Aircraft Remote Sensing in Chesapeake Bay Larry Harding Horn Point Laboratory University of Maryland Center for Environmental Science NOAA Coastal Services.

Slides:



Advertisements
Similar presentations
REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales.
Advertisements

Lesson 12: Technology I Technology matters Most of the topics we’ve learned so far rely on measurement and observation: – Ocean acidification – Salinity.
Large-scale Satellite Oceanography in Eastern Pacific Upwelling Regions Andrew Thomas University of Maine Recent manuscript collaborators: Jose Luis Blanco,
U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis U.S. ECoS Science Team* ABSTRACT. The U.S. Eastern Continental.
Evaluation of Trends in Chlorophyll-a Concentration in Response to Climatic Variability in the Eastern Bering Sea from MODIS Puneeta Naik a,b and Menghua.
OMSAP Public Meeting September 1999 The Utility of the Bays Eutrophication Model in the Harbor Outfall Monitoring Program James Fitzpatrick HydroQual,
CBEO Year 3 Planning Rebecca Murphy Dec. 9, 2008.
NRL 7343 Nov’97 Seasonal Variability of the surface bio-optical and Thermal Structure of the Japan/East Sea Using AVHRR and SeaWIFS Robert ArnoneRichard.
Jason Hopkins Post doctoral researcher
Temporal scales of coastal variability and land-ocean processes J. Salisbury, J. Campbell, D. Vandemark, A. Mahadevan, B. Jonsson, H. Xue, C. Hunt.
Temporal and Spatial Variations of Sea Surface Temperature and Chlorophyll a in Coastal Waters of North Carolina Team Members: Brittany Maybin Yao Messan.
Organic Matter Metabolism in a Coastal Ocean Ecosystem Patricia Matrai Mike Sieracki Nicole Poulton Carlton Rauschenberg Bigelow Laboratory for Ocean Sciences.
Abbie Harris - NOAA Ocean Acidification Think Tank #5 Current and Future Research at the Institute for Marine Remote Sensing Abbie Rae Harris Institute.
UNH Coastal Observing Center NASA GEO-CAPE workshop August 19, 2008 Ocean Biological Properties Ru Morrison.
SST Diurnal Cycle over the Western Hemisphere: Preliminary Results from the New High-Resolution MPM Analysis Wanqiu Wang, Pingping Xie, and Chenjie Huang.
Combining Observations & Numerical Model Results to Improve Estimates of Hypoxic Volume within the Chesapeake Bay JGR-Oceans, October 2013 issue Aaron.
Coastal Water Quality Remote Sensing Welcome Dr. Jeff Payne Deputy Director NOAA Coastal Services Center October 7, 2003.
Climate-driven Trends in Contemporary Ocean Productivity Michael Behrenfeld Oregon State University Robert O’MalleyJorge SarmientoWayne Esaias Don SheaGene.
Transitioning a Chesapeake Bay Ecological Prediction System to Operations January 24, 2012 D. Green 1, C. Brown 1, F. Aikman 1, A. Siebers 1, H. Tolman.
Isaac (Ike) Irby 1, Marjorie Friedrichs 1, Yang Feng 1, Raleigh Hood 2, Jeremy Testa 2, Carl Friedrichs 1 1 Virginia Institute of Marine Science, The College.
Monitoring for Restoration Ocean Leadership 2012 Public Policy Forum The Science of Ocean, Coastal, and Great Lakes Restoration W. C. Boicourt University.
Isaac (Ike) Irby 1, Marjorie Friedrichs 1, Yang Feng 1, Raleigh Hood 2, Jeremy Testa 2, Carl Friedrichs 1 1 Virginia Institute of Marine Science, The College.
Considerations for future remote sensing activities Edward D. Santoro, M.S. Monitoring Coordinator Delaware River Basin Commission
Ship-board radiometric measurements of the air-sea temperature difference P. J. Minnett, A. Chambers & N. Perlin Rosenstiel School of Marine and Atmospheric.
Modeling Support for James River Chlorophyll Study Dave Jasinski, CEC Jim Fitzpatrick, HDR|HrydroQual Andrew Parker, Tetra Tech Harry Wang, VIMS Presentation.
GHRSST, V1, CGMS 41 July 2013 Coordination Group for Meteorological Satellites - CGMS Add CGMS agency logo here (in the slide master) Coordination Group.
Harmful Algal Blooms A marine ecosystem manager is interested in using satellite and ocean model products to find precursors for the determination of harmful.
Little Diomede Island, Bering Strait BERING STRAIT THROUGHFLOW ARC Comparison of Water Properties and Flows in the U.S. and Russian Channels of.
1 Suborbital Science Program Airborne Remote Sensing of the SF Bay NASA Ames Research Center University of California Santa Cruz Airborne Science & Technology.
SeaWiFS Highlights February 2002 SeaWiFS Views Iceland’s Peaks Gene Feldman/SeaWiFS Project Office, Laboratory for Hydrospheric Processes, NASA Goddard.
Imagery.
Predicting right whale distributions from space Andrew J. Pershing University of Maine/ Gulf of Maine Research Institute.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Presented by Menghua Wang.
Ocean Color Remote Sensing Pete Strutton, COAS/OSU.
U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis U.S. ECoS Science Team* ABSTRACT. The U.S. Eastern Continental.
Optical Water Mass Classification for Interpretation of Coastal Carbon Flux Processes R.W. Gould, Jr. & R.A. Arnone Naval Research Laboratory, Code 7333,
Gulf of Mexico Primary Productivity Estimates of NPP based on NASA Satellite data.
An analysis of Russian Sea Ice Charts for A. Mahoney, R.G. Barry and F. Fetterer National Snow and Ice Data Center, University of Colorado Boulder,
Estimating Sea Surface Salinity in the Chesapeake Bay From Ocean Color Radiometry Measurements Christopher W. Brown 1 and Ronald L. Vogel 2 1 NOAA/NESDIS.
Further information Results 19 tournaments surveyed : 415 interviews; 579 fishing locations; 1,599 fish hooked/landed Variable.
2006 OCRT Meeting, Providence Assessment of River Margin Air-Sea CO 2 Fluxes Steven E. Lohrenz, Wei-Jun Cai, Xiaogang Chen, Merritt Tuel, and Feizhou Chen.
Relationship Between Cholera and Ocean Net Heat Flux in the Bay of Bengal By Erin James Department of Geography University of California, Santa Barbara.
NRL 7343 Nov’97 Remote Sensing in the Japan East Sea Robert ArnoneRichard Gould Chistine Chan Sherwin Ladner Naval Research Laboratory Stennis Space Center.
NOAA/NOS/OCS/Coast Survey Development Laboratory Lyon Lanerolle 1,2, Richard Patchen 1 and Frank Aikman III 1 1 National Oceanic and Atmospheric Administration.
Suhung Shen James G. Acker Denis Nadeau George Serafino Goddard Earth Sciences (GES) Data and Information Services Center (DISC) Distributed Active Archive.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Characterization of Global Ocean Turbidity from MODIS Aqua Ocean Color.
Goal: to understand carbon dynamics in montane forest regions by developing new methods for estimating carbon exchange at local to regional scales. Activities:
Robert M. Hirsch, Research Hydrologist, USGS September 6, 2012 Nitrogen, Phosphorus, and Suspended Sediment fluxes from the Susquehanna River to the Bay.
ISAC Contribution to Ocean Color activity Mediterranean high resolution surface chlorophyll mapping Use available bio-optical data sets to estimate the.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Satellite Observation and Model Simulation of Water Turbidity in the Chesapeake.
State Agency Needs for Remote Sensing Data Related to Water Quality By Bob Van Dolah Marine Resources Research Institute South Carolina Department of Natural.
NRL 7333 Rb = 1-  1+  1+  2 Non- Linear b1- b2q3 influences We developed improved SeaWIFS coastal ocean color algorithms to derived inherent optical.
Giovanni and LOCUS: Innovative Ways for Teachers and Students to Conduct Online Learning and Research with Oceanographic Remote Sensing Data James G. Acker.
Coastal Optical Characterization Experiment (COCE) Activities at STAR NOAA 2013 Satellite Conference, April 7-12, 2013 M. Ondrusek,
CIOSS Ocean Optics Aug 2005 Ocean Optics, Cal/Val Plans, CDR Records for Ocean Color Ricardo M Letelier Oregon State University Outline - Defining Ocean.
Smithsonian Environmental Research Center. Temporal Changes in SAV Coverage Total # of Species Total No. of All Species Eurasian Watermilfoil Dominant.
TS 15 The Great Salt Lake System ASLO 2005 Aquatic Sciences Meeting Climatology and Variability of Satellite-derived Temperature of the Great Salt Lake.
A Net Primary Productivity Algorithm Round Robin (PPARR) for the Arctic Ocean: A brief introduction to the PPARR 5 adventure Patricia Matrai 1, Yoonjoo.
Incorporating Satellite Time-Series data into Modeling Watson Gregg NASA/GSFC/Global Modeling and Assimilation Office Topics: Models, Satellite, and In.
Ocean Sciences The oceans cover 3/4 of the Earth’s surface. They provide the thermal memory for the global climate system, and are a major reservoir of.
Remote Sensing of the Ocean and Coastal Waters
NASA/US Ocean Satellite Missions
Sea Surface Temperature as a Trigger of Butterfish Migration: A Study of Fall Phenology Amelia Snow1, John Manderson2, Josh Kohut1, Laura Palamara1, Oscar.
GOES-R Resources from NOAA, NASA & CIMSS
Validation of Satellite-derived Lake Surface Temperatures
Coastal CO2 fluxes from satellite ocean color, SST and winds
Michael, B. D. , Trice, T. M. , Heyer, C. J. , Stankelis, R. M
D. Green1, C. Brown1, F. Aikman1, A. Siebers1, H. Tolman1, M. Ji1, D
Space and time scales in satellite oceanography
Generation of Simulated GIFTS Datasets
Presentation transcript:

Aircraft Remote Sensing in Chesapeake Bay Larry Harding Horn Point Laboratory University of Maryland Center for Environmental Science NOAA Coastal Services Center Charleston, South Carolina 7 October 2003

History of Program Started in 1988 with NASA Ocean Data Acquisition System (ODAS) on test flights in collaboration with NASA, NOAA and CBP; Spring-summer flight series began in 1989; spring-fall flight series began in 1990 and now extends through 2003; Initial goal was to better define spatial and temporal extent of the winter-spring diatom bloom and of summer dinoflagellate blooms; Developed regional algorithms using a combination of aircraft and shipboard data to recover surface chlorophyll (chl-a), temperature (SST) and integrated, water-column chlorophyll as a measure of phytoplankton biomass; Introduced SAS II in 1995 and SAS III in 1997, replacing ODAS with more capable instruments; Web page ( launched in spring 2001 containing complete imagery from ODAS, SAS II and SAS III flights on the main stem Bay for , and from Choptank and Patuxent river flights,

Effect of freshwater flow from the Susquehanna R. on the magnitude and position of the spring diatom bloom

Freshwater flow from the Susquehanna R. during LMER TIES ( ); cumulative flow volumes show 1996 had significantly higher flow than other years in the recent record Year

Aircraft Piper Aztec Cessna Skyhawk Main stem Bay Tributaries

Instrumentation SeaWiFS Aircraft Simulator (SAS III) (Satlantic, Inc.) for measurements of ocean color to determine chlorophyll con- centrations; Infrared Thermometer (Heimann Instruments, Inc.) to measure sea surface temperature.

Chesapeake Bay main stem flight tracks

Comparison of shipboard, satellite and aircraft recoveries of chl-a for matching dates in 1998

Pre- and post- Isabel flights, September, 2003

CBPM-1 and CBPM-2 recoveries of gross PP for LMER TIES data, CBPM models are multiple regression DIMs in logarithmic space, using the “usual” suspect variables of this lineage of models

Comparison of PP from LMER TIES cruises in 1999 with PP from CBPM-2 applied to merged aircraft/ shipboard data for the lower Bay

Develop models of AIP based on TN/TP loading using AIP data from CBPM-2 applied to merged aircraft/shipboard data; Satellite chl-a retrievals from SeaWiFS ocean color measurements offer the advantage of synopticity and are increasingly accurate for Case II waters exemplified by Chesapeake Bay; Use these products as inputs to CBPM-2 in the same way we have with ODAS, SAS II and SAS III products; Generate time-series of chl-a and PP from spatially-explicit model outputs to improve the data underlying computations of AIP; Build on early success with the use of winter-spring TN and TP loading to predict AIP with aircraft- and satellite-derived products that have much improved spatial and temporal resolution. So, where do we go next?

Summary 1.Phytoplankton biomass and primary productivity (PP) in Chesapeake Bay are highly variable, both spatially and temporally; 2.Variability on seasonal to inter-annual time scales is strongly coupled to winter-spring fresh-water flow; 3.Ocean color measurements from aircraft provide data that can be used with shipboard observations to estimate PP at high resolution.

Acknowledgments Mike Mallonee, Tom Fisher, Blanche Meeson, Sam White, Wayne Esaias, Eric Itsweire, Elgin Perry, Christy Jordan, Jason Adolf, Dave Miller, Kathleen Cone, Andrea Magnuson, Tom Malone, Mike Lomas, Janet Campbell, Jim Cloern, Ed Houde, Mike Roman, Bill Boicourt, the captains and crews of the R/V Ridgely Warfield, Cape Hatteras, and Cape Henlopen, and pilots of Aerosource and Airborne. Also – NASA, NSF, NOAA, Maryland Sea Grant, and EPA for grant support.