CRES – Cloud Classification
Cloud classification based on satellite images has always played an important role allowing the observation of different kinds of clouds and monitoring their temporal evolution. Fields in which this type of analysis are more common are Climatology, Meteorology and studies on cloud microphysics.
The CRES system works on the 36 spectral bands of the MODIS sensor to identify up to 10 cloud classes and 5 different groups:
- Deep Cloud and Cirrus
- Thin Cloud
- Low Cloud and Shadow
- High Cirrus
- Thin Cirrus
Also, CRES workson NOAA-AVHRR and METEOSAT data with somewhat less efficiency.
CRES – Rainfall Rate Estimation
Not only meteorology and environmental monitoring studies and applications need accurate, frequent and diffused rainfall rate information. The use of multispectral satellite data allows the estimation rainfall rate fields on the ground at synoptic scale with up to 15 minute time frequency and a few kilometers’ ground resolution.
From the Rainfall Rate menu, the user can select among three different rainfall rate estimation methods:
- Cloud Map Based (AVHRR, METEOSAT, MODIS)
- Convective Stratiform Technique (AVHRR, METEOSAT, MODIS).
- Enhanced CST (MODIS)
CRES – Soil Erosion
Soil erosion is a complex phenomenon influenced by different factors: climate, soil morphology, hydrology, vegetation and anthropic territorial impact.
In the framework of the RIADE project (focused on desertification effects on the Mediterranean area), MEEO has carried out an analysis of the soil energetic exchange during convective and stratiform precipitation events.
Based on rainfall rate estimation maps, the CRES software allows the computation of soil erosion indexes directly from satellite data.
Moreover, the drop size distribution effect is taken into account on the energy exchange model as a function of three different precipitation regimes (light, medium or intense).