The Effects Of Rain On TOPEX/poseidon Altimeter ... - Semantic Scholar

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 35, NO. 5, SEPTEMBER 1997

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The Effects of Rain on TOPEX/Poseidon Altimeter Data Jean Tournadre and June C. Morland

Abstract— The presence of rain in the sub-satellite track can significantly degrade altimeter measurements by causing an attenuation of the backscattered signal, a change in its path length through the atmosphere and a change in the mean square slope of the sea surface. This can cause errors, not only in the measurement of the satellite altitude, but also in the determination of wind speed and wave height. TOPEX/Poseidon dual-frequency altimeter data (cycles 3 and 8) were searched for instances where the data were possibly degraded by the presence of rain over the North and inter-Tropical Atlantic. A subjective analysis of the data, similar to the one used in previous studies was conducted on the backscatter coefficient, wind speed, significant wave height, sea surface height, TOPEX Microwave Radiometer (TMR) brightness temperatures, liquid water content and data quality flags to identify the orbits possibly affected by rain. From the 105 probable rain events identified, the effects of rain on the TOPEX measurements and data quality parameters were characterized. The strong differential effect of rain on the Ku and C band measurements was then used to define a new rain flag based on a departure from the normal relationship between the C and Ku band backscatter. This new rain flag was shown to detect all the identified rain events, as well as new ones. The TMR rain flag, used operationally, was shown to flag too many altimeter samples and too few rain events, mainly because of its large resolution (few tens of kilometers compared to few kilometers for the altimeter). An estimation of the rainfall rate from the attenuation of the Ku band backscatter was proposed. Index Terms—Ku and C bands 0 , rain flag, TOPEX altimeter.

I. INTRODUCTION

S

INCE the launch of Geosat (1985–1989) and the subsequent launches of ERS-1 (1991 to the present), TOPEX/Poseidon (1992–present) and ERS-2 (1995–present), a nearly continuous series of altimeter data is now available for oceanographic studies. Altimeter data have become over the past years a major and standard tool for analyzing the world ocean circulation. The fundamental parameters measured by an altimeter are the significant wave height ( ), the backscatter power ( ) (related to the surface wind) and the time taken for a radar pulse to be reflected from the sea surface. From the Manuscript received April 9, 1996; revised March 3, 1997. This work was supported in part by a contract from the European Union, program MAST, entitled European Community Wave Model (ECAWOM), N MAS2-CT940091. J. Tournadre is with the Département d’Océanographie Spatiale, Institut Fran¸cais de Recherche pour l’Exploitation de la Mer, (IFREMER), 29280 Plouzané, France (e-mail: [email protected]). J. C. Morland is with the Department of Meteorology, University of Reading, Reading, U.K. (e-mail: [email protected]). Publisher Item Identifier S 0196-2892(97)05523-X.

time interval between the emission and reception of the pulse, the satellite height above the sea surface can be calculated. Given information about the satellite orbit and the earth’s geoid, together with various instrumental, atmospheric and tide corrections, it is possible to derive the dynamic topography of the oceans. For most oceanographic studies, the accuracy required for the topographic measurement is of the order of a few centimeters, i.e., the limit of the present systems. To increase the accuracy of the altimeter height measurement, corrections are routinely applied to account for various factors such as atmospheric water vapor, ionospheric time delay, etc. [1]. Among the different atmospheric phenomena which can affect the altimeter measurement, rain is one of the less well understood and at present no reliable correction can be made for the whole range of geophysical parameters. To avoid any contamination by rain, data which are possibly affected are simply discarded using a flag set by concurrent passive microwave measurements. These passive microwave data are also used to calculate an atmospheric water vapor correction to the height and can also give an estimate of atmospheric liquid water [2]. As already pointed out by [3], there are two problems with the discarding of data possibly affected by rain. Firstly, rain events are not randomly distributed in time and space across the oceans and discarding data affected by rain in regions where precipitation is common (such as the intertropical convergence zone or the Arabian sea during the monsoon) might bias the analysis of dynamic topography. Second, the efficacy of the rain flagging algorithm has never been fully assessed, nor has the effect of rain on altimeter measurements. Thus, it is still questionable whether all rain-affected data are flagged or whether good data are falsely discarded due to an incorrect rain detection algorithm. In previous studies [4], [5], careful subjective analysis of the altimeter geophysical parameters have been used to identified possible rain events. This method allowed a good description of the effects of rain on Seasat and ERS-1 altimeter data. However, it can only applied for case studies and can not be used operationally. The main motivations for this study are firstly, to better understand the behavior of altimeter data when rain is present, and secondly, to show that the differential effect of rain on Ku and C band microwave signals [6], [7] can be used to define a better and possibly operational rain flag. A further goal is to investigate the possibility of using dual-frequency altimeter data to make direct measurements of rainfall over the ocean. Precipitation over the ocean is a poorly known quantity

0196–2892/97$10.00  1997 IEEE

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that is crucial for calculating the ocean-atmosphere freshwater flux. A good overview of the theory of the effect of rain on altimeter signals is given in [7], [8]. At Ku and C-band frequencies, where the TOPEX dual-frequency altimeter operates, the prime effect of rain is the attenuation of the pulse. It is an order of magnitude larger at Ku band than at C-band [6]. At high rain rates, in addition to attenuation, rain can also change the shape of the return pulse and hence the measurement of and sea surface height (ssh) can also be affected [8]. Anomalies in radar return due to rain have been reported for Seasat [9] and ERS-1 [4], [5]. The results from these studies can be summarized as follows: 1) all rain events were associated with an attenuation of the Ku band backscatter coefficient and with increased variability in the signal; 2) high rain rates can distort the return waveforms leading to erroneous and ssh measurements; and 3) a small number of cases where the backscatter was attenuated and enhanced in the presence of rain were found. The backscatter enhancement is in general located on the edge of the rain cell [3]. A possible explanation is the damping of short-scale waves by rain [10], which would decrease the mean square slope of the surface and hence increase the backscatter. However, other explanation may exist (see for example [11]). These past studies mostly constituted preliminary investigations where only particular cases were analyzed. A more comprehensive study of the effects of rain on ERS-1 altimeter data was presented by [3]. However, these studies of single frequency altimeter data lacked the additional information from a second altimeter frequency available on the TOPEX/Poseidon altimeter. The data available from the NASA Radar Altimeter (NRA) on board the TOPEX/Poseidon satellite allow a more systematic study of the effect of rain to be carried out. The dual-frequency capabilities of NRA is used to define a more effective rain flag. The paper is laid out as follows. Section II presents a brief summary of the principal results of theoretical studies and of the main results of earlier studies of ERS-1 and TOPEX/Poseidon data. The method used to detect data possibly affected by rain is described in Section III. Several case studies and a statistical analysis of the behavior of different altimeter parameters during rain events are also presented in this section. Section IV presents a new rain flag based on Ku and C band and compares it with the TMR rain flag. Section V examines the attenuation as a function of liquid water content and investigates the possibility of estimating rainfall rate from altimeter data. II. BACKGROUND A. TOPEX/Poseidon Data The TOPEX/Poseidon satellite, which was developed by the National Aeronautics and Space Administration (NASA) and the French Space Agency (CNES) was launched on August 10, 1992. TOPEX/Poseidon is dedicated to ocean altimetry: the orbit, satellite bus and payload are optimized to map the ocean

surface. The satellite carries two altimeters, one developed by CNES and the other by NASA. The single frequency Solid State Altimeter developed by CNES is an experimental instrument intended to demonstrate a new technology. It operates approximately 10% of the time. The NASA Radar Altimeter (NRA), which operates at 13.6 GHz (Ku band) and 5.3 GHz (C band) simultaneously, is the primary sensor of the mission. Only the dual-frequency NRA data will be considered in this study. NRA emits radar pulses at a rate of 4500 Hz in the Ku band and 1200 Hz in the C band [12], [13]. The waveforms received after reflection from the surface and transmission through the atmosphere are averaged onboard in groups of 228 in the Ku band and 50 in the C band, to minimize the impact of noise. These 20 Hz waveforms are interpreted to yield geophysical variables of interest, i.e., the travel time of the radar pulse and thus the altimetric height as well as the significant wave height. The automatic gain control (AGC) of the altimeter is used to calculate the radar cross section, which is related to the surface wind speed [14]. The so-called Witter and Chelton algorithm [15] is used operationally to infer wind speeds from the radar cross section. A detailed description of the NRA instrument and data processing is given in [12], [16]. The TOPEX Microwave Radiometer (TMR) measures the sea surface microwave brightness temperatures at three frequencies (18, 21, and 37 GHz) to provide the total water vapor content of the atmosphere. A detailed description of the instrument and its brightness temperature algorithms is given in [2], [17]. The 21 GHz channel is used primarily for water vapor measurements. The 18 and 37 GHz channels are used to remove the effects of wind speed and cloud cover. The wet tropospheric range correction as well as the liquid water content of the atmosphere are estimated from the triple frequency TMR measurements using the algorithms described by [18]. The liquid water content is used to calculate the delay due to water vapor and to flag the data possibly affected by rain (see Appendix C). It should be noted that these estimate of liquid water are not yet fully validated and are still under question. The TOPEX/Poseidon Geophysical Data Records (GDR’s) used in this study come from the AVISO CD-ROM’s [1]. For each altimeter sample, 128 parameters are available. They are grouped into 11 sets: time, location, altitude, attitude, altimeter range, environmental correction, significant wave height, backscatter coefficient and AGC, geophysical quantity, brightness temperature and data quality flag [1]. In this study, the backscatter coefficient, significant wave height and data quality flag groups are of primary interest. The GDR’s in the Ku and C bands are corrected for the atmospheric attenuation. The Ku band estimate is used to correct both even though the C band correction is smaller. The correction ( ) is computed from the radiometer vapor induced path delay ( ) and liquid water content ( ) by [24]: (1) where

is defined as (2)

TOURNADRE AND MORLAND: EFFECTS OF RAIN ON TOPEX/POSEIDON ALTIMETER DATA

where is given in cm and constants for the Ku band:

, in m

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are the following (3)

For the C band, the correction should be computed with the following parameters [24]: (4) The difference between the two corrective terms is small ( 0.5 dB with a mean value of 0.15 dB). The water vapor correction term ( ) is alway almost negligible. It is less than 0.0025 dB in the Ku band and 0.0001 dB in the C band for less than 50 cm. The liquid water term ( ) is in general very small but can reach 0.6 dB (0.1 dB) in the Ku (C) band for a integrated content of 2000 m. As the correction is not fully validated, especially for the liquid water term and as we are mainly interested with the attenuation of the signal by rain, the GDR atmospheric correction have been subtracted from the Ku and C band . The have then been corrected for water vapor attenuation ( ) using the coefficients given in (3) and (4). The difference between the two corrections is almost constant at 0.03 dB. B. Rain Effects on Altimeter Data All geophysical variables measured by an altimeter can be affected by rain. The results of the principal past studies are summarized in this section. Rain has three possible effects on microwave pulses. Firstly, liquid water alters the refractive index of the atmosphere and lowers the velocity at which microwaves propagate. The arrival of the pulse is thus retarded, artificially increasing the range measured by the altimeter. This error was modeled by [6] and it was showed that at Ku and C-band frequencies the range errors induced by rain can be considered as negligible, except during heavy thunderstorms. Secondly, raindrops scatter some of the energy of the incident pulse back to the sensor, and thus increase the power backscattered to the altimeter. At Ku and C band frequencies, scattering is weak and can be neglected [6] Thirdly, raindrops absorb the altimeter pulse and cause a decrease in the return pulse power. Absorption is the prime contribution of rain to the signal in the Ku and C bands and the attenuation increases with frequency [6]. Fig. 1 shows the dependence of the absorption coefficient on rain rate at various frequencies as calculated by these authors. The attenuation is an order of magnitude larger in the Ku band than in the C band. For instance, a rain rate of 10 mm h and a 5-km thick rain cell causes an attenuation about 4 dB in the Ku band and 0.35 dB in the C band (see the table in Fig. 1). Rain may not be homogeneous over the altimeter footprint, i.e., a rain cell might not completely fill the footprint or the rainfall might vary in intensity across the footprint. When this occurs, the signal received by the altimeter is distorted. The echo return power for given rain cell dimensions was modeled by [8] in order to investigate the effect of changing the position of the rain cell relative to the altimeter nadir. When the rainfall is light, is reduced, and the distortion in the pulse shape is

Fig. 1. The dependence of the absorption coefficient on rain rate at various frequencies [6].

small. For heavier rains, more severe distortion occurs, leading to biases in and ssh measurements. Such distortions were observed on ERS-1 altimeter waveforms [5]. III. REVIEWS

OF

PAST STUDIES

The discussion so far has been based on theoretical models of rain effects. This section goes on to discuss studies made using altimeter data. A preliminary assessment of the effects of rain on ERS-1 altimeter data was made by [4]. They based their criteria for identifying rain events on the experience of [9] that an abrupt change in is always associated with rain. Altimeter data covering a two month period were searched to find 2 dB/50 km. This gradient was judged to be sufficiently steep to eliminate changes caused by wind speed fluctuations. When the wind speed is low, small variations in wind speed can cause large changes in , and to avoid these situations they chose to eliminate cases where dB. For the two month period studied, they found 38 possible and atmospheric rain events. For each event in , the liquid water content along the orbit were examined. They found that rain events were normally associated with decreased backscatter, although they also found one instance of enhanced backscatter. Since the latter was observed at the edge of a rain area, they postulated that it might be due to the rain cell not completely filling the altimeter footprint. Changes in associated with the rain events were also observed. In one instance, where the altimeter passed over Hurricane Andrew, it temporarily lost lock and stopped tracking. An increase in

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Fig. 2. Location of the TOPEX/Poseidon cycle 3 altimeter data (a): which do not pass the 0 Ku band gradient criterion and (b) which do not pass the HS Ku band gradient criterion.

Fig. 3. Rain events identified using gradient criterion ( ) and TMR flagged rain events (o). (a) cycle 3 and (b) cycle 8.

liquid water content was observed with each of the possible rain events. They concluded that although the liquid water content, calculated from the Microwave Sounder data, was a promising rain flag, the changes in liquid water content were not proportional to those in . The study of rain effects was continued by [3] on ERS-1 altimeter data. They used the same criteria as were previously outlined in [4] and searched data covering a two month time period for sharp changes in . Their paper described the observed changes in , atmospheric liquid water content and examined, for two cases, the echo waveforms. They also present an example of enhanced backscatter for which they believe the variation to be totally attributable to rain. An attenuation in followed by a rise was observed,

+

as was an increase in the liquid water content. No change in occurred. They attribute this secondary effect of rain to the damping of short waves on the ocean surface. This can reduce the sea surface mean square slope and thus increase the surface backscatter. They suggest that this effect might occur to some extent in most of the rain events but that it can only be detected in the few cases where and wind speed are low and where the increase due to wave damping overcomes the atmospheric attenuation effect at the edge of a rain cell. Sharp drops in , coincident with sharp rises in and a rise in the liquid water content, were associated with another event. When the waveforms were examined, the leading edge was observed to become progressively shallower as the altimeter footprint passed over the rain cell. The leading edge eventually disappeared, and the track point shifted toward


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Fig. 4. Surface weather map for October 13, 1992, 1200 UT showing a low pressure system centered at 41 N and 32 W. The dashed line represents the TOPEX/Poseidon ground track for pass 11 cycle 3.

the trailing edge. It was concluded that it is this distortion of the waveform shape which causes the to increase. These observations were found to be in good agreement with the theoretical work of [8]. IV. SELECTION

OF

ORBITS POSSIBLY AFFECTED

Using a method similar to the ones used by previous authors [3], [4], the first ten cycles of TOPEX were searched for probable rain events. The set of detected events was then used to analyze the behavior of TOPEX altimeter measurements during rain events and to define a new rain flag. A. Method The first ten cycles of TOPEX/Poseidon data over the North and inter-Tropical Atlantic (20 S–60 N, 10 –70 W) were searched for sharp changes in the Ku and C band and measurements. The following criteria were used: or or

dB m

km km

(5)

represents the parameter gradient. The thresholds where were judged sufficiently high to eliminate small variations in

and caused by geophysical changes of the parameters. at low wind speeds were not excluded Abrupt changes in as rain might occurs under light wind conditions, especially in the Tropics. In practice, this method searches for changes of more than ( ) over nine or less samples in the data 2 dB (m) in records. This corresponds to an along track length of 52 km. To prevent the detection of false cases, a five point running mean filter was applied to remove the effect of outliers. Fig. 2 and presents the location of the samples flagged for the criterion for TOPEX cycle 3 (12 to 22 October 1992). Among the events picked out by these criteria were some which could not be attributed to rain. To distinguish these, the selected orbits were then carefully screened and the behavior and in of the following parameters was examined: the Ku and C bands, the standard errors of these parameters, wind speed, TMR brightness temperatures at 18, 21, and 37 GHz, wet tropospheric correction, liquid water content, ssh and its standard deviation, and data quality flags. To verify that the altimeter anomalies were likely to be associated with precipitation, weather maps and, when available, Special Sensor Microwave Imager (SSM/I) data, were used as an

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Fig. 5. Pass 11 cycle 3 (0930 UT 13 October 1992) TOPEX altimeter measurements over North Atlantic, (a) 0 in the Ku band (solid line) and the C band (thin line), the stars denote the samples flagged by the TMR rain flag, (b) HS in the Ku band (solid line) and in the C band (thin line), (c) TMR liquid water content, LZ , and (d) ssh.

independent means of rain detection. Although it was not possible to completely ascertain the presence of rain, this analysis eliminated problems due to sea ice, small island or land contamination and small fluctuations of low wind speeds which can lead to large fluctuations in . This general philosophy was initially applied to Seasat data [9] and was also used to examine ERS-1 data [4]. Because of the quantity of data involved, only the two TOPEX cycles where the most possible rain events were detected (cycles 3 and 8) were analyzed in detail. This careful subjective analysis identified 105 highly probable rain events, 57 in cycle 3 and 48 in cycle 8. Fig. 3 presents the location of the identified rain events for both cycles. Two groups of rain events can be distinguished

in Fig. 3. The first group is associated with low pressure systems traveling across the North Atlantic. The second one is centered around 5–10 N and is associated with the Inter Tropical Convergence Zone. B. Example of Rain Events The cases presented in this section have been selected to show examples of the wide diversity of behavior exhibited by the altimeter parameters. 1) Cycle 3 Pass 11 (October 13, 1992, 0930UT): During this TOPEX ascending pass, the satellite overflew a low pressure system centered at 41 N and 32 W (Fig. 4). Rapid and sharp drops in are observed at 21 , 24.2 , 24.9 ,


Fig. 6. (top) SSM/I liquid water content, LW85 , from the 85.5 GHz data (0805 UT 13 October 1992) and TOPEX pass 11 cycle 3 (black and white line) and (bottom) LW85 interpolated along the TOPEX ground track.

26.8 , 27.7 , 32.2 , 34 , 35.8 , 43.8 , 51.5 , and 52.5 N (Fig. 5). In some occurrences, attenuation can be as high as 4 dB (24.2 N). Some of these variations are associated with at 21 , 24.2 , 32.2 , 51.5 , and 52.5 N rapid variations of and in two occasions with sharp peaks of and at 24.2 and 32.2 N. The liquid water content estimated from the TMR brightness temperatures ( ) (see Appendix B) exceeds 1000 m at 24.2 and 43.8 N triggering the rain flag. Where measurements are erroneous, so are ssh measurements. ) Fig. 6 presents the SSM/I liquid water content ( estimated from the polarized 85 GHz data (see Appendix C) and the interpolated values along the satellite track. The SSM/I data were obtained at 0805 UT, i.e., one and a half hours before the TOPEX pass. The SSM/I shows the presence of precipitating cells associated with the conveyor belt of the cyclone and with the warm front. Regions of sharp variations in are associated with high value of . The behavior of the parameters varies greatly for the three probable rain events detected along this track at 24 -25 , 32.2 , 35.8 N by the subjective analysis. The cases are examined in detail in the following. Case 1 (Fig. 7): This case corresponds to a simple case of attenuation by a quite intense rain cell observed at 35.8 N. The attenuation of reaches 2 dB at 35.8 N. The TMR

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liquid water content rises to about 250 m, far below the 1000 m threshold used for the rain flag. in both bands is quite constant at around 2.5 m. The rms of the ssh stays within the standard limits ( 15 cm) but a relatively high value of 10 cm coincides with the maximum observed attenuation. At this location, a rise of about 10 cm, which might be attributed to rain, is observed in the ssh data. Except for one sample, where the high rate waveform flag is set, the measurement conditions are good. A slight enhancement of of about half a decibel is observed at 35.8 N at the center of the cell. It might result from damping of capillary waves by rain. Four samples are flagged by the gradient criterion for near 35.8 N. The attenuation is significant for four samples, giving an apparent rain cell diameter of about 10 km. The rain rate, calculated from the results of [6] and for a 5 km thickness rain cell, is about 5 mm h . The peak of TMR liquid water content centered at 35.8 indicates the presence of a cloud, albeit a non precipitating one. However, SSM/I data confirm the presence of precipitating cells near the cold front at 36 N ( peak of 0.7 kg/m ). The small size of the rain cell, the difference of resolution between the TMR (40 km for the 18GHz channel) and the altimeter (3 km) and/or a calibration problem with the liquid water content algorithm might explain the non detection of rain by the TMR. Around 34 N, is enhanced by almost 1 dB then attenuated by 0.7 dB, while the liquid water content reaches 250 m. Similar behavior in the Ku band altimeter measurements were presented by [3]. This pattern is very probably associated with a smaller and weaker rain cell. Case 2 (Fig. 8): This case is that of a large rain event detected by both the TMR and our subjective analysis. Two large drops in are observed at 24.2 N and 24.7 N. The region is broad enough to exhibit some structure within it. The attenuation of reaches 3 dB at 24.3 N and 2 dB measurements in both Ku and C bands are at 24.7 N. erroneous between 24.2 and 24.4 N. The same is true of ssh measurements. This results from the large distortion of the return waveforms by rain which causes the data quality flag to attenuation be triggered for all these samples. Where the is enhanced by 2 dB. The data quality flags is greatest, is quite unreliable. The enhancement of indicate that could be associated with a modification of the sea surface roughness. The TMR liquid water content is high enough to trigger the rain flag between 24.25 N and 24.8 N. However, the flagged points only partially overlap the area of attenuation. This is especially true for the edges of the rain cell. This again results almost certainly from the difference of resolution and from the averaging of the brightness temperatures. SSM/I data shows the presence of squall lines within the conveyor belt of the cyclone at around 25 N. It should be noted that the gradient criteria tend to prefervariation entially flag the edge of the rain cell where the is larger. Case 3 (Fig. 9): This case is an example of a rain cell which was detected by TMR but which was unseen by the gradient criterion. A rain event of about 60 km extent (12 samples) is detected by TMR between 43.4 and 44 N. The

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Fig. 7. TOPEX altimeter profiles for TOPEX pass 11 cycle 3 (first example), (a) 0 in the Ku band (thin solid line) and the C band (solid line) (3.9 dB have been subtracted from 0C to give similar scales between Ku and C bands); samples flagged by the TMR: stars; samples flagged by the new rain flag: circles, (b) HS in Ku (solid line) and C band (thin line), (c) TMR liquid water content, (d) ssh (solid line) and ten times the rms of the ssh (thin line), (e) departure from the normal C/Ku relationship (solid line) and rms of the relation (thin line), (f) data quality flag Alt_bad_1, the samples where a flag is set are represented by stars, (g) gradient flag (bit 0: 0Ku , bit 1: 0C , bit 2 HSKu , bit 3: HSC ).

liquid water content reaches 1500 m. At this location, is attenuated by less than 1 dB and the gradient is not high enough to be signaled. An enhancement of 0.5 dB is observed at the southern edge of the cell associated with a small peak . Except for one sample where the rms ( 0.5m) of reaches 9 cm, ssh appears unaffected by rain. 2) Cycle 8 Pass 202 (December 9, 1992, 0959UT) (Fig. 11): When looking for data possibly affected by rain, [3] discarded exceeded 12 dB, i.e., light winds ( 4 m/s), data where because in this regime, small variation in wind speed can cause large fluctuations in . However, especially in tropical and

equatorial regions, rain can occur under light wind condition and for this reason, such a restriction was not applied in our analysis. The presence of rain is difficult to ascertain under can light wind condition, as in both the Ku and C bands fluctuate by several decibels. Therefore, TMR liquid water content and SSM/I data were used to help in the decision. The following case is an example of the detection of rain under light wind speed conditions. Fig. 10 presents SSM/I liquid water content obtained at 0928UT as well as the TOPEX ground track. The time lag of less than half an hour between the two satellite observations allows a good comparison of the


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Fig. 8. Same as Fig. 7 for the second example.

data. The SSM/I data show that near 22 N, TOPEX overflew a cloud which was associated with a liquid water content of over 0.7 kg/m , and was therefore very likely to precipitate. The presence of precipitation is also detected by TMR (Fig. 11) near 21.5 N. Between 21 N and 22 N, large fluctuations in the backscatter of several dB are observed in both bands, they may result from wind speed fluctuations associated with the rain cell. As a result of these large variations of , the gradient criteria is set for almost all the samples making the detection difficult. C. Statistical Analysis of the Behavior of the Parameters The different examples shown in the previous section illustrate the widely varying behavior of the altimeter data during rain events. This section attempts to quantify several of the

observations, and to give an idea of how frequently they occur. This analysis is performed on the 105 possible rain events detected over the North Atlantic during cycles 3 and 8 of TOPEX by the gradient criteria and the subjective analysis. The behavior of the following parameters was analyzed: and in both the Ku and C bands, the TMR liquid water content and rain flag, the ssh and its rms and the data quality flag. As can be seen from the examples described in the previous section, the samples where rain attenuates the altimeter signal do not necessarily overlap all the samples flagged for rain by TMR or by the measurement condition flags (Fig. 8). In this analysis, a rain event is considered flagged if at least one point is attenuated is flagged. Table I summarizes the where results of this statistical analysis.

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Fig. 9. Same as Fig. 7 for the third example.

For the data quality flag, indicating altimeter measurement problems, each bit signals about 40% of the rain events, with the exception of Bit 2 which flagged over 60% of the cases identified. Bit 2 indicates that too many high rate waveforms used to compute the one per second values are flagged, certainly as a result of some waveform distortion caused by rain. The TMR liquid water content exceeds 200 m in all the cases, 500 m in 64% and 1000 m in only 36%, triggering the rain flag. Table II summarizes the behavior of the altimeter parameters during the detected rain events. All of the events show some effect on the backscatter coefficient. As expected, given that rain absorbs the altimeter pulse, an attenuation in the Ku band

is observed in all cases. It is associated in 28 cases (27%) with enhanced Ku band backscatter, such as the example is rarely attenuated (10 given in Fig. 9. In contrast, cases, 9%). The troughs are generally observed under light wind conditions. The number of events (36, 34%) displaying enhanced backscatter in the C band such as the example given in Fig. 8 is similar to that in the Ku band. However, increases is attenuated in the in the C band generally occur where Ku band (see Fig. 7 and 8). Wave height measurements are only affected in 49 cases (47%). This is to be expected since only heavy rain cells cause the inhomogeneous absorption which deforms the waveforms and affects the values [8]. A larger percentage of events are observed to show changes in the Ku (47%) than in the C


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Fig. 10. (top) SSM/I liquid water content, LW85 , from the 85.5 GHz data (0928UT 9 December 1992) and TOPEX cycle 8 pass 202 ground track (white and black line), (bottom) LW85 interpolated along the TOPEX ground track.

TABLE I TOPEX DATA QUALITY FLAGS, TMR RAIN FLAG, AND LIQUID WATER CONTENT DURING THE 105 PROBABLE RAIN EVENTS

band (36%) signal, which is not surprising considering that absorption in the Ku band is stronger than that in the C band. Changes in the ssh measurement could be expected to occur at the same time as changes in the measurement, since both are related to instrumental problems occurring as a result of differential absorption across the altimeter footprint. In more than 50% of the cases, some changes are observed in ssh (peak or trough), although it is often difficult to discriminate between possible rain effects and normal ssh variability. The rms of the ssh exceeds 10 cm in two thirds of the cases and in one third it is over 15 cm, triggering the ssh quality flag (bit 4).

BEHAVIOR

OF

TABLE II ALTIMETER PARAMETERS DURING

THE

DETECTED RAIN EVENTS

D. Discussion of Unusual Observations So far only the atmospheric effect on rain on the microwave signal has been considered, but it is by no means the only contribution to measurement errors. An explanation of the measurement (such as enhanced unexpected features in the backscatter in the Ku and C band) may lie in the modification of the sea surface roughness by rain drops. When a raindrop strikes a relatively calm water surface, a crown forms around the point of impact. This subsides and

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Fig. 11.

Same as Fig. 7 for the fourth example.

a stalk appears which grows to a height of 2 to 3 cm. Its lifetime is less than 0.1 s, but as it develops it generates rings of gravity-capillary waves, which have a wavelength of 1 to 2 cm and a lifetime on the order of tens of seconds. The rings can expand to a diameter of 25 to 50 cm before they disappear [11], [21]. Surface roughening by rain decreases the number of specular surfaces from which the altimeter signal can be reflected, and thus causes the backscattered power to decrease. Since surface roughening increases with rain rate, so does the effect on the echo signal. The magnitude of the effect also varies with frequency as it depends on the similarity of the radar pulse wavelength to that of the surface waves [19], [20]. Although it increases the roughness of a relatively calm sea surface, rain dampens sea waves when the surface is rough.

This phenomenon has been observed for centuries, but the exact mechanism by which it occurs is ill understood. It is thought that rainfall increases the viscosity or turbulence of a thin layer near the surface, and thus dampens the waves, since the decay of surface gravity waves increases with viscosity. Short waves are the most severely affected, but long waves also lose their energy through wave-wave interactions. The resulting decrease in surface roughness decreases the wind stress and impedes the growth of long waves [10], [11]. The power backscattered to a Synthetic Aperture Radar (SAR) increases with sea surface roughness. Echo-free holes have been observed in Seasat 23 cm (1.3 GHz) SAR images [11]. These correspond to areas where rain has smoothed the sea surface to the point where no echo is received by the


Fig. 12.

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(a)

Scatter plot of 0 of the C and Ku bands for TOPEX cycle 8.

instrument. This could explain the features observed in the C band in Fig. 8 where a strong enhancement of is observed in the center of the rain cell where is most attenuated. Occasionally an area of high radar return was also observed in SAR images near the center of the echo-free hole. This was thought to be caused by an increase in small-scale surface roughness as a result of the rain splash features described above. V. A NEW RAIN FLAG BASED Ku/C RELATION SHIP

ON THE

A. Definition The previous analysis showed that neither the TMR rain flag nor the gradient criterion signal all the possible rain events detected by a careful analysis of TOPEX cycles 3 and 8. From the observations, it has been shown that rain (at least when it is strong enough) attenuates . The behavior of is more complex. Enhancement is more frequently observed than attenuation; and when a trough is observed, it is generally related to a wind speed variation and is much weaker than in the Ku band. According to theory, rain absorption in the Ku band is greater than that in the C band (see Section II) by an order of magnitude, and therefore rain should affect the normal relationship between the Ku and C bands, i.e., under clear sky conditions. The possibility of using this change as a basis for defining a rain flag was explored. A theoretical relationship between Ku and C band backscatter was proposed by [22]; however, problems still remain especially for low wind speeds, and the relation cannot yet be used operationally. To avoid this problem, as well as any intercalibration problems, we choose to use the observed in both bands to determine for each cycle a mean relationship (C versus Ku) as well as a standard

(b)

6 1 rms); (a) cycle 3 and (b) cycle 8.

Fig. 13. C/Ku band relationship: (

deviation around this relation. Fig. 12 presents the scatter plot of the cycle 8 measurements of in both bands for which the samples were not flagged for data quality and the attitude was less than 0.1 . Fig. 13 presents the relationship ( 1 rms) estimated for cycle 3 and 8. Except for very low and very high wind speed, i.e., high and low, where few data points are available, the relationship is almost identical for the two cycles. It can be considered to be linear with two regimes, a 11 dB, i.e., wind 1.3 slope for high wind speeds ( speed 6–7 m/s) and 1.0 slope for low winds. This change of regime around 7m/s is also observed in the versus wind speed relationship [23].

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BEHAVIOR

(a)

OF

TABLE III ALTIMETER PARAMETERS DURING

THE

NEW RAIN EVENTS

TABLE IV STATISTICAL ANALYSIS OF THE SAMPLES FLAGGED BY THE TMR RAIN FLAG AND BY THE NEW RAIN FLAG

(b) Fig. 14. Rain events identified in Section II (circles), flagged by the new rain flag (pluses) and by the TMR rain flag (crosses): (a) cycle 3 and (b) cycle 8.

The main idea of our rain flag is to search for occurrences where is significantly attenuated as compared to . As the difference between the two channels might result from other phenomena than rain, especially for low winds, the TMR liquid water content is also used to ensure the presence of cloud liquid water. The new rain detection criteria are defined as rms m

(6)

where is the Ku/C band relationship, rms is the standard deviation of this relation, and is the TMR liquid water is the expected predicted from content estimate. the measurement. It should be noted that this expected value could be used to estimate a rain-free wind speed.

Table II shows that these criteria signal all the events of Section IV. The difference ( ) between the expected and measured , and the associated rms are presented in Fig. 7 to 10 for the different examples given in Section III. The new rain flag detects all the cases given as examples including the third one which was not detected by the gradient criterion (Fig 9). Only samples where attenuation is larger than the geophysical/instrumental variability are signaled. Using (6), 505 samples are flagged in cycle 3 and 425 in cycle 8., i.e., about 1% of the data. These samples can be regrouped as 87 rain events for cycle 3 and 91 for cycle 8 (Fig 14). The 30 40 new rain events were carefully analyzed to investigate the possibility of false alarm. The results of this analysis are summarized in Table III. The Ku/C rain flag signals 31 events which were detected by TMR but which were unseen by the gradient criterion. The liquid water content is above 500 m in 49 cases (70%). The overall measurement conditions are most of the time nominal since less than 10% of the events are also signaled by a data quality flag, except for bit 2 of Alt_Bad_1 which is signaled in 17% of the cases. A careful analysis of the new events, similar to the one used in Section III, did not reveal any dubious cases


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(a)

(b)

1

Fig. 15. (a) Attenuation estimated as the difference between the values expected in the Ku band from C and Ku band measurements, 0 , as a function of TMR liquid water content LW85 . (b) 0 as a function of the GDR’s atmospheric attenuation correction. The solid lines represent the regression lines of the two parameters.

1

and the probability of false alarm can be considered as low. Compared to the gradient criterion which tends to flag too many samples and to detect the edges of the rain cells (where the variation is more important), the new rain flag picks out only the samples where the Ku band signal is attenuated.

The difference of resolution between TMR and the altimeter can also explain the difference observed in the number of samples flagged by the two rain flags where measurements conditions are nominal. Small heavy rain cells might not be detected by TMR but they can strongly affect the shape of the pulse thus causing the data quality flags to be set.

B. Comparison with the TMR Rain Flag The TMR rain flag is set on for 470 and 661 samples in cycles 3 and 8, respectively (Table IV). The TMR flagged samples can be regrouped into 39 events for cycle 3 and 40 for cycle 8 (Fig. 14). Although the number of flagged samples is somewhat larger than the number of samples flagged by the Ku/C flag, the TMR rain flag signals less than half of the rain events picked out by the Ku/C flag. The mean extent of a rain event is nearly three times larger when flagged by TMR ( 14 samples, 80 km) than when flagged by the C/Ku criterion. ( 5 samples, 25 km). When rain is heavy enough and/or when the rain cell is large enough to trigger the TMR rain flag, the number of flagged samples is too large, certainly because of the large footprint (Fig. 9). When the size of the rain cell is small compared to the TMR footprint, the liquid water content does not exceed the rain threshold and samples which are almost certainly affected by rain will be undetected (Fig. 7).

VI. RAIN ATTENUATION

AND

RAIN RATE

The dual-frequency capability of the TOPEX altimeter can also be used to investigate the attenuation as a function of liquid water and to estimate the rainfall rate. A. Attenuation Samples were selected from cycles 3 and 8 for which the TMR liquid water content was above 100 m was positive (i.e., Ku attenuated versus C), and measurement conditions were nominal were selected. As can be enhanced during rain events, samples where the variation over 5 samples was greater than 0.3 dB were discarded. This removes samples where enhancement is too large. Fig. 15 presents the scatter plot of the absolute two-way path attenuation in the Ku band versus coincident TMR liquid water content. The large dispersion observed for greater than 500 m might

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Fig. 16.


Rainfall rate (in mm h01 ) estimates for the rain flagged samples of cycle 3.

result from the difference in sensors resolution and/or from a calibration problems in the retrieval algorithm. The linear regression of the data gives the following relationship: (7) Fig. 15 also presents the attenuation estimated from C and Ku band measurements versus the two-way atmospheric attenuation correction applied to the Ku band backscatter as given in the TOPEX AVISO GDR’s (see Section II). The correction of atmospheric attenuation appears largely underestimated compared to the observed attenuation. As the water vapor term is almost negligible, (7) can be used to estimate the atmospheric attenuation of the signal in the Ku band. VII. RAINFALL RATE ESTIMATE Since the launch of Seasat, different studies of the possibilities of rain measurements from radar altimeter have been conducted [25], [26]. These studies proposed to relate the echo power in various range bin to the rain rate. Again, the dualfrequency capability of NRA allows a much simpler approach to the problem which can be outlined as follows. The coefficient of attenuation by rain (k) can be expressed by the empirical relation [27]: (8) where k is the absorption coefficient in dB km , R is the rainfall rate in mm h and a and b are coefficients dependent on the frequency of the radar pulse. The total attenuation (A), for a two-way path, is given by: (9) where l is the rain thickness. The rainfall rate, R, is calculated as follows: (10) The absorption in the C band is normally on the order of fractions of a decibel. For a rainfall rate of 10 mm h and a

rain cell thickness of 5 km the C band attenuation is 0.26 dB compared with 4.5 dB in the Ku band. Rainfall rates exceeding 10 mm/h occur only 0.2% of the time [26]. In a first order approximation, absorption in the Ku band can be estimated by the difference between the expected and observed . The a and b coefficients used were those given by [27]. (11) for Ku band, and (12) for C band. As rainfall rate could be overestimated if is enhanced, samples where the standard deviation is larger than 0.3 dB are discarded. Fig. 16 presents the rainfall rate estimated for the samples of cycle 3 which were flagged as affected by rain. Rainfall rate varies from 2 to 20 mm h . VIII. CONCLUSION The present study presents an investigation of the effects of rain on TOPEX/Poseidon NASA Radar Altimeter data, the aims being to evaluate the effectiveness of the TOPEX data quality flags in signaling problems due to rain, to characterize the effects of rain on TOPEX measurements, and to define a new rain flag. The theoretical aspects of rain absorption have been studied by [8], [6], [25], [28], [7]. A few studies have been made using altimeter data, namely those by [9], [4], [5], but none have involved TOPEX/Poseidon data. Two cycles of TOPEX/Poseidon altimeter data were searched for possible rain events using criteria based on the detection of sharp changes in and . The data quality flags and altimeter measurements for two cycles were also examined. A statistical analysis was conducted for the 105 probable rain events identified. The TMR liquid water content exceeds 1000 m in only 39 cases (36%) triggering the rain flag. As expected from atmospheric attenuation arguments, a reduction of in the Ku band is always observed, associated in one third of the cases with enhanced backscatter. A drop is rarely observed (9%) and is in general in the C band associated with low wind speed variations. Enhanced C band


backscatter occurs in about 34% of the rain events. A possible cause of the enhanced backscatter could lie in wave-damping effects due to rain. For heavy rains, theory predicts that the echo waveforms can be distorted, leading to erroneous and ssh measurements. When the distortion is important, data quality flags are set and the data can easily be removed. However, in nearly 20% of the studied rain events, some changes in ssh are observed under nominal measurement conditions. It is thus possible that a rain cell can produce shifts of some centimeters in ssh, such as in Fig. 8 at 24.8 N, leading to artificially higher variability. Peaks in measurements observed in half of the cases can also lead to an overestimation of electromagnetic bias correction and can therefore affect the ssh measurements. Since the criteria for detecting sharp changes of backscatter flagged too many samples as well as being difficult to implement operationally, and since the rain flag based on coincident brightness temperature measurements does not detect all rain events, a new rain flag based on the dual-frequency capabilities of TOPEX NRA is proposed. According to the theory and previous studies of microwave signal, attenuation by rain is an order of magnitude larger in the Ku band than that in the C band. The analysis of the identified rain events confirms this result. The new rain flag searches for occurrences where the measured is attenuated compared to the value expected from the measured by more than 1.9 rms. The expected value and rms are calculated from the observed C/Ku pairs to avoid any calibration problem. To ensure the presence of cloud, samples where the TMR liquid water is under 200 m are discarded. This new rain flag signals all the identified rain events. It also flags new events where the variation due to attenuation was not high enough to be detected by the gradient criterion. Some of these events were also detected by the TMR. The signal is significantly attenuated in about half of the rain events signaled by the TMR and this proportion falls to only 35% after a sample by sample analysis. A large proportion of the samples flagged by the TMR could be used for analysis. The discrepancy between the two flags almost certainly results from the large difference of resolution of the two sensors, few tens of kilometer for TMR, and few kilometers for NRA. The new rain flag appears very promising for operational use as it relies on simple criteria and only flags affected samples. The differential attenuation of the Ku and C band signals by rain can be used to estimate the attenuation as a function of liquid water content in view to improve the correction of single frequency Ku band altimeter measurements, such as the ERS-1 and ERS-2 ones [30]. The analysis of the data from two TOPEX cycles shows that the correction used for the ERS-1 altimeter might be underestimated by a factor of two. The difference between the expected and measured can be considered as an estimate of the attenuation by atmospheric liquid water and can be used to estimate the rainfall rate. APPENDIX A DATA QUALITY FLAG The data quality flag, named Alt-Bad_1 in the AVISO merged products [1], indicates whether problems were detected

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in the altimeter measurements conditions. It concerns the quality of the measuring conditions of the data products obtained from averaging the ten per second echo waveforms. Bit 0 Indicator is on if the compression used is median. Normally the mean of the ten measurements is taken, but if the data are anomalous, the median value is used. Bit 1 Indicator is on if the fit of the waveform leaves too many invalid points. Bit 2 Indicator is on if too many ten per second waveforms cannot be fitted by a theoretical waveform. Bit 3 Indicator is on for the TFLAG. Bit 4 Indicator is on if the slope fitted to the ten measurements is too steep. Bit 5 Indicator is on if the r.m.s. of the one per second altimeter range quality exceeds 15 cm. Bit 6 Indicator is on if too many errors are reported in the dual-frequency ionospheric correction. APPENDIX B TMR LIQUID WATER CONTENT

AND

RAIN FLAG

A complete description of the TMR instrument and brightness temperature algorithm is given in [2], [17], [18]. Expressed in terms of kilometers on the ground seen at nadir from the TOPEX orbit, the half-power beam width is 43.4 km at 18 GHz, 36.4 km at 21 GHz and 22.9 km at 37 GHz, whereas the effective altimeter footprint diameter is on the order of 3 km [29]. Since the three channels may not integrate the same atmospheric patterns, ground processing partly solves the problem by averaging along track brightness temperatures [24]. The rain flag, given in the merged TOPEX/Poseidon products, is based on an algorithm for detecting excess liquid water in the atmosphere [1]. The atmospheric liquid water content, , is calculated from the TMR brightness temperatures at 18, 21, and 37 GHz [18], and [31], using the following relationship: (13)

(14) If

m then (15)

Otherwise, when m The rain flag is signaled whenever exceeds 1000 m. This threshold was chosen on the basis of observations made by ground-based water vapor radiometers. Rain was almost always present when the liquid water measurement exceeded 1500 m. If Lz, averaged over a 40 km footprint, exceeds 1000 m, rain is almost certainly present over a significant fraction of the footprint. The rain flag is also triggered if the brightness temperature are of the following limits: (16)

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APPENDIX C SSM/I LIQUID WATER CONTENT To derive the integrated cloud liquid water (or, equivalently, the liquid water path), [32] showed that in the absence of anisotropic extinction by precipitation particles, the normalized polarization difference ( ) at any SSM/I frequency is well approximated by the effective transmittance associated with cloud liquid water, raised to a power. That is,

(17) is the effective mass extinction coefficient of the where liquid water in the cloud, is the liquid water path, is the SSM/I viewing angle (53.1 ). Using a model and assuming conditions typical for marine stratocumulus to determine , [32] inverted the above expression to obtain the liquid water path ( ) from the 85.5 GHz channels (in kg. m ): (18) The normalized polarization difference,

is given by

(19)

where are the brightness temperature at 85.5 GHz in vertical and horizontal polarization, the wind speed estimated from the brightness temperature and the integrated water vapor. ACKNOWLEDGMENT The authors wish to thank B. Chapron and A. Cavanié of IFREMER for fruitful discussions and comments, to M. Srokosz of the James Rennell Center who initiated the study, and to D. Vandemark and G. Hayne of the NASA Goddard Space Flight Center for their assistance with the TOPEX data. The authors acknowledge the AVISO group for providing them with a copy of the TOPEX/Poseidon CD-ROM’s. REFERENCES [1] AVISO, Aviso User Handbook: Merged TOPEX/Poseidon Products, AVI-NT-02-101-CN, Edition 2.1, 1992. [2] C. Ruf, S. J. Keihm, and M. A. Janssen, “TOPEX/Poseidon Microwave Radiometer (TMR): I Instrument description and antenna temperature calibration,” IEEE Trans. Geosci. Remote Sensing, vol. 33, pp. 125–137, Jan. 1995. [3] T. H. Guymer, G. D. Quartly, and M. A. Srokosz, “The effect of rain on ERS-1 altimeter data,” J. Atmos. Ocean. Technol., vol. 12, pp. 1229–1247, 1995. [4] T. H. Guymer and G. D. Quartly, “The effect of rain on ERS-1 altimeter data,” Proc. First ERS-1 Symp.—Space at the Service of our Environment, Cannes, France, 4–6 Nov. 1992, ESA SP-359, 1993. [5] G. D. Quartly, T. H. Guymer, and S. W. Laxon, “Detection of rain cells in altimeter returns,” Proc. Second ERS-1 Symp. —Space at the Service of our Environment, Hamburg, Germany, 11–14 Oct.1993, ESA SP-361, pp. 799–804, 1994.

[6] J. Goldhirsh and J. R. Rowland, “A tutorial assessment of atmospheric height uncertainties for high-precision satellite altimeter missions to monitor ocean currents,” IEEE Trans. Geosci. Remote Sensing, vol. GE-20, pp. 418–434, 1982. [7] E. J. Walsh, F. M. Monaldo, and J. Goldhirsh, “Rain and cloud effects on a satellite dual-frequency radar altimeter operating at 13.5 GHz and 35 GHz,” IEEE Trans. Geosci. Remote Sensing, vol. GE-22, pp. 615–622, 1984. [8] D. E. Barrick and B. J. Lipa, “Analysis and interpretation of altimeter sea echo,” Adv. Geophys., vol. 27, pp. 61–100, 1985. [9] M. A. Srokosz and T. H. Guymer, “A study of the effect of rain on Seasat radar altimeter data,” Proc. IGARSS ‘88 Symp., Edinburgh, Scotland, 13–16 Sept. 1988, ESA SP-284, pp. 651–654, 1988. [10] M. Tsimplis and S. A. Thorpe, “Wave damping by rain,” Nature, vol. 342, pp 893–895, 1989. [11] D. Atlas, “Footprints of storms on the sea: A view from spaceborne synthetic aperture radar,” J. Geophys. Res., 99, C4, pp. 7961–7969, 1994. [12] A. R. Zieger, D. W. Hancock, G. S. Hayne, and C. L. Purdy, “NASA radar altimeter for the TOPEX/Poseidon project,” Proc. IEEE, vol. 79, pp. 810–826, June 1991. [13] P. C. Marth, J. R., Jensen, C. C. Kilgus, J. A. Perschy, J. L. MacArthur, D. W. Hancock, G. S. Hayne, C. L. Purdy, L. C. Rossi, and C. J. Koblinsky, “Prelaunch performance of the NASA altimeter for the TOPEX/Poseidon project,” IEEE Trans. Geosci. Remote Sensing, vol. 31, pp. 315–332, 1993. [14] D. B. Chelton and P. J. MacCabe, “A review of satellite altimeter measurements of sea surface wind speed with a proposed new algorithm,” J. Geophys. Res., vol. 90, pp. 4707–4720, 1985. [15] D. L. Witter, and D. B. Chelton, “A Geosat altimeter wind speed algorithm and a method for altimeter wind speed algorithm development,” J. Geophys. Res., vol. 96, pp. 9853–9860, 1991. [16] G. S. Hayne, D. W. Hancock and C. L. Purdy, “The corrections for significant wave height and attitude effects in the TOPEX/Poseidon radar altimeter,” J. Geophys. Res., vol. 90, pp. 24.941–24.955, 1994. [17] M. A. Janssen, C. Ruf, and S. J. Keihm, “TOPEX/Poseidon Microwave Radiometer (TMR): II Antenna pattern corrections and brightness temperature algorithm,” IEEE Trans. Geosci. Remote Sensing, vol. 33, pp. 138–146, 1995. [18] S. J. Keihm, M. A. Janssen, and C. Ruf, “TOPEX/Poseidon Microwave Radiometer (TMR): III Wet troposphere range correction algorithm and prelaunch error budget,” IEEE Trans. Geosci. Remote Sensing, vol. 33, pp. 147–161, 1995. [19] T. M. Elfouhaily, B. Chapron, and K. Katsaros, “Microwave scattering distributions from a rain-roughened water surface: Measurements and Modeling,” Proc. IGARSS’94, vol. II, pp 9., Pasadena, CA, July 1994. [20] L. Bliven, P. Sobieski, and T. Elfouhaily, “Ring wave frequency spectra: Measurements and model,” Proc. IGARSS’95, vol. I, pp 829, Florence, Italy, July 1995. [21] P. Sobieski, L. Bliven, H. Branger, and J. P. Giovanangeli, “Experimental comparison of scatterometric signatures from a water surface agitated by wind and artificial rain,” Proc. IGARSS ‘93 Symp., Tokyo, Japan, 18–21 Aug. 1993. [22] B. Chapron, K. Katsaros, T. Elfouhaily, and D. Vandemark, “A note on relationships between sea surface roughness and altimeter backscatter,” Selected papers from Third Int. Symp. Air-Water Gas Transfer, Heidelberg University, B. Jähne and E. C. Monahan, Eds., AEON Verlag and Studio, pp. 869–878, July 24–27, 1995. [23] L. S. Fedor and G. S. Brown, “Waveheight and wind speed measurements from the SEASAT radar altimeter,” J. Geophys. Res., vol. 87, C5, pp. 3254–3260, 1982. [24] TOPEX/Poseidon, TOPEX/Poseidon Project, TOPEX Ground System Science Algorithm Specification, Jet Propulsion Lab., Pasadena, CA, 1992. [25] J. Goldhirsh and E. J. Walsh, “Rain Measurements from space using a modified Seasat-type radar altimeter,” IEEE Trans. Antennas Propagat., vol. AP-30, 4, pp. 726–733, 1982. [26] J. Goldhirsh, “Rain cell size statistics as a function of rain rate for attenuation modeling,” IEEE Trans. Antennas Propagat., vol. AP-31, pp. 799–801, 1983. [27] R. L. Olsen, D. V. Rogres, and D. B. Hodge, “The aRb Relation in the calculation of rain attenuation,” IEEE Trans. Antennas Propagat., vol. AP-26, pp. 318–329, 1978. [28] F. M. Monaldo, J. Goldhirsh, and E. J. Walsh, “Altimeter height measurement error introduced by the presence of variable cloud and rain attenuation,” J. Geophys. Res.,” vol. 91, pp. 2345–2350, 1986. [29] TOPEX. TOPEX Radar Altimeters Systems Specification, NASA Wallops Doc. WFF-672-85-004004, Rev. 6, 1989.


[30] ERS-1 Altimeter products, User Manual, C1-EX-MUT-A21-01-CN, Rev. 6, IFREMER, BP 70, 29280 Plouzané, France, 1994. [31] S. J. Keihm, personal communication 1995. [32] G. W. Petty, “On the response of the SSM/I to the marine environment: Implication for atmospheric parameters retrievals,” Ph.D. dissertation, Univ. Washington, Seattle, 291 pp., 1990.

Jean Tournadre was born in Clermont-Ferrand, France, in 1959. He received a diplôme d’ingénieur degree from the Ecole Centrale de Lyon, Lyon, France, and the Doctorate in Meteorology degree from the University Blaise Pascal, ClermontFerrand, France, in 1981 and 1984, respectively. From 1984 to 1987, he was Post-doctoral researcher at the Scripps Institution of Oceanography, University of California, San Diego, and Visiting Scientist at the National Center for Atmospheric Research, Boulder, CO. In 1987, he joined the Institut Fran¸cais de Recherche pour l’Exploitation de la Mer, Plouzané, France, where he works in the Département d’Océanographie Spatiale as a researcher. His research interests are ocean surface winds and waves and precipitations using remote sensing data, with a special emphasis on altimeter and scatterometer data. Dr. Tournadre is a member of the American Geophysical Union.

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June C. Morland was born in 1971 in Glasgow, Scotland. She received the B.Sc. degree in physics and astronomy and astrophysics from the University of St. Andrews, St. Andrews, Scotland, in 1993, and attended the International Space University Summer Session. She received the M.Sc. degree in remote sensing from University College London, London, U.K., in 1994. This involved work at IFREMER (Institut Francais pour la Recherche et Exploitation de la MER) where she investigated a new rain flag for the TOPEX-Poseidon satellite. She is currently a post-graduate student in the TAMSAT (Tropical Meteorology using SATellite data) group at the University of Reading, Reading, U.K. Her research interest is the influence of the land surface on microwave rainfall estimates.