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Access to Information • Public availability of key documents • Mission and instrument descriptions • Algorithm Theoretical Basis Documents (ATBDs) • Data Catalogues and data set examples • Data Quality Summaries • Open and advertised A-Train Data Policy • Open and advertised Science Team meetings • Public availability of Level 1 and 2 data products soon after start of operations (beta or provisional data quality) • Better to keep data formats simple • Near real-time access • Creation of fused data sets (slow to develop for A-Train) Example - initial data release for CALIPSO & CloudSat within first 6 months
Open Validation • Sustained calibration and validation efforts • Formulation of pre-launch plans • Data processing effort includes iterative processing to capitalize on improved calibration/validation approaches • Committed funding from sponsoring agencies • Coordinated comparison field missions • Optimizes resources (instruments, aircraft, ground systems) • Brings more eyes to a set of issues • Promotes additional interest • Independent assessments Example – ozone trend studies in late 1980: TOMS, SBUV, SAGE, HALOE, NDSC Example – Cirrus optical thickness: CALIPSO lidar and IIR, MODIS, PARASOL, CloudSat, in situ measurements, CPL
Page 1 and 2: A-Train formulation with the arriva
Page 3 and 4: A-Train science is having an profou
Page 6 and 7: Selected highlights with a little i
Page 8 and 9: A-Train demonstrated how formation
Page 10 and 11: Example of combining data CloudSat,
Page 12 and 13: The classic Riehl and Malkus “hot
Page 14 and 15: Buoyancy Entrainment rate ΔT = T p
Page 16 and 17: A-Train reveals important insights
Page 18 and 19: Aerosol effects on clouds - largest
Page 20 and 21: The more global picture from the A-
Page 22 and 23: A- Train Precipitation
Page 24 and 25: MODIS Insight on the rain process -
Page 26 and 27: Global Precipitation - combining di
Page 28 and 29: Summary (i) New science continues t
Page 31 and 32: Comparison of level 2 products Asse
Page 33 and 34: CloudSat-CALIPSO-AMSR-E data docume
Page 35 and 36: Multi-sensor fusion - new insights
Page 37 and 38: Access to Information • Public av
Page 39 and 40: NASA A-Train member missions NASA E
Page 41 and 42: Sensor data used A-Train What is pr
Page 43 and 44: A-Train Science Concepts 4 slides f
Page 45: Leadership • Mission leads (Princ
Page 49 and 50: Identifying core cloud Tested sever
Page 52 and 53: A-Train Constellation Evolution Aqu

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