49 citations · 87 across the 10 of their papers we have counts for
10 papers
UT-GraphCast Hindcast Dataset: A Global AI Forecast Archive from UT Austin for Weather and Climate Applications
Naveen Sudharsan, Manmeet Singh, Harsh Kamath +4
The UT GraphCast Hindcast Dataset from 1979 to 2024 is a comprehensive global weather forecast archive generated using the Google DeepMind GraphCast Operational model. Developed by…
Enhancing Near Real Time AI-NWP Hurricane Forecasts: Improving Explainability and Performance Through Physics-Based Models and Land Surface Feedback
Naveen Sudharsan, Manmeet Singh, Sasanka Talukdar +12
Hurricane track forecasting remains a significant challenge due to the complex interactions between the atmosphere, land, and ocean. Although AI-based numerical weather prediction…
Developing Gridded Emission Inventory from High-Resolution Satellite Object Detection for Improved Air Quality Forecasts
Shubham Ghosal, Manmeet Singh, Sachin Ghude +8
This study presents an innovative approach to creating a dynamic, AI based emission inventory system for use with the Weather Research and Forecasting model coupled with Chemistry…
Developing Digital Twins for Earth Systems: Purpose, Requisites, and Benefits
Yuhan Rao, Rob Redmon, Kirstine Dale +10
The accelerated change in our planet due to human activities has led to grand societal challenges including health crises, intensified extreme weather events, food security, enviro…
NDUI+: A fused DMSP-VIIRS based global normalized difference urban index dataset
Manmeet Singh, Subhasis Ghosh, Harsh Kamath +9
Urbanization is advancing rapidly, covering less than 2% of Earth's surface yet profoundly influencing global environments and experiencing disproportionate impacts from extreme we…
Fire and Smoke Digital Twin -- A computational framework for modeling fire incident outcomes
Junfeng Jiao, Ryan Hardesty Lewis, Kijin Seong +4
Fires and burning are the chief causes of particulate matter (PM2.5), a key measurement of air quality in communities and cities worldwide. This work develops a live fire tracking…
Urban precipitation downscaling using deep learning: a smart city application over Austin, Texas, USA
Manmeet Singh, Nachiketa Acharya, Sajad Jamshidi +5
Urban downscaling is a link to transfer the knowledge from coarser climate information to city scale assessments. These high-resolution assessments need multiyear climatology of pa…
Short-range forecasts of global precipitation using deep learning-augmented numerical weather prediction
Manmeet Singh, Vaisakh S B, Nachiketa Acharya +5
Precipitation governs Earth's hydroclimate, and its daily spatiotemporal fluctuations have major socioeconomic effects. Advances in Numerical weather prediction (NWP) have been mea…
GLObal Building heights for Urban Studies (UT-GLOBUS) for city- and street- scale urban simulations: Development and first applications
Harsh G. Kamath, Manmeet Singh, Neetiraj Malviya +8
We introduce University of Texas - Global Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200…
Deep learning for improved global precipitation in numerical weather prediction systems
Manmeet Singh, Bipin Kumar, Suryachandra Rao +4
The formation of precipitation in state-of-the-art weather and climate models is an important process. The understanding of its relationship with other variables can lead to endles…