The global and multi-annual MUSICA IASI {H&lt;sub&gt;2&lt;/sub&gt;O, &lt;i&gt;δ&lt;/i&gt;D} pair dataset

Abstract. We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to December 2020 with global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1500 million individually processed observations. The retrievals are most sensitive to variations in {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but higher latitudes also show a considerable amount of reliable data. Exemplary time series over the tropical Atlantic and West Africa are chosen to illustrate the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studies. Furthermore, in order to facilitate the application of this rather comprehensive MUSICA IASI {H2O, δD} pair dataset (referred to as Level-2), we additionally provide the data in a re-gridded and simplified format (Level-3) with focus on the quality-filtered {H2O, δD} pairs in the free troposphere. A technical documentation for guiding the use of both datasets is attached as the Supplement. Finally, the Level-2 dataset is referenced with the DOI https://doi.org/10.35097/415 (Diekmann et al., 2021a) and the Level-3 dataset with DOI https://doi.org/10.35097/495 (Diekmann et al., 2021b).

Download Full-text

The MUSICA IASI {H2O, δD} pair product

10.5194/essd-2021-87 ◽

2021 ◽

Author(s):

Christopher J. Diekmann ◽

Matthias Schneider ◽

Benjamin Ertl ◽

Frank Hase ◽

Omaira García ◽

...

Keyword(s):

A Priori ◽

Optimal Estimation ◽

Reliable Data ◽

Tropical Atlantic ◽

Atmospheric Moisture ◽

A Posteriori ◽

Infrared Sensor ◽

Atmospheric Sounding ◽

Dry Conditions ◽

Global Coverage

Abstract. We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) onboard the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but also for higher latitudes there is a considerable amount of reliable data. Exemplary time-series over the Tropical Atlantic and West Africa are chosen to illustrates the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studiess. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021).

Download Full-text

Ozone profile smoothness as a priori information in the inversion of limb measurements

Annales Geophysicae ◽

10.5194/angeo-22-3411-2004 ◽

2004 ◽

Vol 22 (10) ◽

pp. 3411-3420 ◽

Cited By ~ 42

Author(s):

V. F. Sofieva ◽

J. Tamminen ◽

H. Haario ◽

E. Kyrölä ◽

M. Lehtinen

Keyword(s):

A Priori ◽

Optimal Estimation ◽

Maximum A Posteriori ◽

A Posteriori ◽

A Priori Information ◽

Ozone Profile ◽

Stellar Occultation ◽

Atmospheric Profiles ◽

Priori Information ◽

Typical Measurement

Abstract. In this work we discuss inclusion of a priori information about the smoothness of atmospheric profiles in inversion algorithms. The smoothness requirement can be formulated in the form of Tikhonov-type regularization, where the smoothness of atmospheric profiles is considered as a constraint or in the form of Bayesian optimal estimation (maximum a posteriori method, MAP), where the smoothness of profiles can be included as a priori information. We develop further two recently proposed retrieval methods. One of them - Tikhonov-type regularization according to the target resolution - develops the classical Tikhonov regularization. The second method - maximum a posteriori method with smoothness a priori - effectively combines the ideas of the classical MAP method and Tikhonov-type regularization. We discuss a grid-independent formulation for the proposed inversion methods, thus isolating the choice of calculation grid from the question of how strong the smoothing should be. The discussed approaches are applied to the problem of ozone profile retrieval from stellar occultation measurements by the GOMOS instrument on board the Envisat satellite. Realistic simulations for the typical measurement conditions with smoothness a priori information created from 10-years analysis of ozone sounding at Sodankylä and analysis of the total retrieval error illustrate the advantages of the proposed methods. The proposed methods are equally applicable to other profile retrieval problems from remote sensing measurements.

Download Full-text

Data Fitting

10.1093/oso/9780199662104.003.0011 ◽

2017 ◽

Author(s):

Kelly Chance ◽

Randall V. Martin

Keyword(s):

A Priori ◽

Optimal Estimation ◽

Data Fitting ◽

Line Of Sight ◽

Model Parameters ◽

Nonlinear Fitting ◽

Atmospheric Data ◽

Atmospheric Sounding ◽

Chi Squared ◽

Correlated Parameters

This chapter explores several of the most common and useful approaches to atmospheric data fitting as well as the process of using air mass factors to produce vertical atmospheric column abundances from line-of-sight slant columns determined by data fitting. An atmospheric spectrum or other type of atmospheric sounding is usually fitted to a parameterized physical model by minimizing a cost function, usually chi-squared. Linear fitting, when the model of the measurements is linear in the model parameters is described, followed by the more common nonlinear fitting case. For nonlinear fitting, the standard Levenberg-Marquardt method is described, followed by the use of optimal estimation, one of several retrieval methods that make use of a priori information to providing regularization for the solution. In the context of optimal estimation, weighting functions, contribution functions, and averaging kernels are described. The Twomey-Tikhonov regularization procedure is presented. Correlated parameters, with the important example of Earth’s atmospheric ozone, are discussed.

Download Full-text

Level 2 processor and auxiliary data for ESA Version 8 final full mission analysis of MIPAS measurements on ENVISAT

10.5194/amt-2021-235 ◽

2021 ◽

Author(s):

Piera Raspollini ◽

Enrico Arnone ◽

Flavio Barbara ◽

Massimo Bianchini ◽

Bruno Carli ◽

...

Keyword(s):

Spectroscopic Data ◽

A Priori ◽

Michelson Interferometer ◽

Temporal Stability ◽

Optimal Estimation ◽

Initial Guess ◽

Atmospheric Composition ◽

Data Set ◽

Auxiliary Data ◽

Level 2

Abstract. High quality long-term data sets of altitude-resolved measurements of the atmospheric composition are important because they can be used both to study the evolution of the atmosphere and as a benchmark for future missions. For the final ESA reprocessing of MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) on ENVISAT (ENViromental SATellite) data, numerous improvements were implemented in the level 2 (L2) processor Optimised Retrieval Model (ORM) version 8.22 (V8) and its auxiliary data. The implemented changes involve all aspects of the processing chain, from the modelling of the measurements with the handling of the horizontal inhomogeneities along the line of sight to the use of the Optimal Estimation for retrieving the minor species, from a more sensitive approach to detect the spectra affected by clouds to a refined method for identifying low quality products. Improvements in the modelling of the measurements were obtained also with an update of the used spectroscopic data and of the databases providing the a priori knowledge of the atmosphere. The HITRAN_mipas_pf4.45 spectroscopic database was finalised with new spectroscopic data verified with MIPAS measurements themselves, while recently measured cross-sections were used for the heavy molecules. The so-called IG2 data set, containing the climatology used by MIPAS L2 processor to generate the initial guess and interfering species profiles when the retrieved profiles from previous scans are not available, was improved taking into account the diurnal variation of the profiles defined using climatologies from both measurements and models. Horizontal gradients were generated using ECMWF ERA-Interim data closest in time and space to the MIPAS data. Further improvements in the L2 V8 products derived from the use of the L1b V8 products, which were upgraded to reduce the instrumental temporal drift and to handle the abrupt changes in the calibration gain. The improvements introduced into the ORM V8 L2 processor and its upgraded auxiliary data, together with the use of the L1b V8 products, lead to the generation of the MIPAS L2 V8 products that are characterised by an increased accuracy, better temporal stability, and a greater number of retrieved species.

Download Full-text

The MUSICA IASI CH4 and N2O products and their comparison to HIPPO, GAW and NDACC FTIR references

Atmospheric Measurement Techniques ◽

10.5194/amt-11-4171-2018 ◽

2018 ◽

Vol 11 (7) ◽

pp. 4171-4215 ◽

Cited By ~ 5

Author(s):

Omaira E. García ◽

Matthias Schneider ◽

Benjamin Ertl ◽

Eliezer Sepúlveda ◽

Christian Borger ◽

...

Keyword(s):

Water Vapour ◽

Reference Data ◽

A Priori ◽

Long Term Evolution ◽

High Latitudes ◽

Free Troposphere ◽

A Posteriori ◽

Term Evolution ◽

Ch4 And N2o

Abstract. This work presents the methane (CH4) and nitrous oxide (N2O) products as generated by the IASI (Infrared Atmospheric Sounding Interferometer) processor developed during the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor retrieves CH4 and N2O with different water vapour and water vapour isotopologues (as well as HNO3) and uses a single a priori data set for all the retrievals (no variation in space and time). Firstly, the characteristics and errors of the products are analytically described. Secondly, the products are comprehensively evaluated by comparisons to the following reference data measured by different techniques and from different platforms as follows: (1) aircraft CH4 and N2O profiles from the five HIAPER Pole-to-Pole Observation (HIPPO) missions; (2) continuous in situ CH4 and N2O observations performed between 2007 and 2017 at subtropical and mid-latitude high-mountain observatories (Izaña Atmospheric Observatory and Jungfraujoch, respectively) in the framework of the WMO–GAW (World Meteorological Organization–Global Atmosphere Watch) programme; (3) ground-based FTIR (Fourier-transform infrared spectrometer) measurements made between 2007 and 2017 in the framework of the NDACC (Network for the Detection of Atmospheric Composition Change) at the subtropical Izaña Atmospheric Observatory, the mid-latitude station of Karlsruhe and the Kiruna polar site.The theoretical estimations and the comparison studies suggest a precision for the N2O and CH4 retrieval products of about 1.5–3 % and systematic errors due to spectroscopic parameters of about 2 %. The MUSICA IASI CH4 data offer a better sensitivity than N2O data. While for the latter the sensitivity is mainly limited to the UTLS (upper troposphere–lower stratosphere) region, for CH4 we are able to prove that at low latitudes the MUSICA IASI processor can detect variations that take place in the free troposphere independently from the variations in the UTLS region. We demonstrate that the MUSICA IASI data qualitatively capture the CH4 gradients between low and high latitudes and between the Southern Hemisphere and Northern Hemisphere; however, we also find an inconsistency between low- and high-latitude CH4 data of up to 5 %. The N2O latitudinal gradients are very weak and cannot be detected. We make comparisons over a 10-year time period and analyse the agreement with the reference data on different timescales. The MUSICA IASI data can detect day-to-day signals (only in the UTLS), seasonal cycles and long-term evolution (in the UTLS and for CH4 also in the free troposphere) similar to the reference data; however, there are also inconsistencies in the long-term evolution connected to inconsistencies in the used atmospheric temperature a priori data.Moreover, we present a method for analytically describing the a posteriori-calculated logarithmic-scale difference of the CH4 and N2O retrieval estimates. By correcting errors that are common in the CH4 and N2O retrieval products, the a posteriori-calculated difference can be used for generating an a posteriori-corrected CH4 product with a theoretically better precision than the original CH4 retrieval products. We discuss and evaluate two different approaches for such a posteriori corrections. It is shown that the correction removes the inconsistencies between low and high latitudes and enables the detection of day-to-day signals also in the free troposphere. Furthermore, they reduce the impact of short-term atmospheric dynamics, which is an advantage, because respective signals are presumably hardly comparable to model data. The approach that affects the correction solely on the scales on which the errors dominate is identified as the most efficient, because it reduces the inconsistencies and errors without removing measurable real atmospheric signals. We give a brief outlook on a possible usage of this a posteriori-corrected MUSICA IASI CH4 product in combination with inverse modelling.

Download Full-text

Retrieval of macrophysical cloud parameters from MIPAS: algorithm description and preliminary validation

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-3-3877-2010 ◽

2010 ◽

Vol 3 (4) ◽

pp. 3877-3906

Author(s):

J. Hurley ◽

A. Dudhia ◽

R. G. Grainger

Keyword(s):

Atmospheric Chemistry ◽

A Priori ◽

Michelson Interferometer ◽

Optimal Estimation ◽

Additional Information ◽

The Past ◽

Cloud Parameters ◽

Preliminary Validation ◽

Atmospheric Sounding ◽

Cloud Top Temperature

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard ENVISAT has the potential to be particularly useful for studying high, thin clouds, which have been difficult to observe in the past. This paper details the development, implementation and testing of an optimal-estimation-type retrieval for three macrophysical cloud parameters (cloud top height, cloud top temperature and cloud extinction coefficient) from infrared spectra measured by MIPAS, employing additional information derived to improve the choice of a priori. The retrieval is applied and initially validated on MIPAS data. From application to MIPAS data, the retrieved cloud top heights are assessed to be accurate to within 50 m, the cloud top temperatures to within 0.5 K and extinction coefficients to within a factor of 15%. This algorithm has been adopted by the European Space Agency's ''MIPclouds'' project, which itself recognises the potential of MIPAS beyond monitoring atmospheric chemistry and seeks to study clouds themselves rigorously using MIPAS.

Download Full-text

Historical text archives and prosopography: the COEL database system

History and Computing ◽

10.3366/hac.1998.10.1-3.57 ◽

1998 ◽

Vol 10 (1-3) ◽

pp. 57-72 ◽

Cited By ~ 4

Author(s):

K. S. B. Keats-Rohan

Keyword(s):

Research Tool ◽

Direct Access ◽

Specific Situation ◽

Core Data ◽

Secondary Sources ◽

The Core ◽

Level 3 ◽

Full Discussion ◽

Available Information ◽

Level 2

The COEL database and database software, a combined reference and research tool created by historians for historians, is presented here through Screenshots illustrating the underlying theoretical model and the specific situation to which that has been applied. The key emphases are upon data integrity, and the historian's role in interpreting and manipulating what is often contentious data. From a corpus of sources (Level 1) certain core data are extracted for separate treatment at an interpretive level (Level 3), based upon a master list of the core data (Level 2). The core data are interdependent: each record in Level 2 is of interest in itself; and it either could or should be associated with an(other) record(s) as a specific entity. Sometimes the sources are ambiguous and the association is contentious, necessitating a probabilty-coding approach. The entities created by the association process can then be treated at a commentary level, introducing material external to the database, whether primary or secondary sources. A full discussion of the difficulties is provided within a synthesis of available information on the core data. Direct access to the source texts is only ever a mouse click away. Fully query able, COEL is formidable look-up and research tool for users of all levels, who remain free to exercise an alternative judgement on the associations of the core data. In principle, there is no limit on the type of text or core data that could be handled in such a system.

Download Full-text