acronyms.tex

\addcontentsline{toc}{chapter}{Acronyms and Symbols}
\chapter*{Acronyms and Symbols}

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\section*{Acronyms}

\noindent
\begin{longtable}{@{}p{0.25\textwidth}p{0.7\textwidth}@{}}
FMI & Finnish Meteorological Institute \\
NWP & Numerical Weather Prediction \\
Z & Reflectivity factor (mm$^{6}$/m$^{3}$) \\
dBZ & Decibel relative to Z \\
DL & Deep learning \\
NN & Neural Network \\
BNN & Bayesian Neural Network \\
ELBO & Evidence Lower Bound \\
CNN & Convolutional Neural Network \\
BCNN & Bayesian Convolutional Neural Network \\
SVI & Stochastic Variational Inference \\
BBB & Bayes-By-Backprop \\
NLL & Negative Log Likelihood \\
STEPS & Short-Term Ensemble Prediction System \\
LINDA & Lagrangian Integro-Difference equation model with Autoregression\\
CSI & Critical Success Index \\
ETS & Equitable Threat Score \\
FAR & False Alarm Rate \\
POD & Probability of Detection \\
MAE & Mean Absolute Error \\
ME & Mean Error \\
FSS & Fractions Skill Score \\
RAPSD & Radially-averaged Power Spectral Density \\
CRPS & Continuous Ranked Probability Score \\
ROC & Receiver Operating Characteristic \\
AUC & Area Under the Curve \\
\end{longtable}

\vspace*{5mm}

\section*{Symbols}

Possibly confusing symbols are listed here (non-exhaustively).

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\begin{longtable}{@{}p{0.25\textwidth}p{0.7\textwidth}@{}}
$\sigma_q$ & Gaussian Posterior standard deviation \\
$\mu_q$ & Gaussian Posterior mean \\
$\sigma_\ell$ & Gaussian Negative Log Likelihood observational noise parameter \\
$\sigma_1$, $\sigma_2$ & Gaussian Scale Mixture prior standard deviations one and two \\
$\sigma_P$ & Gaussian Prior standard deviation \\
$\mu_P$ & Gaussian Prior mean \\
\end{longtable}