Transcript Document
Integrating Satellite Data with Ecosystem Models
Progress & Prospects
Ramakrishna Nemani Petr Votava Andy Michaelis Forrest Melton Hirofumi Hashimoto Weile Wang Cristina Milesi Sam Hiatt NASA Ames Research Center Moffett Field, CA Global Vegetation Workshop, Missoula, MT, June 24, 2009
outline Need for integrating satellite data into ecosystem models Retrospective to near-realtime integration Drowning in data: From data-poor to a data-rich environment Building community focused data - modeling centers
Integrated, Multiple Constraints on the Biosphere 1000 km Upscaling Prediction 10 km 1km 1ha 1m Downscaling Verification
Original FOREST-BGC flow diagram, emphasizing dual time steps, critical role of LAI, C-H2O-N interactions, and remote sensing applications, 1988
no LAI spoken here…
First? spatial ecosystem model driven by remote sensing Two weather stations One AVHRR scene Two years after acquisition 24 hours to run the model Less than 1500 km 2 Running et al. Ecology 1989
Retrospective to Real time
Key elements: Monitoring Modeling Forecasting Local to Global Nemani et al., RSE, 2008
Raw data
Daily Weather Surfaces 1
KM Gridded Products TMAX TMIN Humidity Rainfall Sunshine
Satellite data
1/05 2/05
California : Ecological Daily Nowcast at 1km Climate + Satellite [Feb/01/2006] Carbon and water cycles
T P RAD
Biome-BGC Simulation models
GPP ET 0 2.5
GPP (gC/m2/d) ET (mm/d) 5 Outputs include plant growth, irrigation demand, streamflow
Meteorology Daily Nowcasts: California Hydrology Vegetation Ecosystem
Ensemble Model Experiments TOPS BGC CASA LPJ BEAMS SimCYCLE More
* Data sets are available at the TOPS website: ( http://ecocast.arc.nasa.gov
)
Wang, Michaelis, Dungan
Near realtime monitoring of global NPP anomalies Mapping changes in global net primary production near real-time depiction of the droughts in the Amazon and Horn of Africa, May 2005
Running et al., 2004, Bioscience, 54:547-560
Irrigation Forecasts Irrigation Forecast for week of July 19-26, 2005 Tokalon Vineyard, Oakville, CA
CIMIS Measured Weather Data through July 18, 2005 NWS Forecast Weather Data July 19-26, 2005 0 30 Forecast Irrigation (mm) Seasonal 0 meters 1000
N
Fully automated web delivery to growers
Drowning in Data
Less than 10 years ago, modelers spent nearly 90% of their time gathering appropriate data Now the DAACs distribute about 4TB a day Global data at 8km, 1km, 500m, 250m and 30m
From data to knowledge/decisions
Limitations of Current Standard Practice •
Data volume:
Long term analyses of climate and ecosystem change increasingly require retrieval and processing of multiple terrabytes of data from a diversity of models and sensors. •
Bandwidth:
As the growth in bandwidth begins to flatten, transmission of data from centralized data archives presents an increasing challenge. •
Data management costs and redundant storage and processing:
Costs associated with local storage and management of data and compute resources add significant costs to individual research and application development efforts. >$100k/year
Proposed solution
Community-focused data-modeling centers (bring your code to the data)
Proposals solicited for 50 of $400M for NASA Earth Sciences Prototyping exercise, funded as part of the stimulus activity Possibly matching funds from CISCO
Proposed Data Modeling Center
What will it have 2 x 512 core CPUs 2 PB disk storage Data: MODIS, AVHRR, LANDSAT… Models: publicly available codes Software Utilities: public domain Web Portal
How will it work?
Generalized Disturbance Index
Mildrexler et al 2006
Mildrexler et al 2006
Gaining access
Users register Only registered users can request project resources Project Request Template A one page summary of proposed work Requested Datasets Spatial subset Temporal subset Requested models Requested utilities Estimated CPU hours Length of time the resources are requested for
We're working on licensing issues for commercial packages
Create virtual environment
Allocate computing resources Allocate disk space Make available all requested data sets Create a project page on the Social Network
User gains access
Shell access Can bring their own models Can bring their own data Run and modify their algorithms Publish results and share them with other researchers Save their environment (data, algorithms etc.) for future re-use and reproducibility of results
This environment can be shared with other people
Resources get recycled If desired, captured knowledge is archived Environment Results Data Models Clean-up
Social networking component
Search for related work Who's doing what where Map interface Categorized by discipline Categorized by geographic region Create your own project Control the visibility of your project Control the access to your project Control level of sharing Link to other projects Add publications
A prototype will be ready in Spring 2010 Available first to NASA Centers NASA funded researchers then to the rest of the community
Phasing access