Computer Modeling Laboratory 9

Written report due: 13 November

Applications of passive remote sensing: Sensing of clouds.

Lectures 5 and 13

Example of interpretation of MODIS cloud products:
L1B & L2 Granule Case Study: Kamchatka Cloud Properties

Examples of good retrievals (called golden granules) of MODIS cloud products - see here



The detection of clouds is a first key step not only in retrievals of cloud properties, but also in many remote sensing applications that require a cloud-free condition. A combination of solar and IR observations are commonly used to overcome the inherent problems in detecting clouds with either solar or IR remote sensing.

  1. Give three examples when clouds are hard to detect from the visible imagery.
    HINT: Recall an expression for a combined reflectance of the cloud-underlying surfcae system. The albedo of cloud itself (for conservative scattering) can be approximated as Rcl = [(1-g)τ]/[1+(1-g)τ]
  2. You analyze a satellite image of two clouds with one appearing brighter at the visible wavelengths. In general, would you expect more, less, or unknown infrared radiance emitted by the brighter-looking cloud?
  3. This animation helps to visualize the effect of clouds on remote sensing in the IR.
    Answer the questions listed under the animation figure.



Instruction:to compute the TOA radiances click on RUN RT code

The solar reflectance technique enables to retrieve the optical depth and effective drop size of clouds using radiances measured by a passive satellite sensor in the solar spectrum (see Lecture 13).

Using MODIS 2.1 and 0.86 μm channels, investigate whether this technique is capable of retrieving the optical depth and effective particle size of low level clouds over the deserts (Rsur = 0.3). Both MODIS channels have a band width of 0.05 μm. Take same solar and viewing zenith angles as in the figures in Lecture 13 (p.21).



In this task, you will be analyzing MODIS cloud products using a web interface that provides an access to the Level 1 and Atmosphere Archive and Distribution System (LAADS). Go to Images, Level2 Browser. Select Nov.1, Terra MODIS, parameter RGB, and get granule images of a 10x10 degrees box over the Northern Africa. This selection includes three day-time granules (10:25; 10:30 and 12:00).
Select (click on image) the 10:25 am granule. By clicking on View Side by Side Parameter Comparison, you can see cloud and some other atmospheric products retrieved for this granule. Download images for cloud fraction, cloud-top pressure, cloud optical depth and effective particle radius. Download the same cloud products for other two granules.
1) Analyze cloud fraction images against RGB images for 10:25; 10:30 and 12:00 granules. Find a few instances when cloud fraction was retrieved incorrectly. Briefly discuss the possible reasons.
2) Using cloud-top-pressure and cloud optical depth images, identify a stratus cloud over ocean and over land. Compare retrieved effective particle radius for these cases. Do retrievals look reasonable (refer to table 5.4 of Lecture 5).
3) Identify a few cirrus clouds in RGB images and analyze retrieved cloud products, if any. Do the retrieved products look reasonable? Briefly discuss what might be causing problems in retrievals of ice clouds.