Frontal Scale Air–Sea Interaction in High-Resolution Coupled Climate Models

2010 ◽  
Vol 23 (23) ◽  
pp. 6277-6291 ◽  
Author(s):  
Frank O. Bryan ◽  
Robert Tomas ◽  
John M. Dennis ◽  
Dudley B. Chelton ◽  
Norman G. Loeb ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Climate Models ◽  
Prediction Models ◽  
Weather Prediction ◽  
Surface Wind ◽  
Coupled Model ◽  
Climate System Model ◽  
Surface Wind Stress ◽  
Coupled Climate Models

Abstract The emerging picture of frontal scale air–sea interaction derived from high-resolution satellite observations of surface winds and sea surface temperature (SST) provides a unique opportunity to test the fidelity of high-resolution coupled climate simulations. Initial analysis of the output of a suite of Community Climate System Model (CCSM) experiments indicates that characteristics of frontal scale ocean–atmosphere interaction, such as the positive correlation between SST and surface wind stress, are realistically captured only when the ocean component is eddy resolving. The strength of the coupling between SST and surface stress is weaker than observed, however, as has been found previously for numerical weather prediction models and other coupled climate models. The results are similar when the atmospheric component model grid resolution is doubled from 0.5° to 0.25°, an indication that shortcomings in the representation of subgrid scale atmospheric planetary boundary layer processes, rather than resolved scale processes, are responsible for the weakness of the coupling. In the coupled model solutions the response to mesoscale SST features is strongest in the atmospheric boundary layer, but there is a deeper reaching response of the atmospheric circulation apparent in free tropospheric clouds. This simulated response is shown to be consistent with satellite estimates of the relationship between mesoscale SST and all-sky albedo.

scholarly journals The role of urban boundary layer investigated by high resolution models and ground based observations in Rome area: a step for understanding parameterizations potentialities

2013 ◽  
Vol 6 (3) ◽  
pp. 5297-5344
Author(s):  
E. Pichelli ◽  
R. Ferretti ◽  
M. Cacciani ◽  
A. M. Siani ◽  
V. Ciardini ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Urban Areas ◽  
Prediction Models ◽  
Weather Prediction ◽  
Sonic Anemometer ◽  
Lower Atmosphere ◽  
Area Of Interest ◽  
The Impact

Abstract. The urban forcing on thermo-dynamical conditions can largely influences local evolution of the atmospheric boundary layer. Urban heat storage can produce noteworthy mesoscale perturbations of the lower atmosphere. The new generations of high-resolution numerical weather prediction models (NWP) is nowadays largely applied also to urban areas. It is therefore critical to reproduce correctly the urban forcing which turns in variations of wind, temperature and water vapor content of the planetary boundary layer (PBL). WRF-ARW, a new model generation, has been used to reproduce the circulation in the urban area of Rome. A sensitivity study is performed using different PBL and surface schemes. The significant role of the surface forcing in the PBL evolution has been verified by comparing model results with observations coming from many instruments (LiDAR, SODAR, sonic anemometer and surface stations). The crucial role of a correct urban representation has been demonstrated by testing the impact of different urban canopy models (UCM) on the forecast. Only one of three meteorological events studied will be presented, chosen as statistically relevant for the area of interest. The WRF-ARW model shows a tendency to overestimate vertical transmission of horizontal momentum from upper levels to low atmosphere, that is partially corrected by local PBL scheme coupled with an advanced UCM. Depending on background meteorological scenario, WRF-ARW shows an opposite behavior in correctly representing canopy layer and upper levels when local and non local PBL are compared. Moreover a tendency of the model in largely underestimating vertical motions has been verified.

scholarly journals Screen-level non-GTS data assimilation in a limited-area mesoscale model

2010 ◽  
Vol 10 (6) ◽  
pp. 1129-1149 ◽  
Author(s):  
M. Milelli ◽  
M. Turco ◽  
E. Oberto
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Data Assimilation ◽  
Planetary Boundary Layer ◽  
Prediction Models ◽  
Mesoscale Model ◽  
Positive Impact ◽  
Weather Prediction ◽  
Limited Area ◽  
Very High

Abstract. The forecast in areas of very complex topography, as for instance the Alpine region, is still a challenge even for the new generation of numerical weather prediction models which aim at reaching the km-scale. The problem is enhanced by a general lack of standard observations, which is even more evident over the southern side of the Alps. For this reason, it would be useful to increase the performance of the mathematical models by locally assimilating non-conventional data. Since in ARPA Piemonte there is the availability of a great number of non-GTS stations, it has been decided to assimilate the 2 m temperature, coming from this dataset, in the very-high resolution version of the COSMO model, which has a horizontal resolution of about 3 km, more similar to the average resolution of the thermometers. Four different weather situations have been considered, ranging from spring to winter, from cloudy to clear sky. The aim of the work is to investigate the effects of the assimilation of non-GTS data in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast starting from these analyses (RUC or Rapid Update Cycle). The results, in terms of Root Mean Square Error, Mean Error and diurnal cycle of some surface variables such as 2 m temperature, 2 m relative humidity and 10 m wind intensity show a positive impact during the assimilation cycle which tends to dissipate a few hours after the end of it. Moreover, the 2 m temperature assimilation has a slightly positive or neutral impact on the vertical profiles of temperature, eventhough some calibration is needed for the precipitation field which is too much perturbed during the assimilation cycle, while it is unaffected in the forecast period. So the stability of the planetary boundary layer, on the one hand, has not been particularly improved by the new-data assimilation, but, on the other hand, it has not been destroyed. It has to be pointed out that a correct description of the planetary boundary layer, even only the lowest part of it, could be helpful to the forecasters and, in general, to the users, in order to deal with meteorological hazards such as snow (in particular snow/rain limit definition), or fog (description of temperature inversions).

scholarly journals Wind Features Extracted from Weather Simulations for Wind-Wave Prediction Using High-Resolution Neural Networks

2021 ◽  
Vol 9 (11) ◽  
pp. 1257
Author(s):  
Chih-Chiang Wei
Keyword(s):  
High Resolution ◽  
Spatial Data ◽  
Prediction Models ◽  
Wind Wave ◽  
Weather Prediction ◽  
Time Series Prediction ◽  
Surface Wind ◽  
Wind Fields ◽  
Forecast Horizon ◽  
Wave Prediction

Nearshore wave forecasting is susceptible to changes in regional wind fields and environments. However, surface wind field changes are difficult to determine due to the lack of in situ observational data. Therefore, accurate wind and coastal wave forecasts during typhoon periods are necessary. The purpose of this study is to develop artificial intelligence (AI)-based techniques for forecasting wind–wave processes near coastal areas during typhoons. The proposed integrated models employ combined a numerical weather prediction (NWP) model and AI techniques, namely numerical (NUM)-AI-based wind–wave prediction models. This hybrid model comprising VGGNNet and High-Resolution Network (HRNet) was integrated with recurrent-based gated recurrent unit (GRU). Termed mVHR_GRU, this model was constructed using a convolutional layer for extracting features from spatial images with high-to-low resolution and a recurrent GRU model for time series prediction. To investigate the potential of mVHR_GRU for wind–wave prediction, VGGNet, HRNet, and Two-Step Wind-Wave Prediction (TSWP) were selected as benchmark models. The coastal waters in northeast Taiwan were the study area. The length of the forecast horizon was from 1 to 6 h. The mVHR_GRU model outperformed the HR_GRU, VGGNet, and TSWP models according to the error indicators. The coefficient of mVHR_GRU efficiency improved by 13% to 18% and by 13% to 15% at the Longdong and Guishandao buoys, respectively. In addition, in a comparison of the NUM–AI-based model and a numerical model simulating waves nearshore (SWAN), the SWAN model generated greater errors than the NUM–AI-based model. The results of the NUM–AI-based wind–wave prediction model were in favorable accordance with the observed results, indicating the feasibility of the established model in processing spatial data.

Boundary Layer and Surface Verification of the High-Resolution Rapid Refresh, Version 3

2020 ◽  
Vol 35 (6) ◽  
pp. 2255-2278
Author(s):  
Robert G. Fovell ◽  
Alex Gallagher
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Wind Speed ◽  
Prediction Models ◽  
Weather Prediction ◽  
Potential Temperature ◽  
Ground Level ◽  
Systematic Errors ◽  
Radiosonde Data ◽  
Near Surface

AbstractWhile numerical weather prediction models have made considerable progress regarding forecast skill, less attention has been paid to the planetary boundary layer. This study leverages High-Resolution Rapid Refresh (HRRR) forecasts on native levels, 1-s radiosonde data, and (primarily airport) surface observations across the conterminous United States. We construct temporally and spatially averaged composites of wind speed and potential temperature in the lowest 1 km for selected months to identify systematic errors in both forecasts and observations in this critical layer. We find near-surface temperature and wind speed predictions to be skillful, although wind biases were negatively correlated with observed speed and temperature biases revealed a robust relationship with station elevation. Above ≈250 m above ground level, below which radiosonde wind data were apparently contaminated by processing, biases were small for wind speed and potential temperature at the analysis time (which incorporates sonde data) but became substantial by the 24-h forecast. Wind biases were positive through the layer for both 0000 and 1200 UTC, and morning potential temperature profiles were marked by excessively steep lapse rates that persisted across seasons and (again) exaggerated at higher elevation sites. While the source or cause of these systematic errors are not fully understood, this analysis highlights areas for potential model improvement and the need for a continued and accessible archive of the data that make analyses like this possible.

An Assessment of the Sea Surface Temperature Influence on Surface Wind Stress in Numerical Weather Prediction and Climate Models

2006 ◽  
Vol 19 (12) ◽  
pp. 2743-2762 ◽  
Author(s):  
Eric D. Maloney ◽  
Dudley B. Chelton
Keyword(s):  
Wind Stress ◽  
Climate Models ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Satellite Observations ◽  
Grid Resolution ◽  
Coupling Coefficients ◽  
Surface Wind Stress ◽  
Current Systems

Abstract The ability of six climate models to capture the observed coupling between SST and surface wind stress in the vicinity of strong midlatitude SST fronts is analyzed. The analysis emphasizes air–sea interactions associated with ocean meanders in the eastward extensions of major western boundary current systems such as the Gulf Stream, Kuroshio, and Agulhas Current. Satellite observations of wind stress from the SeaWinds scatterometer on NASA’s Quick Scatterometer and SST from the Advanced Microwave Scanning Radiometer clearly indicate the influence of SST on surface wind stress on scales smaller than about 30° longitude × 10° latitude. Spatially high-pass-filtered SST and wind stress variations are linearly related, with higher SST associated with higher wind stress. The influence of SST on wind stress is also clearly identifiable in the ECMWF operational forecast model, having a grid resolution of 0.35° × 0.35° (T511). However, the coupling coefficient between wind stress and SST, as indicated by the slope of the linear least squares fit, is only half as strong as for satellite observations. The ability to simulate realistic air–sea interactions is present to varying degrees in the coupled climate models examined. The Model for Interdisciplinary Research on Climate 3.2 (MIROC3.2) high-resolution version (HIRES) (1.1° × 1.1°, T106) and the NCAR Community Climate System Model 3.0 (1.4° × 1.4°, T85) are the highest-resolution models considered and produce the most realistic air–sea coupling associated with midlatitude current systems. Coupling coefficients between SST and wind stress in MIROC3.2_HIRES and the NCAR model are at least comparable to those in the ECMWF operational model. The spatial scales of midlatitude SST variations and SST-induced wind perturbations in MIROC3.2_HIRES are comparable to those of satellite observations. The spatial scales of SST variability in the NCAR model are larger than those in the ECMWF model and satellite observations, and hence the spatial scales of SST-induced perturbations in the wind fields are larger. It is found that the ability of climate models to simulate air–sea interactions degrades with decreasing grid resolution. SST anomalies in the GFDL Climate Model 2.0 (CM2.0) (2.0° × 2.5°), Met Office Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3) (2.5° × 3.8°), and MIROC3.2 medium-resolution version (MEDRES) (2.8° × 2.8°, T42) have larger spatial scales and are more geographically confined than in the higher-resolution models. The GISS Model E20/Russell (4.0° × 5.0°) is unable to resolve the midlatitude ocean eddies that produce prominent air–sea interaction. Notably, MIROC3.2_MEDRES exhibits much weaker coupling between wind stress and SST than does the higher vertical and horizontal resolution version of the same model. GFDL CM2.0 and Met Office HadCM3 exhibit a linear relationship between SST and wind stress. However, coupling coefficients for the Met Office model are significantly weaker than in the GFDL and higher-resolution models. In addition to model grid resolution (both vertical and horizontal), deficiencies in the parameterization of boundary layer processes may be responsible for some of these differences in air–sea coupling between models and observations.

scholarly journals The role of urban boundary layer investigated with high-resolution models and ground-based observations in Rome area: a step towards understanding parameterization potentialities

2014 ◽  
Vol 7 (1) ◽  
pp. 315-332 ◽  
Author(s):  
E. Pichelli ◽  
R. Ferretti ◽  
M. Cacciani ◽  
A. M. Siani ◽  
V. Ciardini ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Urban Areas ◽  
Prediction Models ◽  
Weather Prediction ◽  
Sonic Anemometer ◽  
Lower Atmosphere ◽  
Area Of Interest ◽  
The Impact

Abstract. The urban forcing on thermodynamical conditions can greatly influence the local evolution of the atmospheric boundary layer. Heat stored in an urban environment can produce noteworthy mesoscale perturbations of the lower atmosphere. The new generation of high-resolution numerical weather prediction models (NWP) is nowadays often applied also to urban areas. An accurate representation of cities is key role because of the cities' influence on wind, temperature and water vapor content of the planetary boundary layer (PBL). The Advanced Weather Research and Forecasting model WRF (ARW) has been used to reproduce the circulation in the urban area of Rome. A sensitivity study is performed using different PBL and surface schemes. The significant role of the surface forcing in the PBL evolution has been investigated by comparing model results with observations coming from many instruments (lidar, sodar, sonic anemometer and surface stations). The impact of different urban canopy models (UCMs) on the forecast has also been investigated. One meteorological event will be presented, chosen as statistically relevant for the area of interest. The WRF-ARW model shows a tendency to overestimate the vertical transport of horizontal momentum from upper levels to low atmosphere if strong large-scale forcing occurs. This overestimation is partially corrected by a local PBL scheme coupled with an advanced UCM. Moreover, a general underestimation of vertical motions has been verified.

scholarly journals GFDL's CM2 Global Coupled Climate Models. Part I: Formulation and Simulation Characteristics

2006 ◽  
Vol 19 (5) ◽  
pp. 643-674 ◽  
Author(s):  
Thomas L. Delworth ◽  
Anthony J. Broccoli ◽  
Anthony Rosati ◽  
Ronald J. Stouffer ◽  
V. Balaji ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Surface Wind ◽  
Coupled Model ◽  
Forecast Model ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Coupled Models ◽  
Coupled Climate Models

Abstract The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2° latitude × 2.5° longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1° in latitude and longitude, with meridional resolution equatorward of 30° becoming progressively finer, such that the meridional resolution is 1/3° at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic. Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).

Wind Stress Over Waves: Effects of Sea Roughness and Atmospheric Stability

2002 ◽  
Vol 124 (3) ◽  
pp. 169-172 ◽  
Author(s):  
Dag Myrhaug ◽  
Olav H. Slaattelid
Keyword(s):  
Boundary Layer ◽  
Wind Stress ◽  
Local Equilibrium ◽  
Surface Wind ◽  
Atmospheric Stability ◽  
Sea Surface ◽  
Stability Function ◽  
Sea Surface Wind ◽  
Surface Wind Stress ◽  
Sea Surface Roughness

The paper considers the effects of sea roughness and atmospheric stability on the sea surface wind stress over waves, which are in local equilibrium with the wind, by using the logarithmic boundary layer profile including a stability function, as well as adopting some commonly used sea surface roughness formulations. The engineering relevance of the results is also discussed.

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