A strong candidate for the next generation spaceborne rain radar is a dual-wavelength one. The performance of the radar was studied. First, the sensitivity of the shorter wavelength radar was investigated. Based on the data taken by a single-wavelength precipitation radar aboard the Tropical Rainfall Measuring Mission satellite, the frequency distribution of the received power of the shorter wavelength radar was calculated assuming typical rain attenuation. If the receiver noise level is equivalently about 10 dBZ, the missing rain fraction is about 15.41% over land and 3.22% over ocean. Second, the accuracy of the rainrate estimate was studied based on disdrometer measured data. The intrinsic radar signal fluctuation, the Mie scattering effect and receiver noise effect were incorporated. The result shows good potential for accurate rainrate estimate. Third, rainrate estimate of dry snow was investigated. Based on the disdrometer data, snow particle distribution was generated using non-coalescence, non-breakup assumption. After using an empirical relationship between snow density and particle size, a rainrate retrieval formula for snow was proposed. It was also shown that dual-wavelength radar has a good capability for discrimination of snow from rain.

This paper studies the performance of a spaceborne precipitation radar in measuring vertical Doppler velocity of rainfall. As far as a downward pointing precipitation radar is concerned, one of the major problems affecting Doppler measurement at the nadir direction arises from the Non-Uniform Beam-Filling effect (NUBF). That is, when significant variation in rain rate is present within the radar IFOV in the along track direction. The Doppler shift caused by the radial component of the horizontal speed of the satellite is weighted differently among the portions of IFOV. The effects of this non-uniform weighting may dominate any other contribution. Under this condition, shape, average value and width of the Doppler spectrum may not be directly correlated with the vertical velocity of the precipitating particles. However, by using an inversion technique which over-samples the radar measurements in the along track direction, we show that the shift due to NUBF can be evaluated, and that the NUBF induced errors on average fall speed can be reduced.

During the TEFLUN-B (Texas-Florida under-lights for TRMM) field experiment of August-September, 1998, a number or ER-2 aircraft flights with a host of microwave instruments were conducted over many convective storms, including some hurricanes, in the coastal region of Florida and Texas. These instruments include MIR (Millimeter-wave Imaging Radiometer), AMPR (Advanced Microwave Precipitation Radiometer), and EDOP (ER-2 Doppler Radar). EDOP is operated at the frequency of 9.7 GHz, while the AMPR and the MIR together give eleven channels of radiometric measurements in the frequency range of 10-340 GHz. The concurrent measurements from these instruments provide unique data sets for studying the details of the microphysics of hydrometeors. Preliminary examination of these data sets shows features that are generally well understood; i.e., radiometric measurements at frequencies <EQ 37 GHz mainly respond to rain, while those at frequencies >= 150 GHz, to ice particles above the freezing level. Model calculations of brightness temperature and radar reflectivity are performed and results compared with these measurements. For simplicity the analysis is limited to the anvil region of the storms were hydrometeors are predominantly frozen. Only one ice particle size distribution is examined in the calculations of brightness temperature and radar reflectivity in this initial study. Estimation of ice water path is made based on the best agreement between the measurements and calculations of brightness temperature and reflectivity. Problems associated with these analyses and measurement accuracy will be discussed.

The first Doppler radar observation on the Tibetan Plateau was conducted for the GEWEX/GAME-Tibet project in 1997 and 1998 in order to clarify the evolution and mesoscale structure of the rainfall system. The TRMM satellite also observed the rainfall in the Tibetan area in 1998. TRMM's precipitation radar (PR) detected a diurnal cycle of rainfall in Tibet. Much rainfall was brought both by convection in the daytime and by stratiform precipitation over a wide rain area in the evening. A case study was conducted to clarify the structure of stratiform rainfall. On 7 July, a synoptic convergence area developed in the southern part of the Plateau in the evening. Small convective echoes and stratiform echoes coexisted in the radar coverage at the beginning of the rainfall. Southwesterly wind dominated above the 6km ASL, but the wind direction below 6km ASL was variable during the rainfall. On 8 July, a cold front between southwesterly wind and northerly wind was detected over the radar site. A sudden wind direction change from westerly to northwesterly was observed below 8km ASL from the vertical profiles at the radar site with the passage of the cold frontal surface. The precipitation with the frontal passage was stratiform and has a low echo top.

To facilitate warning of low-level wind shear associated with convective storms, a Terminal Doppler Weather Radar (TWDR) was installed about 12 km to the northeast of the Hong Kong International Airport (HKIA). The HKIA is located just off the northern shore of an island known as Lantau. The HKIA lies on the lee side of the complex terrain of Lantau when winds come from the east through the southwest. With the commissioning of the TDWR in 1997, interesting high-resolution radar data were collected in strong southerly flows during tropical cyclone passages. These data sets reveal the complex low-level atmospheric flow in the vicinity of the HKIA, including streaks of low-speed flow, reverse flows, small-scale vortices and high-speed gap flows. Animation sequences of the radar images suggest existence of von Karman vortex streets and vortex shedding in the wake regions. These phenomena could induce strong shear regions which led to significant low-level wind shear for landing/departing aircraft. Analysis of on-board flight data for a wind shear event experienced by a landing aircraft in strong southeasterly flow revealed that terrain- induced features with horizontal scale less than 1 km brought significant air speed changes to the aircraft over a short duration of time.

With their high vertical and temporal resolution, vertically-pointing profilers offer valuable information about the vertical structure of precipitating cloud systems. The observed vertical structure of the precipitating cloud is related to the latent heating profile in the cloud system. The different precipitation regimes (e.g., convective, stratiform, and transitional precipitation) can be identified by diagnosing the profiler resolved vertical structure of reflectivity, mean Doppler velocity, and turbulence. The classifications based on these vertical profiles are important for estimating the frequency and percent occurrence of the precipitation regimes.

We have been working on rainfall observation project at tropical site in India, in order to study tropical storm structure and raindrop size distribution (DSD) characteristics for improving the current PR rainfall retrieval algorithm, and for making the ground validation of TRMM PR observation. At Gadanki (53-MHz VHF MST radar, an L-band lower atmospheric wind profiler (LAWP), a disdrometer and an optical rain gauge (ORG) are set up to obtain more knowledge on vertical properties of DSD and rain structure during monsoon season. Measurements of drop size distribution (DSD) with disdrometer have been providing the information to study basic DSD characteristics in tropical India. We have found a clear seasonal dependence in Reflectivity (Z) - Rainfall (R) relations (i.e. DSD characteristics) in India. Our results indicate that there are about 3-times differences peak-to-peak in estimates of rain rate using a single Z-R relation. It seems that this type of seasonal dependence should be taken into account to improve the accuracy of the PR algorithm. Drop size distribution characteristics were retrieved in moderate/heavy precipitation using VHF wind profiler. The retrieved drop size parameters were compared to corresponding disdrometer data and found that there is reasonably good agreement between the measurements, lending credence to the profiler retrievals of DSD parameters. Preliminary study on the ground validation of TRMM PR shows fairly good agreement between the disdrometer and TRMM precipitation radar measurements.

In this paper, we propose a simplified method for rain rate estimation only using simple parameters instead of the fitting or retrieval calculation using data of UHF wind profiler measurement, which operated by Kind Mongkut's Institute of Technology Lardkrabang (KMITL) in Bangkok, Thailand. The simple parameters in this method use only the peak position of rain echo and Doppler velocity of clear air echo from Doppler spectral for estimated rain drop size distribution (DSD), which is more important to calculate rain rate. Doppler spectra of UHF wind profiler at KMITL during the rainy season are used for testing the availability of this simplified rain estimation method. Rough agreement between rain rate estimation from the surface rain gauge and UHF wind profiler at KMITL can be seen at the range of low rain rate. At the range of high rain rate, the estimation by this method does not correspond to the surface rain gauge since the Doppler spectra seems saturated with too strong rain echo.

The study of low atmospheric boundary layer wind by wind profiler radar is the aim of this present. The L-band Doppler radar used as the meteorological equipment using operating frequency 1357.5 MHz. The transmitter radiates the pulse signal of peak power 1 kW through the upper air. The single parabolic antenna is steering into three directions, vertical, north and east respectively. This radar received the echo scattered back by the irregularity of atmospheric refractivity along the beam. The Doppler shift frequency deviates by the movement of turbulent are used to calculate the wind velocity and wind direction. The observation height starts from 150 meters to 4 km. The diurnal and seasonal wind had been observed for six years continuously. It shows the variation of wind in each year, which correspond to Asia monsoon, Northeastern monsoon and Southwestern monsoon. While the radio sonde, which operates by radio propagation technique is used for wind measurements too. The comparisons of both systems are present in correlation method.

Spaceborne scatterometers are active microwave radar instruments designed to acquire near-simultaneous, spatially collocated measurements of the normalized radar backscattering cross section (sigma0) of the global surface from several azimuth and/or incidence angles. The primary objective of the scatterometer mission is to measure the near-surface wind speed and direction over the global ocean using sigma0 measurements together with a wind geophysical model function. However, since sigma0 measurements are collected globally all the time, sigma0 data can also be used for global land and ice applications. In this paper, we will first present the objectives of the QSCAT mission, the instrument design, and the unique features of the Ku- band scatterometer currently in operation, called SeaWinds on QuikSCAT (QSCAT). We will then present some emerging land and ocean applications of the QSCAT data, which include (1) global snow detection and monitoring, (2) melt region mapping on the Greenland ice sheet, (3) Monsoon flood detection and monitoring, (4) soil wetness application at large scale, and (5) hurricane monitoring and tracking.

In order to validate wind vectors observed by QuikSCAT (QSCAT)/SeaWinds, statistical distributions of wind directions are investigated by comparison with those from numerical weather prediction wind analyses. Frequency distribution of wind directions relative to spacecraft flight direction is calculated form the QSCAT data for a period of two months to assess the self-consistency of the wind directions. It is found that the QSCAT wind vectors exhibit systematic directional preference relative to antenna beams, which is very similar to that found in the NASA Scatterometer (NSCAT) winds Sharp spikes are discernible in the directional distributions and azimuth location of the spikes varies with cross-track cell location reflecting azimuth angle combination of scatterometer beams. The variation of azimuth location of the spikes is interpreted by using a simple model which examines effects of errors in the geophysical model function on the retrieved winds. It is concluded that the artificial directivities are caused by imperfections in the geophysical model function used to retrieve the wind vectors.

The Phased Array type L-band Synthetic Aperture Radar (PALSAR) on board the Advanced Land Observing Satellite (ALOS) scheduled for launch in June 2003 will be the Japanese second-generation spaceborne SAR following the Japanese Earth Resources Satellite-1 (JERS-1) SAR. The PALSAR is designed to achieve high performance and flexibility and the L-band data continuity of JERS-1. Active phased array antenna equipment provides variable incidence angle ranging from 8 to 50 degrees and allows ScanSAR operation. Especially, a full polarimetric function is the most challenging development. The JERS-1 SAR has demonstrated the advantage of L-band signals on SAR interferometry in vegetated areas. Based on the results from the JERS-1 SAR, applications of the PALSAR such as an environment monitoring, Earth science research will be enhanced. System characteristics and operational modes of the PALSAR and its expected applications are presented.

We have developed a new, fully automatic method for detecting and visualizing narrow open-water rivers from 3- look JERS-1 SAR images of Amazon rainforests. We expect this method to become an operational tool for detecting river water levels in remote tropical rainforests for the purposes of environmental and disaster monitoring. To demonstrate its use, we apply this method to eight continuous and one isolated Amazon scene. The resulting approximate range of waterways corresponds highly with those seen in JERS-1 VNIR image data observed one week later in cloud-free areas. Estimates from the optical JERS-1 VNIR images give the minimum detectable width of those visualized rivers to be approximately 20 m. The brightness of the river can be used to estimate the width of the fiver from approximately 20m to approximately 150m. In wider rivers, dark areas become predominant.

Detection of the bright band (BB) is carried out in 2A23, which is one of the TRMM Precipitation Radar (PR) standard algorithms. Though BB shows up rather clearly in the TRMM PR data near nadir directions, the observed BB smears as the antenna scan angle, defined as the off nadir angle of the radar beam, increases. Because of this smearing of BB and of other reasons, not all the BBs are detected by 2A23. Statistics of 2A23 show that BB is detected in about 40% of stratiform precipitation. What remains to be made in 2A23 includes the determination of the width of BB, which is challenging because we have to deal with the smeared BB profiles. Definition of the width of BB itself also is an issue. This paper examines the statistical range profiles of BB, which may give us some hints how to define the width of BB observed by the TRMM PR. The width of BB, obtained for the statistically averaged BB profiles, becomes larger as the intensity of BB increases; this result is consistent with those reported in the literature.

Mirror image is a virtual image of precipitation below the ocean surface when we use an airborne or a spaceborne radar to view the rainfall over ocean. It is due to a double reflection, that is energy reflected form the sea surface goes to the precipitation and back to the radar via a second reflection at sea surface. We investigated the mirror image characteristics using TRMM Precipitation Radar data and found: 1) The radar can detect the mirror image clearly over the ocean, 2) the mirror image echo corresponds well to the direct rain echo at nadir and near nadir incidence angle, 3) in a weak rain region, mirror echo intensity is nearly proportional to the direct echo power except near noise level, 4) in the strong rain region, rain attenuation effect clearly appears, and 5) the ratio of mirror echo power to direct echo power is affected by the rain attenuation which varies with the bright band height and the range of the target rain from surface. Further, we performed a simple simulation in order to confirm the above characteristics. The signal fluctuation, noise contamination, rain attention and surface cross section are taken into account in the simulation, and the results of simulation confirmed the observation results.

Preliminary error analysis results of the near surface rain rate (NSR) measured by Precipitation Radar (PR) onboard Tropical Rainfall Measuring Mission (TRMM) satellite are introduced in this paper. Statistical errors are analyzed by comparison of rain rates measured by TRMM PR and ground- based Instruments, i.e. Automatic Weather System (AWS) over Korean peninsula. The ground and satellite measurements are fundamentally different time and spatial resolution. AWSs sample the rainfall continuously in time but at a separate point, while TRMM PR samples an area average over the field of view but a snapshot in time. Therefore the comparison of two data with different temporal and spatial resolution include much errors. The purpose of this study is to investigate the errors according to the field of view of averaged grid, the number of AWS stations and the threshold of rain rate. However, in this paper we will introduce only the variations of errors by the number of AWS in a FOV and by the averaging time of rainrate, in advance. Results show that the RMSEs are decreased inversely by the number of AWS rain gauges, but correlation coefficients (CC) are increased as the number of AWS rain gauges are more. In addition, the CC according to the number of AWS tend to increase as the averaging time is longer and shows opposite relation with RMSE. The PR agrees well to the AWSs with the highest CC of 0.79 and the smallest RMSE of 2.285. The RMSE is smallest when 10 rain gauges in a grid averaged for 30 minutes. However the PR seems to estimate rain rate lower than AWSs.

The Precipitation Radar (PR0 on the Tropical Rainfall Measuring Mission (TRMM) satellite continues observation. Many ground validation efforts have been made to confirm the accuracy of rain rates estimated by standard PR algorithms from observed radar reflectivity. However, so far there have been no conclusive results giving the absolute difference of PR estimated rain rates from the true rain rates from ground validation efforts. The difficulty of ground validation of rain is due to the large variance of spatial and temporal distributions of rain. However, there is a dense rain gauge and radar observation network operated by Japan Metrological Agency (JMA) that covers Japan. In this paper, TRMM estimated rain rates are compared to Radar- AMeDAS rain analysis data on a monthly averaged basis, and retrieval errors were estimated by assuming that Radar- AMeDAS is truth data. The estimated averaged retrieval error for five degree by 5 degree areas for 12 months was 25%, and PR and Radar-AMeDAS rain amounts were almost the same for a year. However, the estimate exhibits seasonal dependency. Specifically, PR overestimates rain rates in winter and under estimates them in the summer. Sampling errors included in TRMM monthly products were also estimated. The estimated sampling error was 15%. This magnitude of sampling error seems quite reasonable considering the results before TRMM was launched.

This paper provides an overview of the Shuttle Radar Topography Mission SRTM), with emphasis on flight system implementation and mission operations from systems engineering perspective. Successfully flown in February, 2000, the SRTM's primary payload consists of several subsystems to form the first spaceborne dual-frequency (C- band and X-band) fixed baseline interferometric synthetic aperture radar (InSAR0 system, with the mission objective to acquire data sets over 80% of Earth's landmass for height reconstruction. The paper provides system architecture, unique design features, engineering budgets, design verification, in-flight checkout and data acquisition of the SRTM payload, in particular for the C-band system. Mission operation and post-mission data processing activities are also presented. The complexity of the SRTM as a system, the ambitious mission objective, the demanding requirements and the high inter-dependency between multi-disciplined subsystems posed many challenges. The engineering experience and the insight thus gained have important implications for future spaceborne interferometric SAR mission design and implementation.

A highly accurate global topographic map of the Earth's surface has been an elusive goal for at least three decades that may soon be achieved with the newly acquired Shuttle Radar Topographic Mission (SRTM) data. SRTM collected data for 99.97% of the Earth's landmass between -57 degree(s) and 60 degree(s) latitude during a 11 day mission in February, 2000. A modified version of the SIR-C radar that previously flew on the shuttle in 1994 augmented with a radar mounted on a 62 m boom was used to collect radar interferometric data at C (5.6 cm wavelength) and X (3 cm wavelength) bands. The C- band radar was operated in the SCANSAR mode in order to extend the swath width to 225 km, the minimal amount required to achieve contiguous coverage at the equator. This paper presents an overview of the new algorithms and techniques used to process the SCANSAR data to digital elevation maps. First results of topographic maps generated from the SRTM data are used to illustrate the techniques described in this paper.

Synthetic aperture radar (SAR) interferometry has become an important tool for measuring the surface deformation and mapping topography. The largest error source of the SAR interferometry measurements is differential atmospheric delay of water vapor. It reflects detailed distribution of water vapor in troposphere at data acquisition. We found phase difference associated with atmospheric waves and severe local atmospheric phenomena in interferograms. To distinguish phase difference associated with surface deformation from tropospheric effect, we need several SAR interferograms including the time period of the deformation. Averaging the interferograms is an effective way to reduce the tropospheric delay from horizontal inhomogeneity of the water vapor distribution. Apart form the tropospheric delay of the horizontal water vapor inhomogeneity, we often find the differential phase correlated to the topography (elevation) in interferograms, which might cause error in interpretation of surface deformation. This phase is due to the differential tropospheric delay caused by the topography and vertical change of water vapor between two images in different atmospheric condition. Theoretical calculation shows that the phase difference can be approximated by linear expression of the elevation. We applied a simple and effective correction method that the error is removed by subtracting the DEM multiplied a coefficient.

We evaluated the performance of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) at-launch algorithm for monthly oceanic rain rate using two years (January 1998-December 1999) of TMI data. The TMI at-launch algorithm is based on Wilheit et al.'s technique for estimating monthly oceanic rainfall that relies on histograms of multichannel microwave measurements. Comparisons with oeanic monthly rain rated derived from the Defense Meteorological Satellite Program (DMSP) F-13 and F- 14 Special Sensor Microwave Imager (SSM/I) data show the average rain rates over the TRMM region (between 40 degree(s)S and 40 degree(s)N) are 3.0, 2.85 and 2.89 mm/day, respectively for F-13, F-14 and TMI. Based on the latest version of TB data (version 5), both rain rate and freezing height derived from TMI are similar to those from the F-13 and F-14 SSM/I data. However, regionally the differences are statistically significant at the 95% confidence. Three hourly monthly rain rates are also computed from 3-hourly TB histograms to examine the diurnal cycle of precipitation. Over most of the oceanic TRMM area, a distinct early morning rainfall peak is found. A harmonic analysis shows that the amplitude of the 12h harmonic is significant and comparable to that of the 24h harmonic.

A major objective of the Tropical Rainfall Measuring Mission (TRMM) is to produce a multi-year time series of monthly rainfall over 5 degree(s) latitude and 5 degree(s) longitude boxes with an uncertainty of 1mm/day for low rain rates and 10% for high rain rates. Based on some simple assumptions about the error structure, we compute the non-systematic errors of monthly oceanic rainfall over the same space/time domain derived from data taken by the Special Sensor Microwave Imager (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites and TRMM Microwave Imager (TMI). The mean rain rates over a two-year period (1998-1999) are calculated to be 3.0, 2.85, 2.94 mm day^-1 for SSM/I onboard the DMSP F-13, F-14 and TMI, respectively. Assuming that the non-systematic errors for each sensor are independent, the errors are calculated to be 22.2%, 22.4%, and 19.7% for F-13, F-14 and TMI, respectively. The non- systematic error for the TMI is smaller than that for either F-13 or F-14 SSM/I at the low rain rates but is comparable at rain rates higher than about 5mm/day. The TRMM objective of 1mm day^-1 for non-systematic error is met by TMI for rain rates up to 5-6mm day^-1. For higher rain rates, the nonsystematic error is in the 15% range. The goal of a 10% error for high rain rates may be realized by a combination of sensor measurements from multiple satellites, such as that advocated by the Global Precipitation Mission (GPM).

We performed a preliminary experiment of assimilating TMI total column precipitable water (TCPW) into the global numerical weather prediction (NWP) system. TCPW was not produced as a TMI standard product. Hence, we retrieved it from the brightness temperature over the ocean using the Meteorological Satellite Center algorithm, which will be the standard TCPW retrieval algorithm for AMSR on board ADEOS- II. The analysis method of the NWP system used in the experiment was 3D optimum interpolation (3D-OI), and TCPW data couldn't be assimilated directly. We therefore introduced a method to modify the water vapor field of an analysis by 3D-OI according to TCPW analysis assimilated TMI TCPW data. Using the analysis system, we performed the TMI TCPW observation system experiment. The results revealed clear positive impacts on forecasted wind fields of 850 and 250 hPa height over the tropics and small positive impacts on same levels and region. Improvements of the one-day forecasted rainfall over the tropical region were also recognized. In addition, we found a strange seasonal variability in the TCPW field of the JMA operational global analysis in 1998. We also found 15-42-day oscillation cycles in the difference between TMI and SSM/I TCPW, which we assume originates from the bias of the TMI brightness temperature and the effect that TRMM flied on a non-sun- synchronous orbit.

An over-ocean precipitation retrieval algorithm is developed to retrieve precipitation for the Baiu period from brightness temperatures (TB's) supplied by the TRMM Microwave Imager (TMI). The basic idea of the algorithm is to find the optimal precipitation that gives radiative transfer model (RTM)-calculated, field-of-view (FOV)- averaged TB's that fit best with the TMI TB's at 10.7, 19.7, and 85.5 GHz with vertical polarization. For the RTM calculation, spatial precipitation inhomogeneity and freezing level height are estimated from TMI TB's. The optimal precipitation with 10 km resolution is obtained by solving the gradient equation of a cost function that is a weighted sum of squares of TB differences between the TMI observation and the RTM calculation. Precipitation retrieved by this algorithm was validated using TRMM Precipitation Radar (PR) data from the western part of Japan during June-July of 1998. The results indicate: 1) Meso- scale (approximately 100 km) structures of precipitation disturbances were retrieved successfully with the algorithm. However, there were discrepancies in position and strength of individual rain cells between the precipitation retrievals and PR data. 2) Precipitation retrieved by the algorithm agreed well with PR data within the precipitation range of 1-25 mm/hr, irrespective of precipitation type.

The Texas A&M monthly oceanic rainfall retrieval algorithm is based on radiative transfer models and can only be modified on a physically sound basis. Within this constraint we have examined some improvements to the algorithm and it appears that it can be made significantly better. In particular, it appears that by proper use of the range of frequencies available on TMI and AMSR that the need for the log-normal fit can be eliminated.

A submillimeter limb-emission sounder, that is to be aboard the Japanese Experiment Module (JEM, dubbed as KIBO) at the International Space Station, has been designed. This payload, Superconducting Submillimeter-wave Limb-emission Sounder (SMILES), is aimed at global mappings of stratospheric trace gases by means of the most sensitive submillimeter receiver ever operated in space. Such sensitivity is ascribed to a Superconductor-Insulator- Superconductor (SIS) mixer, which is operated at 4.5 K in a dedicated cryostat combined with a mechanical cooler. SMILES will observe ozone-depletion-related molecules such as ClO, Hcl, HO₂, HNO₃, BrO and O₃ in the frequency bands at 624.32-626.32 GHz and 649.12-650.32 GHz. A scanning antenna will cover tangent altitudes from 10 to 60 km in every 53 seconds, while tracing the latitudes form 38 S to 65 N along its orbit. This global coverage makes SMILES a useful tool of observing the low- and mid- latitudinal areas as well as the Arctic peripheral region. The molecular emissions will be detected by two units of acousto-optic spectrometers (AOS), each of which has coverage of 1.2 GHz with a resolution of 1.8 MHz. This high-resolution spectroscopy will allow us to detect weak emission lines attributing to less-abundant species.

An acousto-optical spectrometer (AOS) is employed in order to meet scientific mission objectives of submillimeter-wave limb-emission sounder (SMILES) to be aboard the Japanese Experiment Module (JEM) of the International space station (ISS). The capability of multi channel detection with AOS is suitable for observing multi chemical species in a wide frequency region. Wide noise dynamic range enables us to obtain the spectra without unnecessary increase of system noise, suggesting a good combination of AOS with low noise front end system of SMILES> Several technical concerns relating to important instrumental characteristics of AOS are discussed and expected performance of the spectrometers to be used in the JEM/SMILES mission are over viewed.

JEM/SMILES (superconducting SubMIllimeter-wave Limb-Emission Sounder) is currently under development to demonstrate a submillimeter-wave sounder with extremely high sensitivity on the platform of the Japanese Experiment Module (JEM). In the submillimeter region, this is the first mission in space using a low-noise 4K cooled receiver, which is expected to give new observations for radicals in the stratosphere such as BrO. One of the most unique characteristics of the JEM/SMILES observation is its high sensitivity in detecting atmospheric limb emissions in the submillimeter wave range. The purpose of SMILES is global monitoring of the radicals which play important roles in the stratospheric system. We are now using the newly developed JEM/SMILES simulator to model observed spectra (including the characteristics of the SMILES sensor) and simulate the retrieval performance. Some preliminary results of the simulation are obtained in view of the scientific targets of JEM/SMILES.

In order to estimate measurement capability of the Superconducting Submillimter-Wave Limb-Emission Sounder (SMILES) on the Japanese Experiment Module (JEM) of the International Space Station (ISS) and to clarify the scientific impacts of the JEM/SMILES, we are developing the JEM/SMILES simulator. The simulator consists of the forward model and the inversion model. The forward model calculates a brightness temperature by applying the radiative transfer formula to a limb sounding geometry and simulates the effects of the JEM/SMILES sensor characteristics including optics superconductor-insulator-superconductor (SIS) mixers, Acousto-Optical Spectrometer (AOS), and so on, to it. Because it is important to estimate the effects of the sensor for the retrieval, we develop carefully simulated sensor model. The forward model also calculates weighting functions of molecular, the temperature, the pressure and so on. This paper describes how the brightness temperature and weighting functions are calculated in the forward model and how the effects of the sensor are taken into account in the simulator, and finally shows how the optical estimation method (OEM) is applied to our retrieval model.

Superconducting sub-millimeter-wave limb-emission sounder (SMILES) using 4K Superconductor-Insulator-Superconductor (SIS) detector for ISS/JEM is under development. Spectrum of 600 GHz regions will be acquired using acousto-optics spectrometer (AOS). The high sensitivity of SMILES will enable us to measure O₃, ClO without enhancement, BrO, Hcl, HO₂, HNO₃ from 10 to 60 km. This paper describes a current plan of data retrieval algorithms (L0, L1, L2 and L3), ground data system, data validation and data distribution.

We describe a passive microwave radiometer that provides continuous unattended atmospheric temperature and humidity profiles up to 10 km in height, and low resolution liquid water profiles. Profile accuracies in cloudy and clear conditions up to 7 km height are better than 2.5 K (temperature) and 1.1 g/m³ (humidity) as determined by statistical comparison with radiosondes. The microwave profiler observes 12 channels in the 20 to 60 GHz range, 1 infrared channel, and surface temperature, pressure and humidity. Retrieval coefficients for specific locations are derived using local radiosonde data and a neural network or regression analysis. The commercial microwave radiometer design has logged more than a million hours in locations ranging form the arctic to the tropics. We provide examples of microwave profiler soundings in various locations and weather conditions, and comparisons with radiosondes. We discuss recent high resolution water vapor field analysis results based on simulated slant GPS and microwave profiler data.

The Airborne Microwave Radiometer (AMR) is a multifrequency, passive microwave radiometer to be installed on an aircraft. Form 1996, the AMR has been used in two spaceborne instrument projects: the Advanced Microwave Scanning Radiometer (AMSR) on the Advanced Earth Observing Satellite- II (ADEOS-II) and the AMSR-E on the EOS Aqua satellite. The major objectives of AMR are to develop retrieval algorithms and to calibrate and validate AMSR and AMSR-E. We recently modified the instrument to improve its stability and usability. The results of a set of test flights show an improved in-flight and interflight stability. We will conduct several AMR underflights to confirm AMSR and AMSR-E on-orbit calibration.

Remote sensing of low-altitude temperature profile is important for a variety of studies, including air-sea interaction, short-term meteorological forecasting, forecasting of dissipation of fog and stratus, and air pollution. During December 1999, and January-February 2000, a microwave temperature profiler (MTP-5), manufacturing by Russian Scientific Production Company ATTEX, was installed at the Russian meteorological station Val at the north part of Sakhalin Island (LN6 143 degree(s)E, LAT 52 degree(s)N, ALT-32M). The MTP-5 is an angular-scanning self-calibrating instrument operated at a center frequency of 59, 6 GHz, with a sensitivity of 0,03K at 1-sec integration time, a cycle time of 120 sec for one temperature profile measurement and an accuracy of 0,5K up to the altitude 600 m. Before installation on site the MTP-5 data were compared with radiosonde data and with the data from in situ sensors at the meteorological tower. The RMS was less than 0.5K at all altitude (up to 600 m). The using of microwave remote sensing firstly gave the possibility of providing a continuous monitoring of the temperature profile above the north part of Sakhalin Island where the sea ice was formed. About 13000 temperature profiles at altitude range 0divided by600 m were obtained during observation period. The measurement was provided as a part of the project Clarification of the actual condition of sea ice in the Sea of Okhotsk and its role in the climate system.

The goal of this study is to develop an algorithm for estimating the surface soil moisture and surface roughness using polarimetric Synthetic Aperture Radar (SAR) data. In this study, an algorithm was applied to polarimetric airborne SAR data to estimate distributions of surface soil moisture and roughness. To validate the estimated soil moisture, we simultaneously conducted an experiment in October 1999 in Tsukuba Science City, Ibaragi Prefecture of Japan. Surface soil moisture was obtained by the Time- Domain Reflectometry (TDR) method, and the horizontal profiles of the land surface height were measured by a comb- style instrument for calculating the surface roughness parameters in test sites. Because the problem is site- specific and depends upon the measurement accuracy of both the ground truth data, the SAR system including speckle noise, and the effects of vegetation and artificial constructions, such as buildings, houses, roads, and roadside trees, the comparison results did not agree well with measured and inferred soil moisture.

In recent years, the application of radar polarimetry for remote sensing of land cover types has attracted extensive interest. Numerous microwave scattering models have been developed and used to interpret the polarimetric SAR data. In this paper, existing L-band backscatter models were used to model land-cover types, such as smooth and slightly rough surfaces (single scattering), urban area and tree trunks (double-bounce scattering) and forested area (diffuse scattering). Using these models, it is possible to construct the amplitude scattering matrix, Mueller matrix, Stokes parameter, etc. for each target. However, a state- vector was created using the Stokes parameters, degree of unpolarization and the phase difference between the HH and VV polarizations. The angle between two state-vectors (the theoretical state-vector derived from the calculation using the existing models and the state-vector derived from the observation or image data) was calculated for each land cover-type. We found that there is a strong correlation between the model predicted and the observed state-vectors for the same land cover types. The angle between the calculated and observed state-vectors is very useful for contrast enhancement and classifying the polarimetric radar data. For this purpose, polarimetric L-band airborne SAR data acquired over a variety of geographic targets are analyzed with the support of field investigations of forest, bare land and smooth surface (or ground and water), urban and rough surfaces. The classification results were presented.

We have acquired ground truth data at Lake Saroma and its surrounding area since 1993 in order to collect data on regional sea ice in the Sea of Okhotsk. The data was acquired in 1999 by Polarimetric and Interferometric SAR (PI-SAR), a dual-frequency, fully polarimetric airborne SAR system jointly developed by the National Space Development Agency of Japan (NASDA) and the Communications Research Laboratory (CRL), simultaneously with ground experiments. This paper describes the results of polarimetric data analysis of typical sea ice observed in the off-shore region near Lake Saroma. Considering sea ice classification capability by using L-band polarimetric SAR data, we found that the correlation coefficients between RR and LL, polarimetric entropy, and polarimetric anisotropy were candidates for discriminating three ice types as well as open water at small incidence angles.

We have conducted a feasibility study on measuring the tree height distribution by using polarimetric SAR interferometry datasets acquired by the NASDA-CRL's L-band Polarimetric Interferometric Synthetic Aperture Radar (PI-SAR). Test site is the Tottori Dune and its surrounding area, where pine trees were planted. Coherence and the phase differences obtained by the interferometric analysis were evaluated. As a result, we could estimate the tree height distribution if the polarimetric SAR images (co-pol and cross-pol) are acquired with larger baselines and smaller slant ranges. Quantitative evaluation is required to relate the phase center differences and the tree types and the polarization combinations.

In this paper, we report the preliminary studies of cloud microphysics by using ground-based 95GHz cloud radar and lidar systems. Although the active sensors are expected to increase our knowledge about clouds, e.g., vertical profiles of clouds, the single use of radar or lidar gives limited information and it is difficult to retrieve the ice water content (IWC and effective radius of cloud particles. We develop the new method for the combinational use of radar and lidar signals. The algorithm includes the attenuation corrections on both signals which is a long standing problems especially in the analysis of lidar signals. The system enables to retrieve the vertical profiles of effective radius and IWC in each cloud layer. Since both active sensors have dual polarization capabilities, the system provides a unique opportunity to study cloud microphysics form many aspects, e.g., vertical profiles of the relationship between effective radius, IWC and/or depolarization ratio. This system also has a great potential to study aerosol-cloud interaction studies.

Vertical profile of liquid water cloud microphysics is retrieved by a newly proposed algorithm using radar and microwave radiometer. The data used in this algorithm is obtained form a 95-GHz cloud profiling radar (CPR) and a dual-wavelength microwave radiometer. This technique is applicable to liquid water clouds and its products are vertical profiles of attenuation-corrected radar reflectivity factor, liquid water content (LWC), and cloud dropsize distribution. The basic idea of this algorithm is to solve the radar equation with a constraint of integrated liquid water content (LWP: liquid water path) obtained from microwave radiometer. The main features of this algorithm are that it yields an attenuation-corrected radar reflectivity factor and the analytical solution is stable for the attenuation expected in typical stratocumulus clouds. Examples of its application to cloud data observed with a 95 GHz CPR and a microwave radiometer at Kashima, Japan on 4 February 2000 are described. The larger cloud drop size than the typical value retrieved and descending motion seen in the clouds examined is explained by the existence of drizzle particles in the lower part of cloud layer.

A ground-based millimeter-wave radiometer was developed in Communications Research laboratory, and will be operated to observe stratospheric chlorine monoxide, ozone, and nitrous oxide at Eureka, the Arctic stratospheric observatory at 80 degree(s)N and 86 degree(s)W from December 2000. The radiometer is designed to detect weak emission and for long-term observation in a remote site. The most remarkable feature is that all optical components are integrated in the cryo- dewar and cooled down to less than 60 K. This makes the optical length short and is a great advantage to spectroscopic observation of atmosphere because the rapid ripple of spectral baseline due to standing waves never occurs in the input optics and the optics is thermally stable. This new radiometer was installed in Eureka in the spring of 2000. The radiometer system is fully remote- controllable, and will be operated without frequent local operation. We are expecting quasi-simultaneous observation of three molecules with the radiometer from this winter. The detail of the radiometer instruments is presented in this paper.

Hourly rain rates are estimated operationally in Korea Meteorological Administration (KMA) since last year by the regression method (A_REG), which uses the GMS-5 IR and Automatic Weather Systems (AWS) gauges data over Korean Peninsula. As the results, A_REG method estimates rain rate better than other retrieval methods such as probability matching method and look up table method do. However, this equation can't represent on the whole area including oceans because a number of rain gauges are limited over Korean peninsula. In this study the A_REG method has been improved by using the radar rain rate over Japan instead of AWS over Korea Peninsula. As the statistical verification, the estimated rain rates by R_REG method are improved than existing method (A_REG). The mean errors of R_REG nearly don't appear though A_REG show positive bias. Root mean square errors of R_REG are 2-3 times smaller than A_REG. The correlation coefficients of two methods are similar.