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  1. Abstract

    Global Forecast System (GFS), North American Mesoscale Forecast System (NAM), and High-Resolution Rapid Refresh (HRRR) 2-m temperature, 10-m wind speed, and precipitation accumulation forecasts initialized at 1200 UTC are verified against New York State Mesonet (NYSM) observations from 1 January 2018 through 31 December 2021. NYSM observations at 126 site locations are used to calculate standard error statistics (e.g., forecast error, root-mean-square error) for temperature and wind speed and contingency table statistics for precipitation across forecast hours, meteorological seasons, and regions. The majority of the focus is placed on the first 18 forecast hours to allow for comparison among all three models. A daily NYSM station-mean temperature error analysis identified a slight cold bias at temperatures below 25°C in the GFS, a cool-to-warm bias as forecast temperatures warm in the HRRR, and a warm bias at temperatures above 30°C in each model. Differences arise when considering temperature biases with respect to lead times and seasons. Wind speeds are overforecast at all ranges in each season, and forecast wind speeds ≥ 18 m s−1are rarely observed. Performance diagrams indicate overall good forecast performance at precipitation thresholds of 0.1–1.5 mm, but with a high frequency bias in the GFS and NAM. This paper provides an overview of deterministic forecast performance across New York State, with the aim of sharing common biases associated with temperature, wind speed, and precipitation with operational forecasters and is the first step in developing a real-time model forecast uncertainty prediction tool.

     
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  2. null (Ed.)
    Abstract This study examines climatological potential vorticity streamer (PVS) activity associated with Rossby wave breaking (RWB), which can impact TC activity in the subtropical North Atlantic (NATL) basin via moisture and wind anomalies. PVSs are identified along the 2-PVU (1 PVU = 10 −6 K kg −1 m 2 s −1 ) contour on the 350-K isentropic surface, using a unique identification technique that combines previous methods. In total, 21 149 individual PVS instances are identified from the ERA-Interim (ERAI) climatology during June–November over 1979–2015 with a peak in July–August. The total number of PVSs identified in this study is more than previous PVS climatologies for this region, since the new technique identifies a wider range of cases. Variations in PVS size and intensity prompt the development of a new PVS activity index (PVSI), which provides an integrated measure of PVS activity that can improve comparisons with TC activity. For instance, PVSI has a stronger negative correlation with seasonal TC activity ( r = −0.55) relative to PVS frequency, size, or intensity alone. PVSI in June–July is also positively correlated with PVSI in August–November ( r = 0.67), suggesting predictive capability. Compared to the ERAI and Japan Meteorological Agency 55-Year Reanalysis (JRA-55) climatology, there are more PVSs in the Climate Forecast System Reanalysis (CFSR) but these have weaker average intensity overall. While no long-term trend in PVSI is observed in the ERAI or JRA-55 climatologies, a negative trend is observed in CFSR, which could be related to differences in near tropopause static stability early in the climatological period (1979–86) between the CFSR and ERAI datasets. 
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  3. Abstract

    Stochastic model error schemes, such as the stochastic perturbed parameterization tendencies (SPPT) and independent SPPT (iSPPT) schemes, have become an increasingly accepted method to represent model error associated with uncertain subgrid-scale processes in ensemble prediction systems (EPSs). While much of the current literature focuses on the effects of these schemes on forecast skill, this research examines the physical processes by which iSPPT perturbations to the microphysics parameterization scheme yield variability in ensemble rainfall forecasts. Members of three 120-member Weather Research and Forecasting (WRF) Model ensemble case studies, including two distinct heavy rain events over Taiwan and one over the northeastern United States, are ranked according to an area-averaged accumulated rainfall metric in order to highlight differences between high- and low-precipitation forecasts. In each case, high-precipitation members are characterized by a damping of the microphysics water vapor and temperature tendencies over the region of heaviest rainfall, while the opposite is true for low-precipitation members. Physically, the perturbations to microphysics tendencies have the greatest impact at the cloud level and act to modify precipitation efficiency. To this end, the damping of tendencies in high-precipitation forecasts suppresses both the loss of water vapor due to condensation and the corresponding latent heat release, leading to grid-scale supersaturation. Conversely, amplified tendencies in low-precipitation forecasts yield both drying and increased positive buoyancy within clouds.

     
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  4. Abstract

    Perturbations to the potential vorticity (PV) waveguide, which can result from latent heat release within the warm conveyor belt (WCB) of midlatitude cyclones, can lead to the downstream radiation of Rossby waves, and in turn high-impact weather events. Previous studies have hypothesized that forecast uncertainty associated with diabatic heating in WCBs can result in large downstream forecast variability; however, these studies have not established a direct connection between the two. This study evaluates the potential impact of latent heating variability in the WCB on subsequent downstream forecasts by applying the ensemble-based sensitivity method to European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasts of a cyclogenesis event over the North Atlantic. For this case, ensemble members with a more amplified ridge are associated with greater negative PV advection by the irrotational wind, which is associated with stronger lower-tropospheric southerly moisture transport east of the upstream cyclone in the WCB. This transport is sensitive to the pressure trough to the south of the cyclone along the cold front, which in turn is modulated by earlier differences in the motion of the air masses on either side of the front. The position of the cold air behind the front is modulated by upstream tropopause-based PV anomalies, such that a deeper pressure trough is associated with a more progressive flow pattern, originating from Rossby wave breaking over the North Pacific. Overall, these results suggest that more accurate forecasts of upstream PV anomalies and WCBs may reduce forecast uncertainty in the downstream waveguide.

     
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  5. Abstract

    The representation of model error in ensemble prediction systems (EPSs) can be limited by the assumptions within parameterization schemes. Stochastic perturbed parameterization tendencies (SPPT) is one representation of model error that randomly perturbs parameterized physical tendencies using a spatially and temporally correlated red-noise field. This research investigates the sensitivity of ensemble rainfall forecasts produced by the Weather Research and Forecasting (WRF) Model to the configuration of SPPT and independent SPPT (iSPPT) for three meso–synoptic-scale heavy rainfall events over the United States and Taiwan, primarily focusing on the ensemble mean and standard deviation as well as forecast skill. Thirty-two 20-member ensembles, which represent a combination of eight configurations of the stochastic perturbation time scale, length scale, and amplitude scale, and four perturbed parameterization schemes, as well as an unperturbed control simulation, are examined for each event. In each case, rainfall standard deviation is most sensitive to the perturbation time scale and amplitude scale. Moreover, microphysics tendency perturbations are associated with the largest standard deviation in two of the three events, followed by perturbations to the total (nonmicrophysics), turbulent mixing, and radiation parameterized tendencies. Additionally, microphysics tendency perturbations are associated with an increase in the areal coverage of heavy rainfall compared to the control forecast, regardless of whether the control forecast over or underrepresents the observed rainfall distribution.

     
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  6. Although there have been numerous studies documenting the processes/environments that lead to the intensification of African easterly waves (AEWs), only a few of these studies investigated the effect of those processes or the environment on the predictability of AEWs. Here, the large-scale modulation of AEW intensity predictability is evaluated using the 51-member ECMWF ensemble prediction system (EPS) during an active AEW period (July–September 2011–13). Forecasts are stratified based on the 72-h AEW intensity standard deviation (SD) to evaluate hypotheses for how different processes contribute to large forecast SD. While large and small SD forecasts are associated with similar baroclinic and barotropic energy conversions, forecasts with large SD are characterized by higher relative humidity values downstream of the AEW trough. These areas of higher humidity are also associated with higher precipitation and precipitation SD, suggesting that uncertainty associated with diabatic processes could be linked with large AEW intensity SD. Although water vapor is a strong function of longitude and phase of convectively coupled equatorial waves, the cases with large and small SD are characterized by similar longitude and wave phase, suggesting that AEWs occurring in certain locations or convectively coupled equatorial wave phases are not more or less predictable.

     
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