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NASA NTRS2010

Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data

Introduction to the overlapped cloud properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.

Chang, Fu-Lung↗
NASA NTRS2009

Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

Grecu, Mircea↗
NASA NTRS1998

Enhanced Sea Ice Concentration and Ice Temperature Algorithms for AMSR

Accurate quantification of sea ice concentration and ice temperature from satellite passive microwave data is important because they provide the only long term, spatially detailed and consistent data set needed to study the climatology of the polar regions. Sea ice concentration data are used to derive large-scale daily ice extents that are utilized in trend analysis of the global sea ice cover. They are also used to quantify the amount of open water and thin ice in polynya and divergence regions which together with ice temperatures are in turn needed to estimate vertical heat and salinity fluxes in these regions. Sea ice concentrations have been derived from the NASA Team and Bootstrap algorithms while a separate technique for deriving ice temperature has been reported. An integrated technique that will utilizes most of the channels of AMSR (Advanced Microwave Scanning Radiometer) has been developed. The technique uses data from the 6 GHz and 37 GHz channels at vertical polarization obtain an initial estimate of sea ice concentration and ice temperature. The derived ice temperature is then utilized to estimate the emissivities for the corresponding observations at all the other channels. A procedure for calculating the ice concentration similar to the Bootstrap technique is then used but with variables being emissivities instead of brightness temperatures to minimizes errors associated with spatial changes in ice temperatures within the ice pack. Comparative studies of ice concentration results with those from other algorithms, including the original Bootstrap algorithm and those from high resolution satellite visible and infrared data will be presented. Also, results from a simulation study that demonstrates the effectiveness of the technique in correcting for spatial variations in ice temperatures will be shown. The ice temperature results are likewise compared with satellite infrared and buoy data with the latter adjusted to account for the effects of the snow cover.

Comiso, Josefino C.↗
NASA NTRS2006

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Markus, Thorsten↗
NASA NTRS1977

Synthesis and analysis of precise spaceborne laser ranging systems, volume 1

Measurement accuracy goals of 2 cm rms range estimation error and 0.003 cm/sec rms range rate estimation error, with no more than 1 cm (range) static bias error are requirements for laser measurement systems to be used in planned space-based earth physics investigations. Constraints and parameters were defined for links between a high altitude, transmit/receive satellite (HATRS), and one of three targets: a low altitude target satellite, passive (LATS), and active low altitude target, and a ground-based target, as well as with operations with a primary transmit/receive terminal intended to be carried as a shuttle payload, in conjunction with the Spacelab program.

Paddon, E. A.↗
NASA NTRS1986

Satellite microwave and in situ observations of the Weddell Sea ice cover and its marginal ice zone

The radiative and physical characteristics of the Weddell Sea ice cover and its marginal ice zone are analyzed using multichannel satellite passive microwave data and ship and helicopter observations obtained during the 1983 Antarctic Marine Ecosystem Research. Winter and spring brightness temperatures are examined; spatial variability in the brightness temperatures of consolidated ice in winter and spring cyclic increases and decrease in brightness temperatures of consolidated ice with an amplitude of 50 K at 37 GHz and 20 K at 18 GHz are observed. The roles of variations in air temperature and surface characteristics in the variability of spring brightness temperatures are investigated. Ice concentrations are derived using the frequency and polarization techniques, and the data are compared with the helicopter and ship observations. Temporal changes in the ice margin structure and the mass balance of fresh water and of biological features of the marginal ice zone are studied.

Comiso, J. C.↗
NASA NTRS1987

Severe storm identification with satellite microwave radiometry - An initial investigation with Nimbus-7 SMMR data

The use of satellite passive microwave observations for the detection of severe thunderstorms is investigated. Nimbus 7 SMMR data obtained from 1979 to 1980 over the U.S. east of 105 deg W are analyzed. The relative temperature brightnesses of the severe storms are examined; it is observed that temperature brightness decreases as the storm severity increases. The temperature brightness data were transformed into a quantitative measure of storm detection ability using the critical success index of Donaldson et al. (1975). Critical success indices of 0.32, 0.48, and 0.38 were obtained for the low-brightness-temperature thresholding of severe versus nonsevere storms during 1979, 1980, and 1979 and 1980 combined, respectively. The data reveal that the geostationary passive microwave imaging capability at 37 GHz is applicable to the detection and monitoring of severe convective storms.

Howland, Michael R.↗
NASA NTRS1988

Sea ice/climate studies

The objectives were to determine and analyze the annual cycle of sea ice extents in the Arctic Ocean and peripheral seas and bays over the period 1973 to 1986, looking in particular for any long term trends; to examine the relationship between local sea ice covers and the surrounding atmosphere and ocean; and to examine sea ice as a potential early indicator of climate change. The work involves creating regional and hemispheric time series of sea ice variables from satellite passive microwave data and analyzing these through various intercomparisons amongst themselves and with oceanographic and atmospheric fields.

Parkinson, C. L.↗
NASA NTRS1990

Precipitation observed over the South China Sea by the Nimbus-7 Scanning Multichannel Microwave Radiometer during Winter Monex

Mesoscale cloud clusters near the northwestern coast of Borneo were observed by the Scanning Multichannel Microwave Radiometer (SMMR) on three occasions during the Winter Monsoon Experiment in December 1978. A nondimensional form of the SMMR 37 GHz polarization difference is introduced and used to identify regions of precipitation, and these are compared with visible and infrared imagery from the GMS-1 geostationary satellite. For two of the three cloud cluster cases, quantitative comparisons are made between nearly simultaneous SMMR observations and reflectivity observations made by the MIT WR-73 digital weather radar at Bintulu. Though limited in scope, these represent the first known direct comparisons between digital radar-derived rain parameters and satellite passive microwave observations of near-equatorial precipitation. SMMR 37 GHz observations are found to be much better indicators of fractional coverage of each SMMR footprint by rain than of average rain rate within the footprint. Total area coverage by precipitation is estimated for all three clusters using this result.

Petty, Grant W.↗
NASA NTRS1990

Convective dynamics - Panel report

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

Carbone, Richard↗
NASA NTRS1991

Interannual variability of the spatial distribution of sea ice in the north polar region

The interannual variability of the monthly average spatial distributions of northern hemisphere sea ice was examined for the 1973-1987 period of the electrically scanning microwave radiometer on the Nimbus 5 satellite and the scanning multichannel microwave radiometer on the Nimbus 7 satellite passive microwave data record. Strong seasonal and spatial contrasts in the amount of interannual variability are mapped and identified. The maps and analyses provide a baseline against which future northern hemisphere sea ice distributions can be compared in the continuing attempt to analyze global climate and to determine whether or not significant climate change is occurring.

Parkinson, Claire L.↗
NASA NTRS1993

The Arctic Ocean ice balance - A Kalman smoother estimate

The methodology of Kalman filtering and smoothing is used to integrate a 7-year time series of buoy-derived ice motion fields and satellite passive microwave observations. The result is a record of the concentrations of open water, first-year ice, and multiyear ice that we believe is better than the estimates based on the microwave data alone. The Kalman procedure interprets the evolution of the ice cover in terms of advection, melt, growth, ridging, and aging of first-year into multiyear ice. Generally, the regions along the coasts of Alaska and Siberia and the area just north of Fram Strait are sources of first-year ice, with the rest of the Arctic Ocean acting as a sink for first-year ice via ridging and aging. All the Arctic Ocean except for the Beaufort and Chukchi seas is a source of multiyear ice, with the Chukchi being the only internal multiyear ice sink. Export through Fram Strait is a major ice sink, but we find only about two-thirds the export and greater interannual variation than found in previous studies. There is no discernible trend in the area of multiyear ice in the Arctic Ocean during the 7 years.

Thomas, D. R.↗
NASA NTRS1993

A recent sea-ice retreat west of the Antarctic Peninsula

Satellite passive microwave data show a record decrease in sea ice extent in the Bellingshausen Sea from mid-1988 through early 1991. The change coincides with more southerly surface winds, increased cyclonic activity and rising surface air temperatures, which reached historic highs along the west coast of the Antarctic Peninsula in 1989. Preceded by high ice cover in 1986-87, the retreat was most evident during summer in the formerly perennial sea-ice field over the continental shelf. Ocean heat storage probably contributed to the persistence and coastal propagation of this anomaly.

Jacobs, Stan S.↗