Okay, hi everybody, my name is Dick Dee. I work at the European Centre for Media Range Weather Forecasts in Reading, the UK, and I want to explain to you why you're doing this painstaking work on station data, and why it's actually really important work. And so you should be excited about doing it, and

we are also very happy that that you are doing this. So the reason is that at ESMWF we are also, well, we're responsible for weather forecasting, that's really our core business, but we're also very involved in climate. And at the moment we are implementing for the European Commission what's called the

Copernicus Climate Change Service. And Copernicus is a large EU program that is mainly about satellites and how satellites can be used to monitor the environment, but they have also set up a number of services where we can, where we show how to use these data for the benefit of society, and one of the

services is focused on climate change. So you may know that in order to use satellite data in the right way you really need in situ data, station data, and if you want to create a climate data record from all these observations together, you need especially to go far back into the past,

you need every single observation that you can get your hands on. And it's very important that all these observations are quality control, because you will find out in your work that there are ridiculous problems in the data. For example, data that are supposed to be on land stations but actually are located in the ocean and that kind of thing. And it's really

crucial that we find those errors and correct them if we can, because if you use those data in the wrong way, you can just get completely wrong information about climate. So we're really excited that we have this project going and that you have a part in it. A very important part is something about observations that it requires a lot of work, but,

you know, an observation is only taken once and you can't go back in time, at least not yet, to do it again. So we just have to work with what we have, and it's really important that people spend a lot of time on getting the best out of these observations and fixing any problems that they can find. So thank you very much and good luck,

and I look forward to getting all this data so that we can use them.