European Space Agency (ESA) Landsat MSS/TM/ETM+ Archive Bulk-Processing: processor improvements and data quality

2014 ◽  
Author(s):  
F. Gascon ◽  
R. Biasutti ◽  
R. Ferrara ◽  
P. Fischer ◽  
L. Galli ◽  
...  
Keyword(s):  
Data Quality ◽  
European Space Agency ◽  
Space Agency ◽  
Bulk Processing

Bulk processing of the Landsat MSS/TM/ETM+ archive of the European Space Agency

2015 ◽  
Author(s):  
F. Gascon ◽  
R. Biasutti ◽  
R. Ferrara ◽  
P. Fischer ◽  
L. Galli ◽  
...  
Keyword(s):  
European Space Agency ◽  
Space Agency ◽  
Bulk Processing

Quality Status of the CryoSat Data Products

2020 ◽  
Author(s):  
Erica Webb ◽  
Ben Wright ◽  
Marco Meloni ◽  
Jerome Bouffard ◽  
Tommaso Parrinello ◽  
...  
Keyword(s):  
Sea Ice ◽  
Data Quality ◽  
Positive Impact ◽  
European Space Agency ◽  
Performance Standards ◽  
Radar Altimeter ◽  
Mountain Glaciers ◽  
Space Agency ◽  
And Performance ◽  
Quality Status

<p>Launched in 2010, the European Space Agency’s (ESA) polar-orbiting CryoSat satellite was specifically designed to measure changes in the thickness of polar sea ice and the elevation of the ice sheets and mountain glaciers. Beyond the primary mission objectives, CryoSat is also valuable source of data for the oceanographic community and CryoSat’s sophisticated SAR Interferometric Radar Altimeter (SIRAL) can measure high-resolution geophysical parameters from the open ocean to the coast.</p><p>CryoSat data is processed operationally using two independent processing chains: Ice and Ocean. To ensure that the CryoSat products meet the highest data quality and performance standards, the CryoSat Instrument Processing Facilities (IPFs) are periodically updated. Processing algorithms are improved based on feedback and recommendations from Quality Control (QC) activities, Calibration and Validation campaigns, the CryoSat Expert Support Laboratory (ESL), and the Scientific Community. </p><p>Since May 2019, the CryoSat ice products are generated with Baseline-D, which represented a major processor upgrade and implemented several improvements, including the optimisation of freeboard computation in SARIn mode, improvements to sea ice and land ice retracking and the migration from Earth Explorer Format (EEF) to Network Common Data Form (NetCDF). A reprocessing campaign is currently underway to reprocess the full mission dataset (July 2010 – May 2019) to Baseline-D.</p><p>The CryoSat ocean products are also generated in NetCDF, following a processor upgrade in November 2017 (Baseline-C). Improvements implemented in this new Baseline include the generation of ocean products for all data acquisition modes, therefore providing complete data coverage for ocean users. This upgrade also implemented innovative algorithms, refined existing ones and added new parameters and corrections to the products. Following the completion of a successful reprocessing campaign, Baseline-C ocean products are now available for the full mission dataset (July 2010 – present).</p><p>Since launch, the CryoSat ice and ocean products have been routinely monitored as part of QC activities by the ESA/ESRIN Sensor Performance, Products and Algorithms (SPPA) office with the support of the Quality Assurance for Earth Observation (QA4EO) service (formerly IDEAS+) led by Telespazio VEGA UK. The latest processor updates have brought significant improvements to the quality of CryoSat ice and ocean products, which in turn are expected to have a positive impact on the scientific exploitation of CryoSat measurements over all surface types.</p><p>This poster provides an overview of the CryoSat data quality status and the QC activities performed by the QA4EO consortium, including both operational and reprocessing QC. Also presented are the main evolutions and improvements that have implemented to the processors, and anticipated evolutions for the future.</p>

Quality Status of the CryoSat Data Products

2021 ◽  
Author(s):  
Erica Webb ◽  
Jenny Marsh ◽  
Laura Benzan Valette ◽  
Jerome Bouffard ◽  
Tommaso Parrinello ◽  
...  
Keyword(s):  
Sea Ice ◽  
Data Quality ◽  
Positive Impact ◽  
European Space Agency ◽  
Performance Standards ◽  
Radar Altimeter ◽  
Mountain Glaciers ◽  
Space Agency ◽  
And Performance ◽  
Quality Status

<p>Launched in 2010, the European Space Agency’s (ESA) polar-orbiting CryoSat satellite was specifically designed to measure changes in the thickness of polar sea ice and the elevation of the ice sheets and mountain glaciers. Beyond the primary mission objectives, CryoSat is also valuable source of data for the oceanographic community and CryoSat’s sophisticated SAR Interferometric Radar Altimeter (SIRAL) can measure high-resolution geophysical parameters from the open ocean to the coast.</p><p>CryoSat data is processed operationally using two independent processing chains: Ice and Ocean. To ensure that the CryoSat products meet the highest data quality and performance standards, the CryoSat Instrument Processing Facilities (IPFs) are periodically updated. Processing algorithms are improved based on feedback and recommendations from Quality Control (QC) activities, Calibration and Validation campaigns, the CryoSat Expert Support Laboratory (ESL), and the Scientific Community.</p><p>Since May 2019, the CryoSat ice products have been generated with Baseline-D, which represented a major processor upgrade and implemented several improvements, including the optimisation of freeboard computation in SARIn mode, improvements to sea ice and land ice retracking and the migration from Earth Explorer Format (EEF) to Network Common Data Form (NetCDF). The Baseline-D reprocessing campaign completed in May 2020, and the full mission Baseline-D dataset is now available to users (July 2010 – present). The next major processor upgrade, Baseline-E, is already under development and following testing and refinement is anticipated to be operational in Q3 2021.</p><p>The CryoSat ocean products are also generated in NetCDF, following a processor upgrade in November 2017 (Baseline-C). Improvements implemented in this baseline include the generation of ocean products for all data acquisition modes, therefore providing complete data coverage for ocean users. This upgrade also implemented innovative algorithms, refined existing ones and added new parameters and corrections to the products. Following the completion of a successful reprocessing campaign, Baseline-C ocean products are now available for the full mission dataset (July 2010 – present). Preparations are underway for the next major processor upgrade, Baseline-D.</p><p>Since launch, the CryoSat ice and ocean products have been routinely monitored as part of QC activities by the ESA/ESRIN Sensor Performance, Products and Algorithms (SPPA) office with the support of the Quality Assurance for Earth Observation (QA4EO) service (formerly IDEAS+) led by Telespazio UK. The latest processor updates have brought significant improvements to the quality of CryoSat ice and ocean products, which in turn are expected to have a positive impact on the scientific exploitation of CryoSat measurements over all surface types.</p><p>This poster provides an overview of the CryoSat data quality status and the QC activities performed by the IDEAS-QA4EO consortium, including both operational and reprocessing QC. Also presented are the main evolutions and improvements that have implemented to the processors, and anticipated evolutions for the future.</p>

Six years of Swarm: instruments and data quality status

2020 ◽  
Author(s):  
Enkelejda Qamili ◽  
Jerome Bouffard ◽  
Filomena Catapano ◽  
Christian Siemes ◽  
Jan Miedzik ◽  
...  
Keyword(s):  
Data Quality ◽  
Temporal Evolution ◽  
European Space Agency ◽  
Quality Data ◽  
Product Evolution ◽  
The Earth ◽  
Space Agency ◽  
The Magnetic Field ◽  
Swarm Mission ◽  
Quality Status

<p>The European Space Agency (ESA) Swarm mission, launched in November 2013, continue to provide the best ever survey of the geomagnetic field and its temporal evolution. These high quality measurements of the strength, direction and variation of the magnetic field, together with precise navigation, accelerometer, electric field, plasma density and temperature measurements, are crucial for a better understanding of the Earth’s interior and its environment. This paper will provide an overview of the Swarm Instruments and data quality status and product evolution after six years of operations, focusing on the most significant payload investigations to improve science quality, data validation activities and results along with future validation/calibration plans.</p>

scholarly journals Swarm Langmuir Probes' data quality and future improvements

2021 ◽  
Author(s):  
Filomena Catapano ◽  
Stephan Buchert ◽  
Enkelejda Qamili ◽  
Thomas Nilsson ◽  
Jerome Bouffard ◽  
...  
Keyword(s):  
Data Quality ◽  
Numerical Models ◽  
European Space Agency ◽  
Langmuir Probes ◽  
Plasma Parameters ◽  
Plasma Dynamics ◽  
High Data ◽  
Space Agency ◽  
Swarm Satellites ◽  
The Impact

Abstract. Swarm is ESA's (European Space Agency) first Earth observation constellation mission, which was launched in 2013 to study the geomagnetic field and its temporal evolution. Two Langmuir Probes (LPs) on board of each of the three Swarm satellites provide very accurate measurements of plasma parameters, which contribute to the the study of the ionospheric plasma dynamics. To maintain a high data quality for scientific and operational applications, the Swarm products are continuously monitored and validated via science-oriented diagnostics. This paper presents an overview of the data quality of the Swarm Langmuir Probes' measurements. The data quality is assessed by analysing short and long data segments, where the latter are selected sufficiently long to consider the impact of the solar activity. Langmuir Probes data have been validated through comparison with numerical models, other satellite missions, and ground observations. Based on the outcomes from quality control and validation activities conduced by ESA, as well as scientific analysis and feedback provided by the user community, the Swarm products are regularly upgraded. In this paper we discuss the data quality improvements introduced with the latest baseline, and how the data quality is influenced by the solar cycle. The main anomaly affecting the LP measurements is described, as well as possible improvements to be implemented in future baselines.

scholarly journals Detailed Modeling of Cork-Phenolic Ablators in Preparation for the Post-flight Analysis of the QARMAN Re-entry CubeSat

2021 ◽  
Author(s):  
Claudio Miccoli ◽  
Alessandro Turchi ◽  
Pierre Schrooyen ◽  
Domenic D’Ambrosio ◽  
Thierry Magin
Keyword(s):  
Fluid Dynamics ◽  
Thermal Protection ◽  
A Priori ◽  
European Space Agency ◽  
Thermal Response ◽  
Accurate Method ◽  
Navier Stokes ◽  
Advection Equation ◽  
High Enthalpy ◽  
Space Agency

AbstractThis work deals with the analysis of the cork P50, an ablative thermal protection material (TPM) used for the heat shield of the qarman Re-entry CubeSat. Developed for the European Space Agency (ESA) at the von Karman Institute (VKI) for Fluid Dynamics, qarman is a scientific demonstrator for Aerothermodynamic Research. The ability to model and predict the atypical behavior of the new cork-based materials is considered a critical research topic. Therefore, this work is motivated by the need to develop a numerical model able to respond to this demand, in preparation to the post-flight analysis of qarman. This study is focused on the main thermal response phenomena of the cork P50: pyrolysis and swelling. Pyrolysis was analyzed by means of the multi-physics Computational Fluid Dynamics (CFD) code argo, developed at Cenaero. Based on a unified flow-material solver, the Volume Averaged Navier–Stokes (VANS) equations were numerically solved to describe the interaction between a multi-species high enthalpy flow and a reactive porous medium, by means of a high-order Discontinuous Galerkin Method (DGM). Specifically, an accurate method to compute the pyrolysis production rate was implemented. The modeling of swelling was the most ambitious task, requiring the development of a physical model accounting for this phenomenon, for the purpose of a future implementation within argo. A 1D model was proposed, mainly based on an a priori assumption on the swelling velocity and the resolution of a nonlinear advection equation, by means of a Finite Difference Method (FDM). Once developed, the model was successfully tested through a matlab code, showing that the approach is promising and thus opening the way to further developments.

scholarly journals Applicability of NGGM near-real time simulations in flood detection

2019 ◽  
Vol 9 (1) ◽  
pp. 111-126
Author(s):  
A. F. Purkhauser ◽  
J. A. Koch ◽  
R. Pail
Keyword(s):  
European Space Agency ◽  
Earth System ◽  
The Earth ◽  
Future Mission ◽  
Space Agency ◽  
Flood Detection ◽  
The One ◽  
Real Time Simulations ◽  
Grace Mission ◽  
Gravity Mission

Abstract The GRACE mission has demonstrated a tremendous potential for observing mass changes in the Earth system from space for climate research and the observation of climate change. Future mission should on the one hand extend the already existing time series and also provide higher spatial and temporal resolution that is required to fulfil all needs placed on a future mission. To analyse the applicability of such a Next Generation Gravity Mission (NGGM) concept regarding hydrological applications, two GRACE-FO-type pairs in Bender formation are analysed. The numerical closed loop simulations with a realistic noise assumption are based on the short arc approach and make use of the Wiese approach, enabling a self-de-aliasing of high-frequency atmospheric and oceanic signals, and a NRT approach for a short latency. Numerical simulations for future gravity mission concepts are based on geophysical models, representing the time-variable gravity field. First tests regarding the usability of the hydrology component contained in the Earth System Model (ESM) by the European Space Agency (ESA) for the analysis regarding a possible flood monitoring and detection showed a clear signal in a third of the analysed flood cases. Our analysis of selected cases found that detection of floods was clearly possible with the reconstructed AOHIS/HIS signal in 20% of the tested examples, while in 40% of the cases a peak was visible but not clearly recognisable.

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