Automatic detection of typical dust devils from Mars landscape images

This paper presents an improved algorithm for automatic detection of Martian dust devils that successfully extracts tiny bright dust devils and obscured large dust devils from two subtracted landscape images. These dust devils are frequently observed using visible cameras onboard landers or rovers. Nevertheless, previous research on automated detection of dust devils has not focused on these common types of dust devils, but on dust devils that appear on images to be irregularly bright and large. In this study, we detect these common dust devils automatically using two kinds of parameter sets for thresholding when binarizing subtracted images. We automatically extract dust devils from 266 images taken by the Spirit rover to evaluate our algorithm. Taking dust devils detected by visual inspection to be ground truth, the precision, recall and F-measure values are 0.77, 0.86, and 0.81, respectively.     

Numerical simulations of the regional characteristics of dust transport on Mars

Using a Martian general circulation model (GCM), regions favorable for expansion of dust storms on Mars are identified. Dust transport simulations for the northern fall provide global maps of dust expansibility. These global maps show that dust injected from certain areas in the northern mid-latitudes tends to spread widely within a few days. The high expansibility of dust in such areas results from thermal tides, baroclinic waves, and quasi-stationary disturbances. Dust injected into the vast regions around Tharsis and the Sirenum–Aonia regions also tends to spread extensively. However, dust expansion around these two regions largely depends on the local time of dust injection. On the other hand, dust injected at high latitudes in either hemisphere does not spread extensively. Such global maps indicating regions favorable for dust storm expansion are a clue to understanding the expansion processes and climatology of great dust storms on Mars.     

Improvement of the ADEOS-II/GLI sun-glint algorithm using concomitant microwave scatterometer-derived wind data

The tendency of over-estimation of sun-glint reflectance was found in GLI satellite ocean color data, after applying the traditional sun-glint model of Cox and Munk together with objective analysis wind data. ADEOS-II has provided a good opportunity to improve the glint model using data measured by GLI and SeaWinds, both onboard the satellite. With the help of simultaneous wind measurements achieved by SeaWinds, the Cox and Munk model is re-evaluated using GLI measurements to obtain a new relationship between the surface mean square slope and wind. The new model was found to be very close to the Cox and Munk under moderate wind speed but is much different under calm condition, where it shows similarity to the result reported by Ebuchi and Kizu. It also improves the ocean color data availability and the precision of sun-glint reflectance, based on the evaluation result of the generated Level 3 data products.