Cyclone

1. Low-Pressure System

A low-pressure system is an area where the atmospheric pressure is lower than its surroundings. These systems are associated with rising warm air, which leads to cloud formation and precipitation. They are the primary drivers of weather disturbances like cyclones and storms.

Concept: Warm air rises, creating a region of lower pressure at the surface. As air converges to fill this void, it starts to rotate due to the Coriolis effect.
Example: A monsoon low-pressure system forming over the Bay of Bengal, leading to heavy rains in eastern India.

2. Depression

A depression is a more developed form of a low-pressure system with a well-defined circulation. It brings moderate to heavy rainfall and gusty winds.

Concept: When a low-pressure system intensifies with wind speeds between 31-49 km/h, it is classified as a depression.
Example: The depression over the Arabian Sea that causes heavy rainfall in Mumbai during the monsoon season.

3. Deep Depression

A deep depression is a further intensification of a depression with stronger winds and heavier rainfall.

Concept: A depression becomes a deep depression when wind speeds increase to 50-61 km/h. This stage is a precursor to a tropical storm or cyclone.
Example: A deep depression forming over the Bay of Bengal, later developing into Cyclone Yaas in 2021.

4. Cyclone

A cyclone is a large-scale air mass that rotates around a strong center of low atmospheric pressure. It is classified into different categories based on wind speed.

Concept: A cyclone forms when a deep depression further intensifies, with wind speeds exceeding 62 km/h. Warm ocean waters provide energy, causing rapid intensification.
Types of Cyclones:
- Tropical Cyclones: Form over warm ocean waters (e.g., Cyclone Amphan in 2020).
- Extratropical Cyclones: Occur outside tropical regions and are associated with frontal systems (e.g., Nor'easters in the U.S.).

5. Storm

A storm is a general term for a disturbed state of the atmosphere that can bring strong winds, heavy rain, thunder, lightning, and sometimes snow.

Concept: When wind speeds reach 62-88 km/h, the system is called a "Cyclonic Storm." If it intensifies further, it may become a Severe Cyclonic Storm (89-117 km/h) or even a Super Cyclone (>222 km/h).
Example: Cyclone Fani (2019) was classified as an Extremely Severe Cyclonic Storm with wind speeds exceeding 250 km/h, causing significant destruction in Odisha, India.

Wind Speed Classifications

System Type	Wind Speed (km/h)
Low Pressure	< 31
Depression	31-49
Deep Depression	50-61
Cyclonic Storm	62-88
Severe Cyclonic Storm	89-117
Very Severe Cyclonic Storm	118-165
Extremely Severe Cyclonic Storm	166-221
Super Cyclone	> 222

Comments

Quantitative Revolution in Geography

The Quantitative Revolution was a major change in Geography during the 1950s and 1960s. It introduced mathematical, statistical and scientific methods to understand geographical phenomena. Before this revolution, geographers mainly described places, regions, landscapes and differences between areas. After the revolution, they increasingly used numerical data, statistical analysis, mathematical models and theories to explain why geographical patterns occur and how they may change. For example: Traditional approach: Describe the distribution of population in different regions. Quantitative approach: Use statistical methods to identify population patterns, explain the factors influencing population distribution and predict future population growth. The revolution helped establish Geography as a spatial science, focusing on the location, distribution, relati...

Satellite Remote Sensing: Concepts and Imaging Systems

Satellite remote sensing relies on detectors (sensors) that measure reflected/emitted electromagnetic radiation from the Earth. How sensors collect data depends on: Spectral coverage → Multispectral (few bands), Hyperspectral (hundreds), Thermal, Microwave. Detector type → Discrete detectors, linear arrays, or area arrays. Scanning mechanism → Scanning mirrors (whiskbroom) vs. linear arrays (pushbroom). Multispectral Imaging Using Discrete Detectors and Scanning Mirrors (Whiskbroom scanners) Principle : A single detector (or a few detectors) measures radiation one pixel at a time. A scanning mirror sweeps across-track (perpendicular to the satellite path) to build up the image line by line. The forward motion of the satellite provides the along-track dimension. Known as a whiskbroom scanner . Characteristics : Good calibration stability. Narrow instantaneous field of view (IFOV). Susceptible to mechanical wear (moving ...

Spectral Signature vs. Spectral Reflectance Curve

Spectral Signature A spectral signature is the unique pattern in which an object: absorbs energy reflects energy emits energy across different wavelengths of the electromagnetic spectrum. ✔ Key Points Every natural and man-made object on Earth interacts with sunlight differently. These interactions produce a distinct pattern , just like a "fingerprint". Sensors on satellites record these patterns as digital numbers (DN values) . These patterns help to identify and differentiate objects such as vegetation, soil, water, snow, buildings, minerals, etc. ✔ Examples of Spectral Signatures Healthy vegetation → High reflectance in NIR , strong absorption in red Water → Strong absorption in NIR and SWIR , low reflectance Dry soil → Gradual increase in reflectance from visible to NIR Snow → High reflectance in visible , low in SWIR ✔ Why Spectral Signature Matters It allows: Land cover classification Chan...

Geometric Correction

When satellite or aerial images are captured, they often contain distortions (errors in shape, scale, or position) caused by many factors — like Earth's curvature, satellite motion, terrain height (relief), or the Earth's rotation . These distortions make the image not properly aligned with real-world coordinates (latitude and longitude). 👉 Geometric correction is the process of removing these distortions so that every pixel in the image correctly represents its location on the Earth's surface. After geometric correction, the image becomes geographically referenced and can be used with maps and GIS data. Types 1. Systematic Correction Systematic errors are predictable and can be modeled mathematically. They occur due to the geometry and movement of the satellite sensor or the Earth. Common systematic distortions: Scan skew – due to the motion of the sensor as it scans the Earth. Mirror velocity variation – scanning mirror moves at a va...

RADIOMETRIC CORRECTION

Radiometric correction is the process of removing sensor and environmental errors from satellite images so that the measured brightness values (Digital Numbers or DNs) truly represent the Earth's surface reflectance or radiance. In other words, it corrects for sensor defects, illumination differences, and atmospheric effects. 1. Detector Response Calibration Satellite sensors use multiple detectors to scan the Earth's surface. Sometimes, each detector responds slightly differently, causing distortions in the image. Calibration adjusts all detectors to respond uniformly. This includes: (a) De-Striping Problem: Sometimes images show light and dark vertical or horizontal stripes (banding). Caused by one or more detectors drifting away from their normal calibration — they record higher or lower values than others. Common in early Landsat MSS data. Effect: Every few lines (e.g., every 6th line) appear consistently brighter or darker. Soluti...

Vineesh V, Geography

Search This Blog