2000: Student Polarimeter Aerosol and Cloud Experiment (SPACE)

Demonstrate the SPACE team's capability to support mission operations activities dealing with the storage of raw data (level-0) and the next processed data stage (level-1). Demonstrate the SPACE team's capability to contribute to field campaigns utilizing a ground-based network of sunphotometers, polarimeter and Lidar instruments to retrieve aerosol data for satellite ground truth and environmental studies concerning the spatial (vertical and horizontal) variability and concentration of aerosol.

Research Objectives

Design and develop a mission operations facility at CCNY, including a staged database structure to support Level-0 and Level-1 data formats and communications capabilities with ISS at Marshall Space Flight Center.

Conduct a three-week field campaign that produces a data stream from stationary and mobile instruments at locations in New York City and in Black Rock Forest. Required data stream consists of the following instruments - Lidar and sunphotometer instruments on the CCNY mobile van, sunphotometers based at Medgar Evers College and GISS and a polarimeter based at LaGuardia Community College.

Derive a quantitative estimate of aerosol variability for New York City in comparison to a nearby rural locale Black Rock Forest to demonstrate capability to contribute to SPACE environmental research objectives.

Develop capability to compare SPACE field campaign data with satellite retrievals to contribute to SPACE ground truth requirements.

Tasks and Responsible Researchers

Medgar Evers Team

Determine the reasons why the MEC sunphotometer is not producing a data stream, trouble-shoot these problems. Document the problems, status and solutions in a team log to demonstrate team's technical oversight capability. Set up and implement protocols for monitoring data stream and quality.

Produce a week of "good" MFRSR data, July 1-7. Work with the GISS team to assess data.

Obtain the College of Staten Island sunphotometer and bring to GISS for summer research activities.

Participate in a field campaign conducted July 10th to July 28th, contributing a continuous data stream from GISS and MEC, with the CSI instrument running side-by-side with GISS instrument. Have team reps contribute to the Black Rock field measurements, collecting aerosol data with the CSI sunphotometer.

Conduct analysis to assess data quality for contributing to SPACE field campaign science objectives. Correlate the data collected from the three MFRSRs: GISS, MEC and CSI. Are ozone estimates consistent? How do aerosol size, optical depth and water vapor column burden compare? Are there significant differences on this 10km spatial scale?

Prepare written documentation describing each instrument in the MEC Environmental Science Lab (including: the variable measured, temporal/spatial scale, data accuracy). Can these instruments make a viable contribution to the identification of aerosol sources?

LaGuardia Team

Work with the CCNY team on the R&D of more durable hand-held polarimeter design, as well as its integration with a minispectrometer.

Determine and document the protocols for hand-held polarimeter measurements in SPACE field campaigns.

Participate in the SPACE field campaign (July 10th to July 28th), contributing a daily data stream from the polarimeter (old and new design) based at LaGuardia CC, whenever there are clear skies.

Develop calibration protocol and apply it to the calibration of the two polarimeter designs. Typically use stacked polaroids for test of instrument capabilities to measure high polarization scenes and use tilted piece of float glass for test of instrument capabilities to measure weak polarization scenes.

Using this calibration as a basis for an instrumental accuracy estimate, determine how well the refractive index of aerosols can be estimated from handheld polarimetry when measurements are made in conjunction with sunphotometry.

Develop, test and document web-based programs to retrieve, store and manipulate polarimeter data collected. Include capability to use correlative sunphotometer (e.g. MFRSR) data to constrain aerosol model retrieval.

CCNY Team

Field Studies

1. Equip the Mobile Environmental Monitoring Lab (MEMLab) with 2 and 3 wavelength Mie LIDAR. Conduct and document tests to evaluate and demonstrate the effective operation of the LIDAR instruments in MEMLab and in the Optical Remote Sensing Lab.
2. Prepare a schedule and team assignments for the mobile van field campaign activities (July 10-28). Request that Jeff Steiner's air sampler be included in the field campaign. Plan to take measurements in Black Rock Forest July 20-21.
3. Develop and implement inversion algorithms that effectively synthesize the data from Lidars and sunphotometers.
4. Coordinate the analysis of all field campaign data among participants.
   1. Examine gradients of aerosol properties using GISS, MEC and Black Rock Forest and Queensbury to provide differential spatial scales of 10, 50 and 200km. On what spatial scale do the aerosol properties become decorrelated? Is this scale the same for size, mass loading and water vapor, or do they each have their own spatial scale? Identify aerosol sources and relationships to concentration and optical properties..
   2. Work with the GISS team to study how MFRSR, Lidar and handheld multispectral data can be compared with aircraft and satellite data. Develop tools to implement such a comparison during a fall field campaign using an aircraft mounted version of the SPACE polarimeter
   3. Work with the GISS team to assess the accuracy of retrievals and their ability to address the SPACE science objectives of an accurate estimate of aerosol radiative forcing and the components that contribute to it and the ability to perform regional environmental research and assess aerosol transports accurately.

Mission Operations

1. Set up mission operations site with capability to design and test data storage and communications capabilities with SPACE partners and ISS ground station at Marshall Space Flight Center. Begin to build a Unix and NT network environment.
2. Design, construct and evaluate a staged database to store Level-0 (raw data) and Level-1 (next stage data) data formats. Determine speed of data upload, evaluate ability to recover from network outages and decide on form which data backups will take and where data backups will be located (e.g. GISS and CCNY, or different CCNY buildings).
3. Design schema and index designs for higher order (above Level-1) data integrations using aircraft data as a basis for the design.
4. Develop an in-depth understanding of ISS data acquisition protocols/requirements. Conduct/document data transmission/processing trials to test the development of CCNY's Oracle 8i parallel database environment.
5. Learn the orbital software package. Develop skills needed to utilize the orbital software package for the following mission operations activities: a) locating the ISS, b) geolocating data, c) propagate orbit forward in time d) include ISS platform perturbations (pitch, roll and yaw) in data geolocation.

GISS Team

Development of sunphotometer analysis package to study O₃ and NO₂

Participate in SPACE field campaign (July 10-28), contributing MFRSR measurements.

Derive an estimate of the aerosol radiative forcing based on the field campaign measurements from polarimeters, sunphotmeters and Lidar. Define how different measurements contribute to deriving this estimate -- what are their specific constraints on the radiative forcing of aerosols.

Team Products

The following products will be evaluated for their potential use in preparing a case study to include in the SPACE Concept Study to demonstrate the team's capability to conduct mission operations and field campaigns

1. A field campaign report, including protocols, data analysis and assessments, technical logs on instrument trouble-shooting capabilities. Include MEC Environmental Sciences Lab instrument documentation.
2. Mission operations report, including: documentation of database design and evaluation, CCNY - ISS communications, status of mission operations facility set-up.