Data Assimilation in the Snow

by Sarah Dance

Snowbird mountains

I’ve just got back from attending the Society of Industrial and Applied Mathematics (SIAM) Conference on Dynamical Systems in the beautiful mountains of Snowbird, Utah,USA.  I was invited to attend the meeting to give part of a Mini-Tutorial on Data Assimilation(available here) with Elaine Spiller and Eric Kostelich.

Even though my undergraduate degree and PhD were in Applied Mathematics, I don’t tend to go to many Mathematics conferences. I often meet with fellow data assimilation practitioners at Meteorology conferences instead.  So it was great to see people proving data assimilation related theorems, applying data assimilation in different applications like neuroscience and cancer treatment, and of course to get some new ideas from dynamical systems approaches that have potential to be applied in different ways.  I particularly enjoyed Mary Silber’s talk on using Landsat data to understand vegetation pattern formation in the drylands of Africa

A slow march through the desert

Gowda/Silber’s work on African drylands. This image shows shrublands in Somalia from high above. Two images – from 1952 (purple) and 2006 (green) – are overlaid here for comparison. The colors highlight the large communities of shrubs and grasses which grow in bands along this sloping landscape. Over the fifty years shown here, all the vegetation has moved uphill – the green bands of modern plant growth are further up the hillside than the purple bands from 1952.

2017 Annual European Geosciences Union (EGU) Conference

    by Liz Cooper

The 2017 Annual European Geosciences Union (EGU) conference was held at the International Centre in Vienna from 23rd to 28th April.  During that time over 14,000 scientists from 107 countries shared ideas and results in the form of talks, posters and PICOs .The PICO (Presenting Interactive COntent) format is a relatively new idea for presenting work, where participants prepare an interactive presentation. In each PICO session the presenters first take turns to give a 2 minutes summary of their work for a large audience. The PICOS are then each displayed on an interactive touch screen and conference delegates can chat to the presenters and get further details on the research, with the PICO for illustration. This format has features of both traditional poster and oral presentations and provides a great scope for audience participation. I saw several which took advantage of this, including a very popular flood forecasting adventure game by a fellow Reading Phd student Louise Arnal.

I was delighted to be able to present some of my own recent results at EGU, in a talk titled ‘The effect of domain length and parameter estimation on observation impact in data assimilation for inundation forecasting.’ (see photo)

Presenting at an international conference was a really valuable and enjoyable experience, if a little daunting beforehand. I found it a really useful opportunity to get feedback from experts in the field and find out more about work by people with related interests.

The EGU conference has many participants and covers a huge range of topics from atmospheric and space science to soil science and geomorphology. My research deals with data assimilation for inundation forecasting, so I was most interested in sessions within the Hydrological Sciences and Nonlinear Processes in Science programmes. Even within those disciplines there was a huge breadth of research on display and I saw some really interesting work on synchronization in data assimilation, approaches to detection of floods from satellite data and various methods for measuring and characterizing floods.

As well as subject-specific programmes, there was also a very good Early Career Scientist (ECS) programme at EGU, with networking events, discussion sessions and a dedicated ECS lounge with much appreciated free coffee!

EGU was a hugely enjoyable experience and Vienna is a beautiful city with excellent transport links. With so many parallel sessions it’s really essential to plan which talks and posters are a priority in advance but I would heartily recommend it to anyone involved in geosciences research.

7th Japanese Data Assimilation Workshop

By Joanne A. Waller

For decades data assimilation (DA) has played a crucial role in numerical weather prediction (NWP) where it is used to provide initial conditions for weather forecasts. These ‘initial conditions’ describe the current atmospheric state and are estimated using data assimilation by blending previous forecasts with atmospheric observations, weighted by their respected uncertainties. However data assimilation is not only applicable to NWP and in recent years it has been applied widely to different applications where numerical simulations and observations are available.

At the end of February 2017 over 100 scientists from around the globe arrived at the Japanese RIKEN Advanced Institute for Computational Science (AICS)  for the 7th Japanese Data Assimilation Workshop. The aim of the symposium was to bring together scientist from from numerous different disciplines, such as neuroscience, cardiology, molecular dynamics, cosmology, nanoscale materials science, terrestrial magnetism, paleoclimate, oceanography, atmospheric chemistry and of course NWP, to discuss the data assimilation issues shared  across these broad applications.

Presentations and posters covered a wide variety of topics including: how data assimilation combined with advanced intelligence can help improve numerical models; how high performance computing can be used to deal with the new era of ‘Big Data’; how non-Gaussianity and non-linearity can be handled in data assimilation; ideas on how assimilate data into multi component models (i.e. systems that connect multiple models such as atmospheric, land and ocean models) and many more.

The conference provided a perfect platform for many cross-disciplinary discussions and this highlighted that much can be learnt in general about data assimilation by considering the issues that arise across different scientific areas.

(Photo from http://www.data-assimilation.riken.jp/risda2017/)