Meteorology. Agreement concerning the conduct of a pro- gram known as the Equatorial Mesoscale Ex- periment, with related letter. Exchange of notes at Canberra January 5, 1987; entered into force January 5, 1987. TIAS PACIFIC SETTLEMENT OF DISPUTES Treaty amending in their application to Aus- tralia certain provisions of the treaty for the advancement of peace between the United States and the United Kingdom signed at Washington September 15, 1914. Signed at Washington September 6, 1940; entered into force August 13, 1941. 55 Stat. 1211; TS 974; 5 Xxxxxx 143.
Meteorology. Table 5-1 summarizes the meteorological measurements validated at 5-minute time resolution for the period 5/8/01-6/30/02. Parameters marked with an asterisk (*) were continuously measured (1 second frequency except barometric pressure and precipitation) with averaging to 5-minute intervals and calculations of 5-minute standard deviations performed by the datalogger. Table 5-1. Meteorological parameters validated at 5-minute resolution. Parameter Units Sensor (all Climatronics) scalar mean wind speed at 10m* m/s 102083-G0-H0 anemometer vector wind speed at 10m m/s standard deviation of wind speed at 10m m/s unit vector wind direction at 10m* °N 102083-G0-H0 wind vane resultant vector wind direction at 10m °N Xxxxxxxxx standard deviation of wind direction at 10m deg Xxxxxxxx sigma-theta at 10m deg temperature at 10 m* °C 100093 thermocouple standard deviation of temperature at 10m °C temperature at 2m* °C standard deviation of temperature at 2m °C temperature at 2m minus temperature at 10m °C standard deviation of temperature at 2m minus temperature at 10m °C relative humidity* % 102425 lithium chloride sensor standard deviation of relative humidity % solar radiation* W/m2 CM3 102318 pyranometer standard deviation of solar radiation W/m2 barometric pressure* hPa 102270-G3 barometer standard deviation of barometric pressure hPa total period precipitation* mm 100097-1-G0 tipping bucket maximum wind gust at 10m m/s 102083-G0-H0 anemometer time of maximum wind gust at 10m hh:mm CST wind direction of maximum wind gust at 10m °N 102083-G0-H0 wind vane Solar Radiation Solar radiation was measured using a Climatronics CM3 102318 pyranometer and validated at 5-minute time resolution. The manufacturer-reported zero offset is less 15 W/m2 at 200 W/m2 thermal radiation. Using October – December 2002 hourly data, the average of the reported hourly standard deviation in solar radiation is 0.4 W/m2 for hours with negative solar radiation reported (nighttime conditions). Using three times this metric as a crude estimate for the MDL, the solar radiation MDL would be 1.2 W/m2. A DRI site audit in October 2002 included collocation of a continuously measuring Xxxxxx Precision Spectral Pyranometer (PSP) which was installed near the site sensor with an exposure as close to that of the site sensor as possible. Nighttime data (1700 through 0500 CST) were excluded from the comparison since the sensors read zero within the measurement precision. Figure 5-1a shows the collocated hourl...
Meteorology. The Atmosphere interacts with and affects all earth systems, it is therefore required that Earth Science students demonstrate competency in Meteorology. Students will demonstrate competency by: • Listing the primary gaseous components of the atmosphere and explaining the importance of each. • Explaining why the atmosphere has the observed vertical temperature, density, and pressure profiles that it has. • Applying the first law of thermodynamics and the ideal gas law to the atmosphere. • Describing the short and longwave radiation balance of the earth/atmosphere system, and explaining how that radiation balance influences climate and weather. • Describing the details of the earth’s orbit around the sun, and explaining how this earth/sun geometry influences the seasons. • Listing and explaining the major factors that control the daily and seasonal temperatures. • Describing how humidity is quantified and measured, and how to convert between the various measures of humidity. • Describe how temperature and moisture determine the stability of the atmosphere, and explain how stability influences cloud and storm development. • Applying the skew-t diagram to determining atmospheric static stability and cloud development. • Listing the types and characteristics of the various clouds found in the atmosphere. • Explaining how precipitation is formed, measured, and what determines the type of precipitation reaching the ground. • Applying Xxxxxx’x second law of motion to the atmosphere. • Quantitatively describing geostrophic, hydrostatic, and gradient wind balance, and conceptually explaining departures from a balanced state. • Explaining how pressure gradient force, Coriolis force, and friction determine the wind direction and speed. • Describe how the vertical wind shear of the geostrophic wind relates to the horizontal temperature gradient. • Listing the various scales of atmospheric motion, and providing examples of each. • Explaining how the various scales of atmospheric motion interact. • Describing how local wind systems develop and are maintained. • Describing how the global circulation of the atmosphere is maintained. • Listing the characteristics of the different types of air masses, and explaining how the air masses are formed. • Defining a front, and explaining why fronts are regions of active weather. • Listing the cloud sequences and other characteristics of warm, cold, occluded, and stationary fronts. • Describing the horizontal and vertical structure ...
Meteorology. HSPF and QUAL2Kw require time series data inputs representing precipitation and potential evapotranspira- tion (PET) at a minimum over the watershed. In addition, time series data inputs for air temperature, dew point, wind speed, cloud cover, and solar radiation are required to simulate stream water temperature. Long- term time series are desirable to perform simulations that reflect a wider range of potential conditions. Table 4-2 and Table 4-3 summarize the meteorological data sources available for this effort. Table 4-2. Meteorological Data Sources Data Model Units Calibration Pe- riod Data Source Long-term Simulation Data Source a, b Source for Filling Data Gaps Precipitation inch(es) per hour WSU Puyallup Sea-Tac, WSU Puyallup, XxXxxxxx Reservoir, Canyon Road Neighboring gages, based on the closest gage with available data (WSU Puyallup, Sea-Tac, or King County) PET inch(es) per hour WSU Puyallup c WSU Puyallup Monthly average value Air temperature degree(s) Fahrenheit WSU Puyallup Sea-Tac, WSU Puyallup Average of adjacent time steps; monthly average for large data gaps Dew point tem- perature degree(s) Fahrenheit WSU Puyallup Sea-Tac, WSU Puyallup Average of adjacent time steps; average monthly daily minimum temperature for large data gaps Wind speed mile(s) per hour WSU Puyallup Sea-Tac, WSU Puyallup Average of adjacent time steps; neighboring gages for large data gaps Cloud cover Tenths of sky dome (0–10) Sea-Tac d Sea-Tac Mean monthly cloud cover estimates based on two cloud cover values: (a) 1 for days without precipitation; and (b) 1 for days with precipitation Solar radiation Xxxxxxx per hour WSU Puyallup Sea-Tac, WSU Puyallup Average of adjacent time steps; monthly average for large data gaps
Meteorology. Agreement relating to a cooperative program to improve and modernize the Iranian meteoro- logical services, with annexes. Signed at Tehran November 26, 1977; entered into force November 26, 1977. 29 UST 5546; TIAS 9127; 1134 UNTS 359. MISSIONS, MILITARY Agreement relating to the privileges and im- munities granted American military and non- military technicians assisting in the moderniza- tion program of the Imperial Iranian Armed Forces. Exchange of notes at Tehran May 24 and 30, 1973; entered into force May 30, 1973. 25 UST 3048; TIAS 7963.
Meteorology. Knowledge of shipborne meteorological instruments and their application. Knowledge of the characteristics of various weather systems, reporting procedures and recording systems and the ability to apply the meteorological information available.
Meteorology. 4.5.1 The potential for the dispersion of air pollution is very much dependent on local factors such as wind speed and direction, and atmospheric stability.
Meteorology. 3.1.1. Freely available data Real-time atmospheric observations from a multitude of sources are being shared globally via the Global Telecommunication System (GTS) of the WMO Information System (WIS). GTS is implemented and operated by National Meteorological Services and International Organizations, such as ECMWF and EUMETSAT, to ensure that all WMO Members have timely and reliable access to all meteorological and related data, forecasts and alerts. GTS data are exchanged according to WMO Resolution 40 (Cg. XII) and Resolution 25 (Cg XIII) for meteorological, and hydrological data respectively. Annex 1 to Resolution 40 defines a set of essential data that each member shall exchange without charge and with no conditions on use. Each member should provide as many data as possible, but at least those that will assist in defining the state of the atmosphere at least on a scale of the order of 200 km horizontal resolution and six to 12 hours in time. The essential data thus include, 6-hourly SYNOP data, all marine in situ observations, all available aircraft reports as well as all data from upper air sounding networks.
Meteorology. A primary focus of this work is to investigate the influence of meteorological conditions, and in particular, high-energy wind events (storms), on inner shelf processes in Louisiana. Annually, average wind speed in coastal Louisiana is approximately 3 m s-1 from the southeast. Since wind conditions vary considerably over the course of the year, however, storm climatology is most conveniently represented by means of two “seasons”—a summer season lasting roughly from April to November, and a winter season comprising the remainder of the year. During the summer months, coastal Louisiana’s weather is dominated by Maritime Tropical air masses centered over the Gulf of Mexico. This almost always results in uniformly hot, humid, and calm weather, aside from localized convectional thunderstorm activity. Infrequent but often very powerful tropical cyclones (tropical storms and hurricanes), do occur, however, during this time. Tropical storms and hurricanes have made landfall on the Louisiana coast during the past century once every 3.3 and 4.0 years, respectively, with the highest frequency in September (Stone et al., 1997). Tropical cyclones can obviously be extremely high-energy events; for example, sustained winds during Hurricane Xxxxxxx, which struck the Louisiana coast in 1969, were in excess of 100 m s-1 (Stone et al., 1997). The impact of such storms on a particular section of coast, while potentially dramatic however, is highly variable, and depends upon the intensity, duration, and track of the individual cyclone. Since no tropical cyclones influenced the study area during the deployment period, however, no further discussion of such events is included. From approximately November to April, extratropical, or mid-latitude, meteorological systems dominate coastal Louisiana’s weather. Since mid-latitude meteorology is controlled by a complex interrelationship of air masses, cyclones, anticyclones and fronts, only a brief overview is offered here, although more detailed references are abundant (e.g. Moran and Xxxxxx, 1994). Ultimately, extratropical storms are the result of Rossby waves generated by heat transfer along the polar front, which forms the global boundary between tropical and polar air masses (Xxxxxxxxx-Xxxxxxx and Xxxxxxxx, 1986). Synoptic-scale storms are initiated along this front through cyclogenesis, a regular sequence of events that commences when an area of strong divergence in the upper atmosphere causes a drop in surface air pressure and ...
Meteorology. As a first approach, general trends have been defined for meteorology for the United States and could be used to define typical meteorological inputs for specific areas. Figure 5.1 and Figure 5.2 how these attributes for thermal mixing (based on incoming solar radiation) and wind speed, respectively30. Similar data for temperature (minimums and maximum by season), inversion heights, and precipitation are also available. While figures are shown here for clarity, the information is also available in tabular form. This information could be used to develop general inputs for meteorology by area directly, interpolating in some cases (e.g., wind speeds by time of day) and integrating in other cases (e.g., atmospheric stability). In some cases developing such general inputs would be a very straight forward process for State DOTs. In Florida, for example, this would be very easy to implement as similar trends exist throughout the state. In other cases, where meteorology varies substantially across the state, as in California, greater interpolation would be required. The final product would be a tabular listing of geographically defined areas with inputs to be used within the dispersion modeling. Notably, there are different geographic areas across the U.S. with the same characteristics, which could be combined to reduce the overall selection process. These listings could serve two purposes: as a quality control measure and serve as a comparison with similar projects, or as defaults for simple screening analysis.
