Satellite Passive Microwave Measurements Research Articles

Behavior of an Inversion-Based precipitation Retrieval Algorithm with High-Resolution AMPR Measurements Including a Low-Frequency 10.7-GHz Channel

A microwave-based, profile-type precipitation retrieval algorithm has been used to analyze high-resolution passsive microwave measurements over an ocean background, obtained by the Advanced Microwave Precipitation Radiometer (AMPR) flown on a NASA ER-2 aircraft. The analysis is designed to first determine the improvements that can be gained by adding brightness temperature information from the AMPR low-frequency channel (10.7 GHz) to a multispectral retrieval algorithm nominally run with satellite information at 19, 37, and 85 GHz. The impact of spatial resolution degradation of the high-resolution brightness temperature information on the retrieved rain/cloud liquid water contents and ice water contents is then quantified in order to assess the possible biases inherent to satellite-based retrieval. Careful inspection of the high-resolution aircraft dataset reveals five distinctive brightness temperature features associated with cloud structure and scattering effects that are not generally detectable in current passive microwave satellite measurements. Results suggest that the inclusion of 10.7-GHz information overcomes two basic problems associated with three-channel retrieval. Intercomparisons of retrievals carried out at high-resolution and then averaged to a characteristic satellite scale to the corresponding retrievals in which the brightness temperatures are first convolved down to the satellite scale suggest that with the addition of the 10.7-GHz channel, the rain liquid water contents will not be negatively impacted by special resolution degradation. That is not the case with the ice water contents as they appear ti be quite sensitive to the imposed scale, the implication being that as spatial resolution is reduced, ice water contents will become increasingly underestimated.

Oceanic monthly rainfall derived from SSM/I

Accurate measurements of global precipitation are vital to the advancement of our understanding of the global hydrological cycle. The lack of rain‐gauge networks over the vast oceans points to satellite techniques as the only means by which oceanic rainfall can be measured and monitored. Passive microwave satellite measurements, obtained by the Special Sensor Microwave Imager (SSM/I) onboard the Defense Meteorological Satellite Program satellites, augmented with sophisticated retrieval and statistical techniques, can now provide quantitative climate‐scale oceanic rainfall estimates.It has long been recognized that precipitation is a major component of the global hydrological cycle and of the energetics of atmospheric circulation. However, the spatial and temporal variabilities of rain fields and the scarcity of rain‐gauge networks, especially over the oceans, lead to large uncertainties in oceanic rainfall climatology.

Foundations for Statistical–Physical Precipitation Retrieval from Passive Microwave Satellite Measurements. Part II: Emission-Source and Generalized Weighting-Function Properties of a Time-dependent Cloud-Radiation Model

The foremost physical aspects of microphysical-radiative interactions that control the formation and modulation of frequency-dependent passive microwave TB over a continental cold-rain precipitation system are explained within the framework of the essential ingredients of a physically based precipitation-retrieval algorithm. The analysis is based on a modeling study in which a 3D cloud model has provided the objective basis for generating an extensive set of microphysical profiles that describe numerous precipitation features in the course of the evolution of a continental hail storm. A summary of the various components of the algorithm, as well as the surface rain rates, is given. The algorithm employs the cloud model to provide a consistent and objectively generated source of detailed microphysical information as the underpinnings to an inversion-based perturbative retrieval scheme.

Foundations for Statistical-Physical Precipitation Retrieval from Passive Microwave Satellite Measurements. Part I: Brightness-Temperature Properties of a Time-dependent Cloud-Radiation Model

The relationship between emerging microwave brightness temperatures (T(B)s) and vertically distributed mixtures of liquid and frozen hydrometeors was investigated, using a cloud-radiation model, in order to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. Although strong relationships were found between the T(B) values and various rain parameters, these correlations are misleading in that the T(B)s are largely controlled by fluctuations in the ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. However, the empirically based T(B)-rain-rate (T(B)-RR) algorithms can still be used as tools for estimating precipitation if the hydrometeor profiles used for T(B)-RR algorithms are not specified in an ad hoc fashion.

Passive microwave remote and in situ measurements of artic and subarctic snow covers in Alaska

Between 11 and 19 March 1988, airborne and satellite passive microwave measurements were acquired simultaneously with ground measurements of depth, density and stratigraphy of the snow in central and northern Alaska. Five aircraft flights were flown along a north-south transect between about 147 ° W and 152 ° W, and extending from about 63° N (south of Fairbanks, Alaska) to the Arctic Ocean coastline, with an Aircraft Multichannel Microwave Radiometer (AMMR) on-board operating at 92 GHz, 37 GHz, 21 GHz, and 18 GHz. Passive microwave data from the satellite-borne Special Sensor Microwave Imager (SSMI), operating at 85.5 GHz, 37 GHz, 21 GHz, 18 GHz, and 10 GHz, were obtained concurrently. A good correspondence in brightness temperature (T B ) trends between the aircraft and satellite data was found. However, an expected inverse correlation between depth hoar thickness and T B was not found to be strong. A persistent T B minimum in both the aircraft and the satellite data was detected along the northern foothills of the Brooks Range. In an area located at about 68° 50'N, 149° 20'W, the T B as recorded from the aircraft microwave sensor dropped by 55 K. Satellite microwave measurements showed a T B decrease of up to 45 K at approximately the same location. Snow pit measurements did not reveal notable differences in snow characteristics or depth in this location. An examination of passive microwave satellite data from 1978 to 1987 revealed that similar low latewinter T B values were found in approximately the same locations as those observed in March 1988. According to the satellite data, the zone of low T B develops as the snow deepens, and reaches the lowest values in March or April each year. The cause of this T B minimum is unknown but thought to be related to snow stratigraphy. The observed difficulty in relating the ground measurements to data collected using aircraft and satellite passive microwave sensors is attributed to the fact that the snow depth and character are highly variable in central and northern Alaska. This variability is exemplified in the field measurements as well as in the passive microwave measurements.

Energy flux density estimation over sea ice based on satellite passive microwave measurements

This paper discusses in detail the energy flux density estimation at the ice/atmosphere interface over the entire North Water region, based on the ice-type distribution during the winter (1978/79 to 1985/86). The analysis is based on passive microwave measurements of the scanning multichannel microwave radiometer (SMMR) onboard the Nimbus 7 satellite. Based on the relation of increasing polarization ratio (18 or 37 GHz) with decreasing ice thickness, a threshold technique was applied to classify the different young ice types. The polarization ratio method seems feasible for climatological applications, such as energy flux density estimations, over large areas with homogeneous young ice. More than 20% young ice (<0.3m) was found in the North Water area (100,000 km2) throughout most winters, with maximal values of 60% and more, and only a few percent of open water were classified. In general, the young ice cover in the North Water was decreasing towards the end of the winter. The mean energy loss for the entire North Water region was found to be 77 W m−2 for the months of November to March. Considering an energy supply by refreezing of 38 W m−2, the remaining 39 W m−2 must be withdrawn from the enthalpy in the sea water.

Energy flux density estimation over sea ice based on satellite passive microwave measurements

This paper discusses in detail the energy flux density estimation at the ice/atmosphere interface over the entire North Water region, based on the ice-type distribution during the winter (1978/79 to 1985/86). The analysis is based on passive microwave measurements of the scanning multichannel microwave radiometer (SMMR) onboard the Nimbus 7 satellite. Based on the relation of increasing polarization ratio (18 or 37 GHz) with decreasing ice thickness, a threshold technique was applied to classify the different young ice types. The polarization ratio method seems feasible for climatological applications, such as energy flux density estimations, over large areas with homogeneous young ice. More than 20% young ice (<0.3m) was found in the North Water area (100,000 km2) throughout most winters, with maximal values of 60% and more, and only a few percent of open water were classified. In general, the young ice cover in the North Water was decreasing towards the end of the winter. The mean energy loss for the entire North Water region was found to be 77 W m−2for the months of November to March. Considering an energy supply by refreezing of 38 W m−2, the remaining 39 W m−2must be withdrawn from the enthalpy in the sea water.

Classification of Geophysical Parameters Using Passive Microwave Satellite Measurements

Surface and precipitation features are determined over a test site in central North America during January 1979 using the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR). An algorithm that uses the 18-and 37-GHz vertical polarization measurements is developed that can identify and separate six specific geophysical parameters: dry snow, sea ice, flooded or very wet land, dry land, open water, and rain. The algorithm is applied to a sequence of SMMR passes over the test site, and changes in various features, which are presented as color maps of geophysical parameters, are discussed.

Determination of snowpack properties from satellite passive microwave measurements

The use of satellite microwave data to determine snowpack properties is investigated through calculation of theoretical microwave brightness temperatures and comparison of the computed brightness temperatures with actual satellite microwave measurements. Archived data from the Nimbus-5 and Nimbus-6 Electrically Scanning Microwave Radiometers (ESMR), as well as data from the Nimbus-7 Scanning Multifrequency Microwave Radiometer (SMMR), are analyzed for a study area in the north-central United States. The results of the investigation indicate that snow boundaries can usually be defined by the 37-GHz or 18 (19) GHz data because of the sharp decrease in brightness temperature when going from land to a snow surface. For dry snow conditions, the 37 GHz data display a decrease in brightness temperature with snow depth due to the stronger volume scattering effect of the deeper snow; at 18–19 GHz, the sensitivity to snow depth is not as significant. The onset of snowmelt can be determined at both microwave frequencies investigated (18–19 GHz and 37 GHz) because of the significant increase in the brightness temperature with melting due to the decrease in volume scattering that occurs in the presence of free water.