8 shows the satellite-derived SST com-parison with expandable Bathy thermograph(XBT) measurements giving an accuracy of 1.4 K.Global maps of SST were also generated andcompared with 20-year climatology records andsimilar 10-day intervals ship reports. Because ofsampling problems, the two results are not quitethe same, but the essential features do agree andare revealed ".

Nimbus- 7 SMMR data were also used to study

precipitable water vapour distribution over Indianregion by Ramesh Kumar et alP They have alsogenerated an Atlas " and used the data to estim-ate evaporation rates over the Arabian sea?".

In June 1987, SSM/I DMSP-F8 was launchedin near polar sun synchronous orbit with horizon-tal and vertical polarization channels for 85.5, 37,and 19.5 GHz except the single polarization chan-nel with 22.235 GHz. The spatial resolution ofthese channels was (16 km x 14 km),(38 km x 30 km), (60 km x 40 km), - and(70 km x 45 km) respectively. The instrument de-tails are described by Hollinger",

Gairola and Krishnamurty" proposed a novelalgorithm to retrieve precipitation from a combi-nation of SSM/I, OLR and surface-based raingauge measurements. These data sets have beenused as initial conditions in numerical weatherprediction models and significant improvementshave been noticed in the medium range weatherforecast. The flow chart of the method of Gairolaand Krishnamurty" is described in Fig. 9.

In another significant study, Gautam et a/.32derived a relation between total precipitable waterand surface level humidity which was later usedby Nimmi Nair et al.33 for studying the seasonaland annual latent heat flux over .the seas aroundIndia. Figure 10 shows the latent heat distributionover Indian oceans for the months of May andJune 1988 characterized by high values of latentheat flux.

Recently efforts have also been made by Basuet al.34 to derive humidity profiles over oceans us-ing a combination of SSM/I derived precipitablewater and empirical orthogonal functions of pastradiosonde profiles for the years 1982-91. Figure11 shows the profiles retrieved by the method andcollocated radiosonde observations for the pur-pose of comparison. These were in the month ofMay 1988 and over different locations in theArabian Sea. NCMRWF is currently planning touse the humidity profiles derived by Basu et al.34

for their medium range numerical weather predic-tion model.

We now explain the basic principles of temper-ature sounding and the results obtained in analys-ing microwave sounding data from TIROS-N sa-tellite. Consider the atmosphere to be divided intolayers each characterized by temperature and ab-sorption coefficients. Temperature sounding isdone with gases with constant mixing ratio suchas oxygen and carbon dioxide. Consider the sens-ing slightly away from the line centre, the contrib-ution to the spacecraft will come from top of the

PANDEY: SATELLITE-BORNE MICROWAVE RADIOMETRY FOR ATMOSPHERIC STUDIES 251

30 60

SEA SAT -SMMR

90 120

SPEED (m /s) 7 July - 6 Aug. 1978

180 210 240 270 330 36060o

30

o

_6oL_~~~t=:L~~~:::::~~~~-'--:=:==-::::"::L~~~~~=~~_~-60o 30 60 90 120 150 180 210 240 270 300 330 360

EAST LONGITUDE (deg)

Fig. 7-Global distribution of SEASAT-SMMR wind speed for the period 7 July-S Aug. 1978.

302r---------------------------~--~300

..DATA POINT: nr.m.s.DlFFERENCE: 1·4 K ,.

CHANNELS USED:6.6V,6.6 H ,18V ••

296 ·.•....292'"'"0::2:~ 288

284 LINE OF PERFECTAGREEMENT

280\'-.__ L.-- '-- '-- '-- L.--__ ~

280 282 286 290 294XBT SST ( K )

(a)

298

4r-------------------------------~3

I· •

·. .... •• :... · ..'" 1 •~ or---------~.~.~~.~'~.~·~~~~~~~5 -1Vi.~ -3

-5~~----~----~----~----~----~280 282 286 290 294 298

PREDICTED SST (K I

(b I

Fig. 8-(a) Comparison of SMMR SST with XBT .sST overthe North Pacific, and (b) residual plots.

atmosphere where concentration of gases is lowand. also the atmosphere above that is also thin sothat little attenuation takes place. On the otherhand, the contribution from the lowest level of at-mosphere will be more but the attenuation of theatmosphere will be very high resulting in a low ra-diation reaching at the spacecraft. In between the

points in the atmosphere for low radiation reach-ing the spacecraft, there will be intermediateheight in the atmosphere which gives maximumradiation. Tills will give rise to a shape called theweighting function or contribution function for agiven channel. Thus by sensing at various chan-nels of an absorption line, it is possible to get thepeak radiation from different portions of the at-mosphere. An inversion process is used to re-cover the profile. One of the problems with nadirsounding described above is the broad weightingfunction and there is a limit to which it can beimproved. Limb sounding offers attractive advan-tages for high vertical resolution but it cannot beused for troposphere due to cloud, haze and dustand is suitable for above troposphere sounding.

Sounding near 60 GHz oxygen channels fromTIROX-N, MSU has been used for.sounding theatmospheric temperature. These sounding profilesare available globally from NOAA as finishedproducts. There is scope for improvements usingseasonal and regional coefficients for retrievals.Gohil et al.35 were the first scientists in India tohave looked into the problem of temperature pro-file retrieval using MSU data. They developed astatistical retrieval technique, demonstrated ascase studies the retrieval of temperature profilesand their comparison with radiosonde tempera-ture profiles at Trivandrum, Cochin, Madras andHyderabad; Figure 12 is an example. Such typesof data could be used for studying phenomenasuch as warm core structure of a tropical cyclone,sudden stratospheric warming, etc. Planned AM-SU will provide sounding up to stratosphere.However, Gohil et al.35 did notice some discre-pancy for retrieval at Hyderabad, without givingany physical explanation of the discrepancy andsuggested further research work.

302

302

252 INDIAN J RADIO & SPACE PHYS, OCTOBER 1995

RegressIOn..,2 RSSMI = 0..,2 ROL +b

Regression of OLRRoin andSSMIRoinbetween 100S to IO"N

Fig. 9-Flow chart for calculating rain rates from a mix of OLR, SSM/I and rain gauge data sets. The far left boxes denote aregression (or sharpening) of OLR rain, the boxes on right denote objective analysis (After Gairola and Krishnamurty-").

0,---------------,

200

(a)

UJo:J•..•.. 5<t..J

~o.0 400E90 100

MAY ..:;600II)II)..Ii:'"•.-c

A- Radiosonde value

(12 GMT)TIROS-N MSUderived value(approx. 10 GMT)

• Present analysisA Standard coefficie- A

l000~ __ ~~~ __ ~_n~t~s~~180 220 260 300

T ( K)

800UJo:J 10•..•..<t 5..J

°4~0--~~~LL--~~~---L-----LL---~~L--L~U60 70 80 90 100LONGITUDE (deg) JUN O,-----------------~

( b)

Fig. lO-Mean monthly latent heat flux field (W/m2) over In-dian oceans for May and June 1988. 200

300 300ACTUAL .... ACTUAL..RETRIEVED_ RETRIEVED_

'D 500 -" 500E 5

w -.UJ ce<r ::>::> Vl 700Vl 700 VlVl UJUJ <r<r Q.Q.

900 -, 900

0,0 5.0 10.0 15.0 20.0 25.0 0.0 5.0 10.0 15.0 20.0 25.0SPECIFIC HUMIDITY(g/kg) SPECIFIC HUMIDITY (g /kg )

~o.0

E 400

- Radiosonde value(12 GMT)

TlROS-N MSUderived value(approx.l0 GMT)

• Present analysisA Stcindard

coefficients

800

1000~ __ ~~ ~~ __ ~~180 220 260

T ( K)Fig. ll-Comparison of humidity profiles retrieved usingSSM/I data and empirical orthogonal function method (After

Basu et aP4)Fig. 12-MSU-radiosonde comparison of temperature profile

over (a) Trivandrum and (b) Cochin (After Gohil et al.35).

PANDEY: SATELLITE-BORNE MICROWAVE RADIOMETRY FOR ATMOSPHERIC STUDIES 253

500.0r--.,----r----r---,---,---,.----,,.---.---,

<0."

WATERVAPOUR

\00·0__ CH.16

CH.19

CH.20CH.3·14

--111---

~ 10·0uito;: 1·0zUJN

CH.17

OXYGEN

40 80 120 160 200 240 280 320FREQUENCY .( GHz )

Fig. 13-Atmospheric absorption lines and AMSU Channelselection.

Sounding near 183 GHz water vapour line willprovide moisture profile with 20 per cent accura-cy, ~s si~ulations suggest. The temperature pro-file IS an mput for moisture profile retrieval. Thissounding is being planned for future NASA mis-sions with very strong emphasis by operationalmeteorologists. Figure 13 shows the spectra of theatmospheric absorption lines and the position ofdifferent AMSU channels.

.Besides the .exciting possibilities with passivemicrowave radiometry in providing geophysicalpr~meters of oceans and atmosphere, some inter-estmg study to extend the usefulness of the micro-wave data to the near coast has been reported byBhandari." by studying several passes of land-seaboundaries based on a deconvolution method.W~lheit and Chang " studied the sensitivity ofbn~htness temperature with various geophysicalvan abIes and had suggested the SMMR channelsonboard SEASAT and NIMBUS- 7 satellites. Pan-dey and Kakar7 studied the radiometer require-ments for correcting the TOPEX altimeter datafor water vapour. Pandey et al.38 also studied thecapability of 31 GHz channel on Bhaskara-Il ascompared to the 19 GHz and recommended itsinclusion in the second Bhaskara mission for bet-ter separation of water vapour and liquid watercontent. SAMlR characteristics have been de-scribed by Calla et al/".

6 Microwave Limb SounderMLS launched on 11 Sep. 1991 onboard

UARS is a 6-band spectrometer near 63, 205and 183 GHz, 15 channels each. These measure-ments are providing tangent pressures and pro-files of the species CIO, 03, H20 required forozone research. There are ten scientific payloadsonboard UARS, each providing complementary

information so as to address the broad scientificissues of upper atmospheric chemistry, dynamicsand radiation balance. The instruments are pro-viding global view of some of the ozone destroy-ing chemicals such as CIO, ozone, S02' etc. as re-ported recently by Waters et al.40

Currently, an ambitious programme of MLS isbeing pursued under the leadership of Dr J WWaters''? at the JPL. An EMLS up to 3000 GHz(earlier it was at 647 GHz) is currently beingplanned for future missions, the next generationof NASNs Earth Observation Missions (£OS). Itwill. provide distribution of several known keyradicals that affect the ozone destruction. Scienti-fic community is looking forward to such an ex-citing mission.

7 Future directionBased on the experience gained in analysing

SAMIR, SMMR, SSM/I and MSU and criticallyevaluating their usefulness, it is recommendedthat India should develop multichannel microwaveradiometry and atmospheric sounder to meetsome of the operational requirements ofNCMRWF and ocean scientific community.

ISRO is already working to launch OC£AN-SAT with a host of sensors working in the micro-wave region to meet the various user require-ments in oceanography and numerical weatherprediction.

AcknowledgementsThe author thanks Dr B V Krishna Murthy, Di-

rector, Space Physics Laboratory, Trivandrum, forinviting him to deliver the lecture at NSSS-94 atTrivandrum and also to write this review article.His sincere thanks are also due to Shri B S GohilShri R M Gairola, Shri Raj Kumar, Dr S K Basu:Dr S M Bhandari, Shri N Gautam, Shri A Varmaand Shri C M Kishtwal for helping him in prepar-ing the manuscript and providing lecture materi-als .:

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board Bhaskara, ISRO Technical Report No. ISRO-TR-16-81 (Indian Space Research Organisation, Bangalore,[ndia),1982.

3_ Project Bhaskara Doc. No. SEO-ISAC-PD-79-11-06-017[[SRO Satellite Centre ([SAC), Bangalore, India], 1979.

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ACRONYMS

Advanced Microwave Sounding UnitDefense Meteorological-Program, (USA)European Centre For Medium Range WeatherForecast

EMLS Enhanced Microwave Limb SounderEOS Earth Observing SystemsFOV Field of View (Instrument)IGBP International Geosphere and Biosphere ProgrammeITCZ Inter Tropical Convergence ZoneJASIN Joint Air-Sea InteractionJPL Jet Propulsion Laboratory, USAMLS Microwave Limb SounderMONEX Monsoon ExperimentMSU Microwave Sounding UrntNASA National Aeronautics and Space AdministrationNCMRWF National Centre for Medium Range Weather

ForecastNational Oceanic and Atmospheric AdministrationOutgoing Long Wave RadiationSpace Applications Centre, Ahamedabad, IndiaSatellite Microwave Radiometer (Indian)Scanning Multichannel Microwave RadiometerSpecial Sensor Microwave ImagerSea Surface TemperatureTropical Global Ocean AtmosphereOcean Topography ExperimentWorld Climate Research ProgrammeWorld Ocean Circulation ExperimentWater Vapour (Integrated)

AMSUDMSPECMWF

NOAAOLRSACSAMIRSMMRSSM/ISSTTOGATOPEXWCRPWOCEWV