Johannes Verlinde

Cloud Droplet Size Distributions in Low-Level Stratiform Clouds

Abstract A database of stratus cloud droplet (diameter <50 μm) size distribution parameters, derived from in situ data reported in the existing literature, was created, facilitating intercomparison among datasets and quantifying typical values and their variability. From the datasets, which were divided into marine and continental groups, several parameters are presented, including the total number concentration, effective diameter, mean diameter, standard deviation of the droplet diameters about the mean diameter, and liquid water content, as well as the parameters of modified gamma and lognormal distributions. In light of these results, the appropriateness of common assumptions used in remote sensing of cloud droplet size distributions is discussed. For example, vertical profiles of mean diameter, effective diameter, and liquid water content agreed qualitatively with expectations based on the current paradigm of cloud formation. Whereas parcel theory predicts that the standard deviation about the mean d...

The Mixed-Phase Arctic Cloud Experiment

The Mixed-Phase Arctic Cloud Experiment (M-PACE) was conducted from 27 September through 22 October 2004 over the Department of Energys Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) on the North Slope of Alaska. The primary objectives were to collect a dataset suitable to study interactions between microphysics, dynamics, and radiative transfer in mixed-phase Arctic clouds, and to develop/evaluate cloud property retrievals from surface-and satellite-based remote sensing instruments. Observations taken during the 1977/98 Surface Heat and Energy Budget of the Arctic (SHEBA) experiment revealed that Arctic clouds frequently consist of one (or more) liquid layers precipitating ice. M-PACE sought to investigate the physical processes of these clouds by utilizing two aircraft (an in situ aircraft to characterize the microphysical properties of the clouds and a remote sensing aircraft to constraint the upwelling radiation) over the ACRF site on the North Slope of Alaska. The measureme...

An Evaluation of a 94-GHz Radar for Remote Sensing of Cloud Properties

Abstract The performance of a 94-GHz radar is evaluated for a variety of cloud conditions. Descriptions of the radar hardware, signal processing, and calibration provide an overview of the radars capabilities. An important component of the signal processing is the application of two cloud-mask schemes to the data to provide objective estimates of cloud boundaries and to detect significant returns that would otherwise be discarded if a simple threshold method for delectability was applied to the return power. Realistic profiles of atmospheric pressure, temperature, and water vapor are used in a radiative transfer model to address clear-sky attenuation. A physically relevant study of beam extinction and backscattering by clouds is attempted by modeling cloud drop size distributions with a gamma distribution over a range of number concentrations, particle mean diameters, and distribution shape factors; cloud liquid water contents and mean drop size diameters reported in the literature are analyzed in this c...

Can Ice-Nucleating Aerosols Affect Arctic Seasonal Climate?

Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate and regional models have generally proven unsuccessful at simulating Arctic cloudiness, particularly during the colder months. Specifically, models tend to underpredict the amount of liquid water in mixed-phase clouds. The Mixed-Phase Arctic Cloud Experiments (M-PACE), conducted from late September through October 2004 in the vicinity of the Department of Energys Atmospheric Radiation Measurement (ARM) North Slope of Alaska field site, focused on characterizing low-level Arctic stratus clouds. Ice nuclei (IN) measurements were made using a continuous-flow ice thermal diffusion chamber aboard the University of North Dakotas Citation II aircraft. These measurements indicated IN concentrations that were significantly lower than those used in many models. Using the Regional Atmospheric Modeling System (RAMS), we show that these low IN concentrations, as well as inadequate parameteri...

Stratospheric influence on upper tropospheric tropical cirrus

Radiosonde data from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Nauru99 experiment revealed waves with downward phase propagation from the lower stratosphere into the upper troposphere. The occurrence of cirrus clouds and the tropical tropopause structure were closely related to these waves. This study reveals a close relationship between upper tropospheric cirrus and large-scale dynamics, suggesting that tropical cirrus cannot be studied in isolation from planetary scale forcing.

Preferential concentration of cloud droplets by turbulence : Effects on the early evolution of cumulus cloud droplet spectra

Abstract A mechanism is presented, based on the inherent turbulent nature of cumulus clouds, for the broadening of cloud droplet spectra during condensational growth. This mechanism operates independent of entrainment and, therefore, can operate in adiabatic cloud cores. Cloud droplets of sufficient size are not randomly dispersed in a cloud but are preferentially concentrated in regions of low vorticity in the turbulent flow field. Regions of high vorticity (low droplet concentration) develop higher supersaturation than regions of low vorticity (high droplet concentration). Therefore, on small spatial scales cloud droplets are growing in a strongly fluctuating supersaturation field. These fluctuations in supersaturation exist independent of large-scale vertical velocity fluctuations. Droplets growing in regions of high vorticity will experience enhanced growth rates, allowing some droplets to grow larger than predicted by the classic theory of condensational growth. This mechanism helps to account for tw...

A Focus on Mixed-Phase Clouds: The Status of Ground-Based Observational Methods

The phase composition and microphysical structure of clouds define the manner in which they modulate atmospheric radiation and contribute to the hydrologic cycle. Issues regarding cloud phase partitioning and transformation come to bear directly in mixed-phase clouds, and have been difficult to address within current modeling frameworks. Ground-based, remote-sensing observations of mixed-phase clouds can contribute a significant body of knowledge with which to better understand, and thereby more accurately model, clouds and their phase-defining processes. Utilizing example observations from the Mixed-Phase Arctic Cloud Experiment (M-PACE), which occurred at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Programs Climate Research Facility in Barrow, Alaska, during autumn 2004, we review the current status of ground-based observation and retrieval methods used in characterizing the macrophysical, microphysical, radiative, and dynamical properties of stratiform mixed-phase clouds. In...

Fitting Microphysical Observations of Nonsteady Convective Clouds to a Numerical Model: An Application of the Adjoint Technique of Data Assimilation to a Kinematic Model

Abstract Rapid advances in the quality and quantity of atmospheric observations have placed a demand for the development of techniques to assimilate these data sources into numerical forecasting models. Four-dimensional variational assimilation is a promising technique that has been applied to atmospheric and oceanic dynamical models, and to the retrieval of three-dimensional wind fields from single-Doppler radar observations. This study investigates the feasibility of using space–time variational assimilation for a complex discontinuous numerical model including cloud physics. Two test models were developed: a one-dimensional and a two-dimensional liquid physics kinematic microphysical model. These models were used in identical-twin experiments, with observations taken intermittently. Small random errors were introduced into the observations. The retrieval runs were initialized with a large perturbation of the observation run initial conditions. The models were able to retrieve the original initial condi...

Analytical solutions to the collection growth equation : comparison with approximate methods and application to cloud microphysics parameterization schemes

Abstract A closed form solution for the collection growth equation as used in bulk microphysical parameterizations is derived. Although the general form is mathematically complex, it can serve as a benchmark for testing a variety of approximations. Two special cases that can immediately be implemented in existing cloud models are also presented. This solution is used to evaluate two commonly used approximations. The effect of the selection of different basis functions is also investigated.

Dynamical and Microphysical Retrievals from Doppler Radar Observations of a Deep Convective Cloud

A four-dimensional variational data assimilation system consisting of a three-dimensional time-dependent cloud model with both liquid and ice phase microphysics parameterization was used to assimilate radar data into a cloud model. Data of a severe thunderstorm observed during the Cooperative Huntsville Meteorological Experiment project were assimilated and results compared to a conventional analysis. The analysis system was able to retrieve all the prominent features of the storm, but differed in some of the details. However, the consistency of this retrieval dataset lent credence to the results. It was found that the algorithm was very sensitive to several coefficients in the microphysical and turbulence parameterizations. Simulations proved to be unable to reproduce the evolution of the observed storm even with parameterization coefficients set at values that produce reasonable storm evolutions. This result has implications for short-range forecasting of convective events. Such forecasts require initial fields that currently can only be derived from observations such as used in this study. The problems with assimilating radar observations point to additional work to design parameterizations that allow models to more accurately simulate actual observed storms.