Precipitation distributions for explicit versus parametrized convection in a large‐domain high‐resolution tropical case study

Global climate and weather models tend to produce rainfall that is too light and too regular over the tropical ocean. This is likely because of convective parametrizations, but the problem is not well understood. Here, distributions of precipitation rates are analyzed for high-resolution UK Met Office Unified Model simulations of a 10 day case study over a large tropical domain (∼20°S–20°N and 42°E–180°E). Simulations with 12 km grid length and parametrized convection have too many occurrences of light rain and too few of heavier rain when interpolated onto a 1° grid and compared with Tropical Rainfall Measuring Mission (TRMM) data. In fact, this version of the model appears to have a preferred scale of rainfall around 0.4 mm h−1 (10 mm day−1), unlike observations of tropical rainfall. On the other hand, 4 km grid length simulations with explicit convection produce distributions much more similar to TRMM observations. The apparent preferred scale at lighter rain rates seems to be a feature of the convective parametrization rather than the coarse resolution, as demonstrated by results from 12 km simulations with explicit convection and 40 km simulations with parametrized convection. In fact, coarser resolution models with explicit convection tend to have even more heavy rain than observed. Implications for models using convective parametrizations, including interactions of heating and moistening profiles with larger scales, are discussed. One important implication is that the explicit convection 4 km model has temperature and moisture tendencies that favour transitions in the convective regime. Also, the 12 km parametrized convection model produces a more stable temperature profile at its extreme high-precipitation range, which may reduce the chance of very heavy rainfall. Further study is needed to determine whether unrealistic precipitation distributions are due to some fundamental limitation of convective parametrizations or whether parametrizations can be improved, in order to better simulate these distributions. Copyright © 2012 Royal Meteorological Society

[1]  Wojciech W. Grabowski,et al.  MJO-like Coherent Structures: Sensitivity Simulations Using the Cloud-Resolving Convection Parameterization (CRCP) , 2003 .

[2]  R. Hogan,et al.  Evaluation of the model representation of the evolution of convective systems using satellite observations of outgoing longwave radiation , 2010 .

[3]  Matthew E. Peters,et al.  Relationships between Water Vapor Path and Precipitation over the Tropical Oceans , 2004 .

[4]  S. Solomon,et al.  How Often Does It Rain , 2006 .

[5]  D. Randall,et al.  Large‐Eddy Simulation of Maritime Deep Tropical Convection , 2009 .

[6]  J. David Neelin,et al.  Critical phenomena in atmospheric precipitation , 2006 .

[7]  A. Matthews,et al.  Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject , 1996 .

[8]  Barnaby S. Love,et al.  The diurnal cycle of precipitation over the Maritime Continent in a high‐resolution atmospheric model , 2011 .

[9]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[10]  D. Randall,et al.  Convective Precipitation Variability as a Tool for General Circulation Model Analysis , 2007 .

[11]  Hiroaki Miura,et al.  A Madden-Julian Oscillation Event Realistically Simulated by a Global Cloud-Resolving Model , 2007, Science.

[12]  P. O'Gorman,et al.  The physical basis for increases in precipitation extremes in simulations of 21st-century climate change , 2009, Proceedings of the National Academy of Sciences.

[13]  A. Bodas‐Salcedo,et al.  Dreary state of precipitation in global models , 2010 .

[14]  J. David Neelin,et al.  Moisture Vertical Structure, Column Water Vapor, and Tropical Deep Convection , 2009 .

[15]  Chung-Lin Shie,et al.  Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part III: Estimating Apparent Moisture Sink Profiles over Tropical Oceans , 2008 .

[16]  J. Slingo,et al.  Uncertainties in future projections of extreme precipitation in the Indian monsoon region , 2009 .

[17]  Shuyi S. Chen,et al.  The CBLAST-Hurricane program and the next-generation fully coupled atmosphere–wave–ocean models for hurricane research and prediction , 2007 .

[18]  A. Staniforth,et al.  A new dynamical core for the Met Office's global and regional modelling of the atmosphere , 2005 .

[19]  E. Guilyardi,et al.  UNDERSTANDING EL NINO IN OCEAN-ATMOSPHERE GENERAL CIRCULATION MODELS : Progress and Challenges , 2008 .

[20]  Nigel Roberts,et al.  Characteristics of high-resolution versions of the Met Office unified model for forecasting convection over the United Kingdom , 2008 .

[21]  Richard H. Johnson,et al.  Large-Scale Heat and Moisture Budgets over the ASTEX Region , 1999 .

[22]  Jeroen C. J. H. Aerts,et al.  Partial costs of global climate change adaptation for the supply of raw industrial and municipal water: a methodology and application , 2010 .

[23]  M. Lemone,et al.  Cumulonimbus vertical velocity events in GATE. Part I: Diameter, intensity and mass flux , 1980 .

[24]  Damian R. Wilson,et al.  A microphysically based precipitation scheme for the UK meteorological office unified model , 1999 .

[25]  P. Rowntree,et al.  A Mass Flux Convection Scheme with Representation of Cloud Ensemble Characteristics and Stability-Dependent Closure , 1990 .

[26]  A. Deluca,et al.  Universality of rain event size distributions , 2010, 1010.4201.

[27]  C. Bretherton,et al.  An Energy-Balance Analysis of Deep Convective Self-Aggregation above Uniform SST , 2005 .

[28]  P. Bechtold,et al.  Modelling convective processes during the suppressed phase of a Madden–Julian oscillation: Comparing single‐column models with cloud‐resolving models , 2010 .

[29]  S. Esbensen,et al.  Determination of Bulk Properties of Tropical Cloud Clusters from Large-Scale Heat and Moisture Budgets , 1973 .

[30]  K. Trenberth,et al.  The Diurnal Cycle and Its Depiction in the Community Climate System Model , 2004 .

[31]  Ping Liu,et al.  An MJO Simulated by the NICAM at 14- and 7-km Resolutions , 2009 .

[32]  Kuolin Hsu,et al.  The frequency, intensity, and diurnal cycle of precipitation in surface and satellite observations over low- and mid-latitudes , 2007 .

[33]  P. Field,et al.  Properties of normalised rain‐rate distributions in the tropical Pacific , 2009 .

[34]  F. Wentz,et al.  Intercalibrated Passive Microwave Rain Products from the Unified Microwave Ocean Retrieval Algorithm (UMORA) , 2008 .

[35]  M. Newman,et al.  Stratiform Precipitation, Vertical Heating Profiles, and the Madden Julian Oscillation , 2004 .

[36]  P. Good,et al.  Current changes in tropical precipitation , 2010 .

[37]  K. Lau,et al.  Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations. Part I: South China Sea Monsoon Experiment , 2007 .

[38]  Masaki Satoh,et al.  Ensemble Simulation of Cyclone Nargis by a Global Cloud-System-Resolving Model—Modulation of Cyclogenesis by the Madden-Julian Oscillation , 2010 .

[39]  G. Martin,et al.  A New Boundary Layer Mixing Scheme. Part I: Scheme Description and Single-Column Model Tests , 2000 .

[40]  Hiroaki Miura,et al.  A Simulated Preconditioning of Typhoon Genesis Controlled by a Boreal Summer Madden-Julian Oscillation Event in a Global Cloud-system-resolving Model , 2009 .

[41]  Philip J. Rasch,et al.  Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals , 2006 .

[42]  T. L’Ecuyer,et al.  Spectral Retrieval of Latent Heating Profiles from TRMM PR data. Part 3; Moistening Estimates over Tropical Ocean Regions , 2007 .

[43]  Katherine Thayer-Calder,et al.  The Role of Convective Moistening in the Madden–Julian Oscillation , 2009 .

[44]  Pedro M. M. Soares,et al.  Sensitivity of moist convection to environmental humidity , 2004 .

[45]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[46]  L. Donner,et al.  The Frequency of Extreme Rain Events in Satellite Rain-Rate Estimates and an Atmospheric General Circulation Model , 2007 .

[47]  W. Tao,et al.  Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations , 2007 .

[48]  J. Janowiak,et al.  The Global Precipitation Climatology Project (GPCP) combined precipitation dataset , 1997 .

[49]  N. McFarlane,et al.  Sensitivity of Climate Simulations to the Parameterization of Cumulus Convection in the Canadian Climate Centre General Circulation Model , 1995, Data, Models and Analysis.