Severe weather and air quality events have major ecological, human-health, and socio-economic impacts. Anthropogenic and natural emissions drive air quality and climate change, which in turn drive severity and frequency of future weather events. GHGs, ozone, and aerosols play an important role in global climate change, but the impact of aerosols on climate remains the largest uncertainty in climate forecasts. Under Theme II we will use innovative technology and integrative observations to study atmospheric processes and trace constituents, validate satellite products, and improve model predictions.
Project I: Weather Hazards
Storm and Storm Surge Prediction: Heavy precipitation and storm surge prediction continues to be a key task at NOAA. Research will address these hazards through: (1) an extra-tropical cyclone storm surge analysis, (2) high-temporal resolution convective storm analysis, and (3) analysis and modeling of convective initiation in Puerto Rico.
Heat Stress and Urban Modeling: Heat advisory products are of high value for public health. Each year more people perish due to heat related ailments compared to other natural hazards. Persistent thermal IR imagery from GOES-R will enable derivation of key products including Heath Index and Thermal Storage in urban areas. These products and related analysis above will drive CREST’s urbanized Weather Research and Forecast Model (uWRF).
Project 2: CREST Observing Systems for Atmospheric Process and Air Quality Applications
The CREST Earth System Observing Network (CESON): CESON is the result of extensive enhancement to the CREST Lidar Network (CLN) with sites at CCNY (NYC), UMBC (Baltimore, MD), HU (Hampton, VA), and UPRM (Mayaguez, PR) with extensive remote and in-situ observation capabilities, and Direct Broadcast Satellite stations for receiving data from GOES/GOES-R, as well as Suomi-NPP/JPSS-1, Terra/Aqua, and other polar orbiting satellites. CESON will be utilized for satellite validation/calibration, and forecast model verification and refinement.
Observing System Technologies and Field Campaigns: CREST research will engage in optimal application and new products from existing observing systems and networks and development of advanced sensing and observation technologies. CREST capabilities and technologies will be engaged in NOAA field campaigns.
Students will be trained in remote sensing techniques and technologies, instrumentations design and engineering, field measurements and campaigns, statistical data analysis, and inversion algorithms for products development. Student training component include; downloading and analysis of satellite data; Statistical data analysis; Geo-spatial and multi-dimensional data analysis; Blending data with multiple spatial and temporal resolutions; Development of data products including spatial product maps, model urban physical and transport processes and work with and optimization of numerical urbanized weather forecast models.