SOFOS - A new Satellite-based Operational Fog Observation Scheme

This thesis introduces a new technique for the operational observation of fog from space. The scheme presented uses the Meteosat-8 SEVIRI system for near-real-time detection of low stratus and ground fog areas

How thermodynamic environments control stratocumulus microphysics and interactions with aerosols

Aerosol–cloud interactions are central to climate system changes and depend on meteorological conditions. This study identifies distinct thermodynamic regimes and proposes a conceptual framework for interpreting aerosol effects. In the analysis, ten years (2003–2012) of daily satellite-derived aerosol and cloud products are combined with reanalysis data to identify factors controlling Southeast Atlantic stratocumulus microphysics. Considering the seasonal influence of aerosol input from biomass burning, thermodynamic environments that feature contrasting microphysical cloud properties and aerosol–cloud relations are classified. While aerosol impact is stronger in unstable environments, it is mostly confined to situations with low aerosol loading (aerosol index AI ≲ 0.15), implying a saturation of aerosol effects. Situations with high aerosol loading are associated with weaker, seasonally contrasting aerosol-droplet size relationships, likely caused by thermodynamically induced processes and aerosol swelling

First fully diurnal fog and low cloud satellite detection reveals life cycle in the Namib

Fog and low clouds (FLCs) are a typical feature along the southwestern African coast, especially in the central Namib, where fog constitutes a valuable resource of water for many ecosystems. In this study, a novel algorithm is presented to detect FLCs over land from geostationary satellite data using only infrared observations. The algorithm is the first of its kind as it is stationary in time and thus able to reveal a detailed view of the diurnal and spatial patterns of FLCs in the Namib region. A validation against net radiation measurements from a station network in the central Namib reveals a high overall accuracy with a probability of detection of 94%, a false-alarm rate of 12% and an overall correctness of classification of 97%. The average timing and persistence of FLCs seem to depend on the distance to the coast, suggesting that the region is dominated by advection-driven FLCs. While the algorithm is applied to study Namib-region fog and low clouds, it is designed to be transferable to other regions and can be used to retrieve long-term data sets

An improved return-mapping scheme for nonsmooth yield surfaces: PART I - the Haigh-Westergaard coordinates

The paper is devoted to the numerical solution of elastoplastic constitutive initial value problems. An improved form of the implicit return-mapping scheme for nonsmooth yield surfaces is proposed that systematically builds on a subdifferential formulation of the flow rule. The main advantage of this approach is that the treatment of singular points, such as apices or edges at which the flow direction is multivalued involves only a uniquely defined set of non-linear equations, similarly to smooth yield surfaces. This paper (PART I) is focused on isotropic models containing: $a)$ yield surfaces with one or two apices (singular points) laying on the hydrostatic axis; $b)$ plastic pseudo-potentials that are independent of the Lode angle; $c)$ nonlinear isotropic hardening (optionally). It is shown that for some models the improved integration scheme also enables to a priori decide about a type of the return and investigate existence, uniqueness and semismoothness of discretized constitutive operators in implicit form. Further, the semismooth Newton method is introduced to solve incremental boundary-value problems. The paper also contains numerical examples related to slope stability with available Matlab implementation.Comment: 25 pages, 10 figure

A satellite‐based climatology of fog and low stratus formation and dissipation times in central Europe

Knowledge of fog and low stratus (FLS) cloud patterns and life cycles is important for traffic safety, for the production of solar energy and for the analysis of cloud processes in the climate system. While meteorological stations provide information on FLS, a data set describing FLS formation and dissipation times on large spatial and temporal scales does not exist yet. In this study, we use logistic regression to extract FLS formation and dissipation times from a satellite-based 10-year FLS data set covering central Europe. The resulting data set is the first to provide a geographic perspective on FLS formation and dissipation at a continental scale. The patterns found show a clear dependency of FLS formation and dissipation times on topography. In mountainous areas, FLS forms in the night and dissipates in the morning. In river valleys, the typical FLS life cycle shifts to formation after sunrise and dissipation in the afternoon. Seasonal patterns of FLS for mation and dissipation show similar FLS formation and dissipation times in winter and autumn, and in spring and summer, with longer events in the former two seasons

Machine-Learning Based Analysis of Liquid Water Path Adjustments to Aerosol Perturbations in Marine Boundary Layer Clouds Using Satellite Observations

Changes in marine boundary layer cloud (MBLC) radiative properties in response to aerosol perturbations are largely responsible for uncertainties in future climate predictions. In particular, the relationship between the cloud droplet number concentration (N$_d$, a proxy for aerosol) and the cloud liquid water path (LWP) remains challenging to quantify from observations. In this study, satellite observations from multiple polar-orbiting platforms for 2006–2011 are used in combination with atmospheric reanalysis data in a regional machine learning model to predict changes in LWP in MBLCs in the Southeast Atlantic. The impact of predictor variables on the model output is analysed using Shapley values as a technique of explainable machine learning. Within the machine learning model, precipitation fraction, cloud top height, and N$_d$ are identified as important cloud state predictors for LWP, with dynamical proxies and sea surface temperature (SST) being the most important environmental predictors. A positive nonlinear relationship between LWP and N$_d$ is found, with a weaker sensitivity at high cloud droplet concentrations. This relationship is found to be dependent on other predictors in the model: N$_d$–LWP sensitivity is higher in precipitating clouds and decreases with increasing SSTs

Enhanced nighttime fog and low stratus occurrence over the Landes forest, France

Understanding the drivers of fog and low stratus (FLS) cloud occurrence is important for traffic, ecosystems and climate models, but challenging to analyze due to the complex interactions between meteorological factors and land cover. Here, we use active and passive satellite data, as well as reanalysis data to investigate nighttime FLS occurrence over the expansive Landes forest in France from 2006-2015. We find significant FLS enhancement over the forest compared to surrounding areas, especially in summer and fall. Lower wind speed and lower temperatures are found over the forest at night, which can enhance FLS development over the forest. Still, other drivers, such as biovolatile organic compounds acting as cloud condensation nuclei, are most likely important as well. The results show that the influence of forests on boundary layer clouds is not limited to convective daytime conditions

High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds

The observation of boundary layer clouds with high-resolution satellite data can provide comprehensive insights into spatiotemporal patterns of land-surface-driven modification of cloud occurrence, such as the diurnal variation of the occurrence of fog holes and cloud enhancements attributed to the impact of the urban heat island. High-resolution satellite-based cloud-masking approaches are often based on locally optimised thresholds that can be affected by the local surface reflectance, and they therefore introduce spatial biases in the detected cloud cover. In this study, geostationary satellite observations are used to develop and validate two high-resolution cloud-masking approaches for the region of Paris to show and improve applicability for analyses of urban effects on clouds. Firstly, the Local Empirical Cloud Detection Approach (LECDA) uses an optimised threshold to separate the distribution of visible reflectances into cloudy and clear sky for each individual pixel accounting for its locally specific brightness. Secondly, the Regional Empirical Cloud Detection Approach (RECDA) uses visible reflectance thresholds that are independent of surface reflection at the observed location. Validation against in-situ cloud fractions reveals that both approaches perform similarly, with a probability of detection (POD) of 0.77 and 0.69 for LECDA and RECDA, respectively. Results show that with the application of RECDA a decrease of cloud cover during typical fog or low-stratus conditions over the urban area of Paris for the month of November is likely a result of urban effects on cloud dissipation. While LECDA is representative for the widespread usage of locally optimised approaches, comparison against RECDA reveals that the cloud masks obtained from LECDA result in regional biases of ±5 % that are most likely caused by the differences in surface reflectance in and around the urban areas of Paris. This makes the regional approach, RECDA, a more appropriate choice for the high-resolution satellite-based analysis of cloud cover modifications over different surface types and the interpretation of locally induced cloud processes. Further, this approach is potentially transferable to other regions and temporal scales for analysing long-term natural and anthropogenic impacts of land cover changes on clouds

An analysis of fog and low stratus life‐cycle regimes over central Europe

A better understanding of fog and low stratus (FLS) life cycles, in particular the typical onset and dissipation times, can help traffic safety and solar power planning. Besides its high dependence on the prevalent meteorological conditions, the FLS life cycle is further determined by the FLS type as well as the underlying geography and climate. While satellite-based FLS data sets with high temporal and spatial resolution are available, an objective, large-scale, satellite-based classification of FLS life-cycle regions, which would allow for more targeted analyses of the FLS life cycle, is lacking. In this study, a hierarchical clustering algorithm is applied to identify regions of similar relationships of the FLS life cycle to environmental conditions over central Europe. The clustering reveals major FLS life-cycle regimes with distinct differences in FLS occurrence, temporal FLS life-cycle patterns, and climatic characteristics. Based on regime-specific sensitivity analyses, the relationships of the FLS life cycle with near-ground temperature and specific humidity are identified as the most relevant input relationships for the clustering algorithm, especially in the Mediterranean region. FLS life-cycle regimes are further presented at a regional scale, outlining the applicability of the derived FLS life-cycle regimes to future regional process-oriented FLS life-cycle studies

Short-Term Frequency Stability Measurement of BVA Oscillators

This paper discusses the time-domain measurement of short-term frequency stability of ultra-stable BVA oscillators with flicker frequency modulation noise on the order of 10‑14 at averaging intervals from hundreds of milliseconds to tens of seconds. The stability has been measured with a highly sensitive phase-time comparator based on the dual-mixer time-difference multiplication with a background instability of ≈7x10-15/τ in terms of Allan deviation. A discrepancy has been observed in the comparator background noise found with two signals from a single oscillator (comparator test) and with two signals from two oscillators (stability measurements)