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.

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.

Fast and Slow Responses to Global Warming: Sea Surface Temperature and Precipitation Patterns

2014 ◽  
Vol 27 (1) ◽  
pp. 285-299 ◽  
Author(s):  
Shang-Min Long ◽  
Shang-Ping Xie ◽  
Xiao-Tong Zheng ◽  
Qinyu Liu
Keyword(s):  
Global Warming ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Radiative Forcing ◽  
Diagnostic Method ◽  
Slow Component ◽  
Sea Surface ◽  
Annual Rainfall ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Quasi Equilibrium

Abstract The time-dependent response of sea surface temperature (SST) to global warming and the associated atmospheric changes are investigated based on a 1% yr−1 CO2 increase to the quadrupling experiment of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1. The SST response consists of a fast component, for which the ocean mixed layer is in quasi equilibrium with the radiative forcing, and a slow component owing to the gradual warming of the deeper ocean in and beneath the thermocline. A diagnostic method is proposed to isolate spatial patterns of the fast and slow responses. The deep ocean warming retards the surface warming in the fast response but turns into a forcing for the slow response. As a result, the fast and slow responses are nearly opposite to each other in spatial pattern, especially over the subpolar North Atlantic/Southern Ocean regions of the deep-water/bottom-water formation, and in the interhemispheric SST gradient between the southern and northern subtropics. Wind–evaporation–SST feedback is an additional mechanism for the SST pattern formation in the tropics. Analyses of phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble of global warming simulations confirm the validity of the diagnostic method that separates the fast and slow responses. Tropical annual rainfall change follows the SST warming pattern in both the fast and slow responses in CMIP5, increasing where the SST increase exceeds the tropical mean warming.

scholarly journals Sea Surface Temperature Warming Patterns and Future Vegetation Change

2015 ◽  
Vol 28 (20) ◽  
pp. 7943-7961 ◽  
Author(s):  
Sara A. Rauscher ◽  
Xiaoyan Jiang ◽  
Allison Steiner ◽  
A. Park Williams ◽  
D. Michael Cai ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Vegetation Change ◽  
Tree Mortality ◽  
Ensemble Member ◽  
Sea Surface ◽  
Community Land Model ◽  
Sst Warming ◽  
The Tropics

Abstract Recent modeling studies of future vegetation change suggest the potential for large-scale forest die-off in the tropics. Taken together with observational evidence of increasing tree mortality in numerous ecosystem types, there is clearly a need for projections of vegetation change. To that end, the authors have performed an ensemble of climate–vegetation experiments with the National Science Foundation–DOE Community Atmosphere Model (CAM) coupled to the Community Land Model (CAM–CLM-CN) with its dynamic vegetation model enabled (CAM–CLM-CNDV). To overcome the limitations of using a single model, the authors employ the sea surface temperature (SST) warming patterns simulated by eight different models from the Coupled Model Intercomparison Program phase 3 (CMIP3) as boundary conditions. Since the SST warming pattern in part dictates how precipitation may change in the future, in this way a range of future vegetation–climate trajectories can be produced. On an annual average basis, this study’s CAM–CLM-CN simulations do not produce as large a spread in projected precipitation as the original CMIP3 archive. These differences are due to the tendency of CAM–CLM-CN to increase tropical precipitation under a global warming scenario, although this response is modulated by the SST warming patterns imposed. However, the CAM–CLM-CN simulations reproduce the enhanced dry season in the tropics simulated by CMIP3. These simulations show longer fire seasons and increases in fractional area burned. In one ensemble member, extreme droughts over tropical South America lead to fires that remove vegetation cover in the eastern Amazon, suggesting that large-scale die-offs are an unlikely but still possible event.

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.

Intelligent analysis of global warming effects on sea surface temperature in Hormuzgan Coast, Persian Gulf

2016 ◽  
Vol 9 (4) ◽  
pp. 452 ◽  
Author(s):  
Saeed Samadianfard ◽  
Reza Delirhasannia ◽  
Masoud Torabi Azad ◽  
Sima Samadianfard ◽  
Mehrdad Jeihouni
Keyword(s):  
Global Warming ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Persian Gulf ◽  
Sea Surface ◽  
Intelligent Analysis

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.

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