A simulation technique for the determination of atmospheric water content with Bhaskara satellite microwave radiometer (SAMIR

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A simulation technique has been developed to estimate the integrated atmospheric water content over oceans using the 19·35 and 22·235 GHz brightness temperature data from satellite microwave radiometer (SAMIR) on board the Indian satellite Bhaskara.
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  Proc. Indian Acad. Sci. (Earth Planet. Scl.), Vol. 90 Number 1, March 1981, pp. 105-110. ~) Printed in India. A simulation teelmique for the determination of atmospheric water content with Bhaskara satellite microwave radiometer (SAMIR) P C PANDEY, A K SHARMA and B S GOI-I/L Meteorology Division, Space Applications Centre, Ahmedabad 380053, India MS received 6 September 1980; revised 20 December 1980 Abstract. A simulation technique has been developed to estimate the integrated atmospheric water content over oceans using the 19"35 and 22.235 GHz brightness temperature data from satellite microwave radiometer (SAMIR) on board the Indian satellite Bhaskara. The results obtained have been compared with those from linear statistical regression and empirical methods as well as from the nearest radiosonde observations. Based on the ~mulation method, a map of total precipitable water for some of the Bhaskara passes in July 1980 over Bay of Bengal is given. The possible applications of such maps in the study of Indian stmamar monsoon and boundary layer characteristics have been l;ointed out. Keywot~Is. Simulation technique; Bhaskara SAMIR; atmospheric water content; brightness temperature. L Introduction The total water vapour and liquid water contents over oceans have been derived by Staelin et al (1976) and Grody (1976) using data from Nimbus E microwave spectrometer. Basharinov etal (1969) and Gurvich and Domin (1970)have derived these quantities using Cosmos-243 microwave radiometer data. In the present paper, the authors have developed a simulation technique to derive total water content over oceans using data from the microwave radiometer (SAM/R) on board the Indian satellite Bhaskara. SAMIR is a two-frequency radiometer, one at 19.35 Glqz and the other at 22.235 GI-Iz. The ground resolution at nadir is 125km and 200kin circle respectively for 19 and 22 GI-Iz frequencies. The temperature resolution of either channel is about 1 ~ K. The instrument collects data at + 5.6, + 2.8, -2-8, -5.6 ~ from nadir along the subsatellite track at 19.35 GHz and at + 11.2, + 2.8, - 2.8, - 11-6 ~ at 22.235GHz. The data at 2.8 ~ look angle have been used in the present analysis. The details are described by Pandey et al (1980). The effect of ocean surface roughness was taken into account using an empirical expression suggested by Hollinger etal (1975), wherever information on ocean surface wind was known; otherwise the wind effect was not included. 105 P.(A~-IO  106 P C Pandey, A K Sharma and B S Gohil Possible applications of total precipitable water and the maps generated there- from for synoptic analysis, boundary layer studies and computation of fluxes of total precipitable water in the study of Indian summer monsoon have been pointed out 2. Math~natical developments For a nonscattering atmosphere in local thermodynamic equilibrittm, the radiative transfer equation describing the intensity of radiation emerging from the atmos- phere can be written in terms of brightness temperature (equivalent black body) as r. fv) = H f T(z)~r "~ (O, H) [% (v) r. + (1 - ".0'))1 ~Z o o x f r (z) ~ ~, (o, z) &. ~ ~Z H O) The three terms on the right side of equation (1) represents (a) the upward emis- sion by the atmosphere, (b) emission by the surface attenuated by the intervening atmosphere and (c) downward emission of the atmosphere that is reflected by the surface and attenuated in its upwelling path by the intervening atmosphere. The satellite altitude, emissivity and sea surface temperature are designated by H, ,~ (v) and T,. Equation (1) can be rewritten in an alternate form as follows : T. iv) = T~ [a v) - ~ v) ~, Co, H) C1 - ,. (v)], (2) H j 1 ~T(Z)... where a (v) = 1 + (1 - z, (Z, H)) To ~ a-., (3) o H f l ~ r (Z) dZ, (4) /J(v) = I - (1 - ~,(Z,~)T.,,(Z,H ~Z o using atmospheric data, the expressions for a (v) and fl (v) ~, (0, H) could be written in terms of total transmittance,. a (0 = A + B~ + C~L (5) (0 ~ (o, ~ = o + E~ + F~', (~) - s - Er) +_ {(B - ~)' - 4 (C - Fr) (A - Or - [TB (01r~ * = 2 ( C Fr) where rfl-~.(v). The constants, A, B, C, D, E and F axe determined using 300, atmospheric simulations with both clear and cloudy atmospheres. The solution of (2) after  Determination of atmospheric water content Table 1. Values of the constants in the rogrossion oquations (5) and (6). 107 Froquaney A B C rrr~ D E F rms OHz orror orror vt= 19" 35 0" 5037 1" 1106 --0" 6289 0"0029 0" 0272 --0"0021 0" 9726 0"C005 v,=22"235 0'8611 0'2679 --0"1384 0"0012 --0"0023 0"0674 0"933 0"0009 substituting (5) and (6) is given in terms of brightness temperature by (6a). The clouds with liquid water contents in the multiple of 0.15 g m -3 with maximum 0.60 g m -s were used in the simulation. The base and top of the cloud were also varied (1.5-5.5 km). The constants in the regression equations (5) and (6) and the r.m.s, error in the determination of a (v) and fl(v)~2 (0, H) using exact expressions [equations (3)-(4)] are given irt table 1. In the case of cloudy atmosphere, the main absorbers of the electromagnetic radiation are water vapour, and oxygen molecule in gaseous phase and liquid water in the form of clouds. The total transmittance can therefore be written as z, = zd (v). (Z,,o (v) 9 ~ (v)). (7) The relation between bracketted parts of (7), for the two frequencies 19 and 22.235GI-Iz, obtained from atmospheric calculations, yielded the following regression equation : z~ (19) %,(19) = a ~,o (22) ~ (22) + b, (8) where a = 0-3846 and b = 0.6155. The transmittance due to cloud is given by (v) = exp (- Q), (9) where v is in Gl-Iz and the parameter k is given by k = 1 -11 x 10t0.012g (~1-T~1)-4] where T,~ = cloud temperature in degree K. From (9), the transmittances due to cloud at 19.35 and 22.235 GHz frequencies are related as 1 (v2) = (a' + b' Q + c' Q~) z,1 (vl) (10) where the constants are given as a' = 1.0, b' = - 0.0318, c' = 0.0005. Equations (7)-(10) can be solved in a straightforward manner to yield z (22) and r (22) %, (22). From (7), (8) and (10), and using atmospheric simulations it is possible to derive the following expressions for total atmospheric water vapour and liquid water contents : 14," = 19.2676 (1 - 1.0365 Z,,o (22) ~o, (22)) (11) ( x(22) ) (12) and Q = 7.6279 1 - ~ (22) ~o, (22) "  108 P C Pandey A K Sharma and B S Gohil However, it should be noted that the above procedure requires the values of Tc~ ,-~ (260 ~ K in the present calculations), sea surface temperature (T, ,-, 300 ~ K) and the emissivity calculated from Fresnel's formula. The increased emissivity due to wind-generated foams and surface roughness could be accounted using the empirical equation given by Hollinger et al (1975) ATs - O. 134 AWf 1/2 (13) where AW is in knots (> 7 knots) f in GI-Iz, and ATe in degree K. 3. Results and discussions The results of the computation using simulation technique are presented in table 2 along with results obtained from other methods. It is seen that the agreement is satisfactory. The antenna pattern correction has not been taken into account while processing the SAMIR data. The effect of different atmospheres used in the simulation to derive the coeffi- cients has also been analysed and the results given in table 3 show that all the three regression equations give the values of W and Q and are within about _+ Based on the simulation method discussed earlier, it is possible to map the total water vapour and study its variations along with auxiliary data such as visible and infrared bands. Such types of global maps have been derived by Grody (1978) using the data from a scanning microwave spectrometer (SCAMS) that was flown on Nimbus 6. Maps for total precipitable water and remotely-sensed sea surface temperature can be used to infer the gross characteristics of the boundary layer over the oceanic regions. This is possible because, on an average, the vertical distribution of water vapour in the atmosphere over the water bodies can be represented with a Table 2. Comparison of total water vapour content (g cm t) and liquid water- content (kgm s) as determined from different methods. Orbit Simulation Statistical Empirical Radiosonde Day 1979 No. W Q W' Q W' Q W Q July 6 434 3 50 1 I 3.68 1 05 4.39 .. 4 4 .. July 8 464 3 92 0.89 4.19 1.03 4 70 .. 4-4 .. July 15 575 4 28 0 57 4-09 0.82 4.62 .. 4 4 .. August 1 829 5'04 0.85 4 70 1 12 5 07 .. 5 3 .. August 3 860 5 17 0.60 4 58 0.94 4 79 .. 5-2 .. August 22 1149 3.65 0.56 3-72 0-73 4-34 .. 4.0 .. August 23 1164 3-57 0-63 3-75 0.78 4.36 .. 4.8 .. September 3 1327 5.92 0.36 4-78 0.84 5.06 ...... October 10 1812 4-59 0 56 4.25 0.84 4.70 ...... October 17 1998 4 55 0 72 4-37 0 97 4 81 ...... Ootober 21 2057 2.99 0.67 3.46 0.74 4 16 ......  Determination of atmospheric water content 109 Table 3. Total water vapour (gem 2) and liquid water contents (kgm 2) determined from simulation method using three different atmospheric conditions for simulation. Day 1979 Orbit Lati- Longi- TB(19) Ta(22) 1st 2nd 3rd No. tude tude (~ K) (~ K) regression regression regression W Q I~ Q Fir Q July 8 464 07-42 72-33 167-8 209 4 3.90 C'88 3-99 0-86 3.89 0.88 July 15 575 10-55 90-11 159 8 206.2 4 28 0.57 4.32 0-56 4 27 0 57 August 1 829 12-42 73--02 172 0 218-6 5 04 0 84 5 10 0'81 5.07 0 83 August3 860 16-08 70-36 165.3 215.3 5 17 0-60 5 21 0-58 5 21 0.59 August22 1149 17-05 69-14 156 0 199 4 3 65 0 56 3 68 0-55 3.61 0.57 August23 1164 07-23 74-19 157 8 200 2 3.~57 0 63 3-62 0 62 3 54 0 64 September 1 1297 23-20 87-70 169 0 218,0 5.24 0 71 5.30 0 68 $'30 0.69 September3 1327 21-32 83-35 162 0 218 0 5-92 0.36 5 94 0.35 5.99 0.34 October5 1812 14-53 80-51 161 0 209.0 4.59 0 56 4-63 0.54 4-60 0,'56 October 17 1998 07-20 80-31 166-0 212 0 4.55 0.72 4.61 0 70 4.56 0-72 October21 2057 18-10 91-46 156 0 195'0 2-30 0.67 3-04 0.66 2 94 0.68 November 7 2311 08-~1 84-35 193-0 219-0 2-04 2 03 2 06 2 03 1-93 2 09 Nowmber 14 2423 11-31 82--42 173.0 219 0 4.99 0-88 5 05 0-86 5.03 0.87 November 22 2542 09--54 88-53 177-0 223 0 5 27 0.98 5.34 0.95 5-35 0 96 simple model. Then some average value of precipitable water W can be asso- ciated to a given surface temperature. The departure of the measured W from the corresponding W relates to the atmospheric stratification in the boundary layer. For instance when W > I~', convective conditions (ITCZ) are present anti when W < W stable condition prevails (Prabhakara etal 1978). In addition, such types of maps could as well be used for calculating fluxes of total precipitable water affecting the monsoon. Ghosh et al (1978) have studied the Indian summer monsoon based on the conventional data alone but it is now conceivable to utilise satellite data for similar studies. Acknowledgements The authors are grateful to Dr T A I-Iariharan, Meteorology Division, for constant encouragement and useful suggestions. Thanks are also due to Prof Yash Pal for his keen interest in the present investigation. The authors are grateful to Dr Norman Grody, NOAA, USA for many useful suggestions through correspondence. The authors acknowledge the benefit of their discus- sions with Drs P S Desai, M S Narayanan and V K Agarwal of the Meteoro- logy Division.
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