Global aerosol simulations using NICAM.16 on a 14-km grid spacing for a climate study: Improved and remaining issues relative to a lower-resolution model

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.

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Global aerosol simulations using NICAM.16 on a 14 km grid spacing for a climate study: improved and remaining issues relative to a lower-resolution model

Geoscientific Model Development ◽

10.5194/gmd-13-3731-2020 ◽

2020 ◽

Vol 13 (8) ◽

pp. 3731-3768

Author(s):

Daisuke Goto ◽

Yousuke Sato ◽

Hisashi Yashiro ◽

Kentaroh Suzuki ◽

Eiji Oikawa ◽

...

Keyword(s):

Interannual Variability ◽

Black Carbon ◽

Optical Thickness ◽

Wet Deposition ◽

Global Scale ◽

Horizontal Resolution ◽

The Arctic ◽

Grid Spacing ◽

The Difference ◽

Horizontal Grid

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.

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Simulation of the Summer Monsoon Rainfall over East Asia Using the NCEP GFS Cumulus Parameterization at Different Horizontal Resolutions

Weather and Forecasting ◽

10.1175/waf-d-13-00143.1 ◽

2014 ◽

Vol 29 (5) ◽

pp. 1143-1154 ◽

Cited By ~ 25

Author(s):

Kyo-Sun Sunny Lim ◽

Song-You Hong ◽

Jin-Ho Yoon ◽

Jongil Han

Keyword(s):

Summer Monsoon ◽

Monsoon Rainfall ◽

Asian Summer Monsoon ◽

Monsoon Season ◽

Wrf Model ◽

Horizontal Resolution ◽

Cumulus Parameterization ◽

Grid Spacing ◽

Simulated Precipitation ◽

Horizontal Grid

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.

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Sensitivity of Fine-Scale Structure in Tropical Cyclone Boundary Layer to Model Horizontal Resolution at Sub-Kilometer Grid Spacing

Frontiers in Earth Science ◽

10.3389/feart.2021.707274 ◽

2021 ◽

Vol 9 ◽

Author(s):

Hongxiong Xu ◽

Yuqing Wang

Keyword(s):

Boundary Layer ◽

Tropical Cyclone ◽

Inner Core ◽

Mesoscale Model ◽

Horizontal Resolution ◽

Scale Structure ◽

Fine Scale ◽

Grid Spacing ◽

Large Eddies ◽

Horizontal Grid

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.

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European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

Geoscientific Model Development ◽

10.5194/gmd-13-5485-2020 ◽

2020 ◽

Vol 13 (11) ◽

pp. 5485-5506

Author(s):

Marie-Estelle Demory ◽

Ségolène Berthou ◽

Jesús Fernández ◽

Silje L. Sørland ◽

Roman Brogli ◽

...

Keyword(s):

High Resolution ◽

Climate Models ◽

Daily Precipitation ◽

Global Climate ◽

Regional Climate ◽

Global Climate Models ◽

Model Intercomparison ◽

Grid Spacing ◽

Intercomparison Project ◽

Horizontal Grid

Abstract. In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.

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Aerosols at the Poles: An AeroCom Phase II multi-model evaluation

10.5194/acp-2016-1120 ◽

2017 ◽

Cited By ~ 1

Author(s):

Maria Sand ◽

Bjørn H. Samset ◽

Yves Balkanski ◽

Susanne Bauer ◽

Nicolas Bellouin ◽

...

Keyword(s):

Phase Ii ◽

Biomass Burning ◽

Radiative Forcing ◽

Fossil Fuel ◽

Organic Aerosols ◽

Global Climate Models ◽

Sea Salt ◽

The Arctic ◽

Anthropogenic Aerosols ◽

The Antarctic

Abstract. Atmospheric aerosols from anthropogenic and natural sources reach the Polar Regions through long-range transport. Such transport is however poorly constrained in present day global climate models, and few multi-model evaluations of Polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550 nm from simulations with 16 global aerosol models from the AeroCom phase II model inter-comparison project with available observations at both Poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the inter-model spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species; black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OA), dust and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOA), we document the role of these aerosols at high latitudes. The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in the winter (sea-salt) and spring (dust), whereas AOD from anthropogenic aerosols peaks during late spring/summer. The models produce a median annual mean (AOD) of 0.07 in the Arctic (defined here as north of 60° N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70° S) with a resulting AOD varying between 0.01–0.02. The models have also estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOA, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modeled annual mean DAE is slightly negative (−0.12 W m−2), dominated by a positive BC FF DAE during spring and a negative sulfate DAE during summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in East Asia, result in a 33 % increase in Arctic AOD of BC. However, radical changes such as reducing the e-folding lifetime by half or doubling it, still fall within the AeroCom model range.

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European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

10.5194/egusphere-egu21-14363 ◽

2021 ◽

Author(s):

Marie-Estelle Demory ◽

Ségolène Berthou ◽

Keyword(s):

High Resolution ◽

Climate Models ◽

Daily Precipitation ◽

Global Climate ◽

Regional Climate ◽

Global Climate Models ◽

Model Intercomparison ◽

Grid Spacing ◽

Intercomparison Project ◽

Horizontal Grid

In this study, we evaluate a set of high-resolution (25&#8211;50&#8201;km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12&#8211;50&#8201;km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50&#8201;km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events.The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12&#8201;km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50&#8201;km scale.

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A multi-resolution assessment of the Community Multiscale Air Quality (CMAQ) Model v4.7 wet deposition estimates for 2002–2006

Geoscientific Model Development Discussions ◽

10.5194/gmdd-3-2315-2010 ◽

2010 ◽

Vol 3 (4) ◽

pp. 2315-2360 ◽

Cited By ~ 6

Author(s):

K. W. Appel ◽

K. M. Foley ◽

J. O. Bash ◽

R. W. Pinder ◽

R. L. Dennis ◽

...

Keyword(s):

Air Quality ◽

Wet Deposition ◽

Model Performance ◽

Grid Spacing ◽

Model Simulations ◽

Western Us ◽

Primary Focus ◽

National Trends ◽

Horizontal Grid ◽

No Emissions

Abstract. This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002–2006 using both 36-km and 12-km horizontal grid spacing with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (SO4=), ammonium (NH4+) and nitrate (NO3−). Performance of the wet deposition species is determined by comparing CMAQ predicted concentrations to concentrations measured by the National Acid Deposition Program (NADP), specifically the National Trends Network (NTN). For SO4= wet deposition, the CMAQ model estimates were generally comparable between the 36-km and 12-km simulations for the eastern US, with the 12-km simulation giving slightly higher estimates of SO4= wet deposition than the 36-km simulation on average. The normalized mean bias (NMB) was slightly higher for the 12-km simulation, however, both simulations had annual biases that were less than ±15% for each of the five years. The model estimated SO4= wet deposition values improved when they were adjusted to account for biases in the model estimated precipitation. The CMAQ model underestimates NH4+ wet deposition over the eastern US using both the 36-km and 12-km horizontal grid spacing, with a slightly larger underestimation in the 36-km simulation. The largest underestimations occur during the winter and spring periods, while the summer and fall have slightly smaller underestimations of NH4+ wet deposition. Annually, the NMB generally ranges between −10% and −16% for the 12-km simulation and −12% to −18% for the 36-km simulation over the five-year period for the eastern US. The underestimation in NH4+ wet deposition is likely due, in part, to the poor temporal and spatial representation of ammonia (NH3) emissions, particularly those emissions associated with fertilizer applications and NH3 bi-directional exchange. The model performance for estimates of NO3− wet deposition are mixed throughout the year, with the model largely underestimating NO3− wet deposition in the spring and summer in the eastern US, while the model has a relatively small bias in the fall and winter. Model estimates of NO3− wet deposition tend to be slightly lower for the 36-km simulation as compared to the 12-km simulation, particularly in the spring. Annually for the eastern US, the NMB ranges from roughly −12% to −20% for the 12-km simulation and −18% to −26% for the 36-km simulation. The underestimation of NO3− wet deposition in the spring and summer is due, in part, to a lack of lightning generated NO emissions in the upper troposphere, which can be a large source of NO in the spring and summer when lightning activity is the high. CMAQ model simulations that include the production of NO from lightning show a significant improvement in the NO3− wet deposition estimates in the eastern US in the summer. Model performance for the western US was generally not as good as that for the eastern US for all three wet deposition species.

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Sensitivity of Simulated Tropical Cyclone Structure and Intensity to Horizontal Resolution

Monthly Weather Review ◽

10.1175/2009mwr2976.1 ◽

2010 ◽

Vol 138 (3) ◽

pp. 688-704 ◽

Cited By ~ 132

Author(s):

Megan S. Gentry ◽

Gary M. Lackmann

Keyword(s):

Tropical Cyclone ◽

Wrf Model ◽

Domain Size ◽

Horizontal Resolution ◽

Weather Research And Forecasting ◽

Grid Spacing ◽

Physical Processes ◽

Hurricane Ivan ◽

Horizontal Grid ◽

Grid Length

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.

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

10.5194/egusphere-egu21-15452 ◽

2021 ◽

Author(s):

Yohei Yamada ◽

Chihiro Kodama ◽

Akira Noda ◽

Masaki Satoh ◽

Masuo Nakano ◽

...

Keyword(s):

Atmospheric Model ◽

Global Precipitation Climatology Project ◽

Horizontal Resolution ◽

Global Model ◽

South Pacific Convergence Zone ◽

Climate Simulation ◽

Grid Spacing ◽

Test Feasibility ◽

One Year ◽

Horizontal Grid

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-1), 7 km and 3.5 km simulations underestimated the global mean precipitation (2.54 mm day-1 and 2.67 mm day-1), while 14 km and 28 km simulations overestimated (2.84 mm day-1 and 2.78 mm day-1). 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.

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Next-Day Convection-Allowing WRF Model Guidance: A Second Look at 2-km versus 4-km Grid Spacing

Monthly Weather Review ◽

10.1175/2009mwr2924.1 ◽

2009 ◽

Vol 137 (10) ◽

pp. 3351-3372 ◽

Cited By ~ 156

Author(s):

Craig S. Schwartz ◽

John S. Kain ◽

Steven J. Weiss ◽

Ming Xue ◽

David R. Bright ◽

...

Keyword(s):

Wrf Model ◽

Heavy Rain ◽

The United States ◽

Skill Score ◽

Horizontal Resolution ◽

Substantial Improvement ◽

Added Value ◽

Grid Spacing ◽

Similar Work ◽

Horizontal Grid

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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