Using Generalized Extreme Value analysis, this study details the independent seasonal impacts of the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on rainfall extremes that cause many hydro-meteorological hazards and affect vulnerable populations in Indonesia, based on indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), for the period 1981-2019. Gridded Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is used to calculate maximum consecutive 5-day precipitation (Rx5d), total precipitation from days above 95 percentile (R95p), and maximum number of consecutive dry days (CDD). Consistent with previous studies, the ENSO and IOD impacts on rainfall extremes are shown to be strongest during the dry seasons (JJA-SON) and weaker in the wet seasons (DJF-MAM). Rainfall extremes appear to be widely influenced throughout Indonesia by ENSO, whereby extremes become drier (wetter) during El Niño (La Niña). Similarly, positive (negative) phases of the IOD lead to more extreme dry (wet) conditions. However, distinct from previous studies, as ENSO and IOD often co-occur, we also provide independent influences of the two climate modes. Low-level circulation northeast and southwest of Indonesia, both previously suggested as main drivers of impacts on Maritime Continent rainfall, are more closely associated with independent ENSO and IOD, respectively. For example, ENSO, independent of IOD, impacts rainfall extremes more in the northern and eastern regions of Indonesia, and the IOD, independent of ENSO, modulates rainfall extremes more over southern and western regions. Despite independent ENSO and IOD impacts understandably being found more eastward and westward of the country, respectively, details provided here help explain regional differences between rainfall extremes and ENSO and IOD, such as Jakarta in west Java, which is predominantly influenced by local forcing associated with the IOD.

This study conducted a detection and attribution analysis of the observed global and regional changes in extreme temperatures during 1951-2015. HadEX3 observations were compared with multimodel simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) using an optimal fingerprinting technique. Annual maximum daily maximum/minimum temperatures (TXx/TNx, warm extremes) and annual minimum daily maximum/minimum temperatures (TXn/TNn, cold extremes) over land were analyzed considering global, continental, and subcontinental scales. Response patterns (fingerprints) of extreme temperatures to anthropogenic (ANT), greenhouse gases (GHG), aerosols (AA), and natural (NAT) forcings were obtained from CMIP6 forced simulations. The internal variability ranges were estimated from preindustrial control simulations. A two-signal detection analysis where the observations are regressed onto ANT and NAT fingerprints simultaneously reveals that ANT signals are robustly detected in separation from NAT over global and all continental domains (North and South America, Europe, Asia, and Oceania) for most of the extreme indices. ANT signals are also detected over many subcontinental regions, particularly for warm extremes (more than 60% of 33 subregions). A three-signal detection analysis which considers GHG, AA, and NAT fingerprints simultaneously demonstrates that GHG signals are detected in isolation from other external forcings over global, continental, and several subcontinental domains especially for warm extremes, explaining most of the observed warming. Moreover, AA influences are detected for warm extremes over Europe and Asia, indicating significant offsetting cooling contributions. Overall, human influences are detected more frequently, compared to previous studies, particularly for cold extremes, due to the extended period and the improved spatial coverage of observations.

Waves exert stress on coastal structure, sediment transport, coastal erosion, and so on and are therefore an important contributor to coastal hazards. The coincidence of high waves and a high tide further augments coastal vulnerability. Waves are primarily driven by surface wind. Wave height increase associated with mean and extreme wind speed increase are well documented in literature (

No abstract

Understanding regional hydro‐climatic extreme responses to CO2 pathways is fundamental to climate change mitigation and adaptation. This study evaluates responses of extreme precipitation frequency (R30mm: days with precipitation ≥30 mm) over East Asia to idealized CO2 forcing using the Community Earth System Model (CESM1). Under a symmetric increase (ramp‐up, +1% per year until quadrupling level) and decrease (ramp‐down, about −1% per year back to the present level) of CO2 concentrations, East Asian R30mm shows an asymmetric response with higher frequency during the ramp‐down period. This hysteresis behavior is found to be due to a northwestward propagating wave response to the El Niño‐like warming, which induces a three‐cell (positive‐negative‐positive) R30mm difference pattern from central equatorial Pacific to East Asia. Monthly analysis further reveals that this asymmetry has a seasonal locking, occurring during July–September only, constrained by the background precipitation climatology over the sub‐tropical western Pacific.