The Ozone Mapping and Profiler Suite (OMPS) will collect total column and vertical profile ozone data and continue the daily global data produced by the current operational satellite monitoring systems, the Solar Backscatter Ultraviolet radiometer (SBUV/2) and the Total Ozone Mapping Spectrometer (TOMS), but with higher fidelity. The collection of this data will contribute to fulfilling US treaty obligations to monitor ozone depletion for the Montreal Protocol. OMPS has been selected to fly on the National Polar-Orbiting Operational Satellite System (NPOESS) spacecraft - the next generation of polar orbiting environmental satellites. The first OMPS flight unit will fly on the NPOESS Preparatory Project (NPP) spacecraft. On-orbit calibration of the OMPS instruments is critical to maintaining quality data products. A number of signal corrections and calibrations are applied on-board the sensor and in ground processing to account for instrument non-idealities and to convert measured digital signals to calibrated radiances and irradiances. Three fundamental on-orbit calibration measurements are made to provide the required data to perform the radiometric calibration and trending.
The Ozone and Mapping Profiler Suite (OMPS) is an instrument suite in the National Polar-orbiting Operation Environmental Satellite System (NPOESS). The OMPS instrument is designed to globally retrieve both total column ozone and ozone profiles. To do this, OMPS consists of three sensors, two Nadir Instruments and one Limb Instrument. Each OMPS sensor has an End-to-End Model (ETEM) developed using the Toolkit for Remote Sensing, Analysis, Design, Evaluation, and Simulation (TRADES), a Ball Aerospace proprietary set of software tools developed in Matlab. The end-to-end modeling activities, which includes a radiative transfer model, the ETEM, and retrieval algorithms, have three fundamental objectives: sensor performance validation, aid in algorithm development, and algorithm robustness validation. The end-to-end modeling activities are key to showing sensor performance meets the system level Environmental Data Record (EDR) requirements. To do this, the ETEM incorporates sensor data; including point spread functions, stray light, dispersion, bandpass, and focal plane array (FPA) noise parameters. The sensor model characteristics are first implemented with predictions and updated as component test data becomes available. To evaluate the system’s EDR performance, the input radiance derived from the radiative transfer model is entered into the ETEM, which outputs a simulated image. The retrieval algorithms process the simulated image to determine the ozone amount. The system level EDR performance is determined by comparing the retrieved ozone amount with the truth, which was entered into the forward model. Additionally, the ETEM aids the algorithm development by simulating the expected sensor and calibration data with the expected noise characteristics. Finally, the algorithm robustness can be validated against extreme conditions using the ETEM.
One of the objectives of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program is to continue the long-term data set of total column ozone measurements from the Total Ozone Mapping Spectromenter (TOMS) systems while providing the increased accuracy and precision required by the NPOESS Integrated Program Office (IPO). In developing an Ozone Mapping and Profiler Suite (OMPS) sensor-algorithm system to meet the NPOESS requirements, we systematically analyzed the performance of the TOMS system and determined that it provided a strong starting point for the design of the OMPS system. In fact, our analysis showed that modern TOMS systems meet the NPOESS accuracy requirements for retrievals below 475 Dobson Units (DU). However, the NPOESS precision requirements are met only for retrievals below 225 DU. In order to meet the NPOESS accuracy and, particularly, precision requirements for all total column ozone amounts, we identified areas where improvements in the heritage design lead to the improved performance needed for the OMPS system. Simulations performed using the OMPS system design confirm that the algorithm enhancements, coupled with improvements contained in the OMPS sensor, provide performance that meets the NPOESS IPO requirements.
The objective of the NASA Ames Kepler mission is the detection of extrasolar terrestrial-size planets through transit photometry. In an effort to optimize the Kepler system design, Ball Aerospace has developed a numerical photometer model to simulate the sensor as well as stars and hypothetical planetary transits. The model emulates the temporal behavior of the incident light from 100 stars (with various visual magnitudes) on one CCD of the Kepler focal plane array. Simulated transits are inserted into the light curves of the stars for transit detection signal-to-noise ratio analyses. The Kepler photometer model simulates all significant CCD characteristics such as dark current, shot noise, read out noise, residual non-uniformity, intrapixel gain variation, charge spill over, well capacity, spectral response, charge transfer efficiency, read out smearing, and others. The noise effects resulting from background stars are also considered. The optical system is also simulated to accurately estimate system optical point spread functions and optical attenuation. In addition, spacecraft pointing and jitter are incorporated. The model includes on-board processing effects such as analog-to-digital conversion, photometric aperture extraction, and 15-minute frame co-addition. Results from the model exhibit good agreement with NASA Ames lab data and are used in subsequent signal-to-noise ratio analyses to assess the transit detection capability. The reported simulations are run using system requirements rather than predicted performance to guarantee that mission science objectives can be attained. The Kepler Photometer Model has given substantial insight into the Kepler system design by offering a straightforward means of assessing system design impacts on the ability to detect planetary transits. It is used as one of the various tools for the establishment of system requirements to ensure mission success.
Polar sea ice plays an important role in the global climate and other geophysical processes. Although spaceborne scatterometers such as NSCAT have low inherent spatial resolution, resolution enhancement techniques can be utilized to make NSCAT data useful for monitoring sea ice extent in the Antarctic. Dual polarization radar measurement parameters, A and B, are used to identify sea ice and ocean pixels in composite images where A is (sigma) <SUP>o</SUP> normalized to 40 degrees and B is the incidence angle dependence of (sigma) <SUP>o</SUP>. In particular, the copol ratio and the vertical polarization B values contain useful information about the presence of sea ice. A first estimate of the sea ice extent is obtained through an automated linear discrimination that assigns the decision boundary based upon the properties of the bivariate distribution. This is used to obtain estimates of the statistics needed to perform a more accurate Mahalanobis distance discrimination. Ice edge detection noise reduction is performed through region growing and erosion/dilation techniques. The algorithm is applied to NSCAT data. The resulting edge closely matches the NSIDC SSM/I derived 30 percent ice concentration edge.