scholarly journals Precipitation Partitioning in Multiscale Atmospheric Simulations: Impacts of Stability Restoration Methods

2018 ◽  
Vol 123 (18) ◽  
Author(s):  
Jian He ◽  
Kiran Alapaty
2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.


Urban Climate ◽  
2013 ◽  
Vol 6 ◽  
pp. 24-43 ◽  
Author(s):  
Erik Johansson ◽  
Jörg Spangenberg ◽  
Mariana Lino Gouvêa ◽  
Edmilson D. Freitas

2009 ◽  
Vol 137 (7) ◽  
pp. 2164-2174 ◽  
Author(s):  
Masaru Yamamoto ◽  
Naoki Hirose

The present study examines the influence of an assimilation SST product on simulated monthly precipitation. The high-resolution SST structures located close to the oceanic front and coastal areas are important in regional atmospheric simulations over semienclosed marginal seas such as the Japan Sea. Two simulations are conducted using assimilation and interpolation SST products (experiments R and N, respectively), for January 2005. The surface heat fluxes and PBL height in experiment R are lower than those in experiment N in coastal areas and the cold tongue. A decrease of 4 K in SST leads to decreases of 120 W m−2 in surface sensible and latent fluxes and 300 m in PBL height. The precipitation in experiment R is less than that in experiment N for the sea area except at 38°N, 137°E. The cold tongue in the central Japan Sea acts to reduce moisture supply via the latent heat flux, resulting in low precipitation in coastal areas. The fact that the difference between observed and modeled precipitation in experiment R is 21% less than that in experiment N demonstrates that the assimilation of SST data leads to improved regional atmospheric simulations of monthly precipitation.


2015 ◽  
Vol 8 (8) ◽  
pp. 6987-7061
Author(s):  
D. Heinzeller ◽  
M. G. Duda ◽  
H. Kunstmann

Abstract. The Model for Prediction Across Scales (MPAS) is a novel set of earth-system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This makes MPAS a promising tool for conducting climate-related impact studies of, for example, land use changes in a consistent approach. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different High Performance Computing sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African Monsoon and its associated precipitation. Comparing 11 month runs for two meshes with observations and a Weather Research & Forecasting tool (WRF) reference model, we show that MPAS can reproduce the atmospheric dynamics on global and local scales, but that further optimisation is required to address a precipitation excess for this region. Finally, we conduct extreme scaling tests on a global 3 km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70 % parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3 km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.


2016 ◽  
Vol 9 (1) ◽  
pp. 77-110 ◽  
Author(s):  
D. Heinzeller ◽  
M. G. Duda ◽  
H. Kunstmann

Abstract. The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This concept allows one to include the feedback of regional land use information on weather and climate at local and global scales in a consistent way, which is impossible to achieve with traditional limited area modelling approaches. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different high-performance computing (HPC) sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African monsoon (WAM) and its associated precipitation in a pilot study. Constrained by available computational resources, we compare 11-month runs for two meshes with observations and a reference simulation from the Weather Research and Forecasting (WRF) model. We show that MPAS can reproduce the atmospheric dynamics on global and local scales in this experiment, but identify a precipitation excess for the West African region. Finally, we conduct extreme scaling tests on a global 3 km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70 % parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3 km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.


2009 ◽  
Vol 22 (14) ◽  
pp. 3993-4013 ◽  
Author(s):  
Guillaume Gastineau ◽  
Laurent Li ◽  
Hervé Le Treut

Abstract Sea surface temperature (SST) changes constitute a major indicator and driver of climate changes induced by greenhouse gas increases. The objective of the present study is to investigate the role played by the detailed structure of the SST change on the large-scale atmospheric circulation and the distribution of precipitation. For that purpose, simulations from the Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4) are used where the carbon dioxide (CO2) concentration is doubled. The response of IPSL-CM4 is characterized by the same robust mechanisms affecting the other coupled models in global warming simulations, that is, an increase of the hydrological cycle accompanied by a global weakening of the large-scale circulation. First, purely atmospheric simulations are performed to mimic the results of the coupled model. Then, specific simulations are set up to further study the underlying atmospheric mechanisms. These simulations use different prescribed SST anomalies, which correspond to a linear decomposition of the IPSL-CM4 SST changes in global, longitudinal, and latitudinal components. The simulation using a globally uniform increase of the SST is able to reproduce the modifications in the intensity of the hydrological cycle or in the mean upward mass flux, which also characterize the double CO2 simulation with the coupled model. But it is necessary (and largely sufficient) to also take into account the zonal-mean meridional structure of the SST changes to represent correctly the changes in the Hadley circulation strength or the zonal-mean precipitation changes simulated by the coupled model, even if these meridional changes by themselves do not change the mean thermodynamical state of the tropical atmosphere. The longitudinal SST anomalies of IPSL-CM4 also have an impact on the precipitation and large-scale tropical circulation and tend to introduce different changes over the Pacific and Atlantic Oceans. The longitudinal SST changes are demonstrated to have a smaller but opposite effect from that of the meridional anomalies on the Hadley cell circulations. Results indicate that the uncertainties in the simulated meridional patterns of the SST warming may have major consequences on the assessment of the changes of the Hadley circulation and zonal-mean precipitation in future climate projections.


2015 ◽  
Vol 16 (4) ◽  
pp. 367-391 ◽  
Author(s):  
Vadym Aizinger ◽  
Peter Korn ◽  
Marco Giorgetta ◽  
Sebastian Reich

2008 ◽  
Vol 112 (3) ◽  
pp. 720-734 ◽  
Author(s):  
Souhail Boussetta ◽  
Toshio Koike ◽  
Kun Yang ◽  
Tobias Graf ◽  
Mahadevan Pathmathevan

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