Daily Temperature Analysis

The Maproom explores historical daily temperature by calculating simple seasonal statistics.

Many options can be specified to produce yearly time series of a chosen seasonal diagnostic of the daily temperature data. The user can then choose to map the mean, standard deviation, coefficient of variation or probability of exceeding a chosen threshold, over years; clicking on the map will then produce a local yearly time series of the chosen diagnostic.

Years and Season: Specify the range of years over which to perform the analysis and choose the start and end dates of the season , over which the diagnostics are to be performed.
Hot/Cold Day Definitions: These define the temperature in Celsius (non inclusive) above which a day is considered to be a hot day (as opposed to cold). Note that hot/cold days are computed respectively with maximum/minimum temperatures.

Seasonal daily statistics: Choose the seasonal diagnostic quantity (i.e the statistic of the daily data) to be computed for each season, from the following choices.
Mean Temperature: mean temperature (in Celsius) over the season.
Minumum Temperature: minimum temperature (in Celsius) over the season.
Maximum Temperature: maximum temperature (in Celsius) over the season.
Number of Hot Days: the number of hot days (as defined above) during the season.
Number of Cold Days: the number of cold days (as defined above) during the season.
Chilling Degree Days: chilling degree days are summations of negative differences between the mean daily temperature and user-defined reference base temperature during the season. They are comparable to the more familiar heating degree day definitions utilized by energy-sector.
Growing Degree Days: growing degree days are summations of positive differences between the mean daily temperature and user-defined reference base temperature during the season. They are comparable to the more familiar cooling degree day definitions utilized by energy-sector.

Yearly seasonal statistics: a choice of yearly statistics over the chosen season of the selected range of years to produce the map among: the mean, the standard deviation, the coefficient of variation and the probability of exceeding a user specified threshold.

Spatial Resolution: The analysis can performed and map at each 0.0375 resolution grid point. Additionally it is possible to average the results of the analysis over the 0.0375 grid points falling within administrative boundaries for the time series graph.

Dataset Documentation

Reconstructed rainfall on a 0.0375 x 0.0375 lat/lon grid (about 4km) from Ethiopia Meteorology Institute. The time series (1961 to 2018) were created by combining quality-controlled station observations in EMI’s archive with satellite rainfall estimates.

How to use this interactive map

ThePlots Range controls define the range of the vertical axis of the time series and the horizontal axis of the probability of exceeding graph. Blanking the boxes will set the range to the extrema of graph in view.

Helpdesk

ContactEMI with any technical questions or problems with this Map Room.