Applications Capability Matrix

The PACE mission will advance the state of the art of satellite-driven Earth science, while fulfilling tangible needs of society. The PACE Applications program provides real-world context for the mission and establishes the utility and relevance of this next-generation Earth-observing satellite to decision-makers. The PACE Applications Capability Matrix asks fundamental applied science questions and demonstrates how PACE Early Adopters and Science and Applications Team members are working to solve them.

Can marine mammal activity serve as an indicator of a changing climate?

Overview

	PI: Elizabeth Ferguson	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Combine in situ & satellite data to assess ecological characteristics associated with marine mammal occurrence & the impacts of climate change on indicator species	Advance marine mammal monitoring & understanding of indicator species; Extend spatial domain & temporal capacity of marine mammal monitoring in coastal Oregon	Water Resources	Early Adopter: Ocean Science Analytics End Users: Commercial & recreational fishing industry; online training community	1

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	PI: Elizabeth Ferguson
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, fluorescence line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition	PACE OCI is expected to produce highly accurate measurements related to phytoplankton in coastal oceans (~1.1 km spatial resolution at nadir) every 1-2 days	Toby Westberry	In situ Chla, pH, pCO2, bio-acoustic data, SST

How do ocean organisms affect the atmosphere and coastal air quality?

Overview

	PI: Daniel Tong	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Combine hyperspectral satellite data of phytoplankton communities with polarimetric retrievals of trace gases & aerosols in the atmosphere	Improve the accuracy of global & regional air quality prediction	Air Quality	Early Adopter: George Mason University End Users: National Weather Service; air quality and climate research community	3

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	PI: Daniel Tong
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Aerosol fine mode fraction (over ocean), Chla, daily PAR, water path of liquid and ice clouds, cloud phase, optical thickness of liquid and ice clouds, spectral aerosol optical depth, instantaneous PAR, cloud top height	PACE aerosol and cloud data will be used to estimate the effect of maritime aerosols on ocean ecosystems & cycling of organic matter in the ocean but using models that correlate aerosol characteristics & abundance to such properties as OCI chlorophyll & phytoplankton concentration	Pengwang Zhai; Jacek Chowdhary	Wind, air temperature, Goddard Modeling & Assimilation Office's MERRA model outputs

What are the long-term changes in air quality and pollutants? How do they vary with climate change?

Overview

	PI: Mariusz Pagowski	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral remote sensing data to constrain aerosol concentrations within the FV3-GF5/GOCART model	Improve the global climate model's ability to estimate aerosols states & their impact on weather and climate	Air Quality; Climate	Early Adopter: National Oceanic and Atmospheric Administration End Users: NOAA Climate Prediction Office: Modeling, Analysis, Predictions, and Projections Program; NOAA Office of Weather and Air Quality	2

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	PI: Mariusz Pagowski
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Aerosol fine mode fraction (over ocean), spectral aerosol optical depth, aerosol single scattering albedo	PACE polarimeters will provide a number of spectral aerosol properties, along with model data that will be used to identify aerosol types & correlate variations in climate with long term trends of aerosol types such as sulfates, dust, smoke, sea salt, organic carbon, & black carbon	Snorre Stames; Jacek Chowdhary; Lorraine Remer	FV3-GF5/GOCART model, JEDI assimilation toolkit, Goddard Modeling & Assimilation Office's MERRA-2 analysis

Can user-friendly mobile and desktop apps support near-real-time decision making and resource management?

Overview

	PI: Marina Marrari	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Digest satellite data into mobile app serving near-real-time fisheries products	Enable advanced & continuous mobile app data, related to phytoplankton community structure & red tides, for users	Water Resources	Early Adopter: La Federación Costarricense de Pesca End Users: Recreational anglers, commercial fishermen, tourism agents, non-government organizations, academia	3

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	PI: Marina Marrari
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, NPP, phytoplankton community composition	PACE OCI will provide hyperspectral measurements, related to phytoplankton & algal blooms, for coastal oceans every 1 to 2 days with a data latency of 6-12 hours	Brian Barnes	SST, currents, sea level anomalies, bathymetry, mixed layer depth, tide forecasts, moon phase

Overview

	PI: Vardis Tsontos	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Ingestion of hyperspectral ocean color products within COVERAGE as a complement to current baseline set of global interagency datasets for the range of key ocean parameters	Enable use of advanced ocean products via COVERAGE in support of population & biodiversity responses to environmental variability & climate, species habitat characterization & utilization, by-catch mitigation, fishing closed area & marine protected areas	Water Resources	Early Adopter: NASA JPL End Users: GEO-Marine Biodiversity Observation Network; GEO-Blue Planet; GOOS-AniBOS; Sargasso Sea Commission; Inter-American Tropical Tuna Commission	4

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	PI: Vardis Tsontos
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Spectral remote sensing reflectance (Rrs), Fluorescence line height, Spectral diffuse attenuation coefficients (Kd), Spectral CDOM absorption, Chla, NPP, Phytoplankton community composition	PACE OCI will offer highly accurate (high signal to noise) hypespectral measuremetns in coastal environments enabling validation/tuning of hypespectral algorithms every 1 to 2 days	Chuanmin Hu	In situ HPLC Chla (from SEABASS, EXPORTS, CORALS)

How does water clarity information help monitor estuary health, river outflow, and manage resources?

Overview

	PI: Jessica Turner	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral remotely sensed data to improve estimation of water clarity & suspended particle size estimation in the Chesapeake Bay	Better estimation of water clarity & advanced water quality benchmarking for the Chesapeake Bay watershed	Water Resources	Early Adopter: University of Connecticut, Department of Marine Sciences End Users: Chesapeake Bay Program Modeling Workgroup & Scientific, Technical Assessment & Reporting Workgroup; Virginia Shellfish Aquaculture Industry Advisory Committee	3

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	PI: Jessica Turner
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, POC, spectral Rrs, spectral bbp coefficients, spectral Kd, spectral non-algal particles plus DOM absorption coefficients, spectral phytoplankton absorption, instantaneous PAR, NPP, spectral CDOM absorption, spectral slope coefficients of CDOM absorption, phytoplankton pigment concentrations, concentration of phytoplankton carbon, concentration of DOC, suspended particulate matter, ocean surface refractive index	PACE OCI will offer highly accurate (high signal to noise) hypespectral measuremetns in coastal environments enabling estimation of water clarity/quality every 1 to 2 days	Robert Frouin; Emmanuel Boss	In situ measurements from the Chesapeake Bay Program and model output, simulated data in coastal waters

Overview

	PI: Jason Jolliff	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral data to retrieve true-color water clarity indices to better constrain high-temporal geostationary data	Informed monitoring of river plume outflows and coastal water clarity to enhance civilian and military operations and resource management	Water Resources	Early Adopter: U.S. Naval Research Laboratory End Users: NRL-Ocean Modeling and Prediction Branch	3

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	PI: Jason Jolliff
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Rrs, Kd, bbp, spectral top-of-atmosphere radiances from OCI	PACE OCI will offer highly accurate (high signal to noise) hypespectral measuremetns in coastal environments every 1 to 2 days	Michael Twardowski	GOES-R ABI visible band data & other geostationary satellite data

Overview

	PI: Michael Ondrusek	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral data to reconfigure & optimize TSM algorithms for a wide range of inland and coastal waters	Improved ability to quantify TSM concentrations under different environmental conditions	Water Resources	Early Adopter: National Oceanic and Atmospheric Administration End Users: Maryland Department of Natural Resources; NOAA Coastwatch	2

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	PI: Michael Ondrusek
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Rrs, Chla, Kd, spectral non-algal particles plus DOM absorption coefficients, bbp, suspended particulate matter, spectral slope coefficients of CDOM absorption, spectral CDOM absorption	PACE OCI will offer highly accurate (high signal to noise) hypespectral measuremetns in coastal environments enabling validation/tuning of hypespectral algorithms every 1 to 2 days	Nima Pahlevan and Michael Twardowski	In situ measurements of hyperspectral Rrs, chla, absorption and scattering coefficients, Kd, phytoplankton composition, and AOD

Can air quality alerts, warnings, and forecasts be enhanced to better support human health?

Overview

	PI: Madhusudan Anand	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hypspectral & polarimetric cloud and aerosol data to inform air quality in India.	Advanced air quality modelling in India including improved aerosol emissions, forecasting visibility, understanding extreme temperatures, accounting for carbon emissions and climate risk, predicting health impacts	Air Quality	Early Adopter: Datair Tech. PVT LTD End Users: Bayer; InkRepubliq; NIKE; Brigade Group	4

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	PI: Madhusudan Anand
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Aerosol fine mode fraction (over ocean), Cloud mask, Cloud phase, Optical thickness of liquid and ice clouds, Cloud top pressure of opaque clouds, Cloud detection, Cloud physical thickness, Cloud top height, Liquid cloud optical depth, Liquid cloud droplet effective radius, Liquid cloud droplet effective variance, Thin cloud contamination, Spectral aerosol optical depth, aerosol number concentration, aerosol size distribution, aerosol complex refractive index, aerosol layer height, aerosol shape-fractional spherical, aerosol single scattering albedo, Aerosol optical depth in the near-infrared, Ocean surface refractive index	PACE data will also be used to identify aerosol types and locate aerosol layers in the vertical and estimate boundary layer height enabling estimation of PM2.5 near the surface.	Alexei Lyapustin; Lorraine Remer; Snorre Stamnes	In situ air quality data, NO2, SO2, OZONE, CO, and other pollutant data, Methane Plume data, CO2, Water Vapor, air temperature, altitude, pressure, humidity, wind, in situ weather station data, radiation and heat flux data, fire data, land use and land surface data

Overview

	PI: Heather Holmes	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral remote sensing data to track wildfire plumes, improve emissions modeling, & determine pollutant sources	Improve air quality & exposure models of elevated PM2.5 concentrations in the western United States. Provide more accurate and refined smoke forecasts, air quality alerts & advisories	Air Quality	Early Adopter: University of Utah End Users: Washoe County Air Quality Management Division; University of Nevada Living With Fire Program; Western States Air Resources Council; Western Regional Air Partnership	2

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	PI: Heather Holmes
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Aerosol fine mode fraction (over ocean), spectral aerosol optical depth, aerosol number concentration, aerosol size distribution, aerosol complex refractive index, aerosol layer height, aerosol shape-fractional spherical, aerosol single scattering albedo	PACE data will be used to locate aerosol layers in the vertical and estimate boundary layer height enabling estimation of PM2.5 near the surface. PACE data will also be used to identify aerosol types, in particular smoke plumes, to improve smoke transport & deposition models that will inform the impact of wildfires on air quality.	Alexei Lyapustin	Wind, air temperature, fire radiative power, soil moisture, in situ observations, Goddard Modeling & Assimilation Office's MERRA model outputs

Overview

	PI: S. Marcela Loría-Salazar	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use and evaluation of hypespectral & polarimetric aerosol data to advance smoke air quality models	Advance air quality models to better inform public health alerts in the Southern Great Plains region of the United States and additional understanding the role of aerosols in regional weather	Air Quality	Early Adopter: Univ. of Oklahoma End Users: Oklahoma MESONET Fire Network; Oklahoma Air Quality Division	4

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	PI: S. Marcela Loría-Salazar
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Aerosol fine mode fraction (over ocean), Spectral aerosol optical depth, aerosol number concentration, aerosol size distribution, aerosol complex refractive index, aerosol layer height, aerosol shape-fractional spherical, aerosol single scattering albedo	PACE data will be used to locate aerosol layers in the vertical and estimate boundary layer height enabling estimation of PM2.5 near the surface. PACE data will also be used to identify aerosol types, in particular smoke plumes, to improve smoke transport & deposition models that will inform the impact of wildfires on air quality.	Alexei Lyapustin	In situ AERONET spectral aerosol and water vapour measurements, surface PM2.5 mass concentrations measurements, MODIS & VIIRS AOD, VIIRS Deep Blue (DB), plume injection height (PIH) ASHE & MAIAC retrievals

When oil leaks, seeps, or spills into the environment, how do we know its amount and impact?

Overview

	PI: Chuanmin Hu	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral remote sensing data to differentiate oil types & amounts	Improved detection, differentiation, & estimation of oil thickness/depth for oil seeps/spills	Disasters	Early Adopter: University of South Florida End Users: Oil management agencies; NOAA NRDA; NOAA CoastWatch; USEPA	1

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	PI: Chuanmin Hu
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Rrs, ocean surface roughness, ocean surface refractive index	PACE polarimeters will provide observations in UV, visible, NIR, and IR spectral region (380 - 1000 nm) and in the SWIR spectral region (1.2 and 1.6 mm) to spectrally differentiate various types of oil slicks & quantify oil thickness	Matteo Ottaviani	Hyperspectral Rrs measurements (in situ, airborne), oil collection samples, wind, SSH

How does coastal water quality affect aquaculture site selection and fishery operations?

Overview

	PI: Damian Brady	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Relate remotely sensed phytoplankton size to bivalve feeding rates to inform offshore site selection in Maine	Provide more relevant information for aquaculture site selection in Maine's estuaries	Water Resources; Ecological Forecasting	Early Adopter: University of Maine End Users: Limited purpose aquaculture license holders in Maine	4

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	PI: Damian Brady
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, fluorescence line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition	PACE OCI will deliver hyperspectral measurements of phytoplankton characteristics in coastal environments with a ground track spacing of ~1.1 kilometers every 1 to 2 days	Emmanuel Boss	SST, currents, SSH, bathymetry, thermocline depth, tide forecasts

Overview

	PI: Marié Smith	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Integrate hyperspectral phytoplankton data into phytoplankton IOP model for a fisheries & aquaculture decision-support tool	Support small scale commercial and subsistence fishing in South African waters & identify productive areas for fishing	Water Resources; Ecological Forecasting	Early Adopter: Council of Scientific & Industrial Research End Users: Aquaculture farms; local municipalities; desalination plants; fisherpeople; CSIR and Southern Ocean Carbon & Climate Observatory	3

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	PI: Marié Smith
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, Rrs, Fluorescence line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition	PACE OCI will deliver hyperspectral measurements of phytoplankton characteristics in coastal environments with a ground track spacing of ~1.1 kilometers every 1 to 2 days	Peter Gaube; Alison Chase	Sentinel-3 OLCI reflectance products, in situ phytoplankton counts, SST from MODIS, VIIRS & SLSTR

What risks do climate extremes and natural disasters pose to food security, coasts, and wetland ecosystems?

Overview

	PI: Jordan Borak	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral satellite data to resolve spectral characteristics of surface vegetation (predictor of surface permeability and runoff during extreme rain events)	Improved understanding of wetland ecosystem health & structure (during flood events) in the Chesapeake Bay & southeastern Virginia	Terrestrial Resources; Ecological Forecasting	Early Adopter: University of Maryland End Users: Chesapeake Bay water quality managers and run-off modelers; coastal Virginia and Maryland city managers and disaster/flooding responders	2

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	PI: Jordan Borak
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Surface reflectance, NDVI, BRDF/albedo and model parameters, land surface BRDF	PACE OCI will provide high-resolution spectral information (5 nm) in the UV & NIR regions of the spectrum capable of identifying spectral characteristics of surface vegetation	Fred Huemmrich	ICESat-2 vegetation/land heights and inland water product, NWI wetlands designations, MODIS land cover, high-resolution gridded DEM

Overview

	PI: Anastasia Romanou	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Assimilate satellite retrievals of phytoplankton productivity & community composition into global climate models	Improve global climate models for risk analysis to protect natural and food resources against current & future climate extremes	Climate; Water Resources	Early Adopter: NASA Goddard Institute for Space Studies/Columbia University End Users: World Wildlife Fund; United Nations Disaster Risk Reduction Office; United Nations Development Program; Wildlife Conservation Society	3

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	PI: Anastasia Romanou
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, daily PAR, Rrs, Kd, spectral non-algal particles plus DOM absorption coefficients, bbp, spectral phytoplankton absorption coefficients, POC, instantaneous PAR, NPP, CDOM absorption, phytoplankton pigment concentrations, phytoplankton community composition, concentration of phytoplankton carbon, DOC, suspended particulate matter	PACE OCI is expected to produce hyperspectral observations, including phytoplankton characertistics, for global oceans with a footprint of ~1.1 kilometers every 1 to 2 days, available within 6-12 hours	Peter Gaube, Cecile Rousseaux, and Patricia Castellanos	SST, SSH, precipitation, riverine outflow, Chla, NPP, MERRA-2 atmospheric conditions fields, Model-E model daily simulation climate data, ECCO data

Where do algal blooms occur? How do environmental factors enhance and respond to algal blooms?

Overview

	PI: Clarissa Anderson	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Apply satellite data to California HAB forecasting tool (C-HARM) to protect ecosystem health & understand coastal ocean ecological dynamics	Improve coastal California HAB model products for water resource managers & federal, state, regional partners & decision-makers	Water Resources; Ecological Forecasting	Early Adopter: Scripps Institution of Oceanography End Users: Marine mammal resource managers; shellfish growers; the California Department of Fish and Wildlife; California Department of Public Health; California Office of Environmental Health and Hazard Assessment; fisherfolk	5

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	PI: Clarissa Anderson
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, spectral top-of-atmosphere radiances from OCI, fluorescence line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition	PACE OCI is expected to produce hyperspectral observations, related to phytoplankton & algal blooms, for coastal oceans every 1 to 2 days, available within 6-12 hours	Dave Siegel	SST, winds, currents, SSH, model output, buoy data, simulated data over coastal California

Overview

	PI: Richard Stumpf	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral Rrs to separate out bloom types in turbid coastal & estuarine environments	Targeted HAB management to advise state managers, local health department, water treatment operators, aquaculture & commercial fisheries	Water Resources	Early Adopter: National Oceanic and Atmospheric Administration End Users: State managers in Florida, Maryland, Virginia, Ohio, California	3

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	PI: Richard Stumpf
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Rrs, bbp, spectral non-algal particle plus DOM absorption coefficients, Chla, fluorescence line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition, ocean body properties	PACE OCI will produce highly accurate observations of phytoplankton characteristics & water inherent optical properties enabling separation of bloom types in coastal waters (~1.1 km spatial resolution at nadir) every 1 to 2 days	Robert Shuchman	In situ data and laboratory analysis, in situ hyperspectral radiances, Sentinel 2-3 satellite data, simulated data in coastal waters

Overview

	PI: Salem Ibrahim Salem	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Combine in situ water quality data with hyperspectral satellite data to develop HAB estimation models for inland & coastal waters	Improved detection of HABs, red tides, and blue tides in coastal areas and lakes of Japan, Indonesia, and Thailand	Water Resources	Early Adopter: Kyoto University of Advanced Science End Users: Ministry of Land, Infrastructure, Transport, & Tourism, Government of Japan; Port & Airport Research Institute; Marine Environmental Information Group; Chiba Prefectural Fisheries Research Center	3

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	PI: Salem Ibrahim Salem
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, spectral top-of-atmosphere radiances from OCI, fluorescence line height, Rrs, daily PAR, bbp, spectral phytoplankton absorption coefficients, spectral non-algal particle plus DOM absorption coefficients, fluorescene line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition, suspended particulate matter, CDOM absorption, spectral slope coefficients of CDOM absorption, POC, PIC, spectral aerosol optical depth	PACE OCI will produce highly accurate observations of phytoplankton characteristics & water inherent optical properties enabling separation of bloom types in coastal waters (~1.1 km spatial resolution at nadir) every 1 to 2 days	Nima Pahlevan	In situ Rrs, Kd, CDOM, bbp, Chla, AOD, TSS, and phytoplankton absorption; HICO satellite observations

Overview

	PI: Moritz Lehmann	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Combine in situ phytoplankton abundance & pigment analysis with satellite data to support routine monitoring of bloom events	Improve HAB alert systems & better inform the restoration activities in New Zealand waters	Water Resources	Early Adopter: Xerra End Users: Environment Canterbury Bay of Plenty Regional Council; Waikato Regional Council; New Zealand Antarctic Science Platform	2

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	PI: Moritz Lehmann
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, spectral top-of-atmosphere radiances from OCI, fluorescence line height, Rrs, Kd, NPP, phytoplankton pigment concentrations, phytoplankton community composition, suspended particulate matter	PACE OCI will produce highly accurate observations of phytoplankton characteristics & in water constituents enabling identification of bloom types in coastal waters every 1 to 2 days	Peter Gaube; Alison Chase	In situ hyperspectral surface reflectance, phytoplankton species counts, multispectral and hyperspectral reflectance from UAV-borne sensors, water constituents (CDOM, Chla, phycocyanin)

Overview

	PI: Fernanda Maciel	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Use hyperspectral data to understand suspended sediments and detect cyanobacteria HABs in the Río de la Plata Estuary, Uruguay	Improve detection and quantification of cyanobacteria in the Río de la Plata Estuary	Water Resources	Early Adopter: Universidad de la República, Uruguay End Users: Uruguay Ministry of the Environment; Río de la Plata Managing Agency; Ministry of Livestock, Agriculture, and Fisheries; Department of Environmental Development, Municipality of Montevideo	3

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	PI: Fernanda Maciel
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, Spectral top-of-atmosphere radiances from OCI, Rrs, daily PAR, bbp, Spectral phytoplankton absorption coefficients, Spectral non-algal particle plus DOM absorption coefficients, Phytoplankton pigment concentrations, Phytoplankton community composition, Suspended particulate matter, CDOM absorption	PACE OCI will produce highly accurate observations of phytoplankton characteristics & water inherent optical properties enabling separation of bloom types in coastal waters (~1.1 km spatial resolution at nadir) every 1 to 2 days.	Mike Twardowski, Dave Siegel, and Nima Pahlevan	In situ Chla, biovolume of cyanobacteria (total and percentage of total phytoplankton), Chla fluorescence, phycocyanin fluorescence, DOM fluorescence, CDOM absorption, turbidity, particle size distribution, SST, conductivity/salinity, depth, significant wave height, daily discharge of main tributaries, wind speed

Overview

	PI: Joaquim Goes	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Ingest hyperspectral ocean color and aerosol data into Noctiluca specific ocean color algorithms for coastal waters of Oman	Increased prediction of hypoxia and species level HABs (Noctiluca) in Oman, enabling the possibility of not only forecasting fish kill events, but the follow-up analysis of their cause	Water Resources; Ecological Forecasting	Early Adopter: Columbia University End Users: Ministry of Agriculture and Fisheries Wealth, Oman; Ministry of Environment and Climate Affairs, Oman; Desalination plants, Aquaculture, Oil Refineries, Shipbuilding and Tourism companies	7

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	PI: Joaquim Goes
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, Spectral top-of-atmosphere radiances from OCI, spectral phytoplankton absorption coefficients, spectral particle backscattering coefficients, Fluorescence line height, Rrs, Kd, NPP, Phytoplankton pigment concentrations, phytoplankton community composition, Suspended particulate matter, PAR, spectral aerosol optical depth, ocean roughness	PACE OCI will produce highly accurate observations of phytoplankton characteristics and in water constituents enabling identification of bloom types in coastal waters every 1 to 2 days	Heidi Dierssen	SST, SSH, SLA, Outputs from a coupled physical-biogeochemical model (NRL's NCOM-COSiNE; NASA ECCO)

How does climate change impact water-borne pathogens in coastal waters and estuaries?

Overview

	PI: Antar Jutla	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Enhance Vibrio risk models by integrating hyperspectral remotely sensed plankton & plankton health data into algorithms for Florida and the Chesapeake Bay	Better understanding of the relationship between plankton & Vibrio spp. bacteria to improve 1) risk assessment of infections, & 2) improve advisories	Water Resources; Public Health; Ecological Forecasting	Early Adopter: University of Florida End Users: United Nations Office for Coordinator of Humanitarian Affairs; World Health Organization; United Nations International Children's Emergency Fun	4

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	PI: Antar Jutla
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, spectral top-of-atmosphere radiances from OCI, fluorescence line height, NPP, phytoplankton pigment concentrations, phytoplankton community composition	PACE OCI will produce highly accurate observations of phytoplankton characteristics & health in coastal waters every 1 to 2 days	Michael Twardowski; Tim Moore	In situ HAB, Vibrio concentration, molecular/genetics data, SST, salinity, precipitation, nutrient flows, SSH

What role does phytoplankton primary productivity play in the global carbon budget?

Overview

	PI: Dustin Carroll	Application Concept	Application Goal	Category	Host Agency and Potential Users	ARL
		Direct assimilation of hyperspectral satellite observations into the ECCO-Darwin global-ocen biogeochemistry model	Improve estimates of oceanic carbon to better understand the global carbon budget & reduce uncertainty around carbon sources/sinks	Water Resources; Climate	Early Adopter: Moss Landing Marine Labs End Users: ECCO Consortium; Columbia University, California Institute of Technology - Division of Geological and Planetary Sciences	3

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	PI: Dustin Carroll
	Mission Data Product (provisional and test products in italics; view data products table)	Mission Performance Characteristics	SAT Partner	Ancillary Measurements
	Chla, spectral top-of-atmosphere radiances from OCI, fluorescence line height, NPP, phytoplankton community composition, concentration of phytoplankton carbon	PACE OCI is expected to produce hyperspectral observations, including phytoplankton characteristics, for global oceans with a footprint of ~1.1 km every 1-2 days, available within 6-12 hours	Cecile Rousseaux	Global climate model ancillary inputs