Michael P. Weinreb

Destriping GOES images by matching empirical distribution functions

Abstract The current and future geostationary operational environmental satellites (GOES) of the National Oceanic and Atmospheric Administration (NOAA) are designed to produce visible images of the earth with linear arrays of eight detectors. Because the imaging instruments are not calibrated radiometrically in orbit, differences among instrument gains associated with the different detectors may cause artificial stripes to appear in the images. In the data processing on the ground, the images are “normalized” to remove the stripes. Images from future geostationary satellites, GOES I-M, will be normalized by the method of matching empirical distribution functions (EDFs). In this paper we report on a study of EDF matching with data from GOES-7. The technique was used to generate a normalization look-up table from data taken on 18 May 1988, and the table was applied to image data obtained 2 weeks later, on 1 June 1988. This removed the stripes from the image. The technique is expected to be even more effective with data from GOES I-M because of improvements in instrumentation.

Estimation of long-term throughput degradation of GOES 8 and 9 visible channels by statistical analysis of star measurements

Each Imager and Sounder on the present generation of GOES satellites has an eight-channel visible detector array. These visible arrays perform star-sensing measurements to establish inertial attitude references so that earth observations can be registered to the earths latitude and longitude coordinates. The Imagers visible array also performs earth observations. We have used the archived signal levels of star measurements to estimate the long-term throughput loss in these channels of the Imager and Sounder on GOES 8 and GOES 9. An exponential decay rate was determined for each sensor by averaging the values derived from each of approximately 30 stars over a time interval of at least 500 days. Large degradations in image quality occur during local night, when direct sunlight enters the optical ports of the two sensor. Therefore, we have deleted observations made during the 10 hour interval around midnight, satellite time, from our analysis. Variable stars and stars with low signal-to-noise ratios were also excluded. The annual throughput losses for the four sensors, derived from measured star signal levels, range from 3.8 percent to 9.6 percent.

Satellite Observations of Atmospheric Water Vapor

Observations in the spectral window at 11-12 microm, in the carbon dioxide band at 13.3-13.4 microm, and in the water vapor rotation band at 18.7-18.8 microm have been made by the satellite infrared spectrometer and the vertical temperature profile radiometer on the Nimbus 4 and NOAA-2 satellites. Combinations of radiances measured by the separate instruments have been used to infer sea-surface temperatures and mesoscale precipitable water in tropical regions. In each spectral interval, atmospheric transmittances for these analyses were constructed from continuous absorption (of unexplained origin), which is dependent upon the square of the partial pressure of water vapor and about the inverse fifth power of temperature, in addition to absorption by resonance lines. Results are consonant with those from other laboratory and atmospheric transmittance measurements, and they underline the importance of properly modeling the water-vapor continuum in calculations of atmospheric radiation in the middle infrared.

Optimization of spectral intervals for remote sensing of atmospheric temperature profiles

Abstract An expression to evaluate the information content of solutions of the radiative transfer equation other than the minimum-rms solution is derived. This expression can be applied to the problem of selecting the spectral location and number of tropospheric channels for a remote temperature sounder. Application is made to a minimum information solution. The results indicate that three tropospheric channels will suffice, and that it is possible to find a single set of channels which will be nearly optimal over all regions of the globe.

Characteristics of E/W stripes in infrared images from the GOES-8 imager

East-west stripes are observed in images in channels 4 (10.7 micrometers ) and 5 (12 micrometers ) of the GOES-8 imager. These channels use two detectors arranged in a north-south array to sweep out alternate lines of an image. The stripes are caused by differences in the outputs of the two detectors. There is a clear correlation between scene temperature and the magnitude of the striping. Measured in temperature units, the striping is more severe at the cold end of the spectrum, and therefore affects meteorological products which depend on observations of cold targets. The striping can be divided into three components: 1) within-frame random, 2) systematic within-frame but random from frame-to-frame, and 3) systematic over many frames. The first two components are caused by 1/f noise during data-taking and calibrations. The cause of the third component of the striping is not known. Examples of each striping element are presented and discussed. A brief comparison of GOES-8 and GOES-9 imager striping is made.

Atmospheric Transmission For Remote Temperature Sounding

Calculations of atmospheric radiances are compared with observations made in the 15 pm and 4.3 pm spectral regions by the HIRS/2 on TIROS-N. Differences between calculation and observation lead us to make empirical corrections in calculations of atmospheric transmittances. The largest correction is required in the HIRS/2 interval at 690 cm-1. Corrections arealso required in the intervals centered at 703, 2210, and 2270 cm-1. At NOAAs National Environmental Satellite Service, several studies of laboratory spectra show good agreement between observation and calculation in these spectral regions. However, in the 15 μm CO2 Q-branch, classical theory underestimates the observed temperature dependence of widths of spectral lines.

Recent advances in calibration of the GOES Imager visible channel at NOAA

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.

Refined algorithms for star-based monitoring of GOES Imager visible-channel responsivities

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.

Trends and diurnal cycles of GOES imager scan-mirror emissivity

This paper discusses the operational in-orbit GOES-8 and GOES-10 imager scan-mirror emissivity trends, as well as their diurnal cycles. The imagers (and sounders) aboard both GOES-8 and GOES-10 experience a variation in scan-mirror emissivity along the east-west scan direction. The most obvious manifestation of this phenomenon is a difference in output between the east and west sides when the insthiments view space, but it is also present in observations of the Earth. The phenomenon is accounted for in the calibration process with an algorithm that makes use ofcoefficients incorporating the variation ofthe scanmirror emissivity with east-west scan angle. The coefficients are derived from measurements of space above the north pole and below the south pole made during GOES station-keeping maneuvers, which are performed a few times a year. Over time, these measurements allow us to compile a trend ofthe east-westemissivityvariation. Operational full-disk images are used to diagnose the diurnal behavior of the residual (after correction) east-west output differences. A comparison between the scan-mirror emissivity of GOES-8 and that of GOES-10 is made to search for patterns related to specific satellites. This paper also reviews how the east-west scan-mirror emissivity coefficients are derived and evaluates the effect ofuncertainties in the band-averaged emissivity measurements on the GOES calibration. An effective scan-mirror temperature is proposed to minimize the residual east-west output differences.

Optical Passive Sensor Calibration for Satellite Remote Sensing and the Legacy of NOAA and NIST Cooperation

This paper traces the cooperative efforts of scientists at the National Oceanic and Atmospheric Administration (NOAA) and the National Institute of Standards and Technology (NIST) to improve the calibration of operational satellite sensors for remote sensing of the Earth’s land, atmosphere and oceans. It gives a chronological perspective of the NOAA satellite program and the interactions between the two agencies’ scientists to address pre-launch calibration and issues of sensor performance on orbit. The drive to improve accuracy of measurements has had a new impetus in recent years because of the need for improved weather prediction and climate monitoring. The highlights of this cooperation and strategies to achieve SI-traceability and improve accuracy for optical satellite sensor data are summarized1.