Aaron Johnson

Frostburg State University · Department of Geography

This study aims to investigate how assimilating GOES‐16 ABI infrared brightness temperature (BT) with different microphysics schemes affects the convection‐allowing analysis and prediction of the 3 May 2020 bow echo case. The Gridpoint Statistical Interpolation‐based Ensemble Kalman Filter (GSI‐EnKF) system and Weather Research and Forecasting (WRF...

The Advanced Baseline Imager (ABI) aboard the GOES-16 and GOES-17 satellites provides high-resolution observations of cloud structures that could be highly beneficial for convective-scale DA. However, only clear-air radiance observations are typically assimilated at operational centers due to a variety of problems associated with cloudy radiance da...

This study evaluates simulated radiance forecasts from a series of controlled experiments consisting of FV3‐LAM forecasts with different configurations of model physics and vertical resolution. The forecasts were produced during the 2020 Hazardous Weather Testbed Spring Forecasting Experiments on the same forecast cases. The evaluation includes gri...

Given the large range of resolvable space and time scales in large-domain convection-allowing for ensemble forecasts, there is a need to better understand optimal initial-condition perturbation strategies to sample the forecast uncertainty across these space and time scales. This study investigates two initial-condition perturbation strategies for...

There is a growing interest in the use of ground-based remote sensors for Numerical Weather Prediction (NWP), which is sparked by their potential to address the currently existing observation gap within the Planetary Boundary Layer (PBL). Nevertheless, open questions still exist regarding the relative importance of and synergy among various instrum...

Convection-allowing model (CAM) ensembles contain a distinctive ability to predict convective initiation location, mode, and morphology. Previous studies on CAM ensemble verification have primarily used neighborhood-based methods. A recently introduced object-based probabilistic (OBPROB) framework provides an alternative and novel framework in whic...

A case study characterized by Arctic cyclogenesis following a tropopause polar vortex (TPV)-induced Rossby wave initiation event is used to better understand how well existing observations constrain analyses of processes influencing Arctic cyclone predictive skill. Complementary techniques of observation system experiments (OSE) and ensemble sensit...

This study investigates impacts on convection-permitting ensemble forecast performance of different methods of generating the ensemble IC perturbations in the context of simultaneous physics diversity among the ensemble members. A total of 10 convectively active cases are selected for a systematic comparison of different methods of perturbing IC pe...

An object-based probabilistic (OBPROB) forecasting framework is developed and applied, together with a more traditional neighborhood-based framework, to convection-permitting ensemble forecasts produced by OU (University of Oklahoma) MAP (Multi-scale data-Assimilation and Predictability) lab during 2017 and 2018 NOAA Hazardous Weather Testbed Sprin...

Four case studies from the Plains Elevated Convection at Night (PECAN) field experiment are used to investigate the impacts of horizontal and vertical resolution, and vertical mixing parameterization, on predictions of bore structure and upscale impacts of bores on their mesoscale environment. The reduction of environmental convective inhibition (C...

There has been a recent wave of attention given to atmospheric bores in order to understand how they evolve and initiate and maintain convection during the night. This surge is attributable to data collected during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. A salient aspect of the PECAN project is its focus on using multip...

This paper presents a case study from an intensive observing period (IOP) during the Plains Elevated Convection at Night (PECAN) field experiment that was focused on a bore generated by nocturnal convection. Observations from PECAN IOP 25 on 11 July 2015 are used to evaluate the performance of high-resolution Weather Research and Forecasting Model...

The initiation of new convection at night in the Great Plains contributes to a nocturnal maximum in precipitation and produces localized heavy rainfall and severe weather hazards in the region. Although previous work has evaluated numerical model forecasts and data assimilation (DA) impacts for convection initiation (CI), most previous studies focu...

A prototype convection-allowing system using the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model and employing an ensemble Kalman filter (EnKF) data assimilation technique has been developed and used during the spring 2016 and 2017 Hazardous Weather Testbeds. This system assimilates WSR-88D reflectivity and radial...

Multi-scale ensemble-based data assimilation and forecasts were performed in real time during the Plains Elevated Convection At Night (PECAN) field experiment. A 20-member ensemble of forecasts at 4km grid spacing was initialized daily at both 1300 and 1900 UTC, together with a deterministic forecast at 1km grid spacing initialized at 1300 UTC. The...

A real-time GSI-based and ensemble-based data assimilation (DA) and forecast system was implemented at the University of Oklahoma during the 2015 Plains Elevated Convection At Night (PECAN) experiment. Extensive experiments on the configuration of the cycled DA and on both the DA and forecast physics ensembles were conducted using retrospective cas...

The impacts of multiscale flow-dependent initial condition (IC) perturbations for storm-scale ensemble forecasts of midlatitude convection are investigated using perfect-model observing system simulation experiments. Several diverse cases are used to quantitatively and qualitatively understand the impacts of different IC perturbations on ensemble f...

A GSI-based data assimilation (DA) system, including three-dimensional variational assimilation (3DVar) and ensemble Kalman filter (EnKF), is extended to the multiscale assimilation of both meso- and synoptic-scale observation networks and convective-scale radar reflectivity and velocity observations. EnKF and 3DVar are systematically compared in t...

Multiscale convection-allowing precipitation forecast perturbations are examined for two forecasts and systematically over 34 forecasts out to 30-h lead time using Haar Wavelet decomposition. Two small-scale initial condition (IC) perturbation methods are compared to the larger-scale IC and physics perturbations in an experimental convection-allowi...

Forecasts generated by the Center for Analysis and Prediction of Storms with 1- and 4-km grid spacing using the Advanced Research Weather Research and Forecasting Model (ARW-WRF; ARW1 and ARW4, respectively) for the 2009-11 NOAA Hazardous Weather Testbed Spring Experiments are compared and verified. Object-based measures, including average values o...

Object-based verification of deterministic forecasts from a convection-allowing ensemble for the 2009 NOAA Hazardous Weather Testbed Spring Experiment is conducted. The average of object attributes is compared between forecasts and observations and between forecasts from subensembles with different model dynamics. Forecast accuracy for the full ens...

Neighborhood and object-based probabilistic precipitation forecasts from a convection-allowing ensemble are verified and calibrated. Calibration methods include logistic regression, one- and two-parameter reliability-based calibration, and cumulative distribution function (CDF)-based bias adjustment. Newly proposed object-based probabilistic foreca...

Twenty-member real-time convection-allowing storm-scale ensemble forecasts with perturbations to model physics, dynamics, initial conditions (IC), and lateral boundary conditions (LBC) during the NOAA Hazardous Weather Testbed Spring Experiment provide a unique opportunity to study the relative impact of different sources of perturbation on convect...

Convection-allowing ensemble forecasts with perturbations to model physics, dynamics, and initial (IC) and lateral boundary conditions (LBC) generated by the Center for the Analysis and Prediction of Storms for the NOAA Hazardous Weather Testbed (HWT) Spring Experiments provide a unique opportunity to understand the relative impact of different sou...

This study seeks a systematic understanding of the impacts and importance of sampling different sources of uncertainties using the convection-allowing ensemble run by Center for Analysis and Prediction of Storms (CAPS) during the Hazardous Weather Testbed Spring Experiment. Recent advances in computational resources allowed production of an exper...