Key Points:• MJO influences probability of extreme rainfall over southeast Asia • A seasonal forecast system reproduces the influence and shows prediction skills • Prediction of extreme events will help preparedness AbstractThe influence of Madden-Julian Oscillation (MJO) on the rainfall distribution of Southeast Asia is studied using TRMM satellite-derived rainfall and rain gauge data. It is shown that convectively active (suppressed) phases of MJO can increase (decrease) the probability of extreme rain events over the land regions by about 30-50% (20-25%) during November-March season. The influence of MJO on localized rainfall extremes are also observed both in rainfall intensity and duration. The Met Office Global Seasonal forecasting system seasonal forecasting system is shown to reproduce the MJO influence on rainfall distribution well despite the model biases over land. Skills scores for forecasting 90th percentile extreme rainfall shows significant skills for convective phases. This study demonstrates the feasibility of deriving probabilistic forecasts of extreme rainfall at medium range.
Sea surface temperature (SST) anomalies in the tropical Pacific are commonly used indicators for diagnosing the El Niño-Southern Oscillation (ENSO) state. Global warming has the potential to affect these indicators so that the indicators provide a less representative picture of El Niño/La Niña developments. The SST trend has not been uniform across the Tropics; hence, accounting for local trends may not account for widespread warming. A method is proposed to remove tropical SST trend from the Niño3.4 index, one of the most common indices for monitoring ENSO. The trend and climatology analysis periods are selected based on the Interdecadal Pacific Oscillation. The climatology period contains an equal number of years with positive and negative phases , while the trend is estimated over a longer period with no significant trend in the Interdecadal Pacific Oscillation . Furthermore, the trend is estimated using three SST datasets and sampling of the time period to account for uncertainty in measurements. Once the tropical trend is removed, new Niño3.4 values are calculated and a new ENSO classification proposed to re-classify ENSO events since 1976. The recent 3 years with the largest deviation due to global warming (2014)(2015)(2016), once corrected contain the full ENSO cycle with neutral, strong El Niño, and La Niña years. These events based on the new classification align well with other ENSO predictors, such as outgoing longwave radiation and zonal wind at 850 hPa, particularly for marginal cases such as the 2016 La Niña event. These results have implications for how ENSO is monitored and predicted in relation to climate change.
<p>Southeast Asia (SEA) is a rapidly developing and densely populated region that is home to over 600 million people. This, together with the region&#8217;s high sensitivity, exposure and low adaptive capacities, makes it particularly vulnerable to climate change and extremes such as floods, droughts and tropical cyclones. While the last decade saw some countries in SEA develop their own climate change projections, studies were largely uncoordinated and most countries still lack the capability to independently produce robust future climate information. Following a proposal from the World Meteorological Organisation (WMO) Regional Association (RA) V working group on climate services, the ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series was conceived in 2017 to bridge these gaps in regional synergies. The ARCDAP series has been organised annually since 2018 by the ASEAN Specialised Meteorological Centre (hosted by Meteorological Service Singapore) with support from WMO through the Canada-funded Climate Risk and Early Warning Systems (Canada-CREWS) initiative.</p> <p>This presentation will cover the activities and outcomes from the first two workshops, as well as the third which will be held in February 2020. The ARCDAP series has so far brought together representatives from ASEAN National Meteorological and Hydrological Services (NMHSs), climate scientists and end-users from policy-making and a variety of vulnerability and impact assessment (VIA) sectors, to discuss and identify best practices regarding the delivery of climate change information, data usage and management, advancing the science etc. Notable outputs include two comprehensive workshop reports and a significant regional contribution to the HadEX3 global land in-situ-based dataset of temperature and precipitation extremes, motivated by work done with the ClimPACT2 software.</p> <p>The upcoming third workshop will endeavour to encourage the uptake of the latest ensemble of climate simulations from the Coupled Model Intercomparison Project (CMIP6) using CMIP-endorsed tools such as ESMValTool. This will address the need for ASEAN climate change practitioners to upgrade their knowledge of the latest global climate model database. It is anticipated that with continued support from WMO, the series will continue with the Fourth workshop targeting the assessment of downscaling experiments in 2021.</p>
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