Global bundle adjustment with variable orientation point distance for precise mars express orbit reconstruction

The photogrammetric bundle adjustment of line scanner image data requires a precise description of the time-dependent image orientation. For this task exterior orientation parameters of discrete points are used to model position and viewing direction of a camera trajectory via polynomials. This paper investigates the influence of the distance between these orientation points on the quality of trajectory modeling. A new method adapts the distance along the trajectory to the available image information. Compared to a constant distance as used previously, a better reconstruction of the exterior orientation is possible, especially when image quality changes within a strip. In our research we use image strips of the High Resolution Stereo Camera (HRSC), taken to map the Martian surface. Several experiments on the global image data set have been carried out to investigate how the bundle adjustment improves the image orientation, if the new method is employed. For evaluation the forward intersection errors of 3D points derived from HRSC images, as well as their remaining height differences to the MOLA DTM are used. In 13.5 % (515 of 3,828) of the image strips, taken during this ongoing mission over the last 12 years, high frequency image distortions were found. Bundle adjustment with a constant orientation point distance was able to reconstruct the orbit in 239 (46.4 %) cases. A variable orientation point distance increased this number to 507 (98.6 %).German Federal Ministry for Economic Affairs and Energy (BMWi)German Aerospace Center (DLR)/50 QM 130

Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats.

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., Andre, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbeoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouet, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourles, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P., Rannou, J., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P., Velez-Belchi, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S., & Park, H. Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats. Frontiers in Marine Science, 7, (2020): 700, doi:10.3389/fmars.2020.00700.In the past two decades, the Argo Program has collected, processed, and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1,000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed.AW, SR, and other scientists at the University of Washington (UW) were supported by the US Argo Program through the NOAA Grant NA15OAR4320063 to the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) at the UW. SW and other scientists at the Woods Hole Oceanographic Institution (WHOI) were supported by the US Argo Program through the NOAA Grant NA19OAR4320074 (CINAR/WHOI Argo). The Scripps Institution of Oceanography's role in Argo was supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). Euro-Argo scientists were supported by the Monitoring the Oceans and Climate Change with Argo (MOCCA) project, under the Grant Agreement EASME/EMFF/2015/1.2.1.1/SI2.709624 for the European Commission

Classification of case-II waters using hyperspectral (HICO) data over North Indian Ocean

State of the art Ocean color algorithms are proven for retrieving the ocean constituents (chlorophyll-a, CDOM and Suspended Sediments) in case-I waters. However, these algorithms could not perform well at case-II waters because of the optical complexity. Hyperspectral data is found to be promising to classify the case-II waters. The aim of this study is to propose the spectral bands for future Ocean color sensors to classify the case-II waters. Study has been performed with Rrs’s of HICO at estuaries of the river Indus and GBM of North Indian Ocean. Appropriate field samples are not available to validate and propose empirical models to retrieve concentrations. The sensor HICO is not currently operational to plan validation exercise. Aqua MODIS data at case-I and Case-II waters are used as complementary to in- situ. Analysis of Spectral reflectance curves suggests the band ratios of Rrs 484 nm and Rrs 581 nm, Rrs 490 nm and Rrs 426 nm to classify the Chlorophyll –a and CDOM respectively. Rrs 610 nm gives the best scope for suspended sediment retrieval. The work suggests the need for ocean color sensors with central wavelength’s of 426, 484, 490, 581 and 610 nm to estimate the concentrations of Chl-a, Suspended Sediments and CDOM in case-II waters

Spatio-temporal evolution of chlorophyll-a in the Bay of Bengal: a remote sensing and bio-argo perspective

Argo floats equipped with sensors to measure Dissolved Oxygen, Chlorophyll-a and backscattering are deployed in the Arabian Sea, Bay of Bengal and Southern Indian Ocean as part of Indian Argo program. In this study, abnormal chlorophyll-a bloom observed by a float with WMO ID 2902086 deployed in the south central Bay of Bengal is analyzed. High concentration of chlorophyll > 0.8 mg/l is observed during December 2013. This period is also associated with drop in temperature and increase in salinity. Analysis of data from the bio-Argo float has shown the impact of many cyclones and depressions that occurred during the period. Of particular importance is cyclone ‘Madi’, which passed very near to the position of mentioned float, during December 2013. This is also evident from the satellite based wind observations from OSCAT through curl of wind stress and Ekman pumping. The sub-surface chlorophyll bloom is substantiated by the surface chlorophyll-a values of MODIS during the period. Intense mixing caused due to the passage of cyclone might have resulted in mixing of subsurface waters thereby breaking the stratification of otherwise stable surface waters of Bay of Bengal, enhancing the nutrient supply, which resulted in strong chlorophyll bloom. The subsurface chlorophyll structure of Bay of Bengal and its variability during the passage of cyclone is for the first time revealed by the floats equipped with biological sensors. This work reveals the synergistic application of in-situ (Bio- Argo) and satellite data to monitor the changes in subsurface structure during the passage of cyclones

Ocean Data and Information System (ODIS) and web-based services

The Ocean Data and Information System (ODIS) is a one stop shop for providing data and information on physical, chemical and biological parameters of ocean and coasts on various spatial and temporal domains that is vital for both research and operational oceanography. It is an end-to-end ocean data management system, developed by exploiting the advances in the field of information and communication technology that brought revolutionary changes in data acquisition, processing, analysis and data availability at a click away. ODIS is fed by voluminous (˜5 Tb per year) and highly heterogeneous oceanographic data in real time, acquired from the Ocean Observing Systems (both in-situ and remote sensing) established in the Indian Ocean. The challenges involved in developing ODIS are integration of heterogeneous data received from a wide variety of ocean observing systems, generation of metadata, quality control, generation of database and implementation of data warehousing and mining concepts for providing web-based data services. ODIS forms as a vital component for providing web-based services. The web-site has been matured as a prime vehicle for providing ocean data, information and advisory services such as potential fishing zone, ocean state forecast, Indian Argo, Indian Ocean Global Ocean Observing System, etc. The web-based online delivery system facilitates the user with multi-lingual and Web-GIS capabilities to query, analyze, visualize and download the ocean data, information and advisory services on different spatial and temporal resolutions. In this paper, we describe the development of ocean data and information system, data flow from various ocean observing system, formats, metadata base, quality control procedures and web-based data services that facilitates online data discovery, visualization and delivery. We also give an account on the web-based ocean information and advisory services and the challenges involved in ocean data management and web-based services. Further, we briefly discuss on the efforts with regard to open standards and interoperability issues pertaining to marine data management for seamless exchange of data

COASTAL OCEAN OBSERVING NETWORK – OPEN SOURCE ARCHITECTURE FOR DATA MANAGEMENT AND WEB-BASED DATA SERVICES

The observations from the oceans are the backbone for any kind of operational services, viz. potential fishing zone advisory services, ocean state forecast, storm surges, cyclones, monsoon variability, tsunami, etc. Though it is important to monitor open Ocean, it is equally important to acquire sufficient data in the coastal ocean through coastal ocean observing systems for re-analysis, analysis and forecast of coastal ocean by assimilating different ocean variables, especially sub-surface information; validation of remote sensing data, ocean and atmosphere model/analysis and to understand the processes related to air-sea interaction and ocean physics. Accurate information and forecast of the state of the coastal ocean at different time scales is vital for the wellbeing of the coastal population as well as for the socio-economic development of the country through shipping, offshore oil and energy etc. Considering the importance of ocean observations in terms of understanding our ocean environment and utilize them for operational oceanography, a large number of platforms were deployed in the Indian Ocean including coastal observatories, to acquire data on ocean variables in and around Indian Seas. The coastal observation network includes HF Radars, wave rider buoys, sea level gauges, etc. The surface meteorological and oceanographic data generated by these observing networks are being translated into ocean information services through analysis and modelling. Centralized data management system is a critical component in providing timely delivery of Ocean information and advisory services. In this paper, we describe about the development of open-source architecture for real-time data reception from the coastal observation network, processing, quality control, database generation and web-based data services that includes on-line data visualization and data downloads by various means

GUI based interactive system for Visual Quality Control of Argo data

580-586Argo program is aimed at maintaining an array of 3000 free drifting floats to measure temperature and salinity (T/S). Present study consists a PC-based system developed for visualization and quality control of T/S profiles obtained from Argo floats. The system, coded in Java, is user interactive and runs on Windows platform. Default the Argo T/S profiles pass through 19 automatic checks and quality flags are assigned. Using the system, T/S profiles that failed the automatic Argo tests undergo visual review. This visual review is done to determine whether automatic Argo tests were excessively flagging good measurements as bad or vice-versa, to motivate modifications to automatic Argo tests and to determine whether additional tests were necessary to catch problems that could not be detected by the existing tests. Visual review is done by comparing with 1° X 1° monthly climatologies from WOA01. Profile records deviating beyond 2 standard deviations from the mean are flagged as bad. Provision is also given to compare individual T/S profiles with previous 5 profiles via a waterfall plot

Open Source Architecture for Web-Based Oceanographic Data Services

A GIS for ocean data applications named "Ocean Data and Information Systems (ODIS)" was designed and developed. The system is based on the University of Minnesota MapServer, an open source platform for publishing spatial data and interactive mapping applications to the web with MySQL as the backend database server. This paper discusses some of the details of the storage and organization of oceanographic data, methods employed for visualization of parameter plots, and mapping of the data. ODIS is conceived to be an end-to-end system comprising acquisition of data from a variety of heterogeneous ocean platforms, processing, integration, quality control, and web-based dissemination to users for operational and research activities. ODIS provides efficient data management and potential mapping and visualization functions for oceanographic data

Quality control of oceanographic in situ data from Argo floats using climatological convex hulls

A new method of identifying anomalous oceanic temperature and salinity (T/S) data from Argo profiling floats is proposed. The proposed method uses World Ocean Database 2013 climatology to classify good against anomalous data by using convex hulls. An n-sided polygon (convex hull) with least area encompassing all the climatological points is constructed using Jarvis March algorithm. Subsequently Points In Polygon (PIP) principle implemented using ray casting algorithm is used to classify the T/S data as within or without acceptable bounds. It is observed that various types of anomalies associated with the oceanographic data viz., spikes, bias, sensor drifts etc can be identified using this method. Though demonstrated for Argo data it can be applied to any oceanographic data. • The patterns of variation of the parameter (temperature or salinity) corresponding to a particular depth, along the longitude or latitude can be used to build convex hulls. • This method can be effectively used for quality control by building Convex hulls for various observed depths corresponding to biogeochemical data which are sparsely observed. • This method has the advantage of treating the bulk of oceanographic in situ data in a single iteration which filters out anomalous data

Daily composite wind fields from Oceansat-2 scatterometer

Oceansat-2 scatterometer (OSCAT) is an active microwave sensor, intended to provide ocean surface wind vectors over the global oceans. In the present work, an attempt has been made to generate daily composites of OSCAT Level-3 (L3) wind vectors using Data-Interpolating Variational Analysis (DIVA) method from ascending and descending passes over the Indian Ocean region. This could be useful for operational purposes and in generating value-added products like wind stress and curl of wind stress. The daily composite wind vectors of zonal (U) and meridional (V) components have been validated by comparing with Advanced Scatterometer (ASCAT) and wind from in situ buoys for the year 2012. Wind composites thus generated using DIVA are found to match well with in situ, and ASCAT wind products. Minor deviations are observed with respect to ASCAT wind, which could be attributed to the difference in interpolation techniques used for the two scatterometer products. Given that the repeat period of ASCAT is 5 days and that of OSCAT is only 2 days, OSCAT wind products could be conveniently used for real-time met-ocean studies