1. The 2016/2017 La Niña and S2S prediction for South-East Asia
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Thea Turkington
Acknowledge colleagues: Raizan Rahmat, Bertrand Timbal, and Jia Liu
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FOCRAII
April 25th 2017

2. Part A: The 2016/2017 La Niña (?)

3. Warming in the tropics
Warming trend in the tropics ( K/month)
Just not in the Nino3.4 region
Temperature anomaly
SST anomaly
The pattern of the trend is La nina like (partly at least due to the IPO flip positive to negative)
CPC: La Niña conditions are present, with transition to ENSO-neutral favoured during Jan Mar
SST
OLR anomalies
Enhanced low level easterlies *
BOM: La Niña Watch
Only cloudiness shows La Niña characteristics
SOI negative since Oct, but in neutral range
SST in neutral range
APCC: Expected ENSO neutral phase to prevail
Only weak negative SSTs (Nino3.4 & IOD)
*partly masked by intra-seasonal activity
ERSST v4.0 SST dataset, trend
Black box = Nino3.4, green boxes = Tri-pole index (IPO), blue box = Nino.West
Red = global temperature (NOAA)
Blue =SST trend 30°S – 30°N (ERSST)

4. Nino 3.4 2016 with/without removing trend
Nino 3.4
Without removing trend
Removing trend
Min
Max 5%
95%
Jan-16
2.17
2.48
1.94
2.33
Feb-16
1.91
2.10
1.69
1.96
Mar-16
1.55
1.63
1.31
1.48
Apr-16
1.00
1.09
0.78
0.89
May-16
0.42
0.61
0.20
0.41
Jun-16
-0.11
0.13
-0.33
-0.08
Jul-16
-0.40
-0.26
-0.62
-0.43
Aug-16
-0.56
-0.78
-0.60
Sep-16
-0.68
-0.94
-0.77
Oct-16
-0.79
-0.67
-1.03
-0.83
Nov-16
-1.05
-0.84
Dec-16
-0.76
-1.00
-0.71
Using 3 SST datasets (ERSST v4.0, HadISST v1, COBE)

5.
Neutral
El Niño
La Niña

6. Removing tropical trend Nino 3.4 index
2016/17 and past events
2016
Removing tropical trend Nino 3.4 index
Nino 3.4 index
La Niña events
El Niño events
Using ERSST v4.0 dataset
2015/2016

7. DETRENDING IS IMPORTANT
Part A: Summary
DETRENDING IS IMPORTANT
Major events are still the with/without removing trend
Marginal events differ
In 2016, more aligned with other atmospheric indicators
What does this mean for 2017?

8. Part B: S2S prediction for South-East Asia
-S2S-SEA Workshop 1
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9. S2S-SEA Capability Building Programme (Objectives & Activities)
Establish a project to investigate the usefulness of these forecasts in the database for our region.
A research project to prepare for release of real time products.
Involve all ASEAN NMSs who are interested and engage S2S international experts.
(Li and Robertson, 2015, MWR)
JJAS correlation score

10. S2S-SEA Workshop Series
S2S-SEA I
S2S-SEA II
S2S-SEA III
S2S-SEA IV
AIMS:
Understand S2S better
Know what’s available
What skill assessment methodologies to use
How to move forward in subsequent workshops
Recent workshop
27 Feb – 3 Mar
Research

11. Overview of S2S-SEA I
Lectures: Andrew Robertson (IRI), Frederic Vitart (ECMWF), From Meteorological Services Singapore: Raizan Rahmat, Thea Turkington, Jia Liu
Regional Participants: One from each 10 countries + 6 extra
Topics:
Introduction:
S2S Background, database, ensemble generation etc.
Tools:
Virtual box, NetCDF, python
Observation datasets
Rainfall :TRMM
Temperature: ERA-I
Downloading and processing data
ECMWF – various lead times (+1 week to +4 weeks)
Model verification
Deterministic:
CORA (relationship), MSSS (bias)

12. Case Study: 03 – 09 Nov ‘11

13. Temperature CORA and MSSS (1998-2014)
ECMWF verified against ERA-Interim

14. Precipitation CORA and MSSS (1998-2014)
ECMWF verified against TRMM

15. What next? S2S-SEA II Possibilities: Probabilistic verification
Downscaling to station
Diagnostic studies
Product development
Challenges:
Continuity (same participants?)
A lot to cover within short period
Availability of data

16. Part B: Summary