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August 22-23, 2017
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The goal of Theme IV is to improve the observational and predictive understanding of land surface multi-year, seasonal and ephemeral processes associated with climate drivers through synoptic monitoring of the terrestrial domains. This theme integrates models with state-of-the-art observations across latitudinal gradients and supports NOAA’s goals of Climate Adaptation and Mitigation, and Weather Ready Nation.
Project I. Water resource assessments
Automated System for Evapotranspiration Mapping: An automated mapping at regional and national scales using remote sensing data and global climate grids will be developed. The system using SEBAL algorithm will be tested against both in-situ data from eddy flux correlation towers and other algorithms(MOD16,ALEXI,DisALEXI) in irrigated regions of the western United States, and quantifying the evaporative stress index anomalies using thermal band imagery from geostationary satellites.
Development and validation of Snow Water Equivalent data product: The primary intent consists in the development of a new improved snow and ice cover climatology and a corresponding daily dataset covering the period from 1998 to 2016 for use in climate modeling and in particular within the joint NOAA and NASA Global Precipitation Mission (GPM) project. The second part of the task consists in complementing the derived high-resolution snow extent maps with snow depth and SWE.
Project II. Synoptic and seasonal monitoring of the Earth System
Phenology: To elucidate unique and complimentary information associated with surface processes and vegetation phenology, we will combine radar backscatter and microwave emissivity measurements (e.g. ASCAT, SSM/I, AMSR2, SMAP, WindSAT, GMI) that are sensitive to both vegetation structure and water status, with satellite optical-IR datasets (e.g., MODIS and AVHRR, GOES-R). The products explores the state of the surface in terms of freeze and thaw cycles.
Land-Atmosphere Fluxes: CREST scientists will augment these NOAA capabilities with flux measurements from a network of 12 eddy covariance tower sites from Barrow, Alaska to Southern California, covering Arctic, chaparral and coastal sage scrub, coastal marine and desert systems.The tower measurements compared to inversion modeling of atmospheric concentrations and winds (e.g.WRFSTILT) to give increased confidence in the validity of estimates of surface fluxes.
Sensors for UAS platforms for Environmental Intelligence and Satellite Product Validation: The use of unmanned systems (aerial and water surface) is gaining a great deal of traction within NOAA, as it provides opportunities for more localized and higher resolution observations. These systems can then be used to complement satellite observations, and for calibration/validation of satellite sensors in combination with ancillary sensors.
Projects and tasks will be co-designed with the NOAA collaborators to have bi-directional interaction with NOAA scientists will enable effective transition of research to operations. Data analysis, computer programming and geo-spatial analysis using GIS and remote sensing will be part of all the projects. All students trained through scenario-based problem-solving environments. Wherever possible, the investigators will invite the NOAA collaborators to deliver guest training sessions, so the students can benefit from the discussion on the outcomes and experiences.