Incorporating satellite and reanalysis data with station data

Incorporating satellite and reanalysis data with station data

Host Institution: African Mathematics Initiative (AMI)

 Location: Maseno, Kenya. Contact: James K. Musyoka, School of Mathematics, Statistics and Actuarial Sciences, Maseno University. E-mail:

Supervisors: James K Musyoka, Danny Parsons, IDEMS International, Reading, UK.

 Project Description

The intern will join the AMI team of young staff who are working on a range of topics concerned with mathematics and its applications. They will mainly work on the topic below.  They will also be given the opportunity to take part in occasional AMI initiatives many of which (like Maths camps), are designed to improve Mathematics Education at school and university levels.

This area follows an AIMS MSc essay in 2019.  The presence of satellite and re-analysis data has the potential to transform the products that NMSs can offer.  Suddenly they are at risk of being overwhelmed by the volume of data for their country.  EUMETSAT has contracted one of the supervisors of this project, for the past 3 years, because of the ease with which station and satellite data can be compared using the current R-Instat software.  The intern will extend the facilities in the software and test them on data, probably including those from Western Kenya.

The intern will also continue past work on the mapping of climatological data.  This has usually involved the use of special software, but many useful maps can be provided using R and hence can be added to R-Instat.  This work was started though an AIMS Rwanda coop student and the initial results were enthusiastically endorsed when presented to NMS staff.  This work includes adding contour plots and also raster plots, based on the gridded data.

 Project Expected Outcomes:

Long-Term goals: Each country in Africa has a National Meteorological Service (NMS). The NMS provides their country with the short-term forecast, and also often provides a special service for the aviation sector.  Many countries also provide a seasonal forecast.  In addition, the NMS is usually the custodian of the long-term historical data for their country.  Most countries claim their density of climatic stations is insufficient and the manual stations have recently been supplemented by sets of automatic stations.  There are many important uses of these historical records, particularly with concerns about climate change, but most services would agree that their existing data are currently insufficiently analysed.  This work is designed to provide and illustrate the use of a tool that is a “game changer” in this field. One goal is for NMS staff and others interested in this area, to add the full exploitation of these data into their “comfort zone”, in the same way as they handle climatic forecasts.

 Applications for this internship should be submitted via the online application system, stating clearly the title of the internship.

Deadline for applications: January 20th, 2020 – 11:59 PM (EAT).

Any inquiries about these internships should be sent to: