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In this study, 44 profiles of gross primary productivity (GPP) and sunlight, along with water temperature, Chlorophyll-a (Chla) and nutrients, were observed in Meiliang Bay of Taihu Lake, China, in the spring, summer, and fall seasons.... more
In this study, 44 profiles of gross primary productivity (GPP) and sunlight, along with water temperature, Chlorophyll-a (Chla) and nutrients, were observed in Meiliang Bay of Taihu Lake, China, in the spring, summer, and fall seasons. Effects of water temperature, light, and nutrient concentration were examined in relation to the GPP-unit-Chla (GPP of algae per Chla). The results showed that the optimum temperature for the GPP of phytoplankton was 27.9°C, the optimal PNA-unit-Chla (photon number absorbed by phytoplankton per Chla) was 0.25 (mol), and the HSCN-unit-Chla and HSCP-unit-Chla (half-saturation constants of nitrogen and phosphorus of algae per Chla) were 0.005 (mg/L) and 0.0004 (mg/L), respectively. The seasonal dependency of the effect of different factors on the GPP was analyzed. Compared with temperature and nutrients, light was found to be the most important factor affecting the GPP during the three seasons. The effect of temperature and nutrients on the GPP of phytoplankton has obvious seasonal change. In spring, temperature was the secondary factor affecting the GPP of phytoplankton, and the effect of nutrients may be negligible in the eutrophic lake on account of temperature limit, which showed that the GPP of algae was only affected by the physical process. In summer and fall, temperature didn't affect the GPP of algae, and the presence of nutrients was the secondary factor affecting the GPP of phytoplankton. From summer to fall, effect of phosphorus was weakened and effect of nitrogen was enhanced.
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To improve dust storm identification over the western United States, historical dust events measured by air quality and satellite observations are analyzed based on their characteristics in data sets of regular meteorology,... more
To improve dust storm identification over the western United States, historical dust events measured by air quality and satellite observations are analyzed based on their characteristics in data sets of regular meteorology, satellite-based aerosol optical depth (AOD), and air quality measurements. Based on the prevailing weather conditions associated with dust emission, dust storm events are classified into the following four typical types: <br><br> (1) The key feature of cold front-induced dust storms is their rapid process with strong dust emissions.<br><br> (2) Events caused by meso- to small-scale weather systems have the highest levels of emissions.<br><br> (3) Dust storms caused by tropical disturbances show a stronger air concentration of dust and last longer than those in (1) and (2).<br><br> (4) Dust storms triggered by cyclogenesis last the longest.<br><br> In this paper, sample events of each type are selected an...
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This study uses the most recent simulations from all available fully coupled atmosphere–ocean general circulation models (CGCMs) to investigate whether the North American monsoon (NAM) precipitation seasonal–interannual variations are... more
This study uses the most recent simulations from all available fully coupled atmosphere–ocean general circulation models (CGCMs) to investigate whether the North American monsoon (NAM) precipitation seasonal–interannual variations are simulated and, if so, whether the key underlying physical mechanisms are correctly represented. This is facilitated by first identifying key centers where observed large-scale circulation fields and sea surface temperatures (SSTs) are significantly correlated with the NAM precipitation averages over the core region (central–northwest Mexico) and then examining if the modeled and observed patterns agree. Two new findings result from the analysis of observed NAM interannual variations. First, precipitation exhibits significantly high positive (negative) correlations with 200-hPa meridional wind centered to the northwest (southeast) of the core region in June and September (July and August). As such, wet conditions are associated with strong anomalous sou...
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Trends of NAO and AO are shown, along with trends of various stratospheric fields and dynamical processes, including geopotential height, temperature and zonal wind, as well as EP flux and its divergence, based upon 30 years (19681997)... more
Trends of NAO and AO are shown, along with trends of various stratospheric fields and dynamical processes, including geopotential height, temperature and zonal wind, as well as EP flux and its divergence, based upon 30 years (19681997) of NCEP/NCAR Reanalysis ...
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The Climate-Weather Research and Forecasting (CWRF) is the climate extension of the Weather Research and Forecasting (WRF) model, incorporating all WRF functionalities for numerical weather predictions while enhancing the capability for... more
The Climate-Weather Research and Forecasting (CWRF) is the climate extension of the Weather Research and Forecasting (WRF) model, incorporating all WRF functionalities for numerical weather predictions while enhancing the capability for climate applications. This report focuses on the construction and implementation of surface boundary conditions (SBCs) specifically designed for CWRF mesoscale modeling applications. The primary SBCs include surface topography (mean elevation, slope, curvature, and their standard ...