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David W. Reynolds and Arnett S. Dennis

The Sierra Cooperative Pilot Project (SCPP) is an investigation of cloud seeding as a means of increasing winter precipitation on the Sierra Nevada. It is a concerted effort in the development of a physically sound cloud-seeding technology. It involves the use of remote-sensing devices, in situ observations, and the application of a numerical targeting model in randomized seeding experiments. The results have led SCPP scientists to believe that shallow but widespread orographic clouds provide the best opportunity for glaciogenic seeding in the central Sierra Nevada.

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Ellen M. Sukovich, F. Martin Ralph, Faye E. Barthold, David W. Reynolds, and David R. Novak

Abstract

Extreme quantitative precipitation forecast (QPF) performance is baselined and analyzed by NOAA’s Hydrometeorology Testbed (HMT) using 11 yr of 32-km gridded QPFs from NCEP’s Weather Prediction Center (WPC). The analysis uses regional extreme precipitation thresholds, quantitatively defined as the 99th and 99.9th percentile precipitation values of all wet-site days from 2001 to 2011 for each River Forecast Center (RFC) region, to evaluate QPF performance at multiple lead times. Five verification metrics are used: probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), frequency bias, and conditional mean absolute error (MAEcond). Results indicate that extreme QPFs have incrementally improved in forecast accuracy over the 11-yr period. Seasonal extreme QPFs show the highest skill during winter and the lowest skill during summer, although an increase in QPF skill is observed during September, most likely due to landfalling tropical systems. Seasonal extreme QPF skill decreases with increased lead time. Extreme QPF skill is higher over the western and northeastern RFCs and is lower over the central and southeastern RFC regions, likely due to the preponderance of convective events in the central and southeastern regions. This study extends the NOAA HMT study of regional extreme QPF performance in the western United States to include the contiguous United States and applies the regional assessment recommended therein. The method and framework applied here are readily applied to any gridded QPF dataset to define and verify extreme precipitation events.

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David W. Reynolds, David A. Clark, F. Wesley Wilson, and Lara Cook

During summer, marine stratus encroaches into the approach to San Francisco International Airport (SFO) bringing low ceilings. Low ceilings restrict landings and result in a high number of arrival delays, thus impacting the National Air Space (NAS). These delays are managed by implementation of ground delay programs (GDPs), which hold traffic on the ground at origination airports in anticipation of insufficient arrival capacity at SFO. In an effort to reduce delays and improve both airport and NAS efficiency, the Federal Aviation Administration (FAA) funded a research effort begun in 1995 to develop an objective decision support system to aid forecasters in the prediction of stratus clearing times. By improving forecasts at this major airport, the scope and duration of ground and airborne holds can be reduced. The Marine Stratus Forecast System (MSFS) issues forecasts both deterministically and probabilistically. Following transition to NWS operations in 2004, the system continued to provide reliable forecasts but showed no significant improvement in delay reduction. Changes to the FAA GDP issuance procedures in 2008 allowed them to utilize the improved forecasts, leading to quantifiable reductions in ground and airborne holds for SFO equating to dollars saved. To further reduce delays, a refined statistically based model, the Ground Delay Parameters Selection Model (GPSM) for selecting an optimal ground delay strategy has been developed, utilizing the available archive of objective MSFS probabilistic forecasts and accompanying traffic flow data. This effort represents one of the first systematic attempts to integrate objective probabilistic weather information into the air traffic flow decision process, which is a cornerstone element of the FAA's visionary NextGen program.

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Robert M. Rauber, Robert D. Elliott, J. Owen Rhea, Arlen W. Huggins, and David W. Reynolds

Abstract

A diagnostic technique for targeting during airborne seeding experiments has been developed for the Sierra Cooperative Pilot Project (SCPP). This technique was used operationally during SCPP for real-time guidance to aircraft, providing 1) the location and orientation of the seeding line required to target ice particles created by seeding to a specified ground location and 2) an estimate of the areal coverage of the seeding effect on the ground. Procedures to use this technique as a real-time guidance tool during seeding operations in Sierra wintertime storms are discussed.

Three evaluation studies of the targeting method are presented. These include 1) comparisons of diagnosed wind fields with those measured by aircraft; 2) comparisons of ice particle growth rates and habits within seeded cloud regions with those used in the targeting computations; and 3) comparison of radar echo evolution within seeded cloud regions with calculated particle trajectories.

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David W. Reynolds, Marvin L. Brown, Eric A. Smith, and Thomas H. Vonder Haar

Abstract

A technique is presented for discriminating different cloud types through an image subtraction of visible and infrared SMS/GOES picture pairs. The technique emphasizes how one could separate snow from clouds and identify cirrus by the subtraction method. Quantitative threshold values are shown which can be used in an objective manner to make this separation.

Use is made of an all-digital image display device allowing such mathematical operations to be performed on satellite data. Techniques such as this can be made operational through the interfacing of the image analysis system with a direct-readout SMS/GOES ground station and distribution network.

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F. Martin Ralph, Paul J. Neiman, George N. Kiladis, Klaus Weickmann, and David W. Reynolds

Abstract

A case study is presented of an atmospheric river (AR) that produced heavy precipitation in the U.S. Pacific Northwest during March 2005. The study documents several key ingredients from the planetary scale to the mesoscale that contributed to the extreme nature of this event. The multiscale analysis uses unique experimental data collected by the National Oceanic and Atmospheric Administration (NOAA) P-3 aircraft operated from Hawaii, coastal wind profiler and global positioning system (GPS) meteorological stations in Oregon, and satellite and global reanalysis data. Moving from larger scales to smaller scales, the primary findings of this study are as follow: 1) phasing of several major planetary-scale phenomena influenced by tropical––extratropical interactions led to the direct entrainment of tropical water vapor into the AR near Hawaii, 2) dropsonde observations documented the northward advection of tropical water vapor into the subtropical extension of the midlatitude AR, and 3) a mesoscale frontal wave increased the duration of AR conditions at landfall in the Pacific Northwest.

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Jerome P. Charba, David W. Reynolds, Brett E. McDonald, and Gary M. Carter

Abstract

Comparative verification of operational 6-h quantitative precipitation forecast (QPF) products used for streamflow models run at National Weather Service (NWS) River Forecast Centers (RFCs) is presented. The QPF products include 1) national guidance produced by operational numerical weather prediction (NWP) models run at the National Centers for Environmental Prediction (NCEP), 2) guidance produced by forecasters at the Hydrometeorological Prediction Center (HPC) of NCEP for the conterminous United States, 3) local forecasts produced by forecasters at NWS Weather Forecast Offices (WFOs), and 4) the final QPF product for multi-WFO areas prepared by forecasters at RFCs. A major component of the study was development of a simple scoring methodology to indicate the relative accuracy of the various QPF products for NWS managers and possibly hydrologic users. The method is based on mean absolute error (MAE) and bias scores for continuous precipitation amounts grouped into mutually exclusive intervals. The grouping (stratification) was conducted on the basis of observed precipitation, which is customary, and also forecast precipitation. For ranking overall accuracy of each QPF product, the MAE for the two stratifications was objectively combined. The combined MAE could be particularly useful when the accuracy rankings for the individual stratifications are not consistent. MAE and bias scores from the comparative verification of 6-h QPF products during the 1998/99 cool season in the eastern United States for day 1 (0–24-h period) indicated that the HPC guidance performed slightly better than corresponding products issued by WFOs and RFCs. Nevertheless, the HPC product was only marginally better than the best-performing NCEP NWP model for QPF in the eastern United States, the Aviation (AVN) Model. In the western United States during the 1999/2000 cool season, the WFOs improved on the HPC guidance for day 1 but not for day 2 or day 3 (24–48- and 48–72-h periods, respectively). Also, both of these human QPF products improved on the AVN Model on day 1, but by day 3 neither did. These findings contributed to changes in the NWS QPF process for hydrologic model input.

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Russell S. Vose, Derek Arndt, Viva F. Banzon, David R. Easterling, Byron Gleason, Boyin Huang, Ed Kearns, Jay H. Lawrimore, Matthew J. Menne, Thomas C. Peterson, Richard W. Reynolds, Thomas M. Smith, Claude N. Williams Jr., and David B. Wuertz

This paper describes the new release of the Merged Land–Ocean Surface Temperature analysis (MLOST version 3.5), which is used in operational monitoring and climate assessment activities by the NOAA National Climatic Data Center. The primary motivation for the latest version is the inclusion of a new land dataset that has several major improvements, including a more elaborate approach for addressing changes in station location, instrumentation, and siting conditions. The new version is broadly consistent with previous global analyses, exhibiting a trend of 0.076°C decade−1 since 1901, 0.162°C decade−1 since 1979, and widespread warming in both time periods. In general, the new release exhibits only modest differences with its predecessor, the most obvious being very slightly more warming at the global scale (0.004°C decade−1 since 1901) and slightly different trend patterns over the terrestrial surface.

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Allen B. White, Brad Colman, Gary M. Carter, F. Martin Ralph, Robert S. Webb, David G. Brandon, Clark W. King, Paul J. Neiman, Daniel J. Gottas, Isidora Jankov, Keith F. Brill, Yuejian Zhu, Kirby Cook, Henry E. Buehner, Harold Opitz, David W. Reynolds, and Lawrence J. Schick

The Howard A. Hanson Dam (HHD) has brought flood protection to Washington's Green River Valley for more than 40 years and opened the way for increased valley development near Seattle. However, following a record high level of water behind the dam in January 2009 and the discovery of elevated seepage through the dam's abutment, the U.S. Army Corps of Engineers declared the dam “unsafe.” NOAA's Office of Oceanic and Atmospheric Research (OAR) and National Weather Service (NWS) worked together to respond rapidly to this crisis for the 2009/10 winter season, drawing from innovations developed in NWS offices and in NOAA's Hydrometeorology Test-bed (HMT).

New data telemetry was added to 14 existing surface rain gauges, allowing the gauge data to be ingested into the NWS rainfall database. The NWS Seattle Weather Forecast Office produced customized daily forecasts, including longer-lead-time hydrologic outlooks and new decision support services tailored for emergency managers and the public, new capabilities enabled by specialized products from NOAA's National Centers for Environmental Prediction (NCEP) and from HMT. The NOAA Physical Sciences Division (PSD) deployed a group of specialized instruments on the Washington coast and near the HHD that constituted two atmospheric river (AR) observatories (AROs) and conducted special HMT numerical model forecast runs. Atmospheric rivers are narrow corridors of enhanced water vapor transport in extratropical oceanic storms that can produce heavy orographic precipitation and anomalously high snow levels, and thus can trigger flooding. The AROs gave forecasters detailed vertical profile observations of AR conditions aloft, including monitoring of real-time water vapor transport and comparison with model runs.

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Stephen D. Eckermann, Jun Ma, Karl W. Hoppel, David D. Kuhl, Douglas R. Allen, James A. Doyle, Kevin C. Viner, Benjamin C. Ruston, Nancy L. Baker, Steven D. Swadley, Timothy R. Whitcomb, Carolyn A. Reynolds, Liang Xu, N. Kaifler, B. Kaifler, Iain M. Reid, Damian J. Murphy, and Peter T. Love

Abstract

A data assimilation system (DAS) is described for global atmospheric reanalysis from 0- to 100-km altitude. We apply it to the 2014 austral winter of the Deep Propagating Gravity Wave Experiment (DEEPWAVE), an international field campaign focused on gravity wave dynamics from 0 to 100 km, where an absence of reanalysis above 60 km inhibits research. Four experiments were performed from April to September 2014 and assessed for reanalysis skill above 50 km. A four-dimensional variational (4DVAR) run specified initial background error covariances statically. A hybrid-4DVAR (HYBRID) run formed background error covariances from an 80-member forecast ensemble blended with a static estimate. Each configuration was run at low and high horizontal resolution. In addition to operational observations below 50 km, each experiment assimilated 105 observations of the mesosphere and lower thermosphere (MLT) every 6 h. While all MLT reanalyses show skill relative to independent wind and temperature measurements, HYBRID outperforms 4DVAR. MLT fields at 1-h resolution (6-h analysis and 1–5-h forecasts) outperform 6-h analysis alone due to a migrating semidiurnal (SW2) tide that dominates MLT dynamics and is temporally aliased in 6-h time series. MLT reanalyses reproduce observed SW2 winds and temperatures, including phase structures and 10–15-day amplitude vacillations. The 0–100-km reanalyses reveal quasi-stationary planetary waves splitting the stratopause jet in July over New Zealand, decaying from 50 to 80 km then reintensifying above 80 km, most likely via MLT forcing due to zonal asymmetries in stratospheric gravity wave filtering.

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