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Change of Tropical Cyclone Heat Potential in Response to Global Warming

doi: 10.1007/s00376-015-5112-9

  • Tropical cyclone heat potential (TCHP) in the ocean can affect tropical cyclone intensity and intensification. In this paper, TCHP change under global warming is presented based on 35 models from CMIP5 (Coupled Model Intercomparison Project, Phase 5). As the upper ocean warms up, the TCHP of the global ocean is projected to increase by 140.6% in the 21st century under the RCP4.5 (+4.5 W m-2 Representative Concentration Pathway) scenario. The increase is particularly significant in the western Pacific, northwestern Indian and western tropical Atlantic oceans. The increase of TCHP results from the ocean temperature warming above the depth of the 26°C isotherm (D26), the deepening of D26, and the horizontal area expansion of SST above 26°C. Their contributions are 69.4%, 22.5% and 8.1%, respectively. Further, a suite of numerical experiments with an Ocean General Circulation Model (OGCM) is conducted to investigate the relative importance of wind stress and buoyancy forcing to the TCHP change under global warming. Results show that sea surface warming is the dominant forcing for the TCHP change, while wind stress and sea surface salinity change are secondary.
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    Ishii M., M. Kimoto, 2009: Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections. Journal Oceanography, 65, 287- 299.10.1007/ reported in former studies, temperature observations obtained by expendable bathythermographs (XBTs) and mechanical bathythermographs (MBTs) appear to have positive biases as much as they affect major climate signals. These biases have not been fully taken into account in previous ocean temperature analyses, which have been widely used to detect global warming signals in the oceans. This report proposes a methodology for directly eliminating the biases from the XBT and MBT observations. In the case of XBT observation, assuming that the positive temperature biases mainly originate from greater depths given by conventional XBT fall-rate equations than the truth, a depth bias equation is constructed by fitting depth differences between XBT data and more accurate oceanographic observations to a linear equation of elapsed time. Such depth bias equations are introduced separately for each year and for each probe type. Uncertainty in the gradient of the linear equation is evaluated using a non-parametric test. The typical depth bias is +10 m at 700 m depth on average, which is probably caused by various indeterminable sources of error in the XBT observations as well as a lack of representativeness in the fall-rate equations adopted so far. Depth biases in MBT are fitted to quadratic equations of depth in a similar manner to the XBT method. Correcting the historical XBT and MBT depth biases by these equations allows a historical ocean temperature analysis to be conducted. In comparison with the previous temperature analysis, large differences are found in the present analysis as follows: the duration of large ocean heat content in the 1970s shortens dramatically, and recent ocean cooling becomes insignificant. The result is also in better agreement with tide gauge observations.
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    Leipper D. F., L. D. Volgenau, 1972: Hurricane heat potential of the Gulf of Mexico. J. Phys. Oceanogr., 2, 218- 224.10.1175/1520-0485(1972)0022.0.CO; It has been demonstrated that a large input of energy from the ocean is necessary to establish and maintain hurricane force winds over the sea. However, there has been no suitable data which could serve as a basis for calculating this input. Now, observations are available to show that, early in the hurricane season, there are varying initial conditions in the Gulf of Mexico which could lead to significantly different total heat exchanges. The sea can provide some seven days of energy flow into a hurricane at some times and at some locations, but less than one day in others depending upon the amount of heat initially available in the Gulf waters. In the four summers represented by the data, a quantity defined as hurricane heat potential was found to vary from a low of 700 cal cm 2 column north of Yucatan to a high of 31,600 in the central east Gulf. Synoptic data on hurricane heat potential, if made regularly available to forecasters, might serve as a basis for improved forecasts of changes in Intensity and movement of hurricanes.
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    Lin I. -I., C. -C. Wu, I. -F. Pun, and D. -S. Ko, 2008: Upper-ocean thermal structure and the western North Pacific category 5 typhoons. Part I: Ocean features and the category 5 typhoons閳ワ拷 intensification. Mon. Wea. Rev.,136, 3288-3306, doi: 10.1175/2008MWR2277.1.10.1175/ Category 5 cyclones are the most intense and devastating cyclones on earth. With increasing observations of category 5 cyclones, such as Hurricane Katrina (2005), Rita (2005), Mitch (1998), and Supertyphoon Maemi (2003) found to intensify on warm ocean features (i.e., regions of positive sea surface height anomalies detected by satellite altimeters), there is great interest in investigating the role ocean features play in the intensification of category 5 cyclones. Based on 13 yr of satellite altimetry data, in situ and climatological upper-ocean thermal structure data, best-track typhoon data of the U.S. Joint Typhoon Warning Center, together with an ocean mixed layer model, 30 western North Pacific category 5 typhoons that occurred during the typhoon season from 1993 to 2005 are systematically examined in this study. Two different types of situations are found. The first type is the situation found in the western North Pacific south eddy zone (SEZ; 21°–26°N, 127°–170°E) and the Kuroshio (21°–30°N, 127°–170°E) region. In these regions, the background climatological warm layer is relatively shallow (typically the depth of the 26°C isotherm is around 60 m and the upper-ocean heat content is 6550 kJ cm 612 ). Therefore passing over positive features is critical to meet the ocean’s part of necessary conditions in intensification because the features can effectively deepen the warm layer (depth of the 26°C isotherm reaching 100 m and upper-ocean heat content is 65110 kJ cm 612 ) to restrain the typhoon’s self-induced ocean cooling. In the past 13 yr, 8 out of the 30 category 5 typhoons (i.e., 27%) belong to this situation. The second type is the situation found in the gyre central region (10°–21°N, 121°–170°E) where the background climatological warm layer is deep (typically the depth of the 26°C isotherm is 65105–120 m and the upper-ocean heat content is 6580–120 kJ cm 612 ). In this deep, warm background, passing over positive features is not critical since the background itself is already sufficient to restrain the self-induced cooling negative feedback during intensification.
    Locarnini, R. A., Coauthors , 2013: World Ocean Atlas 2013,Vol. 1: Temperature. S. Levitus, Ed., A. Mishonov Technical Ed. NOAA Atlas NESDIS 73, 40 This atlas consists of a description of data analysis procedures and horizontal maps of climatological distribution fields of temperature at selected standard depth levels of the World Ocean on one-degree and quarter-degree latitude-longitude grids. The aim of the maps is to illustrate large-scale characteristics of the distribution of ocean temperature. The fields used to generate these climatological maps were computed by objective analysis of all scientifically quality-controlled historical temperature data in the World Ocean Database 2013. Maps are presented for climatological composite periods (annual, seasonal, monthly, seasonal and monthly difference fields from the annual mean field, and the number of observations) at 102 standard depths.
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    Mei W., F. Primeau, J. C. McWillams, and C. Pasquero, 2013: Sea surface height evidence for long-term warming effects of tropical cyclones on the ocean. Proceedings of the National Academy of Sciences of the United States of America, 110( 38), 15 207- 15 210.10.1073/ cyclones have been hypothesized to influence climate by pumping heat into the ocean, but a direct measure of this warming effect is still lacking. We quantified cyclone-induced ocean warming by directly monitoring the thermal expansion of water in the wake of cyclones, using satellite-based sea surface height data that provide a unique way of tracking the changes in ocean heat content on seasonal and longer timescales. We find that the long-term effect of cyclones is to warm the ocean at a rate of 0.32 卤 0.15 PW between 1993 and 2009, i.e., 23 times more efficiently per unit area than the background equatorial warming, making cyclones potentially important modulators of the climate by affecting heat transport in the ocean-atmosphere system. Furthermore, our analysis reveals that the rate of warming increases with cyclone intensity. This, together with a predicted shift in the distribution of cyclones toward higher intensities as climate warms, suggests the ocean will get even warmer, possibly leading to a positive feedback.
    Mei W., S. P. Xie, F. Primeau, J. C. McWilliams, and C. Pasquero, 2015: Northwestern Pacific typhoon intensity controlled by changes in ocean temperatures. Science Advances, 1, e1500014.10.1126/ warming is a predicting factor for typhoon intensity. Dominant climatic factors controlling the lifetime peak intensity of typhoons are determined from six decades of Pacific typhoon data. We find that upper ocean temperatures in the low-latitude northwestern Pacific (LLNWP) and sea surface temperatures in the central equatorial Pacific control the seasonal average lifetime peak intensity by setting the rate and duration of typhoon intensification, respectively. An anomalously strong LLNWP upper ocean warming has favored increased intensification rates and led to unprecedentedly high average typhoon intensity during the recent global warming hiatus period, despite a reduction in intensification duration tied to the central equatorial Pacific surface cooling. Continued LLNWP upper ocean warming as predicted under a moderate [that is, Representative Concentration Pathway (RCP) 4.5] climate change scenario is expected to further increase the average typhoon intensity by an additional 14% by 2100.
    Palmer M. D., K. Haines, S. F. B. Tett, and T. J. Ansell, 2007: Isolating the signal of ocean global warming. Geophys. Res. Lett., 34, L23610.10.1029/ the signature of global warming in the world's oceans is challenging because low frequency circulation changes can dominate local temperature changes. The IPCC fourth assessment reported an average ocean heating rate of 0.21 卤 0.04 Wm-2 over the period 1961-2003, with considerable spatial, interannual and inter-decadal variability. We present a new analysis of millions of ocean temperature profiles designed to filter out local dynamical changes to give a more consistent view of the underlying warming. Time series of temperature anomaly for all waters warmer than 14掳C show large reductions in interannual to inter-decadal variability and a more spatially uniform. upper ocean warming trend (0.12 Wm-2 on average) than previous results. This new measure of ocean warming is also more robust to some sources of error in the ocean observing system. Our new analysis provides a useful addition for evaluation of coupled climate models, to the traditional fixed depth analyses. Copyright 2007 by the American Geophysical Union.
    Pun I. -F., I. -I. Lin, and M. -H. Lo, 2013: Recent increase in high tropical cyclone heat potential area in the Western North Pacific Ocean. Geophys. Res. Lett.,40, 4680-4884, doi: 10.1002/grl.50548.10.1002/[1] The Main Development Region (MDR) for tropical cyclones (TCs) in the western North Pacific Ocean is the most active TC region in the world. Based on synergetic analyses of satellite altimetry and gravity observations, we found that the subsurface ocean conditions in the western North Pacific MDR has become even more favorable for the intensification of typhoons and supertyphoons. Compared to the early 1990s, a 10% increase in both the depth of the 26°C isotherm (D26) and Tropical Cyclone Heat Potential (TCHP) has occurred in the MDR. In addition, the areas of high TCHP (≥ 110 kJ cm 612 ) and large D26 (≥ 110 m) have 13% and 17% increases, respectively. Because these high TCHP and large D26 regions are often associated with intensification of the most intense TCs (i.e. supertyphoons), this recent warming requires close attention and monitoring.
    Shay L. K., G. J. Goni, and P. G. Black, 2000: Effects of a warm oceanic feature on hurricane Opal. Mon. Wea. Rev., 128, 1366- 1383.10.1175/1520-0493(2000)128<1366:EOAWOF>2.0.CO; On 4 October 1995, Hurricane Opal deepened from 965 to 916 hPa in the Gulf of Mexico over a 14-h period upon encountering a warm core ring (WCR) in the ocean shed by the Loop Current during an upper-level atmospheric trough interaction. Based on historical hydrographic measurements placed within the context of a two-layer model and surface height anomalies (SHA) from the radar altimeter on the TOPEX mission, upper-layer thickness fields indicated the presence of two warm core rings during September and October 1995. As Hurricane Opal passed directly over one of these WCRs, the 1-min surface winds increased from 35 to more than 60 m s 611 , and the radius of maximum wind decreased from 40 to 25 km. Pre-Opal SHAs in the WCR exceeded 30 cm where the estimated depth of the 20°C isotherm was located between 175 and 200 m. Subsequent to Opal’s passage, this depth decreased approximately 50 m, which suggests upwelling underneath the storm track due to Ekman divergence. The maximum heat loss of approximately 24 Kcal cm 612 relative to depth of the 26°C isotherm was a factor of 6 times the threshold value required to sustain a hurricane. Since most of this loss occurred over a period of 14 h, the heat content loss of 24 Kcal cm 612 equates to approximately 20 kW m 612 . Previous observational findings suggest that about 10%–15% of upper-ocean cooling is due to surface heat fluxes. Estimated surface heat fluxes based upon heat content changes range from 2000 to 3000 W m 612 in accord with numerically simulated surface heat fluxes during Opal’s encounter with the WCR. Composited AVHRR-derived SSTs indicated a 2°–3°C cooling associated with vertical mixing in the along-track direction of Opal except over the WCR where AVHRR-derived and buoy-derived SSTs decreased only by about 0.5°–1°C. Thus, the WCR’s effect was to provide a regime of positive feedback to the hurricane rather than negative feedback induced by cooler waters due to upwelling and vertical mixing as observed over the Bay of Campeche and north of the WCR.
    Sobel A. H., S. J. Camargo, 2011: Projected future seasonal changes in tropical summer climate. J. Climate, 24, 473-487, doi: 10.1175/2010JCLI3748.1.10.1175/ authors analyze changes in the tropical sea surface temperature (SST), surface wind, and other fields from the twentieth to the twenty-first century in climate projections using the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble, focusing on the seasons January--March (JFM) and July--September (JAS). When the annual mean change is subtracted, the remaining ''seasonal changes'' have robust, coherent structures. The JFM and JAS changes resemble each other very closely after either a change of sign or reflection about the equator. The seasonal changes include an increase in the summer hemisphere SST and a decrease in the winter hemisphere SST. These appear to be thermodynamic consequences of easterly trade winds strengthening in the winter subtropics and weakening in the summer subtropics. These in turn are associated with the weakening and expansion of the Hadley circulation, documented by previous studies, which themselves are likely consequences of changes in extratropical eddies. The seasonal SST changes influence the environment for deep convection: peak precipitation in the summer hemisphere increases by around 10%% and convective available potential energy (CAPE) increases by as much as 25%%. Comparable fractions of these changes are attributable to the annual mean change and the seasonal changes, though the two have very different spatial structures. Since the annual mean change is marked by relative warming in the Northern Hemisphere compared to the Southern Hemisphere, the seasonal changes oppose the annual mean change in JFM and enhance it in JAS.
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    Taylor K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485- 498.10.1175/ fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
    Wada A., N. Usui, 2007: Importance of tropical cyclone heat potential for tropical cyclone intensity and intensification in the western North Pacific. Journal of Oceanography,63, 427-447, doi: 10.1007/s10872-007-0039-0.10.1007/ is more important for tropical cyclone (TC) intensity and intensification, sea surface temperature (SST) or tropical cyclone heat potential (TCHP)? Investigations using best-track TC central pressures, TRMM/TMI three-day mean SST data, and an estimated TCHP based on oceanic reanalysis data from 1998 to 2004, show that the central pressure is more closely related to TCHP accumulated from TC formation to its mature stages than to the accumulated SST and its duration. From an oceanic environmental viewpoint, a rapid deepening of TC central pressure occurs when TCHP is relatively high on a basin scale, while composite distributions of TCHP, vertical wind shear, lower tropospheric relative humidity, and wind speed occurring in cases of rapid intensification are different for each TC season. In order to explore the influence of TCHP on TC intensity and intensification, analyses using both oceanic reanalysis data and the results of numerical simulations based on an ocean general circulation model are performed for the cases of Typhoons Chaba (2004) and Songda (2004), which took similar tracks. The decrease in TCHP due to the passage of Chaba led to the suppression of Songda鈥檚 intensity at the mature stage, while Songda maintained its intensity for a relatively long time because induced near-inertial currents due to the passage of Chaba reproduced anticyclonic warm eddies appearing on the leftside of Chaba鈥檚 track before Songda passed by. This type of intensity-sustenance process caused by the passage of a preceding TC is often found in El Ni帽o years. These results suggest that TCHP, but not SST, plays an important role in TC intensity and its intensification.
    Wada A., J. C. L. Chan, 2008: Relationship between typhoon activity and upper ocean heat content. Geophys. Res. Lett., 35,L17603, doi: 10.1029/2008GL035129.10.1029/[1] A 44-year mean distribution of tropical cyclone heat potential (TCHP), a measure of the oceanic heat content from the surface to the 26掳C-isotherm depth, shows that TCHP is locally high in the western North Pacific (WNP). TCHP varies on interannual time scales and has a relationship with tropical cyclone (TC) activity. The third mode of an empirical orthogonal function analysis of TCHP shows that an increase in the total number of TCs is accompanied with a warm central Pacific and cool WNP. Negative TCHP anomalies in the WNP suggest that an increase in total number of TCs results in cooling due to their passages. On the other hand, the first mode shows that the number of super typhoons increases in mature El Ni&ntilde;o years. An increase in accumulated TCHP is related to the increase in the number of super typhoons due to long duration.
    Wada A., N. Usui, and K. Sato, 2012: Relationship of maximum tropical cyclone intensity to sea surface temperature and tropical cyclone heat potential in the North Pacific Ocean. J. Geophys. Res., 117,D11118, doi: 10.1029/2012JD017583.10.1029/ Top of page Abstract 1.Introduction 2.Data and Methodology 3.Results 4.Discussion 5.Concluding Remarks Acknowledgments References Supporting Information [1] We investigated whether the maximum intensity of tropical cyclones (TC) in the North Pacific Ocean depends on sea surface temperature (SST) and tropical cyclone heat potential (TCHP). The study used reanalysis data sets for both the oceans and atmosphere: daily, 10-day, and monthly oceanic data sets; six-hour and monthly atmospheric data sets; and a daily satellite SST data set, for the July-to-October season from 2002 to 2005. For each TC, we summed TCHP from the time of genesis to the time of first reaching a minimum central pressure (MCP), to obtain an accumulated TCHP. In a linear regression analysis, the relationship between maximum TC intensity and accumulated TCHP differed between the eastern and western Pacific: high values of accumulated TCHP were needed before a TC attained a certain MCP in the western Pacific. In addition, the background convective available potential energy (CAPE) value was nearly four times larger in the western Pacific than in the eastern Pacific. The static stability was also 6.5% lower, the inertial stability 29.7% higher, and the size of tropical cyclones 38.2% larger in the western Pacific than in the eastern Pacific. The result indicated a deeper Rossby penetration depth and stronger TC in the western Pacific. Finally, we validated the TCHP values derived from three oceanic reanalysis data sets by using Argo profiling float observations. We found that use of only the daily data can reproduce the cooling effect of a passage of a TC, which caused a decrease in the TCHP values.
    Wang C. Z., L. P. Zhang, S. -K. Lee, L. X. Wu, and C. R. Mechoso, 2014: A global perspective on CMIP5 climate model biases. Nature Climate Change,4, 201-205, doi: 10.1038/nclimate2118.10.1038/ Intergovernmental Panel on Climate Change's Fifth Assessment Report largely depends on simulations, predictions and projections by climate models. Most models, however, have deficiencies and biases that raise large uncertainties in their products. Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of special regions and aspects of the climate system. Here we show that biases or errors in special regions can be linked with others at far away locations. We find in 22 climate models that regional sea surface temperature (SST) biases are commonly linked with the Atlantic meridional overturning circulation (AMOC), which is characterized by the northward flow in the upper ocean and returning southward flow in the deep ocean. A simulated weak AMOC is associated with cold biases in the entire Northern Hemisphere with an atmospheric pattern that resembles the Northern Hemisphere annular mode. The AMOC weakening is also associated with a strengthening of Antarctic Bottom Water formation and warm SST biases in the Southern Ocean. It is also shown that cold biases in the tropical North Atlantic and West African/Indian monsoon regions during the warm season in the Northern Hemisphere have interhemispheric links with warm SST biases in the tropical southeastern Pacific and Atlantic, respectively. The results suggest that improving the simulation of regional processes may not suffice for overall better model performance, as the effects of remote biases may override them.
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Manuscript History

Manuscript received: 30 April 2015
Manuscript revised: 20 August 2015
Manuscript accepted: 21 August 2015
通讯作者: 陈斌,
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Change of Tropical Cyclone Heat Potential in Response to Global Warming

  • 1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012

Abstract: Tropical cyclone heat potential (TCHP) in the ocean can affect tropical cyclone intensity and intensification. In this paper, TCHP change under global warming is presented based on 35 models from CMIP5 (Coupled Model Intercomparison Project, Phase 5). As the upper ocean warms up, the TCHP of the global ocean is projected to increase by 140.6% in the 21st century under the RCP4.5 (+4.5 W m-2 Representative Concentration Pathway) scenario. The increase is particularly significant in the western Pacific, northwestern Indian and western tropical Atlantic oceans. The increase of TCHP results from the ocean temperature warming above the depth of the 26°C isotherm (D26), the deepening of D26, and the horizontal area expansion of SST above 26°C. Their contributions are 69.4%, 22.5% and 8.1%, respectively. Further, a suite of numerical experiments with an Ocean General Circulation Model (OGCM) is conducted to investigate the relative importance of wind stress and buoyancy forcing to the TCHP change under global warming. Results show that sea surface warming is the dominant forcing for the TCHP change, while wind stress and sea surface salinity change are secondary.

1. Introduction
  • The upper ocean sustains tropical cyclone (TC) development by providing a considerable amount of heat and mitigating the sea surface cooling induced by the TC through upwelling and turbulent mixing (Gray, 1979; Mei et al., 2015). Tropical cyclone heat potential (TCHP) (Leipper and Volgenau, 1972) is a measure of the ocean heat content from the surface down to the depth of the 26°C isotherm (hereafter, D26). Many studies have reported that the TCHP in the ocean can affect TC intensity and intensification (e.g., Wada and Usui, 2007; Wada and Chan, 2008; Goni et al., 2009). The larger the TCHP, the more favorable the ocean conditions are for TC intensification (Shay et al., 2000; Lin et al., 2008; Goni et al., 2009; Wada et al., 2012).

    The upper ocean heat content has been shown to have increased in recent decades (Palmer et al., 2007; Domingues et al., 2008; Ishii and Kimoto, 2009; Levitus et al., 2012). (Levitus et al., 2012) reported that the heat content of the global ocean for the 0-700 m layer increased by 16.71.6× 1022 J during 1955-2010. Consistently, using satellite measurements, (Pun et al., 2013) found the TCHP has increased by 10.0% due to the increase in D26 during the past two decades in the western North Pacific Ocean. In a warming climate, the upper ocean could take up half of the heat from the surface to 700 m by the end of the 21st century (Collins et al., 2013). Thus, we expect an increase in TCHP in a warming climate. The structure of the TCHP change, and what determines that change, however, remains unknown.

    In this study, the TCHP change under global warming is analyzed based on 35 models from CMIP5 (Coupled Model Intercomparison Project, Phase 5). Then, a suite of numerical experiments with an OGCM is conducted to investigate the relative importance of wind stress and buoyancy forcing for the TCHP change under global warming.

2. Data and method
  • The model outputs used in this study are from the CMIP5. CMIP5 offers a multi-model perspective of simulated climate variability and change (Taylor et al., 2012). Historical and RCP4.5 (+4.5 W m-2 Representative Concentration Pathway) simulations are used to describe the present-day climate and warmer climate, respectively.

    Climate change is represented by the difference in the climatological mean between the last 25 years of the 21st century (2076-2100; hereafter, RCP) and the last 25 years of the 20th century (1976-2000; hereafter, HIS). The calculation is similar to that used in previous studies (e.g., Sobel and Camargo, 2011). A total of 35 CMIP5 models are used in this study (Table 1). Only one member run ("rlilp1") is selected for each model. We use all 35 models to calculate the multi-model average of each physical parameter. Each model is re-gridded to a common grid before the multi-model average is calculated. The common grid has a uniform 0.5°× 0.5° resolution horizontally, and 50 levels vertically.

  • The OGCM is the OPA (Ocèan Parallèlisè) component of the NEMO (Nucleus for European Modeling of the Ocean) modeling framework (Madec, 2008). It is a dynamic-thermodynamic model specifically designed for climate studies, with a global 1° resolution and a tropical refinement to 1/3°. The model has 46 levels in the vertical direction, with the layer thickness ranging from 6 m at the surface to 250 m at the bottom. The model integration time step is 1 h.

    To reach the quasi-equilibrium state, the model is first integrated for 100 years using the forcing of climatological monthly CORE2 (Coordinated Ocean-ice Reference Experiments, version 2) data (Large and Yeager, 2009). Then, the monthly wind stress, SST, and sea surface salinity (SSS) fields from 1976 to 2100, from the CMIP 35-model ensemble mean, are used to drive the ocean model. The SST and SSS are strongly restored toward the CMIP5 fields, with a relaxation time scale of 20 days (for a 50 m layer). Five experiments are conducted in the study (Table 2). The average of the last 25 years of each experiment is used for analysis. The differences between the four sensitivity experiments and the control experiment are used to represent the TCHP change forced by (1) the combined effects of wind stress, SST and SSS change, (2) the effect of wind stress change, (3) the effect of SST change, and (4) the effect of SSS change, respectively.

  • In this study, TCHP is defined as follows, as in (Leipper and Volgenau, 1972): \begin{equation} \label{eq1} {TCHP}=\sum_{h=0}^H\rho_hc_p(T_h-26)\Delta Z_h , (1)\end{equation} where ρh is the potential density of the sea water in each layer, cp is the specific heat capacity at constant pressure, Th is the ocean temperature in each layer, ∆ Zh is the thickness of each layer, H is D26, and h is the number of a particular vertical layer. When Th is below 26°C, the TCHP in that layer is assumed to be zero.

    Figure 1.  (a) The TCHP (units: 10$^8$ J m$^-2$) in WOA13 data (white contours) and the difference in TCHP between the ensemble mean of the CMIP5 HIS simulation and WOA13 (color shading). (b) The TCHP in the HIS simulation (white contours) and the change in TCHP (color shading). (c) The TCHP in RCP (color shading), and the white contour lines of SST for 26$^\circ$C in the HIS simulation. Basin classification is represented by black boxes. The seven ocean basins are: the North Indian Ocean (NIO); Northwest Pacific (NWP); Northeast Pacific (NEP); North Atlantic (NAT); South Atlantic (SAT); South Indian Ocean (SIO); South Pacific (SP).

3. Results
  • Figure 1a shows the climatological distribution (contours) of the TCHP in the WOA13 (World Ocean Atlas, 2013) dataset (Locarnini et al., 2013). The TCHP is high in the Indo-Pacific warm pool area, with the maximum in the tropical central Pacific Ocean. The TCHP in the tropical Atlantic Ocean is smaller than that in the tropical Pacific Ocean. Figure 1b shows the climatological distribution of the TCHP in HIS of CMIP5 (contours). Generally, the TCHP distribution from CMIP5 (Fig. 1b) is similar to the observation (Fig. 1a), although their differences are significant in some regions. Their spatial correlation reaches 0.88. The TCHP magnitude in CMIP5 is smaller than that in WOA13 in most regions (Fig. 1a, shading), especially in the areas where the climatological TCHP is large, e.g., the Indo-Pacific warm pool area and the western tropical Atlantic Ocean. Smaller TCHP in CMIP5 is also found in the Northwest Pacific Ocean around 15°N. Globally, the TCHP in CMIP5 underestimates the observed TCHP by 9.8%. This underestimation may be partially due to the cold SST bias in the tropical ocean in CMIP5 (Wang et al., 2014).

    Figure 2.  D26 distributions (units: m) along 160$^\circ$E in the HIS and RCP simulations. The numerals I-III indicate the three parts of TCHP change: the ocean temperature warming above D26, the deepening of D26, and the horizontal area expansion of SST above 26$^\circ$C.

    Figure 3.  TCHP change (units: 10$^8$ J m$^-2$) due to (a) the ocean temperature warming above D26, (b) the deepening of D26, and (c) the horizontal area expansion of SST above 26$^\circ$C.

    The high correlation between the historical experiments and observations suggests that the ensemble mean of the CMIP5 models can be a useful dataset for the projection of TCHP under climate change. Figure 1b shows the TCHP change in CMIP5 between the RCP and HIS simulations (shading). As the upper ocean warms up, the TCHP increases globally. The increase is particularly significant in the western Pacific, northwestern Indian, and western tropical Atlantic oceans. Globally, the TCHP increases by 129.4%. The change magnitude varies with ocean basin. The magnitude of increase for the North Atlantic and South Atlantic oceans can reach 312.9% and 287.1%, respectively. The South Pacific Ocean has the smallest magnitude of increase, at 104.4%. The magnitudes of TCHP change in the rest of the basins are as follows: Northeast Pacific (163.3%); Northwest Pacific (108%); North Indian Ocean (136.1%); South Indian Ocean (122.1%). Figure 1c shows the TCHP in RCP. As the SST warms up, the 26°C SST contour line extends a few degrees poleward. The horizontal area of SST above 26°C increases by 30.7% in RCP with respect to HIS. Adding the area expansion part, the TCHP of the global ocean increases by 140.6% in RCP with respect to HIS.

    To better understand the TCHP change under global warming, we decompose it into three parts (Fig. 2) as follows: \begin{eqnarray*} \Delta {TCHP}&=&\underline{{TCHP}(\Delta T,H_{HIS})}+\underline{{TCHP}(T_{RCP},\Delta H)}+\\ &&\qquad\quad\ \ {I}\qquad\qquad\qquad\quad\ \ {II}\\[-1mm] &&\underline{{TCHP}(T_{RCP},H_{RCP})_{AreaExpansion}} .\\ &&\qquad\quad\qquad\quad{III} \end{eqnarray*}

    The three parts describe the TCHP change due to temperature change above D26 (term I), the D26 deepening(term II), and the horizontal area change (term III). Figure 3 shows the three parts of the TCHP change. The TCHP increases significantly due to the ocean warming above D26 (Fig. 3a). The spatial pattern is very similar to the total TCHP change (Fig. 1b), characterized by a significant increase in the western Pacific, northwestern Indian, and western tropical Atlantic oceans. On average, this part of the TCHP change accounts for 69.4% of the total TCHP change, suggesting ocean warming above D26 is the most important part in total TCHP change. The warming of ocean temperature also deepens D26, and enlarges the horizontal area of SST above 26°C (Figs. 3b and c). The TCHP changes due to the deepening of D26 and due to the area expansion account for 22.5% and 8.1% of the total TCHP change, respectively.

    Although the ensemble mean provides some useful information on TCHP change, it is necessary to examine the TCHP change in individual models. Figure 4 shows the global total TCHP and its changes based on the results of both individual models and their ensemble mean. The ensemble-mean TCHP is close to the observation, although the former is relatively smaller than the latter (also shown in Fig. 1a). For individual models, the TCHP ranges from 1.30× 1022 J (EC-EARTH) to 5.89× 1022 J (CESM1-BGC). As the global ocean warms up, the TCHP is projected to increase in all models. Generally, the TCHP change is proportional to the total TCHP, with a linear fit slope of 0.4. We also calculated the TCHP and its change in individual ocean basins for these models. All ocean basins demonstrate similar features (not shown).

    Figure 4.  Scatter plot between the global total TCHP (units: \hbox10$^22$ J) and its change for the 35 CMIP5 models. The ensemble mean is plotted as a black dot. The red line indicates the total TCHP in WOA13. The blue line is the linear fit.

    Figure 5.  Changes of TCHP (units: 10$^8$ J m$^-2$) in different OGCM experiments forced by (a) wind stress, SST and SSS change; (b) SST change only; (c) wind stress change only; and (d) SSS change only.

  • Here, we use an OGCM to test the impact of wind stress, SST and SSS on TCHP change under global warming. Figure 5a shows the spatial pattern of TCHP change in the FULL-forcing experiment. The pattern is quite similar to the ensemble mean of CMIP5 (Fig. 1b). They both show that the TCHP increases in all regions, but with larger magnitudes in the western Pacific, northwestern Indian, and western tropical Atlantic oceans. Generally, the OGCM captures the main features of the TCHP response to climate change in CMIP5. The OGCM experiment forced only by SST change (Fig. 5b) also reproduces the results of the FULL-forcing experiment (Fig. 5a). Their spatial correlation reaches 0.95, with almost the same magnitude. Compared to the SST-only experiment, the TCHP changes in the WIND-only and SSS-only experiments are weak (Figs. 5c and d). The TCHP change in the four sensitivity experiments are 4.15× 1022 J, 4.24× 1022 J, -5.99× 1020 J, and 2.47× 1019 J, respectively. These experiments highlight the dominant role of SST forcing in the TCHP response to global warming.

4. Summary and discussion
  • The TCHP change under future global warming was investigated based on 35 CMIP5 models. As the upper ocean warms up, the TCHP increases globally. The increase is particularly significant in the western Pacific, northwestern Indian, and western tropical Atlantic oceans. The TCHP of the global ocean is projected to increase by 140.6% under the RCP4.5 scenario. Further analysis showed that the projected increase of TCHP mainly results from the ocean warming above D26, which accounts for 69.4% of the total change.

    A suite of OGCM experiments was conducted to investigate the relative importance of wind stress and buoyancy forcing to the TCHP change under global warming. The experiments showed that SST forcing is dominant in the TCHP response to global warming. The effects of wind stress and SSS on TCHP change are secondary.

    Although SST plays an important role in TC genesis, the ocean heat content, e.g., TCHP, has been shown to play a more important role in TC intensity and intensification (Shay et al., 2000; Wada and Usui, 2007; Goni et al., 2009). The projected increase of TCHP under global warming suggests the ocean may become more favorable for TC intensification, although it is still highly debated as to whether the accompanying changes in the ocean subsurface temperature profile may partially oppose this effect (Knutson et al., 2013; Huang et al., 2015). Meanwhile, the long-term effect of increased TC intensity can in turn further strengthen the ocean warming by pumping heat into the ocean, possibly leading to positive feedback (Emanuel, 2001; Sriver and Huber, 2007; Mei, 2013).




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