This dataset contains data on indicators of climate conditions in Austin for the period from January 1, 1999 to September 20, 2023 in order to study how the weather in Austin has changed over the past 25 years, to identify trends in global warming, such as rising temperatures which is a key indicator to monitor climate change and its impacts on populations. The following climate data includes temperature, humidity, precipitation, air pressure, cloud cover, sunrise, sunset, visibility, solar radiation, uvindex, wind speed, wind direction, etc.

The data was downloaded from https://www.visualcrossing.com/weather/weather-data-services# The Visual Crossing Weather Data platform provides the ability to easily access weather forecast data, historical weather observation data and historical summary data.

The City Council of Madrid allows to know at all times the meteorological data of the municipality. In this data set you can get the updated information in real time, updating this data every hour, and this update will be made between 20 and 30 minutes. Important: these real-time data are those that automatically leave the measuring stations and are pending review and validation. See the 'Interpretation of meteorological data' file below in the 'associated documentation' section. All related information can also be reviewed on the Air Quality Web as well as see the map of the weather network. Other air quality datasets are also available on this portal: Weather data. Daily data since 2019. Weather data. Timetable data since 2019 . Weather data. Control stations. Through the Visualization Portal ' Visualize Madrid with Open Data', the Madrid City Council puts at your disposal a visualization made with open data of Meteorological Data. Access the Weather Data visualization

The global weather visualization solutions market is projected to reach $158 million by 2033, expanding at a CAGR of 4.8% from 2025 to 2033. The increasing demand for accurate and real-time weather information for various applications, such as media and broadcasting, aviation, and agriculture, is driving the market growth. Furthermore, technological advancements in data analytics, artificial intelligence (AI), and machine learning (ML) are enhancing the capabilities of weather visualization solutions, making them more user-friendly and efficient. The market is segmented based on type (local and cloud-based) and application (media and broadcasting, aviation, agriculture, and others). The local segment currently holds a larger market share due to the high adoption of on-premise weather visualization solutions, particularly among organizations with stringent data security requirements. However, the cloud-based segment is expected to grow at a faster rate, driven by the increasing adoption of cloud computing and its benefits, such as flexibility, scalability, and cost-effectiveness. The media and broadcasting segment holds the largest market share due to the need for accurate weather information for live broadcasts and weather forecasting programs. The aviation segment is also growing significantly due to the increasing demand for real-time weather data for flight planning, route optimization, and passenger safety.

The Madrid City Council's Comprehensive Air Quality System includes the municipal meteorological network. In this dataset you can get the location of all control stations that can measure the following parameters: 81 - WIND SPEED 82 - DIR. WIND 83 - TEMPERATURE 86 - RELATIVE MOISTURE 87 - BARIOMETRIC PRESSURE 88 - SOLAR RADIATION 89 - PRECIPITATION Other air quality datasets are also available on this portal: Weather data. Daily data since 2019. Weather data. Timetable data since 2019 . Weather data. Real-time data Through the Visualization Portal ' Visualize Madrid with Open Data', the Madrid City Council puts at your disposal a visualization made with open data of Meteorological Data. Access the Weather Data visualization

Data is scraped from OpenWeather, National Weather Service, and Zip-Codes.com APIs to retrieve and display JSON weather information for U.S. cities. Additional information is scraped from the web and manipulated using the Beautiful Soup and Pandas libraries. | Column | Description | | --- | --- | | City | The name of the city. | | State | The state in which the city is located.. | |Date | The date on which the information was requested.| |Time| The time at which the information was requested.| |Weather | A general description of the weather at the current location.| | Current Temperature (Farenheit) |The current temperature of the location in Farenheit. | | High (Farenheit) |The current maximum recorded temperature at the current location.| |Low (Farenheit) | The current minimum recorded temperature at the current location.| | Atmospheric Pressure (hPa) | The atmospheric pressure of the current location. | |Humidity (Percentage) |The relative humidity of the current location. |

Weather Forecast System Market Outlook

The global weather forecast system market size, which was valued at approximately $3.5 billion in 2023, is anticipated to reach around $6.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 8% during this forecast period. This significant growth is driven by the increasing demand for accurate and timely weather forecasting services across various sectors. The rising adoption of advanced technologies such as artificial intelligence and machine learning to enhance the precision of weather prediction models is a major factor propelling the market forward. Furthermore, the growing need for sophisticated weather forecasting systems to mitigate the adverse impacts of climate change is further fueling market expansion.

One key growth factor in the weather forecast system market is the increasing frequency and severity of extreme weather events worldwide. These events, such as hurricanes, floods, and heatwaves, are driving governments and organizations to invest heavily in advanced forecasting systems to improve preparation and response efforts. The ability to predict such events with greater accuracy and lead time can significantly reduce their impact on human lives, infrastructure, and the economy. As climate change continues to influence weather patterns, the role of weather forecast systems becomes even more crucial, leading to increased investment and development in this sector.

Technological advancements play a pivotal role in the expansion of the weather forecast system market. The integration of cutting-edge technologies like big data analytics, machine learning, and the Internet of Things (IoT) has revolutionized the way weather data is collected, analyzed, and disseminated. These technologies enable the processing of vast datasets in real-time, resulting in more accurate and reliable forecasts. Additionally, the use of satellite technology and high-performance computing has enhanced the ability to monitor and predict weather conditions with unprecedented precision, driving the demand for advanced forecasting systems across various industries.

Another significant growth driver is the increasing demand for weather forecast systems from sectors such as agriculture, energy, and transportation. In agriculture, accurate weather forecasts are essential for optimizing planting and harvesting schedules, managing water resources, and reducing crop losses due to adverse weather conditions. Similarly, the energy sector relies on weather forecasts to manage the supply and demand of energy efficiently, especially for renewable energy sources like wind and solar power. In transportation, accurate weather forecasts are crucial for ensuring the safety and efficiency of operations, particularly in aviation and maritime industries. As these sectors continue to grow, the demand for advanced weather prediction systems is expected to rise, contributing to the market's expansion.

Regionally, the weather forecast system market exhibits varying growth patterns across different geographies. North America holds a significant share of the market due to the presence of established infrastructure and the early adoption of advanced technologies. The region's proactive approach to disaster management and climate change mitigation further facilitates market growth. Europe follows closely, with significant investments being made in upgrading weather forecasting capabilities to meet the region's environmental and economic challenges. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increasing investments in infrastructure development, and heightened awareness of climate-related risks. Meanwhile, Latin America and the Middle East & Africa are also anticipated to experience noteworthy growth, albeit at a relatively slower pace.

Component Analysis

The weather forecast system market can be segmented by component into software, hardware, and services, each playing a crucial role in the overall system's functionality and efficacy. The software component is integral to the market, comprising advanced algorithms and models used for data analysis and prediction. As weather forecast systems become more sophisticated, the demand for customized software solutions that can provide accurate and reliable forecasts increases. Software development in this segment focuses on enhancing user interfaces, improving data visualization, and integrating real-time data processing capabilities to offer more actionable insights to end-users across various sectors.

H

The global weather visualization market size was valued at USD 158 million in 2025 and is projected to grow at a CAGR of 4.8% during the forecast period (2025-2033). The increasing demand for weather information from various industries, such as media and broadcasting, aviation, and agriculture, is driving the growth of the market. Additionally, advancements in technology, such as the development of cloud-based platforms and artificial intelligence (AI), are contributing to market growth. North America and Europe are expected to hold the largest market shares during the forecast period. The presence of key players, such as Vizrt, Baron Services, and The Weather Company (IBM), in these regions is expected to contribute to their dominance. However, the Asia Pacific region is projected to witness the highest growth rate during the forecast period due to the increasing adoption of weather visualization solutions by media and broadcasting companies, as well as the growing demand from the aviation and agriculture sectors. This in-depth report provides comprehensive insights into the global weather visualization market, valued at over $100 million. It explores emerging trends, challenges, growth drivers, and competitive landscapes to empower decision-makers with actionable intelligence.

The Madrid City Council's Comprehensive Air Quality System includes the municipal meteorological network. In this data set you can obtain the information collected by the weather stations, with the hourly data, schedules by annuities since January 2019. All related information can also be reviewed on the Air Quality Web as well as see the map of the weather network. The weather network infrastructure was put in place in 2018. Madrid City Council does not have meteorological data prior to January 1, 2019. Other air quality datasets are also available on this portal: Weather data. Daily data since 2019. Weather data. Control stations. Through the Visualization Portal ' Visualize Madrid with Open Data', the Madrid City Council puts at your disposal a visualization made with open data of Meteorological Data. Access the Weather Data visualization

The NOAA Weather and Climate Toolkit is an application that provides simple visualization and data export of weather and climatological data archived at NCDC. The Toolkit also provides access to weather and climate web services provided from NCDC and other organizations. The Viewer provides tools for displaying custom data overlay, Web Map Services (WMS), animations and basic filters. The export of images and movies is provided in multiple formats. The Data Exporter allows for data export in both vector point/line/polygon and raster grid formats. Current data types supported include: CF-compliant Fridded NetCDF; Generic CF-compliant Irregularly-Spaced/Curvilinear Gridded NetCDF/HDF; GRIB1, GRIB2, GINI, GEMPAK, HDF(CF-compliant) and more gridded formats; GPES Satellite AREA Files; NEXRAD Radar Data(Level-II and Level-III); U.S. Drought Monitor Service from the National Drought Mitigation Center (NDMC); OPeNDAP support for Gridded Datasets

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Weather Forecasting Services Market Size 2025-2029

The weather forecasting services market size is forecast to increase by USD 1.6 billion, at a CAGR of 11.8% between 2024 and 2029.

The market is driven by the increasing reliance on accurate weather information in various sectors, particularly agriculture and renewable energy. Farmers heavily depend on weather forecasting services to optimize crop production and mitigate potential losses due to extreme weather conditions. Additionally, the production of renewable energy, such as wind and solar, is heavily influenced by weather patterns, making precise weather forecasting essential for efficient energy generation and grid management. However, the market faces challenges in providing reliable and accurate weather forecasts due to the complexities of weather forecasting models. These models require vast amounts of data and sophisticated algorithms to account for various weather patterns and climate conditions. Ensuring the accuracy and reliability of these models is a significant challenge for market participants, as even minor errors can result in substantial consequences for industries and individuals relying on the forecasts. Companies must invest in advanced technologies and research to improve the accuracy of their weather forecasting models and maintain their competitive edge in this market.

What will be the Size of the Weather Forecasting Services Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market is characterized by continuous evolution and dynamic market activities. Agribusinesses, energy sectors, marine industries, and various other sectors rely on accurate and real-time meteorological data for effective decision-making. Weather forecasting encompasses a range of applications, from agricultural applications that monitor crop growth and irrigation needs to marine applications that ensure safe navigation and marine resource management. Data processing, machine learning, and data analytics play pivotal roles in enhancing forecast accuracy and providing valuable insights. Numerical weather prediction models, data assimilation techniques, and ensemble forecasting methods are essential components of advanced forecasting systems. These technologies enable the prediction of extreme weather events, such as hurricanes, storms, and tornadoes, ensuring public safety and emergency preparedness. Web-based platforms and mobile apps facilitate easy access to weather information, while data licensing and subscription services offer customized solutions for businesses. Satellite imagery and climate data contribute significantly to the understanding of atmospheric conditions and long-term trends. Consulting services provide expert advice on weather risk management, climate change mitigation, and business intelligence. The market's ongoing development is driven by technological advancements, such as cloud computing, data visualization, and artificial intelligence, which enhance data processing capabilities and improve forecast accuracy. Data security and data integrity are crucial concerns, as the market continues to grow and expand its applications across various industries. The market is a dynamic and ever-evolving landscape, with ongoing developments in technology, applications, and market trends. Its significance extends beyond mere weather prediction, as it plays a crucial role in various sectors, from agriculture to energy, transportation, and public safety.

How is this Weather Forecasting Services Industry segmented?

The weather forecasting services industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeMedium-rangeLong-rangeShort-rangeNowcastingApplicationEnergy and utilitiesAviationMedia and consumerLogistics and transportationOthersMethodGround-basedSatellite-basedModel-basedGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW).

By Type Insights

The medium-range segment is estimated to witness significant growth during the forecast period.The market encompasses various applications, including hurricane forecasting, storm tracking, and severe weather warnings. Service providers offer medium-range forecasts, which can extend from three to four days to two weeks. According to NOAA and ECMWF, a 5-day forecast holds a 90% accuracy rate, while a 7-day forecast maintains an 80% accuracy rate. These entities, acting as both research institutes and operational services, generate global numerical weather forecasts and meteorological data for numerous stakeholders. Their advanced supercomputer facilities and extensive

Market Size and Drivers: The global weather visualization platform market is projected to reach a market value of million by 2033, exhibiting a CAGR of 4.8% from 2025 to 2033. This growth is attributed to the increasing adoption of weather visualization platforms in media and broadcasting, aviation, agriculture, and other industries. The demand for real-time and accurate weather information, combined with the proliferation of high-speed internet and the emergence of advanced technologies like artificial intelligence and machine learning, are key drivers of the market. Segment Analysis and Competitive Landscape: Based on type, the market is segmented into local and cloud-based platforms. Cloud-based platforms are expected to dominate the market due to their scalability, cost-effectiveness, and convenience. In terms of application, the media and broadcasting, aviation, and agriculture sectors account for a significant share of the market. The competitive landscape is dominated by established players such as Vizrt, Baron Services, The Weather Company (IBM), MetraWeather, AccuWeather, and Sefaira (by Trimble), among others. These companies offer a wide range of weather visualization solutions, including real-time data, predictive analytics, and interactive visualizations.

[NOTE - 2022-09-07: this dataset is superseded by an updated version https://doi.org/10.15482/USDA.ADC/1526433 ] This dataset consists of weather data for each year when maize was grown for grain at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Maize was grown for grain on four large, precision weighing lysimeters, each in the center of a 4.44 ha square field. The four square fields are themselves arranged in a larger square with the fields in four adjacent quadrants of the larger square. Fields and lysimeters within each field are thus designated northeast (NE), southeast (SE), northwest (NW), and southwest (SW). Irrigation was by linear move sprinkler system in 1989, 1990, and 1994. In 2013, 2016, and 2018, two lysimeters and their respective fields (NE and SE) were irrigated using subsurface drip irrigation (SDI), and two lysimeters and their respective fields (NW and SW) were irrigated by a linear move sprinkler system. Irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. The weather data include solar irradiance, barometric pressure, air temperature and relative humidity, and wind speed determined using sensors placed at 2-m height over a level, grass surface mowed to not exceed 12 cm height and irrigated and fertilized to maintain reference conditions as promulgated by ASCE (2005) and FAO (1996). Irrigation was by surface flood in 1989 through 1994, and by subsurface drip irrigation after 1994. Sensors were replicated and intercompared between replicates and with data from nearby weather stations, which were sometimes used for gap filling. Quality control and assurance methods are described by Evett et al. (2018). These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on maize ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used by the Agricultural Model Intercomparison and Improvement Project (AgMIP), by OPENET, and by many others for testing, and calibrating models of ET that use satellite and/or weather data. Resources in this dataset: Resource Title: 1989 Bushland, TX, standard 15-minute weather data. File Name: 1989_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: The weather data are presented as 15-minute mean values of solar irradiance, air temperature, relative humidity, wind speed, and barometric pressure; and as 15-minute totals of precipitation (rain and snow). Daily total precipitation as determined by mass balance at each of the four large, precision weighing lysimeters is given in a separate tab along with the mean daily value of precipitation. Data dictionaries are in separate tabs with names corresponding to those of tabs containing data. A separate tab contains a visualization tool for missing data. Another tab contains a visualization tool for the weather data in five-day increments of the 15-minute data. An Introduction tab explains the other tabs, lists the authors, explains data time conventions, explains symbols, lists the sensors, and datalogging systems used, and gives geographic coordinates of sensing locations. Resource Title: 1990 Bushland, TX, standard 15-minute weather data. File Name: 1990_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1990. Resource Title: 1994 Bushland, TX, standard 15-minute weather data. File Name: 1994_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1994. Resource Title: 2013 Bushland, TX, standard 15-minute weather data. File Name: 2013_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 2013. Resource Title: 2016 Bushland, TX, standard 15-minute weather data. File Name: 2016_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 2016. Resource Title: 2018 Bushland, TX, standard 15-minute weather data. File Name: 2018_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 2018. Resource Title: 1996 Bushland, TX, standard 15-minute weather data. File Name: 1996_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1996. Resource Title: 1997 Bushland, TX, standard 15-minute weather data. File Name: 1997_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1997. Resource Title: 1998 Bushland, TX, standard 15-minute weather data. File Name: 1998_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1998. Resource Title: 1999 Bushland, TX, standard 15-minute weather data. File Name: 1999_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1999.

The global weather service market, valued at $3122.9 million in 2025, is projected to experience robust growth, driven by increasing demand for accurate weather forecasting across diverse sectors. A compound annual growth rate (CAGR) of 9.1% from 2025 to 2033 indicates significant market expansion. This growth is fueled by several key factors. The agricultural sector relies heavily on precise weather information for optimized planting, irrigation, and harvesting, driving demand for specialized agricultural weather services. Similarly, the industrial sector utilizes weather data for risk management, particularly in transportation, energy, and construction, where adverse weather conditions can significantly impact operations and profitability. The media and individual sectors also contribute to market growth, as access to accurate and timely weather information has become increasingly crucial for daily planning and safety. Furthermore, advancements in technology, including the integration of artificial intelligence and machine learning, are enhancing the accuracy and efficiency of weather forecasting models, contributing to the overall market expansion. The market is segmented by service type (Public Meteorological Service, Decision Weather Service, Professional Meteorological Service) and application (Agricultural, Industrial, Media and Individuals, Transportation, Others), offering a diverse range of specialized services to cater to varying needs. Geographic expansion, particularly in developing economies with growing infrastructure and technological advancements, presents significant opportunities for market growth. The competitive landscape is characterized by a mix of established players and emerging companies. Key players like The Weather Company and Weathernews Inc. are leveraging their technological expertise and extensive data networks to maintain a strong market presence. However, the market also exhibits opportunities for smaller, specialized firms focusing on niche applications or regional markets. Regulatory frameworks concerning data privacy and the accuracy of weather forecasts are expected to shape market dynamics in the coming years. Continued investments in research and development, particularly in improving the accuracy of long-range forecasts and enhancing data visualization tools, will play a crucial role in shaping future market trends. Despite potential restraints like the inherent uncertainties associated with weather prediction and the need for continuous technological upgrades, the overall outlook for the weather service market remains positive, propelled by a growing reliance on accurate weather information for various applications.

The global weather app market is experiencing robust growth, projected to be valued at $472.1 million in 2025. While the provided CAGR is missing, considering the increasing smartphone penetration, advancements in weather forecasting technology (like hyperlocal forecasting and AI-powered predictions), and the rising demand for personalized weather information, a conservative estimate of the Compound Annual Growth Rate (CAGR) for the forecast period (2025-2033) would be around 12%. This suggests a significant expansion of the market, driven by factors such as improved accuracy and enhanced user experience features offered by weather applications. The market segmentation highlights a strong presence across various operating systems (Android and iOS) and diverse application sectors, including agriculture, navigation, and aviation, indicating broad appeal and utility. The presence of numerous established players (AccuWeather, The Weather Channel, Dark Sky - now part of Apple, etc.) and emerging competitors signifies a competitive landscape with ongoing innovation in features and functionalities, such as interactive maps, severe weather alerts, and personalized weather dashboards. This competitive environment fosters continuous improvements in accuracy, user experience, and data visualization, further fueling market growth. Geographic distribution shows a significant market presence across North America and Europe, with considerable potential for growth in Asia-Pacific and other regions as smartphone adoption and internet penetration increase. The market's continued expansion will likely be fueled by several key trends. Increased adoption of IoT devices and integration with smart home systems creates opportunities for weather apps to deliver contextualized information. The growing importance of accurate weather data for various industries, especially agriculture and logistics, will drive demand for specialized weather apps. Furthermore, advancements in machine learning and artificial intelligence will lead to more accurate and timely weather predictions, enhancing the value proposition of these apps. Despite the potential for increased competition, the market will continue to grow due to the fundamental need for accurate and reliable weather information across various demographics and applications. Challenges might include data privacy concerns and the need for consistent accuracy across different geographical locations and weather conditions.

Dataset

This dataset was created by Ahmed Shuja

Contents

Campus Weather Station Market Outlook

In 2023, the global campus weather station market size was valued at approximately USD 350 million and is projected to reach around USD 650 million by 2032, growing at a compounded annual growth rate (CAGR) of 7.5% during the forecast period. The growth of this market is attributed to several factors, including increased climate awareness, advancements in weather prediction technologies, and the rising need for educational and research institutions to monitor and analyze weather patterns accurately.

One of the primary growth factors driving the campus weather station market is the increasing awareness about climate change and its impact on various aspects of life. Governments and educational institutions are becoming more proactive in monitoring weather conditions to better understand climate patterns and their consequences. This heightened awareness has led to a surge in the installation of weather stations in campuses across the globe. Additionally, the integration of advanced technologies such as IoT, AI, and machine learning into weather stations has significantly improved the accuracy and efficiency of weather data collection and analysis, further fueling market growth.

Another significant factor contributing to the market's growth is the growing importance of weather data in various sectors such as agriculture, aviation, and disaster management. Educational institutions and research facilities are increasingly utilizing campus weather stations to gather precise weather data for research purposes and to enhance the educational experience of students studying meteorology and related fields. The data collected from these weather stations is also crucial for government agencies involved in planning and implementing disaster management strategies, making them indispensable tools in mitigating the effects of natural disasters.

The increasing trend of smart campuses is also playing a pivotal role in the market's expansion. Modern campuses are integrating smart technologies to create more efficient and sustainable environments. Campus weather stations are an integral part of these smart infrastructures, providing real-time weather data that can be used to optimize energy consumption, manage water resources, and ensure the safety and comfort of campus occupants. This trend is expected to continue, driving further growth in the market.

From a regional perspective, North America and Europe are currently the leading markets for campus weather stations, primarily due to the presence of numerous educational and research institutions, as well as government support for climate monitoring initiatives. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increasing investments in smart city projects, and a growing focus on climate change mitigation. Latin America and the Middle East & Africa are also anticipated to experience steady growth, supported by government efforts to enhance weather monitoring infrastructure.

Component Analysis

When segmenting the campus weather station market by component, we observe four primary categories: sensors, data loggers, software, and services. Sensors form the backbone of any weather station, capturing critical data such as temperature, humidity, wind speed, and precipitation levels. Advances in sensor technology have led to more accurate and reliable data collection, which is essential for weather forecasting and climate research. Modern sensors are often equipped with IoT capabilities, allowing for real-time data transmission and remote monitoring, significantly enhancing their utility.

Data loggers are another crucial component of campus weather stations. These devices store the vast amounts of data collected by sensors for future analysis. The evolution of data loggers has been marked by improvements in data storage capacity, durability, and connectivity options. Today's data loggers often come with wireless capabilities, enabling seamless data transfer to cloud-based platforms where it can be accessed and analyzed remotely. This is particularly useful for educational and research institutions that require long-term data storage and easy access to historical weather data.

Software solutions play a significant role in the processing, analysis, and visualization of weather data. Advanced software platforms can integrate data from multiple sensors and data loggers, providing comprehensive and actionable insights. These platforms often come with features such

This dataset presents daily meteorological observations collected from the official government website of the Delhi region. The data includes measurements of mean temperature, humidity, wind speed, and mean pressure recorded over a period of time. The inspiration behind compiling this dataset lies in the necessity for researchers, environmentalists, and policymakers to access accurate and up-to-date climate information for the Delhi area. By providing this dataset sourced directly from governmental sources, it aims to support various stakeholders in conducting climate research, analyzing weather patterns, and making informed decisions related to environmental policies and practices.

This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

The global weather app market is experiencing robust growth, with a market size of $249 million in 2025 and a projected Compound Annual Growth Rate (CAGR) of 9.6% from 2025 to 2033. This expansion is driven by several key factors. The increasing reliance on smartphones and mobile devices for information access fuels demand for convenient, readily available weather updates. Furthermore, the incorporation of advanced features like hyperlocal forecasting, interactive radar maps, and severe weather alerts enhances user engagement and app stickiness. The growing adoption of IoT devices and the integration of weather data into smart home systems contribute to market expansion. Segmentation within the market reveals strong demand across both Android and iOS systems, with applications catering to diverse sectors including agriculture, navigation, and aviation, reflecting the versatile utility of precise weather information. The competitive landscape is populated by a diverse range of established and emerging players, ranging from well-known weather services like AccuWeather and The Weather Channel to specialized apps focused on niche markets. This competition fosters innovation and drives improvements in accuracy, features, and user experience. The continued growth trajectory is expected to be propelled by advancements in meteorological technology and data analytics, enabling more accurate and detailed predictions. Expansion into emerging markets, particularly in Asia Pacific and regions with increasing smartphone penetration, represents significant growth opportunities. However, the market faces some challenges. Data privacy concerns and the potential for inaccuracies in weather forecasting could dampen growth if not adequately addressed. Furthermore, the increasing saturation of the app market necessitates continuous innovation and differentiation to maintain a competitive edge. The market's evolution will likely see a shift towards personalized weather services, advanced data visualization, and seamless integration with other smart technologies.

The portable weather station market is experiencing robust growth, driven by increasing demand for hyperlocal weather information among both consumers and professionals. The market, valued at approximately $800 million in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated value exceeding $1.4 billion by 2033. This growth is fueled by several key factors. The rising popularity of smart home technology and the integration of weather data into home automation systems are significant contributors. Furthermore, increasing awareness of extreme weather events and the need for accurate, real-time weather information for safety and planning purposes are driving adoption across various segments. The market segments are well-defined: applications include home and commercial use, while product types encompass indoor and outdoor stations. Key players like Davis Instruments, Ambient Weather, and Netatmo are actively innovating to meet consumer demand for enhanced features, such as improved accuracy, connectivity, and data visualization capabilities. The growing popularity of outdoor activities and gardening is also boosting the demand for portable weather stations, particularly in regions with unpredictable weather patterns. Geographical distribution reveals strong market presence across North America and Europe, which are expected to continue dominating the market share due to high adoption rates and technological advancement. However, rapidly developing economies in Asia-Pacific, particularly China and India, are emerging as lucrative markets for portable weather stations, fueled by rising disposable incomes and increasing urbanization. Challenges such as high initial investment costs and competition from free weather apps may present some restraints; however, the benefits of accurate, localized weather data outweigh these drawbacks for many users, ensuring consistent market expansion. The diverse range of models available, catering to various budgets and needs, further contributes to the market's sustained growth trajectory.