IPCC AR4 模式对热带气旋热力控制因子的模拟评估

余锦华; 唐盛; 吴立广; 施能

IPCC AR4 模式对热带气旋热力控制因子的模拟评估

南京信息工程大学气象灾害省部共建教育部重点实验室,大气科学学院,江苏南京 210044

基金项目: 公益性行业(气象)科研专项(GYHY200806009);"973"项目(2009CB421503);国家自然科学基金(40775060)。

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出版历程
- 收稿日期: 2009-08-21
- 修回日期: 2010-06-07

Assessments on simulation of thermodynamic parameters of tropical cyclone in IPCC-AR4 Models

Key Loboratory of Meteorological Disaster of Ministry of Education, Atmospheric Sciences, NUIST, Nanjing 210044,China

摘要

摘要: 海平面温度是影响热带气旋活动重要的大尺度环境热力控制因子,根据1948-1999年热带地区(30°S－30°N)海平面温度(SST)的气候场、线性趋势、年代际变化与年际变化的空间结构特征,分别就24个IPCC AR4模式的模拟性能进行评估。结果表明,虽然24个IPCC AR4模式对SST气候场的模拟性能都比较好,但大部分模式输出的SST系统性偏低于观测分析场(ERSST)。所有模式热带区域平均SST都表现出与ERSST相一致的增暖趋势,但各模式与ERSST的这一趋势强度差异明显。综合考虑SST线性趋势及年代际变化的空间结构,24个IPCC AR4模式中,有6个模式的模拟性能较差,其空间型态与ERSST相差很大,不应作为模式集成的对象,它们是INM CM3_0, MRI_CGCM2, INGV_ECHAM4,UKMO_HADCM3,NCAR_PCM1,MPI_ECHAM5。前5个空间型态与ERSST最接近的模式依次是:CGCM3.1_T47,GISS ER,MIROC_HIRES,GFDL CM2_1,GFDL CM2_0。对西北太平洋、北大西洋以及南海地区6~10月热带气旋主要活动海域SST进行了评估,相对来说,模式对北大西洋和南海海域SST不论是线性趋势还是年代际变化的模拟都好于西北太平洋。北大西洋有18个模式年代际序列与ERSST的相关较高。在西北太平洋,UKMO_HADGEM1和MPI_ECHAM5的年际变化序列与ERSST的相关达到0.05的显著性水平;在南海,年际变化模拟最好的模式是UKMO_HADCM3。
- IPCCAR4模式 /
- 热带气旋 /
- 热力控制因子 /
- 模拟评估
Abstract: Sea surface temperature (SST) is an important environmental thermodynamic factor affecting tropical cyclone (TC)activity, the fidelity of SST over tropical regions(30°S-30°N)in the coupled general circulation models (CGCM) participating in the Forth Assessment Report(AR4) of Intergovernmental Panel on Climate Change (IPCC)is accessed by virtue of comparing simulated climate field, spatial patterns in linear trends, multidecadal and interannual changes of SST during 1948-1999. It is found that although 24 IPCC-AR4 models show a good performance in mean state, most of SST in models shows a cold bias in comparison with ERSST. Regional mean annual SST gives a warming trend in all models, but there is much discrepancy between the amplitude of trends in models and ERSST. According to the performance of simulation in spatial structure of linear trends and multidecadal changes, six (INM CM3_0, MRI_CGCM2,3.2a, INGV_ECHAM4, UKMO_HADCM3,NCAR_PCM1, MPI_ECHAM5) of 24 IPCC AR4 models should not be ensemble to study a global warming scenario of tropical cyclone activity because of much difference of spatial patterns between these models and ERSST.The first five models, their spatial patterns of linear trends and multidecadal variations represent well with that of ERSST, are CGCM3.1_T47, GISS ER, MIROC_HIRES, GFDL CM2.1, GFDL CM2.0, successively. It also showed that both linear trend and multidecadal change of SST from June to October, a major TC active season, are simulated better over North Atlantic basin than over north western Pacific and South China Sea after evaluating the performance of SST over above three TC active regions. 18 of 24 models have significant relationship in multidecadal series between simulated SST and ERSST over North Atlantic. The performance of UKMO_HADGEM1 and MPI_ECHAM5 in interannual change of SST over north western Pacific is good enough to use them but it is UKMO_HADCM3 in South China Sea.
- IPCC AR4 models /
- tropical cyclone /
- thermodynamic control factors /
- simulation assessment

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参考文献(44)

YU J-H, WANG Y. Response of tropical cyclone potential intensity over the north Indian Ocean to global warming[J]. Geophys Res Lett, 2009, 36:L03709, doi: 10.1029/2008GL036742.

EMANUEL K A, SUNDARAJAN R, WILLIAMS J. Hurricane and global warming: Results from downscaling IPCC AR4 simulations[J]. Bull Amer Meteor Soc, 2008,89:347-367.

KNUTSON T R, SIRUTIS J J, GARMNER S T, et al. Simulated reduction in Atlantic hurricane frequency under twenty-first-century warming conditions[J]. Nature Geoscience, 2008,doi: 10.1038/ngeo202.

MEEHL G A, COVEY C, DELWORTH T, et al. THE WCRP CMIP3 multimodel dataset: A new era in climate change research[J]. Bull Amer Meteor Soc, 2007,88: 1383-1394.

SZOEKE S P , XIE S P. The tropical eastern Pacific seasonal cycle: Assessment of errors and mechanisms in IPCC AR4 coupled ocean atmosphere general circulation models[J]. J Clim, 2008, 21: 2573-2590.

CAI W, COWAN T. Trends in Southern Hemisphere Circulation in IPCC AR4 Models over 1950-99: Ozone depletion versus greenhouse forcing[J].J Clim, 2007,20:681-693.

CAI W, SULLIVAN A, COWAN T. How rare are the 2006-2008 positive Indian Ocean Dipole events? An IPCC AR4 climate model perspective[J]. Geophy Res Lett, 2009,36: L08702, doi: 10.1029/2009GL037982.

LIN J, KILADIS G N, MAPES B E,et al. Tropical intraseasonal variability in 14 IPCC AR4 Climate Models. Part Ⅰ: Convective Signals[J]. J Clim, 2006, 19: 2665-2690.

ACHUTARAO K, SSERBER K R. Simulation of the El Niño Southern Oscillation: Results from the Coupled Model Inter comparison Project[J]. Clim Dyn, 2002,19:191-209.

ACHUTARAO K, SPERBER K R. ENSO simulation in coupled ocean-atmosphere models: are the current models better? [J]. Clim Dyn, 2006,27: 1-15.

SUN Y, DING Y-H.An assessment on the performance of IPCC AR4 climate models in simulating interdecadal variations of the East Asian summer monsoon[J].Acta Meteorogica Sinica, 2008,22: 472-488.

AIGUO D, MEEHL G A, WASHINGTON W M. Climate changes in the 21st Century over the Asia-Pacific region simulated by the NCAR CSM and PCM[J].Advances in Atmospheric Sciences, 2001: 18:639-658.

KRIPALANI R H, OH J H, CHAUDHARI H S. Response of the East Asian summer monsoon to doubled atmospheric CO₂: Coupled climate model simulations and projections under IPCC AR4[J]. Theor Appl Climatol, 2007, 87: 1-28.

KRRIPALANI R H, OH J H, KULKARNI A,et al. South Asian summer monsoon precipitation variability: Coupled climate model simulations and projections under IPCC AR4[J]. Theor Appl Climatol, 2007, 90: 133-159.

祝亚丽,王会军. 基于IPCC AR4耦合模式的南极涛动和北极涛动的模拟及未来变化预估[J].气象学报,2008,66(6):993-1004.

蔡怡 ,王彰贵, 乔方利.全球变暖背景下最近40 a太平洋海温变化数值模拟[J].海洋学报,2008,30(5):9-16.

MALKUS B S, RIEHL H. On the dynamics and energy transformation in steady-state hurricanes[J]. Tellus, 1960, 12: 1-20.

SCHADE L R. Tropical cyclone intensity and sea surface temperature[J]. J Atmos Sci, 2000, 57: 3122-3130.

SAUNDERS M A,HARRIS A R. Statistical evidence links of exceptional 1995 Atlantic hurricane season to record sea warming[J]. Geophys Res Lett, 1997, 24: 1255-1258.

EMANUEL K A. The dependence of hurricane intensity on climate[J]. Nature, 1987,42: 483-485.

EMANUEL K A. Thermodynamic control of hurricane intensity[J]. Nature, 1999,401: 665-669.

HOLLAND G J. The maximum potential intensity of tropical cyclones[J]. J Atmos Sci, 1997,54: 2519-2541.

HENDERSON-SELLERS A, co-authors. Tropical cyclones and global climate change: A POST-IPCC assessment[J]. Bull Amer Meteor Soc, 1998,79: 19-38.

LATIF M, KEENLYSIDE N,BADER J. Tropical sea surface temperature, vertical shear, and hurricane development[J]. Geophy Res Lett, 2007,34: L01710, doi: 10.1029/2006GL027969.

GOLDENBERG S B, SHAPIRO L J. Physical mechanisms for the association of El Niño and West African rainfall with Atlantic major hurricane activity [J]. J Clim, 1996, 9: 1169-1187.

GOLDENBERG S B, LANDSEA C W,MESTAS-NUNEZ A M,et al. The Recent increase in Atlantic hurricane activity: causes and implications[J]. Science, 2001,293: 474-479.

VECCHI G A,SODEN B J. Increased tropical Atlantic wind shear in model projections of global warming[J]. Geophys. Res. Lett., 2007,34, L08702, doi: 10.1029/2006GL028905.

SOBEL A H, HELD I M. The ENSO signal in tropical tropospheric temperature[J]. J Clim, 2002, 15: 2702-2706.

SHEN W, TULEYA R E,GINIS I. A sensitivity study of thermodynamic environment on GFDL model hurricane intensity: Implications for global warming[J]. J Clim, 2000, 1 3: 109-121.

TANG B, NEELIN J. ENSO Influence on Atlantic hurricanes via tropospheric warming[J]. Geophys Res Lett, 2004, 31, L24204, doi: 10.1029/2004GL021072.

SMITH T M , REYNOLDS R W. Improved extended reconstruction of SST (1954-1997)[J]. J Clim, 2004,17: 2466-2477.

CAMARGO S J , SOBEL A H. Western North Pacific tropical cyclone intensity and ENSO[J]. J Clim, 2005,18(15):2996-3006.

STATOSHI L, MATSUURA T. ENSO and Western North Pacific tropical cyclone activity simulated in a CGCM[J]. Clim Dyn, 2008, 30: 815-830.

WANG, CHAN J. How strong ENSO events affect tropical storm activity over the western North Pacific[J]. J Clim, 2002, 15: 1643-1658.

JANICO S. Impact of warm ENSO events on atmospheric circulation and convection over the tropical Atlantic and West Africa[J]. Ann Geophysicae, 1997,15: 471-475.

YUKIMOTO S, NODA A,KITOH A, et al. The New Meteorological Research Institute Coupled GCM (MRI-CGCM2)-Model climate and variability[J]. Meteo Geophys, 2001,51: 47-88.

FLATO G M, BOER G J, LEE W G, et al. The canadian centre for climate modelling and analysis global coupled model and its climate[J]. Climate Dyn,2000, 16: 427-450.

周学鸣,魏应植,吴陈锋.夏季西太平洋台风频数异常与ENSO事件的关系及大气环流异常特征[J].热带气象学报,2006,22:35-40.

HOERLING M P , HURRELL J W,XU T. Tropical origins for recent North Atlantic climate change[J]. Science, 2001,292:90-92.

MUTHUVEL C,BELL G D. Tropical multidecadal and interannual climate variability in the NCEP-NCAR Reanalysis[J]. J Clim, 2004,17: 1777-1802.

MESTAS-NUEZ M A,ENFIELD D B. Rotated global modes of non-ENSO sea surface temperature variability[J]. J Clim, 1999,12:2734-2746.

MESTAS-NUEZ M A, ENFIELD D B. Eastern equatorial Pacific SST variability: ENSO and non-ENSO components and their climatic associations[J]. J Clim, 2001,14:391-402.

GARREAUD R, BATTISTI D S. Interannual and interdecadal (ENSO-like) variability in the Southern Hemisphere tropospheric circulation[J]. J Clim, 1999, 12:2113-2123.

ZHANG Y, WALLACE J M, BATTISTI D S. ENSO-like interdecadal variability[J]. J Clim, 1997,10: 1004-1020.

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