1. Bureau of Meteorology Activities as a GPC of Long Range Forecasts
Dr David Jones
Australian Bureau of Meteorology
EXPERT TEAM ON OPERATIONAL PREDICTIONS FROM SUB-SEASONAL TO LONG TIME-SCALES
EXETER, UK, MARCH 2014
Acknowledgement
Oscar Alves, Andrew Watkins, Lynette Bettio & Andrew Charles

2. Long Range Forecast Service
Delivering useful long range predictions for Australia and WMO member countries
Current seasonal outlooks for Australia based on the dynamical climate model POAMA
Probability of rainfall/temperature in Tercile/Above Below Median categories
A range of predictions of PDFs – e.g., probability of exceedence
Trial of dynamical intraseasonal forecasts
Dynamical model predictions for ocean conditions & and experimental forecasts for extreme events
Focus on the Pacific and Indian Oceans
Developing forecasts for TCs, coral bleaching and heatwaves

3. Recent POAMA 2.4M improvements
POAMA2.4m (multiweek) became fully operational in early 2013, and implemented for GPC services in early 2014
T47L17 + improved physics (land surface, radiation, gravity wave drag, cloud microphysics, etc)
Land surface scheme (ALI) is more realistic and initialized daily
Increased number of ensemble members of hind-cast (30 member) over the last 30 years (updated in real-time), providing better hindcast skill estimates
Real-time forecasts (33 ensemble members twice per week) using a 1981 to 2010 base period
Forecasts use a lagged 99 member ensemble
Improved accessibility – OpenDAP server

4. The Coupled Model: Predictive Ocean Atmosphere Model for Australia
Australian
Community
Ocean Model
(ACOM) v2
POAMA
BoM
Atmospheric
Model (BAM) v3
Simple
land-surface
model = + +
POAMA=Predictive Ocean Atmosphere Model for Australia
Forecasts run for 9 months
Atmospheric model:
Horizontal resolution ~250km
17 vertical levels
Ocean model:
Zonal resolution ~220 km
Meridional resolution ~55km (tropics) to ~165 km (poles)
25 vertical levels

5. Model+Assim Development
POAMA Development Phases and Timelines
POAMA Phases
2013
2014
2015
2016
2017
2018+
Model+Assim Development
Dev new coupled model, Dev assimilation, New physics, tune for seasonal, part of larger modelling effort
POAMA-2 (BAM+ACOM2: ~ 250km)
Operational
Build and Hindcast
Bring components together, build system, Coupled re-analyses, hind-cast set, Ensemble strategy, Skill and product evaluation
POAMA-3 (ACCESS CM1: ~ 150km)
Build and Hindcast
Operationalisation
Operational
Operationalisation
Complete comprehensive hindcast, re-analyses up to date, trans to op machine, op data feeds, trial period, eval op products, declare operational
POAMA-4 (ACCESS CM2: ~ 75km)
Build and Hindcast
Operationalisation
Model+Assim Development
Operational
NMOC/Services support,
evaluation, monitoring,
case studies, new products,
interface to applications, etc

6. Public Website Operational Products:
SSTs, NINO 3,3.4,4 & IOD available

7. Pacific SST skill: Temporal correlation of monthly SSTA
POAMA-2
POAMA-1.5
Correlation
Forecast Lead time (months)
ECMWF System 3
Frontier Research Centre Model (Japan)
NCEP Climate forecast system V1 & 2
POAMA 1.5 & 2

8. POAMA skill - Rainfall Correlation with (CMAP) Rainfall
How well does POAMA do with the rainfall patterns?
Highest correlation is found in the equatorial Pacific and parts of the southwest Pacific.

9. Reliability – Australian rainfall
M24
So what was POAMA’s reliability like?
Here is the reliability diagram for POAMA – when it’s forecasts are considered reliable, they fall within the grey area. The dots are relative to size, so as expected, the bigger dots fall in the middle probabilities. So how does POAMA perform? Well if we look at this dot here *CLICK* … etc
Not isolated to us though - *CLICK* other international models too.
Fig 4 from CAWCR Technical Report 39

10. Architecture for Seasonal Forecast Generation and Publication System

11. The Bureau as a GPC
Hindcasts verified following the LRFVS, though lagging behind with M2.4
Real time forecasts

12. New Rich GPC Webpave Forecast down to "points" as well as data

13. Building The Next Generation Outlook Service
SCO-Rebuild project – 2013/2014
Key Features
Range of user options: simple, intermediate and advanced
Richer user interface with map interface (“MetEye”) based on BoM.Map
Video briefing and contextual information
Drill down to locations
Seamless forecasting – seasonal and intraseasonal

14. The new Seasonal Climate Outlook
Planned release in July 2014
Based on user preferences
More interactive
More explanation
Multi-week forecasts
Coming: additional fields such as evaporation and humidity
The biggest change people will notice with the new SCO design, is it's interactivity. Click on a location, and an information bubble appears; zooming in for details or zooming out for the big picture.
Users will be able to tailor the information to their particular needs: location, type of data (rainfall, temp); format of data (tables, graphs); while still being able to view the national outlook. This was a big outcome of users' "wants" from the review process.
The new SCO will be easy to navigate, with easily accessible average (climatological) maps and forecast accuracy information. We hope to also include monthly podcasts with a climatologist explaining the outlook, as well as many educational features.
One of the many advantages of a dynamical model such as POAMA is it's potential to produce a more extensive range of outlooks for indicators such as sea surface temperatures, wind, humidity and evaporation. The design of our new SCO will enable the incorporation of additional fields as they become available, as well as products such as multi-week outlooks in addition to the 3-monthly outlooks.
It also opens up the possibility of a service for predicting climate extremes.

15. Capacity Building
Extensive training of the Pacific NMS personnel during in-country visits
Series of training workshops across the Pacific
Digitising to improve access to data to train and verify forecasts

16. The Bureau as a GPC
The BoM is a producer of LRFs, following a fixed time schedule
Products are available to other GPCs, RCCs and NMHSs
Forecasts provided to the LRF Lead Centre, LC MME and APCC
Hindcasts have been verified following the Standardized Verification System (some lag with new system)
Systems are scientifically documented
A new GPC website has been produced
The BoM is heavily involved in training and capacity building activities in the South Pacific