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At least 595 records · Page 33

2nd Generation Airborne Precipitation Radar (APR-2)

Dual-frequency operation with Ku-band (13.4 GHz) and Ka-band (35.6 GHz). Geometry and frequencies chosen to simulate GPM radar. Measures reflectivity at co- and cross-polarizations, and Doppler. Range resolution is approx. 60 m. Horizontal resolution at surface is approx. 1 km. Reflectivity calibration is within 1.5 dB, based on 10 deg sigmaO at Ku-band and Mie scattering calculations in light rain at Ka-band. LDR measurements are OK to near -20 dB; LDR lower than this is likely contaminated by system cross-polarization isolation. Velocity is motion-corrected total Doppler, including particle fall speed. Aliasing can be seen in some places; can usually be dealiased with an algorithm. .

Ku-band (13.4 GHz)↗

What Would Happen to Superstorm Sandy Under the Influence of a Substantially Warmer Atlantic Ocean?

Based on ensemble numerical simulations, we find that possible responses of Sandy-like superstorms under the influence of a substantially warmer Atlantic Ocean bifurcate into two groups. In the first group, storms are similar to present-day Sandy from genesis to extratropical transition, except they are much stronger, with peak Power Destructive Index (PDI) increased by 50-80%, heavy rain by 30-50%, and maximum storm size (MSS) approximately doubled. In the second group, storms amplify substantially over the interior of the Atlantic warm pool, with peak PDI increased by 100-160%, heavy rain by 70-180%, and MSS more than tripled compared to present-day Superstorm Sandy. These storms when exiting the warm pool, recurve northeastward out to sea, subsequently interact with the developing midlatitude storm by mutual counterclockwise rotation around each other and eventually amplify into a severe Northeastern coastal storm, making landfall over the extreme northeastern regions from Maine to Nova Scotia.

radar reflectivities↗

Generation of Merged Radar-Lidar Data Products during the IMPACTS 2020 Field Campaign

A novel, composite lidar and radar data products was created using lidar and radar data products generated from the NASA ER-2 aircraft during the NASA IMPACTS 2020 field campaign. This product is intended to supplement the raw data sources, tease out additional aspects of the mechanisms underpinning wintertime cyclones, and enhance our understanding of microphysical properties in sensor overlap regions. Initial combined products focused on generating normalized fields of ER-2 based radar and lidar data to provide a more comprehensive visualization of storm structure (precipitation bands, cloud tops, melting levels, etc.) Ongoing work has focused on developing a combined radar-lidar reflectivity product and deriving hydrometeor particle properties (type, orientation, etc.) using ER-2-based depolarization data. To validate these hydrometeor properties, we leverage coincident overpasses of the high-altitude ER-2 aircraft with the suite of cloud particle probes on the in-situ P-3 aircraft during coincident flight overpasses. This work aims to provide vital information to help IMPACTS achieve its mission goal of improving microphysical properties retrievals from airborne and spaceborne platforms for these high-impact winter storm events.

Stephen D Nicholls↗

Optimal Estimation of Rain-Rate Profiles from Single-Frequency Radar Echoes

The significant ambiguities inherent in the determination of a particular vertical rain intensity profile from a given time profile of radar echo powers measured by a downward-looking (spaceborne or airborne) radar at a single attenuating frequency are well documented. Indeed, one already knows that by appropriately varying the parameters of the reflectivity-rain rate (Z-R) and/or attenuation-rain rate (k- R) relationships one can produce several substantially different rain-rate profiles that would produce the same radar power profile. Imposing the additional constraint that the path-averaged rain rate be a given fixed number does reduce the ambiguities but falls far short of eliminating them. While formulas to generate all mutually ambiguous rain-rate profiles from a given profile of received radar reflectivities have already been derived, there remains to be produced a quantitative measure to assess how likely each of these profiles is, what the appropriate "average" profile should be, and what the "variance" of these multiple solutions is. To do this, one needs to spell out the stochastic constraints that can allow us to make sense of the words "average" and "variance" in a mathematically rigorous way. Such a quantitative approach would be particularly well suited for such systems as the planned precipitation radar of the Tropical Rainfall Measuring Mission (TRMM). Indeed, one would then be able to use the radar reflectivities measured by the TRMM radar to estimate the rain-rate profile that would most likely have produced the measurements, as well as the uncertainty in the estimated rain rates as a function of range. Such an optimal approach is described in this paper.

Haddad, Ziad S.↗

Optimal Estimation of Rain Rate Profiles from Single-Frequency Radar Echoes

The significant ambiguities inherent in the determination of a particular vertical rain intensity profile from a given time profile of radar echo powers measured by a downward-looking (spaceborne or airborne) radar at a single attenuating frequency are well-documented. Indeed, one already knows that by appropriately varying the parameters of the reflectivity-rain-rate (Z - R) and/or attenuation-rain-rate (k - R) relationships, one can produce several substantially different hypothetical rain rate profiles which would have the same radar power profile. Imposing the additional constraint that the path-averaged rain-rate be a given fixed number does reduce the ambiguities but falls far short of eliminating them. While we now know how to generate as many mutually ambiguous rain-rate profiles from a given profile of received radar reflectivities as we like, there remains to produce a quantitative measure to assess how likely each of these profiles is, what the appropriate 'average' profile should be, and what the 'variance' of these multiple solutions is. Of course, in order to do this, one needs to spell out the stochastic constraints that can allow us to make sense of the words 'average' and 'variance' in a mathematically rigorous way. Such a quantitative approach would be particularly well-suited for such systems as the proposed Precipitation Radar of the Tropical Rainfall Measuring Mission (TRMM). Indeed, one would then be able to use the radar reflectivities measured by the TRMM radar from one particular look in order to estimate the most likely rain-rate profile that would have produced the measurements, as well as the uncertainty in the estimated rain-rates as a function of range. Such an optimal approach is described in this paper.

deep space flight computer real-time advanced spac↗

Three-frequency, polarimetric, airborne SAR observations of the Greenland ice sheet

Synthetic aperture radar (SAR) images of the Greenland ice sheet collected by an airborne system clearly reveal the four melting facies of this sheet defined 30 years ago from snow stratigraphy studies by glaciologists. In particular, the radar echoes from the percolation facies have radiometric and polarimetric characteristics that are unique among terrestrial surfaces, but that resemble the exotic radar echoes recorded from the icy Galilean satellites. There, the radar signals interact with subsurface, massive ice features created in the cold, dry snow by seasonal melting and refreezing events. The subsurface features act as efficient reflectors of the incident radiation most likely via internal reflections. In the soaked-snow facies, the radar reflectivity is much lower because radar signals are attenuated by the wetter snow before they can interact with subsurface structures. Inversion algorithms to derive geophysical information from the SAR data are developed in both cases to estimate snow wetness in the soaked-snow facies and the mass of ice water retained in the percolation facies.

Rignot, E.↗

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was -1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching -3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗

Radar properties of Europa, Ganymede, and Callisto

The radar properties of Europa, Ganymede, and Callisto are summarized and present understanding of these properties is documented. The radar techniques are described, observational results reviewed, and salient aspects of the radar data set discussed. Theoretical interpretation of the satellites' anomalous radar properties is addressed, including aspects such as external scattering and double reflection from hemispherical craters, the random-facet model, total internal reflection, multiple total internal reflection, the high radar geometric albedos, the tenous upper layer, the two-component regolith, and compositional effects. It is concluded that multiple total internal reflection from randomly oriented subsurface facets can explain the anomalous circular polarization inversion in the radar echoes from the three satellites. Several refinements of the Goldstein-Green (1980) scattering model are suggested.

Ostro, S. J.↗

Second-order multiple-scattering theory associated with backscattering enhancement for a millimeter wavelength weather radar with a finite beam width

Effects of multiple scattering on reflectivity are studied for millimeter wavelength weather radars. A time-independent vector theory, including up to second-order scattering, is derived for a single layer of hydrometeors of a uniform density and a uniform diameter. In this theory, spherical waves with a Gaussian antenna pattern are used to calculate ladder and cross terms in the analytical scattering theory. The former terms represent the conventional multiple scattering, while the latter terms cause backscattering enhancement in both the copolarized and cross-polarized components. As the optical thickness of the hydrometeor layer increases, the differences from the conventional plane wave theory become more significant, and essentially, the reflectivity of multiple scattering depends on the ratio of mean free path to radar footprint radius. These results must be taken into account when analyzing radar reflectivity for use in remote sensing.

radar reflectivity↗

Mean winds of the upper middle atmosphere (60-110 km): A global distribution from radar systems (M.F., METEOR, VHF)

Since the development of the last CIRA in 1972, the number of radars providing winds in the upper middle atmosphere has increased significantly. These systems fill the data gap between 60 km and 110 km. The radars include medium frequency (MF) radars or partial reflection systems giving data from 60/70 to 100/110 km; meteor radars, 80 to 110 km, and M.S.T. radars operating as meteor radars. Data from 12 locations are shown, which represent a good Northern Hemispheric (NH) North American chain, an Oceanian chain which is mainly in the Southern Hemisphere (SH), and some Western Europe data. Generally tidal oscillations have been removed from days or groups of days, and the remaining mean winds and longer period oscillations plotted as height-time contours. Composite cross sections from the years 1978 to 1982 were formed where possible so that only the major temporal features remain.

Manson, A. H.↗

Airborne radar and radiometer experiment for quantitative remote measurements of rain

An aircraft experiment has been conducted with a dual-frequency (10 GHz and 35 GHz) radar/radiometer system and an 18-GHz radiometer to test various rain-rate retrieval algorithms from space. In the experiment, which took place in the fall of 1988 at the NASA Wallops Flight Facility, VA, both stratiform and convective storms were observed. A ground-based radar and rain gauges were also used to obtain truth data. An external radar calibration is made with rain gauge data, thereby enabling quantitative reflectivity measurements. Comparisons between path attenuations derived from the surface return and from the radar reflectivity profile are made to test the feasibility of a technique to estimate the raindrop size distribution from simultaneous radar and path-attenuation measurements.

Kozu, Toshiaki↗

Radar estimation of slant path rain attenuation at frequencies above 10 GHz and comparisons with measured multi-season results

Techniques and results pertaining to estimating Earth satellite path rain attenuation events and statistics using radar at nonattenuating wavelengths are presented. The radar formulation and beam scanning methods are described and the procedure for relating the radar measured Rayleigh reflectivity to the high frequency Mie attenuation coefficient are given. Examples of radar derived single terminal statistics and estimation criteria as they relate to path angle and frequency are reviewed. Radar derived space diversity statistics and their dependence on terminal spacing and frequency are described. Site diversity performance curves obtained by radar and radiometry are compared with each other demonstrating the utility of radar methods. Results of a multi-year experiment to test, refine, and establish accuracies of radar methods for arriving at estimates of rain attenuation along an Earth-satellite path are discussed. Comparisons of measured and radar estimated fade events are presented and found to be good. Comparisons of cumulative fade distributions show agreement to be excellent giving an rms deviation of 1 dB.

Goldhirsh, J.↗

Magellan

Of all the planets in the solar system, Venus is the most like our own Earth in size, mass, and distance from the Sun. The motions of our planetary "twin" were known to the ancients, and its apparent changes in shape, similar to the phases of the Moon, were first studied by Galileo more than four centuries ago. In the modern era, it is by far the most visited world in the solar system - more than 20 spacecraft from the Soviet Union and the United States have been sent there since the early 1960's. The clouds of Venus have been probed, the structure and composition of its atmosphere measured, its landscape photographed, and its rocks chemically analyzed by automated landers. Yet, for all our fascination with Venus, we have only a sketchy, general knowledge of the planet's surface. While the other three "terrestrial" worlds - Earth, Mercury, and Mars have long since been mapped, details of the face of Venus are still largely unknown, due to the planet's dense, constant cloud cover. The clouds prevent us from ever photographing the solid surface, even from space, with conventional cameras. Beginning in the early 1960s, scientists on Earth began to counter this problem by using radar waves, which, unlike visible light, are able to penetrate the Venusian clouds and reflect off the solid planet back to Earth. With the help of computer processing, these radar reflections can be turned into pictures of the Venus surface. Earth-based radar imaging is thus extremely valuable. but it also is limited-Venus always shows the same hemisphere to us when it is near enough in its orbit for high-resolution study, so only a fraction of the planet can be explored from Earth.

Source record↗

The effect of ionospheric reflected noise on the performance of an orbital-debris radar system

An orbital-debris radar system was designed to detect the presence of small objects in low earth orbit by reflecting radio waves off the objects. The author provides a rigorous derivation of the ionospheric reflected noise power and provides an integration over the complete pulse period. Free electrons and ions contained in the ionosphere cause incoherent scatter of the radar signal. This ionospheric reflection tends to increase the noise at the terrestrial radar receiver. A parameter called the ionospheric scattering cross section per unit volume, which is a function of altitude, is useful for computing the power of the ionospheric reflection signal. The Doppler frequency speed of the ionospheric reflected signal is a function of altitude also. The ionospheric noise of a 9-GHz orbital-debris radar receiver is computed using these concepts. Annual and diurnal variations of the noise are included.

Bishop, Dennis F.↗