Estimating multiple bearings-of-arrival from tornadic storms using the complex Wishart distribution

William G. Frazier; Carrick L. Talmadge; Claus Hetzer; Roger M. Waxler

doi:10.1121/1.5101748

Estimating multiple bearings-of-arrival from tornadic storms using the complex Wishart distribution

The Journal of the Acoustical Society of America ◽

10.1121/1.5101748 ◽

2019 ◽

Vol 145 (3) ◽

pp. 1867-1867

Author(s):

William G. Frazier ◽

Carrick L. Talmadge ◽

Claus Hetzer ◽

Roger M. Waxler

Keyword(s):

Wishart Distribution ◽

Tornadic Storms ◽

Multiple Bearings

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Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms

Atmosphere ◽

10.3390/atmos12050581 ◽

2021 ◽

Vol 12 (5) ◽

pp. 581

Author(s):

Matthew Van Den Broeke

Keyword(s):

Polarimetric Radar ◽

Low Level ◽

Supercell Storms ◽

Supercell Thunderstorms ◽

Near Term ◽

Tornadic Storms ◽

Differential Reflectivity

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

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Sufficiency of a Gaussian power spectrum likelihood for accurate cosmology from upcoming weak lensing surveys

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stab522 ◽

2021 ◽

Author(s):

Robin E Upham ◽

Michael L Brown ◽

Lee Whittaker

Keyword(s):

Power Spectrum ◽

Random Noise ◽

Power Spectra ◽

Stage Iv ◽

Wishart Distribution ◽

Weak Lensing ◽

Dependence Structure ◽

Gaussian Fields ◽

Non Gaussian ◽

Parameter Constraints

Abstract We investigate whether a Gaussian likelihood is sufficient to obtain accurate parameter constraints from a Euclid-like combined tomographic power spectrum analysis of weak lensing, galaxy clustering and their cross-correlation. Testing its performance on the full sky against the Wishart distribution, which is the exact likelihood under the assumption of Gaussian fields, we find that the Gaussian likelihood returns accurate parameter constraints. This accuracy is robust to the choices made in the likelihood analysis, including the choice of fiducial cosmology, the range of scales included, and the random noise level. We extend our results to the cut sky by evaluating the additional non-Gaussianity of the joint cut-sky likelihood in both its marginal distributions and dependence structure. We find that the cut-sky likelihood is more non-Gaussian than the full-sky likelihood, but at a level insufficient to introduce significant inaccuracy into parameter constraints obtained using the Gaussian likelihood. Our results should not be affected by the assumption of Gaussian fields, as this approximation only becomes inaccurate on small scales, which in turn corresponds to the limit in which any non-Gaussianity of the likelihood becomes negligible. We nevertheless compare against N-body weak lensing simulations and find no evidence of significant additional non-Gaussianity in the likelihood. Our results indicate that a Gaussian likelihood will be sufficient for robust parameter constraints with power spectra from Stage IV weak lensing surveys.

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