An Improved Ocean Vector Winds Retrieval Approach Using C- And Ku-band Scatterometer And Multi-frequency Microwave Radiometer Measurements

This dissertation will specifically address the issue of improving the quality of satellite scatterometer retrieved ocean surface vector winds (OVW), especially in the presence of strong rain associated with tropical cyclones. A novel active/passive OVW retrieval algorithm is developed that corrects Ku-band scatterometer measurements for rain effects and then uses them to retrieve accurate OVW. The rain correction procedure makes use of independent information available from collocated multi-frequency passive microwave observations provided by a companion sensor and also from simultaneous C-band scatterometer measurements. The synergy of these active and passive measurements enables improved correction for rain effects, which enhances the utility of Ku-band scatterometer measurements in extreme wind events. The OVW retrieval algorithm is based on the next generation instrument conceptual design for future US scatterometers, i.e. the Dual Frequency Scatterometer (DFS) developed by NASA’s Jet Propulsion Laboratory. Under this dissertation research, an end-to-end computer simulation was developed to evaluate the performance of this active/passive technique for retrieving hurricane force winds in the presence of intense rain. High-resolution hurricane wind and precipitation fields were simulated for several scenes of Hurricane Isabel in 2003 using the Weather Research and Forecasting (WRF) Model. Using these numerical weather model environmental fields, active/passive measurements were simulated for instruments proposed for the Global Change Observation Mission- Water Cycle (GCOM-W2) satellite series planned by the Japanese Aerospace Exploration Agency. Further, the quality of the simulation was evaluated using actual hurricane measurements from the Advanced Microwave Scanning Radiometer and iv SeaWinds scatterometer onboard the Advanced Earth Observing Satellite-II (ADEOS-II). The analysis of these satellite data provided confidence in the capability of the simulation to generate realistic active/passive measurements at the top of the atmosphere. Results are very encouraging, and they show that the new algorithm can retrieve accurate ocean surface wind speeds in realistic hurricane conditions using the rain corrected Ku-band scatterometer measurements. They demonstrate the potential to improve wind measurements in extreme wind events for future wind scatterometry missions such as the proposed GCOM-W2

Challenges to Satellite Sensors of Ocean Winds: Addressing Precipitation Effects

Measurements of global ocean surface winds made by orbiting satellite radars have provided valuable information to the oceanographic and meteorological communities since the launch of the Seasat in 1978, by the National Aeronautics and Space Administration (NASA). When Quick Scatterometer (QuikSCAT) was launched in 1999, it ushered in a new era of dual-polarized, pencil-beam, higher-resolution scatterometers for measuring the global ocean surface winds from space. A constant limitation on the full utilization of scatterometer-derived winds is the presence of isolated rain events, which affect about 7% of the observations. The vector wind sensors, the Ku-band scatterometers [NASA\u27s SeaWinds on the QuikSCAT and Midori-II platforms and Indian Space Research Organisation\u27s (ISRO\u27s) Ocean Satellite (Oceansat)-2], and the current C-band scatterometer [Advanced Wind Scatterometer (ASCAT), on the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)\u27s Meteorological Operation (MetOp) platform] all experience rain interference, but with different characteristics. Over this past decade, broad-based research studies have sought to better understand the physics of the rain interference problem, to search for methods to bypass the problem (using rain detection, flagging, and avoidance of affected areas), and to develop techniques to improve the quality of the derived wind vectors that are adversely affected by rain. This paper reviews the state of the art in rain flagging and rain correction and describes many of these approaches, methodologies, and summarizes the results

Second-order structure function analysis of scatterometer winds over the Tropical Pacific

22 pages, 16 figures, 1 tableKolmogorov second-order structure functions are used to quantify and compare the small-scale information contained in near-surface ocean wind products derived from measurements by ASCAT on MetOp-A and SeaWinds on QuikSCAT. Two ASCAT and three SeaWinds products are compared in nine regions (classified as rainy or dry) in the tropical Pacific between 10°S and 10°N and 140° and 260°E for the period November 2008 to October 2009. Monthly and regionally averaged longitudinal and transverse structure functions are calculated using along-track samples. To ease the analysis, the following quantities were estimated for the scale range 50 to 300 km and used to intercompare the wind products: (i) structure function slopes, (ii) turbulent kinetic energies (TKE), and (iii) vorticity-to-divergence ratios. All wind products are in good qualitative agreement, but also have important differences. Structure function slopes and TKE differ per wind product, but also show a common variation over time and space. Independent of wind product, longitudinal slopes decrease when sea surface temperature exceeds the threshold for onset of deep convection (about 28°C). In rainy areas and in dry regions during rainy periods, ASCAT has larger divergent TKE than SeaWinds, while SeaWinds has larger vortical TKE than ASCAT. Differences between SeaWinds and ASCAT vortical TKE and vorticity-to-divergence ratios for the convectively active months of each region are large. © 2014. American Geophysical Union. All Rights ReservedThe ASCAT-12.5 and ASCAT-25 data used in this work can be ordered online from the EUMETSAT Data Centre (www.eumetsat.int) as SAF type data in BUFR or NetCDF format. They can also be ordered from PO.DAAC (podaac.jpl.nasa.gov) in NetCDF format only. The SeaWinds-NOAA and QuikSCAT-12.5 data are also available from PO.DAAC. The SeaWinds-KNMI data are available from the KNMI archive upon an email request to [email protected]. Rain-rates and sea surface temperatures were obtained from the Tropical Rainfall Measuring Mission's (TRMM) Microwave Imager (TMI) archive at the Remote Sensing Systems web site (www.ssmi.com). SeaWinds Radiometer (SRAD) rain-rates were obtained from the QuikSCAT 25 km L2B science data product that is available from PO.DAAC. This work has been funded by EUMETSAT in the context of the Numerical Weather Prediction Satellite Applications Facility (NWP SAF). The contribution of GPK has been supported by EUMETSAT as part of the SAF Visiting Scientists programmePeer Reviewe

Theoretical modeling of dual-frequency scatterometer response: improving ocean wind and rainfall effects

Ocean surface wind is a key parameter of the Earth’s climate system. Occurring at the interface between the ocean and the atmosphere, ocean winds modulate fluxes of heat, moisture and gas exchanges. They reflect the lower branch of the atmospheric circulation and represent a major driver of the ocean circulation. Studying the long-term trends and variability of the ocean surface winds is of key importance in our effort to understand the Earth’s climate system and the causes of its changes. More than three decades of surface wind data are available from spaceborne scatterometer/radiometer missions and there is an ongoing effort to inter-calibrate all these measurements with the aim of building a complete and continuous picture of the ocean wind variability. Currently, spaceborne scatterometer wind retrievals are obtained by inversion algorithms of empirical Geophysical Model Functions (GMFs), which represent the relationship between ocean surface backscattering coefficient and the wind parameters. However, by being measurement-dependent, the GMFs are sensor-specific and, in addition, they may be not properly defined in all weather conditions. This may reduce the accuracy of the wind retrievals in presence of rain and it may also lead to inconsistencies amongst winds retrieved by different sensors. Theoretical models of ocean backscatter have the big potential of providing a more general and understandable relation between the measured microwave backscatter and the surface wind field than empirical models. Therefore, the goal of our research is to understand and address the limitations of the theoretical modeling, in order to propose a new strategy towards the definition of a unified theoretical model able to account for the effects of both wind and rain. In this work, it is described our approach to improve the theoretical modeling of the ocean response, starting from the Ku-band (13.4 GHz) frequency and then broadening the analysis at C-band (5.3 GHz) frequency. This research has revealed the need for new understanding of the frequency-dependent modeling of the surface backscatter in response to the wind-forced surface wave spectrum. Moreover, our ocean wave spectrum modification introduced to include the influences of the surface rain, allows the interpretation/investigation of the scatterometer observations in terms not only of the surface winds but also of the surface rain, defining an additional step needed to improve the wind retrievals algorithms as well as the possibility to jointly estimate wind and rain from scatterometer observations

Oceanic rain rate estimates from the QuikSCAT Radiometer: A Global Precipitation Mission pathfinder

[1] The SeaWinds scatterometer, launched onboard the QuikSCAT satellite in 1999, measures global ocean vector winds. In addition to measuring radar backscatter, SeaWinds simultaneously measures the microwave brightness temperature of the atmosphere/surface, and this passive microwave measurement capability is known as the QuikSCAT Radiometer (QRad). This paper presents a QRad retrieval algorithm used to infer instantaneous oceanic rain rates. This statistical algorithm is trained using near-simultaneous observations of major rain events by QRad and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). Rain rate retrieval algorithm validation is presented through comparisons with independent rain measurements from the TMI 2A12 surface rain rates and the TRMM 3B42RT composite microwave and visible and infrared near-real time data product. Results demonstrate that QRad rain rate measurements are in good agreement with these independent microwave rain observations and superior to the visible/infrared rain estimates. Thus the QRad rain measurement time series is a valuable addition to the oceanic precipitation climatology that can be used to improve the diurnal estimation of the global rainfall, which is a goal for the future Global Precipitation Mission program. Moreover, the availability of QRad data will provide GPM users early access to learn to use less-precise rain measurements that will occur in the GPM era with the use of less-capable constellation satellites. Finally, these QRad rain estimates will be available in the planned data reprocessing (FY 2006) of QuikSCAT winds to improve the rain flagging of rain-contaminated oceanic wind vector retrievals

Can GNSS reflectometry detect precipitation over oceans?

For the first time, a rain signature in Global Navigation Satellite System Reflectometry (GNSS‐R) observations is demonstrated. Based on the argument that the forward quasi‐specular scattering relies upon surface gravity waves with lengths larger than several wavelengths of the reflected signal, a commonly made conclusion is that the scatterometric GNSS‐R measurements are not sensitive to the surface small‐scale roughness generated by raindrops impinging on the ocean surface. On the contrary, this study presents an evidence that the bistatic radar cross section σ0 derived from TechDemoSat‐1 data is reduced due to rain at weak winds, lower than ≈ 6 m/s. The decrease is as large as ≈ 0.7 dB at the wind speed of 3 m/s due to a precipitation of 0–2 mm/hr. The simulations based on the recently published scattering theory provide a plausible explanation for this phenomenon which potentially enables the GNSS‐R technique to detect precipitation over oceans at low winds

Community Review of Southern Ocean Satellite Data Needs

This review represents the Southern Ocean community’s satellite data needs for the coming decade. Developed through widespread engagement, and incorporating perspectives from a range of stakeholders (both research and operational), it is designed as an important community-driven strategy paper that provides the rationale and information required for future planning and investment. The Southern Ocean is vast but globally connected, and the communities that require satellite-derived data in the region are diverse. This review includes many observable variables, including sea-ice properties, sea-surface temperature, sea-surface height, atmospheric parameters, marine biology (both micro and macro) and related activities, terrestrial cryospheric connections, sea-surface salinity, and a discussion of coincident and in situ data collection. Recommendations include commitment to data continuity, increase in particular capabilities (sensor types, spatial, temporal), improvements in dissemination of data/products/uncertainties, and innovation in calibration/validation capabilities. Full recommendations are detailed by variable as well as summarized. This review provides a starting point for scientists to understand more about Southern Ocean processes and their global roles, for funders to understand the desires of the community, for commercial operators to safely conduct their activities in the Southern Ocean, and for space agencies to gain greater impact from Southern Ocean-related acquisitions and missions.The authors acknowledge the Climate at the Cryosphere program and the Southern Ocean Observing System for initiating this community effort, WCRP, SCAR, and SCOR for endorsing the effort, and CliC, SOOS, and SCAR for supporting authors’ travel for collaboration on the review. Jamie Shutler’s time on this review was funded by the European Space Agency project OceanFlux Greenhouse Gases Evolution (Contract number 4000112091/14/I-LG)

Radiometric correction of scatterometric wind measurements

Use of a spaceborne scatterometer to determine the ocean-surface wind vector requires accurate measurement of radar backscatter from ocean. Such measurements are hindered by the effect of attenuation in the precipitating regions over sea. The attenuation can be estimated reasonably well with the knowledge of brightness temperatures observed by a microwave radiometer. The NASA SeaWinds scatterometer is to be flown on the Japanese ADEOS2. The AMSR multi-frequency radiometer on ADEOS2 will be used to correct errors due to attenuation in the SeaWinds scatterometer measurements. Here we investigate the errors in the attenuation corrections. Errors would be quite small if the radiometer and scatterometer footprints were identical and filled with uniform rain. However, the footprints are not identical, and because of their size one cannot expect uniform rain across each cell. Simulations were performed with the SeaWinds scatterometer (13.4 GHz) and AMSR (18.7 GHz) footprints with gradients of attenuation. The study shows that the resulting wind speed errors after correction (using the radiometer) are small for most cases. However, variations in the degree of overlap between the radiometer and scatterometer footprints affect the accuracy of the wind speed measurements

Operational Use and Impact of Satellite Remotely Sensed Ocean Surface Vector Winds in the Marine Warning and Forecasting Environment

Rhodesia, Corn MillColorVolume 81, Page

Observational studies of scatterometer ocean vector winds in the presence of dynamic air-sea interactions

Ocean vector wind measurements produced by satellite scatterometers are used in many applications across many disciplines, from forcing ocean circulation models and improving weather forecasts, to aiding in rescue operations and helping marine management services, and even mapping energy resources. However, a scatterometer does not in fact measure wind directly; received radar backscatter is proportional to the roughness of the ocean\u27s surface, which is primarily modified by wind speed and direction. As scatterometry has evolved in recent decades, highly calibrated geophysical model functions have been designed to transform this received backscatter into vector winds. Because these products are used in so many applications, it is crucial to understand any limitations of this process. For instance, a number of assumptions are routinely invoked when interpreting scatterometer retrievals in areas of complex air-sea dynamics without, perhaps, sufficient justification from supporting observations. This dissertation uses satellite data, in situ measurements, and model simulations to evaluate these assumptions. Robustness is assured by using multiple types of satellite scatterometer data from different sensors and of different resolutions, including an experimental ultra-high resolution product that first required validation in the region of study. After this validation survey, a subsequent investigation used the multiple data resolutions to focus on the influence of ocean surface currents on scatterometer retrievals. Collocated scatterometer and buoy wind data along with buoy surface current measurements support the theory that scatterometer winds respond to the relative motion of the ocean surface; in other words, that they can effectively be considered current-relative, as has been generally assumed. Another major control on scatterometer retrievals is atmospheric stability, which affects both surface roughness and wind shear. A study using wind, stress, temperature, and pressure measurements at a mooring in the Gulf Stream as well as collocated scatterometer data proved that the scatterometer responds as expected to changes in stability. Therefore, scatterometer retrievals can effectively be used to evaluate changes in wind due to speed adjustment over temperature fronts. Given the conclusions of these individual studies, this work collectively solidifies decades of theory and validates the use of scatterometer winds in areas of complex air-sea interaction