ISRO

Geo-Physical Parameters (GPR) derived from INSAT-3D Imager and Sounder

As part of Initial phase of Operations the IMDPS software at SAC- Bopal has data reception chain (RF and Antenna Segment) , Data Acquisition & Quick Look system (DAQLS), Data Products (DP) of Various types in characterization of both Imager & Sounder in a desired format and Generation few of the important GPR. First cut analysis and Preliminary results are produced from the INSAT-3D Meteorological instruments and Data Products & GPR has come out nicely. Further Calibration and validation and initial Orbit testing (IOT) are mounted and the work is in progress so as to fully characterize and make the full set of GPRs available for weather forecasting.


GPR From Imager

Long Outgoing Wave Radiation (OLR)

The outgoing long wave radiation is a crucial parameter for studying many areas in the field of atmospheric Sciences. The OLR has been used traditionally for radiation budget studies of the Earth atmospheric system. The OLR also has been used for the atmospheric circulation studies over tropical region. This is mainly due to the fact that in the tropics, the OLR is largely modulated by cloudiness. In particular it varies with the cloud top temperature, and consequently, low values of OLR indicate major convective system. OLR is derived using TIR1, TIR2 and WV radiances of Imager.

Rainfall Estimation

Rainfall { Quantitative Precipitation Estimate (QPE) } from INSAT-3D Imager channels is derived based on two methodologies: (i) Rainfall Estimation by Precipitation Index (PI) and (ii) INSAT Multispectral Rainfall Algorithm (IMSRA). The half hourly imageries of TIR1, TIR2, and WV Imager channels are used to determine quantitative estimates of precipitation.

High-Resolution Rainfall Measurements (Hydro-Estimator: HE)

Hydro-estimator provides pixel-scale, half-hourly precipitation measurements over land and oceans. Imager observations in TIR1, TIR2 and WV channels combined with Numerical Weather Prediction (NWP) forecasts are used to estimate high spatial-temporal resolution rainfall estimates.

Sea Surface Temperature (SST)

Sea surface temperature is derived from split thermal window channels (TIR1, TIR2) during daytime and using additional mid IR window channel (MIR) during nighttimes over cloud free oceanic regions. The most important part of the SST retrieval from IR observations is the atmospheric correction, especially over tropics. This correction is determined through a suitable characterization of tropical atmospheres in Radiative Transfer (RT) Model to simulate the brightness temperatures of INSAT-3D channels and then generating the regression coefficients for SST retrieval.

Atmospheric Motion Wind Vectors (AMV)

Spatio-temporal analysis of meteorological events is an important part of routine Numerical weather analysis. Given a pair of remotely sensed images, captured at a fixed time interval (typically, 30 minute), the objective is to derive motion vectors associated with the cloud mass. Suitable tracers are identified in WV, TIR1, TIR2 and VIS band imageries and tracked in subsequent half-hourly imageries to determine Atmospheric Motion Vector (AMV). Water Vapour wind Vector (WVWV), IR wind, VIS wind (Day only) & MIR (Night only) will be generated and these wind estimates are very important parameter in NWP models.

Upper Tropospheric Humidity (UTH)

Upper Tropospheric Humidity (UTH) is an estimate of the mean relative humidity of the atmosphere between approximately 600 hPa and 300 hPa. UTH is basically a measure of weighted mean of relative humidity according to the weighting function of the water vapour channel. Therefore, UTH is more likely a representative of the relative humidity around the atmospheric layer where weighting function of water vapour channel peaks.

Snow-Cover Mapping

The snow-mapping algorithm uses a grouped-criteria technique using the Normalized Difference Snow Index (NDSI) and other spectral threshold tests to identify snow on a pixel-by-pixel basis, and to map snow cover in dense forests. The NDSI is useful for snow mapping, as it reflects more in the visible than in the short-wave IR part of the spectrum. In addition, the reflectance of most clouds remains high in the short-wave IR, while the reflectance of snow is low.

Fire Identification

One of the most important critical elements of the forest fire management system in the country is the real time detection of fire and its progression monitoring; study the rate, direction and quantitative estimation of fire spread. Geostationary satellite like INSAT-3D with imager data of 4x4 km in MIR, TIR1 and TIR2 will help in detecting and monitoring of large scale forest fires in Indian subcontinent.

Smoke Identification

Smoke is a form of particulate matter, which contains liquid or solid particles of the size ranging from 1-200µm. It is formed by combustion or other chemical processes. Smoke plumes can travel over hundreds or even thousands of kilometer horizontally and also reach up to stratosphere under certain atmospheric circulation conditions. Thus smoke can have an impact far beyond the region of fire activity. Smoke plays a major role on the radiation balance of the earth-atmosphere system. Identification of smoke on satellite imagery is a prerequisite to study and retrieve physical, chemical, and optical properties of smoke. Smoke can be detected from high spatial resolution imageries from INSAT-3D Imager channels.

Aerosol Optical Depth (AOD)
Aerosols play an important role in numerous aspects of human life. Aerosols have large-scale effects, such as their impact on climate by redistributing solar radiation and interacting with clouds. Aerosol information is also critical for atmospheric correction algorithms for multi-spectral satellite sensors and military operations. The climate effects of atmospheric aerosols may be comparable to CO2 greenhouse effects, but with opposite sign and larger uncertainty. When in the lower troposphere, aerosols cause poor air quality, reduction of visibility, and public health hazards. Satellite remote sensing provides a means to derive aerosol distribution at global and regional scales. Aerosols can be detected from high spatial resolution imageries in optical bands from INSAT-3D.

FOG
Fog affects visibility near the surface and hence is an important parameter for aviation, transport on land and sea. Night time fog detection is done by looking at the 10.8 and 3.9 µm channel brightness temperatures. This technique relies on fog pixels displaying higher brightness temperature differences as compared to clear pixels and those covered by other clouds.

Sounder Atmospheric Parameters ( Temperature, Moisture Profile and Total Ozone)

INSAT-3D carries an 18-channel infrared Sounder (plus a visible channel). The algorithm is designed for retrieving vertical profiles of atmospheric temperature and moisture along with total column ozone content in the atmosphere from clear sky infrared radiances in different absorption bands observed through INSAT-3D. Sounder derived profiles include temperature at 40 vertical pressure levels from surface to about 70 km and water vapor in 21 levels from surface to around 15 km. Following application products are derived from sounder derived atmospheric profiles. These derived products include:

1. Geopotential height
2. Layer and total precipitable water
3. Lifted index
4. Dry microburst index
5. Maximum vertical theta-e differential
6. Wind index