SeaWinds Scatterometer Research Articles

Offshore Wind Resource Assessment of Thailand Using Remote Sensing Technique

This paper presents the evaluation of the offshore wind resource of Thailand (the Gulf of Thailand and the Andaman Sea) using remote sensing technique. The wind speed at height of 10 m above mean sea level (A.M.S.L.) was measured using SeaWinds Scatterometer on QuickSCAT by NASA. The QuickSCAT satellite images in 1999-2009 with resolution of 1ox1o was interpreted and validated using the measured wind speed provided by the ship observation, buoy data and numerical weather prediction models. The wind speed was interpolated for 1 km resolution enhancement and extrapolated to the height of 50 m A.M.S.L.. The monthly and annual mean wind speed maps were presented in order to show the spatial and temporal variation of offshore wind energy potential. Results showed that QuickSCAT satellite images interpretation gave lower bias in the rage of wind speed of 3-18 m/s, however, the bias was high for wind speed more than 20 m/s. It found that offshore mean wind speed at height of 50 m A.M.S.L. was in the range of 3.0-6.0 m/s where the middle part of Thai offshore had the highest potential with the wind speed in the rage of 7.0-10.0 m/s. The offshore wind speed had high potential during June until August due to the influence of southwest monsoon.

Transformative Urban Changes of Beijing in the Decade of the 2000s

The rapid economic growth, the exodus from rural to urban areas, and the associated extreme urban development that occurred in China in the decade of the 2000s have severely impacted the environment in Beijing, its vicinity, and beyond. This article presents an innovative approach for assessing mega-urban changes and their impact on the environment based on the use of decadal QuikSCAT (QSCAT) satellite data, acquired globally by the SeaWinds scatterometer over that period. The Dense Sampling Method (DSM) is applied to QSCAT data to obtain reliable annual infrastructure-based urban observations at a posting of ~1 km. The DSM-QSCAT data, along with different DSM-based change indices, were used to delineate the extent of the Beijing infrastructure-based urban area in each year between 2000 and 2009, and assess its development over time, enabling a physical quantification of its urbanization which reflects the implementation of various development policies during the same time period. Eventually, as a proxy for the impact of Beijing urbanization on the environment, the decadal trend of its infrastructure-based urbanization is compared with that of the corresponding tropospheric nitrogen dioxide (NO2) column densities as observed from the Global Ozone Monitoring Experiment (GOME) instrument aboard the second European Remote Sensing satellite (ERS-2) between 2000 and 2002, and from the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY aboard of the ESA’s ENVIronmental SATellite (SCIAMACHY /ENVISAT) between 2003 and 2009. Results reveal a threefold increase of the yearly tropospheric NO2 column density within the Beijing infrastructure-based urban area extent in 2009, which had quadrupled since 2000.

Building up or spreading out? Typologies of urban growth across 478 cities of 1 million+

Urban form in both two- (2D) and three-dimensions (3D) has significant impacts on local and global environments. Here we developed the largest global dataset characterizing 2D and 3D urban growth for 478 cities with populations of one million or larger. Using remote sensing data from the SeaWinds scatterometer for 2001 and 2009, and the Global Human Settlement Layer for 2000 and 2014, we applied a cluster analysis and found five urban growth typologies: stabilized, outward, mature upward, budding outward, upward and outward. Budding outward is the dominant typology worldwide, per the largest total area. Cities characterized by upward and outward growth are few in number and concentrated primarily in China and South Korea, where there has been a large increase in high-rises during the study period. With the exception of East Asia, cities within a geographic region exhibit remarkably similar patterns of urban growth. Our results show that every city exhibits multiple urban growth typologies concurrently. Thus, while it is possible to describe a city by its dominant urban growth typology, a more accurate and comprehensive characterization would include some combination of the five typologies. The implications of the results for urban sustainability are multi-fold. First, the results suggest that there is considerable opportunity to shape future patterns of urbanization, given that most of the new urban growth is nascent and low magnitude outward expansion. Second, the clear geographic patterns and wide variations in the physical form of urban growth, within country and city, suggest that markets, national and subnational policies, including the absence of, can shape how cities grow. Third, the presence of different typologies within each city suggests the need for differentiated strategies for different parts of a single city. Finally, the new urban forms revealed in this analysis provide a first glimpse into the carbon lock-in of recently constructed energy-demanding infrastructure of urban settlements.

Further adjustment of the Defense Meteorological Satellite Program—Operational Linescan System using radar data

In the past, the Defense Meteorological Satellite Program—Operational Linescan System (DSMP/OLS) data have been successfully adjusted based on the presence of vegetation in each pixel. We propose a further adjustment based on radar data obtained by the SeaWinds scatterometer. It is shown that the adjustment results in substantial accuracy gains, measured as increased correlation with the more accurate Visible Infrared Imaging Radiometer Suite data as well as with the existing instances of radiance calibrated DSMP/OLS data. The proposed adjustment is easy to implement. The improvement of the proposed method is particularly significant in arid regions where vegetation is relatively sparse.

Mechanistic Processes Controlling Persistent Changes of Forest Canopy Structure After 2005 Amazon Drought

AbstractThe long‐term impact of Amazonian drought on canopy structure has been observed in ground and remote sensing measurements. However, it is still unclear whether it is caused by biotic (e.g., plant structure damage) or environmental (e.g., water deficiency) factors. We used the Community Land Model version 4.5 (CLM4.5) and radar backscatter observations from SeaWinds Scatterometer on board QuikSCAT (QSCAT) satellite to investigate the relative role of biotic and environmental factors in controlling the forest canopy disturbance and recovery processes after the 2005 Amazonian drought. We validated the CLM4.5 simulation of the drought impact and the recovery of leaf carbon (C) pool, an indicator of canopy structure, over southwestern Amazonia with QSCAT backscatter observations, which are sensitive to canopy structure change. We found that the leaf C pool simulated by CLM4.5 recovered to the 2000–2009 mean level (343 g C m−2) in 3 years after a sharp decrease in 2005, consistent with the QSCAT observed slow recovery. Through sensitivity experiments, we found that the slow C recovery was primarily due to biotic factors represented by the canopy damage and reduction of plant C pools. The recovery of soil water and the coupling between water and C pools, which is an environmental factor, only contributes ~24% to the leaf C recovery. The results showed (1) the strength of scatterometer backscatter measurements in capturing canopy damage over tropical forests and in validating C cycle models and (2) the biotic factors play the dominant role in regulating the drought induced disturbance and persistent canopy changes in CLM4.5.

The RapidScat Ocean Winds Scatterometer: A Radar System Engineering Perspective

The NASA International Space Station (ISS)-RapidScat scatterometer operated on board the ISS from October 2014 into August 2016. It was developed using a combination of new subsystems and spare SeaWinds scatterometer engineering model subsystems to interface with the ISS. Using commercial (nonflight-qualified) parts in the new assemblies, developing RapidScat required a relatively small budget and short time schedule (just over two years). This article describes RapidScat's development from the perspective of radar system engineering, particularly in relation to performance requirements and testing.

Comparison of SeaWinds Backscatter Imaging Algorithms.

This paper compares the performance and tradeoffs of various backscatter imaging algorithms for the SeaWinds scatterometer when multiple passes over a target are available. Reconstruction methods are compared with conventional gridding algorithms. In particular, the performance and tradeoffs in conventional 'drop in the bucket' (DIB) gridding at the intrinsic sensor resolution are compared to high-spatial-resolution imaging algorithms such as fine-resolution DIB and the scatterometer image reconstruction (SIR) that generate enhanced-resolution backscatter images. Various options for each algorithm are explored, including considering both linear and dB computation. The effects of sampling density and reconstruction quality versus time are explored. Both simulated and actual data results are considered. The results demonstrate the effectiveness of high-resolution reconstruction using SIR as well as its limitations and the limitations of DIB and fDIB.

Wind changes above warm Agulhas Current eddies

Abstract. Sea surface temperature (SST) estimated from the Advanced Microwave Scanning Radiometer E onboard the Aqua satellite and altimetry-derived sea level anomalies are used south of the Agulhas Current to identify warm-core mesoscale eddies presenting a distinct SST perturbation greater than to 1 °C to the surrounding ocean. The analysis of twice daily instantaneous charts of equivalent stability-neutral wind speed estimates from the SeaWinds scatterometer onboard the QuikScat satellite collocated with SST for six identified eddies shows stronger wind speed above the warm eddies than the surrounding water in all wind directions, if averaged over the lifespan of the eddies, as was found in previous studies. However, only half of the cases showed higher wind speeds above the eddies at the instantaneous scale; 20 % of cases had incomplete data due to partial global coverage by the scatterometer for one path. For cases where the wind is stronger above warm eddies, there is no relationship between the increase in surface wind speed and the SST perturbation, but we do find a linear relationship between the decrease in wind speed from the centre to the border of the eddy downstream and the SST perturbation. SST perturbations range from 1 to 6 °C for a mean eddy SST of 15.9 °C and mean SST perturbation of 2.65 °C. The diameter of the eddies range from 100 to 250 km. Mean background wind speed is about 12 m s−1 (mostly southwesterly to northwesterly) and ranging mainly from 4 to 16 m s−1. The mean wind increase is about 15 %, which corresponds to 1.8 m s−1. A wind speed increase of 4 to 7 m s−1 above warm eddies is not uncommon. Cases where the wind did not increase above the eddies or did not decrease downstream had higher wind speeds and occurred during a cold front associated with intense cyclonic low-pressure systems, suggesting certain synoptic conditions need to be met to allow for the development of wind speed anomalies over warm-core ocean eddies. In many cases, change in wind speed above eddies was masked by a large-scale synoptic wind speed deceleration/acceleration affecting parts of the eddies.

Estimation of the OSCAT Spatial Response Function Using Island Targets

Originally designed for wind velocity estimation over the ocean, scatterometers have been applied to weather forecasting, global climatological studies, and monitoring of large-scale human interaction on the planet. Launched in September of 2009, the Oceansat-2 Ku-band scatterometer (OSCAT) is an excellent candidate for continuing the data time series begun with QuikSCAT, which was the SeaWinds scatterometer flown on the QuikSCAT mission 1999-2009. Some processing algorithms require knowledge of the spatial response function (SRF) of the scatterometer. With limited knowledge of OSCAT implementation, and thus its SRF, a procedure is developed for estimating the SRF. The estimation procedure uses scatterometer measurements over islands to invert the radar equation. A mathematical model is developed that reduces the solution to rank-reduced least-squares estimation. The geographic sampling region is discussed, and a simulation is performed to verify the efficacy of the method, while also providing guidelines for island choice and the number of singular values used in rank reduction. The utility of OSCAT SRF estimates is demonstrated through the construction of an enhanced-resolution radar backscatter image over the Amazon rainforest.

Use of scatterometer data in groundwater vulnerability assessment

Lombardy in Italy has been selected as a case study to evaluate the capability of the QuikSCAT - Dense Sampling Method (QSCAT-DSM) data in delineating urban extent, estimating rate of urban changes, and assessing aquifer vulnerability, in particular to investigate the relationship between land-use changes and groundwater contamination.QSCAT-DSM data represent an innovative approach to delineate urban and interurban areas with satellite scatterometer data. Radar backscatter acquired by the SeaWinds scatterometer aboard the QSCAT satellite together with the DSM are used to identify and map surface features at a posting scale of about 1 km².Through the spatial statistical methods Weight of Evidence (WofE), both urban changes given by QSCAT-DSM data and population changes in the decade of the 2000’s have been correlated to nitrate concentration trend in groundwater in the same time period.Both analyses based on urban change and on population change lead to the same result: urban nitrate sources in Lombardy increase the level of nitrate concentration in groundwater, indicating a degradation of the water quality. Moreover, QSCAT-DSM data proved to be a reliable tool for evaluating urban changes continuously without a temporal or spatial gap, and to be a strategic variable allowing the assessment of groundwater vulnerability consistently throughout the decadal time scale.

A Fieldwise Retrieval Approach to the Noise Versus Resolution Tradeoff in Wind Scatterometry

This paper approaches the noise versus resolution tradeoff in wind scatterometry from a fieldwise retrieval perspective. Theoretical considerations are discussed, and a practical implementation is developed and applied to the SeaWinds scatterometer. The approach is compared with conventional approaches, as well as numerical weather predictions and buoys. The new method incorporates knowledge of the wind spectrum to reduce the impact of components of the wind signal that are expected to be noisy while enabling reconstruction of fine-scale features that are distinguishable from noise.

The Gaussian Statistical Predictability of Wind Speeds

Abstract The statistical predictability of wind speed using Gaussian predictors, relative to the predictability of orthogonal vector wind components, is considered. With the assumption that the vector wind components are Gaussian, analytic expressions for the correlation-based wind speed prediction skill are obtained in terms of the prediction skills of the vector wind components and their statistical moments. It is shown thatat least one of the vector wind components is generally better predicted than the wind speed (often much more so);wind speed predictions constructed from the predictions of vector wind components are more skillful than direct wind speed predictions; andthe linear predictability of wind speed (relative to that of the vector wind components) decreases as the variability in the vector wind increases relative to the mean. These idealized model results are shown to be broadly consistent with linear predictive skills assessed using observed sea surface wind from the SeaWinds scatterometer. Biases in the model predictions are shown to be related to the degree to which vector wind variations are non-Gaussian.

Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence

It is unclear to what extent seasonal water stress impacts on plant productivity over Amazonia. Using new Greenhouse gases Observing SATellite (GOSAT) satellite measurements of sun-induced chlorophyll fluorescence, we show that midday fluorescence varies with water availability, both of which decrease in the dry season over Amazonian regions with substantial dry season length, suggesting a parallel decrease in gross primary production (GPP). Using additional SeaWinds Scatterometer onboard QuikSCAT satellite measurements of canopy water content, we found a concomitant decrease in daily storage of canopy water content within branches and leaves during the dry season, supporting our conclusion. A large part (r(2) = 0.75) of the variance in observed monthly midday fluorescence from GOSAT is explained by water stress over moderately stressed evergreen forests over Amazonia, which is reproduced by model simulations that include a full physiological representation of photosynthesis and fluorescence. The strong relationship between GOSAT and model fluorescence (r(2) = 0.79) was obtained using a fixed leaf area index, indicating that GPP changes are more related to environmental conditions than chlorophyll contents. When the dry season extended to drought in 2010 over Amazonia, midday basin-wide GPP was reduced by 15 per cent compared with 2009.

Assessment of the SeaWinds scatterometer for vegetation phenology monitoring across China

Vegetation phenology tracks plants' lifecycle events, revealing the response of vegetation to global climate changes. Changes in vegetation phenology also influence fluxes of carbon, water, and energy at local and global scales. In this study, we analysed a time series of Ku-band radar backscatter measurements from the SeaWinds scatterometer on board the Quick Scatterometer (QuickSCAT) to examine canopy phenology from 2003 to 2005 across China. The thaw season SeaWinds backscatter and Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) time series were significantly correlated in 20 of the 22 sites (p < 0.05). A weighted curve-fitting method was applied to detect the start of season and end of season from both data sets. The SeaWinds scatterometer generally detected earlier timing of spring leaf-out and later fall senescence than the MODIS LAI data sets. The SeaWinds backscatter detected phenological metrics in 75.85% of mainland China. Similar spatial patterns were observed from the SeaWinds backscatter and MODIS LAI time series; however, the average standard deviation of the scatterometer-detected metrics was lower than that of MODIS LAI products. Overall, the phenological information from the SeaWinds scatterometer could provide an alternative view on the growth dynamics of land-surface vegetation.

Improvement in air–sea flux estimates derived from satellite observations

A new method is developed to estimate daily turbulent air–sea fluxes over the global ocean on a 0.25° grid. The required surface wind speed (w 10) and specific air humidity (q 10) at 10 m height are both estimated from remotely sensed measurements. w 10 is obtained from the SeaWinds scatterometer on board the QuikSCAT satellite. A new empirical model relating brightness temperatures (T b) from the Special Sensor Microwave Imager (SSM/I) and q 10 is developed. It is an extension of the author's previous q 10 model. In addition to T b, the empirical model includes sea surface temperature (SST) and air–sea temperature difference data. The calibration of the new empirical q 10 model utilizes q 10 from the latest version of the National Oceanography Centre air–sea interaction gridded data set (NOCS2.0). Compared with mooring data, the new satellite q 10 exhibits better statistical results than previous estimates. For instance, the bias, the root mean square (RMS), and the correlation coefficient values estimated from comparisons between satellite and moorings in the northeast Atlantic and the Mediterranean Sea are –0.04 g kg−1, 0.87 g kg−1, and 0.95, respectively. The new satellite q 10 is used in combination with the newly reprocessed QuikSCAT V3, the latest version of SST analyses provided by the National Climatic Data Center (NCDC), and 10 m air temperature estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses (ERA-Interim), to determine three daily gridded turbulent quantities at 0.25° spatial resolution: surface wind stress, latent heat flux (LHF), and sensible heat flux (SHF). Validation of the resulting fields is performed through a comprehensive comparison with daily, in situ values of LHF and SHF from buoys. In the northeast Atlantic basin, the satellite-derived daily LHF has bias, RMS, and correlation of 5 W m−2, 27 W m−2, and 0.89, respectively. For SHF, the statistical parameters are –2 W m−2, 10 W m−2, and 0.94, respectively. At global scale, the new satellite LHF and SHF are compared to NOCS2.0 daily estimates. Both daily fluxes exhibit similar spatial and seasonal variability. The main departures are found at latitudes south of 40° S, where satellite latent and sensible heat fluxes are generally larger.

Trends in Antarctic Peninsula surface melting conditions from observations and regional climate modeling

Multidecadal meteorological station records and microwave backscatter time‐series from the SeaWinds scatterometer onboard QuikSCAT (QSCAT) were used to calculate temporal and spatial trends in surface melting conditions on the Antarctic Peninsula (AP). Four of six long‐term station records showed strongly positive and statistically significant trends in duration of melting conditions, including a 95% increase in the average annual positive degree day sum (PDD) at Faraday/Vernadsky, since 1948. A validated, threshold‐based melt detection method was employed to derive detailed melt season onset, extent, and duration climatologies on the AP from enhanced resolution QSCAT data during 1999–2009. Austral summer melt on the AP was linked to regional‐ and synoptic‐scale atmospheric variability by respectively correlating melt season onset and extent with November near‐surface air temperatures and the October–January averaged index of the Southern Hemisphere Annular Mode (SAM). The spatial pattern, magnitude, and interannual variability of AP melt from observations was closely reproduced by simulations of the regional model RACMO2. Local discrepancies between observations and model simulations were likely a result of the QSCAT response to, and RACMO2 treatment of, ponded surface water, and the relatively crude representation of coastal climate in the 27 km RACMO2 grid.

Antarctic surface melting dynamics: Enhanced perspectives from radar scatterometer data

Antarctic ice sheet surface melting can regionally influence ice shelf stability, mass balance, and glacier dynamics, in addition to modulating near‐surface physical and chemical properties over wide areas. Here, we investigate variability in surface melting from 1999 to 2009 using radar backscatter time series from the SeaWinds scatterometer aboard the QuikSCAT satellite. These daily, continent‐wide observations are explored in concert with in situ meteorological records to validate a threshold‐based melt detection method. Radar backscatter decreases during melting are significantly correlated with in situ positive degree‐days as well as meltwater production determined from energy balance modeling at Neumayer Station, East Antarctica. These results support the use of scatterometer data as a diagnostic indicator of melt intensity (i.e., the relative liquid water production during melting). Greater spatial and temporal melting detected relative to previous passive microwave‐based studies is attributed to a higher sensitivity of the scatterometer instrument. Continental melt intensity variability can be explained in part by the dynamics of the Southern Annular Mode and the Southern Oscillation Index, and extreme melting events across the Ross Ice Shelf region may be associated with El Niño conditions. Furthermore, we find that the Antarctic Peninsula accounts for only 20% of Antarctic melt extent but greater than 50% of the total Antarctic melt intensity. Over most areas, annual melt duration and intensity are proportional. However, regional and localized distinctions exist where the melt intensity metric provides greater insight into melting dynamics than previously obtainable with other remote sensing techniques.

Prediction of Tropical Cyclogenesis Using Scatterometer Data

In the present work, a new technique based on the data mining approach has been discussed for the prediction of tropical cyclogenesis using the ocean wind vectors derived from the sea-winds scatterometer on QuikScat satellite. The technique is based on similarity of given wind pattern with wind vector signatures of developing systems, available from the past observations. A database has been formed in this work using the QuikScat-observed vector wind patterns associated with the early stages of tropical cyclones that developed in the North Indian basin during the years 2000-2008. The prediction of possibility of cyclogenesis, in a given scene, is determined by matching it with all the archived scenes in a database using vector block matching algorithm. The system is predicted as developing, if its matching index exceeds the predetermined threshold value (0.5). The prediction of cyclo genesis can be made 24-96 h prior to its classification as a tropical storm by the Joint Typhoon Warning Centre. The probability of detection of the technique is determined using the equivalent of the Jackknife approach in the database as 0.93. The algorithm is tested with a continuous wind data of years 2007-2009 for active cyclone months (excluding the scenes archived in a database). All the 14 tropical disturbances that developed into tropical storms during the test period were predicted using the discussed method, and two false alarms were found.

A Novel Ku-Band Radiometer/Scatterometer Approach for Improved Oceanic Wind Vector Measurements

This paper presents a conceptual conical-scanning radiometer/scatterometer (RadScat) instrument design for the purpose of improving satellite ocean vector wind retrievals under rain-free conditions. This technique combines the wind vector signature in the passive linearly polarized ocean brightness temperatures with the anisotropic signature of multiazimuthal radar cross-sectional measurements to retrieve oceanic surface wind vectors. The performance of the RadScat is evaluated using a Monte Carlo simulation based on actual measurements from the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer onboard the Advanced Earth Observing Satellite II. The results demonstrate significant improvements in wind vector retrievals, particularly in the near-subtrack swath, where the performance of conical-scanning scatterometers degrades.

Inferring Greenland melt and refreeze severity from SeaWinds scatterometer data

Two SeaWinds radar scatterometers operated in tandem for 9 months in 2003, enabling resolution of the diurnal cycle in Greenland. This dataset provides unprecedented temporal resolution for Ku-band scattering observations of snow and ice melt conditions. As a step towards improved radar-based melt intensity estimation, a simple Markov melt–thaw model is developed to estimate melt and refreeze indices. The melt indices model is evaluated with the aid of a simple geophysical–electromagnetic model and validated by comparing tandem SeaWinds observations against automated weather station data. The new approach is used to analyse the melt conditions over the Greenland ice-sheet in 2003. The strengths and limitations of the approach are considered.