The Boreal Summer Intraseasonal Oscillation Simulated in the NCEP Climate Forecast System: The Effect of Sea Surface Temperature
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Abstract Observational evidence has indicated the important role of the interaction of the atmosphere with the sea surface in the development and maintenance of the tropical intraseasonal oscillation (ISO). However, improvements in ISO simulations with fully coupled atmosphere–ocean general circulation models are limited and model dependent. This study further examines the effect of air–sea coupling and the basic-state sea surface temperature (SST) associated with the boreal summer intraseasonal oscillation (BSISO) in a 21-yr free run with the recently developed NCEP coupled Climate Forecast System (CFS) model. For this, the CFS run is compared with an Atmospheric Model Intercomparison Project–type long-term simulation forced by prescribed SST in the NCEP Global Forecast System (GFS) model and flux-corrected version of CFS (referred to as CFSA). The GFS run simulates significantly unorganized BSISO convection anomalies, which exhibit an erroneous standing oscillation. The CFS run with interactive air–sea coupling has limited improvements, including the generation of intraseasonal SST variation preceding the convection anomaly by ∼10 days. However, this simulation still does not show the observed continuous northward propagation over the Indian Ocean due to a cold model bias. The CFSA run removes the cold bias in the Indian Ocean and the simulation of the development and propagation of BSISO anomalies are significantly improved. Enhanced and suppressed convection anomalies exhibit the observed quadrupole-like configuration, and phase relationships between precipitation and surface dynamic and thermodynamic variables for the northward propagation are shown to be coherent and consistent with the observations. It is shown that the surface meridional moisture convergence is an important factor for the northward propagation of the BSISO. On the other hand, both the GFS and CFS runs do not realistically simulate an eastward-propagating equatorial mode. The CFSA run produces a more realistic eastward-propagation mode only over the Indian Ocean and Java Sea due to the improved mean state in SST, low-level winds, and vertical wind shear. Reasons for the failure of farther eastward propagation into the west Pacific in CFSA are discussed. This study reconfirms the significance of air–sea interactions. More importantly, however, the results suggest that in order for the influence of the coupled air–sea interaction to be properly communicated, the mean state SST in the coupled model should be reasonably simulated. This is because the basic-state SST itself acts to sustain BSISO convection and it makes the large-scale dynamical environment (i.e., easterly vertical wind shear or low-level westerly zonal wind) more favorable for the propagation of the moist Rossby–Kelvin wave packet.Keywords:
Madden–Julian oscillation
Anomaly (physics)
Oscillation (cell signaling)
Predictability
Abstract The multi‐year predictability of global sea surface temperature (SST) is examined by applying a model‐analog method to four control simulations to make forecasts at leads of 1–36 months over 1961–2015. The forecasts are found to have skill for annual mean SST at Year 2 (i.e., leads of 13–24 months) or even Year 3 (i.e., leads of 25–36 months) in the tropical Pacific, the North and South Pacific, the southwest Indian Ocean, and the northwestern tropical Atlantic. The seasonality in forecast skill suggests that July is the best time to initialize multi‐year forecasts. The evolution of forecast skill for tropical Pacific SSTs indicates that the predictability of some El Niño Southern Oscillation events is nearly the same at leads of 6 and 18 or 24 months. Further, these El Niño and La Niña events can be predicted at leads of up to 24 and 30 months, respectively.
Predictability
Madden–Julian oscillation
Seasonality
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Anomaly (physics)
Tropical Atlantic
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Based on reanalysis data from 1979 to 2016, this study focuses on the sea surface temperature (SST) anomaly of the tropical North Atlantic (TNA) in El Niño decaying years. The TNA SST exhibits a clear warm trend during this period. The composite result for 10 El Niño events shows that the TNA SST anomaly reaches its maximum in spring after the peak of an El Niño event and persists until summer. In general, the anomaly is associated with three factors—namely, El Niño, the North Atlantic Oscillation (NAO), and a long-term trend, leading to an increase in local SST up to 0.4°C, 0.3°C, and 0.35°C, respectively. A comparison between 1983 and 2005 indicates that the TNA SST in spring is affected by El Niño, as well as the local SST in the preceding winter, which may involve a long-term trend signal. In addition, the lead–lag correlation shows that the NAO leads the TNA SST by 2–3 months. By comparing two years with an opposite phase of the NAO in winter (i.e., 1992 and 2010), the authors further demonstrate that the NAO is another important factor in regulating the TNA SST anomaly. A negative phase of the NAO in winter will reinforce the El Niño forcing substantially, and vise versa. In other words, the TNA SST anomaly in the decaying years is more evident if the NAO is negative with El Niño. Therefore, the combined effects of El Niño and the NAO must be considered in order to fully understand the TNA SST variability along with a long-term trend. 摘要 基于1979年到2016年多种再分析资料, 本文分析了El Niño衰减年热带北大西洋的海温异常. 结果表明, 热带北大西洋海温在此期间呈显著变暖趋势. 10次El Niño事件的合成结果表明热带北大西洋海温异常在El Niño事件峰值之后的春季达到最大值, 并持续到夏季. 一般而言, 这种异常与三个因子有关, 即El Niño, 北大西洋涛动和长期趋势, 能分别导致局地海温上升0.4°C, 0.3°C和0.35°C. 1983年和2005年的对比分析表明, 尽管El Niño强度对春季北大西洋海温起到决定性作用, 与长期趋势密切相关的前冬海温也很重要. 此外, 超前-滞后相关结果表明北大西洋涛动超前海温约2–3个月. 比较两个冬季相反位相北大西洋涛动的年份 (即1992年和2010年) , 表明北大西洋涛动也能调制北大西洋海温异常. 冬季负位相北大西洋涛动能显著增强El Niño的强迫影响, 反之亦然. 换言之, 如果北大西洋涛动与El Niño位相相合, 衰减年北大西洋海温异常才更为显著. 因此, 为全面理解热带北大西洋海温变化, 除长期趋势外, 还必须考虑El Niño和北大西洋涛动的综合影响.
Anomaly (physics)
Forcing (mathematics)
Tropical Atlantic
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This study investigates the evolution of the sea surface temperature (SST) over the cold tongue (CT) region in the central South China Sea (SCS) during various El Niño events. A significant and distinct double-peak warming evolution can occur during EP El Niño and CP El Niño events, with the former being more remarkable and robust than the latter. Further analyses show that the weak and insignificant CT SST anomaly in CP El Niño events is influenced by some CP El Niño events in which the warm sea surface temperature anomaly (SSTA) is located west of 175° E (WCP El Niño). The response of CT SSTA mainly depends on the warm SSTA location of CP El Niño. The different corresponding mechanisms in winter, spring and summer are discussed respectively in this work. Further analysis reveals that the weak and insignificant SST anomaly over the CT region in CP El Niño events is caused by the faint SSTA response during the WCP El Niño events. The results of this study call attention to the response of the SCS climate in both atmosphere and ocean to the diversity of ENSO, especially the CP El Niño.
Anomaly (physics)
Surface air temperature
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The tropical Pacific,the tropical Indian Ocean and the tropical Atlantic are the most prominent areas in terms of Ocean Atmosphere interaction on earth.To probe into some features about the local Ocean Atmosphere interaction,new satellite data for the Sea Surface Temperature(SST) anomaly and Cloud Liquid Water(CLW) have been analysed statistically by correlation analysis in the three tropical oceans in this paper.It is discovered that the synchronous correlation coefficients of SST anomaly and CLW anomaly are always positive within 5 weeks of lead or lag time,which means there is a positive feedback mechanism between SST anomaly and CLW anomaly in the equatorial Pacific and Atlantic;When the SST anomaly leads the CLW anomaly by one week,the positive correlation coefficient is maximum,which means that the SST variation could lead the CLW variation in the west tropical Indian Ocean;Contrary to this,the synchronous correlation coefficient is negative in cold sea surfaces,such as the extra-equatorial southeast and northeast Pacific and extra-equatorial south Atlantic,where the CLW variation could lead to the SST variation.In the tropical northwest pacific,which is in the east of the Philippines,the CLW variation could also lead to the SST variation;In the east equatorial Indian Ocean,the SST increase(decrease) could lead to CLW increase(decrease) in some periods,and CLW increase(decrease) could also conduce to SST decrease(increase) in other periods.Those results will be useful for understanding tropical ocean-atmosphere interaction and improving the parameterization scheme of ocean-atmosphere interaction.
Anomaly (physics)
Lead (geology)
Tropical Atlantic
Sea-surface height
Variation (astronomy)
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Four perpetual January integrations of an atmospheric general circulation model have been performed, in each of which a different sea surface temperature (SST) anomaly was specified in the North Pacific. The observed SST anomaly for the 1976/77 winter was chosen as the basic anomaly, and 1200-day runs were carded out in which this anomaly was multiplied by ±1 and ±2. A fifth run was performed which combined the basic midlatitude SST anomaly from 1976/77 with a tropical Pacific SST anomaly representative of the mature phase of a warm El Niño/Southern Oscillation (ENSO) episode. An ensemble of eight, independent 90-day averaged realizations was extracted from each simulation. Maps of ensemble-mean differences from the model climatology are presented in this paper, together with estimates of the statistical significance of some of the features which appear on these maps. The model response to the basic SST anomaly and to twice the basic SST anomaly is a midiatitude teleconnection pattern, the Pacific/North American (PNA) pattern, which has been found in previous experiments which used tropical Pacific SST anomalies. The amplitude of the model response increases at a slower than linear rate as the magnitude of the SST anomaly is increased. The model response to the basic midlatitude SST anomaly is compared with the model response to tropical Pacific SST anomalies. When the basic midlatitude anomaly is combined with a tropical Pacific SST anomaly, such as commonly occurs during the mature phase of warm ENSO episodes, we find that the model response to the combined SST anomalies is approximately equal to the sum of the model responses produced by the SST anomalies acting separately. The model response to the basic SST anomaly times –1 and times –2 is not a previously described teleconnection pattern. Over the North Pacific, the model response in the upper troposphere is weak, but below 700 mb. the response in heights and temperatures is the opposite of that produced for SST anomalies of the opposite sign. There is also a positive anomalous zonal wind over the southern United States and a negative height anomaly over the eastern United States.
Anomaly (physics)
Teleconnection
Middle latitudes
Forcing (mathematics)
Walker circulation
Atmospheric Circulation
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Sea surface temperature (SST) has important impacts on the global ecology, and having a good understanding of the predictability, i.e., the possibility of achieving accurate prediction, of SST can help us monitor the marine environment and climate change, and guide the selection and design of SST prediction methods. However, existing studies for analyzing SST mostly measure the rising or falling trends of SST. To address this issue, we introduce a temporal-correlated entropy to quantify the predictability of SST series from both global coarse-grained and local fine-grained aspects, and make SST prediction with multiple deep learning models to prove the effectiveness of such predictability evaluation method. In addition, we explore the dynamics of SST predictability by dividing the time range of interest into consecutive time periods, evaluating the corresponding predictability of SST for each time period, and analyzing the stability of the predictability of SST over time. According to the experiments, the SST predictability values near the poles and equator are really high. The average SST predictability values of the East China Sea, Bohai Sea, and Antarctic Ocean are 0.719, 0.706, and 0.886, respectively, and the size relationship of the SST predictability in the three local sea areas is consistent with our prediction results using multiple representative SST prediction methods, which corroborates the reliability of the predictability evaluation method. In addition, we found that the SST predictability in the Antarctic Ocean changes more dramatically over time than in the East China Sea and the Bohai Sea. The results of SST predictability and its dynamic analysis indicate that global warming, ocean currents, and human activities all have significant impacts on the predictability of SST.
Predictability
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Abstract The Madden–Julian Oscillation (MJO) is characterized by slowly eastward‐propagating precipitation and circulation anomalies with time scales of about 30–80 days. Both the phase and amplitude of the MJO fluctuate with time as it propagates eastward. Despite recent progress in understanding the predictability limit of the MJO as a whole, little is known of the difference in the predictability limits of its amplitude and phase. This paper investigates these differences using the nonlinear local Lyapunov exponent approach, which provides an estimate of atmospheric predictability based on observational data. The predictability limit of the phase of the MJO is determined as ~32 days, which is higher than that of its amplitude (about 16 days). In state‐of‐the‐art operational forecast models, the phase of the MJO is also found to have a much better forecast skill than does its amplitude. The relatively low limit of the predictability of the amplitude will pose a challenge to MJO prediction.
Madden–Julian oscillation
Predictability
Oscillation (cell signaling)
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Abstract This study revisits MJO predictability based on the “perfect model” approach with a contemporary model. Experiments are performed to address the reasons for substantial uncertainties in current estimates of MJO predictability, with a focus on the influence of atmospheric convection parameterization. Specifically, two atmospheric convection schemes are applied for experiments with the NOAA Climate Forecast System, version 2 (CFSv2). MJO potential predictability and prediction skill are assessed, with MJO indices taken as the first two principal components of the combined fields of near-equatorially averaged 200-hPa zonal wind, 850-hPa zonal wind, and outgoing longwave radiation at the top of the atmosphere. Analyses indicate that the convection scheme alone can have substantial influence on the estimate of MJO predictability, with estimates differing by as much as 15 days. Further diagnostics suggest that the shorter predictability with one convection scheme is mainly caused by too weak of an MJO signal. The choice of atmospheric convection scheme also exerts effects on the phase dependency of MJO predictability, and the “Maritime Continent prediction barrier” is identified to be more evident with one convection scheme than with the other.
Predictability
Madden–Julian oscillation
Outgoing longwave radiation
Atmospheric models
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