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Thomas A. Jones, Sundar A. Christopher, and Walt Petersen

Abstract

Dual-polarimetric microwave wavelength radar observations of an apartment fire in Huntsville, Alabama, on 3 March 2008 are examined to determine the radar-observable properties of ash and fire debris lofted into the atmosphere. Dual-polarimetric observations are collected at close range (<20 km) by the 5-cm (C band) Advanced Radar for Meteorological and Operational Research (ARMOR) radar operated by the University of Alabama in Huntsville. Precipitation radars, such as ARMOR, are not sensitive to aerosol-sized (D < 10 μm) smoke particles, but they are sensitive to the larger ash and burnt debris embedded within the smoke plume. The authors also assess if turbulent eddies caused by the heat of the fire cause Bragg scattering to occur at the 5-cm wavelength.

In this example, the mean reflectivity within the debris plume from the 1.3° elevation scan was 9.0 dBZ, with a few values exceeding 20 dBZ. The plume is present more than 20 km downstream of the fire, with debris lofted at least 1 km above ground level into the atmosphere. Velocities up to 20 m s−1 are present within the plume, indicating that the travel time for the debris from its source to the maximum range of detection is less than 20 min. Dual-polarization observations show that backscattered radiation is dominated by nonspherical, large, oblate targets as indicated by nonzero differential reflectivity values (mean = 1.7 dB) and low correlation coefficients (0.49). Boundary layer convective rolls are also observed that have very low reflectivity values (−6.0 dBZ); however, differential reflectivity is much larger (3.2 dB). This is likely the result of noise, because ARMOR differential reflectivity is not reliable for reflectivity values <0 dBZ. Also, copolar correlation is even lower compared to the debris plume (0.42). The remainder of the data mainly consists of atmospheric and ground-clutter noise. The large differential phase values coupled with positive differential reflectivity strongly indicate that the source of much of the return from the debris plume is particle scattering. However, given the significant degree of noise present, a substantial contribution from Bragg scattering cannot be entirely ruled out.

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Matthew S. Jones, Mark A. Saunders, and Trevor H. Guymer

Abstract

The Along Track Scanning Radiometer (ATSR) was launched in July 1991 on the European Space Agency's first remote sensing satellite ERS-1. ATSR has the potential to measure sea surface temperature (SST) to a precision of 0.3 K, which is more than double the accuracy of any previously flown infrared radiometer. A key factor limiting ATSR's performance is remnant cloud contamination. Examination of the 0.5° spatially averaged ATSR SST data (version 500) from the South Atlantic for the whole of 1992 and 1993 shows the presence of regional cloud contamination in the night SST measurements. The authors establish a figure of 5.7% as a lower limit for this nighttime cloud contamination. The contamination leads to differences between day and night mean SSTs and to poor comparisons with in situ thermosalinograph SST data. A new cloud filtering process designed for postprocessing of the data is proposed to remove the contamination. The algorithm presented here relies on assumptions that the day data are less cloud contaminated than the night data and that a large proportion of the SST variability can he explained by an annual and semiannual model. Testing the filtering algorithm shows that differences between the day and night SST signals are substantially reduced and that comparisons with the thermosalinograph SST data improve by a factor of 3 in rms scatter and by 0.3 K in the mean difference.

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Robert Davies-Jones, Vincent T. Wood, and Erik N. Rasmussen

Abstract

Formulas are obtained for observed circulation around and contraction rate of a Doppler radar grid cell within a surface of constant launch angle. The cell values near unresolved axisymmetric vortices vary greatly with beam-to-flow angle. To obtain reliable standard measures of vortex strength we bilinearly interpolate data to points on circles of specified radii concentric with circulation centers and compute the Doppler circulations around and the areal contraction rates of these circles from the field of mean Doppler velocities. These parameters are proposed for detection of strong tornadoes and mesocyclonic winds. The circulation and mean convergence around the Union City, Oklahoma, tornado of 24 May 1973 are computed. After doubling to compensate for the unobserved wind component, the circulation (1.1 × 105 m2 s−1) agrees with a previous photogrammetric measurement. The mature tornado was embedded in a region, 6 km in diameter, of nearly uniform strong convergence (~5.5 × 10−3 s−1) without a simultaneous mesocyclone. A model of a convergent vortex inputted to a Doppler radar emulator reproduces these results. Moving the model vortex shows that for a WSR-88D with superresolution, the circulation is relatively insensitive to range and azimuth. WSR-88D data of the 31 May 2013 El Reno storm are also analyzed. The tornado formed in a two-celled mesocyclone with strong inflow 5 km away. In the next 8 min the circulation near the axis doubled and the areal contraction rate at 5 km increased by 50%. This signified a large probability of strong tornadoes embedded in powerful storm-scale winds.

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C. Paton-Walsh, R. L. Mittermeier, W. Bell, H. Fast, N. B. Jones, and A. Meier

Abstract

The authors report the results of an intercomparison of vertical column amounts of hydrogen chloride (HCl), hydrogen fluoride (HF), nitrous oxide (N2O), nitric acid (HNO3), methane (CH4), ozone (O3), carbon dioxide (CO2), and nitrogen (N2) derived from the spectra recorded by two ground-based Fourier transform infrared (FTIR) spectrometers operated side-by-side using the sun as a source. The procedure used to record spectra and derive vertical column amounts follows the format of previous instrument intercomparisons organized by the Network for the Detection of Atmospheric Composition Change (NDACC), formerly known as the Network for Detection of Stratospheric Change (NDSC).

For most gases the differences were typically around 3%, and in about half of the results the error bars given by the standard deviation of the measurements from each instrument did not overlap. The worst level of agreement was for HF where differences of over 5% were typical. The level of agreement achieved during this intercomparison is a little worse than that achieved in previous intercomparisons between ground-based FTIR spectrometers.

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Sijie Pan, Jidong Gao, David J. Stensrud, Xuguang Wang, and Thomas A. Jones

Abstract

In this study, the ensemble of three-dimensional variational data assimilation (En3DVar) method for convective-scale weather is adopted and evaluated using an idealized supercell storm simulated by the Weather Research and Forecasting (WRF) Model. Synthetic radar radial velocity, reflectivity, satellite-derived cloud water path (CWP), and total precipitable water (TPW) data are produced from the simulated supercell storm and then these data are assimilated into another WRF Model run that starts with no convection. Two types of experiments are performed. The first assimilates radar and satellite CWP data using a perfect storm environment. The second assimilates additional TPW data using a storm environment with dry bias. The first set of experiments indicates that incorporating CWP and radar data into the assimilation leads to a much faster initiation of supercell storms than found using radar data alone. Assimilating CWP data primarily improves the analyses of nonprecipitating hydrometeor variables. The results from the second set of experiments demonstrate the critical importance of the storm environment. When using the biased storm environment, assimilation of CWP and radar data enhances the analyses, but the forecast skill rapidly decreases over the subsequent 1-h forecast. Further experiments show that assimilating the TPW data has a large impact on storm environment that is essential to the accuracy of the storm forecasts. In general, the combination of radar data and satellite data within the En3DVar results in better analyses and forecasts than when only radar data are used, especially for an imperfect storm environment.

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C. A. Balfour, M. J. Howarth, D. S. Jones, and T. Doyle

Abstract

An evolving coastal observatory has been hosted by the National Oceanography Centre at Liverpool, United Kingdom, for more than nine years. Within this observatory an instrumented ferry system has been developed and operated to provide near-surface scientific measurements of the Irish Sea. Passenger vessels such as ferries have the potential to be used as cost-effective platforms for gathering high-resolution regular measurements of the properties of near-surface water along their routes. They are able to operate on an almost year-round basis, and they usually have a high tolerance to adverse weather conditions. Examples of the application of instrumented ferry systems include environmental monitoring, the generation of long-term measurement time series, the provision of information for predictive model validation, and data for model assimilation purposes.

This paper discusses the development of an engineering system installed on board an Irish Sea passenger ferry. Particular attention is paid to explaining the engineering development required to achieve a robust, automated measuring system that is suitable for long-term continuous operation. The ferry, operating daily between Birkenhead and Belfast or Dublin, United Kingdom, was instrumented between December 2003 and January 2011 when the route was closed. Measurements were recorded at a nominal interval of 100 m and real-time data were transmitted every 15 min. The quality of the data was assessed. The spatial and temporal variability of the temperature and salinity fields are investigated as the ferry crosses a variety of shelf sea and coastal water column types.

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R. Meneghini, J. A. Jones, T. Iguchi, K. Okamoto, and J. Kwiatkowski

Abstract

Satellite weather radars that operate at attenuating wavelengths require an estimate of path attenuation to reconstruct the range profile of rainfall. One such method is the surface reference technique (SRT), by which attenuation is estimated as the difference between the surface cross section outside the rain and the apparent surface cross section measured in rain. This and the Hitschfeld–Bordan method are used operationally to estimate rain rate using data from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. To overcome some of the problems associated with the latest operational version of the SRT, a hybrid surface reference is defined that uses information from the along-track and cross-track variations of the surface cross sections in rain-free areas. Over ocean, this approach eliminates most of the discontinuities in the path-attenuation field. Self-consistency of the estimates is tested by processing the orbits backward as well as forward. Calculations from 2 weeks of PR data show that 90% of the rain events over ocean for which the SRT is classified as reliable or marginally reliable are such that the absolute difference between the forward and backward estimates is less than 1 dB.

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Robert Meneghini, Hyokyung Kim, Liang Liao, Jeffrey A. Jones, and John M. Kwiatkowski

Abstract

It has long been recognized that path-integrated attenuation (PIA) can be used to improve precipitation estimates from high-frequency weather radar data. One approach that provides an estimate of this quantity from airborne or spaceborne radar data is the surface reference technique (SRT), which uses measurements of the surface cross section in the presence and absence of precipitation. Measurements from the dual-frequency precipitation radar (DPR) on the Global Precipitation Measurement (GPM) satellite afford the first opportunity to test the method for spaceborne radar data at Ka band as well as for the Ku-band–Ka-band combination.

The study begins by reviewing the basis of the single- and dual-frequency SRT. As the performance of the method is closely tied to the behavior of the normalized radar cross section (NRCS or σ0) of the surface, the statistics of σ0 derived from DPR measurements are given as a function of incidence angle and frequency for ocean and land backgrounds over a 1-month period. Several independent estimates of the PIA, formed by means of different surface reference datasets, can be used to test the consistency of the method since, in the absence of error, the estimates should be identical. Along with theoretical considerations, the comparisons provide an initial assessment of the performance of the single- and dual-frequency SRT for the DPR. The study finds that the dual-frequency SRT can provide improvement in the accuracy of path attenuation estimates relative to the single-frequency method, particularly at Ku band.

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Cynthia E. Bluteau, Rolf G. Lueck, Gregory N. Ivey, Nicole L. Jones, Jeffrey W. Book, and Ana E. Rice

Abstract

Ocean mixing has historically been estimated using Osborn’s model by measuring the rate of dissipation of turbulent kinetic energy ϵ and the background density stratification N while assuming a value of the flux Richardson number . A constant is typically assumed, despite mounting field, laboratory, and modeling evidence that varies. This challenge can be overcome by estimating the turbulent diffusivity of heat using the Osborn–Cox model. This model, however, requires measuring the rate of dissipation of thermal variance χ, which has historically been challenging, particularly in energetic flows because the high wavenumbers of the temperature gradient spectra are unresolved with current technology. To overcome this difficulty, a method is described that determines χ by spectral fitting to the inertial-convective (IC) subrange of the temperature gradient spectra. While this concept has been exploited for moored time series, particularly near the bottom boundary, it has yet to be adapted to vertical microstructure profilers such as gliders, and autonomous and ship-based vertical profilers from which there are the most measurements. By using the IC subrange, χ, and hence , can be estimated even in very energetic events—precisely the conditions requiring more field observations. During less energetic periods, the temperature gradient spectra can also be integrated to obtain χ. By combining these two techniques, microstrucure profiles at a field site known for its very energetic internal waves are analyzed. This study demonstrates that the spectral fitting approach resolves intense mixing events with . By equating the Osborn and Osborn–Cox models, indirect estimates for can also be obtained.

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A. Wiacek, J. R. Taylor, K. Strong, R. Saari, T. E. Kerzenmacher, N. B. Jones, and D. W. T. Griffith

Abstract

The authors describe the optical design of a high-resolution Fourier Transform Spectrometer (FTS), which serves as the primary instrument at the University of Toronto Atmospheric Observatory (TAO). The FTS is dedicated to ground-based infrared solar absorption atmospheric measurements from Toronto, Ontario, Canada. Instrument performance is discussed in terms of instrumental line shape (ILS) and phase error and modulation efficiency as a function of optical path difference. Typical measurement parameters are presented together with retrieval parameters used to derive total and partial column concentrations of ozone. Retrievals at TAO employ the optimal estimation method (OEM), and some impacts of the necessary a priori constraints are examined. In March 2004, after participating in a retrieval algorithm user intercomparison exercise, the TAO FTS was granted the status of a Complementary Observation Station within the international community of high-resolution FTS users in the Network for the Detection of Atmospheric Composition and Change (NDACC). During this exercise, average differences between total columns retrieved from the same spectra by different users were below 2.1% for O3, HCl, and N2O in the blind phase, and below 1% in the open phase, when all retrieval constraints were identical. Finally, a 2.5-yr time series of monthly mean stratospheric ozone columns agrees within 3% with those retrieved from Optical Spectrograph and Infrared Imager System (OSIRIS) measurements on board the Odin satellite, which is within the errors of both measurement platforms.

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