The document discusses the recent strong El Niño event and its implications for seasonal rainfall distribution in Belg (FMAM) benefiting areas of Ethiopia. It finds that previous strong El Niño years saw normal to above normal rainfall during Belg, with particularly enhanced rainfall in 1983 and 2010. Based on this, the seasonal rainfall in 2016 is expected to have normal to above normal performance, potentially compensating for low rainfall during the Kiremt season. Further analysis using additional statistical forecasting methods is recommended.

1. Belg Outlook
Climate and Geospatial Research
Directorate(CGRD)
Fasil MEQUANINT January 2016

2. Objective
The intent of this piece of work is to review the current status of
the recent El Nino event and investigate the implications on the
performance of seasonal rainfall distribution on the Belg (FMAM)
benefiting areas.

3. Data and Methodology
 The analysis is based on comparisons of rainfall
performance in past El Nino events based on observation data
from 160 weather stations and CHIRPS v2 5km gridded data.
 The analysis involves computing rainfall analysis during
analogue years and their percent of deviations from long term
climatology and it also compares the expected performance
with Normal years (non ENSO events)

4. Oceanic Niño Index (ONI)
• The ONI is based on SST departures from average in the Niño 3.4
region;
• It is a principal measure for monitoring, assessing, and predicting
ENSO.
• Defined as the three-month running-mean SST departures in the
Niño 3.4 region.
• It is one index that helps to place current events into a historical
perspective

5. Niño Region SST Departures (oC) Recent
Evolution
The latest weekly SST
departures are:
Niño 3.4 2.7ºC
Niño 3 2.6ºC
Niño 1+2 1.6ºC

6. NOAA Operational Definitions for El Niño and La Niña
 El Niño: characterized by a positive ONI greater than or equal to
+0.5ºC.
 La Niña: characterized by a negative ONI less than or equal to -
0.5ºC.
 By historical standards, to be classified as a full-fledged El Niño or
La Niña episode, these thresholds must be exceeded for a period of at
least 5 consecutive overlapping 3-month seasons.
 CPC considers El Niño or La Niña conditions to occur when the
monthly Niño3.4 OISST departures meet or exceed +/- 0.5ºC along
with consistent atmospheric features.
 These anomalies must also be forecasted to persist for 3
consecutive months.

7. ONI (ºC): Evolution
since 1950
The most recent ONI value
(September – November 2015)
is 2.0oC.
El Niño
La Niña
Neutral

8. Historical El Niño and La Niña Episodes Based on the ONI
 Recent Pacific warm (red) and cold (blue) periods based on a threshold of +/-
0.5 ºC for the Oceanic Nino Index (ONI).
 For historical purposes, periods of below and above normal SSTs are colored
in blue and red when the threshold is met for a minimum of 5 consecutive over-
lapping seasons.
Year DJF JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND NDJ
2003 0.9 0.6 0.4 0.0 -0.2 -0.1 0.1 0.2 0.3 0.4 0.4 0.4
2004 0.3 0.2 0.1 0.1 0.2 0.3 0.5 0.7 0.7 0.7 0.7 0.7
2005 0.6 0.6 0.5 0.5 0.4 0.2 0.1 0.0 0.0 -0.1 -0.4 -0.7
2006 -0.7 -0.6 -0.4 -0.2 0.0 0.1 0.2 0.3 0.5 0.8 0.9 1.0
2007 0.7 0.3 0.0 -0.1 -0.2 -0.2 -0.3 -0.6 -0.8 -1.1 -1.2 -1.3
2008 -1.4 -1.3 -1.1 -0.9 -0.7 -0.5 -0.3 -0.2 -0.2 -0.3 -0.5 -0.7
2009 -0.8 -0.7 -0.4 -0.1 0.2 0.4 0.5 0.6 0.7 1.0 1.2 1.3
2010 1.3 1.1 0.8 0.5 0.0 -0.4 -0.8 -1.1 -1.3 -1.4 -1.3 -1.4
2011 -1.3 -1.1 -0.8 -0.6 -0.3 -0.2 -0.3 -0.5 -0.7 -0.9 -0.9 -0.8
2012 -0.7 -0.6 -0.5 -0.4 -0.3 -0.1 0.1 0.3 0.4 0.4 0.2 -0.2
2013 -0.4 -0.5 -0.3 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.3
2014 -0.5 -0.6 -0.4 -0.2 0.0 0.0 0.0 0.0 0.2 0.4 0.6 0.6
2015 0.5 0.4 0.5 0.7 0.9 1.0 1.2 1.5 1.8 2.0

9. CPC/IRI Probabilistic ENSO Outlook
The chance of El Niño gradually decreases into the spring and ENSO-
neutral is favored by May-June-July (MJJ) 2016.

10. IRI/CPC Pacific Niño
3.4 SST Model Outlook
Figure provided by the International Research
Institute (IRI) for Climate and Society
(updated 15 December 2015).
Most models indicate that
Niño 3.4 will remain
strongly positive into early
2016.
Positive anomalies are
predicted to weaken into
the Northern Hemisphere
Spring 2016.

11. El Nino events
Recent analogue El Nino (in green color)
Strength
Season
JJA JAS ASO SON OND
VSE 1997 - 1998 1.4 1.7 2 2.2 2.3
VSE 2015 - 2016 1.2 1.5 1.8 2 2.3
SE 1972 - 1973 1.1 1.3 1.5 1.8 2
SE 1965 - 1966 1 1.3 1.6 1.7 1.8
VSE 1982 - 1983 0.8 1 1.5 1.9 2.1
ME* 1987 - 1988 1.4 1.6 1.6 1.4 1.2
SE 1957 - 1958 1 1.2 1.1 1.2 1.3
ME 2002 - 2003 0.8 0.9 1 1.2 1.3
ME 1963 - 1964 0.7 1 1.1 1.2 1.2
ME 1991 - 1992 0.7 0.7 0.7 0.8 1.2
ME 2009 - 2010 0.5 0.6 0.7 1 1.2
VSE-Very Strong El Nino, SE-Strong El Nino, ME-Moderate El Nino

12. Belg 2016 Outlook
The seasonal outlooks combine the effects of long-term trends, soil moisture,
and, when appropriate, ENSO.
Comparison of previous El Nino years, their ensemble mean and long-term
climatology ( data source: CHIRPS v2)

13. Belg 2016 Outlook
(as previous, data source: Observed (160 weather stations)

14. Belg 2016 Outlook
Comparison of % of deviation previous El Nino years, their ensemble mean
with long-term climatology ( data source: CHIRPS v2)

15. Belg 2016 Outlook
Comparison of % of
deviation previous El Nino
years, their ensemble
mean with long-term
climatology ( data source:
Observation)

16. Summary
 El Niño conditions are present.
 Positive equatorial sea surface temperature (SST) anomalies continue across
most of the Pacific Ocean.
 El Niño is expected to remain strong through the Northern Hemisphere
winter 2015-16, with a transition to ENSO-neutral anticipated during late
spring or early summer 2016.
 In previous El Nino years, the performance of the seasonal rain in belg
benefiting areas was normal and above normal performance.
 The performance was highly enhanced in the case of 1983 and 2010
compared to the other years
 Consequently, the season will have normal and above normal performance in
2016.
 This will create an opportunity to compensate the production gap occurred
during the Kiremt season

17. The way forward
 This work is based on simple analogue method
because it was conducted solely based on self-
initiation
 The author recommends further investigation
based on other statistical forecasting methods.