SIAM UK & Ireland Student Conference.

SIAM UK & Ireland Student Conference, 26 May, at NUI Galway.

Eadaoin and Seánie presented posters at the conference (details of the posters are in separate blog posts).

Students from colleges throughout Ireland and the UK presented on a variety of topics as seen in the list of abstracts

There were two plenary talks.

  1. Lea Deleris from IBM Research -Ireland:  Taking Decision Making to the Next Level. She “ illustrates how applied interdisciplinary research, leveraging advances in artificial intelligence broadly defined, can provide solutions to bridge the gap between theory and practice and eventually bring rigorous decision making to the masses”.
  2. Patrick Farrell from Mathematical Institute, University of Oxford: Scalable Bifurcation Analysis of Nonlinear Partial Differential Equations.

There was also a round table discussion on careers in Mathematical Science which included the plenary speakers.

The 2018 ‘National’ Student Chapter Conference will be hosted by the SIAM Chapter at University of Bath, which we hope to attend. 


SIAM Conference Galway 2017 – An Investigation of Systematic Errors in Solar Radiation for Reanalysis Datasets

The design and estimation of the performance of any solar energy system requires knowledge of solar radiation data obtained over a long period of time. The use of solar photovoltaic (PV) energy in Ireland is growing, leading to more interest in accurate solar shortwave radiation (SW) climatology. Reanalysis models use observational data from the past to simulate climatology. The network of stations measuring radiation is sparse, therefore, reanalysis datasets are used as a representation of climatology. The accuracy of reanalysis SW data can in part be explained by linking it to cloud amount in reanalysis. In this study, time-series analysis is performed to identify links between errors in SW and cloud structures at different spatial scales, by making use of satellite imagery and reanalysis cloud data. This study examines two popular reanalysis datasets, MERRA2 from NASA and ERA-Interim from ECMWF, with the aim of establishing the skill of reanalyses when compared to ground measurements to find which is more suitable for SW over Ireland. Reanalysis datasets are compared with a representative selection of Irish pyranometer data for time periods of up to 35 years, and standard skill scores (bias, RMSE and Pearson’s correlation) are calculated.  Scores relative to climate (Anomaly Correlation Coefficient (ACC)) are also calculated to compare the performance in different seasons.


Journal Club: 18-04-2017

Article Title: Evaluation of the reanalysis surface incident shortwave radiation products from NCEP, ECMWF, GSFC, and JMA using satellite and surface observations. Remote Sensing 8.3 (2016)

This paper evaluates the solar radiation incident at the Earth’s surface (Rs) for six global reanalyses (NCEP–NCAR, NCEP-DOE; CFSR; ERA-Interim; MERRA; and JRA-55) using surface measurements from different observation networks (GEBA; BSRN; GC-NET; Buoy; and CMA) and the Earth’s Radiant Energy System (CERES) EBAF product from 2001 to 2009. For surface measurements which have instantaneous values of Rs, the daily integrated Rs was obtained from the instantaneous values through a sinusoidal interpolation method.

All selected reanalysis Rs products overestimated monthly Rs when compared to the surface measurements from the five networks. Most reanalysis products showed better accuracy in DJF than that in JJA. Reanalysis was also compared to CERES-EBAF. Almost all of the reanalysis overestimated the monthly Rs over land, the oceans, and the globe. Bias and RMSE values of global reanalyses compared with CERES-EBAF Rs data were smaller than those between the global reanalyses and surface observations.

We could look at using GEBA and CERES for evaluation of MERRA2 and ERA-Interim and compare the results here. These might be sources of solar radiation data for the UK (if we expand our research area).


Satellite Data for Solar Energy Applications

As the use of solar energy is constantly growing in Ireland, it has become increasingly important to assess the accuracy and skill of our weather forecasts and models. Satellites can be used on short time-scales to verify incoming solar radiation forecasts and also potentially to update operational PV models. This report outlines appropriate satellite data and the relevant retrieval methods for examining solar energy processes in Ireland.

There are two main categories of satellites: geostationary and polar orbiting satellites. Polar orbiting satellites orbit around the earth longitudinally passing directly over the poles at an altitude of about 850km, taking approximately 100 minutes to complete the orbit. During one half of the orbit, the satellite views the daytime side of the Earth. At the pole, the satellite crosses over to the night-time side of Earth. Our assistant is ready to help you with football betting bonus. Due to the earth rotating underneath the orbiting satellite with each orbit the satellite viewing area is an area west of the previous image. Polar orbiting satellites will view most of the earth at least twice in a 24-hour period.

Geostationary satellites orbit the earth over the equator at an altitude of about 36,000km. These satellites have a lower resolution than polar orbiting satellites due to their higher altitude. However, they record a continuous full disk image of the same region in every image which is advantageous for observing the weather features occurring. A down-side of using geostationary satellite images for Ireland is our high latitude which causes a perspective distortion in the images as the satellite is located over the equator. Nevertheless, this report found geostationary satellite data to be the most suitable for solar energy processes in Ireland.

This report looks at the different formats of satellite data; raw satellite data, derived satellite products and satellite images. The most appropriate source and format found was geostationary Meteosat images from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Data Centre. The images have a temporal resolution of 15 minutes and the data can be easily downloaded from the browser or retrieved via wget.

Satellite Data for Solar Energy