熱帶太平洋對流垂直結構之觀測與模擬特徵｜國立中央大學博碩士論文系統

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研究生：	朴春星 Hien Xuan Bui
論文名稱：	熱帶太平洋對流垂直結構之觀測與模擬特徵 Observed and Simulated Vertical Structure of Convection in Tropical Pacific Climate
指導教授：	余嘉裕 Jia-Yuh Yu
口試委員:
學位類別：	博士 Doctor
系所名稱：	地球科學學院 - 國際研究生博士學位學程 Taiwan international graduate program - Earth system science
論文出版年：	2016
畢業學年度：	105
語文別：	英文
論文頁數：	112
中文關鍵詞：	對流
外文關鍵詞：	Tropical Convection, Vertical structure of Convection, Western and Eastern Pacific
相關次數：	點閱：11 下載：0
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本論文探討對流垂直結構對熱帶氣候之影響，特別注重深對流和淺對流之分配，以及此分配變化如何影響西太平洋和東太平洋間熱帶輻合區(ITCZ)之濕靜能垂直輸送和降水模擬。我們使用氣象觀測再分析資料和CESM氣候模式模擬資料來探討上述變化背後所隱含的物理機制。

本論文主要貢獻有三個：首先，我們檢驗了控制深對流和淺對流垂直濕靜能輸送差異的因素。當最大垂直速度落在高(低)對流層時，如西(東)太平洋ITCZ區，有利於濕靜能輸出(入)。分析顯示，垂直濕靜能輸送的正負號主要由垂直水氣輸送項決定，其值大小對垂直運動的結構非常敏感。第二，我們利用CESM探討了模式空間解析度對對流垂直結構之影響，包含400km，200km，100km和50km四種解析度的敏感度實驗。實驗結果顯示，較高的模式解析度往往產生更多的淺對流，而較粗糙模式解析度傾，往往產生較少淺對流。更多的淺對流可增強降水頻率和強度，以及總降水量。瞭解上述結果對於氣候模式應用極為重要，因為目前氣候模式仍然使用較粗略的空間解析度進行模擬和推估未來氣候。最後，我們比對了13個CMIP5耦合模式深、淺對流的垂直結構特徵，並討論淺對流結構差異對熱帶降水模擬的影響。

This thesis aims to elucidate the impacts of vertical structure of convection on tropical climate. We focus on the partition between deep (top-heavy) and shallow (bottom-heavy) convection and how its change affects the moist static energy (MSE) transport and precipitation over the western and the eastern Pacific ITCZs. Both reanalysis data and model simulation output - using the Community Earth System Model (CESM) - are utilized to explore the mechanisms behind such change.

The thesis provides three main contributions. Firstly, we examined the controlling factors of the column-integrated vertical MSE advection for both deep and shallow convection. The MSE budgets are computed over the western Pacific and the eastern Pacific ITCZs, dominated respectively by a top-heavy and bottom-heavy structure of convection. A top-heavy (bottom-heavy) structure of vertical motion favors an export (import) of MSE and a positive (negative) value of the vertical MSE advection. It was shown that the sign of vertical MSE advection is determined mainly by the vertical moisture transport whose magnitude is very sensitive to the structure of vertical motion. Secondly, we introduced the impacts of model spatial resolutions on the vertical structure of convection in the CESM. Four spatial resolutions, 400 km, 200 km, 100 km and 50 km, are used. Higher resolution tends to produce more partition of shallow convection, while coarser resolution inclines to produce less. More partition of shallow convection tends to enhance precipitation frequency and intensity, as well as the total precipitation amount. This is particularly important in modeling tropical climate and projecting future climate change in which long term model runs are often performed with coarser resolutions. Lastly, we presented the vertical structure of deep and shallow convection in the Coupled Model Intercomparison Project phase 5 (CMIP5) models, that takes into account the impacts of shallow convection depth on precipitation.

Contents
中 文摘 要 ......................................................................................................................... i
Abstract........................................................................................................................... ii
Acknowledgements......................................................................................................... iii
Contents .......................................................................................................................... v
List of Figures................................................................................................................. vi
List of Tables................................................................................................................... ix
Chapter 1 Introduction.................................................................................................... 1
1 The goal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
3 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1 Tropical convection development . . . . . . . . . . . . . . . . . . . 6
3.2 Understanding cumulus parameterization . . . . . . . . . . . . . . . 7
4 Overview of our approach . . . . . . . . . . . . . . . . . . . . . . . . . . 9
5 Outline of the dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Chapter 2 Impacts of Vertical Structure of Convection in Tropical Climate: Moist
Static Energy Framework................................................................................................ 12
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2 Data and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.2 Moist static energy budget . . . . . . . . . . . . . . . . . . . . . . . 16
2.3 Singular value decomposition analysis . . . . . . . . . . . . . . . . . 17
3 Two modes of tropical convection . . . . . . . . . . . . . . . . . . . . . . 18
3.1 Vertical motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.2 Column-integrated vertical MSE advection . . . . . . . . . . . . . . 21
4 Controlling factors for vertical MSE advection . . . . . . . . . . . . . . . 22
4.1 Impacts of large-scale environment (thermodynamic effect) . . . . . 23
4.2 Impacts of vertical velocity proﬁle (dynamic effect) . . . . . . . . . . 24
4.3 Sensitivities to the upper bound of integration . . . . . . . . . . . . . 26
5 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 27
Chapter 3 Impacts of Model Spatial Resolution on the Vertical Structure of Convec-
tion .................................................................................................................................. 31
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2 Design of sensitivity experiments . . . . . . . . . . . . . . . . . . . . . . 34
2.1 The atmospheric model . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.2 The sensitivity experiments . . . . . . . . . . . . . . . . . . . . . . 35
2.3 Satellite and ﬁeld campaign datasets . . . . . . . . . . . . . . . . . . 36
3 Method of analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.1 Heat source (Q1) and moisture sink (Q2) . . . . . . . . . . . . . . . . 37
3.2 The dependence of convective vertical structure on precipitation rate . 38
4 Impacts of spatial resolution on simulations of tropical climate . . . . . . 39
4.1 Contrast between heavy-rain and light-rain regimes . . . . . . . . . . 39
4.2 Contrast between western and eastern Paciﬁc ITCZs . . . . . . . . . 44
5 The moisture budget analysis . . . . . . . . . . . . . . . . . . . . . . . . 48
6 Summary and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Chapter 4 Vertical Structure of Tropical Convection in CMIP5 Models........................ 54
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
2 Data and method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3 Vertical structure of tropical convection in CMIP5 . . . . . . . . . . . . . 59
4 Precipitation pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Chapter 5 Conclusions and Future Work........................................................................ 66
1 Key Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
2 Caveats in this approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Appendix A..................................................................................................................... 71
Appendix B..................................................................................................................... 73
                                

Bibliography
Adler, R. F., and Coauthors, 2003: The version-2 global precipitation climatology project
(GPCP) monthly precipitation analysis (1979-present). J. Hydrometeor, 4 (6), 1147–
1167, doi:10.1175/1525-7541(2003)004h1147:TVGPCPi2.0.CO;2,
Arakawa, 1993: Closure assumptions in the cumulus parameterization problem. The rep-
resentation of cumulus convection in numerical models. Amer. Meteor. Soc., 46, 1–16.
Arakawa, A., and W. H. Schubert, 1974: Interaction of a cumulus cloud ensem-
ble with the large-scale environment, Part I. J. Atmos. Sci., 31 (3), 674–701, doi:
10.1175/1520-0469(1974)031,
Back, L. E., and C. S. Bretherton, 2006: Geographic variability in the export of moist
static energy and vertical motion proﬁles in the tropical paciﬁc. Geophysical Research
Letters, 33 (17), doi:10.1029/2006GL026672,
Back, L. E., and C. S. Bretherton, 2009: On the relationship between sst gradients, bound-
ary layer winds, and convergence over the tropical oceans. J. Climate, 22 (15), 4182–
4196, doi:10.1175/2009JCLI2392.1,
Bellucci, A., S. Gualdi, and A. Navarra, 2010: The double-ITCZ syndrome in coupled
general circulation models: The role of large-scale vertical circulation regimes. J. Cli-
mate, 23 (5), 1127–1145, doi:10.1175/2009JCLI3002.1,
Benedict, J. J., and D. A. Randall, 2007: Observed characteristics of the MJO relative to
maximum rainfall. J. Atmos. Sci., 64 (7), 2332–2354, doi:10.1175/JAS3968.1
Berg, L. K., W. I. Gustafson, E. I. Kassianov, and L. Deng, 2013: Evaluation of a modiﬁed
scheme for shallow convection: Implementation of CuP and case studies. Mon. Wea.
Rev., 141 (1), 134–147, doi:10.1175/MWR-D-12-00136.1,
Betts, A. K., 1986: A new convective adjustment scheme. Part I: Observational and
theoretical basis. Quart. J. R. Meteor. Soc., 112 (473), 677–691, doi:10.1002/qj.
49711247307,
Bony, S., J.-L. Dufresne, H. Le Treut, J.-J. Morcrette, and C. Senior, 2004: On dynamic
and thermodynamic components of cloud changes. Climate Dynamics, 22 (2-3), 71–86,
doi:10.1007/s00382-003-0369-6.
Bony, S., and Coauthors, 2015: Clouds, circulation and climate sensitivity. Nature Geo-
science, 8 (4), 261–268, URL http://dx.doi.org/10.1038/ngeo2398.
Boyle, J., and S. A. Klein, 2010: Impact of horizontal resolution on climate model fore-
casts of tropical precipitation and diabatic heating for the TWP-ICE period. Journal of
Geophysical Research: Atmospheres, 115 (D23), doi:10.1029/2010JD014262,
Bretherton, C. S., P. N. Blossey, and C. R. Jones, 2013: Mechanisms of marine low cloud
sensitivity to idealized climate perturbations: A single-LES exploration extending the
CGILS cases. Journal of Advances in Modeling Earth Systems, 5 (2), 316–337, doi:
10.1002/jame.20019,
Bretherton, C. S., and S. Park, 2009: A new moist turbulence parameterization in
the community atmosphere model. J. Climate, 22 (12), 3422–3448, doi:10.1175/
2008JCLI2556.1,
Bretherton, C. S., M. E. Peters, and L. E. Back, 2004: Relationships between water vapor
path and precipitation over the tropical oceans. J. Climate, 17 (7), 1517–1528, doi:
10.1175/1520-0442(2004)017
Bretherton, C. S., J. R. McCaa, and H. Grenier, 2004: A new parameterization for shallow
cumulus convection and its application to marine subtropical cloud-topped boundary
layers. part i: Description and 1d results. Mon. Wea. Rev., 132 (4), 864–882, doi:10.
1175/1520-0493(2004)132,
Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods
for ﬁnding coupled patterns in climate data. J. Climate, 5 (6), 541–560, doi:10.1175/
1520-0442(1992)005h0541:AIOMFFi2.0.CO;2,
Bui, H. X., J.-Y. Yu, and C. Chou, 2016: Impacts of vertical structure of large-scale ver-
tical motion in tropical climate: Moist static energy framework. J. Atmos. Sci., 73 (11),
4427–4437, doi:10.1175/JAS-D-16-0031.1,
Cai, Q., G. J. Zhang, and T. Zhou, 2013: Impacts of shallow convection on MJO simula-
tion: A moist static energy and moisture budget analysis. J. Climate, 26 (8), 2417–2431,
doi:10.1175/JCLI-D-12-00127.1,
Chaboureau, J.-P., F. Guichard, J.-L. Redelsperger, and J.-P. Lafore, 2004: The role of
stability and moisture in the diurnal cycle of convection over land. Quart. J. R. Meteor.
Soc., 130 (604), 3105–3117, doi:10.1256/qj.03.132,
Chan, S. C., and S. Nigam, 2009: Residual diagnosis of diabatic heating from ERA-40
and NCEP reanalyses: Intercomparisons with TRMM. J. Climate, 22 (2), 414–428,
doi:10.1175/2008JCLI2417.1,
Chen, C.-A., J.-Y. Yu, and C. Chou, 2016: Impacts of vertical structure of convection
in global warming: The role of shallow convection. J. Climate, 29 (12), 4665–4684,
doi:10.1175/JCLI-D-15-0563.1,
Chikira, M., and M. Sugiyama, 2010: A cumulus parameterization with state-dependent
entrainment rate. Part I: Description and sensitivity to temperature and humidity pro-
ﬁles. J. Atmos. Sci., 67 (7), 2171–2193, doi:10.1175/2010JAS3316.1.
Cherry, S., 1996: Singular value decomposition analysis and canonical correlation anal-
ysis. J. Climate, 9 (9), 2003–2009, doi:10.1175/1520-0442(1996)009h2003:SVDAACi
2.0.CO;2,
Cherry, S., 1997: Some comments on singular value decomposition analysis. J. Climate,
10 (7), 1759–1761, doi:10.1175/1520-0442(1997)010h1759:SCOSVDi2.0.CO;2,
Chou, C., C.-A. Chen, P.-H. Tan, and K. T. Chen, 2012: Mechanisms for global warming
impacts on precipitation frequency and intensity. J. Climate, 25 (9), 3291–3306,
Chou, C., and J. D. Neelin, 2004: Mechanisms of global warming impacts on regional
tropical precipitation*. J. Climate, 17 (13), 2688–2701,
Chou, C., L.-F. Huang, L. Tseng, J.-Y. Tu, and P.-H. Tan, 2009a: Annual cycle of rainfall
in the western north paciﬁc and east asian sector. J. Climate, 22 (8), 2073–2094, doi:
10.1175/2008JCLI2538.1,
Chou, C., J. D. Neelin, C.-A. Chen, and J.-Y. Tu, 2009: Evaluating the rich-get-richer
mechanism in tropical precipitation change under global warming. J. Climate, 22 (8),
1982–2005, doi:10.1175/2008JCLI2471.1,
Chou, C., T.-C. Wu, and P.-H. Tan, 2013: Changes in gross moist stability in the trop-
ics under global warming. Climate Dynamics, 41 (9-10), 2481–2496, doi:10.1007/
s00382-013-1703-2,
Clement, A. C., R. Burgman, and J. R. Norris, 2009: Observational and model ev-
idence for positive low-level cloud feedback. Science, 325 (5939), 460–464, doi:
10.1126/science.1171255,
Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Conﬁguration and perfor-
mance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137 (656), 553–597,
doi:10.1002/qj.828.
Deng, A., N. L. Seaman, and J. S. Kain, 2003: A shallow-convection parameterization for
mesoscale models. Part I: Submodel description and preliminary applications. J. Atmos.
Sci., 60 (1), 34–56, doi:10.1175/1520-0469(2003)060,
Derbyshire, S. H., I. Beau, P. Bechtold, J.-Y. Grandpeix, J.-M. Piriou, J.-L. Redelsperger,
and P. M. M. Soares, 2004: Sensitivity of moist convection to environmental humidity.
Quart. J. Roy. Meteor. Soc., 130 (604), 3055–3079, doi:10.1256/qj.03.130,
Deser, C., A. Capotondi, R. Saravanan, and A. S. Phillips, 2006: Tropical Paciﬁc and
Atlantic climate variability in CCSM3. J. Climate, 19 (11), 2451–2481, doi:10.1175/
JCLI3759.1,
Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameteriza-
tions, and basic simulation characteristics of the atmospheric component AM3 of
the GFDL global coupled model CM3. J. Climate, 24 (13), 3484–3519, doi:10.1175/
2011JCLI3955.1.
Emori, S., T. Nozawa, A. Numaguti, and I. Uno, 2001: Importance of cumulus parame-
terization for precipitation simulation over East Asia in June. Journal of the Meteoro-
logical Society of Japan. Ser. II, 79 (4), 939–947, doi:10.2151/jmsj.79.939.
Emanuel, K. A., 1993: A Cumulus Representation Based on the Episodic Mixing Model:
The Importance of Mixing and Microphysics in Predicting Humidity, 185–192. Ameri-
can Meteorological Society, Boston, MA, doi:10.1007/978-1-935704-13-3 19,
Gregory, D., R. Kershaw, and P. M. Inness, 1997: Parametrization of momentum transport
by convection. Part II: Tests in single-column and general circulation models. Quart. J.
Roy. Meteor. Soc., 123 (541), 1153–1183, doi:10.1002/qj.49712354103,
Hack, J. J., 1994: Parameterization of moist convection in the national center for atmo-
spheric research community climate model (ccm2). Journal of Geophysical Research:
Atmospheres, 99 (D3), 5551–5568, doi:10.1029/93JD03478
Hack, J. J., J. M. Caron, G. Danabasoglu, K. W. Oleson, C. Bitz, and J. E. Truesdale,
2006: CCSM-CAM3 climate simulation sensitivity to changes in horizontal resolution.
J. Climate, 19 (11), 2267–2289, doi:10.1175/JCLI3764.1,
Hagos, S., and Coauthors, 2010: Estimates of tropical diabatic heating proﬁles: Common-
alities and uncertainties. J. Climate, 23 (3), 542–558, doi:10.1175/2009JCLI3025.1,
Hannah, W. M., and E. D. Maloney, 2014: The moist static energy budget in NCAR
CAM5 hindcasts during DYNAMO. Journal of Advances in Modeling Earth Systems,
6 (2), 420–440, doi:10.1002/2013MS000272,
Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global
warming. J. Climate, 19 (21), 5686–5699, doi:10.1175/JCLI3990.1,
Holloway, C. E., and J. D. Neelin, 2007: The convective cold top and quasi equilibrium*.
J. Atmos. Sci., 64 (5), 1467–1487, doi:10.1175/JAS3907.1,
Holloway, C. E., and J. D. Neelin, 2009: Moisture vertical structure, column wa-
ter vapor, and tropical deep convection. J. Atmos. Sci., 66 (6), 1665–1683, doi:
10.1175/2008JAS2806.1,
Holton, J. R., 2004: An Introduction to Dynamic Meteorology, 4th edition. Elsevier Aca-
demic Press.
Hourdin, F., and Coauthors, 2006: The LMDZ4 general circulation model: Climate per-
formance and sensitivity to parametrized physics with emphasis on tropical convection.
Climate Dynamics, 27 (7-8), 787–813, doi:10.1007/s00382-006-0158-0.
Jensen, M. P., and A. D. Del Genio, 2006: Factors limiting convective cloud-top height
at the ARM Nauru island climate research facility. J. Climate, 19 (10), 2105–2117,
doi:10.1175/JCLI3722.1
Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski, and W. H. Schubert,
1999: Trimodal characteristics of tropical convection. J. Climate, 12 (8), 2397–2418,
doi:10.1175/1520-0442(1999)012,
Johnson, N. C., and S.-P. Xie, 2010: Changes in the sea surface temperature threshold
for tropical convection. Nature Geoscience, 3 (12), 842–845, URL http://dx.doi.org/10.
1038/ngeo1008.
Lilly, D. K., 1968: Models of cloud-topped mixed layers under a strong inversion. Quart.
J. Roy. Meteor. Soc, 94 (401), 292–309.
Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume
model and its application in convective parameterization. J. Atmos. Sci., 47 (23), 2784–
2802.
Kay, J. E., and Coauthors, 2012: Exposing global cloud biases in the community atmo-
sphere model (CAM) using satellite observations and their corresponding instrument
simulators. J. Climate, 25 (15), 5190–5207, doi:10.1175/JCLI-D-11-00469.1,
Khairoutdinov, M., and D. Randall, 2006: High-resolution simulation of shallow-to-
deep convection transition over land. J. Atmos. Sci., 63 (12), 3421–3436, doi:10.1175/
JAS3810.1,
Kuang, Z., and C. S. Bretherton, 2006: A mass-ﬂux scheme view of a high-resolution
simulation of a transition from shallow to deep cumulus convection. J. Atmos. Sci.,
63 (7), 1895–1909, doi:10.1175/JAS3723.1,
Kuo, H. L., 1974: Further studies of the parameterization of the inﬂuence of cumu-
lus convection on large-scale ﬂow. J. Atmos. Sci., 31 (5), 1232–1240, doi:10.1175/
1520-0469(1974)031h1232:FSOTPOi2.0.CO;2,
Lau, K. M., and Coauthors, 2000: A report of the ﬁeld operations and early results of the south china sea monsoon experiment (SCSMEX). Bull. Amer. Meteor. Soc., 81 (6),
1261–1270, doi:10.1175/1520-0477(2000)081
Lin, S.-J., 2004: A vertically lagrangian ﬁnite-volume dynamical core for global models.
Mon. Wea. Rev., 132 (10), 2293–2307, doi:10.1175/1520-0493(2004)132,
Lindzen, R. S., and S. Nigam, 1987: On the role of sea surface temperature gradients in
forcing low-level winds and convergence in the tropics. J. Atmos. Sci., 44 (17), 2418–
2436, doi:10.1175/1520-0469(1987)044,
Ling, J., and C. Zhang, 2013: Diabatic heating proﬁles in recent global reanalyses. J.
Climate, 26 (10), 3307–3325, doi:10.1175/JCLI-D-12-00384.1,
Ma, Z., J. Fei, X. Huang, and X. Cheng, 2015: A potential problem with the application
of moist static energy in tropical cyclone studies. J. Atmos. Sci., 72 (8), 3009–3019,
doi:10.1175/JAS-D-14-0367.1,
Maloney, E. D., A. H. Sobel, and W. M. Hannah, 2010: Intraseasonal variability in an
aquaplanet general circulation model. Journal of Advances in Modeling Earth Systems,
2 (2), doi:10.3894/JAMES.2010.2.5,
Masunaga, H., M. Satoh, and H. Miura, 2008: A joint satellite and global cloud-resolving
model analysis of a madden-julian oscillation event: Model diagnosis. Journal of Geo-
physical Research: Atmospheres, 113 (D17), doi:10.1029/2008JD009986,
Neale, R. B., J. H. Richter, and M. Jochum, 2008: The impact of convection on ENSO:
From a delayed oscillator to a series of events. J. Climate, 21 (22), 5904–5924, doi:
10.1175/2008JCLI2244.1,
Neale, R. B., and Coauthors, 2010: Description of the ncar community atmosphere model
(CAM 5.0). NCAR Tech. Note NCAR/TN-486+ STR.
Neelin, J. D., and I. M. Held, 1987: Modeling tropical convergence based on the moist
static energy budget. Mon. Wea. Rev., 115 (1), 3–12, doi:10.1175/1520-0493(1987)
115h0003:MTCBOTi2.0.CO;2,
Neelin, J. D., 2007: Moist dynamics of tropical convection zones in monsoons, telecon-
nections and global warming, Chap. 10, 400. Princeton University Press.
Neelin, J. D., and J.-Y. Yu, 1994: Modes of tropical variability under convective ad-
justment and the Madden–Julian oscillation. Part I: Analytical theory. J. Atmos. Sci.,
51 (13), 1876–1894, doi:10.1175/1520-0469(1994)051h1876:MOTVUCi2.0.CO;2,
Neelin, J. D., and N. Zeng, 2000: A quasi-equilibrium tropical circulation model for-
mulation. J. Atmos. Sci., 57 (11), 1741–1766, doi:10.1175/1520-0469(2000)057h1741:
AQETCMi2.0.CO;2,
Neggers, R. A. J., J. D. Neelin, and B. Stevens, 2007: Impact mechanisms of shallow
cumulus convection on tropical climate dynamics*. J. Climate, 20 (11), 2623–2642,
doi:10.1175/JCLI4079.1,
Nigam, S., C. Chung, and E. DeWeaver, 2000: ENSO diabatic heating in ECMWF and
NCEP-NCAR reanalyses, and NCAR CCM3 simulation. J. Climate, 13 (17), 3152–
3171, doi:10.1175/1520-0442(2000)013h3152:EDHIEAi2.0.CO;2,
Nolan, D. S., C. Zhang, and S.-h. Chen, 2007: Dynamics of the shallow meridional cir-
culation around intertropical convergence zones. J. Atmos. Sci., 64 (7), 2262–2285,
doi:10.1175/JAS3964.1,
Nordeng, T. E., 1994: Extended versions of the convective parametrization scheme at
ECMWF and their impact on the mean and transient activity of the model in the tropics.
European Centre for Medium-Range Weather Forecasts.
Newman, M., and P. D. Sardeshmukh, 1995: A caveat concerning singular value decomposition. J. Climate, 8 (2), 352–360, doi:10.1175/1520-0442(1995)008h0352:
ACCSVDi2.0.CO;2
Ogura, Y., and N. A. Phillips, 1962: Scale analysis of deep and shallow convection in the
atmosphere. J. Atmos. Sci., 19 (2), 173–179, doi:10.1175/1520-0469(1962)019,
Park, S., and C. S. Bretherton, 2009: The university of washington shallow convection and
moist turbulence schemes and their impact on climate simulations with the community
atmosphere model. J. Climate, 22 (12), 3449–3469, doi:10.1175/2008JCLI2557.1,
Petch, J. C., A. R. Brown, and M. E. B. Gray, 2002: The impact of horizontal resolution
on the simulations of convective development over land. Quart. J. Roy. Meteor. Soc.,
128 (584), 2031–2044, doi:10.1256/003590002320603511,
Peters, M. E., Z. Kuang, and C. C. Walker, 2008: Analysis of atmospheric energy trans-
port in ERA-40 and implications for simple models of the mean tropical circulation. J.
Climate, 21 (20), 5229–5241, doi:10.1175/2008JCLI2073.1,
Raymond, D. J., S. L. Sessions, A. H. Sobel, and ˚A. Fuchs, 2009: The mechanics of gross
moist stability. Journal of Advances in Modeling Earth Systems, 1 (3), doi:10.3894/
JAMES.2009.1.9,
Richter, J. H., and P. J. Rasch, 2008: Effects of convective momentum transport on the
atmospheric circulation in the community atmosphere model, version 3. J. Climate,
21 (7), 1487–1499, doi:10.1175/2007JCLI1789.1,
Rieck, M., L. Nuijens, and B. Stevens, 2012: Marine boundary layer cloud feedbacks
in a constant relative humidity atmosphere. J. Atmos. Sci., 69 (8), 2538–2550, doi:
10.1175/JAS-D-11-0203.1,
Roeckner, E., and Coauthors, 2006: Sensitivity of simulated climate to horizontal and
vertical resolution in the echam5 atmosphere model. Journal of Climate, 19 (16), 3771–
3791, doi:10.1175/JCLI3824.1
Sherwood, S. C., S. Bony, and J.-L. Dufresne, 2014: Spread in model climate sensitivity
traced to atmospheric convective mixing. Nature, 505 (7481), 37–42.
Slingo, A., R. C. Wilderspin, and R. N. B. Smith, 1989: Effect of improved physi-
cal parameterizations on simulations of cloudiness and the Earth’s radiation budget.
Journal of Geophysical Research: Atmospheres,94 (D2), 2281–2301, doi:10.1029/
JD094iD02p02281,
Slingo, J., P. Inness, R. Neale, S. Woolnough, and G. Yang, 2003: Scale interactions on
diurnal to seasonal timescales and their relevance to model systematic errors. Annals of
Geophysics, 46 (1),
Sobel, A. H., 2007: Simple models of ensemble-averaged precipitation and surface wind,
given the sea surface temperature. The Global Circulation of the Atmosphere, edited by
T. Schneider and AH Sobel, 219–251.
Sobel, A. H., S. E. Yuter, C. S. Bretherton, and G. N. Kiladis, 2004: Large-scale meteorol-
ogy and deep convection during TRMM KWAJEX*. Mon. Wea. Rev., 132 (2), 422–444,
doi:10.1175/1520-0493(2004)132,
Soden, B. J., and I. M. Held, 2006: An assessment of climate feedbacks in coupled
ocean–atmosphere models. J. Climate, 19 (14), 3354–3360, doi:10.1175/JCLI3799.1,
Stephens, G. L., and Coauthors, 2002: The cloudsat mission and the a-train. Bul-
letin of the American Meteorological Society, 83 (12), 1771–1790, doi:10.1175/
BAMS-83-12-1771,
Stephens, G. L., and Coauthors, 2010: Dreary state of precipitation in global
models. Journal of Geophysical Research: Atmospheres, 115 (D24), doi:10.1029/
2010JD014532,
Stevens, B., 2007: On the growth of layers of nonprecipitating cumulus convection. J.
Atmos. Sci., 64 (8), 2916–2931, doi:10.1175/JAS3983.1
Stokes, G. M., and S. E. Schwartz, 1994: The atmospheric radiation measurement (ARM)
program: Programmatic background and design of the cloud and radiation test bed.
Bull. Amer. Meteor. Soc., 75 (7), 1201–1221, doi:10.1175/1520-0477(1994)075,
Sun, Y., S. Solomon, A. Dai, and R. W. Portmann, 2007: How often will it rain? J.
Climate, 20 (19), 4801–4818, doi:10.1175/JCLI4263.1,
Takayabu, Y. N., S. Shige, W.-K. Tao, and N. Hirota, 2010: Shallow and deep latent
heating modes over tropical oceans observed with TRMM PR spectral latent heating
data. J. Climate, 23 (8), 2030–2046, doi:10.1175/2009JCLI3110.1,
Tao, W.-K., and Coauthors, 2006: Retrieval of latent heating from TRMM measurements.
Bull. Amer. Meteor. Soc., 87 (11), 1555–1572, doi:10.1175/BAMS-87-11-1555,
Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2011: An overview of CMIP5 and
the experiment design. Bull. Amer. Meteor. Soc., 93 (4), 485–498, doi:10.1175/
BAMS-D-11-00094.1,
Tiedtke, M., 1989: A comprehensive mass ﬂux scheme for cumulus parameterization in
large-scale models. Mon. Wea. Rev., 117 (8), 1779–1800, doi:10.1175/1520-0493(1989)
117,
Tompkins, A. M., 2001: Organization of tropical convection in low vertical wind
shears: The role of cold pools. J. Atmos. Sci., 58 (13), 1650–1672, doi:10.1175/
1520-0469(2001)058h1650:OOTCILi2.0.CO;2,
von Salzen, K., and N. A. McFarlane, 2002: Parameterization of the bulk effects of lat-
eral and cloud-top entrainment in transient shallow cumulus clouds. Journal of the
Atmospheric Sciences, 59 (8), 1405–1430, doi:10.1175/1520-0469(2002)059h1405:
POTBEOi2.0.CO;2,
Waite, M. L., and B. Khouider, 2010: The deepening of tropical convection by congestus
preconditioning. J. Atmos. Sci., 67 (8), 2601–2615, doi:10.1175/2010JAS3357.1
Wallace, J. M., C. Smith, and C. S. Bretherton, 1992: Singular value decomposition of
wintertime sea surface temperature and 500-mb height anomalies. J. Climate, 5 (6),
561–576, doi:10.1175/1520-0442(1992)005h0561:SVDOWSi2.0.CO;2,
Wang, Z., 2014: Role of cumulus congestus in tropical cyclone formation in a high-
resolution numerical model simulation. J. Atmos. Sci., 71 (5), 1681–1700, doi:10.1175/
JAS-D-13-0257.1,
Webster, P. J., and R. Lukas, 1992: TOGA COARE: The coupled ocean—atmosphere
response experiment. Bull. Amer. Meteor. Soc., 73 (9), 1377–1416, doi:10.1175/
1520-0477(1992)073,
Wu, C.-M., B. Stevens, and A. Arakawa, 2009: What controls the transition from shallow
to deep convection? J. Atmos. Sci., 66 (6), 1793–1806, doi:10.1175/2008JAS2945.1,
Wu, Z., 2003: A shallow CISK, deep equilibrium mechanism for the interaction between
large-scale convection and large-scale circulations in the tropics. J. Atmos. Sci., 60 (2),
377–392, doi:10.1175/1520-0469(2003)060h0377:ASCDEMi2.0.CO;2,
Wu, T., 2012: A mass-ﬂux cumulus parameterization scheme for large-scale models:
description and test with observations. Climate Dynamics, 38 (3), 725–744, doi:10.
1007/s00382-011-0995-3,
Xie, S., T. Hume, C. Jakob, S. A. Klein, R. B. McCoy, and M. Zhang, 2010: Observed
large-scale structures and diabatic heating and drying proﬁles during TWP-ICE. J. Cli-
mate, 23 (1), 57–79, doi:10.1175/2009JCLI3071.1,
Yanai, M., S. Esbensen, and J.-H. Chu, 1973: Determination of bulk properties of tropical
cloud clusters from large-scale heat and moisture budgets. J. Atmos. Sci., 30 (4), 611–
627, doi:10.1175/1520-0469(1973)030,
Yanai, M., and R. Johnson, 1993: Impacts of cumulus convection on thermodynamic
ﬁelds. 39–62, doi:10.1007/978-1-935704-13-3 4
Yanai, M., and T. Tomita, 1998: Seasonal and interannual variability of atmospheric heat
sources and moisture sinks as determined from NCEP-NCAR reanalysis. J. Climate,
11 (3), 463–482, doi:10.1175/1520-0442(1998)011,
Yano, J.-I., and R. Plant, 2012: Interactions between shallow and deep convection under a
ﬁnite departure from convective quasi equilibrium. J. Atmos. Sci., 69 (12), 3463–3470,
doi:10.1175/JAS-D-12-0108.1,
Yoshimura, H., R. Mizuta, and H. Murakami, 2015: A spectral cumulus parameterization
scheme interpolating between two convective updrafts with semi-lagrangian calculation
of transport by compensatory subsidence. Monthly Weather Review, 143 (2), 597–621,
doi:10.1175/MWR-D-14-00068.1,
Yu, J.-Y., C. Chou, and J. D. Neelin, 1998: Estimating the gross moist stability of the
tropical atmosphere*. J. Atmos. Sci., 55 (8), 1354–1372, doi:10.1175/1520-0469(1998)
055h1354:ETGMSOi2.0.CO;2,
Yu, J.-Y., and J. D. Neelin, 1994: Modes of tropical variability under convective ad-
justment and the Madden-Julian oscillation. Part II: Numerical results. J. Atmos. Sci.,
51 (13), 1895–1914, doi:10.1175/1520-0469(1994)051h1895:MOTVUCi2.0.CO;2,
Yu, J.-Y., and J. D. Neelin, 1997: Analytic approximations for moist convectively adjusted
regions. J. Atmos. Sci., 54 (8), 1054–1063, doi:10.1175/1520-0469(1997)054h1054:
AAFMCAi2.0.CO;2,
Yukimoto, S., 2011: Meteorological research institute earth system model version 1
(MRI-ESM1): Model description.
Zhang, C., M. McGauley, and N. A. Bond, 2004: Shallow meridional circulation in
the tropical eastern Paciﬁc. J. Climate, 17 (1), 133–139, doi:10.1175/1520-0442(2004)
017h0133:SMCITTi2.0.CO;2
Zhang, C., D. S. Nolan, C. D. Thorncroft, and H. Nguyen, 2008: Shallow meridional
circulations in the tropical atmosphere. J. Climate, 21 (14), 3453–3470, doi:10.1175/
2007JCLI1870.1,
Zhang, G., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the param-
eterization of cumulus convection in the canadian climate centre general circulation
model. Atmosphere-Ocean, 33 (3), 407–446, doi:10.1080/07055900.1995.9649539,
Zhang, M. H., and Coauthors, 2005: Comparing clouds and their seasonal variations
in 10 atmospheric general circulation models with satellite measurements. Journal of
Geophysical Research: Atmospheres, 110 (D15), doi:10.1029/2004JD005021,
Zhang, Y., and S. A. Klein, 2010: Mechanisms affecting the transition from shallow to
deep convection over land: Inferences from observations of the diurnal cycle collected
at the ARM southern great plains site. J. Atmos. Sci., 67 (9), 2943–2959, doi:10.1175/
2010JAS3366.1

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