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  • Author or Editor: J.C. Wilson x
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J. F. Turner
,
J. C. Iliffe
,
M. K. Ziebart
,
C. Wilson
, and
K. J. Horsburgh

Abstract

As part of the U.K. Hydrographic Office (UKHO)-sponsored Vertical Offshore Reference Frames (VORF) project, a high-resolution model of lowest astronomical tide (LAT) with respect to mean sea level has been developed for U.K.–Irish waters. In offshore areas the model relies on data from satellite altimetry, while in coastal areas data from a 3.5-km-resolution hydrodynamic tide-surge model and tide gauges have been included. To provide for a smooth surface and predict tidal levels in unobserved areas, the data have been merged and interpolated using the thin plate spline method, which has been appropriately tuned by an empirical prediction test whereby observed values at tide gauges were removed from the solution space and surrounding data used to predict its behavior. To allow for the complex coastal morphology, a sea distance function has been implemented within the data weighting, which is shown to significantly enhance the solution. The tuning process allows for independent validation giving a standard error of the resulting surface of 0.2 m for areas with no tidal observations.

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S. H. S. Wilson
,
N. C. Atkinson
, and
J. A. Smith

Abstract

The United Kingdom Meteorological Office (UKMO) has developed an airborne interferometer to act as a simulator for future satellite-based infrared meteorological sounders. The Airborne Research Interferometer Evaluation System (ARIES) consists of a modified commercial interferometer mounted on the UKMO C-130 aircraft. The instrument is sensitive to the wavelength range 3.3–18 μm and has a maximum optical path difference of ±1.037 cm. This paper describes the design and performance of ARIES, discusses instrument calibration, and presents some preliminary results. An important problem associated with the use of the new generation of high-spectral resolution infrared meteorological sounders is that improvements need to be made to knowledge of atmospheric spectroscopy and radiative transfer. These improvements are necessary to extract the promised vertical and absolute resolution in temperature and humidity retrievals from these new high-spectral resolution sounders. By virtue of the extensive instrumentation that is available on the C-130 aircraft for observing and measuring the basic meteorological and atmospheric parameters (e.g., in situ temperature, humidity, and ozone), it is hoped that ARIES will be an important tool for use in studying this issue.

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C. Anderson
,
J. Figa
,
H. Bonekamp
,
J. J. W. Wilson
,
J. Verspeek
,
A. Stoffelen
, and
M. Portabella

Abstract

The Advanced Scatterometer (ASCAT) on the Meteorological Operational (MetOp) series of satellites is designed to provide data for the retrieval of ocean wind fields. Three transponders were used to give an absolute calibration and the worst-case calibration error is estimated to be 0.15–0.25 dB.

In this paper the calibrated data are validated by comparing the backscatter from a range of naturally distributed targets against models developed from European Remote Sensing Satellite (ERS) scatterometer data.

For the Amazon rainforest it is found that the isotropic backscatter decreases from −6.2 to −6.8 dB over the incidence angle range. The ERS value is around −6.5 dB. All ASCAT beams are within 0.1 dB of each other. Rainforest backscatter over a 3-yr period is found to be very stable with annual changes of approximately 0.02 dB.

ASCAT ocean backscatter is compared against values from the C-band geophysical model function (CMOD-5) using ECMWF wind fields. A difference of approximately 0.2 dB below 55° incidence is found. Differences of over 1 dB above 55° are likely due to inaccuracies in CMOD-5, which has not been fully validated at large incidence angles. All beams are within 0.1 dB of each other.

Backscatter from regions of stable Antarctic sea ice is found to be consistent with model backscatter except at large incidence angles where the model has not been validated. The noise in the ice backscatter indicates that the normalized standard deviation of the backscatter values Kp is around 4.5%, which is consistent with the expected value.

These results agree well with the expected calibration accuracy and give confidence that the calibration has been successful and that ASCAT products are of high quality.

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H.H. Jonsson
,
J.C. Wilson
,
C.A. Brock
,
R.G. Knollenberg
,
T.R. Newton
,
J.E. Dye
,
D. Baumgardner
,
S. Borrmann
,
G.V. Ferry
,
R. Pueschel
,
Dave C. Woods
, and
Mike C. Pitts

Abstract

A focused cavity aerosol spectrometer aboard a NASA ER-2 high-altitude aircraft provided high-resolution measurements of the size of the stratospheric particles in the 0.06–2.0-µm-diameter range in flights following the eruption of Mount Pinatubo in 1991. Effects of anisokinetic sampling and evaporation in the sampling system were accounted for by means adapted and specifically developed for this instrument. Calibrations with monodisperse aerosol particles provided the instrument's response matrix, which upon inversion during data reduction yielded the particle size distributions. The resultant dataset is internally consistent and generally shows agreement to within a factor of 2 with comparable measurements simultaneously obtained by a condensation nuclei counter, a forward-scattering spectrometer probe, and aerosol particle impactors, as well as with nearby extinction profiles obtained by satellite measurements and with lidar measurements of backscatter.

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Corey K. Potvin
,
Burkely T. Gallo
,
Anthony E. Reinhart
,
Brett Roberts
,
Patrick S. Skinner
,
Ryan A. Sobash
,
Katie A. Wilson
,
Kelsey C. Britt
,
Chris Broyles
,
Montgomery L. Flora
,
William J. S. Miller
, and
Clarice N. Satrio

Abstract

Thunderstorm mode strongly impacts the likelihood and predictability of tornadoes and other hazards, and thus is of great interest to severe weather forecasters and researchers. It is often impossible for a forecaster to manually classify all the storms within convection-allowing model (CAM) output during a severe weather outbreak, or for a scientist to manually classify all storms in a large CAM or radar dataset in a timely manner. Automated storm classification techniques facilitate these tasks and provide objective inputs to operational tools, including machine learning models for predicting thunderstorm hazards. Accurate storm classification, however, requires accurate storm segmentation. Many storm segmentation techniques fail to distinguish between clustered storms, thereby missing intense cells, or to identify cells embedded within quasi-linear convective systems that can produce tornadoes and damaging winds. Therefore, we have developed an iterative technique that identifies these constituent storms in addition to traditionally identified storms. Identified storms are classified according to a seven-mode scheme designed for severe weather operations and research. The classification model is a hand-developed decision tree that operates on storm properties computed from composite reflectivity and midlevel rotation fields. These properties include geometrical attributes, whether the storm contains smaller storms or resides within a larger-scale complex, and whether strong rotation exists near the storm centroid. We evaluate the classification algorithm using expert labels of 400 storms simulated by the NSSL Warn-on-Forecast System or analyzed by the NSSL Multi-Radar/Multi-Sensor product suite. The classification algorithm emulates expert opinion reasonably well (e.g., 76% accuracy for supercells), and therefore could facilitate a wide range of operational and research applications.

Significance Statement

We have developed a new technique for automatically identifying intense thunderstorms in model and radar data and classifying storm mode, which informs forecasters about the risks of tornadoes and other high-impact weather. The technique identifies storms that are often missed by other methods, including cells embedded within storm clusters, and successfully classifies important storm modes that are generally not included in other schemes, such as rotating cells embedded within quasi-linear convective systems. We hope the technique will facilitate a variety of forecasting and research efforts.

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