10 research outputs found

    Usporedba ALADIN i IFS Modela brzine vjetra preko Jadrana

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    The wind output from atmospheric models is instrumental in forcing the oceanic models. Here we consider the wind output from the ALADIN and IFS models and compare it with the results of scatterometer and altimeter estimates of wind speed over the Adriatic Sea, as well as with the field data from 18 meteorological stations and a gas rig platform. A five-year period from 2008 to 2012 is considered in the comparison. Our principal conclusion is that, overall, both atmospheric models, when compared to the altimeter data, give very similar statistical results, with a scatter index of 0.33 and 0.35 for IFS and ALADIN respectively. More specifically, the ALADIN appears to be better in the Northern Adriatic whereas the IFS seems superior in the Southern Adriatic. A possible explanation of this difference could be that the higher spatial resolution of ALADIN is crucial in resolving the bora wind impact over the Northern Adriatic.Vjetar dobiven atmosferskim modelima je instrumentalan u prisiljavanju oceanskog modela. U ovom radu razmotrit će se vjetra dobiven Aladin i IFS modelima te će se usporediti s rezultatima skat -erometrijske i altimetrijske procjene brzine vjetra iznad Jadranskog mora, kao i s 18 meteoroloških postaja i plinske platforme u razdoblju 2008-2012. Glavni zaključak je da oba atmosferska modela, u usporedbi s podacima altimetrije, daju vrlo slične statističke rezultate, s indeksom raspršenja 0,33 za IFS i 0,35 za ALADIN. Čini se da ALADIN daje bolje rezultate za sjeverni Jadran, a IFS za južni Jadran. Moguće objašnjenje te razlike može biti veća prostorna rezolucija ALADIN-a koja je presudna u rješavanju utjecaja bure na sjevernom Jadranu

    Offshore Wind Resources Assessment from Multiple Satellite Data and WRF Modeling over South China Sea

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    Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. This study outlines a methodology for combining multiple ocean satellite winds and winds from WRF simulations in order to acquire the accurate reconstructed offshore winds which can be used for offshore wind resource assessment. First, wind speeds retrieved from Synthetic Aperture Radar (SAR) and Scatterometer ASCAT images were validated against in situ measurements from seven coastal meteorological stations in South China Sea (SCS). The wind roses from the Navy Operational Global Atmospheric Prediction System (NOGAPS) and ASCAT agree well with these observations from the corresponding in situ measurements. The statistical results comparing in situ wind speed and SAR-based (ASCAT-based) wind speed for the whole co-located samples show a standard deviation (SD) of 2.09 m/s (1.83 m/s) and correlation coefficient of R 0.75 (0.80). When the offshore winds (i.e., winds directed from land to sea) are excluded, the comparison results for wind speeds show an improvement of SD and R, indicating that the satellite data are more credible over the open ocean. Meanwhile, the validation of satellite winds against the same co-located mast observations shows a satisfactory level of accuracy which was similar for SAR and ASCAT winds. These satellite winds are then assimilated into the Weather Research and Forecasting (WRF) Model by WRF Data Assimilation (WRFDA) system. Finally, the wind resource statistics at 100 m height based on the reconstructed winds have been achieved over the study area, which fully combines the offshore wind information from multiple satellite data and numerical model. The findings presented here may be useful in future wind resource assessment based on satellite data

    Wind speed retrieval from the Gaofen-3 synthetic aperture radar for VV- and HH-polarization using a re-tuned algorithm

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    In this study, a re-tuned algorithm based on the geophysical model function (GMF) C-SARMOD2 is proposed to retrieve wind speed from Synthetic Aperture Radar (SAR) imagery collected by the Chinese C-band Gaofen-3 (GF-3) SAR. More than 10,000 Vertical-Vertical (VV) and Horizontal-Horizontal (HH) polarization GF-3 images acquired in quad-polarization stripmap (QPS) and wave (WV) modes have been collected during the last three years, in which wind patterns are observed over open seas with incidence angles ranging from 18° to 52°. These images, collocated with wind vectors from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis at 0.125° resolution, are used to re-tune the C-SARMOD2 algorithm to specialize it for the GF-3 SAR (CSARMOD-GF). In particular, the CSARMOD-GF performs differently from the C-SARMOD2 at low-to-moderate incidence angles smaller than about 34°. Comparisons with wind speed data from the Advanced Scatterometer (ASCAT), Chinese Haiyang-2B (HY-2B) and buoys from the National Data Buoy Center (NDBC) show that the root-mean-square error (RMSE) of the retrieved wind speed is approximately 1.8 m/s. Additionally, the CSARMOD-GF algorithm outperforms three state-of-the-art methods – C-SARMOD, C-SARMOD2, and CMOD7 – that, when applied to GF-3 SAR imagery, generating a RMSE of approximately 2.0–2.4 m/s

     Ocean Remote Sensing with Synthetic Aperture Radar

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    The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

    한반도 주변해 연안 해양현상에 대한 합성개구레이더 활용

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    학위논문 (박사)-- 서울대학교 대학원 : 과학교육과 (지구과학전공), 2016. 8. 박경애.In this thesis, the applicability of synthetic aperture radar (SAR) to interpretation of oceanic phenomena at the coastal regions around Korea peninsula is presented. For that, the spatial and temporal variations of SAR-derived coastal wind fields and evolution of disastrous oil spills on SAR images were analyzed in relation to atmospheric and oceanic environmental factors using in-situ measurement and satellite observations. The SAR wind fields retrieved from the east coast of Korea in August 2007 during the upwelling period revealed a spatial distinction between near and offshore regions. Low wind speeds were associated with cold water regions with dominant coastal upwelling. Time series of in-situ measurements of both wind speed and water temperature indicated that the upwelling was induced by the wind field. SAR data at the present upwelling region showed a relatively large backscattering attenuation to SST ratio of 1.2 dB ºC−1 compared the known dependence of the water viscosity on the radar backscattering. In addition, wind speed magnitude showed a positive correlation with the difference between SST and air temperature. It implies that the low wind field from SAR was mainly induced by changes in atmospheric stability due to air-sea temperature differences. Oil spills at the Hebei Spirit accident off the coast of Korea in the Yellow Sea were identified using SAR data and their evolution was investigated. To quantitatively analyze the spatial and temporal variations of oil spills, objective detection methods based on adaptive thresholding and a neural network were applied. Prior to applying, the results from two methods were compared for verification. It showed good agreement enough for the estimation of the extent of oil patches and their trajectories, with the exception of negligible errors at the boundaries. Quantitative analyses presented that the detected oil slicks moved southeastward, corresponding to the prevailing wind and tidal currents, and gradually dissipated during the spill, except for an extraordinary rapid decrease in onshore regions at the initial stage. It was identified that the initial dissipation of the spilt oil was induced by strong tidal mixing in the tidal front zone from comparison with the tidal mixing index. The spatial and temporal variations of the oil slicks confirmed the influence of atmospheric and oceanic environmental factors. The overall horizontal migration of the oil spills detected from consecutive SAR images was mainly driven by Ekman drift during the winter monsoon rather than the tidal residual current.Chapter 1. Introduction 1 1.1. Study Background 1 1.2. Objectives of the Thesis 14 Chapter 2. Data Description 15 2.1. SAR Data 15 2.2. Other Satellite Data 21 2.2.1. Wind Data 21 2.2.2. Sea Surface Temperature Data 21 2.2.3. Ocean Color Data 22 2.3. Reanalysis Data 23 2.4. In-situ Measurements 23 2.5. Land Masking Data 26 2.6. Tidal Current Data 28 Chapter 3. Methods 29 3.1. SAR Wind Retrieval 29 3.2. Noise Reduction of ScanSAR Images 37 3.3. Conversion of Wind Speed to Neutral Wind 41 3.4. Estimation of Index of the Tidal Front 43 3.5. Estimation of Ekman Drift and Tidal Residual Current 45 3.6. Feature Detection Methods 46 3.6.1. Adaptive Threshold Method 47 3.6.2. Bimodal Histogram Method 50 3.6.3. Neural Network Method 54 Chapter 4. Coastal Wind Fields and Upwelling Response 58 4.1. Variations of Wind Fields during Coastal Upwelling 58 4.2. Stability Effect on Wind Speed 65 4.3. Biological Impact of Upwelling 70 Chapter 5. Characteristics of Objective Feature Detection 74 5.1. Comparison of Thresholding Methods 74 5.2. Oil Spill of the Hebei Spirit by Thresholding Method 81 5.3. Oil Spill by the Hebei Spirit by Neural Network Method 85 5.4. Differences by Detection Methods 88 Chapter 6. Evolution of Oil Spill at the Coastal Region 90 6.1. Temporal Evolution of the Hebei Spirit Oil Spill 90 6.2. Effect of Artificial Factor on the Evolution 96 Chapter 7. Effect of Environmental Factors on the Oil Spill 98 7.1. Effect of Tidal Mixing 98 7.2. Effect of Wind and Tidal Current 103 Chapter 8. Summary and Conclusion 110 Reference 114 Abstract in Korean 142Docto

    On the correlation between GNSS-R reflectivity and L-band microwave radiometry

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    This work compares microwave radiometry and global navigation satellite systems-reflectometry (GNSS-R) observations using data gathered from airborne flights conducted for three different soil moisture conditions. Two different regions are analyzed, a crops region and a grassland region. For the crops region, the correlation with the I/2 (first Stokes parameter divided by two) was between 0.74 and 0.8 for large incidence angle reflectivity data (30°-50°), while it was between 0.51 and 0.61 for the grassland region and the same incidence angle conditions. For the crops region, the correlation with the I/2 was between 0.64 and 0.69 for lower incidence angle reflectivity data (<;30°), while it was between 0.41 and 0.6 for the grassland region. This indicates that for large incidence angles the coherent scattering mechanism is dominant, while the lower incidence angles are more affected by incoherent scattering. Also a relationship between the reflectivity and the polarization index (PI) is observed. The PI has been used to remove surface roughness effects, but due to its dependence on the incidence angle only the large incidence angle observations were useful. The difference in ground resolution between microwave radiometry and GNSS-R and their strong correlation suggests that they might be combined to improve the spatial resolution of microwave radiometry measurements in terms of brightness temperature and consequently soil moisture retrievals.This work was supported in part by the Spanish Ministry of Science and Innovation, “AROSA-Advanced Radio Ocultations and Scatterometry Applications using GNSS and other opportunity signals,” under Grant AYA2011-29183-C02-01/ESP and “AGORA: Tecnicas Avanzadas en Teledetección Aplicada Usando Señales GNSS y Otras Señales de Oportunidad,” under Grant ESP2015-70014-C2-1-R (MINECO/FEDER), in part by the Monash University Faculty of Engineering 2013 Seed Grant, and in part by the Advanced Remote Sensing Ground-Truth Demo and Test Facilities and Terrestrial Environmental Observatories funded by the German Helmholtz-Association. The work of A. A.-Arroyo was supported by the Fulbright Commission in Spain through a Fulbright grant.Peer ReviewedPostprint (author's final draft
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