The US CLIVAR PPAI Panel seeks new panelists with expertise in one or more of the following areas: (a)
predictability of weather / climate extremes, (b) multi-model ensembles, (c) decadal prediction; (d) application, impact, and mitigation strategies for marine ecosystems or (e) agricultural products; or (f) interactions with stakeholders and / or stakeholder boundary organizations.
Topics such as
the predictability of weather phenomena, coupled ocean - atmosphere systems and anthropogenic climate change are among those included.
Not exact matches
Gabriel Vecchi, head
of the climate variations and
predictability group at NOAA's Geophysical Fluid Dynamics Lab and another author on the paper, says decades
of weather prediction data show that forecasts have improved — and will improve — as scientists learn more about hurricanes.
The long - term
predictability of such systems is difficult if boundary conditions change or can not be precisely determined in the first place — just consider the
weather forecast!
The interactions on intra-seasonal time scales represent a potential source
of predictability for
weather forecasting.
One new development is demonstrating the potential
predictability of intra-seasonal teleconnections for middle - latitude
weather because forecast models only recently started to simulate a close to observed variability
of tropics (the tropical forcing).
So
weather forecasts rely on the
predictability of atmospheric systems that persist a couple
of weeks.
Retailers and manufacturers can usually count on the
predictability of seasonal pond sales — depending on local climate — but the
weather didn't cooperate in 2011.
What causes doubt and confusion is that the effects
of global warming are not uniform around the globe and there are always
weather fluctuations (that may even increase in scale and
predictability) as global warming progresses.
Maue discussed how «two camps»
of researchers claim to have increased
predictability of such
weather events over periods
of a month or more by using clues either in the Arctic, related to the extent
of sea ice and snow cover, or in the temperature
of surface waters across the Pacific Ocean.
There are some source
of predictability that are still not fully resolved (including those dealing with improving climate models, but also related to unexplored initial conditions or driving conditions), and a great benefit
of these
predictability studies is that they mimic the practice
of weather prediction by confronting models with observations at the relevant time and spatial scales, leading to the necessary inspiration for this model improvement.
The Observing System Research and
Predictability Experiment (THORPEX) is a 10 - year international research and development programme to accelerate improvements in the accuracy
of one - day to two - week high impact
weather forecasts for the benefit
of society, the economy and the environment.
The topic
of predictability in
weather and climate has advanced significantly in recent years, both in understanding the phenomena that affect
weather and climate and in techniques used to model and forecast them.
Relating the observed chaotic character
of the climatological series to the non-linearity
of the equations ruling the
weather and thus climate evolution, and presenting the example
of a solution
of the Lorenz non-linear equations showing that non-linearity may be responsible for the instability
of the generated process, it seems justified to conclude that there are severe limits to climate
predictability at all scales.
The FMI contributed to the identification
of extreme
weather events, assessment
of predictability and the probability
of extreme
weather hazards in the present and the projected future climate.
Essentially you run a spatially and temporally undersampled
weather prediction model based upon an incomplete set
of highly chaotic physical laws
of over time periods too long to calibrate and test the
predictability of the model.
So
weather forecasts rely on the
predictability of atmospheric systems that persist a couple
of weeks.