Regionally tuned algorithms that deliver remotely sensed marine water quality products from the MODIS/Aqua sensor have been developed and validated for the Great Barrier Reef (GBR). Through the eReefs partnership, these algorithms are being transferred from the research domain and being deployed operationally via the national meteorological agency. Furthermore they are being adapted to work with two other ocean colour satellite instruments, SeaWiFS and VIIRS/NPP to enable extension of the monitoring time series, both historically and into the future. The production infrastructure to manage contemporary data flows from the VIIRS sensor is similarly being extended. In parallel, the validated remote sensing products are being integrated into a hydrodynamic and bio-geochemical regional ocean model through data assimilation to provide a holistic suite of monitoring products for the GBR.
This work is being undertaken with the goal of expanding the monitoring to more of Australia's marine jurisdiction. While the remote sensing algorithms themselves are parameterised for the atmospheric and optical characteristics of the GBR region, they are inherently flexible and are progressively being applied and tested in other locations where suitable in situ data are available. The data processing system for the GBR already is nested within the national data production operated by the Integrated Marine Observing System.
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C4.06: Towards continental-scale operational ocean and coastal monitoring using Earth Observation data in Australia - Thomas Schroeder
1. Towards continental-scale operational ocean & coastal
monitoring using Earth Observation data in Australia
… from a CSIRO perspective
Schroeder T., King E., Steven A., Brando V. and Dekker A.
27-28 May 2015 Blue Planet Symposium, Cairns, Australia
CSIRO OCEANS & ATMOSPHERE FLAGSHIP
Image Credit: NASA
Suomi NPP VIIRS
Austral Summer 21 Dec - 20 Mar 2012
2. 2009 Australian Strategic Plan for Earth Observation
from Space (EOS) report
2013 Australia’s Satellite Utilisation Policy
Development National EOS Infrastructure Plan (not released)
2013 Space Coordination Office
2014 National Marine Science Plan Infrastructure
White Paper
Policy context
5. Declining water quality
Coastal developments
Climate change
Fishing
Biodiversity threats
Bleaching
Sea Surface Temperature
Cyclones
Crown of Thorns Starfish
6. Earth Observation (EO) has come a long way
Ever increasing data volumes
Image Credit: NASA
Julius Neubronner German pharmacist - patent 1908
Spy pigeon
8. See also presentations by
Cedric Robillot Wed 27th 15:40
Emlyn Jones Thu 28th 09:30
Mark Baird Thu 28th 10:00
http://www.bom.gov.au/marinewaterquality
“eReefs will provide unprecedented access to an
Integrated system of data, simulation and forecasting
models and visual products that can embedded in
decision making and improve our understanding of
Risks, pressures and responses of the whole
Great Barrier Reef system.”
The eReefs project
9. (Courtesy: Dr Mark Baird & Team)
eReefs - Modeling ocean colour (reflectance)
Data assimilation
Bio-geochemical model
Modeled ocean colour
Satellite
10. Common analytical framework for large volumes
of regular gridded scientific data (PetaBytes)
Uses National Computational Infrastructure
First data set to be transformed into the AGDC is the entire Australasian
Landsat archive (1979-present) – L2 surface reflectance
Flexible architecture - integration of new sensors Sentinel-2,3 MODIS,
MERIS … sensor blending or merging with other data sources e.g. model
outputs etc.
Some AGDC use cases for coastal monitoring: Bathymetry and habitat
mapping e.g. sea grasses, mangroves etc., effect of land-use change on
runoff
The Australian Geoscience Data Cube (AGDC)
Collaboration between GA, CSIRO and the NCI
11. See also presentations by:
Tim Moltmann Wed 27th 11:30
David Griffin Wed 27th 17:55
Helen Beggs Thu 28th 15:45
http://oceancurrent.imos.org.au
Sea Surface Temperature (BoM)
AVHRR
Ocean Colour (CSIRO)
MODIS
Sea Surface Height (UTAS)
Jason-2, Cryosat-2, SARAL, HY-2A
12. IMOS 1 km Product NASA 4 km Product
Comparison IMOS and NASA L3 products
MODIS standard OC3 chlorophyll-a
14. SeaPRISM (7 wavelengths)
Water-leaving radiance
Aerosol optical thickness
Aerosol absorption
Aerosol size distribution
Refractive index
Single scattering albedo
Phasefunction
Water vapor
Spectral flux
Radiative forcing
Weather Station
Temperature
Pressure
Humidity
Dew point
Wind speed etc
Satlantic
Spectral irradiance
Webcams
Sky and Sea
(A)
(A)
(B)
(B)
(B)
(C)
(C)
(D)
(D)
Above-water measurements
15. WetStar fluorometer
CDOM absorption
Chlorophyll-a
Uranine
Phycoeryhrin
WQM
Temperature
Salinity
Depth
Dissolved oxygen
Turbidity
Back scattering
Chlorophyll fluorescence
ACs (80 wavelengths)
Total absorption
Total attenuation
ACs switching unit
(filtered/unfiltered)
BB9 (9 wavelengths)
Back-scattering
DAPCS
Network enabled
real-time data
logger
Automatic winch controller
keeps cage at a constant depth
In-water optical measurements
Fortnightly servicing and water sampling
16. Continental-scale EOS needs …
Growing investment in national coordination, analysis and
dissemination of information from satellites
Long-term sustained funding in in-situ observing systems (Cal/Val),
computing infra-structure (national archiving and processing) and a
network of receiving stations
International engagement (GEO, CEOS, …) directly with space agencies
to secure ongoing access to data streams, Space Coordination Office
Ultimately funding through the NEOS-Infrastructure Plan
All this allows us to address some of the national challenges (e.g.
Marine Nation 2025) and support National Environmental Accounting
(State of the Environment)
17. Opportunities
Provide products beyond a simple chlorophyll-a map – PFTs, primary
productivity, carbon fluxes, particle size, fronts, surrogates, pixel based
error estimates etc. – engage with user community on needs.
New satellite sensors that provide higher spectral, spatial and temporal
resolution data (see detailed sensor list IOCCG web page)
Polar-orbiting – scheduled:
Sentinel-3 (OLCI) ESA/EUMETSAT (Europe) 2015
GCOM-C (SGLI) JAXA (Japan) 2016
EnMAP (HSI) DLR (Germany) 2017 …
Geo-stationary – in orbit:
Himawari-8/9 (AHI) JAXA (Japan), …
18. Himawari-8
See also presentation by:
Keiji Imaoka Thu 28th 14:30
Successfully launched on 7 Oct 2014
Geostationary orbit 140.7°E
JMA plans formal operation mid-2015 as replacement for MTSAT-2
Himawari-8/9 will observe the East Asia and Western Pacific regions
for period of 14 years (H8 2015-2022, H9 2022-2029)
AHI not an Ocean Colour sensor
19. Courtesy: Yasushi Izumikawa
Big data
Approx. 40 GB per day light set
Approx. 188 GB per day full sethttp://www.jma-net.go.jp/mscweb/en/himawari89/index.html
20. Himawari-8
See also presentation by:
Keiji Imaoka Thu 28th 14:30
Successfully launched on 7 Oct 2014
Geostationary orbit 140.7°E
JMA plans formal operation mid-2015 as replacement for MTSAT-2
Himawari-8/9 will observe the East Asia and Western Pacific regions for
period of 14 years (H8 2015-2022, H9 2022-2029)
AHI not an Ocean Colour sensor
Proposed continental-scale non-met applications:
Turbid water mapping (flood plumes), floating algae (Trichodesmium)
linking into BGCM – improve forecasting
Product development in collaboration with Japanese colleagues
Data through BoM at National Computing Infra-structure (NCI)
21. Advantage of GEO vs LEO observations
Enhanced temporal and spatial coverage – full disk swath
(Source: IOCCG Report 12, Image ACRI-ST)
Constellation of 2 LEO sensors One GEO sensor
Example: Percentage of days in December that a pixel can be observed