scholarly journals The Meteorological Global Model GLOBO at the ISAC-CNR of Italy Assessment of 1.5 Yr of Experimental Use for Medium-Range Weather Forecasts

2011 ◽  
Vol 26 (6) ◽  
pp. 1045-1055 ◽  
Author(s):  
Piero Malguzzi ◽  
Andrea Buzzi ◽  
Oxana Drofa
Keyword(s):  
General Circulation ◽  
Initial Conditions ◽  
Circulation Model ◽  
Daily Basis ◽  
Horizontal Resolution ◽  
Limited Area ◽  
National Council ◽  
Meteorological Model ◽  
Medium Range ◽  
Mean Square Errors

Abstract Since August 2009, the GLOBO atmospheric general circulation model has been running experimentally at the Institute of Atmospheric Sciences and Climate (ISAC) of the National Council of Research of Italy. GLOBO is derived from the Bologna Limited Area Model (BOLAM), a gridpoint limited-area meteorological model that was developed at the same institute and that has been extended to the entire earth atmosphere. The main dynamical features and physical parameterizations of GLOBO are presented. Starting from initial conditions obtained from the analysis of the NCEP Global Forecast System (GFS) model valid at 0000 UTC, 6-day forecasts with average horizontal resolution of 32 km were performed on a daily basis and in real time. The assessment of the forecast skill during the 1.5-yr period included the calculation of the monthly averaged root-mean-square errors (model prediction versus gridded analyses) of geopotential height at 500 hPa and mean sea level pressure for the northern and southern extratropics, performed accordingly to WMO Commission for Basic Systems (CBS) standards. The verification results are compared with models from other global data processing and forecasting system centers, as are available in the literature. The GLOBO skill for medium-range forecasts turns out to be comparable to that of the above models. The lack of analyses based on model forecasts and data assimilation is likely to penalize the scores for shorter-term forecasts.

scholarly journals Simulation of winter and summer climates with PRL Atmospheric General Circulation Model

MAUSAM ◽  
2021 ◽  
Vol 50 (4) ◽  
pp. 391-400
Author(s):  
BIJU THOMAS ◽  
S.V. KASTURE ◽  
S. V. SATYAN
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Large Scale ◽  
Atmospheric General Circulation Model ◽  
Initial Conditions ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Hemispheric Differences ◽  
Physical Research Laboratory ◽  
Atmospheric General Circulation

A global, spectral Atmospheric General Circulation Model (AGCM) has been developed indigenously at Physical Research Laboratory (PRL) for climate studies. The model has six a levels in the vertical and has horizontal resolution of 21 waves with rhomboidal truncation. The model includes smooth topography, planetary boundary layer, deep convection, large scale condensation, interactive hydrology, radiation with interactive clouds and diurnal cycle. Sea surface temperature and sea ice values were fixed based on climatological data for different calender months.   The model was integrated for six years starting with an isothermal atmosphere (2400K), zero winds initial conditions and forcing from incoming solar radiation. After one year the model stabilizes. The seasonal averages of various fields of the last five years are discussed in this paper. It is found that the model reproduces reasonably well the seasonal features of atmospheric circulation, seasonal variability and hemispheric differences.

scholarly journals Sensitivity of Simulated Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere Model

2006 ◽  
Vol 19 (16) ◽  
pp. 3771-3791 ◽  
Author(s):  
E. Roeckner ◽  
R. Brokopf ◽  
M. Esch ◽  
M. Giorgetta ◽  
S. Hagemann ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Boreal Winter ◽  
Cold Bias ◽  
Vertical Resolution ◽  
Max Planck ◽  
Mean Climate ◽  
The Impact ◽  
Mean Square Errors

Abstract The most recent version of the Max Planck Institute for Meteorology atmospheric general circulation model, ECHAM5, is used to study the impact of changes in horizontal and vertical resolution on seasonal mean climate. In a series of Atmospheric Model Intercomparison Project (AMIP)-style experiments with resolutions ranging between T21L19 and T159L31, the systematic errors and convergence properties are assessed for two vertical resolutions. At low vertical resolution (L19) there is no evidence for convergence to a more realistic climate state for horizontal resolutions higher than T42. At higher vertical resolution (L31), on the other hand, the root-mean-square errors decrease monotonically with increasing horizontal resolution. Furthermore, except for T42, the L31 versions are superior to their L19 counterparts, and the improvements become more evident at increasingly higher horizontal resolutions. This applies, in particular, to the zonal mean climate state and to the stationary wave patterns in boreal winter. As in previous studies, increasing horizontal resolution leads to a warming of the troposphere, most prominently at midlatitudes, and to a poleward shift and intensification of the midlatitude westerlies. Increasing the vertical resolution has the opposite effect, almost independent of horizontal resolution. Whereas the atmosphere is colder at low and middle latitudes, it is warmer at high latitudes and close to the surface. In addition, increased vertical resolution results in a pronounced warming in the polar upper troposphere and lower stratosphere, where the cold bias is reduced by up to 50% compared to L19 simulations. Consistent with these temperature changes is a decrease and equatorward shift of the midlatitude westerlies. The substantial benefits in refining both horizontal and vertical resolution give some support to scaling arguments deduced from quasigeostrophic theory implying that horizontal and vertical resolution ought to be chosen consistently.

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals A Multivariate Empirical Orthogonal Function Method to Construct Nitrate Maps in the Southern Ocean

2018 ◽  
Vol 35 (7) ◽  
pp. 1505-1519 ◽  
Author(s):  
Yu-Chiao Liang ◽  
Matthew R. Mazloff ◽  
Isabella Rosso ◽  
Shih-Wei Fang ◽  
Jin-Yi Yu
Keyword(s):  
Southern Ocean ◽  
General Circulation ◽  
Model Simulation ◽  
Potential Temperature ◽  
Circulation Model ◽  
Empirical Orthogonal Functions ◽  
Cluster Method ◽  
Sampling Strategies ◽  
Data Sampling ◽  
Mean Square Errors

AbstractThe ability to construct nitrate maps in the Southern Ocean (SO) from sparse observations is important for marine biogeochemistry research, as it offers a geographical estimate of biological productivity. The goal of this study is to infer the skill of constructed SO nitrate maps using varying data sampling strategies. The mapping method uses multivariate empirical orthogonal functions (MEOFs) constructed from nitrate, salinity, and potential temperature (N-S-T) fields from a biogeochemical general circulation model simulation Synthetic N-S-T datasets are created by sampling modeled N-S-T fields in specific regions, determined either by random selection or by selecting regions over a certain threshold of nitrate temporal variances. The first 500 MEOF modes, determined by their capability to reconstruct the original N-S-T fields, are projected onto these synthetic N-S-T data to construct time-varying nitrate maps. Normalized root-mean-square errors (NRMSEs) are calculated between the constructed nitrate maps and the original modeled fields for different sampling strategies. The sampling strategy according to nitrate variances is shown to yield maps with lower NRMSEs than mapping adopting random sampling. A k-means cluster method that considers the N-S-T combined variances to identify key regions to insert data is most effective in reducing the mapping errors. These findings are further quantified by a series of mapping error analyses that also address the significance of data sampling density. The results provide a sampling framework to prioritize the deployment of biogeochemical Argo floats for constructing nitrate maps.

scholarly journals Numerical investigation of the Arctic ice–ocean boundary layer and implications for air–sea gas fluxes

Ocean Science ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 61-75 ◽  
Author(s):  
Arash Bigdeli ◽  
Brice Loose ◽  
An T. Nguyen ◽  
Sylvia T. Cole
Keyword(s):  
Gas Exchange ◽  
Sea Ice ◽  
Mixed Layer ◽  
General Circulation ◽  
Mixed Layer Depth ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
The Arctic ◽  
Massachusetts Institute Of Technology ◽  
Institute Of Technology

Abstract. In ice-covered regions it is challenging to determine constituent budgets – for heat and momentum, but also for biologically and climatically active gases like carbon dioxide and methane. The harsh environment and relative data scarcity make it difficult to characterize even the physical properties of the ocean surface. Here, we sought to evaluate if numerical model output helps us to better estimate the physical forcing that drives the air–sea gas exchange rate (k) in sea ice zones. We used the budget of radioactive 222Rn in the mixed layer to illustrate the effect that sea ice forcing has on gas budgets and air–sea gas exchange. Appropriate constraint of the 222Rn budget requires estimates of sea ice velocity, concentration, mixed-layer depth, and water velocities, as well as their evolution in time and space along the Lagrangian drift track of a mixed-layer water parcel. We used 36, 9 and 2 km horizontal resolution of regional Massachusetts Institute of Technology general circulation model (MITgcm) configuration with fine vertical spacing to evaluate the capability of the model to reproduce these parameters. We then compared the model results to existing field data including satellite, moorings and ice-tethered profilers. We found that mode sea ice coverage agrees with satellite-derived observation 88 to 98 % of the time when averaged over the Beaufort Gyre, and model sea ice speeds have 82 % correlation with observations. The model demonstrated the capacity to capture the broad trends in the mixed layer, although with a significant bias. Model water velocities showed only 29 % correlation with point-wise in situ data. This correlation remained low in all three model resolution simulations and we argued that is largely due to the quality of the input atmospheric forcing. Overall, we found that even the coarse-resolution model can make a modest contribution to gas exchange parameterization, by resolving the time variation of parameters that drive the 222Rn budget, including rate of mixed-layer change and sea ice forcings.

scholarly journals Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Flood Prediction ◽  
Meteorological Model ◽  
The Impact ◽  
Atmospheric Simulations

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.

scholarly journals Interannual Variations of Summer Monsoons: Sensitivity to Cloud Radiative Forcing

1998 ◽  
Vol 11 (8) ◽  
pp. 1883-1905 ◽  
Author(s):  
O. P. Sharma ◽  
H. Le Treut ◽  
G. Sèze ◽  
L. Fairhead ◽  
R. Sadourny
Keyword(s):  
Optical Properties ◽  
Radiative Forcing ◽  
General Circulation ◽  
Initial Conditions ◽  
Model Simulation ◽  
Circulation Model ◽  
Interannual Variations ◽  
Radiative Effects ◽  
High Concentration ◽  
Sea Temperature

Abstract The sensitivity of the interannual variations of the summer monsoons to imposed cloudiness has been studied with a general circulation model using the initial conditions prepared from the European Centre for Medium-Range Forecasts analyses of 1 May 1987 and 1988. The cloud optical properties in this global model are calculated from prognostically computed cloud liquid water. The model successfully simulates the contrasting behavior of these two successive monsoons. However, when the optical properties of the observed clouds are specified in the model runs, the simulations show some degradation over India and its vicinity. The main cause of this degradation is the reduced land–sea temperature contrast resulting from the radiative effects of the observed clouds imposed in such simulations. It is argued that the high concentration of condensed water content of clouds over the Indian land areas will serve to limit heating of the land, thereby reducing the thermal contrast that gives rise to a weak Somali jet. A countermonsoon circulation is, therefore, simulated in the vector difference field of 850-hPa winds from the model runs with externally specified clouds. This countermonsoon circulation is associated with an equatorial heat source that is the response of the model to the radiative effects of the imposed clouds. Indeed, there are at least two clear points that can be made: 1) the cloud–SST patterns, together, affect the interannual variability; and 2) with both clouds and SST imposed, the model simulation is less sensitive to initial conditions. Additionally, the study emphasizes the importance of dynamically consistent clouds developing in response to the dynamical, thermal, and moist state of the atmosphere during model integrations.

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