In-Season Context Monitoring

Use case 1:
Allocating water

trucks
 

Use case 2:
Scaling farmer fodder schools

Use case 3:

 

Forecast based finance within-season

What's the challenge?

Within Concern Worldwide itself, climate information is used within context monitoring.  Weather and climate information are input into short term reactionary decision making (e.g. whether to send water trucks to a location), longer term resilience planning (e.g. how much to expand farmer field schools or fodder production), or simply sending more monitoring teams into the field to better assess the situation.

At the start and end of each rainy season, it's important to assess how the seasons performed and how the next season might affect local communities across Somalia.  It's vital that this climate analysis is differentiated by climate, geography and livelihood.  

Much of the climate information used comes from looking at climate portals as the season progresses, validated by reports from local staff in Somalia.

Context is king

Normally a household going from three meals a day down to two meals a day would ring all the alarm bells. But if that is a farming family in the midst of a one-in-ten year drought, it might be a sign that the family is actually relatively resiliant - everyone around them could be on one meal a day.

Hard quantitate thresholds of resilience can often be misleading and the same applies to climate thresholds of a 'bad year'.  The same climate event might impact the same family very differently depending on their current intrinsic level of coping ability.  So it's important to be able to pull climate information into a larger context monitoring framework. 


What does Concern need?

One problem that Concern is facing is that they need to spend a lot of time interpreting existing climate data products.  Too much time.  It can be difficult to know what's the best data source to use for a given location, what the uncertainty on it is and what are the best statistics for that context.  For example this might include

  • Proximity to a water source
  • Livelihood type e.g.
    • pastoralist sheep & goats
    • pastoralist camels
    • Agropastorialist (Sorghum, maize)
    • Gravity irrigation riverine farmers
  • Climate zone
    • Areas with one rainy season
    • Areas with 2 rainy seasons with or without hagaa or karaan seasons.
  • Proximity to cities
    • Peri-urban areas
    • Rural areas

To take all of these (and more) into account, it would be useful to look across livelihood zones, or across political districts, or at a specific location.