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I. Gultepe and J. A. Milbrandt

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This study analyzes the occurrence of the visibility (Vis) versus precipitation rates (PR) for rain and versus relative humidity (RH) from surface observations that were collected during the Fog Remote Sensing and Modeling (FRAM) field project, which was conducted near Toronto, Ontario, Canada, during the winter of 2005/06 and in Lunenburg, Nova Scotia, during the summers of 2006 and 2007. The main observations used in the analysis were PR and Vis for rain episodes from the Vaisala, Inc., FD12P present-weather sensor and RH and temperature from the Campbell Scientific Instruments, Inc., HMP45 sensor. The PR is compared with those from a total precipitation sensor to check the accuracy of the FD12P measurements. Vis parameterizations related to precipitation type have been previously studied by many other researchers and showed large variability in Vis (up to 1 order of magnitude) for a fixed PR. The results from the work presented here suggest that 1) significant differences exist among the various parameterizations of Vis (deterministic approach) and 2) statistical relationships obtained using fits applied to percentiles (probabilistic approach) can be a feasible alternative for model applications. Comparisons of previous parameterizations with the new Vis relationships suggest that simulated Vis values based on probabilistic approaches could be used in extreme-weather applications.

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I. Gultepe and G. A. Isaac

Abstract

The vertical distribution of liquid water content (LWC) and its relationship with temperature (T) strongly affect the heat budget of the atmosphere. Some large-scale models of the atmosphere use a relationship between LWC and T to diagnostically obtain LWC from T under saturated conditions. Airborne observations conducted within clouds over northeastern North America during the 1984–93 time period are used to study the relationship between LWC and T. Observed frequency distributions of LWC are approximated by lognormal distribution curves and are best represented by median values. The median LWC values monotonically increase with warmer temperatures. However, the mean LWC reaches 0.23 g m−3 at about T = 2.5°C. LWC decreases below and above 2.5°C, except that it reaches a maximum value of 0.26 g m−3 at 22.5°C. The relationship between LWC and T from the present study is compared with that of earlier studies from the former Soviet Union. Differences can be attributed to the design and limits of the probes, natural variability in the 35 years, and the limited dataset for some temperature intervals. The LWC versus T relationship developed from observations in this study can be compared with large-scale model simulations.

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I. Gultepe and G. A. Isaac

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The purpose of this study, using in situ observations from five field projects, is to analyze cloud boundaries and averaging scales related to droplet number concentration (N d) and total aerosol number concentration (N a), and to discuss parameterizations of these variables for use in numerical weather prediction and global climate models. Here N d and N a for stratus and stratocumulus clouds are averaged over various lengths from 1 km up to 35 km. The relationships between these variables for 1-s and 200-s data are compared with current parameterizations. Comparisons between N d and N a show that N a plays an important role for activating cloud droplets. The variability in N d from 1-s data is estimated to have a standard deviation of about ±150 cm−3. Median values of N d representing scales from about 0.1 km up to approximately 35 km are found to be dependent on scale and the presence of clear patches in the clouds. The average values of N d are also dependent on the lower concentration threshold used to define the cloud boundaries. It is concluded that scale effects, including clear air regions, should be considered when developing parameterization schemes used for modeling studies of cloud systems.

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I. Gultepe, M. Pagowski, and J. Reid

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A warm fog detection (air temperature > −5°C) algorithm using a combination of Geostationary Operational Environmental Satellite-12 (GOES-12) observations and screen temperature data based on an operational numerical model has been developed. This algorithm was tested on a large number of daytime cases during the spring and summer of 2004. Results from the scheme were compared with surface observations from four manned Canadian weather stations in Ontario, including Ottawa, Windsor, Sudbury, and Toronto. Initially, when all cases were included, fog detection (hit rate) by the satellite scheme ranged between 0.26 and 0.32. It is suggested that mid- or high-level clouds within the satellite imagery during the observed foggy periods affected the scheme’s performance in detecting surface-level fog for the majority of the cases. When cases with mid- and high-level clouds were removed using model-based screen temperatures, the hit rate ranged between 0.55 and 1.0. With an average false alarm rate of 0.10, the inclusion of model-based sounding values can be seen to improve results from the satellite-based algorithms by an average of 0.42. Average differences between the screen temperature and the surface-observed air temperature were found to be up to 2°C and this can likely account for some discrepancies in detecting fog. Finally, averaging GOES and model data to scales representing single data-point observations likely resulted in some of the failure of the fog algorithm.

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I. Gultepe and D. O'C. Starr

Abstract

Aircraft data collected during the First International Satellite Cloud Climatology Project Regional Experiment (FIRE)I are used to examine dynamical processes operating in cirrus cloud systems observed on 19 and 28 October 1986. Measurements from Lagrangian spiral soundings and constant-altitude flight legs are analyzed. Comparisons are made with observations in clear air. Each cirrus case contained a statically stable layer, a conditionally unstable or neutrally stratified layer (ice pseudoadiabatic) in which convection was prevalent, and a neutral layer in which convection was intermittent. The analysis indicates that a mixture of phenomena occurred including small-scale convective cells, gravity waves (λ≈2–9 km), quasi-two-dimensional waves (λ≈10–20 km), and larger two-dimensional mesoscale waves (λ≈100 km). The intermediate-scale waves, observed both in clear air and in the cloud systems, likely played an important role in the development of the cloud systems given the magnitude of the associated vertical air velocity. The spectra of perturbations of wind components for layers where convection was prevalent were characterized by a κ−5/3 power law dependence, while a κ−2/4 dependence was found at other levels in the cloud systems. A steeper spectral slope (κ−3) was found in the more stable cloud-base layer on 19 October. Samples in clear air also showed a (κ−2.4) dependence. Flight-leg-averaged eddy potential heat fluxes (H=±8 W m−2) were comparable to observations in marine stratocumulus clouds. Calculated turbulence dissipation rates agree with previously published studies, which indicate a general enhancement within cloud systems (10−6 to 10−3 m2 s−3 in cloud versus values less than 0.5×10−6 m2 s−3 in clear air).

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I. Gultepe, M. D. Müller, and Z. Boybeyi

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The objective of this work is to suggest a new warm-fog visibility parameterization scheme for numerical weather prediction (NWP) models. In situ observations collected during the Radiation and Aerosol Cloud Experiment, representing boundary layer low-level clouds, were used to develop a parameterization scheme between visibility and a combined parameter as a function of both droplet number concentration Nd and liquid water content (LWC). The current NWP models usually use relationships between extinction coefficient and LWC. A newly developed parameterization scheme for visibility, Vis = f (LWC, Nd), is applied to the NOAA Nonhydrostatic Mesoscale Model. In this model, the microphysics of fog was adapted from the 1D Parameterized Fog (PAFOG) model and then was used in the lower 1.5 km of the atmosphere. Simulations for testing the new parameterization scheme are performed in a 50-km innermost-nested simulation domain using a horizontal grid spacing of 1 km centered on Zurich Unique Airport in Switzerland. The simulations over a 10-h time period showed that visibility differences between old and new parameterization schemes can be more than 50%. It is concluded that accurate visibility estimates require skillful LWC as well as Nd estimates from forecasts. Therefore, the current models can significantly over-/underestimate Vis (with more than 50% uncertainty) depending on environmental conditions. Inclusion of Nd as a prognostic (or parameterized) variable in parameterizations would significantly improve the operational forecast models.

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I. Gultepe, A. J. Heymsfield, and D. H. Lenschow

Abstract

Techniques are presented to obtain vertical velocity in cirrus clouds from in situ aircraft lateral wind measurements and from ground-based remote Doppler lidar measurements. In general, direct measurements of absolute vertical velocity w from aircraft are currently not feasible because of offsets in the air velocity sensors. An alternative to direct measurement is to calculate w from the integral of the divergence of the horizontal velocity around a closed path. We discuss divergence measurements from both aircraft and Doppler lidar. The principal errors in the calculation of w from aircraft lateral wind measurements are bias in the lateral wind, ground speed errors, and error due to vertical shear of the horizontal wind. For Doppler lidar measurements the principal errors are in the estimate of mean terminal velocity and the zeroth order coefficient of the Fourier series that is fitted to the data. The technique is applied to a cirrus cloud investigated during the FIRE (First International Satellite Cloud Climatology Regional Experiment) Cirrus Intensive Field Observation Program. The results indicate that the error in w is about ±14 cm s−1 from the aircraft technique. We show that this can be reduced to about ±2 to 3 cm s−1 with technical improvements in both ground speed and lateral velocity measurements. The error in w from Doppler lidar measurements, which is about ±8 cm s−1, can be reduced to about ±5 cm s−1 by improvements in the Doppler velocity measurements with technology that is currently available.

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I. Gultepe, A. J. Heymsfield, P. R. Field, and D. Axisa

Abstract

Ice-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

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I. Gultepe, G. Isaac, D. Hudak, R. Nissen, and J. W. Strapp

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In this study, observations from aircraft, Doppler radar, and LANDSAT are used to better understand dynamical and microphysical characteristics of low-level Arctic clouds for climate change studies. Observations during the Beaufort and Arctic Storms Experiment were collected over the southern Beaufort Sea and the northern Mackenzie River Basin during 1 September–14 October 1994. Measurements from the cases of 8 September and 24–25 September are analyzed. In situ observations were made by instruments mounted on a Convair-580 research aircraft. Reflectivity and radial winds were obtained from an X-band Doppler radar located near Inuvik. The reflectivity field from LANDSAT observations concurrent with the aircraft and radar observations was also obtained. Dynamical activity, representing vertical air velocity (w a) and turbulent fluxes, is found to be larger in cloud regions. The sizes of coherent structures (e.g., cells) are from 0.1 to 15 km as determined by wavelet analysis and time series of aircraft data. This size is comparable with LANDSAT and Doppler radar–derived cell sizes. Reflectivity in embedded cells for the 8 September case was larger than that of single convective cells for the 24–25 September case. The effective radius for ice crystals (droplets) ranged from 37(7.5) μm to 70(9.5) μm for both cases. Using observations, parameterization of the ice crystal number concentration (N i) is obtained from a heat budget equation. Results showed that N i is a function of w a, radiative cooling, particle size, and supersaturation. The large-scale models may have large uncertainties related to microphysical and dynamical processes (e.g., particle size and vertical air velocity, respectively), which can directly or indirectly influence radiative processes. Overall, the results suggest that the microphysical and dynamical properties of Arctic clouds need to be further explored for climate change studies.

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I. Gultepe, G. A. Isaac, W. R. Leaitch, and C. M. Banic

Abstract

Airborne observations conducted in marine stratus over the cast coast of Canada during the North Atlantic Regional Experiment in the summer of 1993 are used to develop cloud microphysical parameterization schemes for general circulation models. Observations of cloud droplet number concentration (N d), interstitial aerosol number concentration, temperature, vertical air velocity (w), and liquid water content (LWC) are considered, as well as determination of the effective radius (r eff) and total particle concentration (interstitial aerosol + cloud droplet). Statistical techniques are used to obtain regression equations among the above parameters. For individual clouds, an inverse relationship between the interstitial aerosol concentration and droplet concentration is always observed. In general, variations in r eff are determined by N d as much as by LWC. The regression equations are compared with current parameterizations for GCMS. Results showed that multiple relationships are present among N d, N t, and w; and r eff, LWC, and N d.

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