Assessment of the quality of the ozone measurements from the Odin/SMR instrument using data assimilation

2007 ◽  
Vol 85 (11) ◽  
pp. 1209-1223 ◽  
Author(s):  
S Massart ◽  
A Piacentini ◽  
D Cariolle ◽  
L El Amraoui ◽  
N Semane
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Three Dimensional ◽  
The Other ◽  
Measuring Instruments ◽  
Atmospheric Measurements ◽  
Data Set ◽  
Ozone Data ◽  
Using Data

Space-based remote-sensing instruments providing atmospheric measurements have different time and space resolutions, and coverage. This makes the direct comparison of the measurements very difficult. Data assimilation has proven to be a far more powerful tool than simple interpolation techniques to create three-dimensional analyzed fields for a given data set. In this paper, we describe how the assimilation of ozone data from the Odin/SMR instrument can be used to assess its precisions and biases against other ozone-measuring instruments. To assess the quality of Odin/SMR ozone retrievals by MOLIERE-5 against ozonesondes, Envisat/MIPAS, Earth Probe/TOMS, and UARS/HALOE data, we use a three-dimensional variational assimilation scheme applied to the Météo-France MOCAGE chemistry transport model. The MOCAGE-PALM assimilation system has been already used by Météo-France and CERFACS to analyse the Envisat/MIPAS data for the ASSET intercomparison exercise. We have further developed and calibrated the configuration of this system to better account for the Odin/SMR ozone profiles. The upgraded system is used to assimilate the Odin/SMR ozone during the August 2003 – November 2003 period and intercomparisons are made with the other ozone measuring techniques. The Odin/SMR analysis and the other ozone data sets are in good agreement at mid and high latitudes, while in the lower tropical stratosphere, we found a positive bias of the Odin/SMR, Envisat/MIPAS, and Earth Probe/TOMS data compared to measurements from UARS/HALOE and ozonesondes. The precision of Odin/SMR ozone retrievals in terms of standard deviation is about 20% in the tropics, below 10% at high southern latitudes, and below 5% at high northern latitudes. PACS No.: 82.33.Tb

scholarly journals Data assimilation for volcanic ash plumes using a satellite observational operator: a case study on the 2010 Eyjafjallajökull volcanic eruption

2017 ◽  
Vol 17 (2) ◽  
pp. 1187-1205 ◽  
Author(s):  
Guangliang Fu ◽  
Fred Prata ◽  
Hai Xiang Lin ◽  
Arnold Heemink ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Volcanic Ash ◽  
Three Dimensional ◽  
Forecast Accuracy ◽  
Improve Model ◽  
Powerful Approach ◽  
Using Data ◽  
D Model

Abstract. Using data assimilation (DA) to improve model forecast accuracy is a powerful approach that requires available observations. Infrared satellite measurements of volcanic ash mass loadings are often used as input observations for the assimilation scheme. However, because these primary satellite-retrieved data are often two-dimensional (2-D) and the ash plume is usually vertically located in a narrow band, directly assimilating the 2-D ash mass loadings in a three-dimensional (3-D) volcanic ash model (with an integral observational operator) can usually introduce large artificial/spurious vertical correlations.In this study, we look at an approach to avoid the artificial vertical correlations by not involving the integral operator. By integrating available data of ash mass loadings and cloud top heights, as well as data-based assumptions on thickness, we propose a satellite observational operator (SOO) that translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The 3-D SOO makes the analysis step of assimilation comparable in the 3-D model space.Ensemble-based DA is used to assimilate the extracted measurements of ash concentrations. The results show that satellite DA with SOO can improve the estimate of volcanic ash state and the forecast. Comparison with both satellite-retrieved data and aircraft in situ measurements shows that the effective duration of the improved volcanic ash forecasts for the distal part of the Eyjafjallajökull volcano is about 6 h.

scholarly journals First steps towards the assimilation of IASI ozone data into the MOCAGE-PALM system

2009 ◽  
Vol 9 (2) ◽  
pp. 6691-6737 ◽  
Author(s):  
S. Massart ◽  
C. Clerbaux ◽  
D. Cariolle ◽  
A. Piacentini ◽  
S. Turquety ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Polar Regions ◽  
Observation Error ◽  
Random Errors ◽  
Chemistry Transport Model ◽  
Ozone Data ◽  
The One ◽  
New Generation

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is one of the five European new generation instruments carried by the polar-orbiting MetOp-A satellite. Data assimilation is a powerful tool to combine these data with a numerical model. This paper presents the first steps made towards the assimilation of the total ozone columns from the IASI measurements into a chemistry transport model. The IASI ozone data used are provided by an inversion of radiances performed at the LATMOS (Laboratoire Atmosphères, Milieux, Observations Spatiales). As a contribution to the validation of this dataset, the LATMOS-IASI data are compared to a four dimensional ozone field, with low systematic and random errors compared to ozonesondes and OMI-DOAS data. This field results from the combined assimilation of ozone profiles from the MLS instrument and of total ozone columns from the SCIAMACHY instrument. It is found that on average, the LATMOS-IASI data tends to overestimate the total ozone columns by 2% to 8%. The random observation error of the LATMOS-IASI data is estimated to about 6%, except over polar regions and deserts where it is higher. Using this information, the LATMOS-IASI data are then assimilated, combined with the MLS data. This first LATMOS-IASI data assimilation experiment shows that the resulting analysis is quite similar to the one obtained from the combined MLS and SCIAMACHY data assimilation.

Descriptors and Indicators of the Acoustic Environment in Andorra and Escaldes-Engordany

Proceedings ◽  
2019 ◽  
Vol 44 (1) ◽  
pp. 6
Author(s):  
Rosa Alsina-Pagès ◽  
Laura Echevarría-Garuz
Keyword(s):  
Quality Of Life ◽  
Noise Pollution ◽  
The Other ◽  
Physical Parameters ◽  
Noise Sources ◽  
Acoustic Environment ◽  
Audio Recordings ◽  
Using Data ◽  
The City

Noise pollution is one of the growing issues in our cities. Every day the streets are full of vehicles of all kinds and works using noisy machinery; it seems difficult to find a quiet area that away from this acoustic environment. Presently, multiple studies are being carried out in the area of engineering in order to be able to attenuate the causes of this noise pollution, in order to improve citizens’ lives. Nevertheless, are cars the only cause of the noise in the city? Are there other noise sources that may affect the quality of life of the citizens? What defines a city as heavily polluted or not? Maybe it can be assumed that truck noise is annoying and that it contributes to noise pollution, while the sound of birds does not and it is pleasant for people. This paper pretends to analyze the physical parameters that allow us to define if any sound causes annoyance, taking into account its acoustic environment. To do this, a specific case will be analysed; we will study three locations measured in Andorra La Vella and Escaldes-Engordany. The audio recordings will be studied deeply, and compared one to the other using data from two different days and all day schedule. We will finally evaluate the annoyance of each location using parameters such as loudness, sharpness and roughness, and taking into account both day and time, as well as giving details about the several types of sound labelled in each recording.

scholarly journals Cryomesh™: A New Substrate for Cryo-Electron Microscopy

2010 ◽  
Vol 16 (1) ◽  
pp. 43-53 ◽  
Author(s):  
Craig Yoshioka ◽  
Bridget Carragher ◽  
Clinton S. Potter
Keyword(s):  
Electron Microscopy ◽  
Semiconductor Industry ◽  
Three Dimensional ◽  
Quality Of Data ◽  
Temperature Conductivity ◽  
Cryo Electron Microscopy ◽  
Transmission Electron ◽  
Using Data ◽  
Collection Methods

AbstractHere we evaluate a new grid substrate developed by ProtoChips Inc. (Raleigh, NC) for cryo-transmission electron microscopy. The new grids are fabricated from doped silicon carbide using processes adapted from the semiconductor industry. A major motivating purpose in the development of these grids was to increase the low-temperature conductivity of the substrate, a characteristic that is thought to affect the appearance of beam-induced movement (BIM) in transmission electron microscope (TEM) images of biological specimens. BIM degrades the quality of data and is especially severe when frozen biological specimens are tilted in the microscope. Our results show that this new substrate does indeed have a significant impact on reducing the appearance and severity of beam-induced movement in TEM images of tilted cryo-preserved samples. Furthermore, while we have not been able to ascertain the exact causes underlying the BIM phenomenon, we have evidence that the rigidity and flatness of these grids may play a major role in its reduction. This improvement in the reliability of imaging at tilt has a significant impact on using data collection methods such as random conical tilt or orthogonal tilt reconstruction with cryo-preserved samples. Reduction in BIM also has the potential for improving the resolution of three-dimensional cryo-reconstructions in general.

scholarly journals EnKF and 4D-Var Data Assimilation with a Chemistry Transport Model

2016 ◽  
Author(s):  
Sergey Skachko ◽  
Richard Menard ◽  
Quentin Errera ◽  
Yves Christophe ◽  
Simon Chabrillat
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Model Error ◽  
The Other ◽  
Full Description ◽  
Observation Error ◽  
Tracer Transport ◽  
Chemistry Transport Model ◽  
Stratospheric Chemistry ◽  
Chemical Tracer

Abstract. We compare two optimized chemical data assimilation systems, one based on the ensemble Kalman filter (EnKF) and the other based on four-dimensional variational (4D-Var), using a comprehensive stratospheric chemistry transport model (CTM). The work is an extension of the Belgian Assimilation System for Chemical ObsErvations (BASCOE), initially designed to work with a 4D-Var data assimilation. A strict comparison of both methods in the case of chemical tracer transport was done in a previous study and indicated that both methods provide essentially similar results. In the present work, we assimilate observations of ozone, HCl, HNO3, H2O and N2O from EOS Aura-MLS data into the BASCOE CTM with a full description of stratospheric chemistry. Two new issues related to the use of full chemistry model with EnKF are taken into account. One issue concerns to a large number of error variance parameters that need to be optimized. We estimate an observation error parameter as function of pressure level for each observed species using the Desroziers' method. For comparison reasons, we apply the same estimate procedure in the 4D-Var data assimilation, where we keep both estimates: the background and observation error variances. However in EnKF, the background error covariance is modelled using the full chemistry model and a model error term. We found that it is adequate to have a single model error based on the chemical tracer formulation that is applied for all species. This is an indication that the main source of model error in chemical transport model is due to the transport. The second issue in EnKF with comprehensive atmospheric chemistry models is the sampling errors between species. When species are weakly chemically related, cross-species sampling noise errors occur at the same location. These errors need to be filtered out, in addition to a localization based on distance. The performance of two data assimilation methods was assessed through an eight-month long assimilation of limb sounding observations from EOS Aura-MLS. The paper discusses the differences in results and their relation to stratospheric chemical processes. Generally speaking, EnKF and 4D-Var provide results of comparable quality but differ substantially in presence of model error or observation biases. If the erroneous chemical modelling is associated with not too small chemical life-times, then EnKF performs better, while 4D-Var develops spurious increments in the chemically related species. If, on the other hand, the observation biases are significant, then 4D-Var is more robust and is able to reject erroneous observations, while EnKF does not.

scholarly journals Contribution of Internal Nutrients Loading on the Water Quality of a Reservoir

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1409 ◽  
Author(s):  
Hye Won Lee ◽  
Yong Seok Lee ◽  
Jonggun Kim ◽  
Kyoung Jae Lim ◽  
Jung Hyun Choi
Keyword(s):  
Water Quality ◽  
Sediment Load ◽  
Transport Model ◽  
Three Dimensional ◽  
Algal Growth ◽  
Nutrient Concentrations ◽  
Internal Load ◽  
Phosphorus Flux

Sediment plays an important role in the water quality of a lake by acting as both a nutrient source and sink. The amount of phosphorus and nitrogen in the water depends on the internal load from the sediment as well as the external load. To estimate the effects of sediment load on the water quality of a reservoir, we applied a three-dimensional hydrodynamic and transport model based on the benthic chamber experimental results at Euiam Lake, South Korea. As shown in the sensitivity analysis results, the eutrophication period could be significantly extended by a change of phosphorus flux rates from the sediments. The increased phosphorus flux from the sediments intensifies the algal growth of Euiam Lake, which could cause serious algal bloom during spring and fall. This study provides information on nutrient concentrations in the sediment of Euiam Lake, verifies the role of the sediment as a source or sink of nutrients, and evaluates the effect of sediment release of nutrients and contaminants on water quality. This research is a useful tool in determining the effects of internal load in lakes and establishing the operation guideline for sediment management in order to maintain feasible water quality for beneficial use.

An Impact Assessment of GPS Radio Occultation Data on Prediction of a Rapidly Developing Cyclone over the Southern Ocean*

2014 ◽  
Vol 142 (11) ◽  
pp. 4187-4206 ◽  
Author(s):  
Shu-Ya Chen ◽  
Tae-Kwon Wee ◽  
Ying-Hwa Kuo ◽  
David H. Bromwich
Keyword(s):  
Data Assimilation ◽  
Southern Ocean ◽  
Large Scale ◽  
Radio Occultation ◽  
Three Dimensional ◽  
Wrf Model ◽  
The Other ◽  
Gps Radio Occultation ◽  
The Antarctic ◽  
The Impact

Abstract The impact of global positioning system (GPS) radio occultation (RO) data on an intense synoptic-scale storm that occurred over the Southern Ocean in December 2007 is evaluated, and a synoptic explanation of the assessed impact is offered. The impact is assessed by using the three-dimensional variational data assimilation scheme (3DVAR) of the Weather Research and Forecasting (WRF) Model Data Assimilation system (WRFDA), and by comparing two experiments: one with and the other without assimilating the refractivity data from four different RO missions. Verifications indicate significant positive impacts of the RO data in various measures and parameters as well as in the track and intensity of the Antarctic cyclone. The analysis of the atmospheric processes underlying the impact shows that the assimilation of the RO data yields substantial improvements in the large-scale circulations that in turn control the development of the Antarctic storm. For instance, the RO data enhanced the strength of a 500-hPa trough over the Southern Ocean and prevented the katabatic flow near the coast of East Antarctica from an overintensification. This greatly influenced two low pressure systems of a comparable intensity, which later merged together and evolved into the major storm. The dominance of one low over the other in the merger dramatically changed the track, intensity, and structure of the merged storm. The assimilation of GPS RO data swapped the dominant low, leading to a remarkable improvement in the subsequent storm’s prediction.

scholarly journals Discovery of Knowledge by using Data Warehousing as well as ETL Processing

2019 ◽  
Vol 8 (2S6) ◽  
pp. 936-945
Keyword(s):  
Data Warehouse ◽  
Real Life ◽  
Real Data ◽  
Automated Testing ◽  
Quality Of Data ◽  
Data Set ◽  
The Real ◽  
Using Data ◽  
Data Warehouse Quality

Testing is very essential in Data warehouse systems for decision making because the accuracy, validation and correctness of data depends on it. By looking to the characteristics and complexity of iData iwarehouse, iin ithis ipaper, iwe ihave itried ito ishow the scope of automated testing in assuring ibest data iwarehouse isolutions. Firstly, we developed a data set generator for creating synthetic but near to real data; then in isynthesized idata, with ithe help of hand icoded Extraction, Transformation and Loading (ETL) routine, anomalies are classified. For the quality assurance of data for a Data warehouse and to give the idea of how important the iExtraction, iTransformation iand iLoading iis, some very important test cases were identified. After that, to ensure the quality of data, the procedures of automated testing iwere iembedded iin ihand icoded iETL iroutine. Statistical analysis was done and it revealed a big enhancement in the quality of data with the procedures of automated testing. It enhances the fact that automated testing gives promising results in the data warehouse quality. For effective and easy maintenance of distributed data,a novel architecture was proposed. Although the desired result of this research is achieved successfully and the objectives are promising, but still there's a need to validate the results with the real life environment, as this research was done in simulated environment, which may not always give the desired results in real life environment. Hence, the overall potential of the proposed architecture can be seen until it is deployed to manage the real data which is distributed globally.

Semi-Automated Roller Parameters Extraction from Terrestrial Lidar

2021 ◽  
Vol 87 (12) ◽  
pp. 879-890
Author(s):  
Sagar S. Deshpande ◽  
Mike Falk ◽  
Nathan Plooster
Keyword(s):  
Rotation Axis ◽  
Moving Average ◽  
Three Dimensional ◽  
Data Sets ◽  
Steel Mill ◽  
Data Set ◽  
Terrestrial Lidar ◽  
Two Dimensional Image ◽  
Average Rotation

Rollers are an integral part of a hot-rolling steel mill. They transport hot metal from one end of the mill to another. The quality of the steel highly depends on the surface quality of the rollers. This paper presents semi-automated methodologies to extract roller parameters from terrestrial lidar points. The procedure was divided into two steps. First, the three-dimensional points were converted to a two-dimensional image to detect the extents of the rollers using fast Fourier transform image matching. Lidar points for every roller were iteratively fitted to a circle. The radius and center of the fitted circle were considered as the average radius and average rotation axis of the roller, respectively. These parameters were also extracted manually and were compared to the measured parameters for accuracy analysis. The proposed methodology was able to extract roller parameters at millimeter level. Erroneously identified rollers were identified by moving average filters. In the second step, roller parameters were determined using the filtered roller points. Two data sets were used to validate the proposed methodologies. In the first data set, 366 out of 372 rollers (97.3%) were identified and modeled. The second, smaller data set consisted of 18 rollers which were identified and modelled accurately.

Estimation of Arctic O3 loss during winter 2006/2007 using data assimilation and comparison with a chemical transport model

2011 ◽  
Vol 137 (654) ◽  
pp. 118-128 ◽  
Author(s):  
O. A. Søvde ◽  
Y. J. Orsolini ◽  
D. R. Jackson ◽  
F. Stordal ◽  
I. S. A. Isaksen ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Using Data
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