[Response: Estimates of the error due to sampling are available from the very high
resolution weather models and from considerations of the number of degrees of freedom in the annual surface temperature anomaly (it's less than you think).
The authors speak of new, higher -
resolution weather models that use horizontal grids.
Not exact matches
This approach is a natural fit for climate science: a single run of a high -
resolution climate
model can produce a petabyte of data, and the archive of climate data maintained by the UK Met Office, the national
weather service, now holds about 45 petabytes of information — and adds 0.085 petabytes a day.
April 23, 2018 - A new earth
modeling system unveiled today will have
weather - scale
resolution and use advanced computers to simulate aspects of Earth's variability and anticipate decadal changes that will critically impact the U.S. energy sector in coming years.
Because they are run for short periods of time only, they tend to have much higher
resolution and more detailed physics than climate
models (but note that the Hadley Centre for instance, uses the same
model for climate and
weather purposes).
They can be simulated to some degree in high
resolution cloud resolving
models; not sure about [numerical
weather prediction]
models, probably not in climate
models.
Surface variables such as T (2m) are strongly affected by their environment, which may be represented differently in different
weather models (e.g. different spatial
resolution implies different altitudes) and therefore is a reason for differences between reanalyses.
What is lacking is mainly the correlation between the
models and real world in local and regional
weather but this is also ever improving as the
model time and spatial
resolution improves.
Latest supercomputers enable high -
resolution climate
models, truer simulation of extreme
weather
NOAA and CIRES scientists have been developing a powerful tool that they believe could provide accurate wind estimates: NOAA's High -
Resolution Rapid Refresh (HRRR)
weather model.
There is a minimum
model resolution that is needed to capture
weather phenomena generating precipitation extremes, for example for simulating tropical cyclones or precipitation enhancement over mountains.
The differences are (1) that you can not afford spatio - temporal
resolution of
weather models to simulate thousand years forward, and (2) in
weather model you don't care if your prediction will blow up in 100 years yielding Venus condition or Ice Ball, you just stop the computer after a week of simulated time, and start over.
Projections of these changes of risk using
models in which changes in the background climate are incorporated, and applied using
models that do a fair job at the short time scale (like high
resolution weather prediction, or hydrological discharge, or...) is thus a viable procedure, and does yield added value.
The intent of downscaling is to achieve accurate, higher spatial
resolution of
weather and other components of the climate system than is achievable with the coarser spatial
resolution global
model.
PIOMAS has higher
resolution and the physics of the cyclone itself is taken care of in the NCEP / NCAR
model, which is basically a forecasting
model - and forecast
models serve us well on a day to day basis forecasting the
weather on local scales.
We can perhaps learn from numerical
weather prediction where the benefits of developing global prediction
models with high vertical and horizontal
resolution are clear cut (confirmed most recently by predictions of Sandy).
If the points are very far away from each other the
model is said to have coarse
resolution and the forecasts is only representative of very large areas, and may not be exactly the
weather where you may be located.
JIGSAW (GEO) is a set of algorithms designed to generate complex, variable
resolution unstructured meshes for geophysical
modelling applications, including: global ocean and atmospheric simulation, numerical
weather prediction, coastal ocean
modelling and ice - sheet dynamics.
As these
models through research and development, become more skilled at higher and higher
resolution and gain the capability of replicating increasingly complex
weather phenomena, the public, through the predictions of the National
Weather Service, will be better served through more precise
weather predictions for places and times where you are.
Apart from the normal progression of climate
modelling to high
resolution, better physics, having a smaller scale to give us better insights into all manner of temperature and
weather extremes, which is very, very important and is ongoing and needs to be continued.
There are many drivers for increased
resolution (spatial and temporal) surface observations, not least being new high
resolution numerical
weather prediction (NWP)
models.
Tselioudis, G., and C. Jakob, 2002: Evaluation of midlatitude cloud properties in a
weather and a climate
model: Dependence on dynamic regime and spatial
resolution.
Re # 162
Models, such as GRIB, lack
resolution, they can't interpolate and determine perfect 3D
weather between distant fixed points, for instance an inversion between two Upper Air stations, some inversions even 30 miles away.
It is worth noting that some high -
resolution operational numerical
weather prediction
models have demonstrated reasonable ability in forecasting tropical cyclones.