Ocean Surface Wind Research Articles

Fundamental Climate Data Records of Microwave Brightness Temperatures

An intercalibrated Fundamental Climate Data Record (FCDR) of brightness temperatures (Tb) has been developed using data from a total of 14 research and operational conical-scanning microwave imagers. This dataset provides a consistent 30+ year data record of global observations that is well suited for retrieving estimates of precipitation, total precipitable water, cloud liquid water, ocean surface wind speed, sea ice extent and concentration, snow cover, soil moisture, and land surface emissivity. An initial FCDR was developed for a series of ten Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments on board the Defense Meteorological Satellite Program spacecraft. An updated version of this dataset, including additional NASA and Japanese sensors, has been developed as part of the Global Precipitation Measurement (GPM) mission. The FCDR development efforts involved quality control of the original data, geolocation corrections, calibration corrections to account for cross-track and time-dependent calibration errors, and intercalibration to ensure consistency with the calibration reference. Both the initial SSMI(S) and subsequent GPM Level 1C FCDR datasets are documented, updated in near real-time, and publicly distributed.

Semi-empirical ocean surface model for compact-polarimetry mode SAR of RADARSAT Constellation Mission

A semi-empirical model of the ocean surface is developed for the compact-polarimetry (CP) mode of Synthetic Aperture Radar (SAR) which will be a main product of the RADARSAT Constellation Mission (RCM), scheduled for launch in November 2018. The fundamental mechanism for the semi-empirical model is the interactions between sea surface waves and the radar microwave. Sea surface waves are generated by ocean surface winds and may be modulated by precipitation or oceanic processes, such as surface currents, internal waves (IWs), and surfactants (e.g. oil spill, and sea ice). Model results for normalized radar cross sections (NRCSs) induced by ocean winds are validated against a database we developed. The ocean wind vectors were observed by in situ buoys of the National Data Buoy Center (NDBC); the RCM NRCSs are obtained from a “CP simulator”, using composites of RADARSAT-2 quad-pol SAR images. We simulate the dependencies of the NRCSs on wind speeds and incidence angles, for up-wind (wind direction is 0°) and cross-wind (wind direction is 90°) conditions. And we report the potential abilities and limitations of ocean winds monitoring using the RCM CP mode, as well as suggest that the RV-pol should be suitable for hurricane monitoring in the future. As hurricanes containing high winds are generally associated with heavy rain conditions, we discuss the possible mechanisms for precipitation effects related to the RV- and RH- polarizations by simulating two effects on the ocean surface waves. Moreover, we suggest that the RCM CP mode is better able to monitor the ocean surface currents than the fully polarimetry SAR systems (e.g. RADARSAT-2), because of the associated large swath and the possible continuous images of three RCM satellites.

A combined passive–active microwave retrieval of ocean surface wind speed from SARAL-AltiKa microwave radar altimeter and radiometer

SARAL (Satellite with Argos and AltiKa) is the first satellite radar altimetry mission to fly a Ka-band instrument (AltiKa), which has completed 5 years in orbit on 25th February 2018. Ka-band SARAL-AltiKa suffers larger signal attenuation due to atmospheric water content and also exhibits a different relationship with wind speed than at Ku and C band. Here an augmentation of our earlier geophysical model function (GMF) that was developed based on first principles for wind speed retrieval from SARAL-AltiKa is proposed. This GMF is further augmented here, taking advantage of the co-aligned passive microwave radiometer making measurements of brightness temperature (BT) along with the primary active radar AltiKa measurements of radar backscatter (RB) and significant wave height (SWH) in conjunction with a large matched database of wind speed from Jason-2, respectively. The retrieved wind speed from currently modified algorithm provides an accuracy of 1.34 ms−1 in root mean square deviation with global buoys. Finally, the new algorithm has been used successfully in demonstrating its applicability in capturing regional to global wind field features and compared with other independent satellite measurements like OceanSat scatterometer, Jason-2 altimeter and DMSP-SSM/I radiometer.

Variational Analysis of Simulated Ocean Surface Winds from the Cyclone Global Navigation Satellite System (CYGNSS) and Evaluation Using a Regional OSSE

AbstractA positive impact of adding directional information to observations from the Cyclone Global Navigation Satellite System (CYNGSS) constellation of microsatellites is observed in simulation using a high-resolution nature run of an Atlantic hurricane for a 4-day period. Directional information is added using a two-dimensional variational analysis method (VAM) for near-surface vector winds that blends simulated CYGNSS wind speeds with an a priori background vector wind field at 6-h analysis times. The resulting wind vectors at CYGNSS data locations are more geophysically self-consistent when using high-resolution 6-h forecast backgrounds from a Hurricane Weather Research and Forecast Model (HWRF) control observing system simulation experiment (OSSE) compared to low-resolution 6-h forecasts from an associated Global Forecast System (GFS) model control OSSE. An important contributing factor is the large displacement error in the center of circulation in the GFS background wind fields that produces asymmetric circulations in the associated VAM analyses. Results of a limited OSSE indicate that CYGNSS winds reduce forecast error in hurricane intensity in 0–48-h forecasts compared to using no CYGNSS data. Assimilation of VAM-CYGNSS vector winds reduces maximum wind speed error by 2–5 kt (1 kt = 0.51 m s−1) and reduces minimum central pressure error by 2–5 hPa. The improvement in forecast intensity is notably larger and more consistent than the reduction in track error. The assimilation of VAM-CYGNSS wind vectors constrains analyses of surface wind field structures during OSSE more effectively than wind speeds alone. Because of incomplete sampling and the limitations of the data assimilation system used, CYGNSS scalar winds produce unwanted wind/pressure imbalances and asymmetries more often than the assimilation of VAM-CYGNSS data.

Perspective of a Ku-Ka Dual-Frequency Scatterometer for Simultaneous Wide-Swath Ocean Surface Wind and Current Measurement

Ocean surface wind and current are essential ocean dynamic environment and climate variables, and simultaneous observations at high resolution have attracted considerable interest. The study on surface wind and current will improve our knowledge of energy transfer between the atmosphere and the ocean, as well as the advection of heat, nutrients, and pollutants in the ocean. Since ocean surface wind and current are tightly coupled, we discuss the wind speed and direction errors effects on current, and find that current velocity is sensitive to wind speed and direction errors. Thus, it is necessary to obtain simultaneous wind field information to mitigate the effects of the wind on current retrieval. In this study, we present a Ka-Ku dual-frequency pencil-beam Doppler Scatterometer (DopScat), keeping the Ku-band for wind measurement and the Ka-band for current measurement. We establish an end-to-end simulation model to analyze the performance of the dual-frequency DopScat, and discuss the effects of satellite attitude and velocity determinations on current retrieval. The system parameters were optimized based on the simulation model. The simulation results show that the Kpc of the Ku-band DopScat is better than that of the traditional fan-beam and pencil-beam scatterometer, which is beneficial to improve wind measurement accuracy. In the Ka-band DopScat, the standard deviations (Stds) of current velocity in both along-track and cross-track directions could be smaller than 0.05 m/s, when the wind speed is larger than 5 m/s. When the wind speed is 7 m/s, the current field effective swath is 660 km, accounting for 63% of the DopScat swath, with an accuracy of 0.05 m/s. Our results indicate that the use of a Ku-Ka dual-frequency DopScat could be a feasible method for wide-swath and high-accuracy simultaneous measurements of ocean surface wind and current.

A C-Band Geophysical Model Function for Determining Coastal Wind Speed Using Synthetic Aperture Radar

A new geophysical model function (GMF), called C_SARMOD2, has been developed to relate high-resolution C-band normalized radar cross section (NRCS), acquired in VV polarization over the ocean, to the 10-m height wind speed. A total of 3078 RADARSAT-2 and Sentinel-1A VV-polarized synthetic aperture radar (SAR) images, acquired under different wind speed conditions, were collocated with in situ buoy measurements. The paired dataset was used to derive transfer functions and coefficients of C_SARMOD2, and then to validate the wind speed retrievals. The comparison between SAR-retrieved wind speeds and buoy measurements show almost no bias and a root mean square error of 1.84 m/s. Two representative quad- and dual-polarization SAR images, acquired from coastal regions, are used as case studies to examine C_SARMOD2 performances. The case study and statistical validation results suggest that the proposed C_SARMOD2 has the potential to measure coastal wind speeds at subkilometer resolutions. Although derived from low resolution NRCS measurements, this study also confirms the great robustness of CMOD5.N and recent CMOD7 when applied to SAR data. In addition, it shows that with the new generation of SAR satellite-borne sensors, it is no longer mandatory to rely on scatterometers in order to build a GMF, which will be used for SAR applications. Such an approach is particularly important in view of the upcoming RADARSAT Constellation Mission with new polarization configurations. Moreover, it also opens new perspectives on the derivation of GMFs in HH-polarization. However, these results also suggest that for coastal areas, the increase of the resolution to define the GMF is less important than adding other geophysical parameters to improve wind retrieval performance. This advocates for the necessity of revisiting the methodologies for ocean surface wind speed measurements in coastal areas.

A Study of the HWRF Analysis and Forecast Impact of Realistically Simulated CYGNSS Observations Assimilated as Scalar Wind Speeds and as VAM Wind Vectors

Abstract In preparation for the launch of the NASA Cyclone Global Navigation Satellite System (CYGNSS), a variety of observing system simulation experiments (OSSEs) were conducted to develop, tune, and assess methods of assimilating these novel observations of ocean surface winds. From a highly detailed and realistic hurricane nature run (NR), CYGNSS winds were simulated with error characteristics that are expected to occur in reality. The OSSE system makes use of NOAA’s HWRF Model and GSI data assimilation system in a configuration that was operational in 2012. CYGNSS winds were assimilated as scalar wind speeds and as wind vectors determined by a variational analysis method (VAM). Both forms of wind information had positive impacts on the short-term HWRF forecasts, as shown by key storm and domain metrics. Data assimilation cycle intervals of 1, 3, and 6 h were tested, and the 3-h impacts were consistently best. One-day forecasts from CYGNSS VAM vector winds were the most dynamically consistent with the NR. The OSSEs have a number of limitations; the most noteworthy is that this is a case study, and static background error covariances were used.

Simultaneous ocean surface current and wind vectors retrieval with squinted SAR interferometry: Geophysical inversion and performance assessment

Simultaneous measurements of ocean surface current and wind vectors at the ocean submesoscale (O [1–10 km]) are needed to improve our understanding of upper ocean mixing, air-sea interactions, ocean biophysical processes and large-scale oceanic transports. A new satellite mission concept called SEASTAR aims to do just that. The concept is a Ku-band along-track interferometric Synthetic Aperture Radar (SAR) system with two squinted beams pointing ±45° from broadside and incidence angles around 30°. The paper presents an inversion strategy to retrieve simultaneously ocean surface current and wind vectors and reports on the performance obtained with different wind/current conditions and instrument configurations. Results are based on numerical simulations using a Bayesian approach and existing geophysical model functions (GMFs) of the microwave Normalized Radar Cross Section (NRCS) and Doppler shift.Using the baseline two-look instrument configuration and realistic instrument noise figures (radiometric resolution: kp = 5 and 12%; Δdf = 2 and 5 Hz), the root-mean square errors (RMSE) of the retrieved current and wind vectors are typically better than [0.1 m/s, 10°] for current and [0.5 m/s, 5°] for wind. This inversion setup yields four ambiguous solutions within a current range of ∼1 m/s. The addition of dual polarization (VV, HH) capability helps to discriminate these ambiguities. The retrieval performance depends weakly on geophysical parameters such as wind speed, current velocity or current direction, but is sensitive to wind direction because of its strong effect on current retrieval through the wind-wave induced artifact surface velocity (WASV). Larger retrieval errors are obtained when the wind is aligned with one of the antenna line-of-sight (LoS) directions, although errors remain typically below [0.2 m/s, 25°] for current and [0.5 m/s, 15°] for wind. Improving the retrieval performance regardless of wind direction could be achieved either with lower noise figures on σ0, or with higher incidence angles, or by including an additional third-look direction in azimuth (e.g. to achieve a configuration similar to Metop/ASCAT scatterometers) as per the SEASTAR mission concept submitted to EE10.

Uncertainties in reanalysis surface wind stress and their relationship with observing systems

Atmospheric reanalysis surface wind stress (SWS) estimates have been widely used as surface forcings to drive ocean model simulations and ocean reanalyses, and for understanding climate variability. In this study, we quantify uncertainty in SWS products from six reanalyses, with five from the third generation reanalysis (CFSR, MERRA-1, MERRA-2, JRA-55, ERA-Interim) and one from the first generation reanalysis (R2). Our goals are to (1) characterize uncertainties in monthly mean reanalysis SWS estimates, (2) investigate relationship between the spatial and temporal variations of uncertainties and changes in numbers of observed surface wind data and (3) examine consistency of SWS estimates across different generation of reanalysis products. The six reanalysis SWS estimates broadly agree on the global pattern but differ considerably in magnitude. Compared with TAO SWS estimates, R2 and MERRA-1 significantly underestimate SWS speed over the central Pacific Ocean, while MERRA-2 overestimates easterly wind stress over the north western Pacific. On interannual time scale, high consistency among the reanalyses is located in mid-to-high latitudes, while large uncertainty is found in tropical oceans. All six reanalyses exhibit a similar pattern of wind response to ENSO, but differ significantly in the strength. Compared with TAO estimates, MERRA-2, JRA-55 and ERA-Interim capture the evolution and amplitude of wind anomaly associated with ENSO reasonably well, while CFSR is the outlier which underestimates the peak wind anomaly by more than 35%. Our analysis highlights the importance of observed surface wind data in constraining the reanalysis SWS. It is found that the time variations of the spread among the six reanalyses follows closely to changes in the input of ocean surface winds from satellite scatteometers in all the three tropical oceans. In the tropical Pacific, the accuracy of reanalysis SWS is also linked to the return number of TAO/TRITON winds. The correlation between R2 and the third generation reanalysis products display a clear TAO signature, while the third generation reanalysis products are in a closer agreement with each other.

Modeling Tangential Vector Fields on a Sphere

ABSTRACTPhysical processes that manifest as tangential vector fields on a sphere are common in geophysical and environmental sciences. These naturally occurring vector fields are often subject to physical constraints, such as being curl-free or divergence-free. We start with constructing parametric models for curl-free and divergence-free vector fields that are tangential to the unit sphere through applying the surface gradient or the surface curl operator to a scalar random potential field on the unit sphere. Using the Helmholtz–Hodge decomposition, we then construct a class of simple but flexible parametric models for general tangential vector fields, which are represented as a sum of a curl-free and a divergence-free components. We propose a likelihood-based parameter estimation procedure, and show that fast computation is possible even for large datasets when the observations are on a regular latitude–longitude grid. Characteristics and practical utility of the proposed methodology are illustrated through extensive simulation studies and an application to a dataset of ocean surface wind velocities collected by satellite-based scatterometers. We also compare our model with a bivariate Matérn model and a non-stationary bivariate global model. Supplementary materials for this article are available online.

Measuring Ocean Surface Wind Field Using Shipborne High-Frequency Surface Wave Radar

Extraction of ocean surface wind field from data collected by shipborne high-frequency surface wave radar (HFSWR) is an ongoing challenge because of the inherent directional ambiguity and the effect of complicated platform motion on radar Doppler spectra. Here, a method for extracting the wind direction and speed from the spreading first-order radar Doppler spectra is first presented. First, the mathematical model of the wind direction versus a variable spreading parameter is developed. Moreover, based on the spreading characteristic of the first-order spectra, an approach for simultaneously determining the unambiguous wind direction and the unique spreading parameter with a single receiving antenna is presented. Furthermore, the relationship between the wind speed and the spreading parameter is derived on the basis of the relationship between the drag coefficient and the spreading parameter, and the wind speed can be determined. Therefore, the wind field of ocean area covered by shipborne HFSWR can be measured by sequentially exploiting the presented method, which is more beneficial for shipborne HFSWR because of smaller installation space and less cost. Simulation results and discussions of basic applications show the feasibility of wind field measurement in shipborne HFSWR. Experimental results validate the presented method and evaluate the detection accuracy and distance limit. The range for wind field measurement is up to 120 km, which is the range for which the signal-to-noise ratio typically exceeds about 11 dB in the relevant first-order portions of the backscatter spectra. Comparisons between the radar-measured and forecasting or buoy-measured results show good agreement.

A Preliminary Analysis of Wind Retrieval, Based on GF-3 Wave Mode Data.

This paper presents an analysis of measurements of the normalized radar cross-(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, this experiment verifies the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it is obviously modulated by the wind direction when the wind speed is greater than 8 m/s. Furthermore, the properties of the polarization ratio, denoted PR, are also investigated. The PR is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the retrieved from new PR models as well as is in good agreement with extracted from SAR images directly.

South China Sea Wave Characteristics under Combined Wind Forcing of Typhoon and Winter Monsoon

Since monsoon winds prevail in South China Sea (SCS), SCS is unique for investigating wave characteristics during a typhoon’s passage in conjunction with steady monsoon wind forcing. This study investigated SCS wave characteristics using Wave Watch III, the third-generation wave model with winter typhoon forcing. The model was forced by a high resolution wind field from NASA’s Cross Calibrated Multi Platform (CCMP) ocean surface winds combined with the tropical cyclone wind model. The Wave Watch III model was evaluated using Jason-2 altimetry observations during the period of Typhoon Durian (2006).

Soil Moisture Sensing Using Spaceborne GNSS Reflections: Comparison of CYGNSS Reflectivity to SMAP Soil Moisture

AbstractThis paper quantifies the relationship between forward scattered L‐band Global Navigation Satellite System (GNSS) signals, recorded by the Cyclone Global Navigation Satellite System (CYGNSS) constellation and Soil Moisture Active Passive (SMAP) soil moisture (SM). Although designed for tropical ocean surface wind sensing, the CYGNSS receivers also record GNSS reflections over land. The CYGNSS observations of reflection power are compared to SMAP SM between March 2017 and February 2018. A strong, positive linear relationship exists between changes in CYGNSS reflectivity and changes in SMAP SM, but not between the absolute magnitudes of the two observations. The sensitivity of CYGNSS reflectivity to SM varies spatially and can be used to convert reflectivity to estimates of SM. The unbiased root‐mean‐square difference between daily averaged CYGNSS‐derived SM and SMAP SM is 0.045 cm3/cm3 and is similarly low between CYGNSS and in situ SM. These results show that CYGNSS, and future GNSS reflection missions, could provide global SM observations.

Estimating Ocean Vector Winds and Currents Using a Ka-Band Pencil-Beam Doppler Scatterometer

Ocean surface currents and winds are tightly coupled essential climate variables, and, given their short time scales, observing them at the same time and resolution is of great interest. DopplerScatt is an airborne Ka-band scatterometer that has been developed under NASA’s Instrument Incubator Program (IIP) to provide a proof of concept of the feasability of measuring these variables using pencil-beam scanning Doppler scatterometry. In the first half of this paper, we present the Doppler scatterometer measurement and processing principles, paying particular attention to deriving a complete measurement error budget. Although Doppler radars have been used for the estimation of surface currents, pencil-beam Doppler Scatterometry offers challenges and opportunities that require separate treatment. The calibration of the Doppler measurement to remove platform and instrument biases has been a traditional challenge for Doppler systems, and we introduce several new techniques to mitigate these errors when conical scanning is used. The use of Ka-band for airborne Doppler scatterometry measurements is also new, and, in the second half of the paper, we examine the phenomenology of the mapping from radar cross section and radial velocity measurements to winds and surface currents. To this end, we present new Ka-band Geophysical Model Functions (GMFs) for winds and surface currents obtained from multiple airborne campaigns. We find that the wind Ka-band GMF exhibits similar dependence on wind speed as that for Ku-band scatterometers, such as QuikSCAT, albeit with much greater upwind-crosswind modulation. The surface current GMF at Ka-band is significantly different from that at C-band, and, above 4.5 m/s has a weak dependence on wind speed, although still dependent on wind direction. We examine the effects of Bragg-wave modulation by long waves through a Modululation Transfer Function (MTF), and show that the observed surface current dependence on winds is consistent with past Ka-band MTF observations. Finally, we provide a preliminary validation of our geophysical retrievals, which will be expanded in subsequent publications. Our results indicate that Ka-band Doppler scatterometry could be a feasible method for wide-swath simultaneous measurements of winds and currents from space.

Observation and prediction of flotsam trajectories in the California Current System based on surface drift of RAFOS floats

Surface drift of eighty-nine undrogued RAFOS floats in the California Current System (CCS) has been studied to describe patterns of flotsam drift, its seasonal variability and predictability limitations. The floats were launched in the California Undercurrent during 1992–2010 and were tracked by the ARGOS system when they surfaced at the end of their subsurface missions. The duration of surface trajectories varied from as short as 11 to as long as 280 days. The surface drift of these floats was typically equatorward in the California Current. However, some floats moved poleward into the Subpolar Gyre, and others drifted westward into the North Equatorial Current.Usually, observations of surface currents use drifters which are coupled to the surface layer by drogues located at 15 m depth. While drogued observations are useful for studies of circulation of the upper layer of the ocean, a more typical operational problem involves trying to find flotsam that has fallen off the deck of a ship or to predict the path of an abandoned vessel. To better understand the behavior of these surface drifting objects, observations of the surface drifts of RAFOS floats in the California Current system were used to compare the floats’ motions to wind-induced drift and to evaluate the drift prediction by three ocean models: Ocean Surface Current Simulator (OSCURS), Global Navy Coastal Model (gNCOM) and Hybrid Coordinate Ocean Model (HYCOM).Cross-Calibrated Multi-Platform Ocean Surface Wind Vector L3.0 First-Look Analysis wind data were used to analyze the surface drift of the RAFOS floats. The best correlation between float drift speed and wind speed was observed during summer and fall months, when the wind regime over the Northeast Pacific is dominated by the North Pacific High. The predominant winds associated with this regime are steady and contribute to the surface drift in the same direction as the large-scale geostrophic component of the California Current.Evaluation of the drift prediction by three ocean models was conducted by comparing observed drifter trajectories with model-simulated trajectories at 7-day time scales. The model-simulated trajectories were initially collocated with RAFOS positions and restarted every 15 days. The OSCURS model was the only one of three analyzed models which allowed for tuning based on the surface RAFOS trajectories. Two main parameters, Wind Angle Deflection (WAD) and Geostrophic Current Factor (GCF), were adjusted to minimize the separation between observed and modeled trajectories. At shorter time scales, from weeks to several months, the tuned OSCURS model outperformed gNCOM and HYCOM models in reproducing the observed surface drift. For seasonal and longer time scales, both gNCOM and HYCOM can reproduce the seasonal variability, flow direction, and eddy-like structures in the California Current system, which may be useful for long-term forecasts of the Northeast Pacific circulation.

Integrated kinetic energy of Atlantic tropical cyclones in a global ocean surface wind analysis

The integrated kinetic energy (IKE) of a tropical cyclone (TC), a volume integration of the surface winds around the centre of the TC, is computed from a comprehensive surface wind (National Aeronautics and Space Administration’s (NASA) cross‐calibrated multi‐platform [CCMP]) analysis available over the global oceans to verify against IKE from wind radii estimates of extended best‐track data maintained by NOAA for the North Atlantic TCs. It is shown that CCMP surface wind analysis severely underestimates IKE largely from not resolving hurricane force winds for majority of the Atlantic TCs, under sampling short‐lived and small‐sized TCs. The seasonal cycle of the North Atlantic TC IKE also verifies poorly in the CCMP analysis. In this article we introduce proxy IKE (PIKE) based on the kinetic energy of the winds at the radius of the last closed isobar (ROCI), which shows promise for a wide range of TC sizes including the smaller‐sized TCs unresolved in the CCMP data set.

Validation of wind speed retrieval from RISAT-1 SAR images of the North Indian Ocean

ABSTRACTAn algorithm has been developed to retrieve ocean surface wind speed from Synthetic Aperture Radar (SAR) on-board Radar Imaging Satellite-1 (RISAT-1). The retrieved wind speed is subsequently validated using observations from Advanced Scatterometers (on-board Metop-A, Metop-B) for the period from July 2012 to September 2016. The quality of the retrieved wind speed was assessed using observations from offshore moored buoys in the Bay of Bengal and Arabian Sea. It has been observed that the RISAT-1 derived wind speed, retrieved using three Geophysical Model Functions (GMFs) viz., CMOD5.N, CMOD5 and CMOD_IFR2 are negatively biased relative to ASCAT as well as Buoy. The biases with ASCAT are 0.38 (0.98) ms−1, 0.96 (1.24) ms−1 and 1.31 (1.55) ms−1 respectively for the coastal (offshore) region. The Root Mean Square Difference (RMSD) between RISAT-1 and ASCAT are 1.58 (1.78), 1.8 (1.85) and 1.96 (1.99) in m s−1 respectively for coastal (offshore) waters, which is well within the acceptable limits. Thus it is found that the quality of the wind speed retrieved using CMOD5.N GMF is better than other GMFs. The high resolution wind data available from RISAT-1 SAR opens new pathways for assessing wind energy potential along the Indian coast.

Assimilation of SMOS L‐band wind speeds: impact on Met Office global NWP and tropical cyclone predictions

A new generation of L‐band sensors, such as the European Space Agency (ESA)'s Soil Moisture Ocean Salinity (SMOS) mission, have the capability to provide information on the ocean surface wind speed under high wind and rain conditions. In this study we evaluate the use of SMOS wind speeds within Met Office numerical weather prediction (NWP). Observation minus model background (O−B) departure statistics are used to investigate SMOS error characteristics, quality flags, and develop a quality‐control method. Observation errors and spatial correlation distances are estimated using a statistical method. Observing system experiments are performed to diagnose the impact of SMOS on NWP forecasts and analyses, including tropical cyclone (TC) predictions.The quality of SMOS retrievals appears reduced in the presence of sea ice, strong river plumes, and radio‐frequency interference (RFI) contamination. SMOS wind retrievals have reduced sensitivity at low–moderate winds speeds. Above 15 m s−1, SMOS winds tend to be faster than the model and have higher O−B variance compared to scatterometer winds from ASCAT. Above 30 m s−1, root‐mean‐square errors from SMOS are smaller than ASCAT. The impact of SMOS on TC predictions is sensitive to the use of the Met Office TC Central Pressure Initialisation Scheme (TCCPIS) which is confirmed to have a large, beneficial impact on intensity predictions. The assimilation of SMOS results in a small increase in TC intensity leading to a reduction in pressure/wind errors in the analysis and short‐range forecasts, but cannot replicate the impact from the TCCPIS. The spatial resolution of SMOS is a clear limitation for analysing TC structure. In the case of Hurricane Kilo, the analysed and short‐range forecast central pressures are closer to best‐track when the storm radius is large and the eye is resolved. The challenge is to extract the useful information on intensity whilst preserving storm structure.

Ocean Wind and Current Retrievals Based on Satellite SAR Measurements in Conjunction with Buoy and HF Radar Data

A total of 168 fully polarimetric synthetic-aperture radar (SAR) images are selected together with the buoy measurements of ocean surface wind fields and high-frequency radar measurements of ocean surface currents. Our objective is to investigate the effect of the ocean currents on the retrieved SAR ocean surface wind fields. The results show that, compared to SAR wind fields that are retrieved without taking into account the ocean currents, the accuracy of the winds obtained when ocean currents are taken into account is increased by 0.2–0.3 m/s; the accuracy of the wind direction is improved by 3 – 4 ° . Based on these results, a semi-empirical formula for the errors in the winds and the ocean currents is derived. Verification is achieved by analysis of 52 SAR images, buoy measurements of the corresponding ocean surface winds, and high-frequency radar measurements of ocean currents. Results of the comparisons between data obtained by the semi-empirical formula and data measured by the high-frequency radar show that the root-mean-square error in the ocean current speed is 12.32 cm/s and the error in the current direction is 6.32°.