On the evening of 28 July 1997 the city of Fort Collins, Colorado, experienced a devastating flash flood that caused five fatalities and over 200 million dollars in damage. Maximum accumulations of rainfall in the western part of the city exceeded 10 in. in a 6-h period. This study presents a multiscale meteorological overview of the event utilizing a wide variety of instrument platforms and data including rain gauge, CSU-CHILL multiparameter radar, Next Generation Radar, National Lightning Detection Network, surface and Aircraft Communication Addressing and Reporting System observations, satellite observations, and synoptic analyses. Many of the meteorological features associated with the Fort Collins flash flood typify those of similar events in the western United States. Prominent features in the Fort Collins case included the presence of a 500-hPa ridge axis over northeastern Colorado; a weak shortwave trough on the western side of the ridge; postfrontal easterly upslope flow at low levels; weak to moderate southwesterly flow aloft; a deep, moist warm layer in the sounding; and the occurrence of a quasi-stationary rainfall system. In contrast to previous events such as the Rapid City or Big Thompson floods, the thermodynamic environment of the Fort Collins storm exhibited only modest instability, consistent with low lightning flash rates and an absence of hail and other severe storm signatures. Radar, rain gauge, and lightning observations provided a detailed view of the cloud and precipitation morphology. Polarimetric radar observations suggest that a coupling between warm-rain collision coalescence processes and ice processes played an important role in the rainfall production. Dual-Doppler radar and mesoscale wind analyses revealed that the low-level flow field associated with a bow echo located 60 km to the southeast of Fort Collins may have been responsible for a brief easterly acceleration in the low-level winds during the last 1.5 h of the event. The enhanced flow interacted with both topography and the convection located over Fort Collins, resulting in a quasi-stationary convective system and the heaviest rainfall of the evening.

Emerging application areas such as air pollution in megacities, wind energy, urban security, and operation of unmanned aerial vehicles have intensified scientific and societal interest in mountain meteorology. To address scientific needs and help improve the prediction of mountain weather, the U.S. Department of Defense has funded a research effort—the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program—that draws the expertise of a multidisciplinary, multi-institutional, and multinational group of researchers. The program has four principal thrusts, encompassing modeling, experimental, technology, and parameterization components, directed at diagnosing model deficiencies and critical knowledge gaps, conducting experimental studies, and developing tools for model improvements. The access to the Granite Mountain Atmospheric Sciences Testbed of the U.S. Army Dugway Proving Ground, as well as to a suite of conventional and novel high-end airborne and surface measurement platforms, has provided an unprecedented opportunity to investigate phenomena of time scales from a few seconds to a few days, covering spatial extents of tens of kilometers down to millimeters. This article provides an overview of the MATERHORN and a glimpse at its initial findings. Orographic forcing creates a multitude of time-dependent submesoscale phenomena that contribute to the variability of mountain weather at mesoscale. The nexus of predictions by mesoscale model ensembles and observations are described, identifying opportunities for further improvements in mountain weather forecasting.

The field campaign, involving multiple aircraft and ground-based instruments, documented numerous long-lived mesoscale convective systems, many producing strong surface winds and exhibiting mesoscale rotation.

The authors evaluate whether the structure and intensity of simulated squall lines can be explained by "RKW theory," which most specifically addresses how density currents evolve in sheared environments. In contrast to earlier studies, this study compares output from four numerical models, rather than from just one. All of the authors' simulations support the qualitative application of RKW theory, whereby squall-line structure is primarily governed by two effects: the intensity of the squall line's surface-based cold pool, and the low-to midlevel environmental vertical wind shear. The simulations using newly developed models generally support the theory's quantitative application, whereby an optimal state for system structure also optimizes system intensity. However, there are significant systematic differences between the newer numerical models and the older model that was originally used to develop RKW theory. Two systematic differences are analyzed in detail, and causes for these differences are proposed.

Diffusion that is implicit in the odd-ordered advection schemes in early versions of the Advanced Research core of the Weather Research and Forecasting (WRF) model is sometimes insufficient to remove noise from kinematical fields. The problem is worst when grid-relative wind speeds are low and when stratification is nearly neutral or unstable, such as in weakly forced daytime boundary layers, where noise can grow until it competes with the physical phenomena being simulated. One solution to this problem is an explicit, sixth-order numerical diffusion scheme that preserves the WRF model’s high effective resolution and uses a flux limiter to ensure monotonicity. The scheme, and how it was added to the WRF model, are explained. The scheme is then demonstrated in an idealized framework and in simulations of salt breezes and lake breezes in northwestern Utah.

Over the past decade, numerous numerical modeling studies have shown that deep convective clouds can produce gravity waves that induce a significant vertical flux of horizontal momentum. Such studies used models with horizontal grid spacings of O(1 km) and produced strong gravity waves with horizontal wavelengths greater than about 20 km. This paper is an examination of how simulated gravity waves and their momentum flux are sensitive to model resolution. It is shown that increases in horizontal resolution produce more power in waves with shorter horizontal wavelengths. This change in the gravity waves’ spectra influences their vertical propagation. In some cases, gravity waves that were vertically propagating in coarse simulations become vertically trapped in fine simulations, which strongly influences the vertical flux of horizontal momentum.

Record‐breaking rainfall of 524.1 mm in 24 hr occurred in the coastal metropolitan city of Guangzhou, China, during 6–7 May 2017 and caused devastating flooding. Observation analysis and a nested very large eddy simulation (VLES) with Weather Research and Forecasting (WRF) model were conducted to investigate various factors that contributed to the heavy rainfall, including synoptic weather pattern, topographic effects, cold pool, and urban effects. First, the warm and moist southerly flow in the lower troposphere over the trumpet‐shaped topography of the Pearl River Delta continuously provided fuel for the development of the severe rainfall. Consequently, the southerly flow from the sea in the south strengthened with the development of the convection. Meanwhile, the precipitation‐produced weak cold pool supported a stationary outflow boundary, where new convective cells were continuously initiated and drifted downstream. The interaction between the cold outflows and the warm moist southerly flows in the lower troposphere formed a back‐building convective system, which produced local persistent heavy rainfall that lasted for more than 5 hr and reached record levels. Sensitivity experiments in which the urban area was removed from the model indicate that the urban forcing affected the timing and location of convective initiation and helped concentrate the maximum rain core. The nested WRF‐LES successfully simulated this heavy rainfall, and the model's advantages are noted for forecasting such local severe weather.

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