CSU-MLP GEFS day-1 "first-guess" excessive rainfall forecasts: aggregate evaluation and synoptic regimes of best- and worst-performing forecasts

2022 Summer.Includes bibliographical references.Forecasting excessive rainfall, particularly flash flood-producing rainfall, is an important problem that remains difficult due to the small spatial scales and varying temporal scales at which they occur. One important operational product that highlights areas for potential excessive rainfall and flash flood occurrences is the Excessive Rainfall Outlook (ERO) issued by the NOAA Weather Prediction Center (WPC), which provides outlooks for lead times of 1-3 days. To address the need for additional tools for WPC forecasters while forming a given ERO, the Colorado State University Machine Learning Probabilities (CSU-MLP) system, a probabilistic forecast system for excessive rainfall (and other convective hazards), was developed to produce forecasts to be used as a "first-guess" ERO. CSU-MLP employs the use of a random forest (RF) algorithm trained using NOAA's Second-Generation Global Ensemble Forecast System Reforecast (GEFS/R) and precipitation observations, while using the operational GEFS with the trained model to produce real-time forecasts. Initially developed as a medium range guidance (2-3 day lead time), CSU-MLP has produced day-1 forecasts that have been evaluated favorably during the 4-week Flash Flood and Intense Rainfall Experiment (FFaIR) in the summer of 2020. However, CSU-MLP day-1 forecasts have been observed to have daily forecast skill that can vary widely between days. This work will include an aggregate evaluation of CSU-MLP day-1 forecasts over a longer period of study (3 March 2019 – 15 October 2020) than that of FFaIR, and an identification of synoptic regimes for which these forecasts tend to perform at their best and worst. Results show that CSU-MLP day-1 forecasts are reliable, provide adequate discrimination of excessive rainfall events (AuROC =0.819), and have comparable performance, evaluated by use of the Brier skill score (BSS), to that of the ERO (CSU-MLP BSS = 0.081; ERO BSS = 0.085). However, CSU-MLP forecasts have a higher frequency of categorical probabilities (≥ 0.05) which results in larger variations of daily BSS. Synoptic regimes of best-performing daily forecasts reveal a tendency for these regimes to be characterized by moderate to strong large-scale forcing and relatively high low-level and column moisture. This would include warm-season regimes with moderate amplitude upper-level troughs, tropical cyclones, cut-off lows, and cool-season regimes where strong forcing is co-located near an abundant moisture source. Forecasts tend to perform worst when there is strong large-scale forcing and low-level and column moisture is relatively low, such as cool-season regimes with large amplitude troughs and surface cyclones but higher levels of atmospheric moisture are not present nor as widespread. This work has implications for WPC forecasters as they use the "first-guess" forecasts while developing the ERO for a given day, as well as implications for future CSU-MLP system model iterations and/or designs

The dipole picture and the non-relativistic expansion

We study exclusive quarkonium production in the dipole picture at next-to-leading order (NLO) accuracy, using the non-relativistic expansion for the quarkonium wavefunction. This process offers one of the best ways to obtain information about gluon distributions at small x, in ultraperipheral heavy ion collisions and in deep inelastic scattering. The quarkonium light cone wave functions needed in the dipole picture have typically been available only at tree level, either in phenomenological models or in the nonrelativistic limit. In this paper, we discuss the compatibility of the dipole approach and the non-relativistic expansion and compute NLO relativistic corrections to the quarkonium light-cone wave function in light-cone gauge. Using these corrections we recover results for the NLO decay width of quarkonium to e+e− and we check that the non-relativistic expansion is consistent with ERBL evolution and with B-JIMWLK evolution of the target. The results presented here will allow computing the exclusive quarkonium production rate at NLO once the one loop photon wave function with massive quarks, currently under investigation, is known. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).Peer reviewe

Modelling and characterization of cell collapse in aluminium foams during dynamic loading

Plate-impact experiments have been conducted to investigate the elastic–plastic behaviour of shock wave propagation and pore collapse mechanisms of closed-cell aluminium foams. FE modelling using a meso-scale approach has been carried out with the FE software ABAQUS/Explicit. A micro-computed tomography-based foam geometry has been developed and microstructural changes with time have been investigated to explore the effects of wave propagation. Special attention has been given to the pore collapse mechanism. The effect of velocity variations on deformation has been elucidated with three different impact conditions using the plate-impact method. Free surface velocity (ufs) was measured on the rear of the sample to understand the evolution of the compaction. At low impact velocities, the free-surface velocity increased gradually, whereas an abrupt rise of free-surface velocity was found at an impact velocity of 845 m/s with a copper flyer-plate which correlates with the appearance of shock. A good correlation was found between experimental results and FE predictions

Embedding in Shawi narrations: A quantitative analysis of embedding in a post-colonial Amazonian indigenous society

In this article, we provide the first quantitative account of the frequent use of embedding in Shawi, a Kawapanan language spoken in Peruvian Northwestern Amazonia. We collected a corpus of ninety-two Frog Stories (Mayer 1969) from three different field sites in 2015 and 2016. Using the glossed corpus as our data, we conducted a generalised mixed model analysis, where we predicted the use of embedding with several macrosocial variables, such as gender, age, and education level. We show that bilingualism (Amazonian Spanish-Shawi) and education, mostly restricted by complex gender differences in Shawi communities, play a significant role in the establishment of linguistic preferences in narration. Moreover, we argue that the use of embedding reflects the impact of the mestizo1 society from the nineteenth century until today in Santa Maria de Cahuapanas, reshaping not only Shawi demographics but also linguistic practice

Parallel Excluded Volume Tempering for Polymer Melts

We have developed a technique to accelerate the acquisition of effectively uncorrelated configurations for off-lattice models of dense polymer melts which makes use of both parallel tempering and large scale Monte Carlo moves. The method is based upon simulating a set of systems in parallel, each of which has a slightly different repulsive core potential, such that a thermodynamic path from full excluded volume to an ideal gas of random walks is generated. While each system is run with standard stochastic dynamics, resulting in an NVT ensemble, we implement the parallel tempering through stochastic swaps between the configurations of adjacent potentials, and the large scale Monte Carlo moves through attempted pivot and translation moves which reach a realistic acceptance probability as the limit of the ideal gas of random walks is approached. Compared to pure stochastic dynamics, this results in an increased efficiency even for a system of chains as short as $N = 60$ monomers, however at this chain length the large scale Monte Carlo moves were ineffective. For even longer chains the speedup becomes substantial, as observed from preliminary data for $N = 200$