Paul Hanson, Fang-Pang Lin, Miron Livny, Chin Wu, Chris Solomon, Many colleagues of the GLEON Transforming ecological sensor networks from data collectors.

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Presentation transcript:

Paul Hanson, Fang-Pang Lin, Miron Livny, Chin Wu, Chris Solomon, Many colleagues of the GLEON Transforming ecological sensor networks from data collectors to knowledge generators

Questions 1.What are the patterns and surprises in sensor data, and what do they tell us about how external drivers influence lake physical, chemical, and biological processes? 2.How do large gradients in geology, hydrology, and climate influence lake responses to external drivers? 3.What are the essential emergent characteristics from lakes that allow us to generalize processes from a few, highly instrumented lakes to regional and global scales?

Time (minutes) GLEON Projected Growth Year Number of data Sandbox threshold (Select, visualize data) Level 1 model threshold (Transformations, simple QA/QC) Level 2 model threshold (0,1-D models) Level 3 model threshold (3-D models) Query time with current system Acceptable thresholds for different tasks. Level 2 models Level 1 models

GLEON Observational Data Repositories Query and display observational data dbBadger Software suite Stream data Web, e.g., dbBadger Mendota buoy LSPA New to this proposal Existing X Y Z Spectral anal. 3D hydrodynamics wavelet Multi-dimensional simulated data repository Surprise anal.

dcoc\simulations\CompareSimulationsMassesFluxes.m Depth (m) Temperature (°C) PAR log 10 (µmol m -2 sec -1 ) A) TBB) SP C) TBD) SP Temperature (°C) PAR log 10 (µmol m -2 sec -1 ) Depth (m) Hanson, Hamilton, Stanley, Langman, Preston in prep. Trout BogSparkling Lake

DIC (mg L -1 ) Chl (µg L -1 ) T (°C) Day of year A) TB epi C) TB hypo E) TB epi G) TB hypo I) TB epi K) TB hypo dcoc\simulations\PlotSeriesWithConfidence.m Day of year B) SP epi D) SP hypo F) SP epi H) SP hypo J) SP epi L) SP hypo Detection band Pulse Day of year How does a large spring pulse of DOC affect other variables?

Morphometry Hydrology, loading Hydrodynamics Physical, chemical processes Landscape setting Microbial processes Higher trophic level processes Predictive uncertainty highlow Meteorology Strong coupling Weak coupling physical chemical biological System level Ecosystem Physical GLEON sites

chlorophyll phycocyanin dissolved oxygen Lake Mendota 2008 July thru Sept hourdayweek Power

10 min scale 60 min scale Phyco Chl DO

Technology will… 1. access large repositories of data, and move data seamlessly through a web of models and repositories; 2.accomplish a complex series of tasks in dependable ways; 3.support the interconnection of models, some of which are extremely compute intensive, in flexible and fast ways; 4.provide on-demand access to GLEON scientists from around the world. This functionality extends existing GLEON technology by leveraging proven workflow and distributed technologies available through Condor and data access, visualization and transport technologies through NCHC.