scholarly journals MIPAS level 2 operational analysis

2006 ◽  
Vol 6 (4) ◽  
pp. 6525-6585 ◽  
Author(s):  
P. Raspollini ◽  
C. Belotti ◽  
A. Burgess ◽  
B. Carli ◽  
M. Carlotti ◽  
...  
Keyword(s):  
Total Error ◽  
Michelson Interferometer ◽  
A Priori Estimate ◽  
Infrared Region ◽  
Forward Model ◽  
Random Errors ◽  
Model Errors ◽  
Convergence Criteria ◽  
Practical Applications ◽  
Level 2

Abstract. The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument has been operating on-board the ENVISAT satellite since March 2002. In the first two years, it acquired in a nearly continuous manner high resolution (0.025 cm−1 unapodised) emission spectra of the Earth's atmosphere at limb in the middle infrared region. This paper describes the level 2 near real-time (NRT) and off-line (OL) ESA processors that have been used to derive level 2 geophysical products from the calibrated and geolocated level 1b spectra. The design of the code and the analysis methodology have been driven by the requirements for NRT processing. This paper reviews the performance of the optimised retrieval strategy that has been implemented to achieve these requirements and provides estimated error budgets for the target products: pressure/temperature, O3, H2O, CH4, HNO3, N2O and NO2, in the altitude measurement range from 6 to 68 km. From application to real MIPAS data, it was found that no change was needed in the developed code although an external algorithm was introduced to identify clouds with high opacity and to exclude affected spectra from the analysis. In addition, a number of updates were made to the set-up parameters and to auxiliary data. In particular, a new version of the MIPAS dedicated spectroscopic database was used and, in the OL analysis, the retrieval range was extended to reduce errors due to uncertainties in extrapolation of the profile outside the retrieval range and more stringent convergence criteria were implemented. A statistical analysis on the χ2 values obtained in one year of measurements shows good agreement with the a priori estimate of the forward model errors. On the basis of the first two years of MIPAS measurements the estimates of the forward model and instrument errors are in general found to be conservative with excellent performance demonstrated for frequency calibration. It is noted that the total retrieval error is limited by forward model errors which make useless a further reduction of random errors. However, such a reduction is within the capabilities of MIPAS measurements, which contain many more spectral signatures of the target species than what currently used. Further work is needed to reduce the amplitude of the forward model errors, so that the random error and the total error budget can be reduced accordingly. The importance of the Averaging kernels for a full characterisation of the target products is underlined and the equations are provided for their practical applications.

scholarly journals MIPAS level 2 operational analysis

2006 ◽  
Vol 6 (12) ◽  
pp. 5605-5630 ◽  
Author(s):  
P. Raspollini ◽  
C. Belotti ◽  
A. Burgess ◽  
B. Carli ◽  
M. Carlotti ◽  
...  
Keyword(s):  
Total Error ◽  
Michelson Interferometer ◽  
A Priori Estimate ◽  
Infrared Region ◽  
Forward Model ◽  
Random Errors ◽  
Model Errors ◽  
Convergence Criteria ◽  
Practical Applications ◽  
Level 2

Abstract. The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument has been operating on-board the ENVISAT satellite since March 2002. In the first two years, it acquired in a nearly continuous manner high resolution (0.025 cm−1 unapodized) emission spectra of the Earth's atmosphere at limb in the middle infrared region. This paper describes the level 2 near real-time (NRT) and off-line (OL) ESA processors that have been used to derive level 2 geophysical products from the calibrated and geolocated level 1b spectra. The design of the code and the analysis methodology have been driven by the requirements for NRT processing. This paper reviews the performance of the optimized retrieval strategy that has been implemented to achieve these requirements and provides estimated error budgets for the target products: pressure, temperature, O3, H2O, CH4, HNO3, N2O and NO2, in the altitude measurement range from 6 to 68 km. From application to real MIPAS data, it was found that no change was needed in the developed code although an external algorithm was introduced to identify clouds with high opacity and to exclude affected spectra from the analysis. In addition, a number of updates were made to the set-up parameters and to auxiliary data. In particular, a new version of the MIPAS dedicated spectroscopic database was used and, in the OL analysis, the retrieval range was extended to reduce errors due to uncertainties in extrapolation of the profile outside the retrieval range and more stringent convergence criteria were implemented. A statistical analysis on the χ2 values obtained in one year of measurements shows good agreement with the a priori estimate of the forward model errors. On the basis of the first two years of MIPAS measurements the estimates of the forward model and instrument errors are in general found to be conservative with excellent performance demonstrated for frequency calibration. It is noted that the total retrieval error is limited by forward model errors which make effectless a further reduction of random errors. However, such a reduction is within the capabilities of MIPAS measurements, which contain many more spectral signatures of the target species than what has currently been used. Further work is needed to reduce the amplitude of the forward model errors, so that the random error and the total error budget can be reduced accordingly. The importance of the Averaging kernels for a full characterization of the target products is underlined and the equations are provided for their practical applications.

scholarly journals A Robust Extended Kalman Filter Applied to Ultrawideband Positioning

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Chuanyang Wang ◽  
Houzeng Han ◽  
Jian Wang ◽  
Hang Yu ◽  
Deng Yang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Robust Estimation ◽  
Hypothesis Test ◽  
Systematic Errors ◽  
Random Errors ◽  
Model Errors ◽  
Global Test ◽  
Practical Applications ◽  
The Individual

Ultrawideband (UWB) is well-suited for indoor positioning due to its high resolution and good penetration through objects. The observation model of UWB positioning is nonlinear. As one of nonlinear filter algorithms, extended Kalman filter (EKF) is widely used to estimate the position. In practical applications, the dynamic estimation is subject to the outliers caused by gross errors. However, the EKF cannot resist the effect of gross errors. The innovation will become abnormally large and the performance and the reliability of the filter algorithm are inevitably influenced. In this study, a robust EKF (REKF) method accompanied by hypothesis test and robust estimation is proposed. To judge the validity of model, the global test based on Mahalanobis distance is implemented to assess whether the test statistical term exceeds the threshold for outlier detection. To reduce and eliminate the effects of the individual outlier, the robust estimation using scheme III of the Institute of Geodesy and Geophysics of China (IGGIII) based on local test of the normalized residual is performed. Meanwhile, three kinds of stochastic models for outliers are expressed by modeling the contaminated distributions. Furthermore, the simulation and measurement experiments are performed to verify the effectiveness and feasibility of the proposed REKF for resisting the outliers. Simulation experiment results are given to demonstrate that the outliers following all the three kinds of contaminated distributions can be detected. The proposed REKF can effectively control the influences of the outliers being treated as systematic errors and large variance random errors. When the outliers come from the thick-tailed distribution, the robust estimation does not play a role, and the REKF are equivalent to the EKF method. The measured experiment results show that the outliers will be generated in the nonline-of-sight environment whose impact is abnormally serious. The robust estimation can provide relatively reliable optimized residuals and control the influences of the outliers caused by gross errors. We can believe that the proposed REKF is effective to resist the effects of outliers and improves the positioning accuracy compared with least-squares (LS) and EKF method. Moreover, the adaptive filter and ranging error model should be considered to compensate the state model errors and ranging systematic errors respectively. Then, the measurement outliers will be detected more correctly, and the robust estimation will be used effectively.

scholarly journals Multivariate Error Covariance Estimates by Monte Carlo Simulation for Assimilation Studies in the Pacific Ocean

2005 ◽  
Vol 133 (8) ◽  
pp. 2310-2334 ◽  
Author(s):  
Anna Borovikov ◽  
Michele M. Rienecker ◽  
Christian L. Keppenne ◽  
Gregory C. Johnson
Keyword(s):  
Monte Carlo ◽  
Data Assimilation ◽  
Forecast Error ◽  
Independent Set ◽  
Velocity Fields ◽  
Optimal Interpolation ◽  
Model Errors ◽  
Error Statistics ◽  
Practical Applications ◽  
Monte Carlo Techniques

Abstract One of the most difficult aspects of ocean-state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model–observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross covariances between different model variables used. Here a comparison is made between a univariate optimal interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature profiles. In the UOI case only temperature is updated using a Gaussian covariance function. In the MvOI, salinity, zonal, and meridional velocities as well as temperature are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimate of the forecast error statistics is made by Monte Carlo techniques from an ensemble of model forecasts. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross covariances between the fields of different physical variables constituting the model-state vector, at the same time incorporating the model’s dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere–Ocean array have been assimilated in this study. To investigate the efficacy of the multivariate scheme, two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity, and temperature. For reference, a control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the UOI and MvOI is similar with respect to the temperature field, the salinity and velocity fields are greatly improved when the multivariate correction is used, as is evident from the analyses of the rms differences between these fields and independent observations. The MvOI assimilation is found to improve upon the control run in generating water masses with properties close to the observed, while the UOI fails to maintain the temperature and salinity structure.

scholarly journals On the improved stability of the version 7 MIPAS ozone record

2018 ◽  
Vol 11 (8) ◽  
pp. 4693-4705 ◽  
Author(s):  
Alexandra Laeng ◽  
Ellen Eckert ◽  
Thomas von Clarmann ◽  
Michael Kiefer ◽  
Daan Hubert ◽  
...  
Keyword(s):  
Michelson Interferometer ◽  
European Space Agency ◽  
Detector Response ◽  
Ozone Level ◽  
Term Stability ◽  
Long Term Stability ◽  
Drift Analysis ◽  
Ground Based Lidar ◽  
Level 2

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was an infrared limb emission spectrometer on the Envisat platform. From 2002 to 2012, it performed pole-to-pole measurements during day and night, producing more than 1000 profiles per day. The European Space Agency (ESA) recently released the new version 7 of Level 1B MIPAS spectra, in which a new set of time-dependent correction coefficients for the nonlinearity in the detector response functions was implemented. This change is expected to reduce the long-term drift of the MIPAS Level 2 data. We evaluate the long-term stability of ozone Level 2 data retrieved from MIPAS v7 Level 1B spectra with the IMK/IAA scientific level 2 processor. For this, we compare MIPAS data with ozone measurements from the Microwave Limb Sounder (MLS) instrument on NASA's Aura satellite, ozonesondes and ground-based lidar instruments. The ozonesondes and lidars alone do not allow us to conclude with enough significance that the new version is more stable than the previous one, but a clear improvement in long-term stability is observed in the satellite-data-based drift analysis. The results of ozonesondes, lidars and satellite drift analysis are consistent: all indicate that the drifts of the new version are less negative/more positive nearly everywhere above 15 km. The 10-year MIPAS ozone trends calculated from the old and the new data versions are compared. The new trends are closer to old drift-corrected trends than the old uncorrected trends were. From this, we conclude that the nonlinearity correction performed on Level 1B data is an improvement. These results indicate that MIPAS data are now even more suited for trend studies, alone or as part of a merged data record.

scholarly journals Comparison of SMILES ClO profiles with other satellite and balloon-based measurements

2013 ◽  
Vol 6 (1) ◽  
pp. 613-663 ◽  
Author(s):  
H. Sagawa ◽  
T. O. Sato ◽  
P. Baron ◽  
E. Dupuy ◽  
N. Livesey ◽  
...  
Keyword(s):  
Systematic Error ◽  
Michelson Interferometer ◽  
Space Station ◽  
Polar Vortex ◽  
Middle Latitude ◽  
Information And Communications Technology ◽  
Polar Regions ◽  
Systematic Bias ◽  
Spectral Bandwidth ◽  
Level 2

Abstract. We evaluate the quality of ClO profiles derived from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on the International Space Station (ISS). Version 2.1.5 of the level-2 product generated by the National Institute of Information and Communications Technology (NICT) is the subject of this study. Based on error analysis simulations the systematic error was estimated as 5–10 pptv at the pressure range of 80–20 hPa, 35 pptv at the ClO peak altitude (~ 4 hPa), and 5–10 pptv at pressures ≤ 0.5 hPa for daytime mid-latitude conditions. For nighttime measurements, a systematic error of 8 pptv was estimated for the ClO peak altitude (~ 2 hPa). The SMILES NICT v2.1.5 ClO profiles agree with those derived from another level-2 processor developed by JAXA within of the bias uncertainties, except for the nighttime measurements in the low and middle latitude region where the SMILES NICT v2.1.5 profiles have a negative bias of ~ 30 pptv in the lower stratosphere. This bias is considered to be due to the use of a limited spectral bandwidth in the retrieval process, which makes it difficult to distinguish between the ClO signal and wing contributions of spectral features outside the bandwidth. In the middle and upper stratosphere outside the polar regions, no significant systematic bias was found for the SMILES NICT ClO profile with respect to datasets from other instruments such as the Aura Microwave Limb Sounder (MLS), the Odin Sub-Millimetre Radiometer (SMR), and the Envisat Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which demonstrates the scientific usability of the SMILES ClO data including the diurnal variations. Inside the chlorine-activated polar vortex the SMILES NICT v2.1.5 ClO profiles show larger volume mixing ratios by 0.3 ppbv (30%) at 50 hPa compared to those of the JAXA processed profiles. This discrepancy is also considered to be an effect of the limited spectral bandwidth in the retrieval processing. We also compared the SMILES NICT ClO profiles of chlorine-activated polar vortex conditions with those measured by the balloon-borne instruments Terahertz and submillimeter Limb Sounder (TELIS) and the MIPAS-balloon (MIPAS-B).

scholarly journals Emergency physicians’ attitudes to implementing ultrasound in Dutch emergency departments after a 2-day training: A qualitative study

2018 ◽  
Vol 25 (5) ◽  
pp. 249-256 ◽  
Author(s):  
Rein Ketelaars ◽  
Esther Van Heumen ◽  
Lambert P Baken ◽  
Marja Witten ◽  
Gert Jan Scheffer ◽  
...  
Keyword(s):  
Emergency Department ◽  
Qualitative Study ◽  
Solid Base ◽  
Emergency Physicians ◽  
Structured Interviews ◽  
Evaluation Program ◽  
Practical Applications ◽  
Assurance System ◽  
Essential Insight ◽  
Level 2

Background: Diagnostic ultrasound is increasingly used by nonradiologists in trauma victims and critically ill patients. In the emergency department, the extended focused assessment with sonography for trauma and Polytrauma Rapid Echo-evaluation Program protocol are often used to assess these patients. Dutch Polytrauma Rapid Echo-evaluation Program-trained Emergency physicians are implementing the use of ultrasound in the emergency department but might encounter barriers to overcome. Objectives: This study aims to explore individual experiences of Dutch emergency physicians. Methods: We performed a qualitative study by conducting semi-structured interviews in Dutch emergency physicians working in a Level 2 emergency department that completed the 2-day Polytrauma Rapid Echo-evaluation Program course at least 1 year before the interviews. Data were analyzed using directed content analysis. Results: Eight emergency physicians employed by eight different hospitals were interviewed. Thirteen categories were identified in the transcribed interviews and these were combined into four general themes: (1) the desire to develop the Emergency Medicine specialty, both nationally and local; (2) incentives to start using ultrasound; (3) exploring practical applications of ultrasound; and (4) barriers faced while implementing emergency physician-performed ultrasound on the emergency department. The interviewees regard the course to be a solid base and are eager to independently perform ultrasound examinations, although challenges are faced. Conclusion: This exploratory study provides essential insight in Dutch emergency physicians implementing ultrasound in their emergency department. It shows that there is a need to develop a quality assurance system and it identified barriers that have to be dealt with.

Improved Estimation and Forecasting Through Residual-Based Model Error Quantification

SPE Journal ◽  
2020 ◽  
Vol 25 (02) ◽  
pp. 951-968 ◽  
Author(s):  
Minjie Lu ◽  
Yan Chen
Keyword(s):  
History Matching ◽  
Historical Data ◽  
Total Error ◽  
Model Error ◽  
Complex Nature ◽  
Model Parameters ◽  
Observation Error ◽  
Model Errors ◽  
Ensemble Smoother ◽  
Iterative Ensemble Smoother

Summary Owing to the complex nature of hydrocarbon reservoirs, the numerical model constructed by geoscientists is always a simplified version of reality: for example, it might lack resolution from discretization and lack accuracy in modeling some physical processes. This flaw in the model that causes mismatch between actual observations and simulated data when “perfect” model parameters are used as model inputs is known as “model error”. Even in a situation when the model is a perfect representation of reality, the inputs to the model are never completely known. During a typical model calibration procedure, only a subset of model inputs is adjusted to improve the agreement between model responses and historical data. The remaining model inputs that are not calibrated and are likely fixed at incorrect values result in model error in a similar manner as the imperfect model scenario. Assimilation of data without accounting for model error can result in the incorrect adjustment to model parameters, the underestimation of prediction uncertainties, and bias in forecasts. In this paper, we investigate the benefit of recognizing and accounting for model error when an iterative ensemble smoother is used to assimilate production data. The correlated “total error” (a combination of model error and observation error) is estimated from the data residual after a standard history-matching using the Levenberg-Marquardt form of iterative ensemble smoother (LM-EnRML). This total error is then used in further data assimilations to improve the estimation of model parameters and quantification of prediction uncertainty. We first illustrate the method using a synthetic 2D five-spot example, where some model errors are deliberately introduced, and the results are closely examined against the known “true” model. Then, the Norne field case is used to further evaluate the method. The Norne model has previously been history-matched using the LM-EnRML (Chen and Oliver 2014), where cell-by-cell properties (permeability, porosity, net-to-gross, vertical transmissibility) and parameters related to fault transmissibility, depths of water/oil contacts, and relative permeability function are adjusted to honor historical data. In this previous study, the authors highlighted the importance of including large amounts of model parameters, the proper use of localization, and heuristic adjustment of data noise to account for modeling error. In this paper, we improve the last aspect by quantitatively estimating model error using residual analysis.

scholarly journals A Passive Microwave Retrieval Algorithm with Minimal View-Angle Bias: Application to the TEMPEST-D CubeSat Mission

2020 ◽  
Vol 37 (2) ◽  
pp. 197-210
Author(s):  
Richard M. Schulte ◽  
Christian D. Kummerow ◽  
Wesley Berg ◽  
Steven C. Reising ◽  
Shannon T. Brown ◽  
...  
Keyword(s):  
Rapid Development ◽  
Passive Microwave ◽  
Forward Model ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Model Errors ◽  
Liquid Water Path ◽  
Water Path ◽  
The Tempest ◽  
Scan Pattern

AbstractThe rapid development of miniaturized satellite instrument technology has created a new opportunity to deploy constellations of passive microwave (PMW) radiometers to permit retrievals of the same Earth scene with very high temporal resolution to monitor cloud evolution and processes. For such a concept to be feasible, it must be shown that it is possible to distinguish actual changes in the atmospheric state from the variability induced by making observations at different Earth incidence angles (EIAs). To this end, we present a flexible and physical optimal estimation-based algorithm designed to retrieve profiles of atmospheric water vapor, cloud liquid water path, and cloud ice water path from cross-track PMW sounders. The algorithm is able to explicitly account for the dependence of forward model errors on EIA and atmospheric regime. When the algorithm is applied to data from the Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D) CubeSat mission, its retrieved products are generally in agreement with those obtained from the similar but larger Microwave Humidity Sounder instrument. More importantly, when forward model brightness temperature offsets and assumed error covariances are allowed to change with EIA and sea surface temperature, view-angle-related biases are greatly reduced. This finding is confirmed in two ways: through a comparison with reanalysis data and by making use of brief periods in early 2019 during which the TEMPEST-D spacecraft was rotated such that its scan pattern was along track, allowing dozens of separate observations of any given atmospheric feature along the satellite’s ground track.

Studies for the Odin sub-millimetre radiometer. II. Retrieval methodology

2002 ◽  
Vol 80 (4) ◽  
pp. 341-356 ◽  
Author(s):  
Ph. Baron ◽  
Ph. Ricaud ◽  
J de la Noë ◽  
J EP Eriksson ◽  
F Merino ◽  
...  
Keyword(s):  
Frequency Band ◽  
Estimation Method ◽  
High Sensitivity ◽  
Optimal Estimation ◽  
Forward Model ◽  
Model Errors ◽  
Target Species ◽  
Spectral Parameters ◽  
Chlorine Monoxide ◽  
Standard Code

This paper presents the first algorithm developed to retrieve atmospheric vertical profiles of trace gases from calibrated spectra measured by the sub-millimetre radiometer (SMR) onboard the Odin satellite. An estimation of atmospheric profiles is obtained by means of an inversion of the spectra using the Optimal Estimation Method. Great attention is paid to the study of the simultaneous retrieval of several species and nonlinearity effects. The measurement response is defined to give the altitude domain of a good retrieval. Main sources of measurement and forward model errors are characterized and separated into two categories: the fixed errors and the variable errors. We define a standard retrieval strategy that can be applied to theoretically investigate any frequency band of any observing Odin mode. For each frequency band, two categories of species are defined: the target species, i.e., the main species to be retrieved, and the interfering species, i.e., molecules emitting an interfering radiance in the observed band. The standard code is based upon an inversion of spectra using a linearized forward model and simultaneously estimates target species and interfering species. As an example, inversions of synthetic noise-free spectra of ozone and chlorine monoxide within an autocorrelator band ranging from 501.18 to 501.58 GHz are shown to behave as expected in the middle stratosphere and in the lower mesosphere. The error analysis shows retrieval limitations in the lower stratosphere that are mainly induced by the high sensitivity of the retrieval to parameters such as tangent height, accuracy in the vertical profile of the interfering species, and spectral parameters of both target lines and interfering lines. PACS Nos.: 42.68Ay, 07.07Df, 07.57Kp

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