This plot shows rainfall amounts for the selected year (dark blue) and for the long term average (20 years, 1994-2013) in light blue. At a glance, you can perceive the general timing of the rainfall season for the area of interest and how the selected year has developed. In particular look for periods with consistently above or below average rainfall, particularly during the early stages of the season and during critical times for crop development.

This plot shows rainfall anomalies for the selected region and year. Two anomalies are shown, with time spans of one and three months. By anomaly we mean a comparison with the long term average: here we show the ratio between rainfall for the current year and the average, expressed in percentage terms - this is done for rainfall of one month and three months duration.

Example:
A value of 73% of the three month anomaly in the second dekad of August means that the rainfall for the three month period ending in August 20 has been 73% of the average. For an average amount of 120mm this would mean a current 3 month rainfall of 87.6mm.

Interpretation:
Values below 100% represent rainfall deficits, above 100% rainfall surplus. Note that 1 month anomalies are more erratic than 3 month anomalies and will reach more extreme values as you would expect. Values between 90% and 110% are considered as being within the range of normal variability for both anomalies.

Note: For locations with very low rainfall or during dry-season periods, anomalies can take extreme values: e.g. if on average you get 2mm and in one particular month you get 8mm, the one month anomaly will be 400%.

This plot shows NDVI values for the selected year and for a medium term average (12 years, 2002-2013). At a glance, you can perceive the general timing of the growing season for the area of interest and how the selected year has developed. In particular look for periods with consistently above or below average NDVI, particularly during the early stages of the season and during critical times for crop development.

This plot shows NDVI anomalies for the selected region and year. A single anomaly is shown calculated based on the 10 day data. Unlike rainfall no aggregation at given time spans is required, since vegetation itself already integrates the effect of previous rainfall. Anomalies are defined in the same way as for rainfall - as the ratio between NDVI for the current year and the average at each time step expressed in percentage terms.

Example:
A value of 87% of the NDVI anomaly in the second dekad of August means that the NDVI at this point in time is 87% of the average. For an average NDVI of 0.6 this would mean a current season NDVI of 0.52

Interpretation:
Values below 100% represent vegetation cover deficits, above 100% vegetation cover above average. Note that NDVI anomalies are much smoother than those of rainfall, since vegetation is naturally far more stable than rainfall. Broadly values between 90% and 110% are considered as being within the range of normal variability.

This plot shows both Rainfall and NDVI values for the selected year and their average, i.e. brings together the two plots on the left. This allows a user to understand the relationship in the timings of rainfall and vegetation variation as the season unfolds. In particular for areas with well defined dry and wet seasons, users should see a well-defined linkage between the rainfall and the vegetation seasonal cycle.

The average data provides an idea of the usual seasonal cycle and its timings:

• Early rainfall followed by increases in NDVI.
• Peak in rainfall preceding the peak in NDVI.
• NDVI decreasing after the rainfall drops off at the end of the season.

For very wet locations, with year round rainfall, users will see little if any linkage between the two and may see a very flat NDVI curve with high values. Users can then compare the current season with the average one in terms of these.

This plot shows both rainfall and NDVI anomalies together for the selected region and year, i.e. brings together the two plots on the above right. By default only the 3 month rainfall anomaly is shown, but users can switch on the 1 month anomaly (and switch off the 3 month anomaly) should they wish.

The aim of the plot is to make more evident the linkages between rainfall and NDVI variations from their average. Users should expect to see a rainfall deficit (below 100%) to be followed by the NDVI dropping below average (100%). And the reverse for above average rainfall.

However, there will be significant variations in the strength and clarity of these linkages. In wetter climates such linkage may simply not exist at all as variations in vegetation growth depend on drivers other than rainfall. But in drier semi-arid climates, where rainfall is the limiting factor for vegetation growth, such linkages should be strong and evident. The time lag between a rainfall anomaly and the corresponding NDVI anomaly (the vegetation response to that rainfall variation) also varies across regions. As a rule of thumb, a one month lag may be expected.

Which of the two rainfall anomalies (1 or 3 months) links better with NDVI anomalies is also variable and has to do with the type of soil and vegetation. The 3 month rainfall anomaly on balance should provide the better relationship, but users are encouraged to experiment.