Observations in the Terra MODIS PVLWIR bands 27 – 30 are known to be influenced by electronic crosstalk from those bands as senders and into those same bands as receivers. The magnitude of this crosstalk affecting L1B radiances has been steadily increasing throughout the mission lifetime, and has resulted in several detectors within these bands to be unusable for making L2 and L3 science products. In recent years, the crosstalk contamination has been recognized as compromising the climate quality status of several MODIS L2 and L3 science products that depend on the PVLWIR bands. In response, the MODIS Characterization Support Team (MCST) has undertaken an effort to generate a crosstalk correction algorithm in the operational L1B radiance algorithm. The correction algorithm has been tested and established and crosstalk corrected L1B radiances have been tested in several Terra MODIS L2 science product algorithms, including MOD35 (Cloud Mask), MOD06 (Cloud Fraction, Cloud Particle Phase, Cloud Top Properties), and MOD07 (Water Vapor Profiles). Comparisons of Terra MODIS to Aqua MODIS and Terra MODIS to MetOp-A IASI show that long-term trends in Collection 6 L1B radiances and the associated L2 and L3 science products are greatly improved by the crosstalk correction. The crosstalk correction is slated for implementation into Collect 6.1 of MODIS processing.
Significant improvements have been made to the MODIS cloud mask (MOD35) in preparation for Collection 5 reprocessing and forward stream data production. Most of the modifications are realized for nighttime scenes where polar and oceanic regions will see marked improvement. For polar night scenes, two new spectral tests using the 7.2 μm water vapor absorption band have been added as well as updates to the 3.9-12 μm and 11-12 μm cloud tests. More non-MODIS ancillary data has been added for nighttime processing. Land and sea surface temperature maps provide crucial information for middle and low-level cloud detection and lessen dependence on ocean variability tests. Sun-glint areas are also improved by use of sea surface temperatures to aid in resolving observations with conflicting cloud vs. clear-sky signals, where visible and NIR reflectances are high, but infrared brightness temperatures are relatively warm. Details and examples of new and modified cloud tests are shown and various methods employed to evaluate the new cloud mask results. Day vs. night sea surface temperatures derived from MODIS radiances and using only the MODIS cloud mask for cloud screening are contrasted. Frequencies of cloud from sun-glint regions will be shown as a function of sun-glint angle to gain a sense of cloud mask quality in those regions.
This paper conducts a preliminary assessment of the cloud detection capability of the Japanese Global Imager (GLI). Cloud detection results from the satellite borne instrument are compared to other satellite, aircraft and ground-based observations. The performance is similar to that of the MODIS results.
MODIS measurements contain the striping signals in the longwave infrared bands because MODIS is a multi-detector sensor. We describe a wavelet method for recovery of MODIS data from its stripe signals. Our work is organized into four broad sections. Section 1 will introduce wavelet shrinkage method for de-noising noisy data, compare the character of the wavelet method and the FFT method in de-noising processing. The objective of section 2 is to find out the scale of MODIS stripe by the wavelet analysis for MODIS stripe data using continuous wavelet transforms. Section 3 analyses Stripe data pattern for the MODIS level 1B stripe data, present the wavelet shrinkage method for MODIS level 1B data. Section 4 will provide a comparing for MODIS cloud product and atmospheric profile product between the original data and de-striped data.
We can find that there’s been an improvement in MODIS cloud product and atmospheric profile product after de-striping. And we can get more understanding for the stripe regular pattern.
The 36 channel Moderate Resolution Imaging Spectroradiometer (MODIS) offers the opportunity for multispectral approaches to cloud detection. The MODIS cloud mask developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) uses several cloud detection tests to indicate a level of confidence that the MODIS is observing clear skies. The MODIS cloud mask algorithm identifies several conceptual domains according to surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. The updated cloud mask has many improvements, such as improved cloud/surface discrimination over desert regions, sun glint processing and thin cirrus detection. For non-snow-covered land areas, a clear sky confidence of 0.96 (probably clear) will be assigned if thresholds are met for three tests: 3.9-11 μm and 3.75-3.9 μm brightness temperature differences and a 1.24/0.55 μm reflectance ratio test. Values of these must be <15K, <11K and >2.0, respectively. A change has been made to the NIR (band 2) reflectance test for sun glint processing. The updated method is to calculate a cloud threshold as a linear function of sun-glint angle in three separate ranges. A new clear-sky restoral test was added where the ratio of band 17/18 reflectance is utilized to discriminate between low clouds and water surfaces. The thin cirrus thresholds using corrected band 26 (1.38 μm) reflectances were also modified.
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