Optimierung der Parameterauswahl für ein operationelles off-line-Retrieval von Spurengasvertikalprofilen aus MIPAS-Daten

“Optimisation of the choice of parameters for an operational off-line retrieval of vertical profiles of trace gases from MIPAS data”. Since March 2002 the environment satellite ENVISAT is operational. ENVISAT carries a series of instruments used for remote sensing the earth atmosphere. MIPAS, as one of those instruments is, due to its conception as a limb sounding infrared spectrometer, intended to provide new insights in the chemical processes of the middle atmosphere. To achieve this MIPAS measures emissions of trace gases like H2O, O3, CH4, NO2, N2O, HNO3. Additionally MIPAS acquires global pressure and temperature profiles. Vertical profiles of trace gases are computed from calibrated measurements in the processing chain by an iterative calculating scheme (retrieval). To this measurements are compared with simulated spectra from a forward model. At each comparison modelling parameters are systematically adjusted until an agreement in the compared quantities is reached, which lies within the boundaries of some previously defined criteria. Improvements in the retrieval scheme are possible in three categories: first, adjustments in the side constraints (regularisation), which divide the mathematical possible solutions from the physical reasonable, are conceivable. Second, adjustments in the handling of certain systematic errors are necessary and finally, one is interested in eliminating measurements which have become useless due to cloud influences. To obtain a measure for the improvements, some criteria are defined and discussed in this work, with which it is possible to compare differently parameterised retrievals with regard to their quality. These criteria are: height resolution (averaging kernel), information content and degrees of freedom, as well as common quantities like root mean square. The subject regularisation is being discussed by the means of a comparison between a newly developed approach (HoMa), a not yet with operational trace gas retrievals used maximum entropy method (MEM2) and the standard methods Optimal Estimation and Tikhonov. It can be shown, that the alternative methods have massive advantages compared with the standard methods in terms of the above defined criteria. This also is true for aspects like transparency, diagnostic options and quality of the retrieved profiles. Especially the results of MEM2 have to be pointed out, because it does not use a priori knowledge. The treatment of systematic errors shows, that this is an essential part of every retrieval. The results of computations with simulated data while using the corrections show tremendous improvements compared to results of not corrected computations. The part which deals with the consideration of cloud influences in measurements shows the advancement of an established idea. A detailed analysis of cloud indices enables to rescue measurements which otherwise would have been parcelled out for security reasons. This may lead to gather additionally knowledge about tropospheric regions from MIPAS measurements. A comparison of results of the work with independent results from the ROSE-model delivers promising consistence.Seit März 2002 ist der Umweltsatellit ENVISAT erfolgreich im Einsatz. ENVISAT trägt eine Reihe von Messinstrumenten zur Fernerkundung der Erdatmosphäre. MIPAS, als eines dieser Instrumen-te, soll durch seine Konzeption als horizontal sondierendes Infrarotspektrometer helfen, die Kenntnisse über die chemischen Zusammenhänge in der mittleren Atmosphäre zu erweitern. Dazu misst MIPAS Emissionen von Spurengasen wie H2O, O3, CH4, NO2, N2O, HNO3. Weiterhin er-mittelt MIPAS globale Druck- und Temperaturprofile. Aus den kalibrierten Messungen werden in der Prozessierungskette durch iterative Rechenverfah-ren (Retrievals) Vertikalprofile von Spurengasen erzeugt. Hierzu werden die Messungen mit simu-lierten Spektren eines Vorwärtsmodells verglichen. Bei jedem Vergleich werden Modellierungspa-rameter systematisch geändert bis es zu einer Übereinstimmung mit den Vergleichsgrößen kommt, die innerhalb der Vorgaben festgelegter Abbruchkriterien liegt. Verbesserungen im Rechenverfah-ren sind zum einen durch Anpassungen in den Nebenbedingungen (Regularisierung), die nötig sind, um die mathematisch möglichen Lösungen der Rechnung von den physikalisch sinnvollen zu trennen, möglich. Zum anderen sind Anpassungen in der Behandlung bestimmter systematischer Fehler notwendig und schließlich ist man daran interessiert, durch Wolkeneinflüsse unbrauchbare Messungen auszusondern. Um ein Maß für die Verbesserungen zu erhalten, werden in dieser Arbeit Kriterien definiert und diskutiert, anhand derer verschieden parametrisierte Rechenverfahren hinsichtlich ihrer Güte ver-glichen werden können. Die Kriterien sind: Höhenauflösung (Averaging Kernel), Informationsge-halt und Anzahl der Freiheitsgrade sowie herkömmliche Kriterien wie Standardabweichungen. Das Thema Regularisierung wird durch eine Vergleichsstudie zwischen einem selbst entwickelten Ansatz (Höhenabhängige Matrix, HoMa), einem noch nicht bei operationellen Spurengasretrievals eingesetzten Verfahren (Maximale-Entropie-Methode, MEM2) und den Standardmethoden Opti-mal Estimation und Tikhonov behandelt. Es stellt sich heraus, dass die spezialisierten Verfahren HoMa und MEM2 gegenüber den etablierten Verfahren unter Zugrundelegung der oben erwähn-ten Kriterien Vorteile bieten, was Transparenz der Verfahren, Diagnosemöglichkeiten und Qualität der erhaltenen Profile angeht. Besonders hervorzuheben sind die Ergebnisse von MEM2, das ohne Vorwissen (a priori-Annahmen) auskommt. Bei der Behandlung systematischer Fehler zeigt sich, dass es sich hierbei um einen unverzichtbaren Bestandteil jedes Retrievals handelt. Die Rechnungen mit Simulationsdaten ergeben bei Hinzunah-me der Korrekturterme dramatische Verbesserungen in den Ergebnissen, wenn systematische Feh-ler vorliegen. Der Komplex, der sich mit der Berücksichtigung von Wolken in den Messungen befasst, zeigt die Weiterentwicklung einer etablierten Idee. Durch genaue Analyse von Wolkenindizes lassen sich Messungen retten, die andernfalls als durch Wolken kontaminiert ausgesondert worden wären. Die-ses Verfahren kann dazu beitragen, wichtige Erkenntnisse aus den unteren Atmosphäreschichten zu erhalten. Ein Vergleich der Ergebnisse der Arbeit mit unabhängigen Ergebnissen des ROSE-Modells zeigt viel versprechende Übereinstimmungen

Precipitation in the Mediterranean Region Observed with TRMM Microwave Data

Self-organized networks require some mechanism to ensure cooperation and fairness in the face of individual utility maximizing users and potential malicious attacks. Otherwise, network performance can be seriously deteriorated. One promising approach are decentralized reputation systems. However, these are vulnerable to users with an interest in passing on false information. Robustness against liars has not yet been analyzed in detail. In this paper, we provide a first step to the robustness analysis of a reputation system based on the deviation test as introduced in [6]. Users accept second hand information only if this does not differ too much from their reputation values. We show that the system exhibits a phase transition: In the subcritical regime, the reputation system is robust and the lying has no effect. In the supercritical regime, the lying does have an impact. We obtain the exact critical values via a mean field approach. We then use explicit computation to verify the mean field results. Thus, we can give conditions under which the deviation test makes the reputation system robust. We also obtain quantitative results on what goes wrong in the supercritical regime

Shape-dependent regularization for the retrieval of atmospheric state parameter profiles

An adaptive regularization approach for the retrieval of vertical state parameter profiles is presented

Use of a Maximum Entropy Method as a Regularization Technique during the Retrieval of Trace Gas Profiles from Limb Sounding Measurements

We compare regularization techniques during the retrieval of trace gas profiles from limb sounding measurements. In particular, we investigate the performance of a dedicated maximum entropy method

Precipitation Estimation: From the RAO to EURAINSAT and Beyond

The key objective of the project “Use of the MSG SEVIRI channels in a combined SSM/I, TRMM and geostationary IR method for rapid updates of rainfall” is the development of algorithms for rapid-update of satellite rainfall estimations at the geostationary (GEO) scale. The new channels available with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer in the visible (VIS), near infrared (NIR) and infrared (IR) portions of the spectrum provide new insights into the microphysical and dynamic structure of precipitating clouds thus allowing for a more precise identification of precipitation intensities. Passive microwave (PMW) radiometers on board low Earth orbiting (LEO) satellites are used to determine information on the vertical cloud structure. Key features of the new method(s) are: 1. Microphysical characterization of precipitating clouds with VIS/IR sensors; 2. Creation of cloud microphysical and radiative databases from cloud model outputs and aircraft penetrations; 3. Tuning of PMW algorithms for different cloud systems (maritime, continental, convective, stratiform,...); 4. Combination of data from different algorithms and application to a rapid update cycle at the GEO scale. The project provided the background for EURAINSAT “European Satellite Rainfall Estimation and Monitoring at the Geostationary Scale”, a research project co-funded by the Energy, Environment and Sustainable Development Programme of the European Commission within the topic “Development of generic Earth observation technologies”. The project web site is accessible at http://www.isac.cnr.it/~eurainsat/. Moreover, it has represented the European framework for the launch of the International Precipitation Working Group (IPWG)