This dataset contains synthetic weather data generated for ten different locations, including New York, Los Angeles, Chicago, Houston, Phoenix, Philadelphia, San Antonio, San Diego, Dallas, and San Jose. The data includes information about temperature, humidity, precipitation, and wind speed, with 1 million data points generated for each parameter.

Features:

• Location: The city where the weather data was simulated.
• Date_Time: The date and time when the weather data was recorded.
• Temperature_C: The temperature in Celsius at the given location and time.
• Humidity_pct: The humidity in percentage at the given location and time.
• Precipitation_mm: The precipitation in millimeters at the given location and time.
• Wind_Speed_kmh: The wind speed in kilometers per hour at the given location and time.

Additional Information:

• Variability and Complexity: The dataset incorporates variability and complexity to simulate realistic weather patterns. For example, adjustments have been made to temperature and precipitation based on seasonal variations observed in certain locations. In New York, higher temperatures and precipitation are simulated during the summer months, while in Phoenix, lower temperatures and increased precipitation are simulated during the winter months.
• Data Generation Method: The dataset was generated using Python's Faker library to create synthetic weather data for each location. Random values within realistic ranges were generated for temperature, humidity, precipitation, and wind speed, with adjustments made to reflect seasonal variations.

Potential Use Cases:

• Weather Prediction Models: Researchers and data scientists can use this dataset to develop and train weather prediction models for various locations.
• Climate Studies: The dataset can be used for climate studies and analysis to understand weather patterns and trends in different regions.
• Educational Purposes: Students and educators can use this dataset to learn about data analysis, visualization, and modeling techniques in the context of weather data.

Acknowledgements:

• This dataset was generated using Python's Faker library.
• Special thanks to the Faker library developers for providing tools to create synthetic data for various purposes.

Image Credits :

Image by Mohamed Hassan from Pixabay

The global weather visualization software market is booming, projected to reach $166 million by 2033 with a 4.9% CAGR. Discover key market trends, leading companies (Vizrt, AccuWeather, IBM), and growth drivers in this in-depth analysis.

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. |

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

Historical and current climate data visualization with trends analysis

Weather Graphics Visualization Market Outlook

According to our latest research, the Global Weather Graphics Visualization market size was valued at $1.4 billion in 2024 and is projected to reach $3.2 billion by 2033, expanding at a CAGR of 9.7% during 2024–2033. This robust growth is primarily fueled by the increasing demand for real-time, high-resolution weather data visualization across sectors such as broadcast meteorology, aviation, and energy. The proliferation of advanced meteorological technologies, coupled with the rising frequency and severity of extreme weather events globally, has prompted organizations to invest in sophisticated weather graphics visualization solutions. These tools not only enhance the accuracy of weather forecasts but also improve public communication and operational decision-making, driving the market’s expansion on a global scale.

Regional Outlook

North America currently holds the largest share of the Weather Graphics Visualization market, accounting for over 38% of global revenue in 2024. This dominance can be attributed to the region’s mature broadcast meteorology sector, widespread adoption of cutting-edge visualization software, and strong presence of leading technology vendors. The United States, in particular, boasts a well-established infrastructure for weather data collection and dissemination, supported by robust government funding and proactive policy frameworks. Additionally, the high frequency of severe weather events, such as hurricanes and tornadoes, necessitates advanced visualization tools for timely and effective public communication. The integration of artificial intelligence and machine learning into weather graphics platforms further enhances their predictive capabilities, cementing North America’s leadership position in this market segment.

The Asia Pacific region is experiencing the fastest growth in the Weather Graphics Visualization market, with a projected CAGR of 12.4% during the forecast period. This rapid expansion is driven by significant investments in meteorological infrastructure, growing awareness of climate change impacts, and increasing demand for accurate weather forecasting in sectors like agriculture, transportation, and energy. Countries such as China, Japan, and India are at the forefront of adopting advanced weather visualization solutions, propelled by government initiatives aimed at disaster management and public safety. The region’s burgeoning media and entertainment industry also contributes to the adoption of sophisticated broadcast meteorology graphics, further accelerating market growth. Strategic partnerships between local technology firms and global solution providers are fostering innovation and enhancing the regional market’s competitive edge.

Emerging economies in Latin America, the Middle East, and Africa are gradually adopting weather graphics visualization technologies, although their market share remains comparatively modest. In these regions, challenges such as limited access to high-quality meteorological data, budget constraints, and a shortage of skilled professionals impede rapid adoption. Nevertheless, localized demand is rising, especially in sectors vulnerable to weather fluctuations, such as agriculture and energy. Policy reforms and international collaborations are beginning to address infrastructure gaps, while tailored solutions that consider regional climatic conditions and language requirements are gaining traction. As these economies continue to modernize their meteorological capabilities, the potential for growth in weather graphics visualization remains significant, albeit at a measured pace compared to more developed markets.

Report Scope

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 daily 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. Time 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

Historical weather data visualization covering temperature, humidity, heat index, and discomfort index for global cities

Year:

Type: Numeric Description: Represents the year of the recorded data. This column is useful for time series analysis and observing trends over the years. Country:

Type: Categorical (Factor) Description: Indicates the country where the data was collected. This column helps in comparing data across different countries. Region:

Type: Categorical (Factor) Description: Specifies the region within the country. Useful for more granular analysis within countries, such as regional climate differences or yield variations. Crop_Type:

Type: Categorical (Factor) Description: Identifies the type of crop being analyzed (e.g., wheat, rice, corn). Helps in analyzing the impact of environmental factors on different crops. Average_Temperature_C:

Type: Numeric Description: The average temperature (in degrees Celsius) recorded during the growing season. Important for studying the impact of temperature on crop yield. Total_Precipitation_mm:

Type: Numeric Description: Total precipitation (in millimeters) during the growing season. Essential for understanding the effect of rainfall on crop growth and yield. CO2_Emissions_MT:

Type: Numeric Description: CO2 emissions (in metric tons) associated with agricultural activities or the region. Useful for studying the relationship between emissions and agricultural productivity. Crop_Yield_MT_per_HA:

Type: Numeric Description: The crop yield measured in metric tons per hectare. This is the target variable for understanding how environmental factors affect agricultural productivity. Extreme_Weather_Events:

Type: Categorical (Factor) or Numeric (Count) Description: Indicates the presence or number of extreme weather events (e.g., droughts, floods) that occurred during the growing season. Key for studying the impact of weather extremes on crop yield. Irrigation_Access_%:

Type: Numeric Description: Percentage of the crop area that has access to irrigation. This column helps in evaluating the impact of irrigation on crop yields and mitigating climate effects.

Weather Graphics Visualization Market Outlook

According to our latest research, the global weather graphics visualization market size in 2024 stands at USD 1.38 billion, driven by the increasing demand for advanced weather visualization tools across multiple industries. The market is experiencing a robust growth trajectory, with a CAGR of 8.7% forecasted from 2025 to 2033. By the end of 2033, the market is projected to reach USD 2.93 billion, reflecting the expanding adoption of real-time weather graphics visualization solutions. The primary growth factor for this market is the rising need for accurate, timely, and visually engaging weather data across sectors such as broadcast meteorology, aviation, and emergency management, which are increasingly relying on sophisticated visualization technologies for improved decision-making and operational efficiency.

The growth of the weather graphics visualization market is fundamentally fueled by technological advancements in data analytics, visualization software, and high-performance computing. As weather data becomes more granular and complex, organizations require robust visualization platforms that can process and display this information in real-time, enabling actionable insights. The proliferation of high-resolution satellite imagery, radar data, and IoT-enabled weather sensors has significantly enhanced the quality and quantity of meteorological data available. This, in turn, has driven demand for advanced weather graphics solutions capable of integrating diverse data sources and presenting them in intuitive, interactive formats. Additionally, the integration of artificial intelligence and machine learning algorithms into weather visualization tools is further augmenting their predictive capabilities, allowing stakeholders to anticipate and respond to weather events with greater accuracy and speed.

Another significant growth driver is the increasing emphasis on public safety and disaster management. Governments and emergency response agencies worldwide are investing heavily in state-of-the-art weather graphics visualization systems to facilitate efficient communication and coordination during extreme weather events. These visualization tools are critical for disseminating real-time weather updates, warnings, and forecasts to both officials and the general public. In the energy sector, accurate weather visualization is essential for optimizing grid operations, managing renewable energy resources, and mitigating the impact of adverse weather on infrastructure. Similarly, the aviation and marine industries rely on precise, real-time weather graphics to ensure safe navigation and operational continuity. The growing frequency and intensity of weather-related disruptions have underscored the importance of advanced visualization solutions, resulting in sustained market growth.

The ongoing digital transformation across various industries is also propelling the adoption of cloud-based weather graphics visualization solutions. Cloud deployment offers significant advantages, including scalability, cost-effectiveness, and remote accessibility, making it an attractive option for organizations seeking to modernize their meteorological operations. The shift towards cloud-based platforms is particularly pronounced among broadcasting companies and government agencies aiming to streamline workflows and enhance collaboration. Furthermore, the increasing penetration of mobile devices and high-speed internet has enabled the widespread dissemination of weather graphics to a broader audience, further amplifying market demand. As organizations continue to prioritize digital innovation and operational resilience, the weather graphics visualization market is poised for sustained expansion over the forecast period.

Regionally, North America remains the dominant market for weather graphics visualization, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of leading technology providers, advanced meteorological infrastructure, and a high level of awareness regarding the benefits of visualization tools underpin North America's leadership. Meanwhile, Asia Pacific is witnessing the fastest growth, driven by rapid urbanization, increased investments in weather monitoring infrastructure, and rising climate-related risks. The region's expanding aviation, energy, and broadcasting sectors are also fueling demand for advanced weather graphics solutions. Europe, with its stringent regulatory standards and focus on en

The size of the Weather Visualization Software market was valued at USD 158 million in 2024 and is projected to reach USD 219.37 million by 2033, with an expected CAGR of 4.8 % during the forecast period.

[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.

Weather Graphics Systems Market Outlook

As per our latest research, the global weather graphics systems market size reached USD 525 million in 2024, reflecting robust demand across multiple sectors. The market is anticipated to expand at a CAGR of 7.2% during the forecast period, projecting a value of USD 970 million by 2033. This growth is primarily driven by the increasing demand for real-time weather visualization, technological advancements in meteorological data processing, and the rising integration of AI and machine learning within weather graphics solutions. The surge in digital broadcasting, coupled with the critical need for accurate and visually engaging weather information, continues to propel the market forward.

One of the primary growth factors for the weather graphics systems market is the escalating demand for high-quality, real-time weather data visualization across industries such as broadcasting, aviation, marine, and agriculture. Broadcasters, in particular, are seeking advanced graphics solutions to enhance viewer engagement and deliver precise, up-to-date weather forecasts. These systems enable meteorologists to present complex data in an accessible and visually appealing format, thereby improving public understanding and safety. Additionally, the proliferation of digital and online media has intensified the need for compelling weather presentations, further fueling market expansion.

Technological innovation plays a pivotal role in the evolution of weather graphics systems. The integration of artificial intelligence, machine learning algorithms, and cloud computing has significantly enhanced the capabilities of these systems. Modern weather graphics platforms can now process vast amounts of meteorological data in real time, enabling dynamic and interactive visualizations. This technological leap not only improves the accuracy and timeliness of weather reporting but also allows for greater customization and automation, which are highly valued by both broadcasters and enterprise users. The increasing adoption of cloud-based deployment models is also facilitating remote access and collaboration, thus expanding the market’s reach.

Another critical driver is the growing importance of weather data in sectors beyond broadcasting. Industries such as aviation, marine, energy, and agriculture rely heavily on precise weather information for operational planning and risk management. Weather graphics systems provide these sectors with actionable insights, enabling informed decision-making and enhancing safety protocols. For instance, in aviation, real-time weather graphics are essential for flight planning and air traffic management, while in agriculture, these systems support crop management and yield optimization. The expanding application landscape is broadening the market’s scope and attracting new end-users.

From a regional perspective, North America continues to dominate the weather graphics systems market, accounting for the largest revenue share in 2024. This leadership is attributed to the presence of established broadcasting networks, significant investments in meteorological infrastructure, and a high level of technological adoption. Europe follows closely, with strong demand from public and private weather agencies, while the Asia Pacific region is witnessing the fastest growth, driven by increasing digitalization, urbanization, and government initiatives to enhance weather forecasting capabilities. Latin America and the Middle East & Africa are also experiencing steady growth, albeit from a smaller base, as awareness and investment in advanced weather systems increase.

Component Analysis

The component segment of the weather graphics systems market is categorized into hardware, software, and services, each playing a unique role in the industry’s value chain. Hardware components, such as high-performance workstations, display units, and data acquisition devices, form the backbone of weather graphics systems. These components are critical for the real-time processing and visualization of meteorological data, ensuring that end-users receive accurate and timely information. The demand for advanced hardware has been bolstered by the need for higher resolution displays and faster data processing capabilities, particularly in broadcasting and aviation applications.

Software solutions are the core enablers of dynamic a

This dataset contains daily meteorological observations spanning several years. The data includes various atmospheric measurements and weather conditions, organized in a tabular format. Below is a summary of the data fields:

Columns and Description: Y, M, D: Year, Month, and Day of the observation. T: Mean temperature (°C). TM: Maximum temperature (°C). Tm: Minimum temperature (°C). SLP: Sea Level Pressure (in hPa, if applicable). STP: Station Level Pressure (in hPa, if applicable). H: Relative Humidity (%). PP: Precipitation (mm). VV: Visibility (km). V: Mean wind speed (m/s). VM: Maximum sustained wind speed (m/s). VG: Gust speed (m/s). FG: Fog indicator (1 if fog is observed, 0 otherwise). RA: Rain indicator (1 if rain is observed, 0 otherwise). SN: Snow indicator (1 if snow is observed, 0 otherwise). GR: Graupel (small hail) indicator (1 if observed, 0 otherwise). TS: Thunderstorm indicator (1 if observed, 0 otherwise). TR: Tornado indicator (1 if observed, 0 otherwise).

Weather Graphics Systems Market Outlook

According to our latest research, the global weather graphics systems market size reached USD 1.48 billion in 2024, with a robust compound annual growth rate (CAGR) of 7.1%. This market is witnessing substantial growth, driven by increasing demand for real-time, visually engaging weather data across diverse industries. By 2033, the market is forecasted to reach USD 2.76 billion, propelled by technological advancements in data visualization and the integration of artificial intelligence for enhanced weather prediction and display. The growing need for accurate and timely weather information, especially in sectors such as broadcasting, aviation, and energy, is a key growth factor shaping the industry’s trajectory.

A primary driver of the weather graphics systems market is the escalating demand for advanced meteorological visualization tools in broadcast meteorology. As television and digital media platforms strive to deliver compelling and easily understandable weather updates, the adoption of high-definition and interactive weather graphics systems has surged. These systems enable broadcasters to present complex meteorological data in an intuitive and visually appealing format, enhancing viewer engagement and comprehension. The increasing frequency of extreme weather events globally has further amplified the importance of accurate and timely weather reporting, pushing media organizations to invest heavily in state-of-the-art weather graphics solutions. Moreover, the proliferation of digital and mobile platforms has extended the reach of weather graphics systems beyond traditional television, fostering market expansion.

Another significant growth factor is the integration of weather graphics systems into critical sectors such as aviation, marine, and energy. In aviation, real-time weather visualization is crucial for flight planning, route optimization, and ensuring passenger safety. Similarly, the marine industry relies on accurate weather graphics to support navigation and operational decisions, particularly in regions prone to severe weather conditions. The energy sector, especially renewable energy operations like wind and solar farms, depends on precise weather data visualization for operational efficiency and risk mitigation. The convergence of weather graphics systems with IoT devices, big data analytics, and cloud computing has empowered these industries to access, interpret, and act on meteorological data more effectively, thereby boosting demand for sophisticated graphics solutions.

Technological advancements are fundamentally transforming the weather graphics systems market. The adoption of artificial intelligence and machine learning algorithms has enhanced the predictive capabilities of these systems, enabling more accurate and dynamic weather visualizations. Cloud-based deployment models are gaining traction due to their scalability, cost-effectiveness, and ability to deliver real-time updates across multiple locations. Furthermore, the integration of augmented reality (AR) and virtual reality (VR) technologies is revolutionizing how meteorological data is presented, offering immersive experiences for both professionals and the general public. These innovations are not only improving the accuracy and reliability of weather forecasts but are also opening new avenues for market growth by expanding the application scope of weather graphics systems.

Regionally, North America continues to dominate the weather graphics systems market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of leading technology providers, high investment in broadcast and meteorological infrastructure, and stringent regulatory standards for weather reporting contribute to North America’s market leadership. Europe’s market is characterized by strong demand from government agencies and commercial enterprises, particularly in the aviation and energy sectors. Meanwhile, Asia Pacific is witnessing the fastest growth, fueled by rapid urbanization, increasing frequency of extreme weather events, and significant investments in digital infrastructure. Emerging economies in Latin America and the Middle East & Africa are also showing promising growth potential, driven by rising awareness of climate risks and the need for advanced weather monitoring solutions.

Comprehensive climate data reports for Temperature in Central New York for 2025. View daily, monthly, and seasonal weather statistics with detailed analysis and color-coded 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

Global Weather Forecast Software Market is segmented by Application (Agriculture_ Disaster Management_ Event Planning), Type (Forecasting Software_ Data Visualization Tools_ Climate Monitoring), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)