 We are now going to discuss how one might go about monitoring draws and assessing their potential impact. So to do so we need some data. The data one might want to use here is naturally climate data or weather data, specifically for example recent precipitation. So let's pick from the weather set and the GFS, as the precipitation. So the idea would be we look for areas where in the recent past there has been generally low precipitation. And then we could add for example minimum temperature. Here the rationale being that you know if the temperature is high the effect of low precipitation increases the impact of this quite a lot. So now that we have these two data layers, let's pick an area. So for this example, let's pick part of Ethiopia where there have been draws in 2017. And now we can filter this. Okay, so let's add as a filter here the population density with the IDB in that you know in areas of low population density the effect of the draw is maybe not that problematic. We're interested in areas where there's more than five people per square kilometer as a density. Now that we like to select this filter, we should pick the time window. So today is March the 5th and we said you know let's go a bit into the past for the precipitation and a bit into the future for the temperature. And we can do aggregation here. So for the precipitation we pick the sum to get the total for the minimum temperature to take them mean is maybe the most relevant quantity here. So to say this again, we're now querying for areas in East Africa where there's population higher than a certain threshold and for these areas we're considering the accumulated precipitation from the last four days in comparing this against the mean minimum temperature forecast for the next three days. Okay, of course, here we actually approximate the accumulated precipitation by its forecast. So we submit this and as in previous examples, we've actually ran this query previously so we can take a look at the result immediately. So you see here now this is the population density. Okay, where we've scaled the color chart a bit so that you know right areas are sort of you know going to saturation at 250 and then you know you see here how some areas have been cut out where the population density is very very low and then we compare for these areas the accumulated precipitation you know we see there's been a very low precipitation in the western in the east and similarly we can compare this with the average minimum temperature you know which surprisingly is very high specifically by here in the east.