Most ensembles suffer from underdispersion and systematic biases. One way to correct for these shortcomings is via machine learning (ML), which is advantageous due to its ability to identify and correct nonlinear biases. This study uses a single random forest (RF) to calibrate next-day (i.e., 12–36-h lead time) probabilistic precipitation forecasts over the contiguous United States (CONUS) from the Short-Range Ensemble Forecast System (SREF) with 16-km grid spacing and the High-Resolution Ensemble Forecast version 2 (HREFv2) with 3-km grid spacing. Random forest forecast probabilities (RFFPs) from each ensemble are compared against raw ensemble probabilities over 496 days from April 2017 to November 2018 using 16-fold cross validation. RFFPs are also compared against spatially smoothed ensemble probabilities since the raw SREF and HREFv2 probabilities are overconfident and undersample the true forecast probability density function. Probabilistic precipitation forecasts are evaluated at four precipitation thresholds ranging from 0.1 to 3 in. In general, RFFPs are found to have better forecast reliability and resolution, fewer spatial biases, and significantly greater Brier skill scores and areas under the relative operating characteristic curve compared to corresponding raw and spatially smoothed ensemble probabilities. The RFFPs perform best at the lower thresholds, which have a greater observed climatological frequency. Additionally, the RF-based postprocessing technique benefits the SREF more than the HREFv2, likely because the raw SREF forecasts contain more systematic biases than those from the raw HREFv2. It is concluded that the RFFPs provide a convenient, skillful summary of calibrated ensemble output and are computationally feasible to implement in real time. Advantages and disadvantages of ML-based postprocessing techniques are discussed.
Fierro, Alexandre O.; Wang, Yunheng; Gao, Jidong; Mansell, Edward R.;
Published Date:
2019
Source:
Mon. Wea. Rev. (2019) 147 (11): 4045–4069.
Description:
The assimilation of water vapor mass mixing ratio derived from total lightning data from the Geostationary Lightning Mapper (GLM) within a three-dimensional variational (3DVAR) system is evaluated for the analysis and short-term forecast (≤6 h) of ...
Weckwerth, Tammy M., 1966-; Hanesiak, John; Wilson, James W.; Trier, Stanley B.; Degelia, Samuel K.; Gallus, William A.; Roberts, Rita D.; Wang, Xuguang;
Nocturnal convection initiation (NCI) is more difficult to anticipate and forecast than daytime convection initiation (CI). A major component of the Plains Elevated Convection at Night (PECAN) field campaign in the U.S. Great Plains was to intensivel...
Weather surveillance radars routinely detect smoke of various origin. Of particular significance to the meteorological community are wildfires in forests and/or prairies. For example, one responsibility of the National Weather Service in the USA is t...
High-sensitivity weather radars easily detect nonmeteorological phenomena characterized by weak radar returns. Fireworks are the example presented here. To understand radar observations, an experiment was conducted in which the National Severe Storms...
Deadly tornadoes are rare events, but that level of rarity varies with many factors. In this work, we summarize and update past research on tornado fatalities, and also discuss the environments of deadly tornadoes both from the perspective of proximi...
Erlingis, Jessica M.; Gourley, Jonathan J.; Basara, Jeffrey B. (Jeffrey Brent), 1973-;
Published Date:
2019
Source:
J. Hydrometeor. (2019) 20 (8): 1511–1531.
Description:
Backward trajectories were derived from North American Regional Reanalysis data for 19 253 flash flood reports published by the National Weather Service to determine the along-path contribution of the land surface to the moisture budget for flash flo...
A potential replacement candidate for the aging operational WSR-88D infrastructure currently in place is the phased array radar (PAR) system. The current WSR-88Ds take ~5 min to produce a full volumetric scan of the atmosphere, whereas PAR technology...
To improve severe thunderstorm prediction, a novel pseudo-observation and assimilation approach involving water vapor mass mixing ratio is proposed to better initialize NWP forecasts at convection-resolving scales. The first step of the algorithm ide...
A real-time, weather adaptive, dual-resolution, hybrid Warn-on-Forecast (WoF) analysis and forecast system using the WRF-ARW forecast model has been developed and implemented. The system includes two components, an ensemble analysis and forecast comp...
J. Appl. Meteor. Climatol. (2020) 59 (6): 1051–1068.
Description:
This study analyzes the microphysics and precipitation pattern of Hurricanes Harvey (2017) and Florence (2018) in both the eyewall and outer rainband regions. From the retrievals by a satellite red–green–blue scheme, the outer rainbands show a st...
Jahn, David E.; Gallus, William A.; Nguyen, Phong T. T.; Pan, Qiyun; Cetin, Kristen; Byon, Eunshin; Manuel, Lance; Zhou, Yuyu; Jahani, Elham;
Published Date:
2019
Source:
Atmosphere 2019, 10(12), 727.
Description:
Climate studies based on global climate models (GCMs) project a steady increase in annual average temperature and severe heat extremes in central North America during the mid-century and beyond. However, the agreement of observed trends with climate ...
The potential future installation of a multifunction phased-array radar (MPAR) network will provide capabilities of case-specific adaptive scanning. Knowing the impacts adaptive scanning may have on short-term forecasts will influence scanning strate...
J. Atmos. Oceanic Technol. (2020) 37 (6): 1103–1116.
Description:
Severe thunderstorms and their associated tornadoes pose significant threats to life and property, and using radar data to accurately measure the rotational velocity of circulations in thunderstorms is essential for appropriate, timely warnings. One ...
Lawson, John R.; Galllus, William A.; Potvin, Corey K.;
Published Date:
2020
Source:
Atmosphere 2020, 11(4), 384.
Description:
The bow echo, a mesoscale convective system (MCS) responsible for much hail and wind damage across the United States, is associated with poor skill in convection-allowing numerical model forecasts. Given the decrease in convection-allowing grid spaci...
A synoptic analysis and soil moisture (SM) sensitivity experiment is conducted on the record-breaking rainstorm in Texas associated with Hurricane Harvey on 26–30 August 2017. The rainstorm occurred as the moist tropical air mass associated with Ha...
Jones, Thomas A.; Skinner, Patrick; Yussouf, Nusrat; Knopfmeier, Kent; Reinhart, Anthony; Wang, Xuguang; Bedka, Kristopher; Smith, William Jr.; Palikonda, Rabindra;
Published Date:
2020
Source:
Mon. Wea. Rev. (2020) 148 (5): 1829–1859.
Description:
The increasing maturity of the Warn-on-Forecast System (WoFS) coupled with the now operational GOES-16 satellite allows for the first time a comprehensive analysis of the relative impacts of assimilating GOES-16 all-sky 6.2-, 6.9-, and 7.3-μm channe...
In idealized, horizontally homogeneous, cloud model simulations of convective storms, the action of surface friction can substantially modify the near-ground environmental wind profile over time owing to the lack of a large-scale pressure gradient fo...
Kong, Rong; Xue, Ming; Fierro, Alexandre O.; Jung, Youngsun; Liu, Chengsi; Mansell, Edward R.; MacGorman, D. R.;
Published Date:
2020
Source:
Mon. Wea. Rev. (2020) 148 (5): 2111–2133.
Description:
The recently launched Geostationary Operational Environmental Satellite “R-series” (GOES-R) satellites carry the Geostationary Lightning Mapper (GLM) that measures from space the total lightning rate in convective storms at high spatial and tempo...
Flora, Montgomery L.; Skinner, Patrick S.; Potvin, Corey K.; Reinhart, Anthony E.; Jones, Thomas A.; Yussouf, Nusrat; Knopfmeier, Kent H.;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (6): 1721–1739.
Description:
An object-based verification method for short-term, storm-scale probabilistic forecasts was developed and applied to mesocyclone guidance produced by the experimental Warn-on-Forecast System (WoFS) in 63 cases from 2017 to 2018. The probabilistic mes...
Davies-Jones, Robert; Wood, Vincent T.; Rasmussen, Erik N.;
Published Date:
2020
Source:
J. Atmos. Oceanic Technol. (2020) 37 (6): 1117–1133.
Description:
Formulas are obtained for observed circulation around and contraction rate of a Doppler radar grid cell within a surface of constant launch angle. The cell values near unresolved axisymmetric vortices vary greatly with beam-to-flow angle. To obtain r...
Here we present a new theoretical framework that connects the error growth behavior in numerical weather prediction (NWP) with the atmospheric kinetic energy spectrum. Building on previous studies, our newly proposed framework applies to the canonica...
Fierro, Alexandre O.; Wang, Yunheng; Gao, Jidong; Mansell, Edward R.;
Published Date:
2019
Source:
Mon. Wea. Rev. (2019) 147 (11): 4045–4069.
Description:
The assimilation of water vapor mass mixing ratio derived from total lightning data from the Geostationary Lightning Mapper (GLM) within a three-dimensional variational (3DVAR) system is evaluated for the analysis and short-term forecast (≤6 h) of ...