A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis
A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis
The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physical parameter to the algorithm is the parameter alpha α, defined as the ratio of specific attenuation A to specific differential phase KDP. Examination of a significant sample of tropical and continental precipitation events indicated that α was sensitive to changes in drop size distribution and exhibited lower (higher) values when there were lower (higher) concentrations of larger (smaller) rain drops. As part of the performance assessment, the prototype algorithm generated QPEs utilizing a real-time estimated and a fixed α were created and evaluated. The results clearly indicated ~26% lower errors and a 26% better bias ratio with the QPE utilizing a real-time estimated α as opposed to using a fixed value as was done in previous studies. Comparisons between the QPE utilizing a real-time estimated α and the operational dual-polarization (dual-pol) QPE used on the WSR-88D radar network showed the former exhibited ~22% lower errors, 7% less bias, and 5% higher correlation coefficient when compared to quality controlled gauge totals. The new QPE also provided much better estimates for moderate to heavy precipitation events and performed better in regions of partial beam blockage than the operational dual-pol QPE.
Spain, E. A.; Johnson, S. C.; Hutton, B.; Whittaker, J. M.; Lucieer, V.; Watson, S. J.; Fox, J. M.; Lupton, J.; Arculus, R.; Bradney, A.; Coffin, M. F.;
Published Date:
2020
Source:
Earth and Space Science, 7(3)
Description:
Bubble emission mechanisms from submerged large igneous provinces remains enigmatic. The Kerguelen Plateau, a large igneous province in the southern Indian Ocean, has a long sustained history of active volcanism and glacial/interglacial cycles of sed...
J. Atmos. Oceanic Technol. (2018) 35 (11): 2169–2187.
Description:
Time series simulation is an important tool for developing and testing new signal processing algorithms for weather radar. The methods for simulating time series data have not changed much over the last few decades, but recent advances in computing t...
Rosenow, Andrew A.; Howard, Kenneth; Meitín, José G.;
Published Date:
2018
Source:
Mon. Wea. Rev. (2018) 146 (8): 2469–2481.
Description:
On 24 January 2017, a convective snow squall developed in the San Luis Valley of Colorado. This squall produced rapidly varying winds at San Luis Valley airport in Alamosa, Colorado, with gusts up to 12 m s−1, and an associated visibility drop to 1...
Potvin, Corey K.; Broyles, Chris; Skinner, Patrick S.; Brooks, Harold E.; Rasmussen, Erik;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (1): 15–30.
Description:
The Storm Prediction Center (SPC) tornado database, generated from NCEI’s Storm Data publication, is indispensable for assessing U.S. tornado risk and investigating tornado–climate connections. Maximizing the value of this database, however, requ...
A prototype quantitative precipitation estimate (QPE) algorithm that utilizes specific attenuation A and specific differential phase KDP was developed for inclusion into the Multi-Radar Multi-Sensor (MRMS) system and the Weather Surveillance Radar-19...
Observations from three nights of the Plains Elevated Convection at Night (PECAN) field campaign were used in conjunction with Rapid Refresh model forecasts to find the cause of north–south lines of convection, which initiated away from obvious sur...
Jones, Thomas A.; Skinner, Patrick; Knopfmeier, Kent; Mansell, Edward; Minnis, Patrick; Palikonda, Rabindra; Smith, William Jr.;
Published Date:
2018
Source:
Wea. Forecasting (2018) 33 (6): 1681–1708.
Description:
Forecasts of high-impact weather conditions using convection-allowing numerical weather prediction models have been found to be highly sensitive to the selection of cloud microphysics scheme used within the system. The Warn-on-Forecast (WoF) project ...
Flora, Montgomery L.; Potvin, Corey K.; Wicker, Louis J.;
Published Date:
2018
Source:
Mon. Wea. Rev. (2018) 146 (8): 2361–2379.
Description:
As convection-allowing ensembles are routinely used to forecast the evolution of severe thunderstorms, developing an understanding of storm-scale predictability is critical. Using a full-physics numerical weather prediction (NWP) framework, the sensi...
Wade, Andrew R.; Coniglio, Michael C.; Ziegler, Conrad L.;
Published Date:
2018
Source:
Mon. Wea. Rev. (2018) 146 (8): 2403–2415.
Description:
A great deal of research focuses on how the mesoscale environment influences convective storms, but relatively little is known about how supercells modify the nearby environment. Soundings from three field experiments are used to investigate differen...
Tornado warnings are one of the flagship products of the National Weather Service. We update the time series of various metrics of performance in order to provide baselines over the 1986–2016 period for lead time, probability of detection, false al...
Adams-Selin, Rebecca D.; Clark, Adam J.; Melick, Christopher J.; Dembek, Scott R.; Jirak, Israel L.; Ziegler, Conrad L.;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (1): 61–79.
Description:
Four different versions of the HAILCAST hail model have been tested as part of the 2014–16 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments. HAILCAST was run as part of the National Severe Storms Laboratory (NSSL) WRF Ensemble du...
Cai, C.; Avise, J.; Kaduwela, A.; DaMassa, J.; Warneke, C.; Gilman, J. B.; Kuster, W.; de Gouw, J.; Volkamer, R.; Stevens, P.; Lefer, B.; Holloway, J. S.; Pollack, I. B.; Ryerson, T.; Atlas, E.; Blake, D.; Rappenglueck, B.; Brown, S. S.; Dube, W. P.;
Published Date:
2019
Source:
Journal of Geophysical Research: Atmospheres, 124(6)
Description:
United States Environmental Protection Agency guidance on the use of photochemical models for assessing the efficacy of an emissions control strategy for ozone requires that modeling be used in a relative sense. Consequently, testing a modeling syste...
Cui, Y. Y.; Henze, D. K.; Brioude, J.; Angevine, W. M.; Liu, Z.; Bousserez, N.; Guerrette, J.; McKeen, S. A.; Peischl, J.; Yuan, B.; Ryerson, T.; Frost, G.; Trainer, M.;
Published Date:
2019
Source:
Journal of Geophysical Research: Atmospheres, 124(6)
Description:
Quantifying methane (CH4) emissions from the oil and natural gas (O/NG) production sector is an important regulatory challenge in the United States. In this study, we conduct a set of inversion calculations using different methods to quantify lognorm...
Journal of the Association of Environmental and Resource Economists,7(3)
Description:
Estimating nonmarket benefits for erosion protection can help inform better decision making and policies for communities to adapt to climate change. We estimate private values for a coastal protection option in an empirical setting subject to irrever...
Koch, Steven E.; Fengler, Martin; Chilson, Philip B., 1963-; Elmore, Kimberly L.; Argrow, Brian M.; Andra, David; Lindley, T. Todd;
Published Date:
2018
Source:
J. Atmos. Oceanic Technol. (2018) 35 (11): 2265–2288.
Description:
The potential value of small unmanned aircraft systems (UAS) for monitoring the preconvective environment and providing useful information in real time to weather forecasters for evaluation at a National Weather Service (NWS) Forecast Office are addr...
Gallo, Burkely T.; Clark, Adam J.; Smith, Bryan T.; Thompson, Richard L.; Jirak, Israel; Dembek, Scott R.;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (1): 151–164.
Description:
Probabilistic ensemble-derived tornado forecasts generated from convection-allowing models often use hourly maximum updraft helicity (UH) alone or in combination with environmental parameters as a proxy for right-moving (RM) supercells. However, when...
Seo, Bong-Chul; Krajewski, Witold F.; Ryzhkov, Alexander;
Published Date:
2020
Source:
J. Hydrometeor. (2020) 21 (6): 1333–1347.
Description:
This study demonstrates an implementation of the prototype quantitative precipitation R estimation algorithm using specific attenuation A for S-band polarimetric radar. The performance of R(A) algorithm is assessed, compared to the conventional algor...
The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantita...
Cannon, Forest; Carvalho, Leila M. V.; Jones, Charles; Noriss, Jesse; Bookhagen, Bodo; Kiladis, George N.;
Published Date:
2017
Source:
JGR Atmospheres 122(3): 1456-1474, 2017
Description:
Numerous studies have projected future changes in High Mountain Asia water resources based on temperature and precipitation from global circulation models (GCMs) under future climate scenarios. Although the potential benefit of such studies is immens...
This study develops a flexible Bayesian technique to quantify uncertainties associated with the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) quantitative precipitation estimation (QPE) products over complex terrain. Radar-only rainfa...
Mueller, Michael J.; Mahoney, Kelly M.; Hughes, Mimi;
Published Date:
2017
Source:
Month Weath Rev (2017) 145(9): 3861-3879
Description:
A series of precipitation events impacted the Pacific Northwest during the first two weeks of November 2006. This sequence was punctuated by a particularly potent inland-penetrating atmospheric river (AR) that produced record-breaking precipitation a...
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