The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.
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...
Loken, Eric D.; Clark, Adam J.; McGovern, Amy; Flora, Montgomery; Knopfmeier, Kent;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (6): 2017–2044.
Description:
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 rand...
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...
Maahn, Maximilian; Hoffmann, Fabian; Shupe, ,Matthew D.; de Boer, Gijs; Matrosov, Sergey Y.; Luke, Edward P.;
Published Date:
2019
Source:
Atmos. Meas. Tech., 12, 3151–3171, 2019
Description:
Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single robust method exists for assessing the calibration of past cloud radar data sets. Here...