scholarly journals An examination of the long-term CO records from MOPITT and IASI: comparison of retrieval methodology

2015 ◽  
Vol 8 (10) ◽  
pp. 4313-4328 ◽  
Author(s):  
M. George ◽  
C. Clerbaux ◽  
I. Bouarar ◽  
P.-F. Coheur ◽  
M. N. Deeter ◽  
...  
Keyword(s):  
A Priori ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Vertical Profiles ◽  
Advantages And Disadvantages ◽  
Atmospheric State ◽  
Priori Information ◽  
Total Column ◽  
Aircraft Data

Abstract. Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007–2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008–2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MOPITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori.

scholarly journals An examination of the long-term CO records from MOPITT and IASI: comparison of retrieval methodology

2015 ◽  
Vol 8 (4) ◽  
pp. 4095-4135 ◽  
Author(s):  
M. George ◽  
C. Clerbaux ◽  
I. Bouarar ◽  
P.-F. Coheur ◽  
M. N. Deeter ◽  
...  
Keyword(s):  
A Priori ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Vertical Profiles ◽  
Unexpected Events ◽  
Advantages And Disadvantages ◽  
Atmospheric State ◽  
Total Column ◽  
Aircraft Data

Abstract. Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another fifteen and more years of observations will be provided by the IASI/MetOp instrument series (2007–2023>). In order to study long term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved products are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a six year overlap period (2008–2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms, and second using a dedicated reprocessing of MOPITT CO profiles and columns based on the IASI a priori constraints. MOPITT v5T total columns are generally slightly higher over land (bias ranging from 0 to 13%) than IASI v20100815 data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15%) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to the less constrained variance-covariance matrix.

scholarly journals Carbon monoxide distributions from the IASI/METOP mission: evaluation with other space-borne remote sensors

2009 ◽  
Vol 9 (21) ◽  
pp. 8317-8330 ◽  
Author(s):  
M. George ◽  
C. Clerbaux ◽  
D. Hurtmans ◽  
S. Turquety ◽  
P.-F. Coheur ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
A Priori ◽  
Global Scale ◽  
Equatorial Region ◽  
Vertical Profiles ◽  
Atmospheric Infrared Sounder ◽  
Upper Troposphere ◽  
Remote Sensors ◽  
Atmospheric Sounding ◽  
Total Column

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp satellite measures carbon monoxide (CO) on a global scale, twice a day. CO total columns and vertical profiles are retrieved in near real time from the nadir radiance spectra measured by the instrument in the thermal infrared (TIR) spectral range. This paper describes the measurement vertical sensitivity and provides a first assessment of the capabilities of IASI to measure CO distributions. On the global scale, 0.8 to 2.4 independent pieces of information are available for the retrieval. At mid latitudes, the information ranges between 1.5 and 2, which enables the lower and upper troposphere to be distinguished, especially when thermal contrast is significant. Global distributions of column CO are evaluated with correlative observations available from other nadir looking TIR missions currently in operation: the Measurements of Pollution in the Troposphere (MOPITT) onboard TERRA, the Atmospheric Infrared Sounder (AIRS) onboard AQUA and the Tropospheric Emission Spectrometer (TES) onboard AURA. The IASI CO columns are compared with MOPITT, AIRS and TES CO columns, adjusted with the a priori, for three different months: August 2008, November 2008 and February 2009. On average, total column discrepancies of about 7% are found between IASI and the three other sounders in the Northern Hemisphere and in the equatorial region. However when strong CO concentrations are present, such as during fire events, these discrepancies can climb as high as 17%. Instrument specifications of IASI versus other missions are also discussed.

scholarly journals Carbon monoxide distributions from the IASI/METOP mission: evaluation with other space-borne remote sensors

2009 ◽  
Vol 9 (2) ◽  
pp. 9793-9822 ◽  
Author(s):  
M. George ◽  
C. Clerbaux ◽  
D. Hurtmans ◽  
S. Turquety ◽  
P.-F. Coheur ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
A Priori ◽  
Global Scale ◽  
Vertical Profiles ◽  
Atmospheric Infrared Sounder ◽  
Upper Troposphere ◽  
Remote Sensors ◽  
Atmospheric Sounding ◽  
Total Column ◽  
Co Concentrations

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp satellite measures carbon monoxide (CO) on a global scale, twice a day. CO total columns and vertical profiles are retrieved in near real time from the nadir radiance spectra measured by the instrument in the thermal infrared (TIR) spectral range. This paper describes the measurement vertical sensitivity of IASI. On the global scale, 0.8 to 2.4 independent pieces of information are available for the retrieval. At mid latitudes, the information ranges between 1.5 and 2, which enables the lower and upper troposphere to be distinguished, especially when thermal contrast is important. Global distributions of column CO are evaluated with correlative observations available from other nadir looking TIR missions currently in operation: the Measurements of Pollution in the Troposphere (MOPITT) onboard TERRA, the Atmospheric Infrared Sounder (AIRS) onboard AQUA and the Tropospheric Emission Spectrometer (TES) onboard AURA. On the global scale and on average, total column discrepancies ranging from 10 to 15% are found for latitudes above 45° N and lower than 15° S, but can reach 30% in cases of strong CO concentrations, e.g. when fires events occur. The choice of the a priori assumptions influences the retrievals and can explain some of the observed differences. Instrument specifications of IASI versus other missions are also discussed.

scholarly journals Clustering a Global Field of Atmospheric Profiles by Mixture Decomposition of Copulas

2005 ◽  
Vol 22 (10) ◽  
pp. 1445-1459 ◽  
Author(s):  
Mathieu Vrac ◽  
Alain Chédin ◽  
Edwin Diday
Keyword(s):  
A Priori ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Specific Humidity ◽  
Vertical Profiles ◽  
Copula Functions ◽  
Mixture Density ◽  
Temperature And Humidity ◽  
Priori Information ◽  
Humidity Profiles

Abstract This work focuses on the clustering of a large dataset of atmospheric vertical profiles of temperature and humidity in order to model a priori information for the problem of retrieving atmospheric variables from satellite observations. Here, each profile is described by cumulative distribution functions (cdfs) of temperature and specific humidity. The method presented here is based on an extension of the mixture density problem to this kind of data. This method allows dependencies between and among temperature and moisture to be taken into account, through copula functions, which are particular distribution functions, linking a (joint) multivariate distribution with its (marginal) univariate distributions. After a presentation of vertical profiles of temperature and humidity and the method used to transform them into cdfs, the clustering method is detailed and then applied to provide a partition into seven clusters based, first, on the temperature profiles only; second, on the humidity profiles only; and, third, on both the temperature and humidity profiles. The clusters are statistically described and explained in terms of airmass types, with reference to meteorological maps. To test the robustness and the relevance of the method for a larger number of clusters, a partition into 18 classes is established, where it is shown that even the smallest clusters are significant. Finally, comparisons with more classical efficient clustering or model-based methods are presented, and the advantages of the approach are discussed.

scholarly journals Retrieval of desert dust aerosol vertical profiles from IASI measurements in the TIR atmospheric window

2013 ◽  
Vol 6 (10) ◽  
pp. 2577-2591 ◽  
Author(s):  
S. Vandenbussche ◽  
S. Kochenova ◽  
A. C. Vandaele ◽  
N. Kumps ◽  
M. De Mazière
Keyword(s):  
Optical Depth ◽  
Radiative Forcing ◽  
Degrees Of Freedom ◽  
A Priori ◽  
Global Scale ◽  
Dust Aerosol ◽  
Vertical Profiles ◽  
Desert Dust ◽  
Dust Aerosols ◽  
Infrared Measurements

Abstract. Desert dust aerosols are the most prominent tropospheric aerosols, playing an important role in the earth's climate. However, their radiative forcing is currently not known with sufficient precision to even determine its sign. The sources of uncertainty are multiple, one of them being a poor characterisation of the dust aerosol's vertical profile on a global scale. In this work, we tackle this scientific issue by designing a method for retrieving dust aerosol vertical profiles from Thermal Infrared measurements by Infrared Atmospheric Sounding Interferometer (IASI) instruments onboard the Metop satellite series. IASI offers almost global coverage twice a day, and long (past and future) time series of radiances, therefore being extremely well suited for climate studies. Our retrieval follows Rodger's formalism and is based on a two-step approach, treating separately the issues of low altitude sensitivity and difficult a priori definition. We compare our results for a selected test case above the Atlantic Ocean and North Africa in June 2009, with optical depth data from MODIS, aerosol absorbing index from GOME-2 and OMI, and vertical profiles of extinction coefficients from CALIOP. We also use literature information on desert dust sources to interpret our results above land. Our retrievals provide perfectly reasonable results in terms of optical depth. The retrieved vertical profiles (with on average 1.5 degrees of freedom) show most of the time sensitivity down to the lowest layer, and agree well with CALIOP extinction profiles for medium to high dust optical depth. We conclude that this new method is extremely promising for improving the scientific knowledge about the 3-D distribution of desert dust aerosols in the atmosphere.

scholarly journals Retrieval of desert dust aerosol vertical profiles from IASI measurements in the TIR atmospheric window

2013 ◽  
Vol 6 (3) ◽  
pp. 4511-4550
Author(s):  
S. Vandenbussche ◽  
S. Kochenova ◽  
A. C. Vandaele ◽  
N. Kumps ◽  
M. De Mazière
Keyword(s):  
Optical Depth ◽  
Radiative Forcing ◽  
Degrees Of Freedom ◽  
A Priori ◽  
Global Scale ◽  
Test Case ◽  
Vertical Profiles ◽  
Desert Dust ◽  
Dust Aerosols ◽  
Infrared Measurements

Abstract. Desert dust aerosols are the most prominent tropospheric aerosols, playing an important role in the Earth's climate. However, their radiative forcing is currently not known with sufficient precision to even determine its sign. The sources of uncertainty are multiple, one of them being a poor characterisation of dust aerosols vertical profile on a global scale. In this work, we tackle this scientific issue by designing a method for retrieving dust aerosols vertical profiles from Thermal Infrared measurements by IASI instruments onboard the Metop satellite series. IASI offers almost global coverage twice a day, and long (past and future) time series of radiances, being therefore extremely well-suited for climate studies. Our retrieval follows Rodger's formalism and is based on a two-steps approach, treating separately the issues of low altitude sensitivity and of difficult a priori definition. We compare our results for a selected test-case, above the Atlantic Ocean and North Africa in June 2009, with optical depth data from MODIS, aerosol absorbing index from GOME-2 and OMI, and vertical profiles of extinction coefficients from CALIOP. We also use literature information on desert dust sources to interpret our results above land. Our retrievals provide perfectly reasonable results in terms of optical depth. The retrieved vertical profiles (with on average 1.5 degrees of freedom) show most of the time sensitivity down to the lowest layer, and agree well with CALIOP extinction profiles for medium to high dust optical depth. We conclude that this new method is extremely promising for improving the scientific knowledge about the 3-D distribution of desert dust aerosols in the atmosphere.

scholarly journals Smoothing error pitfalls

2014 ◽  
Vol 7 (4) ◽  
pp. 3301-3319 ◽  
Author(s):  
T. von Clarmann
Keyword(s):  
Covariance Matrix ◽  
Error Propagation ◽  
A Priori ◽  
A Priori Information ◽  
Atmospheric Variability ◽  
True State ◽  
Statistical Sense ◽  
Atmospheric State ◽  
The Difference ◽  
Priori Information

Abstract. The difference due to the content of a priori information between a constrained retrieval and the true atmospheric state is usually represented by the so-called smoothing error. In this paper it is shown that the concept of the smoothing error is questionable because it is not compliant with Gaussian error propagation. The reason for this is that the smoothing error does not represent the expected deviation of the retrieval from the true state but the expected deviation of the retrieval from the atmospheric state sampled on an arbitrary grid, which is itself a smoothed representation of the true state. The idea of a sufficiently fine sampling of this reference atmospheric state is untenable because atmospheric variability occurs on all scales, implying that there is no limit beyond which the sampling is fine enough. Even the idealization of infinitesimally fine sampling of the reference state does not help because the smoothing error is applied to quantities which are only defined in a statistical sense, which implies that a finite volume of sufficient spatial extent is needed to meaningfully talk about temperature or concentration. Smoothing differences, however, which play a role when measurements are compared, are still a useful quantity if the involved a priori covariance matrix has been evaluated on the comparison grid rather than resulting from interpolation. This is, because the undefined component of the smoothing error, which is the effect of smoothing implied by the finite grid on which the measurements are compared, cancels out when the difference is calculated.

A comparative geochemical study of Mars and Earth basalt petrogenesis

2013 ◽  
Vol 50 (1) ◽  
pp. 78-93 ◽  
Author(s):  
John D. Greenough ◽  
Avee Ya’acoby
Keyword(s):  
Incompatible Element ◽  
A Priori ◽  
Correlation Coefficients ◽  
Small Sample ◽  
Geochemical Data ◽  
Data Set ◽  
Element Ratios ◽  
Highly Correlated ◽  
Small Sample Sizes ◽  
Priori Information

Geochemical data, from the Mars Meteorite Compendium web site, for 13 basaltic meteorites, possibly from only four localities on Mars, are used to study Martian petrogenetic processes. To achieve this goal, an exploratory data analysis technique, multidimensional scaling (MDS), is used to quantitatively assess the relative behavior (measured with correlation coefficients) of 160 incompatible element ratios involving 25 “trace” elements. The ratios behave as in Earth basalts, suggesting that relative element incompatibility is similar in both planets. Because mineralogy controls incompatibility, the mineralogy of Earth and Mars mantles appears similar. In addition, results suggest that ratios involving elements with highly different incompatibility (e.g., La/Yb) are dominantly controlled by % melting. Plots of SiO2 (pressure proxy; decreases with increasing pressure) versus La/Yb and Nb/Y (decrease as melting increases) imply that Mars basalts, like Earth tholeiites, reflect high percentages of melting, but opposite to Earth, % melting appears to increase with increasing pressure. The moderately correlated, positive, SiO2–La/Yb Mars relationship parallels highly correlated Lunar KREEP data and contrasts with Earth’s negative correlation. The positive relationships may reflect restricted mantle convection in some (Mars and the Moon are smaller) planetary bodies. Using similarly incompatible element ratios that are sensitive to source composition, to compare Mars and Earth with MDS, Mars sources most resemble depleted Earth mantle. Additionally, these ratios group Mars sources into enriched, depleted, and intermediate types. The groupings are the same as those suggested by isotopes, and we conclude that trace element data support the hypothesis that chemical variation in Mars may reflect crystallization of a Mars magma ocean. The natural patterns in ratios and samples revealed using MDS, which has no a priori information about relationships, support integrity of the geochemical data set, despite potential shortcomings such as small sample sizes, alteration, and weathering. However, whether the meteorites are representative of Mars as a whole is unknown.

The ILRS Contribution to ITRF2020

2021 ◽  
Author(s):  
Vincenza Luceri ◽  
Erricos C. Pavlis ◽  
Antonio Basoni ◽  
David Sarrocco ◽  
Magdalena Kuzmicz-Cieslak ◽  
...  
Keyword(s):  
Time Series ◽  
Tracking System ◽  
A Priori ◽  
Systematic Errors ◽  
Novel Approach ◽  
Priori Information ◽  
The Stability ◽  
The Individual ◽  
Stability And Consistency

<p>The International Laser Ranging Service (ILRS) contribution to ITRF2020 has been prepared after the re-analysis of the data from 1993 to 2020, based on an improved modeling of the data and a novel approach that ensures the results are free of systematic errors in the underlying data. This reanalysis incorporates an improved “target signature” model (CoM) that allows better separation of true systematic error of each tracking system from the errors in the model describing the target’s signature. The new approach was developed after the completion of ITRF2014, the ILRS Analysis Standing Committee (ASC) devoting almost entirely its efforts on this task. The robust estimation of persistent systematic errors at the millimeter level permitted the adoption of a consistent set of long-term mean corrections for data collected in past years, which are now applied a priori (information provided by the stations from their own engineering investigations are still taken into consideration). The reanalysis used these corrections, leading to improved results for the TRF attributes, reflected in the resulting new time series of the TRF origin and especially in the scale. Seven official ILRS Analysis Centers computed time series of weekly solutions, according to the guidelines defined by the ILRS ASC. These series were combined by the ILRS Combination Center to obtain the official ILRS product contribution to ITRF2020.</p><p>The presentation will provide an overview of the analysis procedures and models, and it will demonstrate the level of improvement with respect to the previous ILRS product series; the stability and consistency of the solution are discussed for the individual AC contributions and the combined SLR time series.</p>

scholarly journals Application of Bayesian Approach to Reduce the Uncertainty in Expert Judgments by Using a Posteriori Mean Function

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2455
Author(s):  
Irina Vinogradova-Zinkevič
Keyword(s):  
Bayesian Method ◽  
A Priori ◽  
Expert Judgment ◽  
A Posteriori ◽  
Personal Qualities ◽  
Data Source ◽  
Priori Information ◽  
Mean Function ◽  
Long Term Experience

Much applied research uses expert judgment as a primary or additional data source, thus the problem solved in this publication is relevant. Despite the expert’s experience and competence, the evaluation is subjective and has uncertainty in it. There are various reasons for this uncertainty, including the expert’s incomplete competence, the expert’s character and personal qualities, the expert’s attachment to the opinion of other experts, and the field of the task to be solved. This paper presents a new way to use the Bayesian method to reduce the uncertainty of an expert judgment by correcting the expert’s evaluation by the a posteriori mean function. The Bayesian method corrects the expert’s evaluation, taking into account the expert’s competence and accumulated long-term experience. Since the paper uses a continuous case of the Bayesian formula, perceived as a continuous approximation of experts’ evaluations, this is not only the novelty of this work, but also a new result in the theory of the Bayesian method and its application. The paper investigates various combinations of the probability density functions of a priori information and expert error. The results are illustrated by the example of the evaluation of distance learning courses.

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