Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Emerging application areas such as air pollution in megacities, wind energy, urban security, and operation of unmanned aerial vehicles have intensified scientific and societal interest in mountain meteorology. To address scientific needs and help improve the prediction of mountain weather, the U.S. Department of Defense has funded a research effort—the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program—that draws the expertise of a multidisciplinary, multi-institutional, and multinational group of researchers. The program has four principal thrusts, encompassing modeling, experimental, technology, and parameterization components, directed at diagnosing model deficiencies and critical knowledge gaps, conducting experimental studies, and developing tools for model improvements. The access to the Granite Mountain Atmospheric Sciences Testbed of the U.S. Army Dugway Proving Ground, as well as to a suite of conventional and novel high-end airborne and surface measurement platforms, has provided an unprecedented opportunity to investigate phenomena of time scales from a few seconds to a few days, covering spatial extents of tens of kilometers down to millimeters. This article provides an overview of the MATERHORN and a glimpse at its initial findings. Orographic forcing creates a multitude of time-dependent submesoscale phenomena that contribute to the variability of mountain weather at mesoscale. The nexus of predictions by mesoscale model ensembles and observations are described, identifying opportunities for further improvements in mountain weather forecasting.

We applied a ground-based vertically-pointing aerosol lidar to investigate the evolution of the instantaneous atmospheric boundary layer depth, its growth rate, associated entrainment processes, and turbulence characteristics. We used lidar measurements with range resolution of 3 m and time resolution of up to 0.033 s obtained in the course of a sunny day (26 June 2004) over an urban valley (central Stuttgart, 48°47' N, 9°12' E, 240 m above sea level). The lidar system uses a wavelength of 1064 nm and has a power-aperture product of 2.1 W m². Three techniques are examined for determining the instantaneous convective boundary layer (CBL) depth from the high-resolution lidar measurements: the logarithm gradient method, the inflection point method, and the Haar wavelet transform method. The Haar wavelet-based approach is found to be the most robust technique for the automated detection of the CBL depth. Two different regimes of the CBL are discussed in detail: a quasi-stationary CBL in the afternoon and a CBL with rapid growth during morning transition in the presence of dust layers atop. Two different growth rates were found: 3–5 m/min for the growing CBL in the morning and 0.5–2 m/min during the quasi-steady regime. The mean entrainment zone thickness for the quasi-steady CBL was found to be ~75 m while the CBL top during the entire day varied between 0.7 km and 2.3 km. A fast Fourier-transform-based spectral analysis of the instantaneous CBL depth time series gave a spectral exponent value of 1.50±0.04, confirming non-stationary CBL behavior in the morning while for the other regime a value of 1.00±0.06 was obtained indicating a quasi-stationary state of the CBL. Assuming that the spatio-temporal variation of the particle backscatter cross-section of the aerosols in the scattering volume is due to number density fluctuations (negligible hygroscopic growth), the particle backscatter coefficient profiles can be used to investigate boundary layer turbulence since the aerosols act as tracers. We demonstrate that with our lidar measurements, vertical profiles of variance, skewness, and kurtosis of the fluctuations of the particle backscatter coefficient can be determined. The variance spectra at different altitudes inside the quasi-steady CBL showed an f^−5/3 dependency. The integral scale varied from 40 to 90 s (depending on height), which was significantly larger than the temporal resolution of the lidar data. Thus, the major part of the inertial subrange was detected and turbulent fluctuations could be resolved. For the quasi-stationary case, negative values of skewness were found inside the CBL while positive values were observed in the entrainment zone near the top of the CBL. For the case of the rapidly growing CBL, the skewness profile showed both positive and negative values even inside the CBL.

In the afternoon of 15 July 2007, a thunderstorm was initiated within a line of cumulus clouds which formed parallel to the crest of the Black Forest mountains during the Intensive Observation Period (IOP) 8b of the Convective and Orographically‐induced Precipitation Study (COPS). This paper extends the analysis of processes that led to convection initiation (CI), i.e. the transition from shallow to deep convection, on this day with the data from several COPS instruments that have not been considered in previous studies. In particular, the boundary‐layer structure, lids and the water‐vapour field in the pre‐convective environment of the event are discussed. For this purpose, we investigated measurements of water‐vapour lidars, temperature lidars and wind lidars, profiles from radiosondes, in situ aircraft data and gridded data of weather stations as well as GPS integrated‐water‐vapour data and satellite imagery. Thermally driven circulation systems formed over both the Black Forest and the Vosges mountain ranges which resulted in local convergence zones. These superimposed with the large‐scale convergence in the Black Forest area. In the presence of sufficient moisture and updraught, clouds formed close to the mountain crests. The related latent‐heat release allowed larger thermals to be produced, which may have had a positive feedback on stabilizing these convergence zones as a whole. We believe that differences in the moisture field explain why convection remained shallow and sparse over the Vosges mountains because these differences were responsible for differences in convective inhibition (CIN). The stationary location of the convergence zone over the southern Black Forest was probably decisive for CI because it constantly transported sensible and latent heat into the area in which CI took place. Copyright © 2011 Royal Meteorological Society

The rotational Raman lidar (RRL) of the University of Hohenheim (UHOH) measures atmospheric temperature profiles with high resolution (10 s, 109 m). The data contain low-noise errors even in daytime due to the use of strong UV laser light (355 nm, 10 W, 50 Hz) and a very efficient interference-filter-based polychromator. In this paper, the first profiling of the second- to fourth-order moments of turbulent temperature fluctuations is presented. Furthermore, skewness profiles and kurtosis profiles in the convective planetary boundary layer (CBL) including the interfacial layer (IL) are discussed. The results demonstrate that the UHOH RRL resolves the vertical structure of these moments. The data set which is used for this case study was collected in western Germany (50°53'50.56'' N, 6°27'50.39'' E; 110 m a.s.l.) on 24 April 2013 during the Intensive Observations Period (IOP) 6 of the HD(CP)² (High-Definition Clouds and Precipitation for advancing Climate Prediction) Observational Prototype Experiment (HOPE). We used the data between 11:00 and 12:00 UTC corresponding to 1 h around local noon (the highest position of the Sun was at 11:33 UTC). First, we investigated profiles of the total noise error of the temperature measurements and compared them with estimates of the temperature measurement uncertainty due to shot noise derived with Poisson statistics. The comparison confirms that the major contribution to the total statistical uncertainty of the temperature measurements originates from shot noise. The total statistical uncertainty of a 20 min temperature measurement is lower than 0.1 K up to 1050 m a.g.l. (above ground level) at noontime; even for single 10 s temperature profiles, it is smaller than 1 K up to 1020 m a.g.l. Autocovariance and spectral analyses of the atmospheric temperature fluctuations confirm that a temporal resolution of 10 s was sufficient to resolve the turbulence down to the inertial subrange. This is also indicated by the integral scale of the temperature fluctuations which had a mean value of about 80 s in the CBL with a tendency to decrease to smaller values towards the CBL top. Analyses of profiles of the second-, third-, and fourth-order moments show that all moments had peak values in the IL around the mean top of the CBL which was located at 1230 m a.g.l. The maximum of the variance profile in the IL was 0.39 K² with 0.07 and 0.11 K² for the sampling error and noise error, respectively. The third-order moment (TOM) was not significantly different from zero in the CBL but showed a negative peak in the IL with a minimum of −0.93 K³ and values of 0.05 and 0.16 K³ for the sampling and noise errors, respectively. The fourth-order moment (FOM) and kurtosis values throughout the CBL were not significantly different to those of a Gaussian distribution. Both showed also maxima in the IL but these were not statistically significant taking the measurement uncertainties into account. We conclude that these measurements permit the validation of large eddy simulation results and the direct investigation of turbulence parameterizations with respect to temperature.