Tangent height registration method for the Version 14 data retrieval algorithm of the solar occultation sensor ILAS-II

2007 ◽  
Vol 46 (29) ◽  
pp. 7196 ◽  
Author(s):  
Tomoaki Tanaka ◽  
Hideaki Nakajima ◽  
Takafumi Sugita ◽  
Mitsumu K. Ejiri ◽  
Hitoshi Irie ◽  
...  
Keyword(s):  
Data Retrieval ◽  
Retrieval Algorithm ◽  
Registration Method ◽  
Solar Occultation

Validation of TROPOMI nadir ozone profile retrievals: Methodology and first results

2021 ◽  
Author(s):  
Arno Keppens ◽  
Jean-Christopher Lambert ◽  
Daan Hubert ◽  
Steven Compernolle ◽  
Tijl Verhoelst ◽  
...  
Keyword(s):  
Near Infrared ◽  
Stratospheric Ozone ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Data Retrieval ◽  
Atmospheric Composition ◽  
Retrieval Algorithm ◽  
Validation Data ◽  
Ozone Profile ◽  
Early Afternoon

<p>Part of the space segment of EU’s Copernicus Earth Observation programme, the Sentinel-5 Precursor (S5P) mission is dedicated to global and European atmospheric composition measurements of air quality, climate and the stratospheric ozone layer. On board of the S5P early afternoon polar satellite, the imaging spectrometer TROPOMI (TROPOspheric Monitoring Instrument) performs nadir measurements of the Earth radiance within the UV-visible and near-infrared spectral ranges, from which atmospheric ozone profile data are retrieved. Developed at the Royal Netherlands Meteorological Institute (KNMI) and based on the optimal estimation method, TROPOMI’s operational ozone profile retrieval algorithm has recently been upgraded. With respect to early retrieval attempts, accuracy is expected to have improved significantly, also thanks to recent updates of the TROPOMI Level-1b data product. This work reports on the initial validation of the improved TROPOMI height-resolved ozone data in the troposphere and stratosphere, as collected both from the operational S5P Mission Performance Centre/Validation Data Analysis Facility (MPC/VDAF) and from the S5PVT scientific project CHEOPS-5p. Based on the same validation best practices as developed for and applied to heritage sensors like GOME-2, OMI and IASI (Keppens et al., 2015, 2018), the validation methodology relies on the analysis of data retrieval diagnostics – like the averaging kernels’ information content – and on comparisons of TROPOMI data with reference ozone profile measurements. The latter are acquired by ozonesonde, stratospheric lidar, and tropospheric lidar stations performing network operation in the context of WMO's Global Atmosphere Watch and its contributing networks NDACC and SHADOZ. The dependence of TROPOMI’s ozone profile uncertainty on several influence quantities like cloud fraction and measurement parameters like sun and scan angles is examined and discussed. This work concludes with a set of quality indicators, enabling users to verify the fitness-for-purpose of the S5P data.</p>

scholarly journals An Optimization Technique of the 3D Indoor Map Data Based on an Improved Octree Structure

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiaomin Yu ◽  
Huiqiang Wang ◽  
Hongwu Lv ◽  
Junqiang Fu
Keyword(s):  
Data Storage ◽  
Optimization Technique ◽  
Data Retrieval ◽  
Retrieval Algorithm ◽  
Storage Structure ◽  
Storage Model ◽  
Indoor Space ◽  
Close Relationship ◽  
Time Requirements ◽  
Map Data

The construction and retrieval of indoor maps are important for indoor positioning and navigation. It is necessary to ensure a good user experience while meeting real-time requirements. Unlike outdoor maps, indoor space is limited, and the relationship between indoor objects is complex which would result in an uneven indoor data distribution and close relationship between the data. A data storage model based on the octree scene segmentation structure was proposed in this paper initially. The traditional octree structure data storage model has been improved so that the data could be backtracked. The proposed method will solve the problem of partition lines within the range of the object data and improve the overall storage efficiency. Moreover, a data retrieval algorithm based on octree storage structure was proposed. The algorithm adopts the idea of “searching for a point, points around the searched point are within the searching range.” Combined with the octree neighbor retrieval methods, the closure constraints are added. Experimental results show that using the improved octree storage structure, the retrieval cost is 1/8 of R-tree. However, by using the neighbor retrieval, it improved the search efficiency by about 27% on average. After adding the closure constraint, the retrieval efficiency increases by 25% on average.

Data Mining Based Intelligent Retrieval Algorithm and its Application

2015 ◽  
Vol 742 ◽  
pp. 340-343
Author(s):  
Chun Ping Wang
Keyword(s):  
Information Retrieval ◽  
Digital Libraries ◽  
Retrieval System ◽  
Data Retrieval ◽  
Retrieval Algorithm ◽  
Accurate Information ◽  
Intelligent Information Retrieval ◽  
Intelligent Information ◽  
Mining Algorithms ◽  
Potential Use

Mathematical model of information retrieval algorithm retrieves digital libraries involved, it is very important to design an algorithm to make the best of the books, in order to extract the required information, including the association rules and classification method for from the database predicting the reader and potential use of fast and accurate information. In this paper, the intelligent data retrieval books mining algorithms to analyze, you can study the books of intelligent retrieval application, until the actual retrieval algorithm to solve the model first developed to meet the requirements, design a library of books intelligent information retrieval system .

Validation of TROPOMI nadir ozone profile retrievals: Methodology and first results

2020 ◽  
Author(s):  
Arno Keppens ◽  
Daan Hubert ◽  
Jean-Christopher Lambert ◽  
Steven Compernolle ◽  
Tijl Verhoelst ◽  
...  
Keyword(s):  
Near Infrared ◽  
Stratospheric Ozone ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Data Retrieval ◽  
Atmospheric Composition ◽  
Retrieval Algorithm ◽  
Validation Data ◽  
Ozone Profile ◽  
Early Afternoon

<p>Part of the space segment of EU’s Copernicus Earth Observation programme, the Sentinel-5 Precursor (S5P) mission is dedicated to global and European atmospheric composition measurements of air quality, climate and the stratospheric ozone layer. On board of the S5P early afternoon polar satellite, the imaging spectrometer TROPOMI (TROPOspheric Monitoring Instrument) performs nadir measurements of the Earth radiance within the UV-visible and near-infrared spectral ranges, from which atmospheric ozone profile data are retrieved. Developed at the Royal Netherlands Meteorological Institute (KNMI) and based on the optimal estimation method, TROPOMI’s operational ozone profile retrieval algorithm has recently been upgraded. With respect to early retrieval attempts, accuracy is expected to have improved significantly, also thanks to recent updates of the TROPOMI Level-1b data product. This work reports on the initial validation of the improved TROPOMI height-resolved ozone data in the troposphere and stratosphere, as collected both from the operational S5P Mission Performance Centre/Validation Data Analysis Facility (MPC/VDAF) and from the S5PVT scientific project CHEOPS-5p. Based on the same validation best practices as developed for and applied to heritage sensors like GOME-2, OMI and IASI (Keppens et al., 2015, 2018), the validation methodology relies on the analysis of data retrieval diagnostics – like the averaging kernels’ information content – and on comparisons of TROPOMI data with reference ozone profile measurements. The latter are acquired by ozonesonde, stratospheric lidar, and tropospheric lidar stations performing network operation in the context of WMO's Global Atmosphere Watch and its contributing networks NDACC and SHADOZ. The dependence of TROPOMI’s ozone profile uncertainty on several influence quantities like cloud fraction and measurement parameters like sun and scan angles is examined and discussed. This work concludes with a set of quality indicators enabling users to verify the fitness-for-purpose of the S5P data.</p>

Trends in spectrally resolved OLR from 10 years of IASI measurements

2021 ◽  
Author(s):  
Simon Whitburn ◽  
Lieven Clarisse ◽  
Andy Delcloo ◽  
Steven Dewitte ◽  
Marie Bouillon ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Data Retrieval ◽  
Radiation Budget ◽  
Retrieval Algorithm ◽  
Earth Atmosphere ◽  
Clear Sky ◽  
The Earth ◽  
Atmosphere System ◽  
Spectrally Resolved ◽  
The Impact

<p>The Earth's Outgoing Longwave Radiation (OLR) is a key component in the study of climate. As part of the Earth's radiation budget, it reflects how the Earth-atmosphere system compensates the incoming solar radiation at the top of the atmosphere. At equilibrium, the two quantities compensate each other on average. Any variation of the climate drivers (e.g. greenhouse gases) causes an energy imbalance which leads to a climate response (e.g. surface temperature increase), with the effect of bringing the radiation budget back to equilibrium. Considerable improvements in our understanding of the Earth-atmosphere system and of its long-term changes have been achieved in the last four decades through the exploitation of measurements from dedicated broadband instruments. However, such instruments only provide spectrally integrated OLR over a broad spectral range and are therefore not well suited for tracking separately the impact of the different parameters affecting the OLR.</p><p>Better constraints can, in principle, be obtained from spectrally resolved OLR (i.e. the integrand of broadband OLR, in units of W m<sup>-2</sup> cm<sup>-1</sup>) derived from infrared hyperspectral sounders. Recently, a dedicated algorithm was developed to derive clear-sky spectrally resolved OLR from the Infrared Atmospheric Sounding Interferometer (IASI) at the 0.25 cm<sup>-1</sup> native spectral sampling of the L1C spectra (Whitburn et al. 2020).  Here, we analyze the changes in 10 years (2008-2017) of the IASI-derived OLR and we relate them to known changes in greenhouse gases concentrations (CO<sub>2</sub>, CH<sub>4</sub>, H<sub>2</sub>O, …) and climate phenomena activity such as El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).</p><p>Whitburn, S., Clarisse, L., Bauduin, S., George, M., Hurtmans, D., Safieddine, S., Coheur, P. F., and Clerbaux, C. (2020). <strong>Spectrally Resolved Fuxes from IASI Data: Retrieval algorithm for Clear-Sky Measurements</strong>. Journal of Climate. doi: 10.1175/jcli-d-19-0523.1</p>

scholarly journals New temperature and pressure retrieval algorithm for high-resolution infrared solar occultation spectroscopy: analysis and validation against ACE-FTS and COSMIC

2015 ◽  
Vol 8 (10) ◽  
pp. 10823-10873 ◽  
Author(s):  
K. S. Olsen ◽  
G. C. Toon ◽  
C. D. Boone ◽  
K. Strong
Keyword(s):  
High Resolution ◽  
Atmospheric Chemistry ◽  
Primary Component ◽  
Retrieval Algorithm ◽  
Cold Bias ◽  
Vertical Profiles ◽  
Solar Occultation ◽  
Spatial Coverage ◽  
Temperature And Pressure ◽  
Mean Differences

Abstract. Motivated by the initial selection of a high-resolution solar occultation Fourier transform spectrometer (FTS) to fly to Mars on the ExoMars Trace Gas Orbiter, we have been developing algorithms for retrieving volume mixing ratio vertical profiles of trace gases, the primary component of which is a new algorithm and software for retrieving vertical profiles of temperature and pressure from the spectra. In contrast to Earth-observing instruments, which can rely on accurate meteorological models, a priori information, and spacecraft position, Mars retrievals require a method with minimal reliance on such data. The temperature and pressure retrieval algorithms developed for this work were evaluated using Earth-observing spectra from the Atmospheric Chemistry Experiment (ACE) FTS, a solar occultation instrument in orbit since 2003, and the basis for the instrument selected for a Mars mission. ACE-FTS makes multiple measurements during an occultation, separated in altitude by 1.5–5 km, and we analyze 10 CO2 vibration-rotation bands at each altitude, each with a different usable altitude range. We describe the algorithms and present results of their application and their comparison to the ACE-FTS data products. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) provides vertical profiles of temperature up to 40 km with high vertical resolution. Using six satellites and GPS radio occultation, COSMIC's data product has excellent temporal and spatial coverage, allowing us to find coincident measurements with ACE with very tight criteria: less than 1.5 h and 150 km. We present an inter-comparison of temperature profiles retrieved from ACE-FTS using our algorithm, that of the ACE Science Team (v3.5), and from COSMIC. When our retrievals are compared to ACE-FTS v3.5, we find mean differences between −5 and +2 K, and that our retrieved profiles have no seasonal or zonal biases, but do have a warm bias in the stratosphere and a cold bias in the mesosphere. When compared to COSMIC, we do not observe a warm/cool bias and mean differences are between −4 and +1 K. COSMIC comparisons are restricted to below 40 km, where our retrievals have the best agreement with ACE-FTS v3.5. When comparing ACE-FTS v3.5 to COSMIC we observe a cold bias in COSMIC of 0.5 K, and mean differences are between −0.9 and +0.6 K.

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