Evaluating performances of one-year simulation by using 3.5 km mesh global nonhydrostatic model

Author(s):  
Yohei Yamada ◽  
Chihiro Kodama ◽  
Akira Noda ◽  
Masaki Satoh ◽  
Masuo Nakano ◽  
...  

<p>Recent advancement of supercomputing enables us to conduct a climate simulation by using a global model with horizontal grid spacing of a few kilometers. We may need to tune the model in order to conduct a reliable simulation. In order to test feasibility of a few kilometer climate simulation in near future, we conducted one-year simulation from June 2004 to May 2005 by using Nonhydrostatic Icosahedral Atmospheric Model (NICAM) with horizontal grid spacing of 28 km, 14 km, 7 km, and 3.5 km, and evaluated their simulation performances. In general, global models have shown weak wind speed of tropical cyclones compared to its central sea level pressure due to insufficient horizontal resolution. As expected, the 3.5 km simulation showed improvement of this bias. As for simulated mean state, globally annual mean precipitation tended to be decreased with finer horizontal resolution in NICAM. Compared with observation (Global Precipitation Climatology Project V2.2; 2.71 mm day<sup>-1</sup>), 7 km and 3.5 km simulations underestimated the global mean precipitation (2.54 mm day<sup>-1</sup> and 2.67 mm day<sup>-1</sup>), while 14 km and 28 km simulations overestimated (2.84 mm day<sup>-1</sup> and 2.78 mm day<sup>-1</sup>). The 3.5 km simulation showed the best performance for reproducing globally annual mean precipitation. However, the 3.5 simulation showed underestimation of the South Pacific Convergence Zone. In order to conduct a reliable simulation, we need to improve performance of the 3.5 km global model. This demands extensive computing resources. The supercomputer Fugaku will give us extensive computing resources for addressing this issue.</p>

2014 ◽  
Vol 29 (5) ◽  
pp. 1143-1154 ◽  
Author(s):  
Kyo-Sun Sunny Lim ◽  
Song-You Hong ◽  
Jin-Ho Yoon ◽  
Jongil Han

Abstract The most recent version of the simplified Arakawa–Schubert (SAS) cumulus scheme in the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) (GFS SAS) is implemented in the Weather Research and Forecasting (WRF) Model with a modification of the triggering condition and the convective mass flux in order to make it dependent on the model’s horizontal grid spacing. The East Asian summer monsoon season of 2006 is selected in order to evaluate the performance of the modified GFS SAS scheme. In comparison to the original GFS SAS scheme, the modified GFS SAS scheme shows overall better agreement with the observations in terms of the simulated monsoon rainfall. The simulated precipitation from the original GFS SAS scheme is insensitive to the model’s horizontal grid spacing, which is counterintuitive because the portion of the resolved clouds in a grid box should increase as the model grid spacing decreases. This behavior of the original GFS SAS scheme is alleviated by the modified GFS SAS scheme. In addition, three different cumulus schemes (Grell and Freitas, Kain and Fritsch, and Betts–Miller–Janjić) are chosen to investigate the role of a horizontal resolution on the simulated monsoon rainfall. Although the forecast skill of the surface rainfall does not always improve as the spatial resolution increases, the improvement of the probability density function of the rain rate with the smaller grid spacing is robust regardless of the cumulus parameterization scheme.


2021 ◽  
Vol 9 ◽  
Author(s):  
Hongxiong Xu ◽  
Yuqing Wang

In view of the increasing interest in the explicit simulation of fine-scale features in the tropical cyclone (TC) boundary layer (TCBL), the effects of horizontal grid spacing on a 7–10 h simulation of an idealized TC are examined using the Weather Research and Forecast (ARW-WRF) mesoscale model with one-way moving nests and the nonlinear backscatter with anisotropy (NBA) sub-grid-scale (SGS) scheme. In general, reducing the horizontal grid spacing from 2 km to 500 m tends to produce a stronger TC with lower minimum sea level pressure (MSLP), stronger surface winds, and smaller TC inner core size. However, large eddies cannot be resolved at these grid spacings. In contrast, reducing the horizontal grid spacing from 500 to 166 m and further to 55 m leads to a decrease in TC intensity and an increase in the inner-core TC size. Moreover, although the 166-m grid spacing starts to resolve large eddies in terms of TCBL horizontal rolls and tornado-scale vortex, the use of the finest grid spacing of 55 m tends to produce shorter wavelengths in the turbulent motion and stronger multi-scale turbulence interaction. It is concluded that a grid spacing of sub-100-meters is desirable to produce more detailed and fine-scale structure of TCBL horizontal rolls and tornado-scale vortices, while the relatively coarse sub-kilometer grid spacing (e.g., 500 m) is more cost-effective and feasible for research that is not interested in the turbulence processes and for real-time operational TC forecasting in the near future.


2021 ◽  
Author(s):  
Ehud Strobach ◽  
Andrea Molod ◽  
Atanas Trayanov ◽  
William Putman ◽  
Dimitris Menemenlis ◽  
...  

<p>During the past few years, the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology general circulation model (MITgcm) groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these simulations is the lack of feedback between the ocean and the atmosphere, limiting their usefulness for studying air-sea interactions and designing observing missions to study these interactions. To remove this limitation, we have coupled the km-scale GEOS atmospheric model with the km-scale MITgcm ocean model. We will present preliminary results from the GEOS-MITgcm contribution to the second phase of the DYAMOND (DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains) initiative.</p><p>The coupled atmosphere-ocean simulation was integrated using a cubed-sphere-1440 (~6-7 km horizontal grid spacing) configuration of GEOS and a lat-lon-cap-2160 (2–5-km horizontal grid spacing) configuration of MITgcm. We will show results from a preliminary analysis of air-sea interactions between Sea Surface Temperature (SST) and surface winds. In particular, we will discuss non-local atmospheric overturning circulation formed above the Gulf Stream SST front with characteristic sub-mesoscale width. This formation of a secondary circulation above the front suggests that capturing such air-sea interaction phenomena requires high-resolution capabilities in both the models' oceanic and atmospheric components.</p>


2018 ◽  
Vol 31 (9) ◽  
pp. 3485-3508 ◽  
Author(s):  
Rachel A. Stratton ◽  
Catherine A. Senior ◽  
Simon B. Vosper ◽  
Sonja S. Folwell ◽  
Ian A. Boutle ◽  
...  

Abstract A convection-permitting multiyear regional climate simulation using the Met Office Unified Model has been run for the first time on an Africa-wide domain. The model has been run as part of the Future Climate for Africa (FCFA) Improving Model Processes for African Climate (IMPALA) project, and its configuration, domain, and forcing data are described here in detail. The model [Pan-African Convection-Permitting Regional Climate Simulation with the Met Office UM (CP4-Africa)] uses a 4.5-km horizontal grid spacing at the equator and is run without a convection parameterization, nested within a global atmospheric model driven by observations at the sea surface, which does include a convection scheme. An additional regional simulation, with identical resolution and physical parameterizations to the global model, but with the domain, land surface, and aerosol climatologies of CP4-Africa, has been run to aid in the understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parameterization and resolution. The effect of enforcing moisture conservation in CP4-Africa is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first five years of the CP4-Africa simulation show substantial improvements in JJA average rainfall compared to the parameterized convection models, with most notably a reduction in the persistent dry bias in West Africa, giving an indication of the benefits to be gained from running a convection-permitting simulation over the whole African continent.


2007 ◽  
Vol 46 (11) ◽  
pp. 1967-1980 ◽  
Author(s):  
Jason E. Nachamkin ◽  
John Cook ◽  
Mike Frost ◽  
Daniel Martinez ◽  
Gary Sprung

Abstract Lagrangian parcel models are often used to predict the fate of airborne hazardous material releases. The atmospheric input for these integrations is typically supplied by surrounding surface and upper-air observations. However, situations may arise in which observations are unavailable and numerical model forecasts may be the only source of atmospheric data. In this study, the quality of the atmospheric forecasts for use in dispersion applications is investigated as a function of the horizontal grid spacing of the atmospheric model. The Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) was used to generate atmospheric forecasts for 14 separate Dipole Pride 26 trials. The simulations consisted of four telescoping one-way nested grids with horizontal spacings of 27, 9, 3, and 1 km, respectively. The 27- and 1-km forecasts were then used as input for dispersion forecasts using the Hazard Prediction Assessment Capability (HPAC) modeling system. The resulting atmospheric and dispersion forecasts were then compared with meteorological and gas-dosage observations collected during Dipole Pride 26. Although the 1-km COAMPS forecasts displayed considerably more detail than those on the 27-km grid, the RMS and bias statistics associated with the atmospheric observations were similar. However, statistics from the HPAC forecasts showed the 1-km atmospheric forcing produced more accurate trajectories than the 27-km output when compared with the dosage measurements.


2010 ◽  
Vol 138 (3) ◽  
pp. 688-704 ◽  
Author(s):  
Megan S. Gentry ◽  
Gary M. Lackmann

Abstract The Weather Research and Forecasting (WRF) model is used to test the sensitivity of simulations of Hurricane Ivan (2004) to changes in horizontal grid spacing for grid lengths from 8 to 1 km. As resolution is increased, minimum central pressure decreases significantly (by 30 hPa from 8- to 1-km grid spacing), although this increase in intensity is not uniform across similar reductions in grid spacing, even when pressure fields are interpolated to a common grid. This implies that the additional strengthening of the simulated tropical cyclone (TC) at higher resolution is not attributable to sampling, but is due to changes in the representation of physical processes important to TC intensity. The most apparent changes in simulated TC structure with resolution occur near a grid length of 4 km. At 4-km grid spacing and below, polygonal eyewall segments appear, suggestive of breaking vortex Rossby waves. With sub-4-km grid lengths, localized, intense updraft cores within the eyewall are numerous and both polygonal and circular eyewall shapes appear regularly. Higher-resolution simulations produce a greater variety of shapes, transitioning more frequently between polygonal and circular eyewalls relative to lower-resolution simulations. It is hypothesized that this is because of the ability to resolve a greater range of wavenumbers in high-resolution simulations. Also, as resolution is increased, a broader range of updraft and downdraft velocities is present in the eyewall. These results suggest that grid spacing of 2 km or less is needed for representation of important physical processes in the TC eyewall. Grid-length and domain size suggestions for operational prediction are provided; for operational prediction, a grid length of 3 km or less is recommended.


2020 ◽  
Author(s):  
Daisuke Goto ◽  
Yousuke Sato ◽  
Hisashi Yashiro ◽  
Kentaroh Suzuki ◽  
Eiji Oikawa ◽  
...  

Abstract. High-performance computing resources allow us to conduct numerical simulations with a horizontal grid spacing that is sufficiently high to resolve cloud systems on a global scale, and high-resolution models (HRMs) generally provide better simulation performances than low-resolution models (LRMs). In this study, we execute a next-generation model that is capable of simulating global aerosols on a nonhydrostatic icosahedral atmospheric model version 16 (NICAM.16). The simulated aerosol distributions are obtained for 3 years with a HRM in a global 14-km grid spacing, an unprecedentedly high horizontal resolution and long integration period. For comparison, a NICAM with a 56-km grid spacing is also run as an LRM, although this horizontal resolution is still high among current global climate models. The comparison elucidated that the differences in the various variables of meteorological fields, including the wind speed, precipitation, clouds, radiation fluxes and total aerosols, are generally within 10 % of their annual averages, but most of the variables related to aerosols simulated by the HRM are slightly closer to the observations than are those simulated by the LRM. Upon investigating the aerosol components, the differences in the water-insoluble black carbon (WIBC) and sulfate concentrations between the HRM and LRM are large (up to 32 %), even in the annual averages. This finding is attributed to the differences in the column burden of the aerosol wet deposition, which is determined by a conversion rate of precipitation to cloud and the difference between the HRM and LRM is approximately 20 %. Additionally, the differences in the simulated aerosol concentrations at polluted sites during polluted months between the HRM and LRM are estimated with medians of −23 % (−63 % to −2.5 %) for BC, −4 % (−91 % to +18 %) for sulfate and −1 % (−49 % to +223 %) for the aerosol optical thickness (AOT). These findings indicate that the differences in the secondary and tertiary products, such as the AOT, between the different horizontal grid spacings are not explained simply by the grid size. On a global scale, the subgrid variabilities in the simulated AOT and COT in the 1°×1° domain using 6-hourly data are estimated to be 28.5 % and 80.0 %, respectively, in the HRM, whereas the corresponding differences are 16.6 % and 22.9 % in the LRM. Over the Arctic, both the HRM and the LRM generally reproduce the observed aerosols, but the largest difference in the surface BC mass concentrations between the HRM and LRM reaches 30 % in spring (the HRM-simulated results are closer to the observations). The vertical distributions of the HRM- and LRM-simulated aerosols are generally close to the measurements, but the differences between the HRM and LRM results are large above a height of approximately 3 km, mainly due to differences in the wet deposition of the aerosols. The global annual averages of the direct and indirect aerosol radiative forcings (ARFs) attributed to anthropogenic aerosols in the HRM are estimated to be −0.29 Wm−2 and −0.93 Wm−2, respectively, whereas those in the LRM are −0.24 Wm−2 and −1.10 Wm−2. The differences in the direct ARF between the HRM and LRM are primarily caused by those in the aerosol burden, whereas the differences in the indirect ARF are primarily caused by those in the cloud expression and performance, which are attributed to the grid spacing. Because one-tenth of the computer resources are required for the LRM (56-km grid) compared to the HRM (14-km grid), we recommend that the various tuning parameters associated with the aerosol distributions using the LRM can be applicable to those using the HRM under the limitation of the available computational resources or before the HRM integration.


2020 ◽  
Vol 13 (8) ◽  
pp. 3731-3768
Author(s):  
Daisuke Goto ◽  
Yousuke Sato ◽  
Hisashi Yashiro ◽  
Kentaroh Suzuki ◽  
Eiji Oikawa ◽  
...  

Abstract. High-performance computing resources allow us to conduct numerical simulations with a horizontal grid spacing that is sufficiently high to resolve cloud systems on a global scale, and high-resolution models (HRMs) generally provide better simulation performance than low-resolution models (LRMs). In this study, we execute a next-generation model that is capable of simulating global aerosols using version 16 of the Nonhydrostatic Icosahedral Atmospheric Model (NICAM.16). The simulated aerosol distributions are obtained for 3 years with an HRM using a global 14 km grid spacing, an unprecedentedly high horizontal resolution and long integration period. For comparison, a NICAM with a 56 km grid spacing is also run as an LRM, although this horizontal resolution is still high among current global aerosol climate models. The comparison elucidated that the differences in the various variables of meteorological fields, including the wind speed, precipitation, clouds, radiation fluxes and total aerosols, are generally within 10 % of their annual averages, but most of the variables related to aerosols simulated by the HRM are slightly closer to the observations than are those simulated by the LRM. Upon investigating the aerosol components, the differences in the water-insoluble black carbon and sulfate concentrations between the HRM and LRM are large (up to 32 %), even in the annual averages. This finding is attributed to the differences in the aerosol wet deposition flux, which is determined by the conversion rate of cloud to precipitation, and the difference between the HRM and LRM is approximately 20 %. Additionally, the differences in the simulated aerosol concentrations at polluted sites during polluted months between the HRM and LRM are estimated with normalized mean biases of −19 % for black carbon (BC), −5 % for sulfate and −3 % for the aerosol optical thickness (AOT). These findings indicate that the impacts of higher horizontal grid spacings on model performance for secondary products such as sulfate, and complex products such as the AOT, are weaker than those for primary products, such as BC. On a global scale, the subgrid variabilities in the simulated AOT and cloud optical thickness (COT) in the 1∘×1∘ domain using 6-hourly data are estimated to be 28.5 % and 80.0 %, respectively, in the HRM, whereas the corresponding differences are 16.6 % and 22.9 % in the LRM. Over the Arctic, both the HRM and the LRM generally reproduce the observed aerosols, but the largest difference in the surface BC mass concentrations between the HRM and LRM reaches 30 % in spring (the HRM-simulated results are closer to the observations). The vertical distributions of the HRM- and LRM-simulated aerosols are generally close to the measurements, but the differences between the HRM and LRM results are large above a height of approximately 3 km, mainly due to differences in the wet deposition of aerosols. The global annual averages of the effective radiative forcings due to aerosol–radiation and aerosol–cloud interactions (ERFari and ERFaci) attributed to anthropogenic aerosols in the HRM are estimated to be -0.293±0.001 and -0.919±0.004 W m−2, respectively, whereas those in the LRM are -0.239±0.002 and -1.101±0.013 W m−2. The differences in the ERFari between the HRM and LRM are primarily caused by those in the aerosol burden, whereas the differences in the ERFaci are primarily caused by those in the cloud expression and performance, which are attributed to the grid spacing. The analysis of interannual variability revealed that the difference in reproducibility of both sulfate and carbonaceous aerosols at different horizontal resolution is greater than their interannual variability over 3 years, but those of dust and sea salt AOT and possibly clouds were the opposite. Because at least 10 times the computer resources are required for the HRM (14 km grid) compared to the LRM (56 km grid), these findings in this study help modelers decide whether the objectives can be achieved using such higher resolution or not under the limitation of available computational resources.


2021 ◽  
Author(s):  
Hiroaki Naoe ◽  
Shinya Kobayashi ◽  
Yuki Kosaka ◽  
Jotaro Chiba ◽  
Takayuki Tokuhiro ◽  
...  

<p>This study evaluates the latest Japanese Reanalysis for Three Quarters of a Century (JRA-3Q) conducted by the Japan Meteorological Agency (JMA), focusing on a semi-period of pre-satellite era (1960s and 1970s). The reanalysis is the third Japanese global atmospheric reanalysis covering the period from late 1940s onward, which is produced with the JMA's operational system as of December 2018. The atmospheric model has a TL479 horizontal resolution and 100 vertical layers up to 0.01 hPa, and the core component of the JRA-3Q data assimilation system is the 6-hourly 4D-Var of the atmospheric state with a T319-resolution inner model. Because there are only few global-covered observational datasets during the pre-satellite era, evaluation of the JRA-3Q is mainly to conduct an intercomparison of other reanalysis datasets such as representation Japanese 55-year Reanalysis (JRA-55), a JRA-55's subset of atmospheric reanalysis assimilating conventional observations only (JRA-55C), and version 3 of the Twentieth Century Reanalysis (20CRv3), and also an intercomparison of JRA-3Q between the pre-satellite and satellite eras. Emphasis of this evaluation during the non-satellite era is placed on the representation of tropical circulation, the consistency in time of the reanalysed fields, detection of tropical cyclones, and the quality of the stratospheric water vapor and ozone. For example, the surface circulation over the tropical Africa is improved by means of reducing spurious anticyclonic circulation anomalies that were found in JRA-55. Although the atmospheric model can produce self-generated quasi-biennial oscillation (QBO) by introducing non-orographic gravity wave drag, the evaluation reveals that JRA-3Q has a shorter period of around one year in the middle stratosphere and diminished QBO amplitude in the lower stratosphere, indicating that representation of the QBO in JRA-3Q is not as good as that in JRA-55.</p>


2009 ◽  
Vol 137 (10) ◽  
pp. 3351-3372 ◽  
Author(s):  
Craig S. Schwartz ◽  
John S. Kain ◽  
Steven J. Weiss ◽  
Ming Xue ◽  
David R. Bright ◽  
...  

Abstract During the 2007 NOAA Hazardous Weather Testbed (HWT) Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced convection-allowing forecasts from a single deterministic 2-km model and a 10-member 4-km-resolution ensemble. In this study, the 2-km deterministic output was compared with forecasts from the 4-km ensemble control member. Other than the difference in horizontal resolution, the two sets of forecasts featured identical Advanced Research Weather Research and Forecasting model (ARW-WRF) configurations, including vertical resolution, forecast domain, initial and lateral boundary conditions, and physical parameterizations. Therefore, forecast disparities were attributed solely to differences in horizontal grid spacing. This study is a follow-up to similar work that was based on results from the 2005 Spring Experiment. Unlike the 2005 experiment, however, model configurations were more rigorously controlled in the present study, providing a more robust dataset and a cleaner isolation of the dependence on horizontal resolution. Additionally, in this study, the 2- and 4-km outputs were compared with 12-km forecasts from the North American Mesoscale (NAM) model. Model forecasts were analyzed using objective verification of mean hourly precipitation and visual comparison of individual events, primarily during the 21- to 33-h forecast period to examine the utility of the models as next-day guidance. On average, both the 2- and 4-km model forecasts showed substantial improvement over the 12-km NAM. However, although the 2-km forecasts produced more-detailed structures on the smallest resolvable scales, the patterns of convective initiation, evolution, and organization were remarkably similar to the 4-km output. Moreover, on average, metrics such as equitable threat score, frequency bias, and fractions skill score revealed no statistical improvement of the 2-km forecasts compared to the 4-km forecasts. These results, based on the 2007 dataset, corroborate previous findings, suggesting that decreasing horizontal grid spacing from 4 to 2 km provides little added value as next-day guidance for severe convective storm and heavy rain forecasters in the United States.


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