P. O. Box 5111
P. O. Box 5111
Yu Y.,CAS Institute of Remote Sensing |
Yu Y.,State Key Laboratory of Remote Sensing Science |
Wang L.,CAS Institute of Remote Sensing |
Li Z.,CAS Institute of Remote Sensing |
And 2 more authors.
Frontiers of Earth Science | Year: 2013
Geostrophic current comprises a large portion of the ocean current, which plays an important role in global climate change. Based on classic oceanography, geostrophic current can be derived from pressure gradient. Assuming water density to be constant, we can estimate geostrophic current from Absolute Dynamic Topography (ADT). In this paper, we use ADT data obtained from multi-satellite altimeters to extract sea surface tilts along-track at crossover points. The calculated tilts along these two tracks can be converted into orthogonal directions and are used to estimate geostrophic current. In northwest Pacific, computed geostrophic current velocities are evaluated with Argos data. In total, 771 pairs of temporally and spatially consistent Argos measurements along with estimated geostrophic velocity datasets are used for validation. In this study, the effect of different cut-off wavelengths of the low pass filter applied to ADT is discussed. Our results show that a cut-off wavelength of 75 km is the most suitable choice for the study area. The estimated geostrophic velocity and the Argos measurement are in good agreement with each other, with a correlation coefficient of 0.867 for zonal component, and 0.734 for meridional one. Furthermore, an empirical relationship between the estimated geostrophic velocity and Argos measurement is derived, providing us a favorable and convenient approach to estimate sea surface flow velocity from the geostrophic velocity derived from altimeter data. The experimental application of the derived method on Kuroshio reveals reasonable results compared with previous studies. © 2013 Higher Education Press and Springer-Verlag Berlin Heidelberg.
Lv X.,Ocean University of China |
Li X.,College Park |
Yang X.,CAS Institute of Remote Sensing |
Pichel W.,National Oceanic and Atmospheric Administration |
And 2 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2013
Tropical cyclones generate powerful wind, torrential rainfall, high waves and damaging storm surge that affect coastal communities. Tracking and predicting cyclones is one of the most important tasks for meteorologists. In this study, we compare the hurricane/typhoon eye locations at the sea level observed by spaceborne Synthetic Aperture Radar (SAR) and its counterpart at the cloud level by the simultaneous infrared imagery. The vertical eye tilt at these two heights is compared with 850-200hPa vertical wind shear from SHIPS data. Five case studies show that the displacements vary from 10 to 22 km, with tilt direction oriented from downshear-left to downshear to downshear-right. These results are consistent with former studies. © 2013 IEEE.
Qin B.,CAS Institute of Remote Sensing |
Zhou X.,CAS Institute of Remote Sensing |
Zhang H.,CAS Institute of Remote Sensing |
Yang X.,P. O. Box 5111 |
And 3 more authors.
Acta Oceanologica Sinica | Year: 2014
Rain effect and lack of in situ validation data are two main causes of tropical cyclone wind retrieval errors. The National Oceanic and Atmospheric Administration's Climate Prediction Center Morphing technique (CMORPH) rain rate is introduced to a match-up dataset and then put into a rain correction model to remove rain effects on "Jason-1" normalized radar cross section (NRCS); Hurricane Research Division (HRD) wind speed, which integrates all available surface weather observations, is used to substitute in situ data for establishing this relationship with "Jason-1" NRCS. Then, an improved "Jason-1" wind retrieval algorithm under tropical cyclone conditions is proposed. Seven tropical cyclones from 2003 to 2010 are studied to validate the new algorithm. The experimental results indicate that the standard deviation of this algorithm at C-band and Ku-band is 1.99 and 2.75 m/s respectively, which is better than the existing algorithms. In addition, the C-band algorithm is more suitable for sea surface wind retrieval than Ku-band under tropical cyclone conditions. © 2014 The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg.
Zhou X.,P. O. Box 5111 |
Zhou X.,CAS Institute of Remote Sensing Applications |
Yang X.,CAS Institute of Remote Sensing Applications |
Hao Y.,P. O. Box 5111 |
And 3 more authors.
Chinese Journal of Oceanology and Limnology | Year: 2013
Rain is one of the main sources of error in dual-frequency altimeter Jason-1 wind measurement. In this study, a new radar altimeter backscatter model is proposed and validated to eliminate rain effects. The model takes into account attenuation, volume backscattering, and sea surface perturbation by raindrops under rain conditions. A match-up dataset is built to evaluate rain effects, in combination with the Jason-1 normalized radar cross section, precipitation radar data from the Tropical Rainfall Measuring Mission, and sea surface wind reanalysis data from the European Centre for Medium-Range Weather Forecasts. The results show that rain-induced surface perturbation backscatter increases with rain rate at Ku-band, but their correlation at C-band is poor. In addition, rain surface perturbation and attenuation have major effects onradar altimeter wind measurements. Finally, a rain correction model for Jason-1 winds is developed and validation results prove its ability to reduce rain-induced inaccuracies in wind retrievals. © 2013 Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag Berlin Heidelberg.