Michael Kiefer

Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations

The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity. Copyright

Process‐evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopic observations: 2. Using isotopic diagnostics to understand the mid and upper tropospheric moist bias in the tropics and subtropics

Evaluating the representation of processes controlling tropical and subtropical tropospheric relative humidity (RH) in atmospheric general circulation models (GCMs) is crucial to assess the credibility of predicted climate changes. GCMs have long exhibited a moist bias in the tropical and subtropical mid and upper troposphere, which could be due to the mis-representation of cloud processes or of the large-scale circulation, or to excessive diffusion during water vapor transport. The goal of this study is to use observations of the water vapor isotopic ratio to understand the cause of this bias. We compare the three-dimensional distribution of the water vapor isotopic ratio measured from space and ground to that simulated by several versions of the isotopic GCM LMDZ. We show that the combined evaluation of RH and of the water vapor isotopic composition makes it possible to discriminate the most likely cause of RH biases. Models characterized either by an excessive vertical diffusion, an excessive convective detrainment or an underestimated in situ cloud condensation will all produce a moist bias in the free troposphere. However, only an excessive vertical diffusion can lead to a reversed seasonality of the free tropospheric isotopic composition in the subtropics compared to observations. Comparing seven isotopic GCMs suggests that the moist bias found in many GCMs in the mid and upper troposphere most frequently results from an excessive diffusion during vertical water vapor transport. This study demonstrates the added value of water vapor isotopic measurements for interpreting shortcomings in the simulation of RH by climate models. Copyright 2012 by the American Geophysical Union.

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.

Cross‐validation of MIPAS/ENVISAT and GPS‐RO/CHAMP temperature profiles

[1]xa0The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the ENVISAT and the Global Positioning System (GPS) receiver on the Challenging Mini-Satellite Payload (CHAMP) provide temperature profiles by limb-viewing midinfrared emission and radio occultation (RO) measurements, respectively. The MIPAS temperatures retrieved at the Institut fur Meteorologie und Klimaforschung (IMK) are compared with the GPS-RO/CHAMP observations derived at Jet Propulsion Laboratory (JPL) and GeoForschungsZentrum (GFZ) Potsdam. The three data sets show generally good agreement. The global mean differences averaged between 8 and 30 km in 14 days of September/October 2002 are −0.44 ± 0.02 K and 0.07 ± 0.02 K for MIPAS/GPS-RO JPL and GFZ comparisons, respectively. The MIPAS global mean temperatures below 25 km are slightly lower than those of GPS-RO JPL and GFZ by less than 1 K and 0.2 K, respectively. Above 25 km, the MIPAS temperatures are higher than the JPL and GFZ data, in particular near both poles and the equator, with maxima of 1 K for JPL and 1.5 K for GFZ at 30 km. The standard deviations are ∼2–4 K. Possible explanations for the observed differences include (1) effect of spatial and temporal mismatch between the correlative measurements on the observed standard deviations, in particular in regions and episodes of enhanced wave activity; (2) a negative bias in GPS-RO/CHAMP temperatures in regions of increased humidity; (3) a mapping of initialization temperature profiles on GPS-RO/CHAMP retrievals at altitudes where low refraction contains no information on air density; and (4) measurement errors of both instruments, particularly the errors due to insufficient knowledge of the instrument line shape and spectroscopy in current MIPAS retrievals.

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.

Ein hedonischer Immobilienpreisindex auf Basis von Internetdaten: 2007–2011

ZusammenfassungDie Beobachtung der Preisentwicklung auf dem Immobilienmarkt ist nicht nur für die Akteure auf diesem Markt, sondern – wie die Finanz- und Wirtschaftskrise gezeigt hat – auch für die Konjunkturanalyse und Wirtschaftspolitik von großer Bedeutung. Existierende Immobilienpreisindizes für Deutschland sind jedoch gerade für die Konjunkturanalyse nur von sehr eingeschränktem Nutzen, da die meisten Indizes weder hinsichtlich ihrer zeitlichen Frequenz noch in der notwendigen Aktualität zur Verfügung stehen. Darüber hinaus stehen die existierenden Indizes häufig nur auf einem sehr hohen Aggregationsgrad zur Verfügung und lassen weder eine regionale Analyse noch eine Analyse für verschiedene Immobilientypen zu. In dieser Arbeit werden auf Basis von Daten der Internetplattform von ImmobilienScout24 hedonische Preisindizes für verschiedene Immobilientypen und verschiedene Städte und Regionen entwickelt. Gegenüber den existierenden Indizes haben diese neuen Indizes insbesondere den Vorteil, dass sie zeitnah in einer monatlichen Frequenz berechnet werden können. Die berechneten Indizes zeigen, dass die Immobilienpreise während der Finanz- und Wirtschaftskrise unter Druck geraten sind, am aktuellen Rand aber wieder stiegen, insbesondere bei Neubauten und in Ballungsgebieten.AbstractThe “Great Recession” has painfully demonstrated the impact of real estate prices on real economic activity. Hence, close examination of real estate price changes is important for business cycle analysis and economic policy. However, most real estate price indices for Germany either exhibit a low frequency or are available with a considerable time lag and thus of limited use. Additionally, existing indices are often highly aggregated and thus exacerbate a regional analysis or an analysis for different real estate market segments. In this paper, we construct hedonic price indices for Germany, for five major German cities, and the rural federal state Mecklenburg-Vorpommern. The indices are constructed for different categories of the real estate market and are based on the data of the internet platform ImmobilienScout24. Compared to already existing indices, our indices exhibit the advantage of monthly frequency. The indices indicate that real estate prices in Germany were under pressure during the financial crisis. However, more recently prices have been rising again, especially for new buildings in conurbations.

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.

Validation of MIPAS/ENVISAT level-1B data products

Spectral limb radiances measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the Envisat Environmental research satellite are characterized in terms of instrument line shape (ILS), noise equivalent spectral radiance (NESR) and possible impact of non-local thermodynamic equilibrium emission in deep space calibration spectra. Furthermore, it is assessed if the operational processing baseline to set the top of the model atmosphere to 120~km is justified. The major findings are: The ILS parametrization provided along with the measurement data is sub-optimal; spectral residuals can be reduced by application of an ILS correction function. Spectral noise as estimated in this study is systematically lower than the values provided along with the measurement data. There is no evidence for significant noise correlations in the spectral domain. There is no indication of non-local thermodynaic equilibrium induced upper atmospheric signal in the so-called deep-space spectra which are used for the radiometric zero-level calibration.

Global Long-Term MIPAS Data Processing: Some Aspects of the Dynamics of the Atmosphere from Lower Stratosphere to Lower Thermosphere

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a Fourier transform mid-infrared limb scanning high resolution spectrometer which allows for simultaneous measurements of more than 30 atmospheric trace species related to atmospheric chemistry and global change. MIPAS is operated by ESA since mid of 2002 and the mission will be extended through 2013. At the Institute for Meteorology and Climate Research (IMK), MIPAS spectra are used for retrieval of altitude-resolved profiles of abundances of trace species of the atmosphere. These 4-D trace gas distributions are used for the assessment of e.g. stratospheric ozone chemistry, stratospheric cloud physics and heterogeneous chemistry, tropospheric stratospheric exchange, intercontinental transport of pollutants in the upper troposphere, mesospheric stratospheric exchange, effects of solar proton events on stratospheric chemistry, and climate-chemistry models. Over the last year the XC4000 supercomputer has become a major contributor to the total amount of MIPAS data processed at IMK, and hence has helped a lot in filling the gap which results from ESA’s failure to produce altitude-resolved species profiles for the time since March of 2004. Due to the extremely low administration/communication overhead within the processing system, up to 800 processors could be used (and have been many times) in parallel, 50% of the projects used more than 200 processors in parallel. In the last year the processing of MIPAS data on the XC4000 became more focussed on species which are strongly influenced by NLTE (non-local thermodynamic equilibrium). Two corresponding examples of scientific exploitation of MIPAS data are given. 1. The distribution of CO, which essentially behaves like a tracer, from upper troposphere to mesosphere allows to gain insight into several aspects of middle atmosphere dynamics. 2. The evolution of the temperature field from stratosphere to lower thermosphere hints at a dynamic coupling of these altitude regions via planetary wave activity during a major warming event.