David S. Crosby

The Limb Adjustment of AMSU-A Observations: Methodology and Validation

Abstract The Advanced Microwave Sounding Unit-A (AMSU-A) is the first of a new generation of polar-orbiting cross-track microwave sounders operated by the National Oceanic and Atmospheric Administration. A feature of a cross-track sounder is that the measurements vary with scan angle because of the change in the optical pathlength between the earth and the satellite. This feature is called the limb effect and can be as much as 30 K. One approach to this problem is to limb adjust the measurements to a fixed view angle. This approach was used for the older series of Microwave Sounding Units. Limb adjusting is important for climate applications and regression retrieval algorithms. This paper describes and evaluates several limb adjustment procedures. The recommended procedure uses a combined physical and statistical technique. The limb adjusted measurements were compared with computed radiances from radiosondes and National Centers for Environmental Prediction models. The model error was found to be less tha...

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.

Recalibration of the NOAA microwave sounding unit

The microwave sounding unit (MSU) prelaunch thermal-vacuum chamber test data for eight MSU flight models that flew on TIROS-N, NOAA 7 through NOAA 12, and NOAA 14 were reanalyzed using an improved calibration algorithm, originally designed for the advanced microwave sounding unit-A (AMSU-A) operations. The new calibration algorithm can automatically adjust for any channel gain shift in operation. Adoption of this calibration algorithm as the MSU calibration procedure in the recalibration project will make the data sets from the MSU and the AMSU-A more consistent. This will be useful for future blending of the climate trends generated from the MSU and AMSU-A data. A single nonlinearity parameter u, which appears in the new calibration algorithm, was obtained for each channel from analysis of the prelaunch calibration test data. A software package for implementing this new calibration algorithm was developed and applied to calculate the MSU time series for improvement of the accuracy of the climate record. Sample calculations of MSU antenna temperatures with the new calibration algorithm were made for two satellites and are compared with similar results obtained from the old MSU calibration algorithm. Significant differences are observed, and strong evidence indicates that the new calibration procedure will provide a more accurate quantification of climate trends.

Determination of total ozone amount from TIROS radiance measurements

Abstract Total ozone amounts are determined from atmospheric radiances measured by the TIROS Operational Vertical Sounder (TOVS). The retrieval procedure is one of linear regression where total ozone amounts derived from Dobson spectrophotometer measurements are regressed against “clear” radiances that are measured in three of the TOVS spectral channels and converted to brightness temperatures. This paper discusses the retrieval technique, the accuracy of the ozone data products compared to an independent set of Dobson measurements used for validation, and comparisons with zonal-averaged total ozone data derived from the Nimbus-7 Solar Backscatter Ultraviolet (SBUV) instrument.

The application of a technique for vector correlation to problems in meteorology and oceanography

Abstract In a recent study, Crosby et al. proposed a definition for vector correlation that has not been commonly used in meteorology or oceanography. This definition has both a firm theoretical basis and a rather complete set of desirable statistical properties. In this study, the authors apply the definition to practical problems arising in meteorology and oceanography. In the first of two case studies, vector correlations were calculated between subsurface currents for five locations along the southeastern shore of Lake Erie. Vector correlations for one sample size were calculated for all current meter combinations, first including the seiche frequency and then with the seiche frequency removed. Removal of the seiche frequency, which was easily detected in the current spectra, had only a small effect on the vector correlations. Under reasonable assumptions, the vector correlations were in most cases statistically significant and revealed considerable fine structure in the vector correlation sequences. ...

Constrained Regression in Satellite Meteorology

Abstract Least squares or regression techniques have been used for many problems in satellite meteorology. Because of the large number of variables and the linear dependence among these variables, colinearity causes significant problems in the application of standard regression techniques. In some of the applications there is prior knowledge about the values of the regression parameters. Since there are errors in the predictor variables as well as the predictand variables, the standard assumptions for ordinary least squares are not valid. In this paper the authors examine several techniques that have been developed to ameliorate the effects of colinearity or to make use of prior information. These include ridge regression, shrinkage estimators, rotated regression, and orthogonal regression. In order to illustrate the techniques and their properties, the authors apply them to two simple examples. These techniques are then applied to a real problem in satellite meteorology: that of estimating theoretical co...

Radiance Estimates from Truncated Observations

Abstract In many experiments where radiation emitted from the surface or lower atmosphere is to be measured, a fundamental difficulty is the presence of clouds. In this paper a technique is developed and described which uses a number of small fields-of-view to estimate the clear radiance. Specifically, it is assumed that some of these small fields-of-view are cloud-free and that the difference between the measured radiance from these cloud-free areas is due to instrument noise, which is normal with known standard deviation. Then the tail of the normal distribution is used to estimate the clear radiance. An example is provided.

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.

Estimating the Probability of Rain in an SSM/I FOV Using Logistic Regression

Abstract The SSM/I has been used successfully to estimate precipitation and to determine the fields of view (FOV) that contain precipitating clouds. The use of multivariate logistic regression with the SSM/I brightness temperatures to estimate the probability that it is raining in an FOV is examined. The predictors used in this study are those that have been evaluated by other investigators to estimate rain events using other procedures. The logistic regression technique is applied to a matched set of SSM/I and radar data for a limited area from June to August 1989. For this limited dataset the results are quite good. In one example, if the predicted probability is less than 0.1, the radar data shows only 2 of 340 FOVs have precipitation. If the predicted probability is greater than 0.9, the radar data shows precipitation in 748 of 774 FOVS. These probabilities can be used for both instantaneous and climate timescale retrievals.

Adjusting Satellite Radiances by Regression with an Orthogonal Transformation to a Prior Estimate

Abstract Many methods for converting satellite radiances to temperatures require a comparison of observed radiances with radiances calculated from a first guess. Usually, measured values must be tuned to agree with theoretical calculations. A regression in which the calculated radiances are predicted from the observed ones is a method of making the adjustment, but results in unrealistic coefficients. Several modifications to standard regression are tried, and it is shown that rotated regression, a technique developed in this paper, provides the required accuracy with coefficients that satisfy the physical constraints.