"Dry periods in monsoon are extended"; "It now rains cats and dogs"; "It's November but not even moderately cold yet"; "It's warm even in February"; "It's unbearably hot in April and mostly will continue till June"; and so on...
These phrases have become a part of everyday conversations, especially among adults or older people who have witnessed these changes.
Not just the visible temperature and rainfall patterns, significant changes are also observed in occurrences and intensities of droughts, floods, and heatwaves (Readers can refer to IPCC AR6 2023 report for more details). A farmer working hard on his fields will be the best person to explain the difficulties caused by varying and annually unpredictable climate or weather patterns or droughts. Similarly, a daily urban commuter can better explain the consequences s/he has to face with extreme downpours of rain or heat waves. Whosoever it may be, an infant or an elder, everyone is facing the harshness of climate change, which will likely worsen with time.
The phenomenon known as global warming is primarily responsible (apart from the natural variations) for this systematic but rapid shift in seasonal instances, which alters the regional climatic patterns. The insight read-out provides concise yet extensive detail about climate change and the importance of climate datasets in identifying the signals of change. Have fun reading it, and don't hesitate to ask us if you have any questions!
Climate and Climate Change
Climate can be described as the long-term pattern of seasonal and annual variations in climate variables visible across regions, with each region having its distinctive characteristics, which vary in intensity, frequency, or the season itself. These characteristics can be of rainfall, temperature variations, humidity levels, wind speed and directions, and/or other atmospheric conditions.
Consequently, climate change can be referred to as any significant and long-term change in the patterns of these characteristics. It can be prominently measured (and mostly visible) in the form of rising regional to global temperatures, changes in precipitation patterns, increase in extreme weather events such as floods, droughts, and heatwaves, rising of sea water levels majorly due to the melting of glaciers and polar ice, and other countless impacts of these changes on the ecosystem. These impacts vary across geographical extents as well as magnitude. Policymakers often need a detailed analysis of climate-related changes and trends to measure, monitor, propose, and implement resilient and adaptive measures for a sustainable future. Under such lines, long-term climate information is essential to statistically understand these changes and their impact on hydrology, agriculture, society, economy, and the ecosystem as a whole.
Importance of Climate Data
Climate data is the backbone of any meaningful effort to understand, predict, and respond to climate change. It helps us decode historical patterns and detect emerging trends and provides the foundation for forecasting and scenario planning, which are essential for proactive decision-making. Because of its cross-cutting relevance, climate data underpins decision-making across multiple sectors:
- Informing Public Policy & Infrastructure: Reliable climate data enables policymakers to design evidence-based climate adaptation and mitigation strategies. For instance, urban planners can integrate rainfall and temperature projections to build flood-resilient infrastructure, while energy planners can use climate scenarios to optimize renewable energy production and grid stability.
- Supporting Agriculture & Food Security: Agricultural systems are highly climate sensitive. Climate datasets help identify shifts in rainfall, heat stress patterns, and drought risks, enabling the development of climate-resilient cropping systems, precision farming strategies, and early-warning systems for pest outbreaks or crop failures. Models like DSSAT and AquaCrop rely heavily on climate data to estimate crop yields under varying climate scenarios.
- Strengthening Public Health Preparedness: The rise in heat waves, vector-borne diseases, and air quality deterioration is directly linked to climate shifts. Climate data, combined with epidemiological models like DengueME or MalariaAtlas, helps forecast disease outbreaks, assess heat-health risks, and support public health interventions such as cooling centers or vaccination drives in high-risk zones.
- Managing Water Resources & Hydrology: Hydrological models use accurate climate inputs to simulate streamflow, groundwater recharge, and flood risks. This information informs reservoir operations, irrigation planning, and disaster preparedness for floods or droughts. Models such as VIC, SWAT, HEC-RAS, HEC-HMS, and others play a pivotal role in understanding the impacts of climate change at a regional, national, and international scale, with climate data as a significant input.
- Mitigating Financial & Insurance Risks: The insurance and reinsurance sectors increasingly rely on climate data to quantify financial exposure to natural hazards, price climate-linked insurance products, and perform catastrophe risk modeling. Accurate climate datasets help reduce uncertainty in estimating losses from extreme events like cyclones, floods, or heat waves.
- Tracking Emissions & Evaluating Climate Actions: Climate data is essential for monitoring the effectiveness of emission reduction strategies, carbon offset projects, and compliance with national and international climate commitments (e.g., Paris Agreement targets).
Overall, climate data transforms abstract notions of climate change into actionable insights. Whether it’s simulating future risks, guiding emergency response, or informing billion-dollar infrastructure investments, robust and accessible climate datasets reduce uncertainty and enable smarter, more resilient decisions across sectors.