München, Univ., Diss., 2002. / Computerdatei im Fernzugriff.

München, Univ., Diss., 2002. / Computerdatei im Fernzugriff.

Proefschrift Amsterdam. / Met lit. opg., reg..

Erlangen, Nürnberg, Univ., Diss., 2007.

University, Diss., 2002--München.

Proefschrift Universiteit van Amsterdam. / Auteursnaam op omslag: Jacco van Loon. Met lit. opg. - Met samenvatting in het Nederlands.

Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the “perfect model approach.” This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.

Simulations alternatively assuming a landscape with and without urbanization plus open-cast mining were performed with a non-hydrostatic model. lt is examined whether the atmospheric response to landuse changes is sensitive to the direction of the geostrophic wind. The results of simulations with the same geostrophic wind direction show that except for the cloud and precipitating particles the daily domain-averages of the variables of state hardly differ for the different landscapes. Nevertheless, the local weather may be affected appreciably over and downwind of the altered surfaces. The significant differences in the cloud and precipitating particles, however, are not bound to the environs of the landuse changes. Generally, the most significant differences occur for the cloud and precipitation particles, the soil wetness factors and the vertical component of the wind vector. The latter changes strongly influence the cloud and precipitation formation by the interaction cloud microphysics-dynamics. The results also indicate that for most of the quantities the local magnitude of the atmospheric response changes for the various directions of the geostrophic wind. However, the differences of the domain-averaged 24h-accumulated evapotranspiration are similar for all geostrophic wind directions. / Um zu untersuchen, ob die atmosphärische Antwort auf Landnutzungsänderungen sensitiv zur Richtung des geostrophischen Windes ist, wurden Simulationen durchgeführt, bei denen alternativ eine Landschaft mit und ohne Urbanisierung plus Tagebauten angenommen wurde. Die Simulationsergebnisse zeigen, daß - außer für Wolken- und Niederschlagspartikel - die täglichen Gebietsmittelwerte der Zustandsvariablen sich kaum für die beiden Landschaften unterscheiden. Trotzdem kann das lokale Wetter merklich über und im Lee der Oberflächen mit veränderter Landnutzung beeinflußt werden. Die signifikanten Differenzen in den Wolken- und Niederschlagspartikeln sind jedoch nicht an die unmittelbare Nähe der Landnutzungsänderungen gebunden. Generell treten die signifikanten Unterschiede bei den Wolkenund Niederschlagspartikeln, der Bodenfeuchte und der Vertikalkomponente des Windvektors auf. Letztere beeinflussen stark die Wolken- und Niederschlagsbildung durch die Wechselwirkung Wolkenmikrophysik-Dynamik. Die Ergebnisse zeigen außerdem, daß lokal der Grad der atmosphärischen Reaktion für die meisten Größen bei unterschiedlicher Richtung des geostrophischen Windes anders ausfällt. Die Differenzen der Gebietsmittelwerte der 24h-akkumulierten Evapotranspiration gleichen sich jedoch für alle Richtungen des geostrophischen Windes.

The accomplished case studies focus on the influence of land-use on the distributions of latent heat-fluxes and cloud-water. The numerical case studies were performed with the threedimensional non-hydrostatic Mesoscale-Model GESIMA for different land-use distributions applying always the same initial conditions of a cloudy day in spring with a geostrophic wind of 8 m/s from the west. The cloud-water distributions at different times and at different levels, their temporal development, the daily sums of the domain-averaged latent heat-fluxes and cloud-water mixing ratios were investigated. Even simple initial conditions (no orography, stable atmosphere) and simple pattern in the land-use distributions emphasize that the influence of surface heterogeneity on meteorological processes cannot be neglected. As shown in this case study, land-use distribution influences the distribution and the amount of cloud-water as weil as the latent heat-flux. On the whole, all these processes are very complex and non-linear. / Die durchgeführten Sensitivitätsstudien konzentrieren sich auf den Einfluß der Landnutzungsverteilung auf die Flüsse latenter Wärme und das Wolkenwasser. Die numerischen Untersuchungen wurden mit dem dreidimensionalen nicht-hydrostatischen Mesoskalen-Modell GESIMA für verschiedene Landnutzungsmuster unter immer den gleichen meteorologischen Anfangsbedingungen für einen bewölkten Frühlingstag mit einem geostrophischen Wind von 8 m/s durchgeführt. Die Wolkenwasserverteilung zu bestimmten Zeiten und in bestimmten Niveaus, die zeitliche Entwicklung der Wolkenwasserverteilung, die Tagessummen der Gebietsmittelwerte der Flüsse latenter Wärme und des Wolkenwassers werden untersucht. Auch einfache Randbedingungen (keine Orographie, stabile, atmosphärische Bedingungen) und einfache Landnutzungsverteilungsmuster machen deutlich, daß der Einfluß der Heterogenität der Unterlage auf meteorologische Prozesse nicht zu vernachlässigen ist. Sie kann entscheidend die Verteilungen der Flüsse latenter Wärme und des Wolkenwassers beeinflussen. Die damit verbundenen Prozesse sind äußerst komplex und nicht linear.

A simple way to diagnose fractional cloud cover in general circulation models is to relate it to the simulated relative humidity, and allowing for fractional cloud cover above a “critical relative humidity” of less than 100%. In the formulation chosen here, this is equivalent to assuming a uniform “top-hat” distribution of subgrid-scale total water content with a variance related to saturation. Critical relative humidity has frequently been treated as a “tunable” constant, yet it is an observable. Here, this parameter, and its spatial distribution, is examined from Atmospheric Infrared Sounder (AIRS) satellite retrievals, and from a combination of relative humidity from the ECMWF Re-Analyses (ERA-Interim) and cloud fraction obtained from CALIPSO lidar satellite data. These observational data are used to evaluate results from different simulations with the ECHAM general circulation model (GCM). In sensitivity studies, a cloud feedback parameter is analyzed from simulations applying the original parameter choice, and applying parameter choices guided by the satellite data. Model sensitivity studies applying parameters adjusted to match the observations show larger positive cloud-climate feedbacks, increasing by up to 30% compared to the standard simulation.