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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Life Cycle of Midlatitude Deep Convective Systems in a Lagrangian Framework

Deep Convective Systems (DCSs) consist of intense convective cores (CC), large stratiform rain (SR) regions, and extensive non-precipitating anvil clouds (AC). This study focuses on the evolution of these three components and the factors that affect convective AC production. An automated satellite tracking method is used in conjunction with a recently developed multi-sensor hybrid classification to analyze the evolution of DCS structure in a Lagrangian framework over the central United States. Composite analysis from 4221 tracked DCSs during two warm seasons (May-August, 2010-2011) shows that maximum system size correlates with lifetime, and longer-lived DCSs have more extensive SR and AC. Maximum SR and AC area lag behind peak convective intensity and the lag increases linearly from ~1-hour for short-lived systems to more than 3-hours for long-lived ones. The increased lag, which depends on the convective environment, suggests that changes in the overall diabatic heating structure associated with the transition from CC to SR and AC could prolong the system lifetime by sustaining stratiform cloud development. Longer-lasting systems are associated with up to 60% higher mid-tropospheric relative humidity and up to 40% stronger mid-to-upper tropospheric wind shear. Regression analysis shows that the areal coverage of thick AC is strongly correlated with the size of CC, updraft strength, and SR area. Ambient upper tropospheric wind speed and wind shear also play an important role for convective AC production where for systems with large AC (radius>120-km) they are 24% and 20% higher, respectively, than those with small AC (radius=20 km).

Anvil↗
DOE OSTI2025

A Climatology and Life‐Cycle Characteristics of Atmospheric Fronts and Their Associated Precipitation

Abstract Atmospheric fronts are one of the main sources of mid‐latitude variability. We employ a novel method for identifying and tracking fronts and frontal precipitation. Thermal and dynamical variables are used to identify fronts as areal objects in space, which are tracked in time using the open‐source TempestExtremes software package. Precipitation objects are co‐located to identify frontal precipitation. The method is subjected to validation and sensitivity tests using manually curated data from the National Weather Service. Climatologies of fronts and frontal precipitation are computed from reanalysis and observations; fronts are present upwards of 14% of the time in the storm tracks, and represent the majority (up to 90%) of total and extreme precipitation. Novel aspects of the method are showcased through the lifetime characteristics of fronts across North America. Three sets of warm and cold fronts were discovered, and their duration, distance‐traveled, and translation velocity are examined. Plain Language Summary Mid‐latitude low‐pressure systems and weather fronts are important for our day‐to‐day experience of weather events, particularly in the mid‐latitudes. This work makes use of standardized atmospheric data and creates a method of automatically tracking these important atmospheric features and their precipitation to quantify their relative role in global precipitation. Weather fronts are persistent in the mid‐latitudes and are associated with the majority of precipitation–particularly the most intense precipitation. Trajectories of fronts over North America are categorized to create a set of archetypal fronts that occur in that region. The differences between these types of fronts are characterized. Key Points An automated, efficient, and skillful frontal detection algorithm is developed and validated Fronts contribute a larger fraction of extreme precipitation than all precipitation in mid‐latitude storm tracks Fronts across North America have substantial variation in characteristics depending on their origin location

extratropical cyclone↗
DOE OSTI2018

Author Correction: Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery

In the original version of this Article, the first sentence of the sixth paragraph of the "Comparing emissions" section, the Results originally incorrectly read as 'In the base case, delivery of a small (0.5 kg) package with the small quadrotor drone has lower impacts than delivery by diesel truck, ranging from a 59% reduction in GHGs in California, to a 17% reduction in Missouri'. The correct version states '54%' instead of '59%' and '23%' instead of '17%'.The fourth sentence of the same paragraph originally incorrectly read as 'In the base case, delivery of a medium-sized (8 kg) package has 17% lower GHGs than delivery by truck in California, is about equivalent to delivery trucks for the U.S. average electricity mix, but has 77% higher GHGs than truck delivery in Missouri, which has a carbon-intensive electricity grid'. The correct version states 'In the base case, delivery of a medium-sized (8 kg) package has 9% lower GHGs than delivery by truck in California, is about 24% higher than delivery trucks for the U.S. average electricity mix, and has 50% higher GHGs than truck delivery in Missouri, which has a carbon-intensive electricity grid.The last sentence of the seventh paragraph of the same section originally incorrectly read as 'Because of the importance of electricity used to power the octocopter, charging with low-carbon electricity of 200 g GHG/kWh can reduce delivered package GHGs by 34% compared to diesel trucks'. The correct version states '37%' instead of '34%'.These errors have been corrected in both the PDF and HTML versions of the Article.

Stolaroff, Joshuah K.↗