Background,aim,and scope Yardang is a kind of typical wind-eroded landform in arid zones both on Earth and other planets.Their geomorphic process records the surface changes and climate,which may play a vital role in ...Background,aim,and scope Yardang is a kind of typical wind-eroded landform in arid zones both on Earth and other planets.Their geomorphic process records the surface changes and climate,which may play a vital role in exploring the coupled landform-atmosphere system in arid zones.Recently,significant progresses have been made in this research field,and a review is still absent,which is the aim of the paper.Materials and methods Previous studies on the distribution,composition,morphology,and climatic driving force of yardang landform were reviewed.Results Earth yardang’s three evolutionary models were generalized:morphology evolution model,altitude evolution model and climate driven evolution model.Extraterrestrial yardang and its evolution are also summarized:the morphology is dominated by long ridges on Venus and Titan,and three yardang evolution hypotheses and an indirect dating method based on stratigraphic contact have been studied on Mars.Discussion In this study,firstly,the definition and morphology of yardang were described to define its characteristics.Secondly,we argue that yardang evolution has two dimensions:short-term variation and longterm variation.In the short-term variation,the morphological evolution of yardang on earth can be divided into four stages:embryonic stage,juvenile stage,mature stage,and demise stage.In the long-term variation,the evolution of yardang on earth is climate-driven,i.e.,it is controlled by atmospheric circulation changes during glacial-interglacial periods.Thirdly,yardang research on extraterrestrial bodies was also summarized:yardang has been found on Mars,Venus,and Titan,and the research focus by far are on geomorphology only.Conclusions(1)Yardang landform is an erosion landform with alternating ridges and troughs,with main form of whale back shape and fluctuations in the range of aspect ratios;(2)the short-term variation of yardang is manifested in its morphological evolution and height change,while the long-term variation is climate-driven;(3)based on Earth yardang,extraterrestrial yardang research has been carried out on Mars,Venus,and Titan.Recommendations and perspectives We then proposed that:(1)yardang formation ages,due to the erosion characteristics,are difficult to constraint;(2)the wind erosion capacity in the yardang areas might have been severely underestimated,making it essential to re-evaluate the previous paleoclimate reconstruction in the closed basins with limited chronological data;(3)yardang evolution is driven by climate change,but the coupling relationship between the yardang geomorphy and the air circulation is still unclear.Finally,future research directions:(1)more chronological data are needed,as well as the wind erosion capacity for yardang initiation and development;(2)the co-evolution of mid-low latitude landforms involved in yardang long-term variation and its relationship with global atmospheric circulation.展开更多
WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this pape...WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.展开更多
The AMSR2 microwave radiometer is the main payload of the GCOM-W1 satellite,launched by the Japan Aerospace Exploration Agency in 2012. Based on the pre-launch information extraction algorithm,the AMSR2 enables remote...The AMSR2 microwave radiometer is the main payload of the GCOM-W1 satellite,launched by the Japan Aerospace Exploration Agency in 2012. Based on the pre-launch information extraction algorithm,the AMSR2 enables remote monitoring of geophysical parameters such as sea surface temperature,wind speed,water vapor,and liquid cloud water content. However,rain alters the properties of atmospheric scattering and absorption,which contaminates the brightness temperatures measured by the microwave radiometer. Therefore,it is difficult to retrieve AMSR2-derived sea surface wind speeds under rainfall conditions. Based on microwave radiative transfer theory,and using AMSR2 L1 brightness temperature data obtained in August 2012 and NCEP reanalysis data,we studied the sensitivity of AMSR2 brightness temperatures to rain and wind speed,from which a channel combination of brightness temperature was established that is insensitive to rainfall,but sensitive to wind speed. Using brightness temperatures obtained with the proposed channel combination as input parameters,in conjunction with HRD wind field data,and adopting multiple linear regression and BP neural network methods,we established an algorithm for hurricane wind speed retrieval under rainfall conditions. The results showed that the standard deviation and relative error of retrievals,obtained using the multiple linear regression algorithm,were 3.1 m/s and 13%,respectively. However,the standard deviation and relative error of retrievals obtained using the BP neural network algorithm were better(2.1 m/s and 8%,respectively). Thus,the results of this paper preliminarily verified the feasibility of using microwave radiometers to extract sea surface wind speeds under rainfall conditions.展开更多
To understand the provenance and evolution of eolian input in the last 1.95 Ma in the Parece Vela Basin in the eastern Philippine Sea, the clay mineral assemblage of a gravity core PV090510 from the basin was investig...To understand the provenance and evolution of eolian input in the last 1.95 Ma in the Parece Vela Basin in the eastern Philippine Sea, the clay mineral assemblage of a gravity core PV090510 from the basin was investigated using paleogeomagnetic dating and X-ray diffraction. The assemblage of the core mainly consisted of smectite （-46%） and illite （-40%）, with some chlorite （-10%） and kaolinite （-4%）. Analysis of the provenance of these minerals suggested that smectite was mainly derived from volcanic rocks of the Mariana Arc, while illite, chlorite, and kaolinite were mainly transported as eolian dust by the East Asian monsoon from central Asia. We used the ratio of （illite＋chlorite＋kaolinite）/smectite as a proxy for Asian eolian input to the Parece Vela Basin since 1.95 Ma. This ratio followed glacial and interglacial cycles and was consistent with the intensity of the East Asian monsoon and aridity of central Asia since 1.95 Ma. The changes of the ratio reflected three different stages of the East Asian monsoon and provenance climate.展开更多
The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing ...The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing efforts to improve the wind speed measurements, a bias dependence on wave state persists in all wind algorithms. On the basis of recent evidence that short waves are essentially modulated by local winds and much less affected by wave state, we proposed a physics-based approach to retrieve the wind speed from the dual-frequency difference in terms of the mean square slope of short waves. A collocated dataset of coincident altimeter/buoy measurements were used to develop and validate the approach. Validation against buoy measurements indicates that the approach is almost unbiased and has an overall root mean square error of 1.24 m s-1, which is 5.3% lower than the single-parameter algorithm in operational use(Witter and Chelton, 1991) and 2.4% lower than another dual-frequency approach(Chen et al., 2002). Furthermore, the results indicate that the new approach significantly improves the wave-dependent bias compared to the single-parameter algorithm. The capacity of altimeter to retrieve sea surface wind speed appears to be limited for the case of winds below 3 m s-1. The validity of the approach at high winds needs to be further examined in the future study.展开更多
To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions （GMFs） have been widel...To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions （GMFs） have been widely applied for wind field retrieval from SAR images. Among them CMOD4 has a good performance under low and moderate wind conditions. Although CMOD5 is developed recently with a more fundamental basis, it has ambiguity of wind speed and a shape gradient of normalized radar cross section under low wind speed condition. This study proposes a method of wind field retrieval from SAR image by com-bining CMOD5 and CMOD4 Five VV-polarisation RADARSAT2 SAR images are implemented for validation and the retrieval re-suits by a combination method （CMOD5 and CMOD4） together with CMOD4 GMF are compared with QuikSCAT wind data. The root-mean-square error （RMSE） of wind speed is 0.75 m s-1 with correlation coefficient 0.84 using the combination method and the RMSE of wind speed is 1.01 m s-1 with correlation coefficient 0.72 using CMOD4 GMF alone for those cases. The proposed method can be applied to SAR image for avoiding the internal defect in CMOD5 under low wind speed condition.展开更多
文摘Background,aim,and scope Yardang is a kind of typical wind-eroded landform in arid zones both on Earth and other planets.Their geomorphic process records the surface changes and climate,which may play a vital role in exploring the coupled landform-atmosphere system in arid zones.Recently,significant progresses have been made in this research field,and a review is still absent,which is the aim of the paper.Materials and methods Previous studies on the distribution,composition,morphology,and climatic driving force of yardang landform were reviewed.Results Earth yardang’s three evolutionary models were generalized:morphology evolution model,altitude evolution model and climate driven evolution model.Extraterrestrial yardang and its evolution are also summarized:the morphology is dominated by long ridges on Venus and Titan,and three yardang evolution hypotheses and an indirect dating method based on stratigraphic contact have been studied on Mars.Discussion In this study,firstly,the definition and morphology of yardang were described to define its characteristics.Secondly,we argue that yardang evolution has two dimensions:short-term variation and longterm variation.In the short-term variation,the morphological evolution of yardang on earth can be divided into four stages:embryonic stage,juvenile stage,mature stage,and demise stage.In the long-term variation,the evolution of yardang on earth is climate-driven,i.e.,it is controlled by atmospheric circulation changes during glacial-interglacial periods.Thirdly,yardang research on extraterrestrial bodies was also summarized:yardang has been found on Mars,Venus,and Titan,and the research focus by far are on geomorphology only.Conclusions(1)Yardang landform is an erosion landform with alternating ridges and troughs,with main form of whale back shape and fluctuations in the range of aspect ratios;(2)the short-term variation of yardang is manifested in its morphological evolution and height change,while the long-term variation is climate-driven;(3)based on Earth yardang,extraterrestrial yardang research has been carried out on Mars,Venus,and Titan.Recommendations and perspectives We then proposed that:(1)yardang formation ages,due to the erosion characteristics,are difficult to constraint;(2)the wind erosion capacity in the yardang areas might have been severely underestimated,making it essential to re-evaluate the previous paleoclimate reconstruction in the closed basins with limited chronological data;(3)yardang evolution is driven by climate change,but the coupling relationship between the yardang geomorphy and the air circulation is still unclear.Finally,future research directions:(1)more chronological data are needed,as well as the wind erosion capacity for yardang initiation and development;(2)the co-evolution of mid-low latitude landforms involved in yardang long-term variation and its relationship with global atmospheric circulation.
文摘WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2013AA09A505)
文摘The AMSR2 microwave radiometer is the main payload of the GCOM-W1 satellite,launched by the Japan Aerospace Exploration Agency in 2012. Based on the pre-launch information extraction algorithm,the AMSR2 enables remote monitoring of geophysical parameters such as sea surface temperature,wind speed,water vapor,and liquid cloud water content. However,rain alters the properties of atmospheric scattering and absorption,which contaminates the brightness temperatures measured by the microwave radiometer. Therefore,it is difficult to retrieve AMSR2-derived sea surface wind speeds under rainfall conditions. Based on microwave radiative transfer theory,and using AMSR2 L1 brightness temperature data obtained in August 2012 and NCEP reanalysis data,we studied the sensitivity of AMSR2 brightness temperatures to rain and wind speed,from which a channel combination of brightness temperature was established that is insensitive to rainfall,but sensitive to wind speed. Using brightness temperatures obtained with the proposed channel combination as input parameters,in conjunction with HRD wind field data,and adopting multiple linear regression and BP neural network methods,we established an algorithm for hurricane wind speed retrieval under rainfall conditions. The results showed that the standard deviation and relative error of retrievals,obtained using the multiple linear regression algorithm,were 3.1 m/s and 13%,respectively. However,the standard deviation and relative error of retrievals obtained using the BP neural network algorithm were better(2.1 m/s and 8%,respectively). Thus,the results of this paper preliminarily verified the feasibility of using microwave radiometers to extract sea surface wind speeds under rainfall conditions.
基金Supported by the National Basic Research Program of China(973 Program)(No.2007CB411703)the National Natural Science Foundation of China(No.40976026)
文摘To understand the provenance and evolution of eolian input in the last 1.95 Ma in the Parece Vela Basin in the eastern Philippine Sea, the clay mineral assemblage of a gravity core PV090510 from the basin was investigated using paleogeomagnetic dating and X-ray diffraction. The assemblage of the core mainly consisted of smectite （-46%） and illite （-40%）, with some chlorite （-10%） and kaolinite （-4%）. Analysis of the provenance of these minerals suggested that smectite was mainly derived from volcanic rocks of the Mariana Arc, while illite, chlorite, and kaolinite were mainly transported as eolian dust by the East Asian monsoon from central Asia. We used the ratio of （illite＋chlorite＋kaolinite）/smectite as a proxy for Asian eolian input to the Parece Vela Basin since 1.95 Ma. This ratio followed glacial and interglacial cycles and was consistent with the intensity of the East Asian monsoon and aridity of central Asia since 1.95 Ma. The changes of the ratio reflected three different stages of the East Asian monsoon and provenance climate.
基金supported by the National High Technology Research and Development Program of China (2013 AA09A505)
文摘The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing efforts to improve the wind speed measurements, a bias dependence on wave state persists in all wind algorithms. On the basis of recent evidence that short waves are essentially modulated by local winds and much less affected by wave state, we proposed a physics-based approach to retrieve the wind speed from the dual-frequency difference in terms of the mean square slope of short waves. A collocated dataset of coincident altimeter/buoy measurements were used to develop and validate the approach. Validation against buoy measurements indicates that the approach is almost unbiased and has an overall root mean square error of 1.24 m s-1, which is 5.3% lower than the single-parameter algorithm in operational use(Witter and Chelton, 1991) and 2.4% lower than another dual-frequency approach(Chen et al., 2002). Furthermore, the results indicate that the new approach significantly improves the wave-dependent bias compared to the single-parameter algorithm. The capacity of altimeter to retrieve sea surface wind speed appears to be limited for the case of winds below 3 m s-1. The validity of the approach at high winds needs to be further examined in the future study.
基金supported by the National Natural Science Foundation of China (Nos.41376010 and 40830959)the Start-up Foundation of Zhejiang Ocean University (No.21105011913)
文摘To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions （GMFs） have been widely applied for wind field retrieval from SAR images. Among them CMOD4 has a good performance under low and moderate wind conditions. Although CMOD5 is developed recently with a more fundamental basis, it has ambiguity of wind speed and a shape gradient of normalized radar cross section under low wind speed condition. This study proposes a method of wind field retrieval from SAR image by com-bining CMOD5 and CMOD4 Five VV-polarisation RADARSAT2 SAR images are implemented for validation and the retrieval re-suits by a combination method （CMOD5 and CMOD4） together with CMOD4 GMF are compared with QuikSCAT wind data. The root-mean-square error （RMSE） of wind speed is 0.75 m s-1 with correlation coefficient 0.84 using the combination method and the RMSE of wind speed is 1.01 m s-1 with correlation coefficient 0.72 using CMOD4 GMF alone for those cases. The proposed method can be applied to SAR image for avoiding the internal defect in CMOD5 under low wind speed condition.
