Laurence N. Connor

Retrieving ocean surface wind speed from the TRMM Precipitation Radar measurements

Spaceborne scatterometery has been used for many years now to retrieve the ocean surface wind field from normalized radar cross-section measurements of the ocean surface. Though designed specifically for the measurement of precipitation profiles in the atmosphere, the Precipitation Radar (PR) of the Tropical Rainfall Measuring Mission (TRMM) also acquires surface backscattering measurements of the global oceans. As such, this instrument provides an interesting opportunity to explore the benefits and pitfalls of alternative radar configurations in the satellite remote sensing of ocean winds. In this paper, a technique was developed for retrieving ocean surface winds using surface backscattering measurements from the TRMM PR. The wind retrieval algorithm developed for TRMM PR makes use of a maximum-likelihood estimation technique to compensate for the low backscattering associated with the PR configuration. The high vertical resolution of the PR serves to filter-out rain-contaminated cells normally integrated into Ku-band scatterometer measurements. The algorithm was validated through comparisons of ocean surface wind speeds derived from PR with remotely measured winds from TMI and QuikSCAT, as well as in situ observations from oceanographic buoys, revealing good agreements in wind speed estimations.

Assessment of radar‐derived snow depth over Arctic sea ice

Knowledge of contemporaneous snow depth on Arctic sea ice is important both to constrain the regional climatology and to improve the accuracy of satellite altimeter estimates of sea ice thickness. We assess new data available from the NASA Operation IceBridge snow radar instrument and derive snow depth estimates across the western Arctic ice pack using a novel methodology based on wavelet techniques that define the primary reflecting surfaces within the snow pack. We assign uncertainty to the snow depth estimates based upon both the radar system parameters and sea ice topographic variability. The accuracy of the airborne snow depth estimates are examined via comparison with coincident measurements gathered in situ across a range of ice types in the Beaufort Sea. We discuss the effect of surface morphology on the derivation, and consequently the accuracy, of airborne snow depth estimates. We find that snow depths derived from the airborne snow radar using the wavelet-based technique are accurate to 1 cm over level ice. Over rougher surfaces including multiyear and ridged ice, the radar system is impacted by ice surface morphology. Across basin scales, we find the snow-radar-derived snow depth on first-year ice is at least ∼60% of the value reported in the snow climatology for the Beaufort Sea, Canada Basin, and parts of the central Arctic, since these regions were previously dominated by multiyear ice during the measurement period of the climatology. Snow on multiyear ice is more consistent with the climatology.

Ocean surface wind retrievals using the TRMM microwave imager

An analysis of one year of brightness temperature data from the TRMM microwave imager (TMI) is presented with regard to the retrieval of ocean surface wind speeds using standard regression techniques with in situ meteorological buoy measurements. Comparisons to similar satellite radiometer data from the special sensor microwave/imager (SSM/I) are also presented to help quantify atmospheric contributions to the surface wind retrievals. Particular emphasis is placed upon the use of the 10.7 GHz channels aboard the TMI in overcoming the contamination in the ocean surface brightness temperature measurements caused by precipitation and water vapor in the propagation path. The resulting wind retrieval improvements permit a relaxation in the rain flag definitions used to determine precipitation interference cutoff criteria, allowing accurate wind speed retrievals over a wider range of precipitation conditions. These improvements are realized through the construction of a new D-matrix wind speed retrieval algorithm suitable for the middle and low latitude coverage provided by the TRMM orbit.

Laser altimetry sampling strategies over sea ice

Abstract With the conclusion of the science phase of the Ice, Cloud and land Elevation Satellite (ICESat) mission in late 2009, and the planned launch of ICESat-2 in late 2015, NASA has recently established the IceBridge program to provide continuity between missions. A major goal of IceBridge is to obtain a sea-ice thickness time series via airborne surveys over the Arctic and Southern Oceans. Typically two laser altimeters, the Airborne Topographic Mapper (ATM) and the Land, Vegetation and Ice Sensor (LVIS), are utilized during IceBridge flights. Using laser altimetry simulations of conventional analogue systems such as ICESat, LVIS and ATM, with the multi-beam system proposed for ICESat-2, we investigate differences in measurements gathered at varying spatial resolutions and the impact on sea-ice freeboard. We assess the ability of each system to reproduce the elevation distributions of two sea-ice models and discuss potential biases in lead detection and sea-surface elevation, arising from variable footprint size and spacing. The conventional systems accurately reproduce mean freeboard over 25 km length scales, while ICESat-2 offers considerable improvements over its predecessor ICESat. In particular, its dense along-track sampling of the surface will allow flexibility in the algorithmic approaches taken to optimize the signal-to-noise ratio for accurate and precise freeboard retrieval.

WindSat validation datasets: an overview

Since the January 6, 2003 launch of the Naval Research Laboratory satellite Coriolis, the WindSat instrument onboard has provided over a year of unprecedented polarimetric microwave measurements of the globe. The WindSat radiometer has five operating frequencies at 6.8, 10.7, 18.7, 23.8 and 37 GHz, with the 10.7, 18.7, and 37 GHz channels providing fully polarimetric signals. The primary mission of Coriolis is to exploit the unique information provided by WindSats polarimetric capabilities to retrieve the complete ocean surface wind vector (speed and direction), though the retrieval of numerous other environmental parameters is being actively pursued as well. As part of a pre-NPOESS risk reduction effort, the NOAA/NESDIS/Office of Research and Applications has been collaborating with the Naval Research Laboratorys Remote Sensing Division in the calibration/validation of WindSat in preparation for the release of WindSat data products to the scientific and operational communities. An extensive overview is presented of the WindSat calibration/validation effort being put forth at NOAA/NESDIS and the associated comparison databases constructed for that purpose. These databases include data of WindSat measurements collocated with measurements from oceanographic buoys, ships, other satellites, and global data assimilation models. The strengths and limitations of these various datasets will be discussed in detail. This includes a synopsis of the colocation strategies used in matchup database construction for comparing WindSat measurements with other satellite based measurements, focusing particularly on similar orbit SSM/I data and its use in brightness temperature calibration. In addition, the use of NCEPs Global Data Assimilation System (GDAS) as a powerful source of plentiful comparison data is explored, particularly with regard to WindSat model function development

Validating ICESat Over Thick Sea Ice in the Northern Canada Basin

Only in the past eight years has the feasibility of using satellite-borne altimeters to estimate sea ice freeboard and thickness been demonstrated, and these estimates still have uncertainties primarily associated with limited knowledge of snow loading on sea ice. Because accurate estimates of Arctic-wide sea ice thickness and volume are fundamental inputs to global climate models, validation of satellite-derived thickness estimates using independent data is required. A detailed assessment of freeboard retrieved by the Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud, and land Elevation Satellite has been carried out using high-resolution laser altimetry from the National Aeronautics and Space Administrations Airborne Topographic Mapper (ATM), the Delay-Doppler radar altimeter, and digital photography collected along a 300-km segment of sea ice in the Canada Basin. Exploiting the repeat coverage of the aircraft flight line, a correction was applied to GLAS footprint geolocations to adjust for sea ice drift that occurred during the time between satellite and aircraft acquisitions. Comparisons of GLAS and ATM measurements over sea ice show excellent agreement (about a 0.00-m mean) with no apparent bias between data sets. Freeboard estimates were examined using data from GLAS and ATM independently, employing measurements over refrozen leads to estimate local sea surface heights (SSHs). The results demonstrate the sensitivity of freeboard and thickness calculations to an accurate estimation of local SSH. Snow depth derived by differencing laser and radar data was combined with the freeboard estimates to yield a mean sea ice thickness of ~ 5.5 m over a 250-km subsection of the flight track.

Sea-Ice Freeboard Retrieval Using Digital Photon-Counting Laser Altimetry

Abstract Airborne and spaceborne altimeters provide measurements of sea-ice elevation, from which sea-ice freeboard and thickness may be derived. Observations of the Arctic ice pack by satellite altimeters indicate a significant decline in ice thickness, and volume, over the last decade. NASA’s Ice, Cloud and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key sea-ice observations through the end of this decade. An airborne simulator for ICESat-2, the Multiple Altimeter Beam Experimental Lidar (MABEL), has been deployed to gather pre-launch data for mission development. We present an analysis of MABEL data gathered over sea ice in the Greenland Sea and assess the capabilities of photon-counting techniques for sea-ice freeboard retrieval. We compare freeboard estimates in the marginal ice zone derived from MABEL photon-counting data with coincident data collected by a conventional airborne laser altimeter. We find that freeboard estimates agree to within 0.03 m in the areas where sea-ice floes were interspersed with wide leads, and to within 0.07 m elsewhere. MABEL data may also be used to infer sea-ice thickness, and when compared with coincident but independent ice thickness estimates, MABEL ice thicknesses agreed to within 0.65 m or better.

Validation of ocean wind vector retrievals from WindSat polarimetric measurements

Using several months of WindSat measurements collocated with the NCEP Global Data Assimilation System model field, the Special Sensor Microwave Imager (SSM/I) measurements and QuikScat scatterometry measurements, we have derived an empirical geophysical model that describes radiometric vector for all WindSat channels, as a function of surface parameters: wind speed, wind direction and sea surface temperature, and atmospheric parameters: total precipitable water and cloud liquid water. This model function was then used to develop an ocean surface wind vector retrieval algorithm from WindSat polarimetric measurements. The accuracy of the retrieved wind vectors was quantified using several months of WindSat measurements collocated with the Special Sensor Microwave Imager (SSM/I) measurements and QuikSCAT scatterometry measurements.

The accuracy of high resolution winds from QuikSCAT

The accuracy of the high resolution QuikSCAT wind product was quantified using spatially and temporally collocated 10 m equivalent neutral stability winds, calculated from selected NOAA NDBC buoy measurements. Only buoys that had sample correlation higher than 1.5 were used in this validation, a total of 5704 records. The validation followed the Freilich nonlinear statistical analysis approach. This analysis of the collocated buoy-scatterometer data set yielded the following statistics for wind speed: deterministic offset -0.25 m/s; linear gain 1.02; standard deviation of component errors 1.9 m/s; and RMS error 2.2 m/s. Wind direction errors were more pronounced for lighter winds, typically for winds up to 5 m/s. The RMS directional error for buoy-QuikSCAT pairs for which /spl Delta//spl theta/<90/spl deg/ is 20.6/spl deg/.

The Imaging Wind and Rain Airborne Profiler - a dual frequency dual polarized conically scanning airborne profiling radar

The University of Massachusetts (UMass), with support from ONR, NOAA and NASA, has developed a novel radar system called the Imaging Wind and Rain Airborne Profiler (IWRAP). IWRAP is a dual frequency (C/Ku band) dual polarized airborne radar that profiles the volume and surface backscatter and Doppler simultaneously at 30, 35, 40 and 50 degrees incidence, while conically scanning at 30 to 90 rpm. Its range resolution can be set at 15, 30, 60 or 120 m. From these measurements the ocean surface wind field, 3-D boundary layer winds within rain bands can be mapped. IWRAP was flown during the 2002 NOAA/NESDIS/ORA Hurricane Ocean Winds Experiment, which was conducted in conjunction with the 2002 NOAA/AOML/HRD Hurricane Field Program. This paper presents the system design, radar processing algorithms and initial results from the 2002 hurricane flights.