scholarly journals Assessment of the Sea Surface Temperature Predictability Based on Multimodel Hindcasts

2019 ◽  
Vol 34 (6) ◽  
pp. 1965-1977 ◽  
Author(s):  
Shouwen Zhang ◽  
Hua Jiang ◽  
Hui Wang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Forecast Accuracy ◽  
Skill Score ◽  
Point Of View ◽  
Sea Surface ◽  
Lead Times ◽  
Spring Predictability Barrier ◽  
Multimodel Ensembles ◽  
The Tropics

Abstract Based on historical forecasts of four individual forecasting systems, we conducted multimodel ensembles (MME) to predict the sea surface temperature anomaly (SSTA) variability and assessed these methods from a deterministic and probabilistic point of view. To investigate the advantages and drawbacks of different deterministic MME methods, we used simple averaged MME with equal weighs (SCM) and the stepwise pattern projection method (SPPM). We measured the probabilistic forecast accuracy by Brier skill score (BSS) combined with its two components: reliability (Brel) and resolution (Bres). The results indicated that SCM showed a high predictability in the tropical Pacific Ocean, with a correlation exceeding 0.8 with a 6-month lead time. In general, the SCM outperformed the SPPM in the tropics, while the SPPM tend to show some positive effect on the correction when at long lead times. Corrections occurred for the spring predictability barrier of ENSO, in particular for improvements when the correlation was low or the RMSE was large using the SCM method. These qualitative results are not susceptible to the selection of the hindcast periods, it is as a rule rather by chance of these individual systems. Performance of our probabilistic MME was better than the Climate Forecast System version2 (CFSv2) forecasts in forecasting COLD, NEUTRAL, and WARM SSTA categories for most regions, mainly due to the contribution of Brel, indicating more adequate ensemble construction strategies of the MME system superior to the CFSv2.

scholarly journals BCC-CSM2-HR: A High-Resolution Version of the Beijing Climate Center Climate System Model

2020 ◽  
Author(s):  
Tongwen Wu ◽  
Rucong Yu ◽  
Yixiong Lu ◽  
Weihua Jie ◽  
Yongjie Fang ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate System ◽  
Sea Surface ◽  
System Model ◽  
Quasi Biennial Oscillation ◽  
Climate System Model ◽  
Medium Resolution ◽  
The Tropics

Abstract. BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model. Its development is on the basis of the medium-resolution version BCC-CSM2-MR which is the baseline for BCC participation to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamic core and physical processes. BCC-CSM2-HR is evaluated for present-day climate simulations from 1971 to 2000, which are performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. We focus on basic atmospheric mean states over the globe and variabilities in the tropics including the tropic cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR keeps well the global energy balance and can realistically reproduce main patterns of atmosphere temperature and wind, precipitation, land surface air temperature and sea surface temperature. It also improves in the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, is almost disappeared in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observation than their counterparts in BCC-CSM2-MR. We also note some weakness in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold Sea Surface Temperature (SST) biases and the insufficient number of tropical cyclones in the North Atlantic.

scholarly journals Tropical and Extratropical predictions of the summer and autumn Niño3.4 Index: a comparison

2016 ◽  
Vol 42 ◽  
pp. 73-81
Author(s):  
Miguel Tasambay-Salazar ◽  
María José OrtizBeviá ◽  
Antonio RuizdeElvira ◽  
Francisco José Alvarez-García
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Linear Models ◽  
Southern Oscillation ◽  
Heat Content ◽  
Sea Surface ◽  
South Pacific Convergence Zone ◽  
Lead Times ◽  
Convergence Zone ◽  
The World

Abstract. The El Niño-Southern Oscillation (ENSO) phenomenon is the main source of the predictability skill in many regions of the world for seasonal and interannual timescales. Longer lead predictability experiments of Niño3.4 Index using simple statistical linear models have shown an important skill loss at longer lead times when the targeted season is summer or autumn. We develop different versions of the model substituting some its variables with others that contain tropical or extratropical information, produce a number of hindcasts with these models using two different predictions schemes and cross validate them. We have identified different sets of tropical or extratropical predictors, which can provide useful values of potential skill. We try to find out the sources of the predictability by comparing the sea surface temperature (SST) and heat content (HC) anomalous fields produced by the successful predictors for the 1980–2012 period. We observe that where tropical predictors are used the prediction reproduces only the equatorial characteristics of the warming (cooling). However, where extratropical predictors are included, the predictions are able to simulate the absorbed warming in the South Pacific Convergence Zone (SPCZ).

scholarly journals Statistical Downscaling Forecasts for Winter Monsoon Precipitation in Malaysia Using Multimodel Output Variables

2010 ◽  
Vol 23 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Liew Juneng ◽  
Fredolin T. Tangang ◽  
Hongwen Kang ◽  
Woo-Jin Lee ◽  
Yap Kok Seng
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Winter Season ◽  
Peninsular Malaysia ◽  
Sea Surface ◽  
Asia Pacific ◽  
Forecast Data ◽  
Multimodel Ensembles

Abstract This paper compares the skills of four different forecasting approaches in predicting the 1-month lead time of the Malaysian winter season precipitation. Two of the approaches are based on statistical downscaling techniques of multimodel ensembles (MME). The third one is the ensemble of raw GCM forecast without any downscaling, whereas the fourth approach, which provides a baseline comparison, is a purely statistical forecast based solely on the preceding sea surface temperature anomaly. The first multimodel statistical downscaling method was developed by the Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) team, whereas the second is based on the canonical correlation analysis (CCA) technique using the same predictor variables. For the multimodel downscaling ensemble, eight variables from seven operational GCMs are used as predictors with the hindcast forecast data spanning a period of 21 yr from 1983/84 to 2003/04. The raw GCM forecast ensemble tends to have higher skills than the baseline skills of the purely statistical forecast that relates the dominant modes of observed sea surface temperature variability to precipitation. However, the downscaled MME forecasts have higher skills than the raw GCM products. In particular, the model developed by APCC showed significant improvement over the peninsular Malaysia region. This is attributed to the model’s ability to capture regional and large-scale predictor signatures from which the additional skills originated. Overall, the results showed that the appropriate downscaling technique and ensemble of various GCM forecasts could result in some skill enhancement, particularly over peninsular Malaysia, where other models tend to have lower or no skills.

scholarly journals A Simple Analytical Model for Understanding the Formation of Sea Surface Temperature Patterns under Global Warming*

2014 ◽  
Vol 27 (22) ◽  
pp. 8413-8421 ◽  
Author(s):  
Lei Zhang ◽  
Tim Li
Keyword(s):  
Global Warming ◽  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Tropical Pacific ◽  
Sea Surface ◽  
The Tropics ◽  
The Tropical Pacific

Abstract How sea surface temperature (SST) changes under global warming is critical for future climate projection because SST change affects atmospheric circulation and rainfall. Robust features derived from 17 models of phase 5 of the Coupled Model Intercomparison Project (CMIP5) include a much greater warming in high latitudes than in the tropics, an El Niño–like warming over the tropical Pacific and Atlantic, and a dipole pattern in the Indian Ocean. However, the physical mechanism responsible for formation of such warming patterns remains open. A simple theoretical model is constructed to reveal the cause of the future warming patterns. The result shows that a much greater polar, rather than tropical, warming depends primarily on present-day mean SST and surface latent heat flux fields, and atmospheric longwave radiation feedback associated with cloud change further enhances this warming contrast. In the tropics, an El Niño–like warming over the Pacific and Atlantic arises from a similar process, while cloud feedback resulting from different cloud regimes between east and west ocean basins also plays a role. A dipole warming over the equatorial Indian Ocean is a response to weakened Walker circulation in the tropical Pacific.

scholarly journals An Analytical Framework for Understanding Tropical Meridional Modes

2017 ◽  
Vol 30 (9) ◽  
pp. 3303-3323 ◽  
Author(s):  
Cristian Martinez-Villalobos ◽  
Daniel J. Vimont
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Ocean Model ◽  
Sea Surface ◽  
Transient Growth ◽  
Kelvin Wave ◽  
Wes Feedback ◽  
Meridional Mode ◽  
The Tropics

A theoretical framework is developed for understanding the transient growth and propagation characteristics of thermodynamically coupled, meridional mode–like structures in the tropics. The model consists of a Gill–Matsuno-type steady atmosphere under the long-wave approximation coupled via a wind–evaporation–sea surface temperature (WES) feedback to a “slab” ocean model. When projected onto meridional basis functions for the atmosphere the system simplifies to a nonnormal set of equations that describes the evolution of individual sea surface temperature (SST) modes, with clean separation between equatorially symmetric and antisymmetric modes. The following major findings result from analysis of the system: 1) a transient growth process exists whereby specific SST modes propagate toward lower-order modes at the expense of the higher-order modes; 2) the same dynamical mechanisms govern the evolution of symmetric and antisymmetric SST modes except for the lowest-order wavenumber, where for symmetric structures the atmospheric Kelvin wave plays a critically different role in enhancing decay; and 3) the WES feedback is positive for all modes (with a maximum for the most equatorially confined antisymmetric structure) except for the most equatorially confined symmetric mode where the Kelvin wave generates a negative WES feedback. Taken together, these findings explain why equatorially antisymmetric “dipole”-like structures may dominate thermodynamically coupled ocean–atmosphere variability in the tropics. The role of nonnormality and the role of realistic mean states in meridional mode variability are discussed.

Local Atmosphere–Ocean Predictability: Dynamical Origins, Lead Times, and Seasonality

2019 ◽  
Vol 32 (21) ◽  
pp. 7507-7519 ◽  
Author(s):  
Eviatar Bach ◽  
Safa Motesharrei ◽  
Eugenia Kalnay ◽  
Alfredo Ruiz-Barradas
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Phase Relationship ◽  
Sea Surface ◽  
Low Frequencies ◽  
Model Studies ◽  
Almost Everywhere ◽  
Summer Hemisphere ◽  
Coupled Data Assimilation ◽  
The Tropics

Abstract Due to the physical coupling between atmosphere and ocean, information about the ocean helps to better predict the future of the atmosphere, and in turn, information about the atmosphere helps to better predict the ocean. Here, we investigate the spatial and temporal nature of this predictability: where, for how long, and at what frequencies does the ocean significantly improve prediction of the atmosphere, and vice versa? We apply Granger causality, a statistical test to measure whether a variable improves prediction of another, to local time series of sea surface temperature (SST) and low-level atmospheric variables. We calculate the detailed spatial structure of the atmosphere-to-ocean and ocean-to-atmosphere predictability. We find that the atmosphere improves prediction of the ocean most in the extratropics, especially in regions of large SST gradients. This atmosphere-to-ocean predictability is weaker but longer-lived in the tropics, where it can last for several months in some regions. On the other hand, the ocean improves prediction of the atmosphere most significantly in the tropics, where this predictability lasts for months to over a year. However, we find a robust signature of the ocean on the atmosphere almost everywhere in the extratropics, an influence that has been difficult to demonstrate with model studies. We find that both the atmosphere-to-ocean and ocean-to-atmosphere predictability are maximal at low frequencies, and both are larger in the summer hemisphere. The patterns we observe generally agree with dynamical understanding and the results of the Kalnay dynamical rule, which diagnoses the direction of forcing between the atmosphere and ocean by considering the local phase relationship between simultaneous sea surface temperature and vorticity anomaly signals. We discuss applications to coupled data assimilation.

scholarly journals Global Warming Pattern Formation: Sea Surface Temperature and Rainfall*

2010 ◽  
Vol 23 (4) ◽  
pp. 966-986 ◽  
Author(s):  
Shang-Ping Xie ◽  
Clara Deser ◽  
Gabriel A. Vecchi ◽  
Jian Ma ◽  
Haiyan Teng ◽  
...  
Keyword(s):  
Global Warming ◽  
Pattern Formation ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Trade Wind ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Equatorial Wave ◽  
Sst Warming ◽  
The Tropics

Abstract Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the twenty-first century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean–atmosphere general circulation models of the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical-mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies whereas the latter is linked to intensified southeast trade winds, suggestive of wind–evaporation–SST feedback. There is a tendency for a greater warming in the northern subtropics than in the southern subtropics in accordance with asymmetries in trade wind changes. Over the equatorial Indian Ocean, surface wind anomalies are easterly, the thermocline shoals, and the warming is reduced in the east, indicative of Bjerknes feedback. In the midlatitudes, ocean circulation changes generate narrow banded structures in SST warming. The warming is negatively correlated with wind speed change over the tropics and positively correlated with ocean heat transport change in the northern extratropics. A diagnostic method based on the ocean mixed layer heat budget is developed to investigate mechanisms for SST pattern formation. Tropical precipitation changes are positively correlated with spatial deviations of SST warming from the tropical mean. In particular, the equatorial maximum in SST warming over the Pacific anchors a band of pronounced rainfall increase. The gross moist instability follows closely relative SST change as equatorial wave adjustments flatten upper-tropospheric warming. The comparison with atmospheric simulations in response to a spatially uniform SST warming illustrates the importance of SST patterns for rainfall change, an effect overlooked in current discussion of precipitation response to global warming. Implications for the global and regional response of tropical cyclones are discussed.

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