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K. J. Evans, P. H. Lauritzen, S. K. Mishra, R. B. Neale, M. A. Taylor, and J. J. Tribbia

Abstract

The authors evaluate the climate produced by the Community Climate System Model, version 4, running with the new spectral element atmospheric dynamical core option. The spectral element method is configured to use a cubed-sphere grid, providing quasi-uniform resolution over the sphere and increased parallel scalability and removing the need for polar filters. It uses a fourth-order accurate spatial discretization that locally conserves mass and total energy. Using the Atmosphere Model Intercomparison Project protocol, the results from the spectral element dynamical core are compared with those produced by the default finite-volume dynamical core and with observations. Even though the two dynamical cores are quite different, their simulated climates are remarkably similar. When compared with observations, both models have strengths and weaknesses but have nearly identical root-mean-square errors and the largest biases show little sensitivity to the dynamical core. The spectral element core does an excellent job reproducing the atmospheric kinetic energy spectra, including fully capturing the observed Nastrom–Gage transition when running at 0.125° resolution.

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R. E. Evans, M. S. J. Harrison, R. J. Graham, and K. R. Mylne

Abstract

One possible method of incorporating model sensitivities into ensemble forecasting systems is to combine ensembles run from two or more models. Furthermore, the use of more than one analysis, to which perturbations are added, may provide further unstable directions for error growth not present with a single analysis.

Results are presented from recent investigations into the potential benefit of combining ensembles from the systems of the European Centre for Medium-Range Weather Forecasts and The Met. Office of the United Kingdom. The multimodel and multianalysis ensemble significantly outperforms either individual system in many performance aspects, including deterministic and probabilistic forecast skill, spread–skill correlations, and breadth of synoptic information. It is demonstrated that these improvements are achieved through the combination of independent, useful information contained in the individual systems, and not through simple cancellation of biases that could occur when ensembles from two different forecast systems are combined. In addition, results indicate that model dependencies are at least comparable with analysis dependencies on medium-range timescales, and so in general both models and both analyses are required in the joint ensemble for the largest benefits.

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K. Franklin Evans, Steven J. Walter, Andrew J. Heymsfield, and Merritt N. Deeter

Abstract

The scattering properties of cirrus clouds at submillimeter-wave frequencies are analyzed and characterized in this paper. This study lays a theoretical foundation for using radiometric measurements to investigate and monitor cirrus properties from high-flying aircraft or satellite. The significance of this capability is that it would provide data on the global distribution of cloud ice mass that is currently required to validate climate models. At present, these needs remain unmet by existing and planned observational systems.

In this study the brightness temperature depression (ΔT b) of upwelling radiation due to cirrus clouds is simulated at 150, 220, 340, 500, 630, and 880 GHz. The effects of a range of size distributions, eight ice particle shapes, and different atmospheric profiles are modeled. The atmospheric transmission is high enough in the submillimeter windows to allow upper-tropospheric sensing from space, but absorption by water vapor reduces the sensitivity to lower cirrus clouds in a simply predictable manner. It is shown that frequencies above 500 GHz have adequate sensitivity to measure cirrus cloud properties. For these higher frequencies, the ΔT b is closely proportional to ice water path (IWP) for median mass equivalent sphere diameters (D me) above 125 μm. The differing sensitivity with frequency allows two channels to determine particle size.

A two-channel Bayesian algorithm is developed to assess retrieval accuracy with a Monte Carlo error analysis procedure. Particle shape, size distribution width, and receiver noise are considered as error sources. The rms errors for a nadir view with 630/880 GHz are less than 40% for IWP > 5 g m−2 and D me > 100 μm, while using an oblique viewing angle of 73° results in the same accuracy down to an IWP of 1 g m−2 (visible optical depth less than 0.1). The two-channel algorithm and error analysis methods are used to show how submillimeter radiometer and millimeter radar measurements may be combined.

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K. Franklin Evans, R. Paul Lawson, Pat Zmarzly, Darren O'Connor, and Warren J. Wiscombe

Abstract

Due to the spatially inhomogeneous nature of clouds there are large uncertainties in validating remote sensing retrievals of cloud properties with traditional in situ cloud probes, which have sampling volumes measured in liters. This paper introduces a new technique called in situ cloud lidar, which can measure extinction in liquid clouds with sampling volumes of millions of cubic meters. In this technique a laser sends out pulses of light horizontally from an aircraft inside an optically thick cloud, and wide-field-of-view detectors viewing upward and downward measure the time series of the number of photons returned. Diffusion theory calculations indicate that the expected in situ lidar time series depends on the extinction and has a functional form of a power law times an exponential, with the exponential scale depending on the distance to the cloud boundary. Simulations of 532-nm wavelength in situ lidar time series are made with a Monte Carlo radiative transfer model in stochastically generated inhomogeneous stratocumulus clouds. Retrieval simulations are performed using a neural network trained on three parameters fit to the time series of each detector to predict 1) the extinction at four volume-averaging scales, 2) the cloud geometric thickness, and 3) the optical depth at four averaging scales. Even with an assumed 20% lidar calibration error the rms extinction and optical depth retrieval accuracy is only 12%. Simulations with a dual wavelength lidar (532 and 1550 nm) give accurate retrievals of liquid water content and effective radius. The results of a mountain-top demonstration of the in situ lidar technique show the expected power-law time series behavior.

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R. J. Taylor, S. T. Evans, N. K. King, E. T. Stephens, D. R. Packham, and R. G. Vines

Abstract

Convection in the air above an intense fire in northern Australia has been studied, and the results are compared with those of an earlier investigation.

At the height of the fire a short-lived condensation cloud, covering little more than 10% of the total fire area, rose to almost 6000 m above ground level. It is suggested that the rising column acted effectively as a barrier to the wind, so reducing mixing with the surrounding air and allowing convection to proceed very rapidly by the release of latent heat alone. In the earlier study it is likely that similar behavior occurred, but the effect was less marked.

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R. A. Ferrare, S. H. Melfi, D. N. Whiteman, K. D. Evans, F. J. Schmidlin, and D. O'C. Starr

Abstract

This paper examines the calibration characteristics of the NASA/GSFC Raman water vapor lidar during three field experiments that occurred between 1991 and 1993. The lidar water vapor profiles are calibrated using relative humidity profiles measured by AIR and Vaisala radiosondes. The lidar calibration computed using the AIR radiosonde, which uses a carbon hygristor to measure relative humidity, was 3%–5% higher than that computed using the Vaisala radiosonde, which uses a thin film capacitive element. These systematic differences were obtained for relative humidities above 30% and so cannot be explained by the known poor low relative humidity measurements associated with the carbon hygristor. The lidar calibration coefficient was found to vary by less than 1% over this period when determined using the Vaisala humidity data and by less than 5% when using the AIR humidity data. The differences between the lidar relative humidity profiles and those measured by these radiosondes are also examined. These lidar–radiosonde comparisons are used in combination with a numerical model of the lidar system to assess the altitude range of the GSFC lidar. The model results as well as the radiosonde comparisons indicate that for a lidar located at sea level measuring a typical midlatitude water vapor profile, the absolute error in relative humidity for a 10-min, 75-m resolution profile is less than 10% for altitudes below 8.5 km. Model results show that this maximum altitude can be extended to 10 km by increasing the averaging time and/or reducing the range resolution.

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D. R. Easterling, J. L. Evans, P. Ya. Groisman, T. R. Karl, K. E. Kunkel, and P. Ambenje

Variations and trends in extreme climate events have only recently received much attention. Exponentially increasing economic losses, coupled with an increase in deaths due to these events, have focused attention on the possibility that these events are increasing in frequency. One of the major problems in examining the climate record for changes in extremes is a lack of high-quality, long-term data. In some areas of the world increases in extreme events are apparent, while in others there appears to be a decline. Based on this information increased ability to monitor and detect multidecadal variations and trends is critical to begin to detect any observed changes and understand their origins.

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J. R. Wang, S. H. Melfi, P. Racette, D. N. Whitemen, L. A. Chang, R. A. Ferrare, K. D. Evans, and F. J. Schmidlin

Abstract

Simultaneous measurements of atmospheric water vapor were made by the Millimeter-wave Imaging Radiometer (MIR), Raman lidar, and rawinsondes. Two types of rawinsonde sensor packages (AIR and Vaisala) were carried by the same balloon. The measured water vapor profiles from Raman lidar, and the Vaisala and AIR sondes were used in the radiative transfer calculations. The calculated brightness temperatures were compared with those measured from the MIR at all six frequencies (89, 150, 183.3 ± 1, 183.3 ±3, 183.3 ±7, and 220 GHz). The results show that the MIR-measured brightness temperatures agree well (within ±K) with those calculated from the Raman lidar and Vaisala measurements. The brightness temperatures calculated from the AIR sondes differ from the MIR measurements by as much as 10 K, which can be attributed to low sensitivity of the AIR sondes at relative humidity less than 20%. Both calculated and the MIR-measured brightness temperatures were also used to retrieve water vapor profiles. These retrieved profiles were compared with those measured by the Raman lidar and rawinsondes. The results of these comparisons suggest that the MIR can measure the brightness of a target to an accuracy of at most ±K and is capable of retrieving useful water vapor profiles.

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B. B. Demoz, D. O’C. Starr, K. D. Evans, A. R. Lare, D. N. Whiteman, G. Schwemmer, R. A. Ferrare, J. E. M. Goldsmith, and S. E. Bisson

Abstract

Detailed observations of the interactions of a cold front and a dryline over the central United States that led to dramatic undulations in the boundary layer, including an undular bore, are investigated using high-resolution water vapor mixing ratio profiles measured by Raman lidars. The lidar-derived water vapor mixing ratio profiles revealed the complex interaction between a dryline and a cold-frontal system. An elevated, well-mixed, and deep midtropospheric layer, as well as a sharp transition (between 5- and 6-km altitude) to a drier region aloft, was observed. The moisture oscillations due to the undular bore and the mixing of the prefrontal air mass with the cold air at the frontal surface are all well depicted. The enhanced precipitable water vapor and roll clouds, the undulations associated with the bore, the strong vertical circulation and mixing that led to the increase in the depth of the low-level moist layer, and the subsequent lifting of this moist layer by the cold-frontal surface, as well as the feeder flow behind the cold front, are clearly indicated.

A synthesis of the Raman lidar–measured water vapor mixing ratio profiles, satellite, radiometer, tower, and Oklahoma Mesonet data indicated that the undular bore was triggered by the approaching cold front and propagated south-southeastward. The observed and calculated bore speeds were in reasonable agreement. Wave-ducting analysis showed that favorable wave-trapping mechanisms existed; a low-level stable layer capped by an inversion, a well-mixed midtropospheric layer, and wind curvature from a low-level jet were found.

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D. N. Whiteman, B. Demoz, K. Rush, G. Schwemmer, B. Gentry, P. Di Girolamo, J. Comer, I. Veselovskii, K. Evans, S. H. Melfi, Z. Wang, M. Cadirola, B. Mielke, D. Venable, and T. Van Hove

Abstract

The NASA Goddard Space Flight Center (GSFC) Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP), which occurred in May and June 2002 in the midwestern part of the United States. The SRL received extensive optical modifications prior to and during the IHOP campaign that added new measurement capabilities and enabled unprecedented daytime water vapor measurements by a Raman lidar system. Improvements were also realized in nighttime upper-tropospheric water vapor measurements. The other new measurements that were added to the SRL for the IHOP deployment included rotational Raman temperature, depolarization, cloud liquid water, and cirrus cloud ice water content. In this first of two parts, the details of the operational configuration of the SRL during IHOP are provided along with a description of the analysis and calibration procedures for water vapor mixing ratio, aerosol depolarization, and cirrus cloud extinction-to-backscatter ratio. For the first time, a Raman water vapor lidar calibration is performed, taking full account of the temperature sensitivity of water vapor and nitrogen Raman scattering. Part II presents case studies that permit the daytime and nighttime error statistics to be quantified.

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