Improving Prediction of Fronts

Lead Research Organisation: Imperial College London
Department Name: Dept of Aeronautics

Abstract

Once a weather
model has been initialised from our best estimate of the current state
of the atmosphere, it will diverge from the real state of the
atmosphere over time. The period of time during which a single
deterministic weather model provides useful information is known as
the "useful forecast range'', which provides a measure of the
predictive skill of the model. For example, the ECMWF useful forecast
range is now typically between 7 and 10 days. Extending the useful forecast range of weather
forecasts (and improving accuracy over that range) would have clear
benefits to society and the economy; benefits include: energy management, protection of
infrastructure, coordinating disaster response, agricultural planning,
planning in travel and leisure industries, transportation management,
targeting of weather-sensitive health conditions, water resource
management, improved decision making in commodity markets,
environmental decision making and natural resource management. In this
project, we will develop a means of understanding of some current
limitations to predictive skill and the useful forecast range, and
will investigate practical methodologies for removing them. This is of
course a huge topic; we shall restrict our investigation to the dry
dynamical core (the part of the model that predicts winds, temperatures and pressures),
and concentrate on one important phenomena, namely the
evolution of fronts and, in particular, the resulting feedback
on the large scale atmospheric circulation. Fronts play a key role in the delivery of
precipitation, and many severe weather events, which have an important
role in all of the socioeconomic areas discussed above. The challenge associated
with fronts is that although the distance from one side of a weather front
to another is very small compared to the distance between two grid points in
an operational forecast model, fronts have a significant impact on the wind speed
and direction as well as the pressure over a large region around the front. The aim of this project
is to find improvements in dynamical core design that can improve the prediction
of the winds and pressures in the vicinity of fronts.

Planned Impact

Beneficiaries of this research include:
* Operational forecasting centres such as the UK Met Office
* Customers of operational forecasting centres such as businesses and policy makers.

Extending the useful forecast range of weather
forecasts (and improving accuracy over that range) would have clear
benefits to society and the economy. Areas that would benefit include improvements in:
energy management, protection of infrastructure, coordinating disaster response, agricultural planning,
planning in travel and leisure industries, transportation management,
targeting of weather-sensitive health conditions, water resource
management, improved decision making in commodity markets,
environmental decision making and natural resource management.

This is blue skies research which will seek to identify strategies to improve
predictability in dynamical cores for numerical weather prediction. Any successful
strategies would be likely to be included on the timescale of the UK "GungHo" Dynamical
Core project which is aiming for operational use by 2020.

Dynamical core developers from operational forecasting centres will be encouraged to engage
through the test case workshop: as well as key participation from the UK Met Office and
the associated "GungHo" dynamical core project, invitees will include representatives of ECMWF,
the DWD/Hamburg/Rosstock ICON team, the NCAR/LANL MPAS team, the Japanese NICAM team,
developers of the various CAM dynamical cores such as CAM-SE, etc.

Policymakers will be engaged through the Grantham Institute by means of a Grantham Discussion Paper
on the topic of predictability and model error.

Publications

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Cotter C (2014) Variational formulations of sound-proof models Variational Sound-Proof Models in Quarterly Journal of the Royal Meteorological Society

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Yamazaki H (2016) Three-dimensional cut-cell modelling for high-resolution atmospheric simulations in Quarterly Journal of the Royal Meteorological Society

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Cotter C (2016) Embedded discontinuous Galerkin transport schemes with localised limiters in Journal of Computational Physics

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Natale A (2016) Compatible finite element spaces for geophysical fluid dynamics in Dynamics and Statistics of the Climate System

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McRae A (2016) Automated Generation and Symbolic Manipulation of Tensor Product Finite Elements in SIAM Journal on Scientific Computing

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Cotter CJ (2016) Mixed finite elements for global tide models. in Numerische mathematik

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Bendall T (2020) A compatible finite-element discretisation for the moist compressible Euler equations in Quarterly Journal of the Royal Meteorological Society

 
Description We have developed our understanding about how the representation of fronts in weather prediction models causes large scale errors, and are developing ways to reduce these errors in order to improve the predictive skill in weather forecasts. We have discovered that the failure to predict the front evolution is not due to the dissipation of energy near the front, but instead is due to errors in the transfer of potential to kinetic energy there, due to lack of resolution. These are currently leading to the development of new "parameterisations" that model the transfer of potential to kinetic energy that takes place at the gridscale. We have also shown that the new algorithm approaches being developed at the Met Office to allow the forecast model to run on the next generation of massively parallel supercomputers represent the frontogenesis and evolution (at least as) well as the current approach. We have also developed a new vertical slice frontogenesis test problem that can be used by weather forecasters.
Exploitation Route Yes, we are designing parameterisations which might be used in operational weather forecast models, such as at the Met Office. The numerical testcase results have also built up confidence in the new algorithm approach being developed at the Met Office. Our new testcase will allow meteorologists to investigate the performance of their forecast models in representing fronts in a simplified setting.
Sectors Environment

 
Description Ongoing colloboration with UK Met Office staff 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Academic/University 
PI Contribution We have developed several collaborative interactions with UK Met Office staff
Start Year 2011
 
Title Gusto 
Description A Python library for compatible finite element dynamical cores 
Type Of Technology Software 
Year Produced 2016 
Open Source License? Yes  
Impact This software is providing a testbed for the development of the Gung Ho dynamical core for the Met Office forecast model. 
URL http://firedrakeproject.org/gusto/
 
Title Slicemodels 
Description This is a code for benchmarking our suite of compatible finite element methods for numerical weather prediction in a vertical slice configuration. 
Type Of Technology Software 
Year Produced 2015 
Open Source License? Yes  
Impact This tool is being used to benchmark numerical schemes for the NERC/Met Office/STFC UK Dynamical Core project ("Gung Ho"). 
URL https://bitbucket.org/colinjcotter/slicemodels
 
Title dcore 
Description Software implementing a numerical model for a 3D dynamical core on the sphere using compatible finite element methods. 
Type Of Technology Software 
Year Produced 2016 
Open Source License? Yes  
Impact This software is being used to benchmark numerical algorithms being developed for the UK Met Office forecast model. 
URL https://github.com/firedrakeproject/dcore
 
Description ICMS Public talk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Public/other audiences
Results and Impact As part of the International Centre for Mathematical Sciences workshop we organised in Edinburgh, we hosted a public talk on climate uncertainty given by David Stainforth. The idea was to engage the public with the importance of mathematics in climate research, particularly in the combination of climate/weather models and statistics in order to understand and quantify uncertainty.

We received excellent feedback about the talk through the ICMS.
Year(s) Of Engagement Activity 2015