Climate-CAFE/era5-daily-heat-aggregation

Using the R ecmwfr package, ERA5 hourly temperature measures are downloaded from the Copernicus Climate Data Store. Using temperature and dewpoint temperature, heat index and humidex metrics are derived. Daily mean, maximum, and minimum measures are assessed across administrative boundaries. Kenya is used as a demonstration area. # Query of Hourly ERA5-Land Data and Aggregation of Daily Summary Heat Metrics ## Project Overview Using the R ecmwfr package, ERA5-Land hourly temperature measures are downloaded from the Copernicus Climate Data Store (CDS). Heat index and humidex metrics are derived from ERA5-Land hourly 2-meter temperature and 2-meter dew point temperature. Daily mean, maximum, and minimum measures are assessed across administrative boundaries for 2-meter temperature, 2-meter dew point temperature, skin temperature, heat index and humidex. Kenya is used as a demonstration area for the Copernicus CDS API query and spatial aggregation, using administrative boundaries from the Database of Global Administrative Areas. ### Why Use ERA5? When selecting a dataset for analysis of the relationship between climate change and health, there are several primary considerations. They include: - **Temporal Resolution**: Depending on your question of interest, hourly, daily, or annual summary metrics could be most appropriate. The ERA5 product we use for this analysis is hourly. There are a range of different temporal resolutions that can be downloaded from the Climate Data Store. - **Time Span**: Selecting a data resource is also informed by the time span available. Some research questions require an extensive historical data record spanning far into the past, and other times the most recent data is more pertinent. ERA5-Land provides data spanning back to 1950, and data for the recent past as well (through a week prior to download). - **Spatial Resolution**: Re-analysis data such as ERA5 use a combination of various inputs to derive estimates of temperature at a finer scale and across greater areas than individual weather stations could provide. Different data sources provide differing resolution, with some datasets sharing temperature and other metrics at 1m x 1m grids, and others at much larger scales. ERA5-Land provides data at approximately 9km x 9km grids. This larger grid size can be adva …