To track the degradation of the Imager visible channel on board NOAA’s Geostationary Operation
Environmental Satellite (GOES), a research program has been developed using the stellar observations
obtained for the purpose of instrument navigation. For monitoring the responsivity of the visible channel, we
use observations of approximately fifty stars for each Imager. The degradation of the responsivity is
estimated from a single time series based on 30-day averages of the normalized signals from all the stars.
Referencing the 30-day averages to the first averaged period of operation, we are able to compute a relative
calibration coefficient relative to the first period. Coupling this calibration coefficient with a GOES-MODIS
intercalibration technique allows a direct comparison of the star-based relative GOES calibration to a
MODIS-based absolute GOES calibration, thus translating the relative star-based calibration to an absolute
star-based calibration. We conclude with a discussion of the accuracy of the intercalibrated GOES Imager
visible channel radiance measurements.
Monitoring the responsivities of the visible channels of the Imagers on GOES satellites is a continuing effort at the National
Environmental Satellite, Data and Information Service of NOAA. At this point, a large part of the initial processing of the
star data depends on the operationalGOES Sensor Processing System(SPS) and GOES Orbit and AttitudeTracking System
(OATS) for detecting the presence of stars and computing the amplitudes of the star signals. However, the algorithms of
the SPS and the OATS are not optimized for calculating the amplitudes of the star signals, as they had been developed to
determine pixel location and observation time of a star, not amplitude. Motivated by our wish to be independent of the SPS
and the OATS for data processing and to improve the accuracy of the computed star signals, we have developed our own
methods for such computations. We describe the principal algorithms and discuss their implementation. Next we show our
monitoring statistics derived from star observations by the Imagers aboard GOES-8, -10, -11, -12 and -13. We give a brief
introduction to a new class of time series that have improved the stability and reliability of our degradation estimates.
Monitoring the responsivities of the visible channel of the Imagers on operational GOES satellites is a continuing effort
at NOAA. To estimate the rate of degradation of the responsivity, we have been analyzing the time series of star signals
measured by the Imagers for attitude and orbit determination. In this report, we begin by showing our latest results of
monitoring of the responsivities of the visible channels of GOES-8, GOES-9, GOES-10, GOES-11, GOES-12, and
GOES-13. One complicating factor in the analysis has been the presence in the time series of an annual cycle that
modulates the gradual long-term degradation whose rate we are trying to infer. We describe a method we are developing
to reduce the influence of the annual cycle on the analysis. The method enables us to include in the analysis the star
observations near local midnight, which had been excluded in the past to prevent loss of accuracy in the derived long-term
degradation rate. With a fuller set of data, we can subdivide the data within each year into 48 bins and estimate the
degradation separately in each bin, thereby reducing the influence of the annual cycle on the derived degradation rates.
One indication that the method is valid is that the degradation rates estimated in all the bins are consistent.
Stars are regularly observed in the visible channels of the GOES Imagers for real-time navigation operations. However, we
have been also using star observations off-line to deduce the rate of degradation of the responsivity of the visible channels.
We estimate degradation rates from the time series of the intensities of the Imagers' output signals when viewing stars,
available in the GOES Orbit and Attitude Tracking System (OATS). We begin by showing our latest results in monitoring
the responsivities of the visible channels of the Imagers on GOES-8, -9, -10, -11 and -12. Unfortunately, the OATS
computes the intensities of the star signals with approximations suitable for navigation, not for estimating accurate signal
strengths, and thus we had to develop objective criteria for screening out unsuitable data. With several layers of screening,
our most recent trending method yields smoother time series of star signals, but the time series are populated by a smaller
pool of stars. With the goal of simplifying the task of data selection and to retrieve stars that have been rejected in
the screening, we tested a technique that accessed the raw star measurements before they were processed by the OATS.
We developed formulations that not only produced star signals more suitable for monitoring the changes in the Imager's
outputs from views of constant-irradiance stellar sources, but also gave more information on the radiometric characteristics
of the visible channels. We present specifics of this technique together with sample results. We discuss improvements in
the quality of the time series that allow for more reliable inferences on the gradually changing responsivities of the visible
channels. We describe further contributions of this method to monitoring of other performance characteristics of the visible
channel of an Imager.
Although the visible channel of the Imagers carried by NOAA's operational Geostationary Operational Environmental Satellites (GOES) has no onboard calibration device, the decrease in the responsivity of this channel over time must be known if we are to make the data in this channel useful for detecting trends in the signals from the Earth. Therefore, some external method is required to provide this information. In this paper, we examine an external technique for monitoring responsivity changes based on empirical distribution functions (EDFs) of observations of the Earth's full disk. A time series of instrument outputs (in digital counts) at fixed levels at the tops of the EDFs is produced. A nonlinear least squares technique is then employed to adjust the time series for solar and seasonal effects and to fit it with an exponential, whose argument provides the rate of degradation of the responsivity. This technique assumes that the probabilistic structure of the signal from the earth does not change over time. The resulting time series and estimated responsivity degradation rates for the visible channels of GOES-8 and -10 Imagers will be presented. These results are similar to those obtained earlier with a star-based technique, thus increasing our confidence in the results of both techniques. The EDF technique and the star-based technique are synergistic, as they use very different approaches and data sets. Also, the star based technique works at the low end of the Imager's output signal range, whereas the EDF technique works at the high end.
Stars are regularly observed in the visible channels of the GOES Imagers for real-time navigation operations. However, we have been also using star observations off-line to deduce the rate of degradation of the responsivity of the visible channels. We estimate degradation rates from the time series of the intensities of the Imagers' output signals, available in the GOES Orbit and Attitude Tracking System (OATS). We begin by showing our latest results in monitoring the responsivities of the visible channels on GOES-8, GOES-10 and GOES-12. Unfortunately, the OATS computes the intensities of the star signals with approximations suitable for navigation, not for estimating accurate signal strengths, and thus we had to develop objective criteria for screening out unsuitable data. With several layers of screening, our most recent trending method yields smoother time series of star signals, but the time series are supported by a smaller pool of stars. With the goal of simplifying the task of data selection and to retrieve stars that have been rejected in the screening, we tested a technique that accessed the raw star measurements before they were processed by the OATS. We developed formulations that produced star signals in a manner more suitable for monitoring the conditions of the visible channels. We present specifics of this process together with sample results. We discuss improvements in the quality of the time series that allow for more reliable inferences on the characteristics of the visible channels.
Monitoring the responsivities of the visible channels of the operational Geostationary Operational Environmental Satellites (GOES) is an on-going effort at NOAA. Various techniques are being used. In this paper we describe the technique based on the analysis of star signals that are used in the GOES Orbit and Attitude Tracking System (OATS) for satellite attitude and orbit determination. Time series of OATS star observations give information on the degradation of the detectors of a visible channel. Investigations of star data from the past three years have led to several modifications of the method we initially used to calculate the exponential degradation coefficient of a star-signal time series. First we observed that different patterns of detector output versus time result when star images drift across the detector array along different trajectories. We found that certain trajectories should be rejected in the data analysis. We found also that some detector-dependent weighting coefficients used in the OATS analysis tend to scatter the star signals measured by different detectors. We present a set of modifications to our star monitoring algorithms for resolving such problems. Other simple enhancements on the algorithms will also be described. With these modifications, the time series of the star signals show less scatter. This allows for more confidence in the estimated degradation rates and a more realistic statistical analysis on the extent of uncertainty in those rates. The resulting time series and estimated degradation rates for the visible channels of GOES-8 and GOES-10 Imagers will be presented.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.