Scatterometer Wind Research Articles

Impacts of Assimilating CYGNSS Satellite Ocean-Surface Wind on Prediction of Landfalling Hurricanes with the HWRF Model

This study examines the impacts of assimilating ocean-surface winds derived from the NASA Cyclone Global Navigation Satellite System (CYGNSS) on improving the short-range numerical simulations and forecasts of landfalling hurricanes using the NCEP operational Hurricane Weather Research and Forecasting (HWRF) model. A series of data assimilation experiments are performed using HWRF and a Gridpoint Statistical Interpolation (GSI)-based hybrid 3-dimensional ensemble-variational (3DEnVar) data assimilation system. The influence of CYGNSS data on hurricane forecasts is compared with that of Advanced Scatterometer (ASCAT) wind products that have already been assimilated into the HWRF forecast system in a series of assimilation experiments. The effects of different versions of CYGNSS data (V2.1 vs. V3.0) on hurricane forecasts are evaluated. The results indicate that CYGNSS ocean-surface wind can lead to improved numerical simulations and forecasts of hurricane track and intensity, asymmetric wind structure, and precipitation. The impacts of CYGNSS on hurricane forecasts are comparable and complementary to the operational use of ASCAT satellite data products. The dependence of the relative impacts of different versions of CYGNSS data on optimal thinning distances is evident.

Impacts of Climate Oscillation on Offshore Wind Resources in China Seas

The long-term stability and sustainability of offshore wind energy resources are very important for wind energy exploration. In this study, the Cyclostationary Empirical Orthogonal Function (CSEOF) method, which can determine the time varying spatial distributions and long-term fluctuations in the cyclostationary geophysical process, was adopted to investigate the geographical and temporal variability of offshore wind resources in China Seas. The CSEOF analysis was performed on wind speeds at 70 m height above the sea surface from a validated combined Quick Scatterometer (QuikSCAT) and Advanced Scatterometer (ASCAT) wind product (2000–2016) with high spatial resolution of 12.5 km, and Climate Forecast System Reanalysis (CFSR) wind data (1979–2016) with a grid size of 0.5° × 0.5°. The decomposition results of the two datasets indicate that the first CSEOF mode represents the variability of wind annual cycle signal and contributes 77.7% and 76.5% to the wind energy variability, respectively. The principal component time series (PCTS) shows an interannual variability of annual wind cycle with a period of 3–4 years. The second mode accounts for 4.3% and 4.7% of total wind speed variability, respectively, and captures the spatiotemporal contribution of El Niño Southern Oscillation (ENSO) on regional wind energy variability. The correlations between the mode-2 PCTS of scatterometer or CFSR winds and the Southern Oscillation Index (SOI) are greater than 0.7, illustrating that ENSO has a significant impact on China’s offshore wind resources. Moreover, the mode-1 or mode-2 spatial pattern of CFSR winds is basically consistent with that of scatterometer data, but CFSR underestimates the temporal variability of annual wind speed cycle and the spatial changes of wind speed related to ENSO. Compared with reanalysis data, scatterometer winds always demonstrate a finer structure of wind energy variability due to their higher spatial resolution. For ENSO events with different intensities, the impact of ENSO on regional wind resources varies with time and space. In general, El Niño has reduced wind energy in most regions of China Seas except for the Bohai Sea and Beibu Bay, while La Niña has strengthened the winds in most areas except for the Bohai Sea and southern South China Sea.

First Assessment of GF3-02 SAR Ocean Wind Retrieval

On 23 November 2021, the Gaofen-3-02 (GF3-02) satellite was successfully launched in the Jiuquan Satellite Launch Center of China. The primary payload is C-band Synthetic Aperture Radar (SAR), with a maximum resolution of 1 m, and includes 12 imaging modes such as Spotlight, Strip, and TOPSAR, which will play an essential role in marine environment monitoring. As an important marine environmental parameter, the wind speed accuracy retrieved by GF3-02 SAR directly reflects its performance and effectiveness as an operational product. Therefore, based on the wind data of buoys of the National Data Buoy Center (NDBC), ECMWF reanalysis V5 (ERA5), and HY-2B Scatterometer (SCA), a preliminary accuracy assessment of the wind speed retrieved by GF3-02 SAR is carried out in this paper. The wind speed retrieval accuracy of GF3-02 SAR in the co-polarization (HH+VV) data under different Geophysical Model Functions (GMFs) is discussed by using 478 level-1A Single Look Complex (SLC) ocean products acquired in Quad-Polarization Strip I (QPSI) and produced by the National Satellite Ocean Application Service (NSOAS) from January to March 2022. The results show that the optimal root mean square errors (RMSE) are 1.40 m/s, 1.18 m/s, and 1.24 m/s for the VV polarization and 1.39 m/s, 1.19 m/s, and 1.52 m/s for the HH polarization compared to the NDBC wind speed, the ERA5 wind speed, and the HY-2B SCA wind speed, respectively. The preliminary results show that GF3-02 SAR has good wind speed retrieval ability and can meet the needs of operational products.

Effects of rain on CFOSAT scatterometer measurements

The Ku-band scatterometer onboard China France Oceanography Satellite (CFOSAT) observes the sea surface with two conically scanning fan beams. Compared to the prior Ku-band pencil beam scatterometers, this innovative observing mechanism provides more independent backscatter measurements at varying incidence and azimuth angles, as such it brings challenges for the sea surface wind inversion, particularly under rainy conditions. In this paper, the rain effects on the CFOSAT SCATterometer (CSCAT) are investigated using the collocated numerical weather prediction (NWP) wind data and the Global Precipitation Measurement (GPM) microwave imager (GMI) rain data. Similar to the prior Ku-band or C-band scatterometers, the sensitivity of CSCAT radar backscatter to rain substantially varies with wind speed, radar polarization and incidence angle. However, due to the complex observation geometries, rain effects on the CSCAT retrieved winds is more complex than that of prior scatterometers, which may lead to a remarkable underestimation of CSCAT wind speed at high winds and heavy rain conditions. A simple simulation method is used to clarify the relation between the retrieved wind speed and the dependency of radar rain effects on the incidence angle. It is found that the backscatter measurements at low incidence angles, which are generally underestimated at high winds and heavy rainy conditions, have a larger influence on the wind inversion minimization, leading to much lower retrieved wind speeds than those of ECMWF and the pencil beam scatterometer (e.g., Haiyang-2B scattometer). Under low and moderate rain conditions though, a more compensated effect between low and high incidence angle measurements is found, leading to generally unbiased CSCAT high winds, in contrast to the generally underestimated pencil-beam scatterometer winds.

Impact of Ocean Currents on Wind Stress in the Tropical Indian Ocean

This study examines the effect of surface currents on the bulk algorithm calculation ofwind stress estimated using the scatterometer data during 2007–2020 in the Indian Ocean. In the study region as a whole, the wind stress decreased by 5.4% by including currents in the wind stress equation. The most significant reduction in the wind stress is found along the most energetic regions with strong currents such as Somali Current, Equatorial Jets, and Agulhas retroflection. The highest reduction of 11.5% is observed along the equator where the Equatorial Jets prevail. A sensitivity analysis has been carried out for the study region and for different seasons to assess the relative impact of winds and currents in the estimation of wind stress by changing the winds while keeping the currents constants and vice versa. The inclusion of currents decreased the wind stress (consistent with scatterometer winds) and this decrease is prominent when the currents are stronger. This study showed that the equatorial Indian Ocean is the most sensitive region where the current can impact wind stress estimation. The results showed that uncertainties in the wind stress estimations are quite large at regional levels and hence better representation of wind stress incorporating ocean currents should be considered in the ocean/climatic models for accurate air-sea interaction studies that are not based on remotely sensed winds.

Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data

The estimation of tropical cyclone (TC) intensity using Ku-band scatterometer data is challenging due to rain perturbation and signal saturation in the radar backscatter measurements. In this paper, an alternative approach to directly taking the maximum scatterometer-derived wind speed is proposed to assess the TC intensity. First, the TC center location is identified based on the unique characteristics of wind stress divergence/curl near the TC core. Then the radial extent of 17-m/s winds (i.e., R17) is calculated using the wind field data from the Haiyang-2B (HY-2B) scatterometer (HSCAT). The feasibility of HSCAT wind radii in determining TC intensity is evaluated using the maximum sustained wind speed (MSW) in the China Meteorological Administration best-track database. It shows that the HSCAT R17 value generally better correlates with the best-track MSW than the HSCAT maximum wind speed, therefore indicating the potential of using the HSCAT data to improve the TC nowcasting capabilities.

Fostering the Need of L-Band Radiometer for Extreme Oceanic Wind Research

Ocean surface winds from space-borne radiometers and scatterometers are crucial inputs for numerical models for the operational weather and oceanic sea state forecasts. The rainfall, associated mainly with deep convective clouds, influences the wind retrievals from these sensors during extreme winds conditions (higher than 30 m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{s}^{-1}$ </tex-math></inline-formula> ), as the signal strongly gets affected by the intervening atmosphere, mainly the precipitation. This study emphasizes the importance of the winds from L-band radiometric measurements from Soil Moisture Active Passive (SMAP) satellite compared to the operational Advanced Scatterometer (ASCAT) (C-band) and SCATSAT-1 (Ku-band) scatterometers, National Centers for Environmental Prediction (NCEP) final analysis, and European Centre for Medium-Range Weather Forecasts reanalysis 5 (ERA5) reanalysis wind products. Investigation at global scale suggests that except SMAP, no other selected data are able to capture wind speed more than 56 m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{s}^{-1}$ </tex-math></inline-formula> , and large underestimations are found in presently available scatterometers and reanalysis. These high wind speed errors are more prominent when verified with Joint Typhoon Warning Center (JTWC) best track data for global storms. Moreover, the high winds near storms from scatterometers are generally flagged as rainy pixels and not used for operational applications. These limitations of capturing high winds in scatterometers have been addressed here using histogram corrections approach using SMAP retrieved winds. Moreover, the regional model simulations for a case study suggest that the modified scatterometer winds have larger impact on tropical storm prediction mainly on track and intensity.

Intercalibration of Backscatter Measurements among Ku-Band Scatterometers Onboard the Chinese HY-2 Satellite Constellation

The Chinese HY-2D satellite was launched on 19 May 2021, carrying a Ku-band scatterometer. Together with the operating scatterometers onboard the HY-2B and HY-2C satellites, the HY-2 series scatterometer constellation was built, constituting different satellite orbits and hence opportunity for mutual intercomparison and intercalibration. To achieve intercalibration of backscatter measurements for these scatterometers, this study presents and performs three methods including: (1) direct comparison using collocated measurements, in which the nonlinear calibrations can also be derived; (2) intercalibration over the Amazon rainforest; (3) and the double-difference technique based on backscatter simulations over the global oceans, in which a geophysical model function and numerical weather prediction (NWP) model winds are needed. The results obtained using the three methods are comparable, i.e., the differences among them are within 0.1 dB. The intercalibration results are validated by comparing the HY-2 series scatterometer wind speeds with NWP model wind speeds. The curves of wind speed bias for the HY-2 series scatterometers are quite similar, particularly in wind speeds ranging from 4 to 20 m/s. Based on the well-intercalibrated backscatter measurements, consistent sea surface wind products from HY-2 series scatterometers can be produced, and greatly benefit data applications.

Numerical Weather Prediction Ocean Calibration for the Chinese‐French Oceanography Satellite Wind Scatterometer and Wind Retrieval Evaluation

AbstractThe rotating fan‐beam architecture wind scatterometer Chinese‐French Oceanography Satellite (CSCAT) onboard the Chinese‐French Oceanography Satellite leads to varying geometries and varying wind retrieval performance across the swath. To assess this, the wind vector cells (WVCs) are classified into three groups: outer, sweet, and nadir. The sweet swath WVCs contain the most diverse geometries, which give the best wind retrieval performance, whereas on the opposite the outer swath WVCs have the least diverse geometries, which makes the wind retrieval and ambiguity removal more challenging. NWP Ocean Calibration (NOC) is used to calibrate the radar backscatter prior to the wind inversion. It computes the difference between measured backscatter and simulated backscatter from collocated NWP winds through the geophysical model function. The difference is applied as a correction. An improved NOC method, NOC as a function of incidence angle and azimuth angle (NOCant) is introduced, which takes the orientation of the antenna into account. This method is compared with the widely used NOC as a function of incidence angle only (NOCinc). It shows a better fit with the geophysical model function, except for the outer swath WVCs which have limited geometry diversity. It also corrects the asymmetric wind direction bias distribution across the swath and reduced the nadir swath relative wind direction bias which is caused by the poor azimuth diversity. In conclusion, the rotating fan‐beam architecture of CSCAT leads to unique and varying data characteristics across the swath. Overall, the performance of the proposed NOCant correction is better than NOCinc and improves the wind statistics.

Impacts of initial conditions and model configuration on simulations of polar lows near Svalbard using Polar WRF with 3DVAR

AbstractThe impacts of initial conditions and model configuration on the simulations of polar lows (PLs) near Svalbard, the global “hotspot” for PL activity, were investigated using the Polar Weather Research and Forecasting (Polar WRF or PWRF) model and WRF three‐dimensional data assimilation (3DVAR). The well‐documented PL case presented by Sergeev et al., in 2017 from March 26, 2013 featuring in situ aircraft observations is revisited using PWRF and 3DVAR to identify the most suitable model configuration to simulate PLs. The simulation results using initial conditions from PWRF and 3DVAR cycling runs were compared with those of cold‐start experiments using reanalysis as the initial condition. For cycling runs, the impacts of initial conditions from synoptic observations together with satellite radiances were superior to the assimilation of synoptic data alone. Several additional experiments were undertaken to further refine the PWRF configuration by considering the horizontal resolution, analysis nudging, digital filter initialization, and two boundary‐layer and four microphysics schemes. Based on the chosen configuration of Polar WRF and 3DVAR from the case‐study, the monthly reanalysis mode with 3 hr time window cycling data assimilation and short‐term forecasts using PWRF alone were performed for March 2013 and the PLs that formed over the Nordic Seas were evaluated. Manual identification and verification of PLs were performed using thermal infrared satellite imagery and 10 m scatterometer winds. Overall, nine PLs were identified in addition to the case presented by Sergeev et al., in 2017. Both the case‐study and monthly simulation results show that the high‐resolution initial condition is the most important factor, but a reasonable forecast model configuration can help to improve the simulation performance. Satellite radiance data are very important for producing the high‐resolution initial conditions for Polar WRF to simulate PLs successfully; the best performance was obtained by assimilating both synoptic data and satellite radiances.

Intercalibration of ASCAT Scatterometer Winds from MetOp-A, -B, and -C, for a Stable Climate Data Record

Scatterometers provide very stable ocean vector wind data records. This is because they measure the ratio of backscattered to incident microwave signal over the ocean surface as opposed to an absolute quantity (e.g., emitted microwave signal). They provide an optimal source of observations for building a long ocean vector wind Climate Data Record (CDR). With this objective in mind, observations from different satellite platforms need to be assessed for high absolute accuracy versus a common ground truth and for fine cross-calibration during overlapping periods. Here we describe the methodology for developing a CDR of ocean surface winds from the C-band ASCAT scatterometers onboard MetOp-A, -B, and -C. This methodology is based on the following principles: a common Geophysical Model Function (GMF) and wind algorithm developed at Remote Sensing Systems (RSS) and the use of in situ and satellite winds to cross-calibrate the three scatterometers within the accuracy required for CDRs, about 0.1 m/s at the global monthly scale. Using multiple scatterometers and radiometers for comparison allows for the opportunity to isolate sensors that are drifting or experiencing step-changes as small as 0.05 m/s. We detected and corrected a couple of such changes in the ASCAT-A wind record. The ASCAT winds are now very stable over time and well cross-calibrated with each other. The full C-band wind CDR now covers 2007-present and can be easily extended in the next decade with the launch of the MetOp Second Generation scatterometers.

Calibration of scatterometer wind speed under hurricane conditions

AbstractFour scatterometers, namely: METOP-A, METOP-B, ERS-2 and OCEANSAT-2 were re-calibrated against combined National Data Buoy Center (NDBC) data and aircraft Stepped Frequency Microwave Radiometer (SFMR) data from hurricanes. As a result, continuous calibration relations over the wind speed range 0 to 45 ms-1 were developed. The calibration process uses match-up criteria of 50 km and 30 min for the buoy data. However, due to the strong spatio-temporal wind speed gradients in hurricanes, a method which considers both scatterometer and SFMR data in a storm-centred translating frame of reference is adopted. The results show that although the scatterometer radar cross-section is degraded at high wind speeds, it is still possible to recover wind speed data using the re-calibration process. Data validation between the scatterometers shows that the calibration relations produce consistent results across all scatterometers and reduce the bias and root mean square error compared to previous calibrations. In addition, the results extend the useful range of scatterometer measurements to as high as 45 ms-1.

Evaluation of Chinese Scatterometer Ocean Surface Wind Data: Preliminary Analysis

AbstractThree scatterometers have been launched in China including Haiyang‐2A scatterometer (HY‐2A/SCAT), Haiyang‐2B scatterometer (HY‐2B/SCAT), and China French Oceanography Satellite scatterometer (CFOSCAT). Both of HY‐2A/SCAT and HY‐2B/SCAT are rotating pencil‐beam scatterometers while CFOSCAT is the first rotating fan‐beam scatterometer (RFSCAT) in the world. In this study, we focus on the evaluation of Chinese scatterometer operational wind products from January 2019 to April 2019. Scatterometer wind products are collocated with buoy measurements. Error varieties under different atmospheric stratification conditions are also taken into consideration. The average biases and root mean square errors (RMSEs) between buoy and scatterometer data are basically satisfied with the scatterometer mission requirements (2 m/s and 20°). HY‐2B/SCAT wind products have the best data quality. However, HY‐2A/SCAT wind products have the largest deviations compared with buoy measurements and the wind direction RMSE was about 24.19°. The biases change a lot between different atmospheric stratification conditions. HY‐2A/SCAT winds have abnormal large deviations when wind speeds are higher than 10 m/s while HY‐2B/SCAT and CFOSCAT winds are stable under neutral conditions. In brief, the wind data quality of HY‐2B/SCAT is the best and then is CFOSCAT while HY‐2A/SCAT winds have the largest deviations and are unstable under different atmospheric stratification conditions. Atmospheric stratification impacts should be considered in wind retrieval and marine application.

SCATSAT-1 backscattering coefficient over distinct land surfaces and its dependence on soil moisture and vegetation dynamics

ABSTRACT The objective of this study is to examine the potential of SCATSAT-1 data for estimating the soil moisture and vegetation over the continental regions by evaluating the variabilities in backscattering coefficients measured over different land surface types. The SCATSAT-1 is Ku-band wind Scatterometer, which provides backscattering coefficient measurements over the globe in HH and VV polarization at fixed incidence angles. Variabilities in the backscatter coefficients over different land surfaces, mainly over four different geo-climatological regions of India, are studied based on 3 years of SCATSAT-1 dataset in conjunction with other collocated measurements. The SCATSAT-1 backscattering coefficient provides the quantitative measure of the seasonality over a region due to unique distribution of soil moisture and vegetation characteristics of that region. The variabilities in soil moisture and vegetation in these regions are compared and applicability of change detection method for estimating the soil moisture over these regions has been analysed. Based on regression analysis on SMOS measured soil moisture and SCATSAT-1 measured backscattering coefficient, a relationship has been established for the soil moisture estimation from the SCATSAT-1 backscattering coefficient.

Assessment of SCATSat‐1 Scatterometer Winds on the Upper Ocean Simulations in the North Indian Ocean

AbstractThe performance of a new scatterometer SCATSat‐1 winds with TropFlux on simulating the upper oceanic processes is analyzed over the northern Indian Ocean (IO) using Regional Ocean Modeling System (ROMS). The nutrient, phytoplankton, zooplankton, and detritus (NPZD) ecosystem model are included for studying the postcyclonic responses on biophysical parameters during three cyclones of different intensities (Maarutha, Mora, and Ockhi) in 2017. The SCATSat‐1 (TropFlux) winds showed that skill scores are higher than 0.85 (0.66), and RMSEs are less than 0.48 (1.96) m s−1 with RAMA and OMNI buoy observations. Two SCATSat‐1 wind experiments, one with 1/4° (SS‐E) and other regridded wind to 1° (SSR‐E), are compared with the simulation by TropFlux air‐sea fluxes available at 1° (TF‐E). Seasonal variability of simulated oceanic parameters in SS‐E and SSR‐E showed marginal improvement than TF‐E as compared with observations. However, SSHA variability associated with downwelling Kelvin waves along the Bay of Bengal coast and southward east India coastal current (EICC) during postmonsoon is better simulated in SCATSat‐1 experiments. All experiments showed observed intraseasonal oscillations (30–90 days) with higher variability in thermocline than upper layers at RAMA locations over the equator. On western (eastern) equatorial IO, the signals are stronger during boreal winter (premonsoon) and summer (monsoon). Drop in temperature up to 2.5°C during cyclonic events is reasonably better captured in SS‐E and SSR‐E than TF‐E due to better accuracy in SCATSat‐1 winds. During cyclones, surface chlorophyll attained a peak after 5–10 days of cyclone passage in SCATSat‐1 winds experiments and satellite observations.

Ocean Surface Wind Speed Dependence and Retrieval From Off‐Nadir CFOSAT SWIM Data

AbstractIn this study, we analyzed the ocean surface wind speed dependence of off‐nadir data from the Surface Waves Investigation and Monitoring (SWIM) aboard the Chinese‐French Oceanography Satellite (CFOSAT). When the data were analyzed, the SWIM normalized radar cross section (NRCS) at most incidence angles decreased along the NCEP Global Forecast System wind speed. This trend is consistent with that in a Ku‐band geophysical model function at low incidence angles (KuLMOD2S), although there was a systematic bias between the two. The consistency indicates that the SWIM data quality was normal in terms of wind speed dependence. The bias was recalibrated using a numerical weather prediction‐based ocean calibration method and the wind speeds were retrieved from the recalibrated NRCS data using the KuLMOD2S model. Finally, the retrievals at off‐nadir as well as the wind products at nadir were validated using collocated CFOSAT scatterometer (CSCAT) wind measurements. When the results were validated, the retrievals at 0.5° were consistent with the averaged wind products at nadir and both had a root mean square difference (RMSD) around 1.4 m/s compared to the CSCAT winds. Moreover, the winds retrieved from the SWIM data at most incidence angles were in good agreement with the CSCAT winds,and the RMSD values were within 2.0 m/s for incidence angles less than 7.5°, although the retrieval accuracy was poor at larger incidence angles. These results demonstrate that the SWIM data at incidence angles below 7.5° have an ability to retrieve the wind speed.

Seasonal distribution and variability of surface winds in the Indonesian seas using scatterometer and reanalysis data

AbstractThe distribution and variability of surface winds in the seas and straits in the Maritime Continent, or the Indonesian seas, are investigated using scatterometer wind measurements and reanalysis wind data. This study focuses on the detailed climatology of surface winds in the Indonesian seas and has significant implications for a better understanding of regional climate, meteorological disasters, and offshore wind resource. The monsoon winds predominantly blow over the seas along the routes formed by the coastlines of the large islands and the chains of the small islands. The wind speeds are persistently strong along these routes, and the major direction of the variability in winds is well aligned with these routes. The wind jets are formed in the central part of the routes. The interisland gaps and channels form wind jets of various scales. The Australian winter monsoon is stronger and more persistent than the East Asian winter monsoon in the Indonesian seas. The onset of each monsoon differs by approximately 40 days between the east and west of the Indonesian seas. The amplitudes and spatial extents of diurnally varying winds dominate along the northern coasts of Java Island and the small islands to the east, along the northwest and northeast coasts of Borneo, along the coast of southern Sulawesi Island, and to the southwest of Papua, and vanish along the centre lines of the monsoon routes. Sea areas with a large amplitude of diurnally varying wind are much the same throughout the year. The amplitude of diurnally varying wind has an annual maximum in September in the southern Indonesian seas, possibly in correspondence with the annual maximum of the temperature difference between land and sea.

Evaluating the Detection of Mesoscale Outflow Boundaries Using Scatterometer Winds at Different Spatial Resolutions

Outflow boundaries induced by cold-pools are a key characteristic of convective systems related to microphysical and kinematic processes during the mature stage of their lifecycle. Over the ocean, such kinematic processes are associated with low-level wind modulations that are captured by scatterometers. This study investigates the ability of the Advanced Scatterometer (ASCAT) wind retrievals to detect the outflow boundary associated with an oceanic mesoscale convective system (MCS). Leveraging a new technique to identify cold pools that is based on features that enclose elevated magnitude of the gradient of the wind, termed as ‘Gradient Feature’ (GF), wind retrievals at 50-, 25- and 7-km spatial resolution were utilized to explore how the characteristics of the outflow boundary vary with resolution. Ground-based radar retrievals were also implemented to assess and correct, when possible, the performance of the ASCAT retrievals. The magnitude of the gradient of the wind for the coarser resolution was an order of magnitude smaller (10−4 s−1) than the finer ones (10−3 s−1). An increase in the magnitude of the gradient wind field associated with the outflow boundary was captured by all resolutions and a respective feature was identified by the GF method. The location of the features relative to the distance from the front edge of the MCS decreased with resolution, indicating the importance of the high resolution ASCAT product to capture their extent, as well as additional smaller scale features. The effect of the background wind field on the selection of the final wind field during the ambiguity removal process for the high-resolution product is also discussed.

Twenty-Seven Years of Scatterometer Surface Wind Analysis over Eastern Boundary Upwelling Systems

More than twelve satellite scatterometers have operated since 1992 through the present, providing the main source of surface wind vector observations over global oceans. In this study, these scatterometer winds are used in combination with radiometers and synthetic aperture radars (SAR) for the better determination and characterization of high spatial and temporal resolution of regional surface wind parameters, including wind speed and direction, wind stress components, wind stress curl, and divergence. In this paper, a 27-year-long (1992–2018) 6-h satellite wind analysis with a spatial resolution of 0.125° in latitude and longitude is calculated using spatial structure functions derived from high-resolution SAR data. The main objective is to improve regional winds over three major upwelling regions (the Canary, Benguela, and California regions) through the use of accurate and homogenized wind observations and region-specific spatial and temporal wind variation structure functions derived from buoy and SAR data. The long time series of satellite wind analysis over the California upwelling, where a significant number of moorings is available, are used for assessing the accuracy of the analysis. The latter is close to scatterometer wind retrieval accuracy. This assessment shows that the root mean square difference between collocated 6-h satellite wind analysis and buoys is lower than 1.50 and 1.80 m s−1 for offshore and nearshore locations, respectively. The temporal correlation between buoy and satellite analysis winds exceeds 0.90. The analysis accuracy is lower for 1992–1999 when satellite winds were mostly retrieved from ERS-1 and/or ERS-2 scatterometers. To further assess the improvement brought by this new wind analysis, its data and data from three independent products (ERA5, CMEMS, and CCMP) are compared with purely scatterometer winds over the Canary and Benguela regions. Even though the four products are generally similar, the new satellite analysis shows significant improvements, particularly in the upwelling areas.

Analysis of the High-Latitude Sea Surface Wind Acquisition Ability of Seven Satellite Scatterometers

Seven satellite scatterometers, namely, the C-band MetOp-A/Advanced Scatterometer (ASCAT), MetOp-B/ASCAT, MetOp-C/ASCAT, Ku-band HY-2A/SCAT, HY-2B/SCAT, Chinese-French Oceanography Satellite (CFOSAT)/SCAT, and SCATSAT-1/OceanSat Satellite Scatterometer (OSCAT2), are operating in orbits. These satellites make a high-frequency observation of sea surface winds possible, particularly at high latitudes. This work analyzes the passing time, passing frequency, coverage of these seven scatterometers, and the quality of high-latitude surface wind products. All the scatterometer wind products were reproduced with the same processing procedures, in terms of backscatter calibration, wind retrieval, numerical weather prediction (NWP) wind, and quality control. The target region (74–78 N, 167°–171 W) was chosen to analyze the passing frequency. A spatial grid of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.25^{\circ } \times 0$ </tex-math></inline-formula> .25° in the range of 60° N–88° N was chosen to analyze the spatial coverage of the scatterometers. The results show that more than 40 observation times can be provided daily by all the seven scatterometers; however, there is a 9-h gap between UTC 9:00 and UTC 18:00, suggesting that international cooperation is needed for optimizing the equatorial crossing time in future scatterometer missions, such that an optimal virtual scatterometer constellation can be achieved. The scatterometer winds are compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) winds, and with each other. The comparison results confirmed noticeable wind speed biases due to sea surface temperature (SST) in all Ku-band scatterometer winds with respect to the C-band scatterometer and ERA5 winds.