This dataset provides 15+ years of daily rainfall data across all Indian states and union territories, from January 2009 to July 2024. It has been sourced from the official India Water Resources Information System (India-WRIS) and is ideal for climate research, weather prediction, and agricultural analytics.

The dataset includes:

• Actual, forecasted, and normal rainfall values
• Deviation from historical average
• State-level granularity across 28 states and 8 union territories
• Over 200,000 observations in total

🧠 Use Cases

• Time series forecasting using ML models (ARIMA, LSTM, Prophet)
• Climate trend analysis and anomaly detection
• Monsoon behavior modeling
• Crop planning and irrigation optimization
• Educational projects in data science and meteorology

📁 Features

🌐 Source

India Water Resources Information System (WRIS)

🔗 indiawris.gov.in/wris

Rainfall in India (Year by Year)

Investigating Changes Over Time

By Rajanand Ilangovan [source]

About this dataset

This dataset contains the annual rainfall data for each subdivision in India from 1901 to 2015. Looking at this data, one can track and compare the amount of rain different parts of India get across a span of 115 years. The insights derived from this dataset can be useful for weather forecasting, crop production, and water management planning. It contains field values including SUBDIVISION that has names of different subdivisions in India, YEAR with the year value ranging from 1901 to 2015 , JAN to DEC with monthly rainfalls values, ANNUAL providing total annual rainfall in millimeters (mm) and Jan-Feb, Mar-May , Jun-Sep & Oct-Dec (total precipitation in mm). This comprehensive dataset can help uncover vital information related to droughts or an overabundance of rain that may have occurred during a particular time period across various parts of India

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How to use the dataset

• This dataset contains annual rainfall data in millimeters (mm) for each subdivision in India from 1901 to 2015. The dataset is broken down into 19 columns containing different pieces of information regarding rainfall in India. This guide will explain how you can use this data and what different values mean to make the most out of this resource.

• The first column is SUBDIVISION which denotes the name of the subdivision such as Andaman & Nicobar Islands, etc. The following columns then are used for displaying yearly rainfall data for each subdivision starting with YEAR representing numeric values from 1901 to 2015 which are self explanatory and followed by 12 months from January- December denoted by JAN- DEC respectively . These values represent the monthly rainfall amounts in mm during that month in a given YEAR, aggregated over all subdivisions present in the corresponding column. For example: JAN 2188 value implies that all subdivisions listed have a total monthly rainfall amount for January in 2001 equal to 2188mm combined without accounting any irregularities( flooding or drought). The following two columns, ANNUAL and Jan-Feb provide an overview of this Annual Rainfall Data providing annual totals along with cumulative Jan-Feb total respectively as named outlines prior. This would allow users to assess these numbers holistically rather having to navigate through every single month’s individual values making it easier and quicker reference point when comparing with other datasets or sources relevant like reports on regional water resources that could be beneficial when working on related research projects or just simply understanding local precipitation patterns across India while trying do certain macro climate studies e.g; monsoon frequency variation seasonally .

• The last three Columns are Mar-May, Jun Sep and Oct - Dec providing cumulative totals from last 3 relevant months distributed over 6 or 9 sub divisions per column (i.,e Mar -may being 3 months long etc) thus organizing it logically based on seasonal time scheme rather than strictly under 12 calendar Months resulting a cleaner more organized structure overall and describes averages generated over those shorter time sequences permitting user’s analysis fast efficient and simple without having crunch through large amount relative records .

• Thus concluding my guide giving you simple yet comprehensive overview using Subdivision Annual Rainfall In India 1901 –2015 dataset at Kaggle let us discuss some interesting topics such as investigating changing precipitation pattern across India while comparing them against global atmospheric phenomenon like El Niño seasons A/O explaining/ understanding relationships between event temperature fluctuations concurrently alongside how they ultimately effect various kinds natural

Research Ideas

• Using the January-February, March-May, June-September, and October-December subtotals for each subdivision's rainfall in India for the 1901 to 2015 timeframe, one can build a tool to predict seasonal shortfalls or excesses of precipitation and plan accordingly. This could be beneficial for farmers who must make decisions on what crops they should plant based on expected rainfall levels.
• The dataset can be used to identify longterm trends in precipitation levels by examining data over an extended period of time and making predictions about future changes in rainfall amounts by accounting for variables such as global warming and El Niño cycles. This is valuable knowledge when assessing irrigation needs or purchasing insurance...

Rainfall: All India: Normal data was reported at 7.000 mm in 18 Mar 2026. This records an increase from the previous number of 6.300 mm for 11 Mar 2026. Rainfall: All India: Normal data is updated weekly, averaging 7.400 mm from Jan 2008 (Median) to 18 Mar 2026, with 933 observations. The data reached an all-time high of 68.700 mm in 29 Jul 2009 and a record low of 0.600 mm in 24 Jan 2024. Rainfall: All India: Normal data remains active status in CEIC and is reported by India Meteorological Department. The data is categorized under India Premium Database’s Environment – Table IN.EVB: Rainfall: by Region: Weekly.

In 2023, the annual rainfall measured across India amounted to ***** millimeters. This was a decrease from around ***** millimeters of rainfall recorded one year earlier. The month of July saw the highest amount of rainfall in 2023 across the country.

Rainfall: All India: Actual data was reported at 11.600 mm in 18 Mar 2026. This records an increase from the previous number of 0.500 mm for 11 Mar 2026. Rainfall: All India: Actual data is updated weekly, averaging 5.100 mm from Jan 2008 (Median) to 18 Mar 2026, with 933 observations. The data reached an all-time high of 96.000 mm in 31 Jul 2019 and a record low of 0.000 mm in 27 Jan 2010. Rainfall: All India: Actual data remains active status in CEIC and is reported by India Meteorological Department. The data is categorized under India Premium Database’s Environment – Table IN.EVB: Rainfall: by Region: Weekly.

*This dataset provides a century-long, monthly and seasonal rainfall patterns across various Indian regions.*

*Spanning from 1901 to 2017, it includes monthly precipitation levels (January to December), annual totals, and seasonal aggregates: January-February (JF), March-May (MAM), June-September (JJAS), and October-December (OND).*

*The India Meteorological Department (IMD) collects rainfall data through a comprehensive and scientifically established network of meteorological observatories, radars, and other monitoring systems*:

1. Data Collection Infrastructure:

Rain Gauges: IMD operates a network of manual and automatic rain gauges across India, including in remote and rural areas. These gauges measure precipitation levels in millimeters daily, monthly, and seasonally.

Automatic Weather Stations (AWS): Modern AWS installations record rainfall, temperature, humidity, and other parameters in real-time. Data from these stations are transmitted electronically to central IMD databases.

Meteorological Observatories: Over 550 observatories in India record rainfall and other weather parameters regularly, contributing to long-term datasets.

Radars and Satellites: Doppler Weather Radars (DWR) and satellites like INSAT and Megha-Tropiques provide complementary data to monitor precipitation, especially during monsoons and extreme weather events.

2. Data Recording and Compilation:

Daily Data Collection: Data from rain gauges and observatories is recorded daily and transmitted to regional centers. This ensures high-resolution monitoring.

Seasonal and Annual Aggregation: Rainfall data is grouped into monthly, seasonal, and annual aggregates for ease of analysis. Key seasons include:

JF (January-February): Winter

MAM (March-May): Pre-Monsoon

JJAS (June-September): Monsoon

OND (October-December): Post-Monsoon

Regional Sub-Divisions: Data is analyzed regionally, divided into 36 meteorological sub-divisions, ensuring localized insights into precipitation trends.

3. Data Processing and Quality Assurance:

Standardization: Data is calibrated and standardized to remove inconsistencies, ensuring reliability across different regions and timeframes.

Historical Adjustments: For century-long datasets (1901–2017), older records are digitized, verified, and aligned with modern measurements for consistency.

Validation: IMD employs statistical methods and cross-references data with satellite observations to validate accuracy.

4. Dissemination of Data:

Mausam IMD Platform: Processed data is published on the IMD website (https://mausam.imd.gov.in/) and through the National Data Sharing and Accessibility Policy (NDSAP) portal on data.gov.in.

Research Reports and Forecasts: IMD regularly publishes reports, forecasts, and climate assessments for research, policy-making, and public awareness.

Key Features of the Dataset:

Timeframe: 1901 to 2017, providing over a century of rainfall data.

Granularity: Includes monthly, seasonal, and annual rainfall statistics.

Coverage: Regional coverage across India's 36 meteorological sub-divisions.

*The dataset supports climate research, policy-making, and data-driven insights into precipitation patterns in India over the past century.*

Source and Licensing:

Source: Sub Divisional Monthly Rainfall from 1901 to 2017.

Data sourced from data.gov.in, published under the National Data Sharing and Accessibility Policy (NDSAP)

https://www.data.gov.in/resource/sub-divisional-monthly-rainfall-1901-2017

Contributed by Ministry of Earth Sciences and India Meteorological Department.

https://mausam.imd.gov.in/

License: This dataset is licensed under the Government Open Data License – India (GODL). For more details on the license, visit: GODL License Terms - https://www.data.gov.in/Godl

Disclaimer:

This dataset is intended for research and analysis. The Ministry of Earth Sciences, IMD, and data.gov.in do not endorse any conclusions derived from this data. Verification of methodologies is recommended before applying it to decision-making.

The Rainfall catalogue contains station-wise data from CWC, Gujarat water resources department, and APWRIMS; and gridded data from IMD & NRSC. Further, this module also shows the daily Normal rainfall as per the IMD up to the district level.

Attribution: Data obtained from data.gov.in, licensed under Government Open Data License – India (GODL). Dataset Title: Daily data of NRSC rainfall Dataset URL: https://www.data.gov.in/resource/daily-data-nrsc-rainfall#api

Domain: Open Government Data(OGD) Platform India

The Dataset contains year wise actual annual rainfall across the meteorological sub divisions in India. The information is collated from RBI's Handbook of Statistics on States and is based on the information received from Indian Meteorological Department.

Note: From 2020 onwards, Jammu & Kashmir includes data for UT of Jammu & Kashmir and UT of Ladakh

This Dataset contains year, month and India Meteorological Department (IMD) sub division wise actual rainfall data

Note: 1. Data for 2024 is available only for South West Monsoon months (June to September) 2. normal_rainfall is for the years 1971-2020. The India Meteorological Department (IMD) uses data from 1971-2020 to define the current normal rainfall for India, which is 868.6 mm annually and 868.6 mm for the southwest monsoon season. This updated Long Period Average (LPA) represents a 50-year average, replacing previous normals based on data from 1961-2010.

Rainfall: All India: Deviation data was reported at -86.000 % in 04 Mar 2026. This records a decrease from the previous number of -70.000 % for 25 Feb 2026. Rainfall: All India: Deviation data is updated weekly, averaging 93.000 % from Jan 2008 (Median) to 04 Mar 2026, with 931 observations. The data reached an all-time high of 528.000 % in 12 Jan 2022 and a record low of -99.000 % in 27 Jan 2010. Rainfall: All India: Deviation data remains active status in CEIC and is reported by India Meteorological Department. The data is categorized under India Premium Database’s Environment – Table IN.EVB: Rainfall: by Region: Weekly.

This dataset offers an in-depth glimpse into the rainfall patterns of India for the month of July 2023, as meticulously recorded by the India Meteorological Department (IMD) using their advanced grid model system.

Usability & Application:

• Agricultural Planning: With India's agrarian economy heavily reliant on monsoon rains, this dataset serves as a pivotal tool for farmers and agricultural bodies to strategize planting and harvesting activities.
• Water Resource Management: Authorities can utilize this data to manage water reservoir levels, ensuring optimal water storage and distribution across regions.
• Environmental Research: Climate researchers can employ this data to understand the monsoon behaviors, track changes, and forecast potential future patterns.
• Urban Planning: For cities that face the challenges of flooding during the monsoon, this dataset can be instrumental in designing better drainage and infrastructure solutions.

Importance: India's monsoon season is not just a weather phenomenon; it plays a vital role in the country's economy, ecology, and way of life. By delving into this dataset, one can glean valuable insights into rainfall distribution, intensity, and variability, critical for diverse sectors from agriculture to urban planning.

Note: It's crucial to mention that the dataset does not include data for the Andaman and Nicobar Islands due to multiple null values. Potential users should consider this when analyzing regional rainfall patterns.

Source

India Meteorological Data includes 3 separate datasets acquired from the India Meteorological Department: Daily District Normals (daily climatological normals for nine different variables, published in 2008); India Rainfall Data 1901 series; and India Rainfall Data 1951 series. The two rainfall datasets consist of grids of latitude-longitude points that representing the daily rainfall across India over time, but are calculated using two different data sources. For more information, please see the README.

From Wikipedia, the free encyclopedia

A scene in Uttarakhand's Valley of Flowers National Park. In contrast to the rain shadow region of Tirunelveli, the park receives ample orographic precipitation due to its location in a mountainous windward-facing region wedged between the Zanskars and the Greater Himalayas. Daytime view of a chain of snow-capped mountains. They advance diagonally thumb from the far-middle distance at left to the nudge distance at right. In the foreground are high montaine meadows and brushband. The formation of the Himalayas (pictured) during the Early Eocene some 52 mya was a key factor in determining India's modern-day climate; global climate and ocean chemistry may have been affected.[1]

The climate of India consists of a wide range of weather conditions across a vast geographic scale and varied topography. Based on the Köppen system, India hosts six major climatic sub types, ranging from arid deserts in the west, alpine tundra and glaciers in the north, and humid tropical regions supporting rain forests in the southwest and the island territories. Many regions have starkly different microclimates, making it one of the most climatically diverse countries in the world. The country's meteorological department follows the international standard of four seasons with some local adjustments: winter (December to February), summer (March to May), monsoon or rainy season (June to September), and a post-monsoon period (October and November).

India's geography and geology are climatically pivotal: the Thar Desert in the northwest and the Himalayas in the north work in tandem to create a culturally and economically important monsoonal regime. As Earth's highest and most massive mountain range, the Himalayas bar the influx of frigid katabatic winds from the icy Tibetan Plateau and northerly Central Asia. Most of North India is thus kept warm or is only mildly chilly or cold during winter; the same thermal dam keeps most regions in India hot in summer. The climate in South India is generally warmer, and more humid due to its coastlines. However some hill stations in South India such as Ooty are well known for their cold climate.

Though the Tropic of Cancer—the boundary that is between the tropics and subtropics—passes through the middle of India, the bulk of the country can be regarded as climatically tropical. As in much of the tropics, monsoonal and other weather patterns in India can be strongly variable: epochal droughts, heat waves, floods, cyclones, and other natural disasters are sporadic, but have displaced or ended millions of human lives. Such climatic events are likely to change in frequency and severity as a consequence of human-induced climate change. Ongoing and future vegetative changes, sea level rise and inundation of India's low-lying coastal areas are also attributed to global warming.[2]

Rainfall: Daily: Past 24 Hours: New Delhi data was reported at 0.000 mm in 27 Mar 2026. This stayed constant from the previous number of 0.000 mm for 26 Mar 2026. Rainfall: Daily: Past 24 Hours: New Delhi data is updated daily, averaging 0.000 mm from Oct 2009 (Median) to 27 Mar 2026, with 5701 observations. The data reached an all-time high of 228.100 mm in 28 Jun 2024 and a record low of 0.000 mm in 27 Mar 2026. Rainfall: Daily: Past 24 Hours: New Delhi data remains active status in CEIC and is reported by India Meteorological Department, Pune. The data is categorized under India Premium Database’s Environment – Table IN.EVB: Rainfall: Daily: Past 24 Hours.

The "Daily_Rainfall_data_from_India_Meteorological_Department_Agency_during_January_2024" dataset provides detailed information about daily rainfall measurements recorded by the India Meteorological Department (IMD) Agency throughout January 2024. The dataset likely includes data points such as date, location or station where rainfall was measured, rainfall amount in millimeters or centimeters, and possibly additional metadata such as weather conditions during the measurements.

This dataset can be valuable for various analyses and applications, including but not limited to:

1. Rainfall Patterns: Analyzing the daily rainfall patterns to understand trends, variability, and anomalies in precipitation during January 2024 across different regions in India.

2. Weather Forecasting: Utilizing historical rainfall data to improve short-term and long-term weather forecasting models, which can be crucial for agricultural planning, disaster preparedness, and infrastructure management.

3. Climate Studies: Incorporating the rainfall data into broader climate studies to assess the impact of climate change on precipitation patterns over time.

4. Water Resource Management: Assessing the impact of rainfall on water resources, including groundwater recharge, reservoir levels, and water availability for various sectors like agriculture, industry, and domestic use.

5. Risk Assessment: Using rainfall data to assess the risk of floods, landslides, and other natural disasters associated with heavy precipitation events.

Overall, this dataset serves as a valuable resource for researchers, meteorologists, policymakers, and various stakeholders interested in understanding and leveraging rainfall data for a wide range of applications and studies related to weather and climate in India.

Rainfall: Daily: Past 24 Hours: Vishakhapatnam data was reported at 0.000 mm in 01 Dec 2018. This stayed constant from the previous number of 0.000 mm for 30 Nov 2018. Rainfall: Daily: Past 24 Hours: Vishakhapatnam data is updated daily, averaging 0.000 mm from Oct 2009 (Median) to 01 Dec 2018, with 2961 observations. The data reached an all-time high of 183.000 mm in 01 Nov 2010 and a record low of -8.000 mm in 18 Oct 2011. Rainfall: Daily: Past 24 Hours: Vishakhapatnam data remains active status in CEIC and is reported by India Meteorological Department, Pune. The data is categorized under India Premium Database’s Agriculture Sector – Table IN.RIS012: Rainfall: Daily: Past 24 Hours.

Explore the rich history of rainfall in India with this dataset, spanning 115 years from 1901 to 2015. Providing sub-division wise monthly rainfall data, this comprehensive resource allows researchers, climatologists, and policymakers to analyze and understand the intricate patterns and variations in India's precipitation over more than a century. Ideal for studying climate trends, agricultural planning, and water resource management.

Rainfall: Daily: Past 24 Hours: Dehra Dun data was reported at 0.000 mm in 01 Dec 2018. This stayed constant from the previous number of 0.000 mm for 30 Nov 2018. Rainfall: Daily: Past 24 Hours: Dehra Dun data is updated daily, averaging 0.000 mm from Oct 2009 (Median) to 01 Dec 2018, with 3119 observations. The data reached an all-time high of 370.200 mm in 17 Jun 2013 and a record low of 0.000 mm in 01 Dec 2018. Rainfall: Daily: Past 24 Hours: Dehra Dun data remains active status in CEIC and is reported by India Meteorological Department, Pune. The data is categorized under India Premium Database’s Agriculture Sector – Table IN.RIS012: Rainfall: Daily: Past 24 Hours.

Rainfall: Daily: Past 24 Hours: Bangalore data was reported at 0.000 mm in 27 Mar 2026. This stayed constant from the previous number of 0.000 mm for 26 Mar 2026. Rainfall: Daily: Past 24 Hours: Bangalore data is updated daily, averaging 5.000 mm from Oct 2009 (Median) to 27 Mar 2026, with 5346 observations. The data reached an all-time high of 131.600 mm in 05 Sep 2022 and a record low of 0.000 mm in 27 Mar 2026. Rainfall: Daily: Past 24 Hours: Bangalore data remains active status in CEIC and is reported by India Meteorological Department, Pune. The data is categorized under India Premium Database’s Environment – Table IN.EVB: Rainfall: Daily: Past 24 Hours.

Dataset

This dataset was created by Jayanti Prasad

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