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Huijie Xue, John M. Bane Jr., and Lauren M. Goodman

Abstract

The greatest fluxes of heat and moisture from the ocean to the atmosphere occur off the east coast of North America during winter when the Gulf Stream is vigorously cooled by strong cold air outbreaks that move off the continent. In this paper observational and numerical modeling methods are employed to investigate the response of the Gulf Stream to such strong cooling events. Both methods show that the surface mixed layer can deepen several tens of meters during a single strong outbreak and that the heat decrease within the upper layer of the Gulf Stream, 2.9 × 1013 J in the model and 3.2(±0.7) × 1013 J in observations (per meter alongstream) for one case study, is balanced closely by the amount of oceanic heat released to the atmosphere. Computations also show that the cross-stream circulation is dominated by Ekman-like, wind-driven motion with velocities on the order of 20 cm s−1. A vertical circulation cell within the Gulf Stream, with vertical velocities on the order of 0.1 cm s−1, is found to be a result of convergence/divergence of the Ekman transport due to the altered inertial frequency caused by the horizontal velocity shear of the Gulf Stream jet.

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Christopher S. Velden, Brian M. Goodman, and Robert T. Merrill

Abstract

A method is examined for estimating the intensity of western North Pacific tropical cyclones from satellite passive microwave observations. Vertical profiles of atmospheric temperature derived from radiances remotely sensed by the Microwave Sounding Unit (MSU) onboard the current NOAA series of polar orbiting satellites are used to depict upper-tiopospheric warm anomalies associated with these storms. Data from a large sample of western North Pacific tropical cyclones are used to develop a nonlinear statistical relationship between the satellite-depicted warm core anomalies and the surface intensifies as measured by reconnaissance aircraft. Results based on an 82-case dependent sample indicate standard errors of 13 mb and 15 kt for estimates of the surface pressure anomalies and maximum wind speeds. These errors are reduced considerably when a bias in the sample intensity distribution is taken into account. Comparisons of results and method accuracy are made with a previous study of North Atlantic tropical cyclones.

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E. Kunze, J. M. Klymak, R.-C. Lien, R. Ferrari, C. M. Lee, M. A. Sundermeyer, and L. Goodman

Abstract

Submesoscale stirring contributes to the cascade of tracer variance from large to small scales. Multiple nested surveys in the summer Sargasso Sea with tow-yo and autonomous platforms captured submesoscale water-mass variability in the seasonal pycnocline at 20–60-m depths. To filter out internal waves that dominate dynamic signals on these scales, spectra for salinity anomalies on isopycnals were formed. Salinity-gradient spectra are approximately flat with slopes of −0.2 ± 0.2 over horizontal wavelengths of 0.03–10 km. While the two to three realizations presented here might be biased, more representative measurements in the literature are consistent with a nearly flat submesoscale passive tracer gradient spectrum for horizontal wavelengths in excess of 1 km. A review of mechanisms that could be responsible for a flat passive tracer gradient spectrum rules out (i) quasigeostrophic eddy stirring, (ii) atmospheric forcing through a relict submesoscale winter mixed layer structure or nocturnal mixed layer deepening, (iii) a downscale vortical-mode cascade, and (iv) horizontal diffusion because of shear dispersion of diapycnal mixing. Internal-wave horizontal strain appears to be able to explain horizontal wavenumbers of 0.1–7 cycles per kilometer (cpkm) but not the highest resolved wavenumbers (7–30 cpkm). Submesoscale subduction cannot be ruled out at these depths, though previous observations observe a flat spectrum well below subduction depths, so this seems unlikely. Primitive equation numerical modeling suggests that nonquasigeostrophic subinertial horizontal stirring can produce a flat spectrum. The last need not be limited to mode-one interior or surface Rossby wavenumbers of quasigeostrophic theory but may have a broaderband spectrum extending to smaller horizontal scales associated with frontogenesis and frontal instabilities as well as internal waves.

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Eugene W. McCaul Jr., Steven J. Goodman, Katherine M. LaCasse, and Daniel J. Cecil

Abstract

Two new approaches are proposed and developed for making time- and space-dependent, quantitative short-term forecasts of lightning threats, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the Weather Research and Forecasting (WRF) model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models.

One method is based on upward fluxes of precipitating ice hydrometeors in the mixed-phase region at the −15°C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash-rate proxy fields against domain-wide peak total lightning flash-rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. The blended solution proposed in this work is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second.

Simulations of selected diverse North Alabama cases show that the WRF can distinguish the general character of most convective events, and that the methods employed herein show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically based model versions, physical parameterizations, initialization techniques, and ensembles of forecasts become available.

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R. L. Beadling, J. L. Russell, R. J. Stouffer, P. J. Goodman, and M. Mazloff

Abstract

The Southern Ocean (SO) is vital to Earth’s climate system due to its dominant role in exchanging carbon and heat between the ocean and atmosphere and transforming water masses. Evaluating the ability of fully coupled climate models to accurately simulate SO circulation and properties is crucial for building confidence in model projections and advancing model fidelity. By analyzing multiple biases collectively across large model ensembles, physical mechanisms governing the diverse mean-state SO circulation found across models can be identified. This analysis 1) assesses the ability of a large ensemble of models contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5) to simulate observationally based metrics associated with an accurate representation of the Antarctic Circumpolar Current (ACC), and 2) presents a framework by which the quality of the simulation can be categorized and mechanisms governing the resulting circulation can be deduced. Different combinations of biases in critical metrics including the magnitude and position of the zonally averaged westerly wind stress maximum, wind-driven surface divergence, surface buoyancy fluxes, and properties and transport of North Atlantic Deep Water entering the SO produce distinct mean-state ACC transports. Relative to CMIP3, the quality of the CMIP5 SO simulations has improved. Eight of the thirty-one models simulate an ACC within observational uncertainty (2σ) for approximately the right reasons; that is, the models achieve accuracy in the surface wind stress forcing and the representation of the difference in the meridional density across the current. Improved observations allow for a better assessment of the SO circulation and its properties.

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Timothy J. Schmit, Paul Griffith, Mathew M. Gunshor, Jaime M. Daniels, Steven J. Goodman, and William J. Lebair

Abstract

The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) is America’s next-generation geostationary advanced imager. GOES-R launched on 19 November 2016. The ABI is a state-of-the-art 16-band radiometer, with spectral bands covering the visible, near-infrared, and infrared portions of the electromagnetic spectrum. Many attributes of the ABI—such as spectral, spatial, and temporal resolution; radiometrics; and image navigation/registration—are much improved from the current series of GOES imagers. This paper highlights and discusses the expected improvements of each of these attributes. From ABI data many higher-level-derived products can be generated and used in a large number of environmental applications. The ABI’s design allows rapid-scan and contiguous U.S. imaging automatically interleaved with full-disk scanning. In this paper the expected instrument attributes are covered, as they relate to signal-to-noise ratio, image navigation and registration, the various ABI scan modes, and other parameters. There will be several methods for users to acquire GOES-R imagery and products depending on their needs. These include direct reception of the imagery via the satellite downlink and an online-accessible archive. The information from the ABI on the GOES-R series will be used for many applications related to severe weather, tropical cyclones and hurricanes, aviation, natural hazards, the atmosphere, the ocean, and the cryosphere.

The ABI on the GOES-R series is America’s next-generation geostationary advanced imager and will dramatically improve the monitoring of many phenomena at finer time and space scales.

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Chad M. Gravelle, John R. Mecikalski, William E. Line, Kristopher M. Bedka, Ralph A. Petersen, Justin M. Sieglaff, Geoffrey T. Stano, and Steven J. Goodman

Abstract

With the launch of the Geostationary Operational Environmental Satellite–R (GOES-R) series in 2016, there will be continuity of observations for the current GOES system operating over the Western Hemisphere. The GOES-R Proving Ground was established in 2008 to help prepare satellite user communities for the enhanced capabilities of GOES-R, including new instruments, imagery, and products that will have increased spectral, spatial, and temporal resolution. This is accomplished through demonstration and evaluation of proxy products that use current GOES data, higher-resolution data provided by polar-orbiting satellites, and model-derived synthetic satellite imagery. The GOES-R demonstration products presented here, made available to forecasters in near–real time (within 20 min) via the GOES-R Proving Ground, include the 0–9-h NearCast model, 0–1-h convective initiation probabilities, convective cloud-top cooling, overshooting top detection, and a pseudo–Geostationary Lightning Mapper total lightning tendency diagnostic. These products are designed to assist in identifying areas of increasing convective instability, pre-radar echo cumulus cloud growth preceding thunderstorm formation, storm updraft intensity, and potential storm severity derived from lightning trends. In turn, they provide the warning forecaster with improved situational awareness and short-term predictive information that enhance their ability to monitor atmospheric conditions preceding and associated with the development of deep convection, a time period that typically occurs between the issuance of National Weather Service (NWS) Storm Prediction Center convective watches and convective storm warnings issued by NWS forecast offices. This paper will focus on how this GOES-R satellite convective toolkit could have been used by warning forecasters to enhance near-storm environment analysis and the warning-decision-making process prior to and during the 20 May 2013 Moore, Oklahoma, tornado event.

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Amanda Rehbein, Martín Rugna, M. Paula Hobouchian, Anna del Moral, Steven J. Goodman, Daniel T. Lindsey, and Janel Thomas
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T. Chronis, Lawrence D. Carey, Christopher J. Schultz, Elise V. Schultz, Kristin M. Calhoun, and Steven J. Goodman

Abstract

This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate [i.e., lightning jump (LJ)]. An automated storm tracking method is used to identify storm “clusters” and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama, and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer and relate to higher maximum expected size of hail, vertical integrated liquid, and lightning flash rates (area normalized) than do the clusters without an LJ (LJ0). The respective mean radar-derived and lightning values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg m−2 (18 kg m−2), and 0.05 flash min−1 km−2 (0.01 flash min−1 km−2). Furthermore, the LJ1 clusters are also characterized by slower-decaying autocorrelation functions, a result that implies a less “random” behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm’s dissipation. Depending on the LJ strength (i.e., varying thresholds), these values typically range between 20 and 60 min, with stronger jumps indicating more time until storm decay. This study’s results support the hypothesis that the LJ is a proxy for the storm’s kinematic and microphysical state rather than a coincidental value.

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Robbie E. Hood, Daniel J. Cecil, Frank J. LaFontaine, Richard J. Blakeslee, Douglas M. Mach, Gerald M. Heymsfield, Frank D. Marks Jr., Edward J. Zipser, and Michael Goodman

Abstract

During the 1998 and 2001 hurricane seasons of the western Atlantic Ocean and Gulf of Mexico, the Advanced Microwave Precipitation Radiometer (AMPR), the ER-2 Doppler (EDOP) radar, and the Lightning Instrument Package (LIP) were flown aboard the NASA ER-2 high-altitude aircraft as part of the Third Convection and Moisture Experiment (CAMEX-3) and the Fourth Convection and Moisture Experiment (CAMEX-4). Several hurricanes, tropical storms, and other precipitation systems were sampled during these experiments. An oceanic rainfall screening technique has been developed using AMPR passive microwave observations of these systems collected at frequencies of 10.7, 19.35, 37.1, and 85.5 GHz. This technique combines the information content of the four AMPR frequencies regarding the gross vertical structure of hydrometeors into an intuitive and easily executable precipitation mapping format. The results have been verified using vertical profiles of EDOP reflectivity and lower-altitude horizontal reflectivity scans collected by the NOAA WP-3D Orion radar. Matching the rainfall classification results with coincident electric field information collected by the LIP readily identifies convective rain regions within the precipitation fields. This technique shows promise as a real-time research and analysis tool for monitoring vertical updraft strength and convective intensity from airborne platforms such as remotely operated or uninhabited aerial vehicles. The technique is analyzed and discussed for a wide variety of precipitation types using the 26 August 1998 observations of Hurricane Bonnie near landfall.

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