question: How do we get weather data and how come it's so unreliable sometimes?
comment: It’s a very very complicated system. There is a network of weather reporting systems. Meteorologists take the information reported from those systems and plug those into simulations. Unfortunately weather is extremely sensitive to tiny differences in measurements. Imaging a simulation running on the real data and a simulation with a hundredth of a degree difference in temperature from one weather station: their predictions would look very different after a while, even though they were almost entirely the same at the beginning. Since no weather reporting system can be precise to the point that we would be able to perfectly report the weather, it still varies quite a lot from our forecasts. A whole lot of unpredictable things that the reporting systems can’t catch end up being very influential.
passages: Section::::History.:AWS data as a teaching tool and TV broadcast use.:Criticisms and acceptance.
   Despite these concerns, meteorologists used AWS data to assist in the study of various weather phenomena, including the heat island effect. One such study, presented to the American Meteorological Society by Davey "et al." of Colorado State University, cited examples and placement of multiple AWS network sites.
   Section::::Current.
   It also has an improved graphics display and dynamic radar capabilities. HiRAD (High Resolution Aggregated Data) technology – which was added to the IntelliStar in 2006 – allows The Weather Channel to choose any city, town or landmark as an observation or forecast site and provide data. Occasionally, the HiRAD function will fail, in which case the National Weather Service sites are used (only the current conditions – and previously, the eight-city product and regional/metro products – are affected significantly).
   Section::::History.
  
  Section::::History.:Initial AWS methodology.
   Installation of SNOTEL began in the mid-1960s. Its use in climate forecasting was not originally envisioned, but it has become the standard climate data for western U.S. locations which are elevated sufficiently to have at least a seasonal snowpack. Ongoing algorithm upgrades correct and backfill missing data, while improvements in communications improve the overall quality of data collection.
  
  Section::::Meteor burst technology.
   BULLET::::- Meteorological Development Laboratory (MDL)
  
  BULLET::::- Climate, Water and Weather Services
  
  BULLET::::- 6 Regions (Eastern, Central, Southern, Western, Alaska & Pacific)
  
  BULLET::::- 122 Weather Forecast Offices (WFOs)
  
  BULLET::::- 21 Center Weather Service Units (CWSU)
  
  BULLET::::- 13 River Forecast Centers (RFC)
  
  BULLET::::- Pacific Tsunami Warning Center (PTWC)
  
  BULLET::::- National Tsunami Warning Center (NTWC)
  
  BULLET::::- Spaceflight Meteorology Group (SMG)
  
  Section::::Accuracy problems.
   Section::::History.:Network growth.
   Because climate change is a very political issue, interested parties could try to corrupt the data by, say, entering temperature figures that are too high or too low. Because three sets of records for each data point will be entered, any set from a digitiser showing a marked deviation from the other records should be easily checkable and eliminated. Large-scale fraud is unlikely because the data is entered one log page at a time, and so is immune to a spam type of attack. Collaborative projects such as Linux and Wikipedia have for the most part been able to rely on the transparent honesty of those taking part.
   BULLET::::- Michigan Automated Weather Network (MAWN)
  
  BULLET::::- Missouri Weather Stations
  
  BULLET::::- National Weather Service Cooperative Observer (COOP) program
  
  BULLET::::- New York State Mesonet
  
  BULLET::::- Oklahoma Mesonet
  
  BULLET::::- The Pacific Northwest Cooperative Agricultural Weather Network
  
  Section::::Networks.:Southern Hemisphere.
  
  BULLET::::- Antarctic Automatic Weather Stations Project
  
  BULLET::::- Australia: Bureau of Meteorology AWS network.
  
  BULLET::::- Australia: Department of Agriculture and Food Western Australia
  
  BULLET::::- Australia: Lower Murray Water Automatic Weather Station Network
  
  Section::::See also.
  
  BULLET::::- Global Telecommunications System
  
  BULLET::::- Lightning detection
  
  BULLET::::- Surface weather observation and surface weather analysis
  
  BULLET::::- Weather radar
  
  BULLET::::- Weather satellite
  
  BULLET::::- Wind profiler
  
  Section::::External links.
  
  BULLET::::- Citizen Weather Observer Program
   For instance, the French weather service, Météo-France, is using a software, named "ASPIC" to extrapolate to a fine scale the areas of precipitation. Other examples are "AutoNowcaster" which has been developed by UCAR to predict short term motion and evolution of thunderstorms, and private firms like ClimaCell using its proprietary HyperCast software for nowcasting precipitation type and intensity at 300-500 m geospatial resolution
  
  Section::::Usage.
   The FindU database is a set of privately operated Internet servers, run by Steve Dimse, (amateur radio callsign K4HG). Numerous IGates (Internet Gateways) receive broadcast amateur radio Automatic Packet Reporting System (APRS) packets containing position and short messages (including telemetry such weather observations), and forward the data to the FindU servers via APRS-IS on the Internet. Weather observations may be polled directly from FindU, and the data is forwarded to MADIS for ingest. APRS messages may also originate directly from computers on the Internet without being broadcast on the radio waves.
  
  Section::::Description.:MADIS.
   Unlike the automated airport weather stations which are located at significant airports, RAWS stations are often located in remote areas, particularly in national forests. Because of this, they usually are not connected to the electrical grid, but rather have their own solar panels, and a battery to store power for overnight reporting. Some instead run on a generator. In both cases, data important to operating the station itself, such as battery voltage or fuel level, is often included in the hourly reports.
   BULLET::::- a data logger
  
  BULLET::::- a satellite communications transmitter attached to a typical 10 foot (3 meter) instrument tower
  
  BULLET::::- at least one weighing rain gauge, encircled by a wind shield
   In use since 1960, the weather satellite is a type of satellite that is primarily used to monitor the weather and climate of the Earth. Satellites can be polar orbiting, covering the entire Earth asynchronously, or geostationary, hovering over the same spot on the equator. Meteorological satellites see more than clouds and cloud systems. Beginning with the Nimbus 3 satellite in 1969, temperature information through the atmospheric column began to be retrieved by satellites from the eastern Atlantic and most of the Pacific Ocean, which led to significant forecast improvements. City lights, fires, effects of pollution, auroras, sand and dust storms, snow cover, ice mapping, boundaries of ocean currents, energy flows, etc., and other types of environmental information are collected using weather satellites. Other environmental satellites can detect changes in the Earth's vegetation, sea state, ocean color, and ice fields. El Niño and its effects on weather are monitored daily from satellite images. Collectively, weather satellites flown by the U.S., Europe, India, China, Russia, and Japan provide nearly continuous observations for a global weather watch.
   A similar program, the Significant Weather Observing Program (SWOP), was begun independently in around the year 2000 by the National Weather Service Lincoln, Illinois. CoCoRaHS data supplements the more rigorous data from the national program with increased spatial and temporal resolution. Real-time data is also provided by the Citizen Weather Observer Program (CWOP), whose users operate weather stations that automatically report over the internet, and which supplements the more rigorous data reported by formal surface weather observation stations. The earliest and thus critically important for its long-term historical record from respective locations is the Cooperative Observer program of manually recorded daily summaries.
   The work described has resulted in a variety of datasets possessing different formats, time/space grids, periods of record and regions of coverage, input datasets, and analysis procedures, as well as many different forms of dataset version designators. In many cases, one of the modern multi-satellite data sets is the best choice for general use.
  
  Section::::Return period.
   As the Washington, D.C. metro area school systems bought into the concept, AWS began working on a way to better archive and manipulate the data generated for use as a teaching tool for computer science, mathematics, geography, and science. Students would log observations and then plot them on a local map, and a series of manually logged observations would be graphed as well. Eventually, an AWS subcontractor wrote a program that would automatically access the existing sites and download data for current observations as well as limited historical data. The program, which ran on desktop computers outfitted with 386 processors, then created graphs of historical data.
   Section::::Reliability.:Sayings which may be locally accurate.:Cloud movement.
   At an elevation of more than 6,000 feet (1,829 meters), the Mount Washington Observatory (MWO) in New Hampshire uses a FreeWave solution to capture data from six weather stations and transmit the data to an Ethernet-connected gateway. The data provides information such as temperature and wind speeds for MWO's climate research. Weather observations are reported to the National Weather Service and National Oceanic and Atmospheric Administration for use in nationwide and global forecasting models. 
   Additional sensor channels and products have been demonstrated to provide additional useful information including visible channels, additional IR channels, water vapor channels and atmospheric sounding retrievals. However, most precipitation data sets in current use do not employ these data sources.
  
  Section::::Measurement.:Satellite data sets.
   AWSs use sensors to take measurements of a variety of meteorological parameters. Those deployed for the Initiative conform to WMO specifications. These units are robust and able to withstand various environmental conditions, yet are economical to operate, calibrate and maintain. They are run on state of the art proprietary software able to handle the reporting of a large network of weather stations and able to detect faulty sensors remotely in real time.
  
  Among other things, automatic weather stations monitor:
  
  BULLET::::- Atmospheric pressure
  
  BULLET::::- Temperature
  
  BULLET::::- Humidity
  
  BULLET::::- Wind speed and direction
  
  BULLET::::- Precipitation
  
  BULLET::::- Sunshine and radiation
   Section::::History.:Creation of AWS network.
   Traditional weather forecasts rely on public data from the government entities. ClimaCell pioneered techniques using existing wireless communication infrastructure and IoT devices to collect real-time weather data. Their observations report conditions closer to the ground than satellite and higher resolution than Doppler weather radar techniques.
   Section::::Data acquisition.:Marine observations.
  