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At least 37 records · Page 2

Numerical simulation of VTPR temperature retrievals in a severe storm environment

Environmental conditions prior to convective development on the Great Plains of the U.S. on one case study day were investigated using the high-resolution infrared radiation sounder (HIRS) on Nimbus 6. A dual-retrieval scheme was developed to retrieve both lower tropospheric moisture and temperature parameters from the HIRS radiances. Total precipitable water, surface dew point temperatures, and stability indices were analyzed at a resolution of up to 30 Km on this day. Correlations with interpolated NES rawinsonde values were high and intrinsic noise levels were low. The true quality of the mesoscale analyses, however, is only seen by examining the small scale features at a scale of approximately 100 Km. Perturbations on the dry line feature for this day were seen in the satellite data, although the dry line position was just as easily picked up by surface observations. Convective development 2 1/2 hours later did seem to correlate well with the local maxima of moisture and instability seen in the satellite analyses.

Vonderhaar, T. H.↗

A mesoscale analysis of the pre-storm environment on the 17 June 1986 COHMEX day

The study presented utilized special mesoscale Cooperative Huntsville Meteorological Experiment (COHMEX) data to understand the evolution of the preconvective environment on June 17, 1986. Using the special mesoscale COHMEX data, several mechanisms for triggering the convection are investigated. Afternoon heating probably was a major factor as observed noontime temperatures were near the sounding-derived convection temperatures. The special surface network revealed a quasi-stationary area of convergence not aligned with the front that may be associated with the orography of the area. This study demonstrates that rapid, small scale atmospheric variations preceded convective development on June 17, 1986.

Fuelberg, Henry E.↗

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗

Meteorology, Macrophysics, Microphysics, Microwaves, and Mesoscale Modeling of Mediterranean Mountain Storms: The M8 Laboratory

Comprehensive understanding of the microphysical nature of Mediterranean storms can be accomplished by a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, from synoptic scale down through the mesoscale, the cloud macrophysical scale, and ultimately the cloud microphysical scale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. This involves intense convective development, stratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that affect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. Insofar as hazardous Mediterranean storms, highlighted in this study by three mountain storms producing damaging floods in northern Italy between 1992 and 2000, developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within a storm domain. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting processes. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size disi:ributions, and fall rates of the various modes of hydrometeors found within hazardous storm environments.

Starr, David O.↗

Microphysics, Meteorology, Microwave and Modeling of Mediterranean Storms: The M(sup 5) Problem

Comprehensive understanding of the microphysical nature of Mediterranean storms requires a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, particularly from synoptic scale down to mesoscale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. Insofar as hazardous Mediterranean storms, highlighted by the September 25-28/1992 Genova flood event, the October 5-7/1998 Friuli flood event, and the October 13-15/2000 Piemonte flood event (all taking place in northern Italy), developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within the storm domains. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting proc esses. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size distributions, and fall rates of the various modes of hydrometeors found within the storm environments. This paper presents detailed 4-dimensional analyses of the microphysical elements of the three severe Mediterranean storms identified above, investigated with the aid of SSM/I and TRMM satellite measurements (and other remote sensing measurements). The analyses are guided by nonhydrostatic mesoscale model simulations at high resolution of the intense rain producing portions of the storm environments. The results emphasize how meteorological controls taking place at the large scale, coupled with localized terrain controls, ultimately determine the most salient features of the bulk microphysical properties of the storms. These results have bearing on precipitation remote sensing from space, and the role of modeling in designing precipitation retrieval algorithms.

Smith, Eric A.↗

A Machine Learning Bias Correction on Large–Scale Environment of High–Impact Weather Systems in E3SM Atmosphere Model

Large–scale dynamical and thermodynamical processes are common environmental drivers of high–impact weather systems causing extreme weather events. However, such large–scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high–impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large–scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ~1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high–impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large–scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias–corrected large–scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large–scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large–scale storm environments simulated by low–resolution climate models.

54 ENVIRONMENTAL SCIENCES↗

Relationships between convective storms and their environment in AVE IV determined from a three-dimensional subsynoptic-scale, trajectory model

The paper describes interrelationships between synoptic-scale and convective-scale systems obtained by following individual air parcels as they traveled within the convective storm environment of AVE IV. (NASA's fourth Atmospheric Variability Experiment, AVE IV, was a 36-hour study in April 1975 of the atmospheric variability and structure in regions of convective storms.) A three-dimensional trajectory model was used to calculate parcel paths, and manually digitized radar was employed to locate convective activity of various intensities and to determine those trajectories that traversed the storm environment. Spatial and temporal interrelationships are demonstrated by reference to selected time periods of AVE IV which contain the development and movement of the squall line in which the Neosho tornado was created.

Wilson, G. S.↗

Seasonal controls on isolated convective storm drafts, precipitation intensity, and life cycle as observed during GoAmazon2014/5

Abstract. Isolated deep convective cloud life cycle and seasonal changes in storm properties are observed for daytime events during the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Green Ocean Amazon Experiment (GoAmazon2014/5) campaign to understand controls on storm behavior. Storm life cycles are documented using surveillance radar from initiation through maturity and dissipation. Vertical air velocity estimates are obtained from radar wind profiler overpasses, with the storm environment informed by radiosondes. Dry-season storm conditions favored reduced morning shallow cloud coverage and larger low-level convective available potential energy (CAPE) than wet-season counterparts. The typical dry-season storm reached its peak intensity and size earlier in its life cycle compared with wet-season cells. These cells exhibited updrafts in core precipitation regions (Z>35 dBZ) to above the melting level as well as persistent downdrafts aloft within precipitation adjacent to their cores. Moreover, dry-season cells recorded more intense updrafts to earlier life cycle stages as well as a higher incidence of strong updrafts (i.e., >5 m s−1) at low levels. In contrast, wet-season storms were longer-lived and featured a higher incidence of moderate (i.e., 2–5 m s−1) updrafts aloft. These storms also favored a shift in their most intense properties to later life cycle stages. Strong downdrafts were less frequent within wet-season cells aloft, indicating a potential systematic difference in draft behaviors, as linked to graupel loading and other factors between the seasons. Results from a stochastic parcel model suggest that dry-season cells may expect stronger updrafts at low levels because of larger low-level CAPE in the dry season. Wet-season cells anticipate strong updrafts aloft because of larger free-tropospheric relative humidity and reduced entrainment-driven dilution. Enhanced dry-season downdrafts are partially attributed to increased evaporation, dry-air entrainment mixing, and negative buoyancy in regions adjacent to sampled dry-season cores.

54 ENVIRONMENTAL SCIENCES↗

Interactions Between Convective Storms and Their Environment

The ways in which intense convective storms interact with their environment are considered for a number of specific severe storm situations. A physical model of subcloud wind fields and vertical wind profiles was developed to explain the often observed intensification of convective storms that move along or across thermal boundaries. A number of special, unusually dense, data sets were used to substantiate features of the model. GOES imagery was used in conjunction with objectively analyzed surface wind data to develop a nowcast technique that might be used to identify specific storm cells likely to become tornadic. It was shown that circulations associated with organized meso-alpha and meso-beta scale storm complexes may, on occasion, strongly modify tropospheric thermodynamic patterns and flow fields.

Maddox, R. A.↗

Numerical Simulations of Precipitation Processes, Microphysics, and Microwave Radiative Properties of flood Producing Storms in Mediterranean & Adriatic Basins

A comprehensive understanding of the meteorological and microphysical nature of Mediterranean storms requires a combination of in situ data analysis, radar data analysis, and satellite data analysis, effectively integrated with numerical modeling studies at various scales. An important aspect of understanding microphysical controls of severe storms, is first understanding the meteorological controls under which a storm has evolved, and then using that information to help characterize the dominant microphysical processes. For hazardous Mediterranean storms, highlighted by the October 5-6, 1998 Friuli flood event in northern Italy, a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution. This involves intense convective development, Sratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that effect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. This talk overviews the microphysical elements of a severe Mediterranean storm in such a context, investigated with the aid of TRMM satellite and other remote sensing measurements, but guided by a nonhydrostatic mesoscale model simulation of the Friuli flood event. The data analysis for this paper was conducted by my research groups at the Global Hydrology and Climate Center in Huntsville, AL and Florida State University in Tallahassee, and in collaboration with Dr. Alberto Mugnai's research group at the Institute of Atmospheric Physics in Rome. The numerical modeling was conducted by Professor Oreg Tripoli and Ms. Giulia Panegrossi at the University of Wisconsin in Madison, using Professor Tripoli's nonhydrostatic modeling system (NMS). This is a scalable, fully nested mesoscale model capable of resolving nonhydrostatic circulations from regional scale down to cloud scale and below.

Smith, Eric A.↗

An intense, quasi-steady thunderstorm over mountainous terrain. II - Doppler radar observations of the storm morphological structure

The morphological characteristics of mean storm-scale airflow patterns of an intense quasi-steady storm formed in South Park, Colorado are described. Vertical transport of northerly low-level momentum within the updraft imparted a significant blocking on mid-level flow with southerly momentum. The blocking affected the movement and characteristics of adjacent, less organized storms, and additional storm-environment interactions produced an organized recirculation of precipitation particles from the mid-level updraft to the low-level updraft. The steadiness of the storm is found to have depended on the introduction of low-level flow directed opposite to mid-level flow, and on the formation of persistent downdrafts of sufficient magnitude to sustain an active gust front.

Knupp, K. R.↗

Kinetic energy budgets during the life cycle of intense convective activity

Synoptic-scale data at three- and six-hour intervals are employed to study the relationship between changing kinetic energy variables and the life cycles of two severe squall lines. The kinetic energy budgets indicate a high degree of kinetic energy generation, especially pronounced near the jet-stream level. Energy losses in the storm environment are due to the transfer of kinetic energy from grid to subgrid scales of motion; large-scale upward vertical motion carries aloft the kinetic energy generated by storm activity at lower levels. In general, the time of maximum storm intensity is also the time of maximum energy conversion and transport.

Fuelberg, H. E.↗

The effect of the arbitrary level assignment of satellite cloud motion wind vectors on wind analyses in the pre-thunderstorm environment

The impact of satellite-derived cloud motion vectors on SESAME rawinsonde wind fields was studied in two separate cases. The effect of wind and moisture gradients on the arbitrary assignment of the satellite data is assessed to coordinate surfaces in a severe storm environment marked by strong vertical wind shear. Objective analyses of SESAME rawinsonde winds and combined winds are produced and differences between these two analyzed fields are used to make an assessment of coordinate level choice. It is shown that the standard method of arbitrarily assigning wind vectors to a low level coordinate surface yields systematic differences between the rawinsonde and combined wind analyses. Arbitrary assignment of cloud motions to the 0.9 sigma surface produces smaller differences than assignment to the 825 mb pressure surface. Systematic differences occur near moisture discontinuities and in regions of horizontal and vertical wind shears. The differences between the combined and SESAME wind fields are made smallest by vertically interpolating cloud motions to either a pressure or sigma surface.

Peslen, C. A.↗

The effect of the arbitrary level assignment of satellite cloud motion wind vectors on wind analyses in the pre-thunderstorm environment

The impact of satellite-derived cloud motion vectors on SESAME rawinsonde wind fields was studied in two separate cases. The effect of wind and moisture gradients on the arbitrary assignment of the satellite data is assessed to coordinate surfaces in a severe storm environment marked by strong vertical wind shear. Objective analyses of SESAME rawinsonde winds and combined winds are produced and differences between these two analyzed fields are used to make an assessment of coordinate level choice. It is shown that the standard method of arbitrarily assigning wind vectors to a low level coordinate surface yields systematic differences between the rawinsonde and combined wind analyses. Arbitrary assignment of cloud motions to the 0.9 sigma surface produces smaller differences than assignment to the 825 mb pressure surface. Systematic differences occur near moisture discontinuities and in regions of horizontal and vertical wind shears. The differences between the combined and SESAME wind fields are made smallest by vertically interpolating cloud motions to either a pressure or sigma surface.

Peslen, C. A.↗

Satellite observations of the onset and growth of severe local storms

The mesoscale nature of the forcing and evolution of these storms was investigated, with emphasis on techniques to aid in the early detection of such severe events. In the pre-storm environment (t-4 to t-2 hours), the satellite wind fields were combined with moisture parameters to derive horizontal moisture flux information. Low level moisture convergence was indicative of regions of subsequent severe storm genesis. Dynamic parameters such as boundary layer vorticity production and relative vorticity were also useful prognosticators of subsequent severe activity.

Negri, A. J.↗