To that end, it is vastly preferable to have as much
meteorological observation data as possible.
Not exact matches
For the position of the jet stream from 1979 to 2015, the researchers relied on
data from
meteorological observations.
The collection of larger than usual amounts of Arctic winter weather
data in 2015 was due to two reasons: the Norwegian research vessel Lance was in the Arctic Ocean observing and collecting upper atmosphere
meteorological data, and the frequency of
observation and
data collection was increased at some of the land - based
observation stations around the Arctic.
Results showed that additional
data collected that year through more frequent
observation of
meteorological conditions in the Arctic's upper atmosphere from both land - based research stations and the research vessel Lance plying winter Arctic waters improved the accuracy of cold wave forecasts.
To conduct its analysis, GISS uses publicly available
data from 6,300
meteorological stations around the world; ship - and buoy - based
observations of sea surface temperature; and Antarctic research station measurements.
To conduct its analysis, GISS uses publicly available
data from three sources: weather
data from more than a thousand
meteorological stations around the world; satellite
observations of sea surface temperature; and Antarctic research station measurements.
The temperature analysis produced at GISS is compiled from weather
data from more than 1,000
meteorological stations around the world, satellite
observations of sea - surface temperature, and Antarctic research station measurements.
Relating to the
meteorological observations done at Svalbard Airport, you may find some additional
data and
observations relevant for this discussion on:
Because the GISS analysis combines available sea surface temperature records with
meteorological station measurements, we test alternative choices for the ocean
data, showing that global temperature change is sensitive to estimated temperature change in polar regions where
observations are limited.
ERA - Interim combines information from
meteorological observations with background information from a forecast model, using the
data assimilation approach developed for numerical weather prediction.
The temperature analysis produced at GISS is compiled from weather
data from more than 1,000
meteorological stations around the world, satellite
observations of sea surface temperature and Antarctic research station measurements.
At present, we maintain a rack full of Linux servers at the University of Victoria which host hundreds of terabytes of high - resolution spatio - temporal climate
data and model output and hundreds of millions of
meteorological observations.
To any extent that the records of «satellite
data» have been used to create assessments of land surface temperatures by way of adjustment to calibrate those
observations against the information harvested from the
meteorological thermometers which are the subjects of the SurfaceStations.org study, the error has crept into the assessments of the satellite
data.
Examining Dr. Hansen's updated figure, it seems that he is using the traditional analysis using only
meteorological station
data for the plot of
observations.
ECMWF carries out scientific and technical research directed to the improvement of its forecasts, collects and processes large amounts of
observations, and manages a long - term archive of
meteorological data.
World city weather
observations, (climate
data and forecasts) from national
meteorological organisations.
We blended surface
meteorological observations, remotely sensed (TRMM and NDVI)
data, physiographic indices, and regression techniques to produce gridded maps of annual mean precipitation and temperature, as well as parameters for site - specific, daily weather generation for any location in Yemen.
The «model» seems essentially a regression on altitude from limited
meteorological data supplemented with satellite
observations of vegetation.
The temperature analysis conducted by NASA draws
data from more than 1,000
meteorological stations worldwide, satellite
observations of temperatures at the surface of the oceans, and measurements taken by Antarctic research stations.
This task has become easier over the last decade with the development of advanced methods of
Data Assimilation commonly used in atmospheric sciences to optimally combine a short forecast with the latest
meteorological observations in order to create accurate initial conditions for weather forecasts generated several times a day by the National Weather Services (e.g., [194,195,196,197,198]-RRB-.
Using
meteorological and air traffic
data scaled to regional
observations of contrail cover, Sausen et al. (1998) estimated the present day global mean cover by line - shaped contrails to be about 0.1 %.
Coastal stations also broadcast predicted tides and real time
observations from buoys and coastal
meteorological stations operated by NOAA's National
Data Buoy Center.