Automated Quality control of meteorological observations


Automated Quality control of meteorological observations

A meteorological observation at a given place can be inaccurate for a variety of reasons, such as a hardware defect. Quality control can help spot which meteorological observations are inaccurate.

One of the main automated quality control program that is used today in the area of meteorological observations is the "Meteorological Assimilation Data Ingest System" (MADIS). [ [http://madis.noaa.gov/ Meteorological Assimilation Data Ingest System (MADIS) ] ]

History

Weather observation quality control systems verify probability, history, and trends. One of the main and simplest forms of quality control is the check of probability. Gandin, L., 1988: Complex Quality Control of Meteorological Observations. Monthly Weather Review, 116, 1137-1156. ] This check throws out impossible observations, such as the dew point being higher than the temperature or data outside acceptable ranges, such as temperatures over 200 degrees Fahrenheit. Another basic quality control check is to have the data compared to preset geographic extremes, DeGaetano, A., 1997: A Quality-Control Routine for Hourly Wind Observations. Journal of Atmospheric and Oceanic Technology, 14, 308-317.] perhaps combined with diurnal variations. However this only flags the data as uncertain because the station could be reporting correctly but there is no way to know. A better way is to correlate with previous observations as well as the other simple checks. Miller, P. and S. Benjamin, 1992: A System for the Hourly Assimilation of Surface Observations in Mountainous and Flat Terrain. Monthly Weather Review, 120, 2342–2359. ] This method uses one hour persistence to check the quality of the current observation. This method makes continuity of observations better since the system is able to make better judgments on whether the current observations are bad or not.

Current

Systems such as MADIS use a three-pronged approach. Graybeal, D., A. DeGaetano, and K. Eggleston, 2004: Improved Quality Assurance for Historical Hourly Temperature and Humidity: Development and Application to Environmental Analysis. Journal of Applied Meteorology,43, 1722-1735.] This approach is much better mainly because it has more information to compare the current observation to. The first part of the process is the limit check. As already described the program checks whether the observation is within predetermined limits that are set according to whether they can physically exist or not. The second part is the temporal check which compares the station to its closest surrounding stations. The third part is internal checking, which compares the observation to previous ones and sees whether it makes sense or not. It also takes into account present weather conditions so that the data is not considered bad just because the system is set for fair weather.

MADIS uses this current three-pronged approach for its quality control tests. They are organized into three different levels of checks. Level one is the validity tests, level two is the internal checks and also statistical spatial tests and level three is the spatial test. The level two statistical spatial test tests whether or not the station has failed any quality control check more than 75% of the time during the previous seven days. Once this has happened the station will continue to fail until it improves to failing only 25% of the time. The spatial check for the MADIS program also uses a reanalysis procedure. What this does is if there is a large difference between the station being checked and the station that it is being checked against then one of them is wrong. Instead of assuming that the station being checked is wrong, the program then moves on to the other stations that are near the one being checked. If the station that is being checked still is way off compared to most of the stations surrounding it then it is flagged as bad. However if the station is close to all of the other ones except for one then that one is bad.

References


Wikimedia Foundation. 2010.

Look at other dictionaries:

  • Ocean observations — The following are considered essential ocean climate variables by the OOPC[1][clarification needed] that are currently feasible with current observational systems. Contents 1 Ocean climate variables 1 …   Wikipedia

  • Ocean Prediction Center — OPC pressure forecast valid at 48 hours The Ocean Prediction Center (OPC), established in 1995, is one of the National Centers for Environmental Prediction’s (NCEP’s) original six service centers.[1] Until January 12, 2003, the name of the… …   Wikipedia

  • Weather forecasting — weather forecaster redirects here. For other uses, see Weatherman (disambiguation). Forecast of surface pressures five days into the future for the north Pacific, North America, and north Atlantic ocean. Weather forecasting is the application of… …   Wikipedia

  • Sea surface temperature — Weekly average sea surface temperature for the World Ocean during the first week of February 2011, during a period of La Niña …   Wikipedia

  • National Weather Service — NWS Agency overview Formed February 9, 1870 Jurisdiction …   Wikipedia

  • Atmospheric model — A 96 hour forecast of 850 mbar geopotential height and temperature from the Global Forecast System An atmospheric model is a mathematical model constructed around the full set of primitive dynamical equations which govern atmospheric motions. It… …   Wikipedia

  • Nobel Prizes — ▪ 2009 Introduction Prize for Peace       The 2008 Nobel Prize for Peace was awarded to Martti Ahtisaari, former president (1994–2000) of Finland, for his work over more than 30 years in settling international disputes, many involving ethnic,… …   Universalium

  • space exploration — Investigation of the universe beyond Earth s atmosphere by means of manned and unmanned spacecraft. Study of the use of rockets for spaceflight began early in the 20th century. Germany s research on rocket propulsion in the 1930s led to… …   Universalium

  • Earth Sciences — ▪ 2009 Introduction Geology and Geochemistry       The theme of the 33rd International Geological Congress, which was held in Norway in August 2008, was “Earth System Science: Foundation for Sustainable Development.” It was attended by nearly… …   Universalium

  • Weather radar — in Norman, Oklahoma with rainshaft …   Wikipedia