Organized convective systems in the tropical western pacific as a process in general circulation models: A toga coare case-study

1997 ◽  
Vol 123 (540) ◽  
pp. 805-827 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Ernst Klinker
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Western Pacific ◽  
Convective Systems ◽  
Tropical Western Pacific ◽  
Toga Coare

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

scholarly journals Importance of the advection scheme for the simulation of water isotopes over Antarctica by general circulation models: a case study with LMDZ-iso (LMDZ5a revision 1750)

2017 ◽  
Author(s):  
Alexandre Cauquoin ◽  
Camille Risi
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Temperature Relationship ◽  
Water Isotopes ◽  
Good Representation ◽  
Advection Scheme ◽  
Atmospheric General Circulation ◽  
Atmospheric General Circulation Models ◽  
Polar Water

Abstract. Atmospheric general circulation models (AGCMs) are known to have a warm and isotopically enriched bias over Antarctica. We test here the hypothesis that these biases are consequences of a too diffusive advection. Using the LMDZ-iso model, we show that a good representation of the advection, especially on the horizontal, is very important to reduce the bias in the isotopic contents of precipitation above this area and to improve the modelled water isotopes – temperature relationship. A good advection scheme is thus essential when using GCMs for paleoclimate applications based on polar water isotopes.

scholarly journals Deterministic and probabilistic evaluation of raw and post-processing monthly precipitation forecasts: a case study of China

2021 ◽  
Author(s):  
Yujie Li ◽  
Bin Xu ◽  
Dong Wang ◽  
QJ Wang ◽  
Xiongwei Zheng ◽  
...  
Keyword(s):  
General Circulation ◽  
Critical Role ◽  
Joint Probability ◽  
General Circulation Models ◽  
Mean Value ◽  
Monthly Precipitation ◽  
Post Processing ◽  
Probabilistic Evaluation ◽  
Forecasting Performance

Abstract Monthly Precipitation Forecasts (MPF) play a critical role in drought monitoring, hydrological forecasting and water resources management. In this study, we applied two advanced Machine Learning Models (MLM) and latest General Circulation Models (GCM) to generate deterministic MPFs with a resolution of 0.5° across China. Then the Bayesian Joint Probability (BJP) modeling approach is employed to calibrate and generate corresponding ensemble MPFs. Raw and post-processing MPFs were put against gridded observations over the period of 1981–2015. The results indicated that: (1) for deterministic evaluation, the forecasting performance of MLMs was more inclined to generate random forecasts around the mean value, while the GCMs could reflect the increasing or decreasing trend of precipitation to some degree; (2) for probabilistic evaluation, the four BJP calibrated ensemble MPFs were unbiased and reliable. Compared to climatology, reliability and sharpness were all significantly improved. However, in terms of overall accuracy metric, the ensemble MPFs generated from MLMs were similar to climatology. In contrast, the ensemble MPFs generated from GCMs achieved better forecasting skill and was not dependent on forecasting regions and months. Moreover, the post-processing method is necessary that achieve not only bias-free but also reliable as well as skillful ensemble MPFs.

Using the Stochastic Multicloud Model to Improve Tropical Convective Parameterization: A Paradigm Example

2012 ◽  
Vol 69 (3) ◽  
pp. 1080-1105 ◽  
Author(s):  
Yevgeniy Frenkel ◽  
Andrew J. Majda ◽  
Boualem Khouider
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Tropical Convection ◽  
Convective Parameterization ◽  
Convective Systems ◽  
Squall Lines ◽  
Walker Cell ◽  
Single Column ◽  
Mesoscale Convective ◽  
Coarse Grids

Abstract Despite recent advances in supercomputing, current general circulation models (GCMs) poorly represent the variability associated with organized tropical convection. A stochastic multicloud convective parameterization based on three cloud types (congestus, deep, and stratiform), introduced recently by Khouider, Biello, and Majda in the context of a single column model, is used here to study flows above the equator without rotation effects. The stochastic model dramatically improves the variability of tropical convection compared to the conventional moderate- and coarse-resolution paradigm GCM parameterizations. This increase in variability comes from intermittent coherent structures such as synoptic and mesoscale convective systems, analogs of squall lines and convectively coupled waves seen in nature whose representation is improved by the stochastic parameterization. Furthermore, simulations with a sea surface temperature (SST) gradient yield realistic mean Walker cell circulation with plausible high variability. An additional feature of the present stochastic parameterization is a natural scaling of the model from moderate to coarse grids that preserves the variability and statistical structure of the coherent features. These results systematically illustrate, in a paradigm model, the benefits of using the stochastic multicloud framework to improve deterministic parameterizations with clear deficiencies.

A Comparison of the Water Budgets between Clouds from AMMA and TWP-ICE

2013 ◽  
Vol 70 (2) ◽  
pp. 487-503 ◽  
Author(s):  
Xiping Zeng ◽  
Wei-Kuo Tao ◽  
Scott W. Powell ◽  
Robert A. Houze ◽  
Paul Ciesielski ◽  
...  
Keyword(s):  
General Circulation ◽  
Three Dimensional ◽  
Vertical Wind Shear ◽  
General Circulation Models ◽  
Warm Pool ◽  
Water Budgets ◽  
Convective Systems ◽  
Convective Clouds ◽  
Distinct Structure ◽  
Multidisciplinary Analysis

Abstract Two field campaigns, the African Monsoon Multidisciplinary Analysis (AMMA) and the Tropical Warm Pool–International Cloud Experiment (TWP-ICE), took place in 2006 near Niamey, Niger, and Darwin, Northern Territory, Australia, providing extensive observations of mesoscale convective systems (MCSs) near a desert and a tropical coast, respectively. Under the constraint of their observations, three-dimensional cloud-resolving model simulations are carried out and presented in this paper to replicate the basic characteristics of the observed MCSs. All of the modeled MCSs exhibit a distinct structure having deep convective clouds accompanied by stratiform and anvil clouds. In contrast to the approximately 100-km-scale MCSs observed in TWP-ICE, the MCSs in AMMA have been successfully simulated with a scale of about 400 km. These modeled AMMA and TWP-ICE MCSs offer an opportunity to understand the structure and mechanism of MCSs. Comparing the water budgets between AMMA and TWP-ICE MCSs suggests that TWP-ICE convective clouds have stronger ascent while the mesoscale ascent outside convective clouds in AMMA is stronger. A case comparison, with the aid of sensitivity experiments, also suggests that vertical wind shear and ice crystal (or dust aerosol) concentration can significantly impact stratiform and anvil clouds (e.g., their areas) in MCSs. In addition, the obtained water budgets quantitatively describe the transport of water between convective, stratiform, and anvil regions as well as water sources/sinks from microphysical processes, providing information that can be used to help determine parameters in the convective and cloud parameterizations in general circulation models (GCMs).

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