General
This five-day module will start on Monday 17 May at 9.00 and finish Friday
21 May at 13.00. Timetable
Short descriptions of the contents of the lectures are given below.
Predictability
The predictability of the atmosphere in the medium and extended range
will be considered. Theoretical aspects associated with ideas in chaos
theory, flow regime diagnosis, and singular vector analysis, will be addressed.
There will be a discussion of ensemble techniques, especially those used
at the Centre, together with an analysis of specific case-studies of ensemble
forecasts. Methods to evaluate the skill of ensemble-based probability
forecasts will be studied. The potential user value of ensemble forecasts
will be assessed through some idealised and practical examples.
Diagnostics
Despite impressive improvements in our ability to model the atmosphere,
forecasts still exhibit systematic and flow-dependent errors as well as
random error. Diagnostics software is a crucial component of the forecast
system, used to document such errors, and to understand their causes.
Lectures on systematic model errors associated with specific atmospheric
processes like the monsoon will be given. The concept of sensitivity studies,
using the adjoint method, and PV diagnostics will be introduced. An overview
of the NAO and its predictability on timescales from days to decades will
also be given.
Seasonal Forecasting
Although detailed weather forecasts are not possible beyond a couple
of weeks ahead, it is possible to make probabilistic forecasts of large-scale
flow anomalies on the seasonal timescale. Predictability on this timescale
arises from ocean-atmosphere interaction, typified by El Niño.
Lectures will cover the El Niño phenomenon and the ocean circulation.
The formulation and performance of the ECMWF coupled ocean-atmosphere
monthly and seasonal forecast systems will be described. Methods for initialization
and ensemble generation in seasonal forecasting will be discussed. The
concept and performance of multi-model ensemble forecasting will also
be studied.
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