Seasonal forecasting Not just seasonal averages Emily Wallace

Seasonal forecasting: Not just seasonal averages! Emily Wallace November 2012 © Crown copyright Met Office

Contents • Traditional seasonal forecasts • Current bespoke products • Tropical storms • Monsoon onset • Hot and cold days • Research into new products • Very wet days in Malaysia © Crown copyright Met Office

Traditional forecasts © Crown copyright Met Office

Glo. Sea 4 ensemble prediction of Nino 3. 4 SST anomaly from March 2010 © Crown copyright Met Office

Precipitation over SE Asia, summer 1998

Reminder: Seasonal forecasts are. . . • Broad-brush • Probabilistic • Large scale • Useful? ?

Impact models: Lake inflow © Crown copyright Met Office

Sector specific applications: Lake Volta, Ghana June forecasts of total July-Oct. inflow Corr. = 0. 69 Preceding rainfall and flow predictors plus seasonal forecast predictors Fcst Obs © Crown copyright Met Office

Reminder: Seasonal forecasts are. . . • Broad-brush • Probabilistic • Large scale • Useful • Wasting information? ?

Tropical storms © Crown copyright Met Office

Current forecast products Public forecast Deterministic forecasts • Provides a best estimate and forecast range (± 1 stdev interval) for: • Numbers of named storms • ACE index • During the following 6 months Tailored products Probabilistic forecasts • Probability distributions • Exceedance of thresholds (to aid assessment of risk) • Help to quantify and communicate the inherent uncertainties in the forecast. © Crown copyright Met Office

Western North Pacific tropical storm tracks in Glo. Sea 5 Storm tracks Model storms have characteristics that are similar to observed storms: • Model storms produced at same latitude • Many storms last longer than 5 days. • Produces straight moving and recurving tracks – important for landfall forecasts Track density • Model peak in TS frequency in the SCS as in observations • Tracks shifted too far north near the dateline. Model Observations June–November 2000– 2009 1 member June–November 1996– 2009 12 members Tropical storm frequency per 5 x 5° box © Crown copyright Met Office

Experimental multi-model seasonal tropical storm forecasts 20 13 240 Skill (1996 -2009) Tropical storms: 0. 47 Typhoons: 0. 62 ACE index: 0. 77 No. forecast ensemble members: 93 © Crown copyright Met Office

Monsoon onset © Crown copyright Met Office

Temporal evolution • Describe “temporal evolution” with local rainfall accumulations between 18 Sep-31 Jan • Express accumulation as percentage of long-term average season total Fraction of season total rainfall example: early onset in individual year • Heavy line: accumulated precip. from climatology Average time of onset • Thin line: accumulated precip. for individual year onset= 20% Time © Crown copyright Met Office

Observed mean evolution: 20 th isochrone • Colours indicate time of local arrival of 20% of average season total rainfall • GPCP average 18 Sep/30 Jan (19962009/10) Observed climatology © Crown copyright Met Office Hindcast climatology

Glo. Sea 4 forecast skill ROC scores 20 th isochrone for 1 August hindcasts Early arrival: © Crown copyright Met Office Late arrival:

Glo. Sea 4 Forecast probabilities for 2011 Short Rains (Sep-Nov) Early onset: Courtesy of Michael Vellinga © Crown copyright Met Office Late onset:

Observations for 2011 Courtesy of Lizzie Good © Crown copyright Met Office

Relocatable Northwest monsoon: Arrival of 30 th isocrone 2011 © Crown copyright Met Office

Hot and cold days © Crown copyright Met Office

What is an extreme day? Extreme day 90 th percentile E. g. 33. 5°C for March 34. 5°C for June © Crown copyright Met Office

What is an extreme day? 2010: 56 extreme days! 2006: No extreme days © Crown copyright Met Office

A global assessment Percentile approach is locally relevant Hamilton et al, 2012, JGR © Crown copyright Met Office

Global assessment: Had. GHCND © Crown copyright Met Office

Results © Crown copyright Met Office

Seasonal temperature: Skill of extremes vs. mean Mean Extremes South east Asia average: 0. 59 © Crown copyright Met Office South east Asia average: 0. 66 Difference -0. 3 0 0. 3 Grey=missing

Is the daily data really providing additional information? © Crown copyright Met Office

Relationship between extremes and mean: Hot days and annual mean temperature © Crown copyright Met Office

Number of days exceeding Relationship in South East Asia seasonally Temperature © Crown copyright Met Office DJF

Extent of the relationship seasonally © Crown copyright Met Office

Change forecast method t s a a c e r dat o F ily da © Crown copyright Met Office

Change forecast method Number of days exceeding Inferring the number of exceedances from the predicted seasonal mean anomaly Temperature © Crown copyright Met Office

Comparing methods Extremes counted from daily data South east Asia average: 0. 49 Difference South east Asia average: 0. 59 © Crown copyright Met Office Extremes inferred from seasonal mean -0. 3 0 0. 3 Grey=missing

Spearman’s Daily data from model gives no skilful information Percentile Extremes counted from daily data © Crown copyright Met Office Extremes inferred from mean

A closer look at the hindcast © Crown copyright Met Office

Product for UK: Cold days © Crown copyright Met Office

Temperature extremes summary • Extremes are predictable on seasonal and decadal timescales. • In general predictability comes from the strong relationship between the seasonal mean and the number of extremes © Crown copyright Met Office

Predictability of daily precipitation extremes…a first look © Crown copyright Met Office

Very wet days (90 th percentile) 10 very wet days © Crown copyright Met Office

Jolly wet days (90 th percentile) 10 very wet days © Crown copyright Met Office

Predictability of very wet days © Crown copyright Met Office

JJ MAM Very wet days: Skill of Total precip : Number of very wet days © Crown copyright Met Office ND ON Similar skill to that of seasonal total precipitation

A closer look at the hindcast Malaysian Peninsular Oct-Nov forecasts of very wet days © Crown copyright Met Office

Conclusions • The Met Office is predicting more user-relevant variables • Tropical storms: Analysis shows that skilful predictions could be made for the western North Pacific basin • Monsoon onset: A useful product in Africa – possible to relocate to South East Asia • Hot and cold days: predictable at seasonal lead time. Predictability linked to seasonal mean temperature predictability • Very wet days: Predictable over South East Asia. • Collaboration needed for best results © Crown copyright Met Office

Questions and answers © Crown copyright Met Office