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.
- 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”.
- 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.
Combining wind and solar power generation has potential to make renewable energy less variable. This is done to take advantage of the fact that it tends to be cloudy when it’s windy and calm when it’s sunny  . Preliminary site assessment for wind and solar
power generation is commonly done by making use of reanalysis data. A reanalysis is a dataset generated using weather observations and a modified forecast model to produce a gridded representation of past weather events. In this study, the correlation between wind speed and solar radiation from two popular reanalysis datasets, ERA- Interim and MERRA2 , have been compared to correlations based on observed data from four Irish weather stations, along with mast observations from Cabauw, Netherlands. Continue reading “SIAM Conference Galway 2017 – Comparison of Correlations Between Wind and Solar Radiation”
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. Continue reading “SIAM Conference Galway 2017 – An Investigation of Systematic Errors in Solar Radiation for Reanalysis Datasets”
WRF required fields: http://www2.mmm.ucar.edu/wrf/OnLineTutorial/Basics/UNGRIB/ungrib_req_fields.htm
- 3D, pressure levels: Temperature=T, Winds=U, V, Relative Humidity=RH, Geopotential Height=PHIS
- 2D: Surface Pressure=PS, Sea Level Pressure=SLP, Skin Temperature=TS, 2-meter Temperature=T2M, 2-meter specific humidity=QV2M, 10-meter U,V=U10M,V10M
- Constant: LANDSEA mask=FRLAND, Soil Height, PHIS
- Optional: Soil Temperature and Soil Moisture, needed for Noah LSM. Water equivalent snow depth=PRECSNOLAND.
Area I download for GFS forecasts: leftlon=-55, rightlon=20, toplat=70, bottomlat=30
MERRA2 Data info from File Specification by Bosilovich et al. here: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/docs/
- inst3_3d_asm_Np (M2I3NPASM): Assimilated Meteorological Fields
- RH : relative humidity after moist, 1
- T : air temperature, K
- U : eastward wind, m/s
- V : northward wind m/s
- PHIS : surface geopotential height, m2/s2
- inst1_2d_asm_Nx (M2I1NXASM): Single-Level Diagnostics
- PS : surface pressure, Pa
- SLP : sea level pressure, Pa
- TS : surface skin temperature, K
- T2M : 2-meter air temperature, K
- QV2M : 2-meter specific humidity, kg/kg
- U10M : 10-meter eastward wind, m/s
- V10M : 10-meter northward wind, m/s
- const_2d_asm_Nx (M2C0NXASM): Constant Model Parameters
- FRLAND : fraction of land, 1
- PHIS : surface geopotential height, m2/s2
To download data, start here: https://disc.gsfc.nasa.gov/uui/datasets?keywords=”MERRA-2″
Then type in the dataset name in the search box. Select the dataset. Click on Subset > Subsetter. Enter lat/lon values. Download list of files. Issue wget command:
wget --load-cookies ~/.urs_cookies --save-cookies ~/.urs_cookies --auth-no-challenge=on --keep-session-cookies --content-disposition -i myfile.dat
The constants files are different, download those directly from the online archive. Downloading requires earthdata login.