An empirical algorithm for cloud liquid water from MSMR and its utilization in rain identification

In this paper, an empirical method to estimate cloud liquid water from Indian Remote Sensing P4 (IRS-P4) Multi-frequency Scanning Microwave Radiometer (MSMR) measurements is presented. MSMR brightness temperatures are collocated with concurrent observations of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI)-derived cloud liquid water. The multiple-correlation coefficient between TMI-derived cloud liquid water and logarithmic of MSMR-derived brightness temperatures, and their differences at 18- and 21-GHz channels, is found to be about 82.4%. The relationship thus obtained has an rms error of 8.75 mgcm/sup -2/ in the measurements of cloud liquid water from MSMR with respect to TMI measurements. Verification of the algorithm is carried out with another set of concurrent measurements from MSMR and TMI. Further, the MSMR-derived cloud liquid water over the global oceans and for extreme weather conditions (cyclone) are compared with that from TMI and the Special Sensor Microwave/Imager (SSM/I) for independent verification. The cloud liquid water from MSMR is further used to successfully delineate rain events for quantitative estimation of rain rate from MSMR.     

The forward problem and corrections for the SSM/T satellitemicrowave temperature sounder

The relationship between atmospheric temperatures and the brightness temperatures measured by the Special Sensor Microwave/Temperature (SSM/T) radiometer is addressed. Physical algorithms for retrieving temperature profiles explicitly employ the physics of radiative transfer. Consequently, it is necessary to do the forward problem accurately before attempting the retrieval problem. The various problems that arise in doing forward calculations over oceans are discussed. These problems include determining when the measurements are cloud contaminated, the amount of liquid water in the fields of view, the surface emissivity under both clear and cloudy conditions, the corrections for liquid water contamination of the measurements, the adjustments for deficiencies in the radiative transfer model, and the compensation for measurement discrepancies by using shrinkage estimation. These procedures are developed for SSM/T data, and their validity is checked by comparing the forward calculations with the corresponding satellite measurements. Application of the procedures to an independent data set confirms their veracity     

A physical-statistical approach to match passive microwave retrieval of rainfall to Mediterranean climatology

A physical-statistical approach to simulate cloud structures and their upward radiation over the Mediterranean is described. It aims to construct a synthetic database of microwave passive observations matching the climatological conditions of this geographical region. The synthetic database is conceived to train a Bayesian maximum a posteriori probability inversion scheme to retrieve precipitating cloud parameters from spaceborne microwave radiometric data. The initial microphysical a priori information on vertical profiles of cloud parameters is derived from a mesoscale cloud-resolving model. In order to complement information from cloud models and to match simulations to the conditions of the area of interest, a new approach is proposed. Climatological constraints over the Mediterranean are derived on a monthly basis from available radiosounding profiles, rain-gauge network measurements, and colocated METEOSAT infrared measurements. In order to introduce the actual surface background in the radiative-transfer simulations, a further constraint is represented by the monthly average and variance maps of surface emissivity derived from Special Sensor Microwave Imager (SSM/I) clear-air observations. A validation of the forward model is carried out by comparing a large set of brightness temperatures measured by the SSM/I with the synthetic cloud radiative database to asses its representativeness and range of variability.     

A comparison of ground-based and satellite-borne microwaveradiometric observations in the Great Plains

The authors compare ground-based and the special sensor microwave/imager (SSM/I) brightness temperatures at 19 and 37 GHz in the Northern and the Southern Great Plains. The comparison was conducted to examine season-related differences in plot-scale and satellite footprint-scale brightness temperatures at these frequencies. The ground-based observations were from the three Radiobrightness Energy Balance Experiments (REBEXs), viz., REBEX-1, REBEX-4, and REBEX-5. REBEX-1 and REBEX-4 were conducted near Sioux Falls, SD, in fall and winter 1992-93, and in summer 1996, respectively. REBEX-5 was conducted near Lamont, OK, during summer 1997 as part of the Southern Great Plains Hydrology Experiment-1997 (SGP'97). The instantaneous fields of view (FOV) of the ground-based radiometers were only a few meters compared to those of the SSM/I, which were several tens of kilometers. The REBEX and the SSM/I brightness temperatures are moderately correlated at both the 19 and 37 GHz. They match well during winter when there was uniform snow cover over the SSM/I footprint. During spring, summer, and fall, REBEX brightness temperatures at the grass-site were on average 18 K higher than the SSM/I brightness temperatures because the SSM/I footprint included nearby agricultural fields in summer and predominantly bare soil in fall and spring. During summer, REBEX-4 brightness temperatures at the bare soil site were on average 10 K cooler than the SSM/I brightness temperatures. In effect, the REBEX grass and bare soil brightness temperatures bracket the SSM/I observations with the SSM/I brightness temperatures lying closest to those of the bare soil     

PIn. II. Comparative evaluation of SSM/I and TMI precipitable waterestimate for the Mediterranean Sea

For pt.I see ibid., vol.39, no.12, p.2566-74 (2001). To estimate integrated precipitable water vapor along with liquid water path and water vapor effective profile (i.e. standard atmospheric profile approximation), utilizing the Special Sensor Microwave/Imager (SSM/I) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometers, an operative procedure was developed and assessed. This procedure is based on a fast nonlinear physical inversion algorithm (PIn) developed by the authors. A large data set of near-coincident TMI and SSM/I data acquisitions were collected and used to supply the procedure. Retrieved parameters were compared against retrievals achieved with well-accepted statistical algorithms, and consistency between TMI and SSM/I retrievals was confirmed. As far as TMI and SSM/I precipitable water retrieving consistency is concerned, this research revealed a linear relationship up to 20 kg/m² and a general overestimate of TMI retrieving, for higher values. A new algorithm for obtaining integrated precipitable water from TMI brightness temperatures was introduced and the goodness of its accuracy was reported. The procedure proved to be reliable and portable and its integrated precipitable water vapor retrieving was assessed to be as accurate as the best radiometric retrieving algorithms, reported in literature. For SSM/I data, developed-procedure liquid water path estimates seemed to be in good agreement with statistical retrievals. Eventually the procedure provided effective water vapor vertical profiles which belong to a deterministic distribution area characterized by an upper and lower limit; it was confirmed that SSM/I and TMI vertical profile distribution areas mainly overlap even if they are characterized by different sensitivities to profile parameters     

Metamorphic signature of snow revealed in SSM/I measurements

Brightness temperatures (19, 22, 37, 85 GHz) measured by the special sensor microwave/imager (SSM/I) are analyzed using data from the snow monitoring network within the former Soviet Union during the 1987-1988 winter period. It is shown that in the beginning of winter, the SSM/I measurements display the classical snow scattering signature, i.e., the brightness temperatures decrease with increasing depth, and the largest decrease occurs at the highest frequency. Dramatic deviations from this pattern are observed in the middle of winter, where the brightness temperature approaches a minimum and then begins to increase despite the fact that the snow depth remains constant or continues to grow. The two-stream radiative transfer model is combined with results from dense media theory to help explain the phenomenon. Model results suggest that the increase in brightness temperature is due to a decrease of the single scattering albedo as the snowpack ages. This decrease of the albedo is related to changes in the snow crystalline structure due to metamorphism. Consequences for the interpretation of satellite measurements and development of algorithms for deriving snow water equivalent are discussed     

Land surface temperature derived from the SSM/I passive microwavebrightness temperatures

Passive microwave brightness temperatures from the Defense Meteorological Space Program Special Sensor Microwave/Imager (SSM/I) were used to determine surface temperature over land areas in the central plains of the United States. A regression analysis comparing all of the SSM/I channels and minimum screen air temperatures (representing the surface temperature) showed good correlations, with root-mean-square errors of 2-3 degC. Pixels containing large amounts of water, snow, and falling rain, as classified with SSM/I brightness temperatures, were excluded from the analysis. The use of independent ground truth data such as soil moisture or land surface type was not required to obtain the correlations between brightness temperatures and surface temperatures     

A microwave technique for mapping ice temperature in the Arcticseasonal sea ice zone

A technique for deriving ice temperature in the Arctic seasonal sea ice zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses ice concentration and type from a previously developed thin ice algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observation from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the ice temperature depends on ice type     

Retrieval of atmospheric and surface parameters from satellite microwave radiometers over the Mediterranean Sea

A procedure to estimate atmospheric and sea surface parameters in the Mediterranean area from satellite microwave radiometric measurements is described. The method is founded on a simulator of brightness temperatures at the top of the atmosphere. The simulator is based on microwave sea emissivity and scattering model functions, derived from the outputs of the SEAWIND software, which implements a two-scale microwave sea surface model and a radiative transfer scheme in a nonscattering atmosphere. The development of the model functions aims to reduce the SEAWIND computational time, still maintaining its sensitivity to the main geophysical variables. Different adaptations of the simulation model have been performed to better reproduce the radiometric data in the region of interest. A comparison between the simulations and the Special Sensor Microwave/Imager (SSM/I) observations acquired throughout year 2000 over the Mediterranean Sea has permitted us to refine the model functions as well as to assess the whole simulation procedure. As for the inversion problem, a regression analysis has been applied to two different synthetic datasets to retrieve integrated precipitable water vapor, liquid water path and wind speed. The first dataset simulates the observations of SSM/I, whilst the second one concerns the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Both have been generated by using the ECMWF atmospheric profiles and the measurements of the SeaWinds scatterometer aboard QuickSCAT. The SSM/I data have been used to carry out a statistical validation of the estimators. AMSR-E observations of a Tramontane-Mistral event, typical of the Mediterranean Sea, have been analyzed to evaluate the benefits of its expanded channel capability.     

SSM/I instrument evaluation

The Special Sensor Microwave/Imager (SSM/I) instrument and scan geometry are briefly described. The results of investigations of the stability of the gain, calibration targets and spin rate, the radiometer noise and sensitivity, the coregistration, the beam width and main-beam efficiency of the antenna beams, and the absolute calibration and geolocation of the instrument are presented. The results of this effort demonstrate that the SSM/I is a stable, sensitive, and well-calibrated microwave radiometric system capable of providing accurate brightness temperatures for microwave images of the Earth and for use by environmental product retrieval algorithms. It is predicted that this SSM/I and the 11 future ones currently built or to be built will provide high-performance microwave measurements for determination of global weather and critical atmospheric, oceanographic, and land parameters to operational forecasters and users and the research community for the next two decades     

Retrieval of land and sea brightness temperatures from mixedcoastal pixels in passive microwave data

A technique is presented to separate uncontaminated land and sea brightness temperatures from mixed coastal pixels in 37-GHz vertically polarized passive microwave data from the Special Sensor Microwave Imager (SSM/I) instrument. Combining a mathematical model of the instrument response over several neighboring footprints with a GIS representation of the coastline yields a relationship between land and sea brightness temperatures and radiation measurements made at the satellite. Inverting this relationship allows separate land and sea brightness temperature values to be derived for each mixed coastal pixel in the original image. The technique has been successfully applied to 37-GHz vertically polarized SSM/I imagery for test areas covering the Gulf of Aden and the British Isles. Errors in the retrieved brightness temperatures were estimated to be of the order of 1-2 K     

The influence of clouds on microwave brightness temperatures viewing downward over open seas

Microwave brightness temperatures for the case of downward viewing from above the earth's atmosphere over water for the 1- to 2-cm wavelength range are calculated for comparison with observations. A model of the troposphere which contains homogeneous layer clouds of varied thickness and liquid water content is used to compute estimates of the influence which clouds would have on real observations. It is assumed that only pure absorption is important for the cloud droplet-size distributions and droplet densities used. Results of the computations indicate that most water clouds will contribute a measurable amount to the microwave emission of the atmosphere and, in some cases, can be the principal source of received radiation. Comparisons of the computed cases with measurements obtained with a high flying aircraft are shown to be in reasonable agreement. These results are significant because they demonstrate that water clouds cannot be neglected in the application of passive microwave techniques to remote probing of the earth's atmosphere and because they indicate that quantitative measures of cloud liquid water contents and cloud thickness might be acquired through multi-frequency measurements.     

Retrieval of cloud base heights from passive microwave and cloudtop temperature data

Water vapor profiling algorithms that treat liquid clouds explicitly yield a cloud base height as a byproduct. A single case of a water vapor profile retrieval using a combination of the SSM/T-2 on the DMSP satellite and cloud parameters from the AVHRR on the NOAA satellite retrieved a reasonable cloud base. While hardly definitive, this case is suggestive. The authors examine the cloud base signal in a combination of the SSM/1 and SSM/T-2 on the DMSP satellite from a theoretical point of view. It is shown that the signal is strong enough for a useful retrieval only over the ocean. For low altitudes, a cloud top temperature (CTT) constraint, as could be provided from an infrared radiometer, is required. While difficult with the DMSP-NOAA satellite combination, this has become much easier with the recent launch of NOAA-K with the AMSU-B and AVHRR. It is shown that the signal is acceptable over the relevant range of cloud liquid water content values. To achieve useful results, some local tuning of the algorithm will be necessary. This tuning could take the form of water vapor profile covariance matrices, climatological estimates of the cloud liquid water density, or purely empirical methods. Broken and multilayer clouds provide additional complications to the problem     

An updated analysis of the ocean surface wind direction signal in passive microwave brightness temperatures

We analyze the wind direction signal for vertically (v) and horizontally (h) polarized microwave radiation at 37 GHz, 19 GHz, and 11 GHz; and an Earth incidence angle of 53/spl deg/. We use brightness temperatures from SSM/I and TMI and wind vectors from buoys and the QUIKSCAT scatterometer. The wind vectors are space and time collocated with the radiometer measurements. Water vapor, cloud water and sea surface temperature are obtained from independent measurements and are uncorrelated with the wind direction. We find a wind direction signal that is noticeably smaller at low and moderate wind speeds than a previous analysis had indicated. We attribute the discrepancy to errors in the atmospheric parameters that were present in the data set of the earlier study. We show that the polarization combination 2v-h is almost insensitive to atmospheric changes and agrees with the earlier results. The strength of our new signals agrees well with JPL aircraft radiometer measurements. It is significantly smaller than the prediction of the two-scale sea surface emission model for low and intermediate wind speeds.     

The potential of combining SSM/I and SSM/T2 measurements to improvethe identification of snowcover and precipitation

The potential of passive microwave radiometry for classifying snowcover and precipitation using measurements from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Water Vapor Profiler (SSM/T2) is investigated by modelling the radiative transfer for different surface types and atmospheric conditions. The model accounts for various land surfaces and vegetation covers, different snow types as well as wind roughened ocean water. The atmospheric part includes multiple scattering and depolarization by cloud droplets and precipitating water as well as ice spheres. It was found, that the combination of a window channel (91 GHz) and an atmospheric sounding channel (183±7 GHz) can improve the separation of snowcover and precipitation which is difficult by using only SSM/I channels. The 183±7 GHz channel is strongly influenced by the water vapor distribution which makes its use difficult for warm rain cases and low cloud tops. Then, the signature at this frequency is not unique and the above relation gives no further improvement of the classification. However, the identification of rainfall over cold land backgrounds can be significantly improved, which is illustrated by the application of a combined SSM/I-SSM/T2 algorithm to two satellite datasets when compared to the SSM/I algorithm and to operational surface weather maps     

Water vapor profiling over ocean surface from airborne 90 and 183GHz radiometric measurements under clear and cloudy conditions

Radiometric measurements at 90 GHz and three sideband frequencies near the water vapor absorption line at 183.3 GHz were made with the Advanced Microwave Moisture Sounder (AMMS) aboard the NASA DC-8 aircraft over some regions of the Pacific Ocean during November 1989. These measurements were used to retrieve atmospheric water vapor profiles over ocean surface using the algorithm developed by T.T. Wilheit (1979). The algorithm incorporates a mechanism to estimate cloud liquid water when the estimated relative humidity is greater than 95%. The results are compared with the estimated values from the measurements of Special Sensor Microwave Imager (SSMI) and TIROS Operational Vertical Sounder (TOVS). The water vapor profiles estimated from AMMS are generally higher at low altitudes and lower at high altitudes compared to those from the TOVS measurements. Values of total precipitable water estimated from the AMMS and SSM/I are in general agreement. Cloud liquid water vapor profiles retrieved from the AMMS show more fluctuations than those from SSM/I     

Retrieval of Atmospheric Integrated Water Vapor and Cloud Liquid Water Content Over the Ocean From Satellite Data Using the 1-D-Var Ice Cloud Microphysics Data Assimilation System (IMDAS)

Reliable prediction of precipitation by numerical weather prediction (NWP) models depends on the appropriate representation of cloud microphysical processes and accurate initial conditions of observations of atmospheric variables. Therefore, to retrieve reasonable cloud distributions, a 1-D variational Ice Cloud Microphysics Data Assimilation System (IMDAS) is developed to improve the predictability of NWP models. The general framework of IMDAS includes the Lin ice cloud microphysics scheme as a model operator, a four-stream fast microwave radiative transfer model in the atmosphere as an observation operator, and a global minimization method that is known as the shuffled complex evolution. IMDAS assimilates the satellite microwave radiometer data set of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and retrieves integrated water vapor and integrated cloud liquid water content. This new method successfully introduces heterogeneity into the initial state of the atmosphere, and the modeled microwave brightness temperatures agree well with the observations of the Wakasa Bay Experiment 2003 in Japan. It has significantly improved the performance of the cloud microphysics scheme by the intrusion of heterogeneity into the external global reanalysis data, which resultantly improved atmospheric initial conditions.     

Raman lidar calibration for the DMSP SSM/T-2 microwave water vaporsensor

Campaigns were conducted at the Pacific Missile Range Facility, Barking Sands, Kauai, investigating Raman lidar as a method to improve calibration of the DMSP SSM/T-2 microwave water vapor profiling instrument. Lidar mixing ratios were calibrated against AIR and Vaisala radiosondes and the calibration was tested in the vicinity of clouds. Above 6 km, radiosondes reported anomalously low relative humidity in the vicinity of clouds. Lidar measurements were confirmed by using an electro-optical shutter, which provided correct measurement of relative humidity at cloud bases above 6 km. Radiative transfer calculations applied to the lidar data closely matched signals observed in the SSM/T-2 atmospheric channels. Forward calculations for surface sensitive channels disagreed with SSM/T-2 and SSM/I observations. Fine scale surface roughness and localized orographic drying are tentatively suggested as explanations. Cloud effects were ruled out as a significant source of discrepancy     

Soil moisture and TRMM microwave imager relationships in theSouthern Great Plains 1999 (SGP99) experiment

Satellite data collected by the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) and the special sensor microwave/imager (SSM/I) were compared to soil moisture observations as part of the Southern Great Plains (SGP) 1999 Experiment. SGP99 was conducted to address significant gaps in the knowledge base on the microwave remote sensing of soil moisture. Satellite, aircraft and ground based data collection were conducted between July 8, 1999 and July 20, 1999, during which an excellent sequence of meteorological conditions occurred. Cross calibration of the SSM/I data to the same TMI channels showed nearly identical brightness temperatures, 19 GHz SSM/I data and soil moisture relationships were similar to those observed in previous experiments in this region. Comparison studies of the SSM/I and TMI channels revealed that only sampling areas with adequate spatial domains should be used for soil moisture validation. Analyses of the TMI 10 GHz data provide new information on potential improvements that this channel can provide for soil moisture estimation. Soil moisture maps of the region were derived for dates of coverage     

Determination of oceanic total precipitable water from the SSM/I

Results are presented of calibration/validation studies showing the ability of the Special Sensor Microwave/Imager (SSM/I) to measure total precipitable water in the atmosphere over the ocean. Comparisons between radiosondes and the SSM/I are presented for three different algorithms. The results show the possibility of a distinct improvement in the retrieval of total precipitable water over the ocean. The global, nonlinear algorithm is more sensitive to cloud liquid water content, rain, and sea ice. The additional sensitivity is due to the screening of rain and sea ice from the dependent data and the squared term in the retrieval algorithm. Thus, it will be very important to have good screening procedures for identifying these conditions. The linear algorithm overestimates in the mid-range and underestimates at large values of total precipitable water. The explanation for this effect is probably related to the selection of the center of the water vapor line as the operating frequency of the SSM/I water vapor channel. The line center is most likely to exhibit a saturation effect at large water vapor amounts, and pressure and temperature effects can also be important, depending on the distribution of water vapor in the atmosphere