The research focus will be to develop a deep learning application to enhance the resolution of GPM data for improved identification of convective scale precipitation features, particularly outside the…

Ended Grant For Research Awarded Last action

Contract number
80NSSC20K0205
Awardee
Awarding agency
Obligated
$1,008,536

Award facts

Contract value 100% obligated
$1,008,535.96 Current and potential, with all options
Completion date 100% complete
  • Current, with exercised options
  • Potential, with all options
Contracting staff
NAICS code
Not on record
Set-aside
No set-aside
Competition
Full and Open Competition Basic Research
Pricing
Other
Place of performance
Huntsville, AL 35805, USA

Award details come from SAM.gov/FPDS.

Transactions

Action Obligated Date
Funding Only Action P00004 -$249
Other Administrative Action P00003 · Cloud-based analytic framework for precipitation research (capri) $0
Funding Only Action P00002 · Cloud based analytic framework for orecipitation reseaarch $182,039
Funding Only Action P00001 $395,000
Original award $431,746

About this award

Written by GovTribe AI ·

The National Aeronautics and Space Administration Shared Services Center awarded a $1,008,535.96 grant to The University of Alabama in Huntsville for research to develop a deep learning application to enhance the resolution of Global Precipitation Measurement data. The goal is improved identification of convective scale precipitation features outside the range of ground-based weather radar. Using convolutional neural networks, the university will build upon an existing prototype to infer high-resolution information from low-resolution variables. The research focuses on a technique called super-resolution or downscaling. Performance will take place in Huntsville, Alabama from February 2020 through December 2022. No set aside designation or involvement of major subcontractors was indicated.

Description

As the agency reported it.

The research focus will be to develop a deep learning application to enhance the resolution of GPM data for improved identification of convective scale precipitation features, particularly outside the range of ground-based weather radar. This resolution enhancement technology is called super-resolution or downscaling. Deep learning convolutional neural networks (cnns) will be used to learn features that can infer high-resolution information from low-resolution variables, building on a prototype developed by the PI of this proposal in collaboration with GPM mission scientists.

Quick answers

Who was awarded contract 80NSSC20K0205?

80NSSC20K0205 was awarded to The University Of Alabama In Huntsville by Shared Services Center (National Aeronautics and Space Administration) on February 15, 2020.

How much is contract 80NSSC20K0205 worth?

The government has obligated $1,008,536 on 80NSSC20K0205.

Was contract 80NSSC20K0205 competed?

The extent of competition for 80NSSC20K0205 was full and open competition.

On GovTribe

See this award's full record

  • Every transaction and funding action
  • The awardee's other awards and teaming partners
  • Similar awards and recompete opportunities
  • Ask GovTribe AI about this award
Try for free Login