| NSF Org: |
AGS Division of Atmospheric and Geospace Sciences |
| Recipient: |
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| Initial Amendment Date: | August 9, 2017 |
| Latest Amendment Date: | August 9, 2017 |
| Award Number: | 1648629 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Varavut (Var) Limpasuvan
AGS Division of Atmospheric and Geospace Sciences GEO Directorate for Geosciences |
| Start Date: | August 15, 2017 |
| End Date: | July 31, 2021 (Estimated) |
| Total Intended Award Amount: | $330,829.00 |
| Total Awarded Amount to Date: | $330,829.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
W5510 FRANKS MELVILLE MEMORIAL LIBRARY STONY BROOK NY US 11794-0001 (631)632-9949 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
NY US 11794-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
PREEVENTS - Prediction of and, Climate & Large-Scale Dynamics |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.050 |
ABSTRACT
Hazardous convective weather (HCW), including tornadoes, damaging wind, and hail, poses significant risk to life and property each year. HCW events are small scale with short duration time, which makes it extremely difficult to predict their occurrence even a few hours in advance. However, they do often form and develop preferentially within certain larger-scale environments and primarily in a few geographical regions globally, the most prominent of which is the Eastern United States. Why these potentially deadly larger-scale environments are confined to such specific regions is not well understood. This lack of knowledge greatly limits our ability to predict how the risk posed to society by these events vary on inter-annual and multi-decadal timescales. This research project aims to examine the factors (such as land-sea contrasts, elevated terrain upstream, and their interferences with atmospheric jet streams) that contribute to environments favorable for the generation of HCW events. Because it is difficult to disentangle specific physical mechanisms that are responsible for HCW environments using observations and realistic modeling simulations alone, the PIs will perform a series of experiments using reduced-complexity models where gross representations of land and terrain are imposed under various complexity configurations.
The project is designed to enhance understanding of the fundamental processes underlying the natural hazards associated with convective weather. It aims to improve our capability to model weather hazards by determining the key elements that must be included in models to capture the distribution of HCWs and the risks they pose. The work addresses forecasting in an aggregate sense, focusing on how HCW activity is likely to change with large-scale conditions. The goal is to predict how HCW environments and, in turn, how the associated societal impacts, including loss of life and property damage, may change from year to year, decade to decade, and beyond. The project will train graduate student and post-doctoral scientists who will make future contributions to the burgeoning field of hazardous convective weather and climate.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The major goals of the project were to improve our understanding of the fundamental role of land surface properties on the generation of environments conducive to Severe Local Storms (SLS, e.g., supercell thunderstorms) on climate time-scales via both modified-Earth and idealized aquaplanet-type global climate simulations. Specifically, we have furthered our understanding of how the combination of land-sea contrast and elevated terrain and their relative orientations serve to produce these environments. This effort includes both simulations in which the real Earth land surface is modified and simulations in which idealized land and elevated terrain are added to an aquaplanet.
Some key outcomes of this work are:
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Reanalysis products compare well against radiosonde observations, particularly east of the Rocky Mountains (where severe local storms are most prevalent).
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The Community Atmosphere Model (CAM) compares quite favorably against reanalysis in both severe local storm environments and large-scale features such as drylines, elevated mixed layers, extratropical cyclone activity, and the Great Plains Low-Level Jet. Some biases in CAPE are found over the far eastern US.
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Overall, severe local storm environments depend strongly on upstream elevated terrain but only weakly on the Gulf of Mexico. Elevated terrain is critical for producing these environments specifically over the continental interior though not necessarily near the coast.
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Idealized climate models with ideal representation of continents are promising tools for studying the fundamental interconnections between large-scale circulation and local scale environments that can lead to extreme weather events.
In addition, this work supported the training of graduate students in atmospheric and climate science. The project also produced a number of CAM simulations that are now publicly available and helped to refine the implementation of idealized continental configurations in CAM for use by the border community.
Last Modified: 01/05/2022
Modified by: Kevin Reed
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