A high-resolution surface vector wind product for coastal oceans: Blending satellite scatterometer measurements with regional mesoscale atmospheric model simulations

2003 ◽  
Vol 30 (1) ◽  
pp. 13-1-13-4 ◽  
Author(s):  
Yi Chao ◽  
Zhijin Li ◽  
John C. Kindle ◽  
Jeffrey D. Paduan ◽  
Francisco P. Chavez
Keyword(s):  
High Resolution ◽  
Atmospheric Model ◽  
Coastal Oceans ◽  
Model Simulations ◽  
Mesoscale Atmospheric Model ◽  
Vector Wind

Exceptional Bora outbreak in winter 2012: Validation and analysis of high-resolution atmospheric model simulations in the northern Adriatic area

2015 ◽  
Vol 71 ◽  
pp. 1-20 ◽  
Author(s):  
Silvio Davolio ◽  
Paolo Stocchi ◽  
Alvise Benetazzo ◽  
Emanuele Bohm ◽  
Francesco Riminucci ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Model ◽  
Northern Adriatic ◽  
Model Simulations

scholarly journals Deriving VIIRS High-Spatial Resolution Water Property Data over Coastal and Inland Waters Using Deep Convolutional Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1944
Author(s):  
Xiaoming Liu ◽  
Menghua Wang
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Ocean Color ◽  
Super Resolution ◽  
Inland Waters ◽  
Coastal Oceans ◽  
Chl A ◽  
Color Data

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been a reliable source of ocean color data products, including five moderate (M) bands and one imagery (I) band normalized water-leaving radiance spectra nLw(λ). The spatial resolutions of the M-band and I-band nLw(λ) are 750 m and 375 m, respectively. With the technique of convolutional neural network (CNN), the M-band nLw(λ) imagery can be super-resolved from 750 m to 375 m spatial resolution by leveraging the high spatial resolution features of I1-band nLw(λ) data. However, it is also important to enhance the spatial resolution of VIIRS-derived chlorophyll-a (Chl-a) concentration and the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), as well as other biological and biogeochemical products. In this study, we describe our effort to derive high-resolution Kd(490) and Chl-a data based on super-resolved nLw(λ) images at the VIIRS five M-bands. To improve the network performance over extremely turbid coastal oceans and inland waters, the networks are retrained with a training dataset including ocean color data from the Bohai Sea, Baltic Sea, and La Plata River Estuary, covering water types from clear open oceans to moderately turbid and highly turbid waters. The evaluation results show that the super-resolved Kd(490) image is much sharper than the original one, and has more detailed fine spatial structures. A similar enhancement of finer structures is also found in the super-resolved Chl-a images. Chl-a filaments are much sharper and thinner in the super-resolved image, and some of the very fine spatial features that are not shown in the original images appear in the super-resolved Chl-a imageries. The networks are also applied to four other coastal and inland water regions. The results show that super-resolution occurs mainly on pixels of Chl-a and Kd(490) features, especially on the feature edges and locations with a large spatial gradient. The biases between the original M-band images and super-resolved high-resolution images are small for both Chl-a and Kd(490) in moderately to extremely turbid coastal oceans and inland waters, indicating that the super-resolution process does not change the mean values of the original images.

scholarly journals Climatological Increased Precipitation from July to August in the Western North Pacific Region Simulated by CMIP6 Models

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 664
Author(s):  
Xiao Dong ◽  
Renping Lin
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Vertical Motion ◽  
Atmospheric Model ◽  
Coupled Models ◽  
Model Simulations ◽  
Observational Analysis ◽  
Budget Analysis ◽  
Circulation Change ◽  
Precipitation Increase

In this study, the climatological precipitation increase from July to August over the western North Pacific (WNP) region was investigated through observations and simulations in the Coupled Model Intercomparison Project Phase 6 (CMIP6), atmospheric model simulations and historical experiments. Firstly, observational analysis showed that the precipitation increase is associated with a decrease in the local sea surface temperature (SST), indicating that the precipitation increase is not driven by the change in SST. In addition, the pattern of precipitation increase is similar to the vertical motion change at 500-hPa, suggesting that the precipitation increase is related to the circulation change. Moisture budget analysis further confirmed this relation. In addition to the observational analysis, the outputs from 26 CMIP6 models were further evaluated. Compared with atmospheric model simulations, air–sea coupled models largely improve the simulation of the climatological precipitation increase from July to August. Furthermore, model simulations confirmed that the bias in the precipitation increase is intimately associated with the circulation change bias. Thus, two factors are responsible for the bias of the precipitation increase from July to August in climate models: air–sea coupling processes and the performance in vertical motion change.

scholarly journals Using wind fields from a high-resolution atmospheric model for simulating snow dynamics in mountainous terrain

2009 ◽  
Vol 23 (7) ◽  
pp. 1064-1075 ◽  
Author(s):  
M. Bernhardt ◽  
G. Zängl ◽  
G. E. Liston ◽  
U. Strasser ◽  
W. Mauser
Keyword(s):  
High Resolution ◽  
Atmospheric Model ◽  
Mountainous Terrain ◽  
Wind Fields

scholarly journals What Should Be Considered When Simulating Doppler Velocities Measured by Ground-Based Weather Radars?

2008 ◽  
Vol 47 (8) ◽  
pp. 2256-2262 ◽  
Author(s):  
Olivier Caumont ◽  
Véronique Ducrocq
Keyword(s):  
High Resolution ◽  
Atmospheric Model ◽  
Physical Processes ◽  
Model Sensitivity ◽  
Sensitivity Experiments ◽  
Weather Radars ◽  
Vertical Beam ◽  
Beam Broadening

Abstract A sophisticated and flexible simulator of Doppler velocities measured by ground-based weather radars is appended to a high-resolution nonhydrostatic atmospheric model. Sensitivity experiments are conducted by using different configurations for each of the physical processes that is modeled by the simulator. It is concluded that neglecting the vertical beam broadening effect or the weighting by reflectivities yields errors of the same order on the simulated reflectivities. Neglecting hydrometeor fall speeds has a much smaller impact. It is also shown that neglecting both the beam broadening effect and the weighting by reflectivities yields errors of the same order as occur when only one of these effects is neglected.

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