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

Holloway, Christopher E.; Woolnough, Steven J.; Lister, Grenville

doi:10.1002/qj.1903

Cited by 86 publications

(93 citation statements)

References 46 publications

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“…This might be due to the use of Kain-Fritsch scheme in the 5-and 20-km-resolution experiments; well-organized convective lines tend to appear. Light precipitation may increase when a cumulus parameterization is used (e.g., Holloway et al 2012). In contrast, large-scale structures in the strong precipitation areas are almost the same in all the experiments (Fig.…”

Section: Discussionmentioning

confidence: 88%

Comparing Simulated Size Distributions of Precipitation Systems at Different Model Resolution

Otsuka

Trilaksono

Yoden

2017

SOLA

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Size distributions of tropical convective systems in regional numerical atmospheric models are analyzed over a 2.5 × 10 5 km 2 domain using different model grid spacing and parameterization schemes. The 5-and 20-km-resolution experiments are configured with a cumulus parameterization scheme, whereas the 2-and 4-km-resolution experiments are not. Precipitation systems are defined by either synthetic satellite infrared images, surface rain rates, or vertical winds at 600 hPa. The size distributions of systems defined by shallower clouds, lower rain rates, and weaker updrafts follow power laws, whereas those defined by deep clouds, higher rain rates, and stronger updrafts show lognormality. The cloud size distribution of the 5-km-resolution experiment is most similar to that of the real geostationary satellite observations. Generally, the largest system size becomes larger in the 5-and 20-km-resolution experiments, implying that the cumulus parameterization may have an impact on that scale. Exceptionally, all the model-simulated size distributions of heavy rain areas agree well at the largest scale. Lower-resolution experiments tend to underestimate the number of small-scale systems when compared with higher-resolution experiments. The size distributions also capture a temporal modulation of precipitation during the 2007 Jakarta flood event; small-scale intense precipitation systems increase during the period.(Citation: Otsuka, S., N. J. Trilaksono, and S. Yoden, 2017: Comparing simulated size distributions of precipitation systems at different model resolution. SOLA, 13, 130−134,

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Section: Discussionmentioning

confidence: 88%

Comparing Simulated Size Distributions of Precipitation Systems at Different Model Resolution

Otsuka

Trilaksono

Yoden

2017

SOLA

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“…Switching off the convective parameterization in high-resolution (17-km grid spacing) global models causes a step change in the way convection is represented. Globally, over both land and sea, the timing of the peak in the diurnal cycle is much improved in the convection-permitting simulations, although the amount of precipitation is biased high, particularly over high orography, which is a known issue in convectionpermitting configurations of the MetUM (Birch et al 2014b;Holloway et al 2012).…”

Section: Discussionmentioning

confidence: 99%

Sea-Breeze Dynamics and Convection Initiation: The Influence of Convective Parameterization in Weather and Climate Model Biases

et al. 2015

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There are some long-established biases in atmospheric models that originate from the representation of tropical convection. Previously, it has been difficult to separate cause and effect because errors are often the result of a number of interacting biases. Recently, researchers have gained the ability to run multiyear global climate model simulations with grid spacings small enough to switch the convective parameterization off, which permits the convection to develop explicitly. There are clear improvements to the initiation of convective storms and the diurnal cycle of rainfall in the convection-permitting simulations, which enables a new process-study approach to model bias identification. In this study, multiyear global atmosphere-only climate simulations with and without convective parameterization are undertaken with the Met Office Unified Model and are analyzed over the Maritime Continent region, where convergence from sea-breeze circulations is key for convection initiation. The analysis shows that, although the simulation with parameterized convection is able to reproduce the key rain-forming sea-breeze circulation, the parameterization is not able to respond realistically to the circulation. A feedback of errors also occurs: the convective parameterization causes rain to fall in the early morning, which cools and wets the boundary layer, reducing the land-sea temperature contrast and weakening the sea breeze. This is, however, an effect of the convective bias, rather than a cause of it. Improvements to how and when convection schemes trigger convection will improve both the timing and location of tropical rainfall and representation of sea-breeze circulations.

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“…Moisture-convection feedback is strongly suspected to be important for the MJO (e.g., Grabowski and Moncrieff 2004;Maloney 2009). The relationship between humidity and precipitation can be strongly sensitive to entrainment rates in simple plume models and convective parameterizations (e.g., Derbyshire et al 2004;Holloway and Neelin 2009), and larger values of entrainment, or evaporation of condensate, can lead to improved MJO variability in GCMs (Lin et al 2006;Maloney 2009). Here, we look at the relationship between free-tropospheric humidity and rainfall in the different models and in ECMWF/TRMM.…”

Section: Humidity-precipitation Relationshipmentioning

confidence: 99%

The Effects of Explicit versus Parameterized Convection on the MJO in a Large-Domain High-Resolution Tropical Case Study. Part I: Characterization of Large-Scale Organization and Propagation*

Holloway

Woolnough

Lister

2013

Journal of the Atmospheric Sciences

112

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High-resolution simulations over a large tropical domain (;208S-208N, 428E-1808) using both explicit and parameterized convection are analyzed and compared to observations during a 10-day case study of an active Madden-Julian oscillation (MJO) event. The parameterized convection model simulations at both 40-and 12-km grid spacing have a very weak MJO signal and little eastward propagation. A 4-km explicit convection simulation using Smagorinsky subgrid mixing in the vertical and horizontal dimensions exhibits the best MJO strength and propagation speed. Explicit convection simulations at 12 km also perform much better than the 12-km parameterized convection run, suggesting that the convection scheme, rather than horizontal resolution, is key for these MJO simulations. Interestingly, a 4-km explicit convection simulation using the conventional boundary layer scheme for vertical subgrid mixing (but still using Smagorinsky horizontal mixing) completely loses the large-scale MJO organization, showing that relatively high resolution with explicit convection does not guarantee a good MJO simulation. Models with a good MJO representation have a more realistic relationship between lower-free-tropospheric moisture and precipitation, supporting the idea that the moisture-convection feedback is a key process for MJO propagation. There is also increased generation of available potential energy and conversion of that energy into kinetic energy in models with a more realistic MJO, which is related to larger zonal variance in convective heating and vertical velocity, larger zonal temperature variance around 200 hPa, and larger correlations between temperature and ascent (and between temperature and diabatic heating) between 500 and 400 hPa.

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

Cited by 86 publications

References 46 publications

Comparing Simulated Size Distributions of Precipitation Systems at Different Model Resolution

Comparing Simulated Size Distributions of Precipitation Systems at Different Model Resolution

Sea-Breeze Dynamics and Convection Initiation: The Influence of Convective Parameterization in Weather and Climate Model Biases

The Effects of Explicit versus Parameterized Convection on the MJO in a Large-Domain High-Resolution Tropical Case Study. Part I: Characterization of Large-Scale Organization and Propagation*

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