U. Grabowski

Mixing Processes during the Antarctic Vortex Split in September–October 2002 as Inferred from Source Gas and Ozone Distributions from ENVISAT–MIPAS

Abstract In late September 2002, an Antarctic major stratospheric warming occurred, which led to a strong distortion of the southern polar vortex and to a split of its mid- and upper-stratospheric parts. Such an event had never before been observed since the beginning of regular Antarctic stratospheric temperature observations in the 1950s. The split is studied by means of nonoperational level-2 CH4, N2O, CFC-11, and O3 data, retrieved at the Institute for Meteorology and Climate Research Karlsruhe (IMK) from high-resolution atmospheric limb emission spectra from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the European research satellite, Environmental Satellite (ENVISAT). Retrieved horizontal and vertical distributions of CH4 and N2O show good consistency with potential vorticity fields of the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis for the entire period under investigation, even for fine structures such as vortex filaments. Tracer correlatio...

A blind test retrieval experiment for infrared limb emission spectrometry

The functionality and characteristics of six different data processors (i.e., retrieval codes in their actual software and hardware environment) for analysis of high-resolution limb emission infrar ...

Remote sensing of the middle atmosphere with MIPAS

On 1 March 2002 the Envisat research satellite has been launched successfully into its sun-synchronous orbit. One of its instruments for atmospheric composition sounding is the Michelson Interferometer for Passive Atmospheric Sounding, a limb-scanning mid-infrared Fourier transform spectrometer. Different scientific objectives of data users require different approaches to data analysis, which are discussed. A strategy on how to validate the involved algorithms and relevant strategies is presented.

Tomographic retrieval of atmospheric parameters from infrared limb emission observations

Typical inversion of limb-sounding measurements assumes local horizontal homogeneity of the atmosphere. This simplification corresponds to spectral radiance errors that can exceed the noise level of a typical infrared instrument by a factor of 10 and causes errors in retrieved state parameters. To avoid these errors and to take the horizontal structure of the atmosphere into account, a two-dimensional (2D) tomographic sequential estimation approach is described. Application to temperature retrievals from simulated measurements yields typical retrieval errors of the order of 1 K, and a one-dimensional retrieval with the same synthetic measurements shows differences to the true values up to 10 K in regions with strong horizontal inhomogeneities. The horizontal resolution of the 2D retrieval is even better (up to 40 km) than the horizontal tangent point spacing.

On the role of non-random errors in inverse problems in radiative transfer and other applications

Abstract The inverse solution of the radiative transfer equation—which here serves as an example for the more general case of multi-dimensional inverse problems—is affected by measurement noise and by uncertain model parameters. We propose to transform the model parameter uncertainties into the measurement domain and include related signal uncertainties in the measurement covariance matrix. The solution of the inverse problem where the Jacobian is weighted by this extended covariance matrix rather than by the pure measurement covariance matrix is shown to be equivalent to an optimal estimation solution where the uncertain parameter is treated as an additional unknown parameter. The advantage of the proposed approach is that, contrary to the optimal estimation approach, the number of fit variables does not increase with the number of uncertain model parameters.

On the Application and Performance of MongoDB for Climate Satellite Data

Analyses in climate research typically operate on large datasets stored in file hierarchies. However, e.g. Indexing, meta-data search and replication is challenging with this approach. A new approach is to store and index datasets in large, distributed databases. In order to demonstrate the performance improvement, we utilized the so-called general matching problem between measurements of two satellites that differ in orbits and measurement cycles. For comparison purpose the measurements are matched within a specified maximum spatial and time offset constraint. We describe the steps from a single-threaded approach using a SQL database to a multi-threaded approach using the NoSQL database MongoDB. The performance as well as limitations on CPU and I/O are evaluated and discussed for each approach. The performance has been improved up to a factor of 46 using 11 threads on a 12-core system.

Early IMK/IAA MIPAS/ENVISAT results

On March 1, 2002 the space-borne limb viewing mid-infrared high-resolution Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) has been brought on board the ENVISAT satellite into a polar sun-synchroneous orbit. Although the level-1 testing and validation phase has not been finished, ESA has made available datasets of 4 early orbits to several groups involved in MIPAS calibration/validation; the groups have been given the opportunity for functionality tests of their analysis codes. We here present some example results of the IMK/IAA MIPAS level-2 processor the concept of which is presented in a companion paper. Temperatures retrieved along the orbits are compared to ECMWF data. Processing parameters as chosen in pre-launch studies, such as cloud identification thresholds, microwindow selection, or instrument characteristics, are discussed. Preliminary retrievals for various atmospheric conditions are shown.

State parameter data base for MIPAS data analysis

Abstract With the launch of ENVISAT in 2001, the high-resolution mid-IR FTS MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) limb emission sounder will be brought into a close-to polar orbit at 800 km altitude. In the scientific data analyses vertical profiles of the temperature and of the volume mixing ratio (vmr) of some 20 species are retrieved. To accelerate the calculations, and hence to maximize the throughput, it is desirable to have initial guess profiles available which are as close as possible to the true profiles. To asses the retrived profiles, and for retrievals with the method of optimal estimation, a-priori knowledge together with related error estimates is furthermore needed. We present a system to generate suitable initial guess profiles, which consists of a data base and corresponding tools to support the scientific data processing. The data base contains individual vmr-profiles for various conditions, meteorological data for the temperature (ECMWF), and climatologies for temperature (MSISE90) and vmr (CIRA, URAP), and corresponding error estimates.

Comparisons of MIPAS-observed temperature profiles with other satellite measurements

MIPAS on ENVISAT measures vertical profiles of atmospheric temperature, ozone, and other species with nearly global coverage and high accuracy/precision. The standard observation mode covers the altitude region between 6 and 68 km. The atmospheric state parameters retrieved from MIPAS measurements using the IMK data analysis processor are compared with a number of other satellite observations. Our comparisons in this paper will focus on temperatures measured by MIPAS, HALOE, SABER, and UKMO Stratospheric Assimilated Data. Both individual profiles and zonal means measured by MIPAS and other instruments at different seasons and geolocations show reasonable agreement, though some differences exist due to characteristics of the individual instruments and observation scenarios. The MIPAS measurements during the stratospheric major sudden warming during the southern hemisphere winter of 2002 are also presented to show the features of this unusual event. The analysis indicates the reliability of MIPAS-IMK data products and their capability for providing valuable scientific information.

Comparison of GPS/SAC-C and MIPAS/ENVISAT Temperature Profiles and Its Possible Implementation for EOS MLS Observations

This analysis presents comparisons of the atmospheric temperatures retrieved from GPS/SAC-C radio occultation observations using the JPL retrieval software, and from MIPAS/ENVISAT infrared spectrum measurements using the IMK data processor. Both individual profiles and zonal means of the atmospheric temperature at different seasons and geo-locations show reasonable agreement. For the temperatures at altitudes between 8–30 km, the mean differences between the correlative measurements are estimated at less than 2 K with rms deviations less than 5 K. A similar cross comparison technique can be used to help validate the observed temperatures from the new EOS MLS instrument, to be launched in 2004.