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Probabilistic thunderstorm forecasts using statistical post-processing: Comparison of logistic regression and quantile regression forests and an investigation of physical predictors

Technical report published by KNMI and University of Utrecht

Authors:

Edward Groot
Advisors: Maurice Schmeits, Kirien Whan, Willem-Jan van de Berg

Abstract:

Probabilities of thunderstorm occurrence and conditional probabilities of lightning intensity over The Netherlands are forecast using statistical post-processing with predictors derived from the operational non-hydrostatic numerical weather prediction model Harmonie, at lead times up to 45 hours. Quantile regression forests (QRF) is compared with logistic regression (LR) for thunderstorm occurrence forecasts and with extended LR for lightning intensity forecasts. Using different sets of predictors that these statistical methods may select, it is demonstrated that pre-selection of predictors based on physical understanding and simultaneously exploiting QRF as machine learning tool can help improving statistical post-processing models. QRF is demonstrated to be beneficial for the predictions, with more skillful forecasts than LR for thunderstorm occurrence. Lightning intensity predictions are influenced by inhomogeneity of lightning detection datasets; despite inhomogeneity, skillful predictions can be made with both extended LR and QRF. The regional maximum of Modified Jefferson index and most unstable CAPE are found as best thunderstorm occurrence predictors and the regional minimum of Bradbury index and maximum of K-index emerge as best for lightning intensity. Neither most unstable CAPE nor microphysical predictors (graupel, snow) are essential for thunderstorm occurrence prediction.

Recovering valuations on Demushkin fields

Authors:

Jochen Koenigsmann, K Strommen

Abstract:

Let $K$ be a field with $G_K(2) \simeq G_{\mathbb{Q}_2}(2)$, where $G_F(2)$ denotes the maximal pro-2 quotient of the absolute Galois group of a field $F$. We prove that then $K$ admits a (non-trivial) valuation $v$ which is 2-henselian and has residue field $\mathbb{F}_2$. Furthermore, $v(2)$ is a minimal positive element in the value group $\Gamma_v$ and $[\Gamma_v:2\Gamma_v]=2$. This forms the first positive result on a more general conjecture about the structure of pro-$p$ Galois groups. As an application, we prove a strong version of the birational section conjecture for smooth, complete curves $X$ over $\mathbb{Q}_2$, as well as an analogue for varieties.
Details from ArXiV

Using Probabilistic Machine Learning to Better Model Temporal Patterns in Parameterizations: a case study with the Lorenz 96 model

Authors:

Raghul Parthipan, Hannah M Christensen, J Scott Hosking, Damon J Wischik
More details from the publisher

Using reliability diagrams to interpret the ‘signal-to-noise paradox’ in seasonal forecasts of the winter North Atlantic Oscilation

Authors:

Kristian Strommen, Molly MacRae, Hannah Christensen
More details from the publisher