Other data sources were investigated, including the new Berkeley land - ocean temperature data, the MERRA
weather model reanalysis, and satellite radiometer datasets from AIRS and AVHRR.
Not exact matches
This involves a combination of satellite observations (when different satellites captured temperatures in both morning and evening), the use of climate
models to estimate how temperatures change in the atmosphere over the course of the day, and using
reanalysis data that incorporates readings from surface observations,
weather balloons and other instruments.
These climate - related land storage effects could be significant for global sea - levels, though unfortunately there seem to be very few direct experimental measurements of the factors involved, and so the only studies of these effects seem to have been from computer
modelling of data from
weather data «
reanalysis»
models (e.g., ERA - 40).
We will analyze synoptic - scale
weather patterns from global
reanalysis models over the past 50 years, utilizing a variety of techniques including self - organizing maps, such that these
weather patterns can be tied to variations in core proxies, as well as relate this to ten years (2003 - 2013) of records from about a dozen automated
weather stations located on and near McCall Glacier.
Type 2 dynamic downscaling refers to regional
weather (or climate) simulations in which the regional
model's initial atmospheric conditions are forgotten (i.e., the predictions do not depend on the specific initial conditions), but results still depend on the lateral boundary conditions from a global numerical
weather prediction where initial observed atmospheric conditions are not yet forgotten, or are from a global
reanalysis.
These include the primary surface temperature thermometer records (NASA GISS, NOAA, and HadCRUT); satellite measurements of the lower troposphere temperature processed by Remote Sensing Systems (RSS) and the University of Alabama - Huntsville (UAH); and 5 major
reanalysis datasets which incorporate station data, aircraft data, satellite data, radiosonde data, buoy and ship measurements, and meteorological
weather modeling.
Instead of just performing a statistical analysis of the
weather station and sea surface observations, the
reanalysis attempts to construct a complete
model of the state of the Earth's atmosphere at any point in time.
The ECMWF provides its supercomputer - run Integrated Forecasting System, a world - renowned numerical
weather prediction
model, as a basis for some Copernicus services, such as atmospheric forecasts and
reanalysis data.
Further evidence is provided by the NCEP / NCAR
reanalysis data, which uses a much more diverse range of observations coupled to a modern
weather model.
ECMWF's approach to
reanalysis combines measurements of temperature and other meteorological variables with a global
weather model to provide a complete picture of the regional patterns of climate.
To answer this question I looked at more than just the traditional Hadley, NASA and NOAA datasets, but also the measurements of the lower troposphere processed by Remote Sensing Systems (RSS) and the University of Alabama - Huntsville (UAH) as well as the 5 major
reanalysis datasets which incorporate station data, aircraft data, satellite data, radiosonde data and meteorological
weather modeling.
The technique was originally developed to examine the storm tracks produced by atmospheric general circulation
models (GCMs), but it is directly applicable to other gridded SLP datasets, such as those derived in
weather forecasts or
reanalysis projects.
For those that don't know, a «
reanalysis» is a climate or
weather model simulation of the past that includes data assimilation of historical observations.
Average of the IPCC computer
model projections for the tropical mid-troposphere versus three standard sets of observations:
weather balloons, temperature sensed from satellites, and «
reanalysis» data used to initialize the daily
weather map.