We evaluate the performance of two 44 year ensemble seasonal hindcast time series for the Nino3 index produced as part of the DEMETER project. We show that the ensemble mean carries useful information out to six months. The ensemble spread, however, only carries useful information out to four months in one of the models, and two months in the other.
The coupled atmosphere-ocean variability of the Indo-Pacific on interannual to multidecadal timescales is investigated in a millennial control run of CCSM4 and in observations using a family of modes recovered in Part~I of this work from unprocessed SST data through nonlinear Laplacian spectral analysis (NLSA). It is found that ENSO and combination modes of ENSO with the annual cycle exhibit a seasonally synchronized southward shift of equatorial surface zonal winds and thermocline adjustment consistent with terminating El Nino and La Nina events. The surface wind patterns associated with thes…
Skillful seasonal prediction of lightning is crucial over several global hotspot regions, as it causes severe damages to infrastructures and losses of human life. While major emphasis has been given for predicting rainfall, prediction of lightning in one season advance remained uncommon, owing to the nature of the problem, which is short-lived local phenomenon. Here we show that on the seasonal time scale, lightning over the major global hot-spot regions is strongly tied with slowly varying global predictors (e.g., El Nino and Southern Oscillation). Moreover, the sub-seasonal variance of light…
Large socio-economic impact of the Indian Summer Monsoon (ISM) extremes motivated numerous attempts at its long range prediction over the past century. However, a rather estimated low potential predictability limit (PPL) of seasonal prediction of the ISM, contributed significantly by 'internal' interannual variability was considered insurmountable. Here we show that the 'internal' variability contributed by the ISM sub-seasonal (synoptic + intra-seasonal) fluctuations, so far considered chaotic, is partly predictable as found to be tied to slowly varying forcing (e.g. El Nino and Southern Osci…
The El Niño Southern Oscillation (ENSO) is the most important driver of interannual global climate variability and can trigger extreme weather events and disasters in various parts of the globe. Depending on the region of maximal warming, El Niño events can be partitioned into 2 types, Eastern Pacific (EP) and Central Pacific (CP) events. The type of an El Niño has a major influence on its impact and can even lead to either dry or wet conditions in the same areas on the globe. Here we show that the zonal difference $ΔT_{WP-CP}$ between the sea surface temperature anomalies (SSTA) in the equato…
Sub-seasonal Modulation and Predictability of Indian monsoon hourly Rainfall Extremes
Gauhati University（古哈提大学）；Indian Institute of Technology Madras（马德拉斯印度理工学院）；Indian Institute of Tropical Meteorology（印度热带气象研究所）；Cotton University（科顿大学）
Precursors, Pathways, and State-Dependent Reliability of Long-range ENSO Prediction in the CESM2 Seasonal-to-Multiyear Large Ensemble
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；NSF National Center for Atmospheric Research (NCAR)（美国国家科学基金会国家大气研究中心）；North Carolina State University（北卡罗来纳州立大学）；University of Hawai’i at Mānoa（夏威夷大学马诺阿分校）
Climatologies of the mixed layer depth (MLD) have been provided using several definitions based on temperature/density thresholds or hybrid approaches. The upper ocean pycnocline (UOP) that sits below the mixed layer base remains poorly characterised, though this transition layer is an ubiquitous feature of the ocean surface layer. Available hydrographic profiles provide near-global coverage of the world's ocean and are used to build a seasonal climatology of UOP properties -- intensity, depth, thickness -- to characterise the spatial and seasonal variations of upper ocean stratification. The …
The El Niño phenomenon, synonymously El Niño-Southern Oscillation (ENSO), is an anomalous climatic oscillation in the Equatorial Pacific that occurs once every 3-8 years. It affects the earth's climate on a global scale. Whether it is a cyclic or a sporadic event, or whether its apparently random behaviour can be explained by stochastic dynamics have remained matters of debate. Herein ENSO is viewed, unconventionally, as a two-dimensional dynamical system on a desktop. The main features of ENSO: irregularity, interannual variability, and the asymmetry between El Niño and La Niña are captured, …
Sensitivity of the ECMWF seasonal forecast model to CO2 and anthropogenic aerosol forcings: Experimental design and impact on climate trends
ECMWF（欧洲中期天气预报中心）；Department of Meteorology and Geophysics, University of Vienna（维也纳大学气象与地球物理系）；NCAS, University of Oxford, Atmospheric, Oceanic and Planetary Physics（牛津大学大气、海洋和行星物理国家环境科学研究中心）
AI-informed model-analogs for understanding subseasonal-to-seasonal jet stream and North American temperature predictability
Department of Atmospheric Science, Colorado State University（科罗拉多州立大学大气科学系）；Faculty of Computing and Data Sciences, Boston University（波士顿大学计算与数据科学学院）；NOAA Physical Sciences Laboratory（美国国家海洋和大气管理局物理科学实验室）
The skill of seasonal precipitation forecasts is assessed worldwide -grid point by grid point- for the forty-years period 1961-2000. To this aim, the ENSEMBLES multi-model hindcast is considered. Although predictability varies with region, season and lead-time, results indicate that 1) significant skill is mainly located in the tropics -20 to 40% of the total land areas-, 2) overall, SON (MAM) is the most (less) skillful season and 3) predictability does not decrease noticeably from one to four months lead-time -this is so especially in northern south America and the Malay archipelago, which s…
Skilful prediction of the seasonal Indian summer monsoon (ISM) rainfall (ISMR) at least one season in advance has great socio-economic value. It represents a lifeline for about a sixth of the world's population. The ISMR prediction remained a challenging problem with the sub-critical skills of the dynamical models attributable to limited understanding of the interaction among clouds, convection, and circulation. The variability of cloud hydrometeors (cloud ice and cloud water) in different time scales (3-7 days, 10-20 days and 30-60 days bands) are examined from re-analysis data during Indian …
Sea surface height anomalies observed by satellites in 1993--2012 are combined with simulation and observations by surface drifters and Argo floats to study water flow pattern in the Near Strait (NS) connected the Pacific Ocean with the Bering Sea. Daily Lagrangian latitudinal maps, computed with the AVISO surface velocity field, and calculation of the transport across the strait show that the flow through the NS is highly variable and controlled by mesoscale and submesoscale eddies in the area. On the seasonal scale, the flux through the western part of the NR is negatively correlated with th…
Scientific basis for long-lead seasonal prediction of Indian summer monsoon rainfall (ISMR) critical for water resource and crop strategy planning is lacking. Using a new predictor discovery method, here we show that the depth of 20 degree isotherm (D20) is least influenced by atmospheric noise and that the 18-month lead forecasts of ISMR have high potential skill (r = 0.86). The high potential predictability is due to smaller initial errors associated with the 18-month lead initial conditions and their slow growth associated with the El Nino and Southern Oscillation (ENSO). The potential skil…
We consider a highly idealized model for El Nino/Southern Oscillation (ENSO) variability, as introduced in an earlier paper. The model is governed by a delay differential equation for sea surface temperature in the Tropical Pacific, and it combines two key mechanisms that participate in ENSO dynamics: delayed negative feedback and seasonal forcing. We perform a theoretical and numerical study of the model in the three-dimensional space of its physically relevant parameters: propagation period of oceanic waves across the Tropical Pacific, atmosphere-ocean coupling, and strength of seasonal forc…
Despite the importance and vulnerability of small island nations and their ecosystems, they frequently have insufficient observations to provide baseline or long-term perspectives on climate variability and change, and global model experiments rarely have the resolution to include them. Many studies in observational climatology, climate modeling, and paleoclimate thus depend to varying degrees on an approximation equating near-surface marine and terrestrial island climates, often with direct implications for island societies and resources. Here we investigate the validity of this approximation…
Knowledge-guided machine learning for disentangling Pacific sea surface temperature variability across timescales
University of Maryland, College Park（马里兰大学帕克分校）；US NSF National Center for Atmospheric Research（美国国家科学基金会国家大气研究中心）；Cooperative Institute for Research in the Environmental Sciences（环境科学合作研究所；科罗拉多大学博尔德分校）；University of Colorado Boulder（美国国家海洋和大气管理局地球系统研究实验室）；NOAA Earth System Research Laboratories
The predictability of fields at the ocean surface in the northern Gulf of Mexico (GoM) is investigated through five ensembles of regional ocean simulations between 2014 and 2016. The ensembles explore two horizontal resolutions and different representations of the riverine inflow, and focus on the Loop Current system (LCS) and the Mississippi-Atchafalaya River System (MARS) interactions. The predictability of the surface fields is high in the northern GoM if the atmospheric forcing and the flow at Yucatan Channel are known, and the ensembles simulate similar LCS behavior up to 5 months. In ter…
Using Deep Learning to Identify Initial Error Sensitivity for Interpretable ENSO Forecasts
National Oceanic and Atmospheric Administration（美国国家海洋和大气管理局）；Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder（科罗拉多大学博尔德分校环境科学合作研究所）；European Centre for Medium Range Weather Forecasts (ECMWF)（欧洲中期天气预报中心）
We consider a delay differential equation (DDE) model for El-Nino Southern Oscillation (ENSO) variability. The model combines two key mechanisms that participate in ENSO dynamics: delayed negative feedback and seasonal forcing. We perform stability analyses of the model in the three-dimensional space of its physically relevant parameters. Our results illustrate the role of these three parameters: strength of seasonal forcing $b$, atmosphere-ocean coupling $κ$, and propagation period $τ$ of oceanic waves across the Tropical Pacific. Two regimes of variability, stable and unstable, are separated…
The path toward realizing the potential of seasonal forecasting and its socioeconomic benefits depends heavily on improving general circulation model based dynamical forecasting systems. To improve dynamical seasonal forecast, it is crucial to set up forecast benchmarks, and clarify forecast limitations posed by model initialization errors, formulation deficiencies, and internal climate variability. With huge cost in generating large forecast ensembles, and limited observations for forecast verification, the seasonal forecast benchmarking and diagnosing task proves challenging. In this study, …
Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
Yunnan Key Laboratory of Complex Systems and Brain-Inspired Intelligence, Kunming University of Science and Technology（云南复杂系统与脑启发智能重点实验室，昆明理工大学）；Faculty of Science, Kunming University of Science and Technology（昆明理工大学理学院）
Improving sub-seasonal wind-speed forecasts in Europe with a non-linear model
a LMD/IPSL, École Polytechnique, Institut Polytechnique de Paris, ENS,Université PSL, Sorbonne Université, CNRS, Palaiseau, 91120, France b INRIA, Paris, France c EDF R\&D, Palaiseau, France
Exascale Hybrid Numerical-AI Ensembles for Operational Flood-Season Forecasting in East Asia: 15-km Decadal Hindcasts and 1-km High-Resolution Capability
Tsinghua University（清华大学）；Sun Yat-Sen University（中山大学）；Jiangsu Provincial Meteorol. Bureau（江苏省气象局）；Beijing Normal University（北京师范大学）；Qinghai University（青海大学）；National Supercomputing Center in Wuxi（无锡国家超级计算中心）；National Supercomputing Center in Shenzhen（深圳国家超级计算中心）；CMA Earth System Modeling and Prediction Center（中国气象局地球系统模式与预报中心）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
Is the 2026 East Asia Summer Extreme Heat Forecast Credible?
Nanjing University of Information Science and Technology（南京信息工程大学）；CAMS（中国气象局）；Center for Earth System Modeling and Prediction of CMA (CEMC)（中国气象局地球系统模式与预测中心）；China Meteorological Administration（中国气象局）
Forecasting the El Nino-Southern Oscillation (ENSO) has been a subject of vigorous research due to the important role of the phenomenon in climate dynamics and its worldwide socioeconomic impacts. Over the past decades, numerous models for ENSO prediction have been developed, among which statistical models approximating ENSO evolution by linear dynamics have received significant attention owing to their simplicity and comparable forecast skill to first-principles models at short lead times. Yet, due to highly nonlinear and chaotic dynamics (particularly during ENSO initiation), such models hav…
