Skip to main content

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 TypeWind Speed (km/h)
Low Pressure< 31
Depression31-49
Deep Depression50-61
Cyclonic Storm62-88
Severe Cyclonic Storm89-117
Very Severe Cyclonic Storm118-165
Extremely Severe Cyclonic Storm166-221
Super Cyclone> 222

Comments

Popular posts from this blog

Radar Remote Sensing SAR

1. Radar and Radar Remote Sensing RADAR stands for Radio Detection and Ranging . It is an active remote sensing system that transmits microwave energy toward the Earth's surface and records the energy that is returned to the sensor as an echo or backscatter . Unlike passive optical remote sensing, radar does not depend on sunlight. Therefore, it can operate day and night and, at suitable wavelengths, can acquire data through clouds, haze and light rain. Hence, radar is widely described as an all-weather, day-and-night remote sensing technology . Basic principle Microwave pulse → transmission → interaction with surface → backscatter/echo → antenna receives signal → signal processing → radar image 2. Microwave Energy Radar systems use microwave electromagnetic radiation , generally in wavelength ranges from approximately 1 mm to 1 m . Important radar bands include: Band Approx. wavelength Common applications ...

Supervised Classification

Image Classification in Remote Sensing Image classification in remote sensing involves categorizing pixels in an image into thematic classes to produce a map. This process is essential for land use and land cover mapping, environmental studies, and resource management. The two primary methods for classification are Supervised and Unsupervised Classification . Here's a breakdown of these methods and the key stages of image classification. 1. Types of Classification Supervised Classification In supervised classification, the analyst manually defines classes of interest (known as information classes ), such as "water," "urban," or "vegetation," and identifies training areas —sections of the image that are representative of these classes. Using these training areas, the algorithm learns the spectral characteristics of each class and applies them to classify the entire image. When to Use Supervised Classification:   - You have prior knowledge about the c...

Lidar

LiDAR (Light Detection and Ranging) is an active remote sensing technology that measures distances by illuminating a target with laser pulses and analyzing the time it takes for the reflected light to return. Unlike passive systems (e.g., cameras, multispectral sensors), LiDAR provides its own energy source (laser), allowing it to operate both day and night and even penetrate through vegetation canopies . 🔹 How LiDAR Works (Step-by-Step Process) Laser Pulse Emission The system emits rapid, short pulses of laser light (commonly in the near-infrared wavelength, 1064 nm ). Some systems emit up to hundreds of thousands of pulses per second . Interaction with Target Surface The laser beam strikes objects such as vegetation, buildings, or bare ground. Depending on the object's structure, part of the pulse may scatter or reflect. Return Signal Detection The sensor records multiple returns : First Return → typically vegetation canopy tops. ...

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...

Image Transformation

In remote sensing, image transformation is used to create new images by manipulating existing ones, enhancing the information extracted from each pixel. Multi-image manipulation and other transformations allow analysts to highlight specific features, compare time-series data, or reduce data dimensions for better interpretation. 1. Multi-Image Manipulation This technique involves applying mathematical operations to multiple images, typically from different bands, dates, or sensors, to highlight specific features or changes. Common methods include: a. Image Addition Purpose : Highlights areas of similarity or enhances features when the same objects appear in multiple images. How it Works : By adding pixel values from two images, the output image emphasizes areas where brightness is high in both. Example : Enhancing overall brightness or detecting seasonal changes by adding images from different times. b. Image Subtraction Purpose : Identifies differences between images, useful for chan...