| NSF Org: |
AGS Division of Atmospheric and Geospace Sciences |
| Recipient: |
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| Initial Amendment Date: | June 16, 2023 |
| Latest Amendment Date: | June 16, 2023 |
| Award Number: | 2330336 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Nicholas Anderson
nanderso@nsf.gov (703)292-4715 AGS Division of Atmospheric and Geospace Sciences GEO Directorate for Geosciences |
| Start Date: | January 1, 2024 |
| End Date: | December 31, 2024 (Estimated) |
| Total Intended Award Amount: | $16,000.00 |
| Total Awarded Amount to Date: | $16,000.00 |
| Funds Obligated to Date: |
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| Recipient Sponsored Research Office: |
3112 LEE BUILDING COLLEGE PARK MD US 20742-5100 (301)405-6269 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
3112 LEE BLDG 7809 REGENTS DR College Park MD US 20742-5103 |
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Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| NSF Program(s): | Physical & Dynamic Meteorology |
| 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
Data assimilation plays a crucial role in weather forecasting by combining observations of the atmosphere with numerical model data to determine the current state of the atmosphere. This is important because the current state of the atmosphere is used as a starting point for the weather forecasts, and the more accurate the starting point is, the better the weather forecast will be. A significant improvement in the accuracy of weather forecasts over the past few decades can be attributed to the enhanced precision of current weather estimates obtained through data assimilation. The Workshop will enable collaboration and discussion between experts in data assimilation, including topics such as using machine learning to enhance the performance of data assimilation, how observations can be optimally used to improve weather forecasts, and how data assimilation methods can be used for the ocean as well as for the atmosphere. The workshop's main goal is to advance fundamental understanding of data assimilation and sensitivity analysis, and their applications to weather forecasting and climate estimation for societal benefit. Travel support will be provided for graduate students to attend the Workshop to learn directly from the scientific community and to present their own research.
The Workshop participants will present, review, discuss, and evaluate works pertaining to atmospheric sensitivity analysis and data assimilation, but will include representation from oceanography, coupled atmosphere-ocean systems, and other fields that employ similar techniques. Topics for presentation and discussion will include development of computationally efficient techniques for sensitivity analysis, including machine learning, diagnostic tools, and consideration of statistical issues affecting sensitivity analysis or data assimilation. Applications of data assimilation to synoptic and dynamic analysis of weather events, to reanalyses, and to estimation of observation impacts will be evaluated. Presentations will include overview talks on fundamentals and recent paths of development, and posters or short seminars on new works.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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 Twelfth Workshop on Meteorological Sensitivity Analysis and Data Assimilation, held from May 19-24, 2024, in Lake George, New York, was partially funded by the National Science Foundation (NSF), through supporting student travels, to enhance knowledge and collaboration in meteorological data assimilation. This workshop featured five days of presentations, discussions, and tutorial sessions aimed at improving weather forecasting and climate modeling.
The workshop focused on advancing scientific understanding in data assimilation methods critical for meteorology. Participants engaged in tutorials that introduced essential concepts and practical techniques. With 35 oral and nine poster presentations covering diverse topics, the workshop fostered innovation and collaboration among both emerging scientists and established researchers, ultimately enhancing the field's research landscape.
Significantly, the workshop promoted diversity and inclusivity within the scientific community, with a notable percentage of attendees from minority-serving institutions and an increase in female representation to 31%. By equipping participants with vital skills, the workshop aimed to improve weather prediction and climate modeling, thereby benefiting public safety and preparedness for extreme weather events. The collaborative environment also facilitated networking, enabling connections that could lead to future research partnerships.
The outcomes surpassed expectations, with a record number of participants, highlighting a growing interest in meteorological research. The workshop not only provided crucial educational experiences but also fostered a sense of community among researchers. Overall, the Twelfth Workshop on Meteorological Sensitivity Analysis and Data Assimilation made significant strides in advancing research, promoting diversity, and enhancing public safety through improved forecasting capabilities.
Last Modified: 09/19/2024
Modified by: Isaac Moradi
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