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David M. Schultz, Robert M. Rauber, and Kenneth F. Heideman
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David M. Schultz, Robert M. Rauber, and Kenneth F. Heideman
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Clifford F. Mass, W. James Steenburgh, and David M. Schultz

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This paper presents the results of a detailed study of the diurnal and semidiurnal pressure variations at the surface across the continental United States. Using a larger dataset than preceding studies and a variety of analysis approaches, the spatial and temporal variations in the diurnal and semidiurnal components of station and sea level pressure are described, and the influence of current pressure reduction techniques on the characteristics of sea level pressure is evaluated. It is shown that the temperature-averaging scheme currently used in sea level pressure reduction creates a bogus semidiurnal signal in sea level pressure over high terrain. This paper also describes the summertime mesoscale evolution of station pressure over the northeast United States and presents 3-h pressure-change maps for the continental United States during the summer and winter seasons.

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Addison L. Sears-Collins, David M. Schultz, and Robert H. Johns
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Jay W. Hanna, David M. Schultz, and Antonio R. Irving

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To explore the role of cloud microphysics in a large dataset of precipitating clouds, a 6-month dataset of satellite-derived cloud-top brightness temperatures from the longwave infrared band (channel 4) on the Geostationary Operational Environmental Satellite (GOES) is constructed over precipitation-reporting surface observation stations, producing 144 738 observations of snow, rain, freezing rain, and sleet. The distributions of cloud-top brightness temperatures were constructed for each precipitation type, as well as light, moderate, and heavy snow and rain. The light-snow distribution has a maximum at −16°C, whereas the moderate- and heavy-snow distributions have a bimodal distribution with a primary maximum around −16° to −23°C and a secondary maximum at −35° to −45°C. The light, moderate, and heavy rain, as well as the freezing rain and sleet, distributions are also bimodal with roughly the same temperature maxima, although the colder mode dominates when compared with the snow distributions. The colder of the bimodal peaks trends to lower temperatures with increasing rainfall intensity: −45°C for light rain, −47°C for moderate rain, and −50°C for heavy rain. Like the distributions for snow, the colder peak increases in amplitude relative to the warmer peak at heavier rainfall intensities. The steep slope in the snow distribution for cloud-tops warmer than −15°C is likely due to the combined effects of above-freezing cloud-top temperatures not producing snow, the activation of ice nuclei, the maximum growth rate for ice crystals at temperatures near −15°C, and ice multiplication processes from −3° to −8°C. In contrast, the rain distributions have a gentle slope toward higher cloud-top brightness temperatures (−5° to 0°C), likely due to the warm-rain process. Last, satellite-derived cloud-top brightness temperatures are compared with coincident radiosonde-derived cloud-top temperatures. Although most differences between these two are small, some are as large as ±60°C. The cause of these differences remains unclear, and several hypotheses are offered.

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Jari-Petteri Tuovinen, Harri Hohti, and David M. Schultz

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Collecting hail reports to build a climatology is challenging in a sparsely populated country such as Finland. To expand an existing database, a new approach involving daily verification of a radar- and numerical weather prediction–based hail detection algorithm was trialed during late May–August for the 10-yr period, 2008–17. If the algorithm suggested a high likelihood of hail from each identified convective cell in specified locations, then an email survey was sent to people and businesses in these locations. Telephone calls were also used occasionally. Starting from 2010, the experiment was expanded to include trained storm spotters performing the surveys (project called TATSI). All the received hail reports were documented (severe or ≥2 cm, and nonsevere, excluding graupel), giving a more complete depiction of hail occurrence in Finland. In combination with reports from the general public, news, and social media, our hail survey resulted in a 292% increase in recorded severe hail days and a 414% increase in observed severe hail cases compared to a climatological study (1930–2006). More than 2200 email surveys were sent, and responses to these surveys accounted for 53% of Finland’s severe hail cases during 2008–17. Most of the 2200 emails were sent into rural locations with low population density. These additional hail reports allowed problems with the initial radar-based hail detection algorithm to be identified, leading to the introduction of a new hail index in 2009 with improved detection and nowcasting of severe hail. This study shows a way to collect hail reports in a sparsely populated country to mitigate underreporting and population biases.

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Paul J. Roebber, David M. Schultz, and Romualdo Romero

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Despite the relatively successful long-lead-time forecasts of the storms during the 3 May 1999 tornadic outbreak in Oklahoma and Kansas, forecasters were unable to predict with confidence details concerning convective initiation and convective mode. The forecasters identified three synoptic processes they were monitoring for clues as to how the event would unfold. These elements were (a) the absence of strong surface convergence along a dryline in western Oklahoma and the Texas Panhandle, (b) the presence of a cirrus shield that was hypothesized to limit surface heating, and (c) the arrival into Oklahoma of an upper-level wind speed maximum [associated with the so-called southern potential vorticity (PV) anomaly] that was responsible for favorable synoptic-scale ascent and the cirrus shield. The Pennsylvania State University–National Center for Atmospheric Research Fifth-Generation Mesoscale Model (MM5), nested down to 2-km horizontal grid spacing, is used in forecast mode [using the data from the National Centers for Environmental Prediction Aviation (AVN) run of the Global Spectral Model to provide initial and lateral boundary conditions] to explore the sensitivity of the outbreak to these features. A 30-h control simulation is compared with the available observations and captures important qualitative characteristics of the event, including convective initiation east of the dryline and organization of mesoscale convective systems into long-lived, long-track supercells. Additional simulations in which the initial strength of the southern PV anomaly is altered suggest that synoptic regulation of the 3 May 1999 event was imposed by the effects of the southern PV anomaly. The model results indicate that 1) convective initiation in the weakly forced environment was achieved through modification of the existing cap through both surface heating and synoptic-scale ascent associated with the southern PV anomaly; 2) supercellular organization was supported regardless of the strength of the southern PV anomaly, although weak-to-moderate forcing from this feature was most conducive to the production of long-lived supercells and strong forcing resulted in a trend toward linear mesoscale convective systems; and 3) the cirrus shield was important in limiting development of convection and reducing competition between storms. The implications of these results for the use of high-resolution models in operational forecasting environments are discussed. The model information provides potentially useful information to forecasters following the scientific forecast process, most particularly by assisting in the revision of conceptual ideas about the evolution of the outbreak. Substantial obstacles to operational implementation of such tools remain, however, including lack of model context (e.g., information concerning model biases), insufficient real-time observations to assess effectively model prediction details from the synoptic to the mesoscale, inconsistent forecaster education, and inadequate technology to support rapid scientific discovery in an operational setting.

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Kimberly L. Elmore, David M. Schultz, and Michael E. Baldwin

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A previous study of the mean spatial bias errors associated with operational forecast models motivated an examination of the mechanisms responsible for these biases. One hypothesis for the cause of these errors is that mobile synoptic-scale phenomena are partially responsible. This paper explores this hypothesis using 24-h forecasts from the operational Eta Model and an experimental version of the Eta run with Kain–Fritsch convection (EtaKF).

For a sample of 44 well-defined upper-level short-wave troughs arriving on the west coast of the United States, 70% were underforecast (as measured by the 500-hPa geopotential height), a likely result of being undersampled by the observational network. For a different sample of 45 troughs that could be tracked easily across the country, consecutive model runs showed that the height errors associated with 44% of the troughs generally decreased in time, 11% increased in time, 18% had relatively steady errors, 2% were uninitialized entering the West Coast, and 24% exhibited some other kind of behavior. Thus, landfalling short-wave troughs were typically underforecast (positive errors, heights too high), but these errors tended to decrease as they moved across the United States, likely a result of being better initialized as the troughs became influenced by more upper-air data. Nevertheless, some errors in short-wave troughs were not corrected as they fell under the influence of supposedly increased data amount and quality. These results indirectly show the effect that the amount and quality of observational data has on the synoptic-scale errors in the models. On the other hand, long-wave ridges tended to be underforecast (negative errors, heights too low) over a much larger horizontal extent.

These results are confirmed in a more systematic manner over the entire dataset by segregating the model output at each grid point by the sign of the 500-hPa relative vorticity. Although errors at grid points with positive relative vorticity are small but positive in the western United States, the errors become large and negative farther east. Errors at grid points with negative relative vorticity, on the other hand, are generally negative across the United States. A large negative bias observed in the Eta and EtaKF over the southeast United States is believed to be due to an error in the longwave radiation scheme interacting with water vapor and clouds. This study shows that model errors may be related to the synoptic-scale flow, and even large-scale features such as long-wave troughs can be associated with significant large-scale height errors.

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Jesse Norris, Geraint Vaughan, and David M. Schultz

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Precipitation patterns along cold fronts can exhibit a variety of morphologies including narrow cold-frontal rainbands and core-and-gap structures. A three-dimensional primitive equation model is used to investigate alongfront variability of precipitation in an idealized baroclinic wave. Along the poleward part of the cold front, a narrow line of precipitation develops. Along the equatorward part of the cold front, precipitation cores and gaps form. The difference between the two evolutions is due to differences in the orientation of vertical shear near the front in the lower troposphere: at the poleward end the along-frontal shear is dominant and the front is in near-thermal wind balance, while at the equatorward end the cross-frontal shear is almost as large. At the poleward end, the thermal structure remains erect with the front well defined up to the midtroposphere, hence updrafts remain erect and precipitation falls in a continuous line along the front. At the equatorward end, the cores form as undulations appear in both the prefrontal and postfrontal lighter precipitation, associated with vorticity maxima moving along the front on either side. Cross-frontal winds aloft tilt updrafts, so that some precipitation falls ahead of the surface cold front, forming the cores. Sensitivity simulations are also presented in which SST and roughness length are varied between simulations. Larger SST reduces cross-frontal winds aloft and leads to a more continuous rainband. Larger roughness length destroys the surface wind shift and thermal gradient, allowing mesovortices to dominate the precipitation distribution, leading to distinctive and irregularly shaped, quasi-regularly spaced precipitation maxima.

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Callum F. Thompson, David M. Schultz, and Geraint Vaughan

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A climatology of tropospheric inertial instability is constructed using the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) at 250, 500, and 850 hPa. For each level, two criteria are used. The first criterion is the traditional criterion of absolute vorticity that is opposite in sign to the local Coriolis parameter. The second criterion, referred to as the gradient criterion, is the traditional criterion with an added term incorporating flow curvature. Both criteria show that instability, on all pressure levels, occurs most frequently in the tropics and decreases toward the poles. Compared to the traditional criterion, the gradient criterion diagnoses instability much more frequently outside the tropics and less frequently near the equator. The global distribution of inertial instability also shows many local maxima in the occurrence of instability. A sample of these local maxima is investigated further by constructing composites of the synoptic-scale flow associated with instability. The composites show that instability occurs in association with cross-equatorial flow in the North Atlantic Ocean, the Somali jet, tip jets off northern Madagascar, the western Pacific subtropical high, gap winds across Central America, upper-level ridging over western North America, and the North Atlantic polar jet. Furthermore, relatively long-lived synoptic-scale regions of instability are found within the midlatitude jet streams.

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