Center for Atmospheric & Space Sciences Data Assimilation, Infrastructure Issues, and International Collaboration R.W. Schunk Center for Atmospheric & Space Sciences Utah State University Logan, Utah 84322 DASI Workshop June, 2004

Large Data Sets Require Data Assimilation Models to Maximize the Science

Global Assimilation of Ionospheric Measurements (GAIM) R. W. Schunk, L Global Assimilation of Ionospheric Measurements (GAIM) R.W. Schunk, L. Scherliess, J.J. Sojka & D.C. Thompson We use a physics-based ionosphere-plasmasphere-polar wind model as a basis for assimilating a diverse set of real-time (or near real-time) measurements. GAIM provides both specifications and forecasts on a global, regional, or local grid. Global Regional Local

GAIM Assimilates Multiple Data Sources Bottomside Ne Profiles from Ionosondes In Situ DMSP Satellite Measurements Ground-Based GPS TECs TECs Between Ground Stations and Low-Earth-Orbiting Satellites With Radio Beacons Satellite Occultation Data Line-of-Sight UV Emissions from DoD Satellites The Data Must be Real-Time or Near Real-Time.

Data Assimilated Exactly as They Are Measured Bottomside Ne Profiles from Digisondes. Slant TEC Ne Along Satellite Tracks Integrated UV Emissions Etc. Modular Construction. Data Quality Algorithms Needed

GAIM Output Continuous Reconstruction of Global Ne Distribution Ionosphere-Plasmasphere-Polar Wind 90-30,000 km Quantitative Estimates of the Accuracy of Reconstruction Auxiliary Parameters NmF2, hmF2, NmE, hmE Slant and vertical TEC Model Drivers High-Latitude Convection and Precipitation Low-Latitude Electric Fields Global Neutral Winds Global Neutral Composition

Data Distribution 080/2002/00:30UT

Sample orbits tracks and occultation locations IOX SAC-C CHAMP Sample orbits tracks and occultation locations

Gauss-Markov Kalman Filter Example November 16, 2003 GPS Ground TEC measurements from more than 900 GPS Receivers (from SOPAC Data Archive) Includes Receivers from: IGS CORS EUREF and others

Gauss-Markov Kalman Filter Reconstruction Climate Kalman Filter More than 3000 Slant TEC Measurements are assimilated every 15 minutes.

Reconstruction of the 3-D Ne Distribution

Are There Enough Data Available to Make Data Assimilation Useful?

NOAA CORS Data • 332 Sites • Dual-frequency Receivers • Slant TEC

Japan GPS Receivers of the Earth Observation Network Dual-Frequency 1000 Receivers (25 km separation) 5000 Satellite-Receiver Paths Every 30 Seconds 12,000,000 Paths/Day Slant TEC

SOPAC Online Map Interface http://sopac.ucsd.edu/cgi-bin/smi

Operating Incoherent Scatter Radar Facilities Jicamarca Arecibo Millstone Hill Kharkov Irkutsk Sondrestrom EISCAT - Tromso EISCAT - Svalbard

Data Sources Ionosondes (>100 Stations) Global GPS Network (>100 Receivers) NOAA CORS GPS Network (400 Receivers) Japan GPS Network (1000 Receivers) SUOMI GPS Network (100 Receivers) FAA-WAAS Network (24 Nodes) 2000 GPS Sites Worldwide (SOPAC Network) DMSP Polar Satellites C/NOFS Equatorial Satellite TOPEX Ocean-Sensing Satellite COSMIC Satellites (3000 Occultations/Day) Geostationary High-Resolution Ionospheric Imagers Magnetometer Network (>1000 Stations) Incoherent Scatter Radar Network SuperDARN Radars Fabry-Perot Optical Network

DASI ISSUES Many of the instrument arrays are spread around the world. The international community should participate in DASI. Funding is needed for a U.S. scientist to coordinate this effort. Data assimilation models not only require data, but the data errors as well. International standards need to be established for ‘errors’ for each data type. Funding is needed for a U.S. scientist to coordinate this effort. Funding is needed to develop and maintain data assimilation models.

Not all scientific studies require real-time measurements and many experimentalists will not be able to provide their data in real time. Therefore, two time windows should be considered ==> Real-time 48 - hours