A heatwave is a period of unusually hot weather with above normal temperatures that typically last three or more days. In India, heatwaves are generally experienced during March-June.
On an average, two-three heatwave events are expected every season. Heatwaves are predominantly observed over two areas, central and northwest India and another over coastal Andhra Pradesh and Odisha, supported by favourable atmospheric conditions.
Total duration of heatwaves has increased by about three days during the last 30 years and a further increase of 12-18 days is expected by 2060. In future climate, heatwaves will be spread to new areas including southern parts of India. Climate change is causing heatwaves more frequently, and they are much stronger and can last for more days.
Heatwaves have multiple and cascading impact on human health, ecosystems, agriculture, energy, water and economy.
The recent 2022 heatwave in India and Pakistan in March-April made devastating impacts.
It is estimated to have led at least 90 deaths across India and Pakistan. It also triggered an extreme Glacial Lake Outburst Flood in northern Pakistan.
How are heatwaves caused?
Heatwaves are caused by large scale atmospheric circulation anomalies like high pressure areas, upper-tropospheric, jet streams, etc.
The global forcing like the El Nino/Southern Oscillation (ENSO) and the Indian Ocean modulate the frequency and duration of Indian
heatwaves. Heatwave can be further accentuated by local effects like depleted soil moisture and enhanced sensible heat flux.
Major regions affected by Heatwave in India
How good is our early warning system for heatwaves?
Research helped us to improve our understanding on the underlying mechanism of its genesis and intensity
Under the National Monsoon Mission, the Ministry of Earth Sciences (MoES) had established an advanced prediction system for early warnings of heatwaves.
IMD has the capability to predict the genesis, duration and intensity of heatwave events with reasonable accuracy up to four-five days in advance.
Adaptation to heatwaves can be effective to minimize the negative impacts, by developing a comprehensive heat response plan that includes early warnings, awareness rising and technology intervention.
India has now a strong national framework for heat action plans involving the India Meteorological Department (IMD), the National and State disaster management authorities, and local bodies.
Early warning systems are an integral part of this heat action plan.
Can we then predict heatwaves two weeks in advance and what about a season in advance?
A recent study published in the Scientific Reports by the scientists at the Indian Institute of Tropical Meteorology (IITM), Pune, has shown that heatwave genesis and duration in India can be predicted with good skill up to two weeks in advance.
They have used the hindcasts from the MoES Extended Range Prediction System (ERPS) that uses ensemble method combining four atmospheric general circulation models.
The model could reproduce the spatial distribution of heatwave frequency and duration very well. The model also showed useful skill in predicting the characteristics of heatwaves for different months (April to June) separately.
The model skill in predicting heatwaves arises due to its fidelity in reproducing the impacts of ENSO and the Indian Ocean on atmospheric circulation anomalies over the Indian region.
Thus, we have an end-to-end seamless prediction system to predict heatwaves in all time scales, from short-range to seasonal. The seasonal forecast will provide an outlook or probability of frequency and duration of heatwaves, one season in advance.
This early outlook can be further strengthened using the extended range (two weeks) and short range (four-five days) forecasts for more focused region-wise response strategies.
Seasonal forecasts should use a multi-model ensemble (MME) forecasting strategy. Short- range ensemble forecasts should use higher resolution global models, initialized with observed soil moisture data, which are available from microwave satellites and IMD’s soil moisture network. We should then expect more advanced forecasting system for heatwaves in the near future.
Darknet, also known as dark web or darknet market, refers to the part of the internet that is not indexed or accessible through traditional search engines. It is a network of private and encrypted websites that cannot be accessed through regular web browsers and requires special software and configuration to access.
The darknet is often associated with illegal activities such as drug trafficking, weapon sales, and hacking services, although not all sites on the darknet are illegal.
Examples of darknet markets include Silk Road, AlphaBay, and Dream Market, which were all shut down by law enforcement agencies in recent years.
These marketplaces operate similarly to e-commerce websites, with vendors selling various illegal goods and services, such as drugs, counterfeit documents, and hacking tools, and buyers paying with cryptocurrency for their purchases.
Anonymity: Darknet allows users to communicate and transact with each other anonymously. Users can maintain their privacy and avoid being tracked by law enforcement agencies or other entities.
Access to Information: The darknet provides access to information and resources that may be otherwise unavailable or censored on the regular internet. This can include political or sensitive information that is not allowed to be disseminated through other channels.
Freedom of Speech: The darknet can be a platform for free speech, as users are able to express their opinions and ideas without fear of censorship or retribution.
Secure Communication: Darknet sites are encrypted, which means that communication between users is secure and cannot be intercepted by third parties.
Illegal Activities: Many darknet sites are associated with illegal activities, such as drug trafficking, weapon sales, and hacking services. Such activities can attract criminals and expose users to serious legal risks.
Scams: The darknet is a hotbed for scams, with many fake vendors and websites that aim to steal users’ personal information and cryptocurrency. The lack of regulation and oversight on the darknet means that users must be cautious when conducting transactions.
Security Risks: The use of the darknet can expose users to malware and other security risks, as many sites are not properly secured or monitored. Users may also be vulnerable to hacking or phishing attacks.
Stigma: The association of the darknet with illegal activities has created a stigma that may deter some users from using it for legitimate purposes.
AI, or artificial intelligence, refers to the development of computer systems that can perform tasks that would normally require human intelligence, such as recognizing speech, making decisions, and understanding natural language.
Virtual assistants: Siri, Alexa, and Google Assistant are examples of virtual assistants that use natural language processing to understand and respond to users’ queries.
Recommendation systems: Companies like Netflix and Amazon use AI to recommend movies and products to their users based on their browsing and purchase history.
Efficiency: AI systems can work continuously without getting tired or making errors, which can save time and resources.
Personalization: AI can help provide personalized recommendations and experiences for users.
Automation: AI can automate repetitive and tedious tasks, freeing up time for humans to focus on more complex tasks.
Job loss: AI has the potential to automate jobs previously performed by humans, leading to job loss and economic disruption.
Bias: AI systems can be biased due to the data they are trained on, leading to unfair or discriminatory outcomes.
Safety and privacy concerns: AI systems can pose safety risks if they malfunction or are used maliciously, and can also raise privacy concerns if they collect and use personal data without consent.