scholarly journals A Comprehensive Assessment of CFS Seasonal Forecasts over the Tropics*

2012 ◽  
Vol 27 (1) ◽  
pp. 3-27 ◽  
Author(s):  
K. P. Sooraj ◽  
H. Annamalai ◽  
Arun Kumar ◽  
Hui Wang
Keyword(s):  
Real Time ◽  
El Niño ◽  
El Nino ◽  
Seasonal Prediction ◽  
Skill Score ◽  
Seasonal Forecasts ◽  
Skill Scores ◽  
Different Types ◽  
The Tropics ◽  
Sst Anomalies

Abstract The 15-member ensemble hindcasts performed with the National Centers for Environmental Prediction Climate Forecast System (CFS) for the period 1981–2005, as well as real-time forecasts for the period 2006–09, are assessed for seasonal prediction skills over the tropics, from deterministic (anomaly correlation), categorical (Heidke skill score), and probabilistic (rank probability skill score) perspectives. Further, persistence, signal-to-noise ratio, and root-mean-square error analyses are also performed. The CFS demonstrates high skill in forecasting El Niño–Southern Oscillation (ENSO) related sea surface temperature (SST) anomalies during developing and mature phases, including that of different types of El Niño. During ENSO, the space–time evolution of anomalous SST, 850-hPa wind, and rainfall along the equatorial Pacific, as well as the mechanisms involved in the teleconnection to the tropical Indian Ocean, are also well represented. During ENSO phase transition and in the summer, the skill of forecasting Pacific SST anomalies is modest. An examination of CFS ability in forecasting seasonal rainfall anomalies over the U.S. Affiliated Pacific Islands (USAPI) indicates that forecasting the persistence of dryness from El Niño winter into the following spring/summer is skillful at leads > 3 months. During strong El Niño years the persistence is predicted by all members with a 6-month lead time. Also, the model is skillful in predicting regional rainfall responses during different types of El Niño. Since both deterministic and probabilistic skill scores converge, the suggestion is that the forecast is useful. The model’s skill in the real-time forecasts for the period 2006–09 is also discussed. The results suggest the feasibility that a dynamical-system-based seasonal prediction of precipitation over the USAPI can be considered.

scholarly journals Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect

2019 ◽  
Vol 5 (7) ◽  
pp. eaav4157 ◽  
Author(s):  
Meng Gao ◽  
Peter Sherman ◽  
Shaojie Song ◽  
Yueyue Yu ◽  
Zhiwei Wu ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
Seasonal Prediction ◽  
Indian Government ◽  
Northern India ◽  
Multivariable Regression Model ◽  
Aerosol Pollution ◽  
Multivariable Regression ◽  
High Degree ◽  
Sst Anomalies

As China makes every effort to control air pollution, India emerges as the world’s most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulated mainly by a combination of El Niño and the Antarctic Oscillation (AAO). Both El Niño sea surface temperature (SST) anomalies and AAO-induced Indian Ocean Meridional Dipole SST anomalies can persist from autumn to winter, offering prospects for a prewinter forecast of wintertime aerosol pollution over northern India. We constructed a multivariable regression model incorporating El Niño and AAO indices for autumn to predict wintertime AOD. The prediction exhibits a high degree of consistency with observation, with a correlation coefficient of 0.78 (P < 0.01). This statistical model could allow the Indian government to forecast aerosol pollution conditions in winter and accordingly improve plans for pollution control.

scholarly journals Seasonal Forecasting in the Pacific Using the Coupled Model POAMA-2

2013 ◽  
Vol 28 (3) ◽  
pp. 668-680 ◽  
Author(s):  
Andrew Cottrill ◽  
Harry H. Hendon ◽  
Eun-Pa Lim ◽  
Sally Langford ◽  
Kay Shelton ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
Regional Climate ◽  
Coupled Model ◽  
Forecast Model ◽  
Seasonal Prediction ◽  
La Niña ◽  
Spatial And Temporal Variability ◽  
Seasonal Forecasts ◽  
La Nina

Abstract The development of a dynamical model seasonal prediction service for island nations in the tropical South Pacific is described. The forecast model is the Australian Bureau of Meteorology's Predictive Ocean–Atmosphere Model for Australia (POAMA), a dynamical seasonal forecast system. Using a hindcast set for the period 1982–2006, POAMA is shown to provide skillful forecasts of El Niño and La Niña many months in advance and, because the model faithfully simulates the spatial and temporal variability of rainfall associated with displacements of the southern Pacific convergence zone (SPCZ) and ITCZ during La Niña and El Niño, it also provides good predictions of rainfall throughout the tropical Pacific region. The availability of seasonal forecasts from POAMA should be beneficial to Pacific island countries for the production of regional climate outlooks across the region.

scholarly journals Effect of the El Niño Decaying Pace on the East Asian Summer Monsoon Circulation Pattern during Post-El Niño Summers

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 140
Author(s):  
Wenping Jiang ◽  
Gen Li ◽  
Gongjie Wang
Keyword(s):  
El Niño ◽  
Asian Monsoon ◽  
East Asian Monsoon ◽  
El Nino ◽  
East Asian ◽  
Circulation Pattern ◽  
Northwest Pacific ◽  
Monsoon Circulation ◽  
Circulation Patterns ◽  
Sst Anomalies

El Niño events vary from case to case with different decaying paces. In this study, we demonstrate that the different El Niño decaying paces have distinct impacts on the East Asian monsoon circulation pattern during post-El Niño summers. For fast decaying (FD) El Niño summers, a large-scale anomalous anticyclone dominates over East Asia and the North Pacific from subtropical to mid-latitude; whereas, the East Asian monsoon circulation display a dipole pattern with anomalous northern cyclone and southern anticyclone for slow decaying (SD) El Niño summers. The difference in anomalous East Asian monsoon circulation patterns was closely associated with the sea surface temperature (SST) anomaly patterns in the tropics. In FD El Niño summers, the cold SST anomalies in the tropical central-eastern Pacific and warm SST anomalies in the Maritime Continent induce the anticyclone anomalies over the Northwest Pacific. In contrast, the warm Kelvin wave anchored over the tropical Indian Ocean during SD El Niño summers plays a crucial role in sustaining the anticyclone anomalies over the Northwest Pacific. In particular, the opposite atmospheric circulation anomaly patterns over Northeast Asia and the mid-latitude North Pacific are mainly modulated by the stationary Rossby wave trains triggered by the opposite SST anomalies in the tropical eastern Pacific during FD and SD El Niño summers. Finally, the effect of distinct summer monsoon circulation patterns associated with the El Niño decay pace on the summer climate over East Asia are also discussed.

scholarly journals The Response of Tropical Atmospheric Energy Budgets to ENSO*

2013 ◽  
Vol 26 (13) ◽  
pp. 4710-4724 ◽  
Author(s):  
Michael Mayer ◽  
Kevin E. Trenberth ◽  
Leopold Haimberger ◽  
John T. Fasullo
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Warm Pool ◽  
Smooth Transition ◽  
Energy Budgets ◽  
Enso Events ◽  
El Niño Modoki ◽  
Static Energy ◽  
The Tropics

Abstract The variability of zonally resolved tropical energy budgets in association with El Niño–Southern Oscillation (ENSO) is investigated. The most recent global atmospheric reanalyses from 1979 to 2011 are employed with removal of apparent discontinuities to obtain best possible temporal homogeneity. The growing length of record allows a more robust analysis of characteristic patterns of variability with cross-correlation, composite, and EOF methods. A quadrupole anomaly pattern is found in the vertically integrated energy divergence associated with ENSO, with centers over the Indian Ocean, the Indo-Pacific warm pool, the eastern equatorial Pacific, and the Atlantic. The smooth transition, particularly of the main maxima of latent and dry static energy divergence, from the western to the eastern Pacific is found to require at least two EOFs to be adequately described. The canonical El Niño pattern (EOF-1) and a transition pattern (EOF-2; referred to as El Niño Modoki by some authors) form remarkably coherent ENSO-related anomaly structures of the tropical energy budget not only over the Pacific but throughout the tropics. As latent and dry static energy divergences show strong mutual cancellation, variability of total energy divergence is smaller and more tightly coupled to local sea surface temperature (SST) anomalies and is mainly related to the ocean heat discharge and recharge during ENSO peak phases. The complexity of the structures throughout the tropics and their evolution during ENSO events along with their interactions with the annual cycle have often not been adequately accounted for; in particular, the El Niño Modoki mode is but part of the overall evolutionary patterns.

scholarly journals Role of the Indo-Pacific Interbasin Coupling in Predicting Asymmetric ENSO Transition and Duration

2012 ◽  
Vol 25 (9) ◽  
pp. 3321-3335 ◽  
Author(s):  
Masamichi Ohba ◽  
Masahiro Watanabe
Keyword(s):  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
La Nina ◽  
The Pacific ◽  
Enso Asymmetry ◽  
Sst Anomalies

Warm and cold phases of El Niño–Southern Oscillation (ENSO) exhibit a significant asymmetry in their transition/duration such that El Niño tends to shift rapidly to La Niña after the mature phase, whereas La Niña tends to persist for up to 2 yr. The possible role of sea surface temperature (SST) anomalies in the Indian Ocean (IO) in this ENSO asymmetry is investigated using a coupled general circulation model (CGCM). Decoupled-IO experiments are conducted to assess asymmetric IO feedbacks to the ongoing ENSO evolution in the Pacific. Identical-twin forecast experiments show that a coupling of the IO extends the skillful prediction of the ENSO warm phase by about one year, which was about 8 months in the absence of the IO coupling, in which a significant drop of the prediction skill around the boreal spring (known as the spring prediction barrier) is found. The effect of IO coupling on the predictability of the Pacific SST is significantly weaker in the decay phase of La Niña. Warm IO SST anomalies associated with El Niño enhance surface easterlies over the equatorial western Pacific and hence facilitate the El Niño decay. However, this mechanism cannot be applied to cold IO SST anomalies during La Niña. The result of these CGCM experiments estimates that approximately one-half of the ENSO asymmetry arises from the phase-dependent nature of the Indo-Pacific interbasin coupling.

scholarly journals ENSO’s Impact on the Gap Wind Regions of the Eastern Tropical Pacific Ocean*

2012 ◽  
Vol 25 (10) ◽  
pp. 3549-3565 ◽  
Author(s):  
Michael A. Alexander ◽  
Hyodae Seo ◽  
Shang Ping Xie ◽  
James D. Scott
Keyword(s):  
Pacific Ocean ◽  
Boundary Conditions ◽  
El Niño ◽  
El Nino ◽  
Tropical Pacific ◽  
Surface Fluxes ◽  
Ocean Dynamics ◽  
Tropical Pacific Ocean ◽  
Variable Surface ◽  
Sst Anomalies

Abstract The recently released NCEP Climate Forecast System Reanalysis (CFSR) is used to examine the response to ENSO in the northeast tropical Pacific Ocean (NETP) during 1979–2009. The normally cool Pacific sea surface temperatures (SSTs) associated with wind jets through the gaps in the Central American mountains at Tehuantepec, Papagayo, and Panama are substantially warmer (colder) than the surrounding ocean during El Niño (La Niña) events. Ocean dynamics generate the ENSO-related SST anomalies in the gap wind regions as the surface fluxes damp the SSTs anomalies, while the Ekman heat transport is generally in quadrature with the anomalies. The ENSO-driven warming is associated with large-scale deepening of the thermocline; with the cold thermocline water at greater depths during El Niño in the NETP, it is less likely to be vertically mixed to the surface, particularly in the gap wind regions where the thermocline is normally very close to the surface. The thermocline deepening is enhanced to the south of the Costa Rica Dome in the Papagayo region, which contributes to the local ENSO-driven SST anomalies. The NETP thermocline changes are due to coastal Kelvin waves that initiate westward-propagating Rossby waves, and possibly ocean eddies, rather than by local Ekman pumping. These findings were confirmed with regional ocean model experiments: only integrations that included interannually varying ocean boundary conditions were able to simulate the thermocline deepening and localized warming in the NETP during El Niño events; the simulation with variable surface fluxes, but boundary conditions that repeated the seasonal cycle, did not.

scholarly journals A Probabilistic Multimodel Ensemble Approach to Seasonal Prediction

2009 ◽  
Vol 24 (3) ◽  
pp. 812-828 ◽  
Author(s):  
Young-Mi Min ◽  
Vladimir N. Kryjov ◽  
Chung-Kyu Park
Keyword(s):  
Real Time ◽  
Gaussian Approximation ◽  
Seasonal Prediction ◽  
Asia Pacific ◽  
Ensemble Prediction ◽  
Prediction System ◽  
Sampling Errors ◽  
Seasonal Forecasts ◽  
Multimodel Ensemble ◽  
Ensemble Prediction System

Abstract A probabilistic multimodel ensemble prediction system (PMME) has been developed to provide operational seasonal forecasts at the Asia–Pacific Economic Cooperation (APEC) Climate Center (APCC). This system is based on an uncalibrated multimodel ensemble, with model weights inversely proportional to the errors in forecast probability associated with the model sampling errors, and a parametric Gaussian fitting method for the estimate of tercile-based categorical probabilities. It is shown that the suggested method is the most appropriate for use in an operational global prediction system that combines a large number of models, with individual model ensembles essentially differing in size and model weights in the forecast and hindcast datasets being inconsistent. Justification for the use of a Gaussian approximation of the precipitation probability distribution function for global forecasts is also provided. PMME retrospective and real-time forecasts are assessed. For above normal and below normal categories, temperature forecasts outperform climatology for a large part of the globe. Precipitation forecasts are definitely more skillful than random guessing for the extratropics and climatological forecasts for the tropics. The skill of real-time forecasts lies within the range of the interannual variability of the historical forecasts.

scholarly journals Lagged Ensembles, Forecast Configuration, and Seasonal Predictions

2013 ◽  
Vol 141 (10) ◽  
pp. 3477-3497 ◽  
Author(s):  
Mingyue Chen ◽  
Wanqiu Wang ◽  
Arun Kumar
Keyword(s):  
Lead Time ◽  
Geographical Location ◽  
Seasonal Prediction ◽  
Skill Score ◽  
Negative Influence ◽  
Positive Influence ◽  
Prediction Skill ◽  
Ensemble Size ◽  
Seasonal Forecasts ◽  
Ensemble Forecasts

Abstract An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), is presented. The focus of the analysis is on the construction of lagged ensemble forecasts with increasing lead time (thus allowing use of larger ensemble sizes) and its influence on seasonal prediction skill. Predictions of seasonal means of sea surface temperature (SST), 200-hPa height (z200), precipitation, and 2-m air temperature (T2m) over land are analyzed. Measures of prediction skill include deterministic (anomaly correlation and mean square error) and probabilistic [rank probability skill score (RPSS)]. The results show that for a fixed lead time, and as one would expect, the skill of seasonal forecast improves as the ensemble size increases, while for a fixed ensemble size the forecast skill decreases as the lead time becomes longer. However, when a forecast is based on a lagged ensemble, there exists an optimal lagged ensemble time (OLET) when positive influence of increasing ensemble size and negative influence due to an increasing lead time result in a maximum in seasonal prediction skill. The OLET is shown to depend on the geographical location and variable. For precipitation and T2m, OLET is relatively longer and skill gain is larger than that for SST and tropical z200. OLET is also dependent on the skill measure with RPSS having the longest OLET. Results of this analysis will be useful in providing guidelines on the design and understanding relative merits for different configuration of seasonal prediction systems.

scholarly journals Precipitation Prediction Skill for the West Coast United States: From Short to Extended Range

2018 ◽  
Vol 32 (1) ◽  
pp. 161-182 ◽  
Author(s):  
Baoxiang Pan ◽  
Kuolin Hsu ◽  
Amir AghaKouchak ◽  
Soroosh Sorooshian ◽  
Wayne Higgins
Keyword(s):  
United States ◽  
West Coast ◽  
El Niño ◽  
El Nino ◽  
The United States ◽  
Prediction Skill ◽  
Precipitation Prediction ◽  
Skill Scores ◽  
Extended Range ◽  
To Receive

Abstract Precipitation variability significantly influences the heavily populated West Coast of the United States, raising the need for reliable predictions. We investigate the region’s short- to extended-range precipitation prediction skill using the hindcast database of the Subseasonal-to-Seasonal Prediction Project (S2S). The prediction skill–lead time relationship is evaluated, using both deterministic and probabilistic skill scores. Results show that the S2S models display advantageous deterministic skill at week 1. For week 2, prediction is useful for the best-performing model, with a Pearson correlation coefficient larger than 0.6. Beyond week 2, predictions generally provide little useful deterministic skill. Sources of extended-range predictability are investigated, focusing on El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO). We found that periods of heavy precipitation associated with ENSO are more predictable at the extended range period. During El Niño years, Southern California tends to receive more precipitation in late winter, and most models show better extended-range prediction skill. On the contrary, during La Niña years Oregon tends to receive more precipitation in winter, with most models showing better extended-range skill. We believe the excessive precipitation and improved extended-range prediction skill are caused by the meridional shift of baroclinic systems as modulated by ENSO. Through examining precipitation anomalies conditioned on the MJO, we verified that active MJO events systematically modulate the area’s precipitation distribution. Our results show that most models do not represent the MJO or its associated teleconnections, especially at phases 3–4. However, some models exhibit enhanced extended-range prediction skills under active MJO conditions.

scholarly journals Linkage between Interannual Variation of the East Asian Intraseasonal Oscillation and Mei-Yu Onset

2018 ◽  
Vol 32 (1) ◽  
pp. 145-160 ◽  
Author(s):  
Yonghong Yao ◽  
Hai Lin ◽  
Qigang Wu
Keyword(s):  
Indian Ocean ◽  
South China Sea ◽  
South China ◽  
El Niño ◽  
El Nino ◽  
East Asian ◽  
Intraseasonal Oscillation ◽  
Eastern Indian Ocean ◽  
Ep El Niño ◽  
Sst Anomalies

AbstractThe mei-yu onset over the middle to lower reaches of the Yangtze River Valley (MLYRV) varies considerably from early June to mid-July, which leads to large interannual changes in rainy-season length, total summer rainfall, and flooding potential. Previous studies have investigated the impact of El Niño–Southern Oscillation (ENSO) on the mei-yu onset. This study shows that a strong (weak) East Asian and western North Pacific (EAWNP) intraseasonal oscillation (ISO) in spring leads to an early (late) onset of the mei-yu over the MLYRV, and this ISO–mei-yu relationship is attributed to different types of ENSO in the preceding winter. A strong EAWNP ISO in spring is related to an eastern Pacific El Niño (EP El Niño) in the previous winter, and negative sea surface temperature (SST) anomalies in the eastern Indian Ocean and the South China Sea (SCS) in May, which can cause an early onset of the South China Sea summer monsoon that also favors an early mei-yu onset. In contrast, a weak EAWNP ISO in spring is associated with a central Pacific El Niño (CP El Niño) before April, but with an EP El Niño after April, and positive SST anomalies in both the eastern Indian Ocean and the SCS in May. A statistical forecast model combining the intensity of spring EAWNP ISO, CP ENSO, and EP ENSO indices shows a high prediction skill of the observed mei-yu onset date.

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