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Sensitivity of the CLAVR-x Cloud Amount/Type Products to the Seasonal Cycle

The goal of this pages to present evidence of how the CLAVR-x cloud amount and cloud type products respond to seasonal cycle. In the analysis, we are only using data from July and January. We have chosen one July and one January month from several of the afternoon polar orbiters and selected months with the same equator crossing time to avoid issues concerned with satellite orbit drift. The effective equator crossing for all data is within 30 minutes of 3:00 PM. The equator crossing times are shown below with times of the months used in this analysis plotted as triangles. The July data are taken from 1982, 1986, 1991, and 1998. The January data are taken from 1983, 1987, 1992, and 1999.

This analysis focuses on the performance of frontend CLAVR-x processor that runs the pixel level cloud mask and cloud typing algorithms. The sensitivity to the seasonal cycle within the other CLAVR-x suite of cloud properties will also be analyzed.

The CLAVR-x cloud type consists of the following classes

0 - clear
1 - partly clear
2 - warm water cloud
3 - super cooled water cloud
4 - opaque ice cloud
5 - non overlapped cirrus cloud
6 - overlapped cirrus cloud

The clear and partly clear types are the same as those in cloud mask and are not run through the cloud typing algorithm. CLAVR-x also computes a water and ice cloud fraction. When doing so, it is assumed that types 2&3 are water and types 4-6 are ice. The partly clear contribution to the fractions are partitioned based on the relative distribution of ice and water types in the grid-cell. The water and ice cloud fractions should sum to be the total cloud fraction. The fractions reported for the types are the fraction of all pixels within a grid-cell for that particular type. The fractions for all types (0-6) should sum to unity.

Global Fields from CLAVR-x for mean July and January (1982-3, 1986-7, 1991-2, 1998-9) Ascending Data from the Afternoon Satellites (NOAA-7,9,11 &14)

	July mean	July Std. Dev.	January mean	January Std. Dev.	July-January mean
Total Cloud	view	view	view	view	view
Water Cloud	view	view	view	view	view
Ice Cloud	view	view	view	view	view
Warm Water Cloud	view	view	view	view	view
Super-cooled Water Cloud	view	view	view	view	view
Opaque Ice Cloud	view	view	view	view	view
Non-overlapped Cirrus Cloud	view	view	view	view	view
Overlapped Cirrus Cloud	view	view	view	view	view

Presented here are some analogous plots to those above derived the ISCCP data. This data is taken from global monthly means available on-line from the ISCCP website. The water cloud fraction was computed as the sum of the low and mid level water cloud amount (there was no high water cloud amount). The ice cloud fraction is derived from the subtraction of the water from the total. Note, the web site provided only daytime data but the total cloud amount is a diurnal average. Therefore, the derivation of the ice cloud amounts may be incorrect. ISCCP is a daytime average while CLAVR-x results are for a local time of approximately 3:00 PM.

Comparison to ISCCP mean July and January Values.

	July mean	January mean	July-January mean
Total Cloud	view	view	view
Water Cloud	view	view	view
Ice Cloud	view	view	view

Conclusions from these Results

There is more agreement in the seasonal cycle then there is the actual monthly cloud amounts between ISCCP and CLAVR-x.
The July - January differences in the polar regions between CLAVR-x and ISCCP are reversed. CLAVR-x sees more cloud in the Arctic in July than January and sees more cloud in the Antarctic in January than July - ISCCP is the opposite.
The seasonal cycle in overlapped cirrus is consistent with notion that overlapped cirrus are most often associated midlatitude cyclones and deep tropical convection.
There is a weakness in the overlap cirrus detection over snow. This can be filtered out since we produce a snow fraction but this was not done in these images.
The largest standard deviations in cloudiness are found in central tropical pacific region. The cause of this is probably ENSO related - the years chosen occur within different parts of the ENSO cycle.

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