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At least 397 records · Page 22

A high-resolution unified observational data product of mesoscale convective systems and isolated deep convection in the United States for 2004–2017

Deep convection possesses markedly distinct properties at different spatiotemporal scales. We present an original high-resolution (4 km, hourly) unified data product of mesoscale convective systems (MCSs) and isolated deep convection (IDC) in the United States east of the Rocky Mountains and examine their climatological characteristics from 2004 to 2017. The data product is produced by applying an updated Flexible Object Tracker algorithm to hourly satellite brightness temperature, radar reflectivity, and precipitation datasets. Analysis of the data product shows that MCSs are much larger and longer-lasting than IDC, but IDC occurs about 100 times more frequently than MCSs, with a mean convective intensity comparable to that of MCSs. Hence both MCS and IDC are essential contributors to precipitation east of the Rocky Mountains, although their precipitation shows significantly different spatiotemporal characteristics. IDC precipitation concentrates in summer in the Southeast with a peak in the late afternoon, while MCS precipitation is significant in all seasons, especially for spring and summer in the Great Plains. The spatial distribution of MCS precipitation amounts varies by season, while diurnally, MCS precipitation generally peaks during nighttime except in the Southeast. Potential uncertainties and limitations of the data product are also discussed. The data product is useful for investigating the atmospheric environments and physical processes associated with different types of convective systems; quantifying the impacts of convection on hydrology, atmospheric chemistry, and severe weather events; and evaluating and improving the representation of convective processes in weather and climate models.

54 ENVIRONMENTAL SCIENCES↗

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗

Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States

Hail and tornadoes are hazardous weather events responsible for significant property damage and economic loss worldwide. The most devastating occurrences of hail and tornadoes are commonly produced by supercells in the United States. However, these supercells may also grow upscale into mesoscale convective systems (MCSs) or be embedded within them. The relationship between hail and tornado occurrences with MCSs in the long-term climatology has not been thoroughly examined. In this study, radar features associated with MCSs are extracted from a 14-year MCS tracking database across the contiguous United States, and hazard reports are mapped to these MCS features. We investigate the characteristics of hail and tornadoes in relation to MCSs, considering seasonal and regional variabilities. On average, 8 %–17 % of hail events and 17 %–32 % of tornado events are associated with MCSs, depending on the criteria used to define MCSs. The highest total and MCS-associated hazard events occur from March to May, while the highest MCS-associated portion (23 % for hail and 45 % for tornadoes) is observed in winter (December–February) due to the dominance of MCSs caused by strong synoptic forcing. As hailstone size increases, the fraction associated with MCS decreases, but there is an increasing trend for tornado severity from EF0 to EF3 (Enhanced Fujita Scale). Violent tornadoes at EF4 and EF5 associated with MCSs were also observed, which are generated by supercells embedded within MCSs.

54 ENVIRONMENTAL SCIENCES↗

Mesoscale history of a small patch of clear air turbulence.

Sequential analyses of data from a network of eight special rawinsonde stations 100 km apart demonstrate the important effects of mesoscale disturbances in a 2.5-hr episode of light-to-moderate clear air turbulence (CAT). The most significant feature was the development of two turbulent fields below and above a 2-km region of a wind minimum which passed over Wallops Island, Va., near 1530 GMT on Feb. 4, 1970. The small scale of these features precludes their detection in the standard 12-hr observation sequence. The rawinsonde network utilized, which incorporates fine-scale details in both space and time, is adequate to provide a very useful current CAT depiction and an excellent source for the preparation of a short-range forecast of CAT.

Boucher, R. J.↗

Mesoscale wake clouds in Skylab pictures.

The recognition of cloud patterns formed in the wake of orographic obstacles was investigated using pictures from Skylab, for the purpose of estimating atmospheric motions. The existence of ship-wake-type wave clouds in contrast to vortex sheets were revealed during examination of the pictures, and an attempt was made to characterize the pattern of waves as well as the transition between waves and vortices. Examples of mesoscale cloud patterns which were analyzed photogrammetrically and meteorologically are presented.

Fujita, T. T.↗

A study of mesoscale surface heat and moisture budgets and their relationship to airmass cumulus clouds observed in LANDSAT imagery

The author has identified the following significant results. The three budget analyses show a weak correspondence between LANDSAT cloud patterns and elements of the energy and moisture budgets. It was found that a little more energy is contributed by the ground to heat the air in cloudy areas. Improvements are warranted in the budget models and data coverage necessary to describe the environment. These models can serve as a basis for more complex models of surface air heat and moisture exchanges which would utilize readily available meteorological data on a mesoscale.

Merritt, E. S.↗

A mesoscale numerical model and the development of a severe storm prediction system

The use of a mesoscale numerical model for predicting preferred zones of severe storm development is analyzed. A 60 consecutive day real-time test of the prediction system during the spring of 1978 proved useful in determining the problems and potentialities of such a system. A case study of severe storm development from this test period is described and compared to the model forecast fields.

Kaplan, M. L.↗

Numerical prediction experiments simulating the impact of mesoscale satellite data

Recent developments in mesometeorology are summarized to place this research in perspective. Recent advances in computer analysis and forecast system development that provide the basis for the simulation tests are discussed. The impact of NIMBUS-6 humidity data on analyses off the West Coast are shown and incorporation of geopotential gradient data is discussed. Experiments to demonstrate the feasibility of incorporating satellite-derived wind fields in mesoscale severe storm models are mentioned briefly.

Kreitzberg, C. W.↗

Acid rain: Mesoscale model

A mesoscale numerical model of the Florida peninsula was formulated and applied to a dry, neutral atmosphere. The prospective use of the STAR-100 computer for the submesoscale model is discussed. The numerical model presented is tested under synoptically undisturbed conditions. Two cases, differing only in the direction of the prevailing geostrophic wind, are examined: a prevailing southwest wind and a prevailing southeast wind, both 6 m/sec at all levels initially.

Hsu, H. M.↗

Observing, analyzing, and modeling mesoscale weather phenomena

The objective of the paper is to place current research into mesoscale weather phenomena in proper perspective, and to discuss key problems to be addressed in the coming years. Key observing systems and field programs are examined, along with analysis techniques in context of the dynamic models with which they interact. The discussion covers different classes of dynamic models, including prediction models, simulation models, and parameterization schemes.

Kreitzberg, C. W.↗

The characteristics of evolving mesoscale systems over mountainous terrain as revealed by radar and PAM

The paper deals with measurements made within the South Park area (which is located near Denver, Colorado, and is a natural genesis area for cumulus clouds) in July and August 1977, using powered aircraft, sailplanes, rawinsondes, boundary layer profilers, acoustic sounders, micrometeorological towers, lidar, research radar, triple-Doppler radar, and a square grid of surface meteorological stations. Extensive analysis revealed a very complex picture of thunderstorm-scale, large-mesoscale, and synoptic-scale interactions.

George, R. L.↗

The use of satellite estimates of rainfall in the initialization of a mesoscale hurricane model

The use of rainfall rate data obtained from satellites to improve the initial specification of the hurricane circulation is discussed with particular reference to the techniques for incorporating rainfall data into high-resolution hurricane models. The variation of latent heating in a numerical model of a steady state tropical cyclone is considered to ascertain what features of the storm motion can be deduced from a given field of latent heat release. A real-data example involving a mesoscale model for hurricane Eloise (1975) has demonstrated that satellite measurements of rainfall may be beneficial to numerical hurricane prediction.

Fiorino, M.↗