scholarly journals Changing structures of summertime heatwaves over China during 19 61–2017

2021 ◽  
Author(s):  
Ning An ◽  
Zhiyan Zuo
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Cloud Cover ◽  
Meteorological Conditions ◽  
Significant Trend ◽  
Daily Variations

AbstractDespite the prevalence of artificial separation of daytime and nighttime hot extremes, they may actually co-occur or occur sequentially. Considering their potential lead-lag configuration, this study identified an entire heatwave period as consecutive days with either daytime or nighttime hot extremes and investigated the changes of the prevalence and sequence of daytime and nighttime hot extremes during heatwaves over China from 1961 to 2017. It was found that the majority (82%) of heatwaves were compound heatwaves that had both daytime and nighttime hot extremes exceeding the 90th percentile-based thresholds, while only 7% (11%) were purely daytime (nighttime) heatwaves that contained only daytime (nighttime) hot extremes. During the entire periods of compound heatwaves, daytime hot extremes usually occurred one day or a few days before nighttime hot extremes, which was in accordance with the daily variations in radiation and meteorological conditions, such as the increasing surface humidity and cloud cover, and decreasing solar radiation during the entire heatwave periods. From 1961 to 2017, compound heatwave numbers exhibited the sharpest increase with a statistically significant trend of 0.44 times decade−1, in contrast to an insignificant trend of 0.00 times decade−1 for purely daytime heatwaves and a significant trend of 0.09 times decade−1 for purely nighttime heatwaves. Within the compound heatwave periods, hot nights were starting earlier and ending later, and numbers of concurrent daytime-nighttime hot extremes increased significantly at 0.20 days decade−1. In particular, urban area were not only subject to increasingly more frequent and longer compound heatwaves, but also to more occurrences of concurrent daytime-nighttime hot extremes with more serious impact. This study provides instructions for researchers to customize and select appropriate heatwave indices.

scholarly journals Spatiotemporal Analysis of Diurnal Temperature Range: Effect of Urbanization, Cloud Cover, Solar Radiation, and Precipitation

Climate ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 89 ◽  
Author(s):  
Andri Pyrgou ◽  
Mattheos Santamouris ◽  
Iro Livada
Keyword(s):  
Solar Radiation ◽  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Longwave Radiation ◽  
Ultraviolet B ◽  
Anthropogenic Sources ◽  
Daily Minimum Temperature ◽  
Urban Station ◽  
Diurnal Temperature ◽  
Temperature Range

High daily temperatures in the Mediterranean and Europe have been documented in observation and modeling studies. Long-term temperature data, from 1988 to 2017, from a suburban station and an urban station in Nicosia, Cyprus have been analyzed, and the diurnal temperature range (DTR) trend was investigated. The seasonal Mann–Kendall test revealed a decreasing DTR trend of −0.24 °C/decade at the urban station and −0.36 °C/decade at the suburban station, which were attributed to an increase in the daily minimum temperature. Variations in precipitation, longwave radiation, ultraviolet-A (UVA), ultraviolet-B (UVB), cloud cover, water vapor, and urbanization were used to assess their possible relationship with regional DTR. The clustering of daytime and night-time data showed a strong relationship between the DTR and observed cloud cover, net longwave radiation, and precipitation. Clouds associated with smaller shortwave and net longwave radiation reduce the DTR by decreasing the surface solar radiation, while atmospheric absolute humidity denotes an increased daytime surface evaporative cooling and higher absorption of the short and longwave radiation. The intra-cluster variation could be reduced, and the inter-cluster variance increased by the addition of other meteorological parameters and anthropogenic sources that affect DTR in order to develop a quantitative basis for assessing DTR variations.

scholarly journals The seasonal variability of the amount of global solar radiation reaching the ground in urban and rural areas on the example of Warsaw and Belsk

2016 ◽  
Vol 20 (4) ◽  
pp. 29-37
Author(s):  
Kinga Nelken ◽  
Kamil Leziak
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Rural Area ◽  
Rural Areas ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Urban Station ◽  
Reverse Relationship ◽  
Urban And Rural Areas ◽  
The Relationship

AbstractThe aim of this paper is to determine the contemporary differences in the inflow of global solar radiation in Warsaw (urban station) and Belsk (rural station). The meteorological data used comprised daily sums of global solar radiation (in MJ•m−2) and the duration of sunshine (in hours) for the period 2008 2014. On clear days in spring and summer, the rural area receives more solar radiation in comparison to the urban area, whereas in autumn a reverse relationship occurs. On cloudy days in all seasons, the rural area receives more solar radiation than the urban area, and the relationship is the strongest in winter. Differences between urban and rural areas on cloudy days are smaller than those observed on clear days.

scholarly journals Forecasting and Modelling of Solar Radiation for Photovoltaic (PV) Systems

2021 ◽  
Author(s):  
Ines Sansa ◽  
Najiba Mrabet Bellaaj
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Cloud Cover ◽  
Moving Average ◽  
Arma Model ◽  
Weather Conditions ◽  
Pv Systems ◽  
Auto Regressive ◽  
Micro Grid ◽  
One Year

Solar radiation is characterized by its fluctuation because it depends to different factors such as the day hour, the speed wind, the cloud cover and some other weather conditions. Certainly, this fluctuation can affect the PV power production and then its integration on the electrical micro grid. An accurate forecasting of solar radiation is so important to avoid these problems. In this chapter, the solar radiation is treated as time series and it is predicted using the Auto Regressive and Moving Average (ARMA) model. Based on the solar radiation forecasting results, the photovoltaic (PV) power is then forecasted. The choice of ARMA model has been carried out in order to exploit its own strength. This model is characterized by its flexibility and its ability to extract the useful statistical properties, for time series predictions, it is among the most used models. In this work, ARMA model is used to forecast the solar radiation one year in advance considering the weekly radiation averages. Simulation results have proven the effectiveness of ARMA model to forecast the small solar radiation fluctuations.

Optimizing cloud cover prediction by the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS)

2021 ◽  
Author(s):  
Yen-Sen Lu ◽  
Philipp Franke ◽  
Dorit Jerger
Keyword(s):  
Boundary Layer ◽  
Solar Radiation ◽  
Planetary Boundary Layer ◽  
Cloud Cover ◽  
Weather Forecasting ◽  
Extreme Weather ◽  
Atmospheric Modeling ◽  
The Other ◽  
Extreme Weather Events ◽  
Weather Events

<p>ESIAS is an atmospheric modeling system including the ensemble version of the Weather Forecasting and Research Model (WRF V3.7.1) and the ensemble version of the EURopean Air pollution Dispersion-Inverse Model (EURAD-IM), the latter uses the output of the WRF model to calculate, amongst others, the transportation of aerosols. <!-- Maybe you can make more clear that only the wrf ensemble is used in this presentation. -->To capture extreme weather events causing the uncertainty in the solar radiation and wind speed for the renewable energy industry, we employ ESIAS by using stochastic schemes, such as Stochastically Perturbed Parameterization Tendency (SPPT) and Stochastic Kinetic Energy Backscatter (SKEBS) schemes, to generate the random fields for ensembles of up to 4096 members.</p><p>     Our first goal is to produce 48 hourly weather predictions for the European domain with a 20 KM horizontal resolution to capture extreme weather events affecting wind, solar radiation, and cloud cover forecasts. We use the ensemble capability of ESIAS to optimize the physics configuration of WRF to have a more precise weather prediction. A total of 672 ensemble members are generated to study the effect of different microphysical schemes, cumulus schemes, and planetary boundary layer parameterization schemes. We examine our simulation outputs with 288 simulation hours in 2015 using model input from the Global Ensemble Forecast System (GEFS). Our results are validated by the cloud cover data from EUMETSAT CMSAF. Besides the precision of weather forecasting, we also determine the greatest spread by generating total 768 ensemble members: 16 stochastic members for each different configurations of physical parameterizations (48 combinations). The optimization of WRF will help for improving the air quality prediction<!-- 16 member out of 48 configurations? Is this a mistake? Otherwise maybe you can be a bit more precise --><!-- I agree with Philipp, this is most unclear. --><!-- Reply to Jerger, Dorit (01/07/2021, 17:15): "..." Well I tried my best for it. The “blue” and the “cross-out red” ones are the two versions, hopefully the “blue” one is better than the “cross-out red” one. --> by EURAD-IM, which will be demonstrated on a test case basis.</p><p>     Our results show that for the performed analysis the Community Atmosphere Model (CAM) 5.1, WRF Single-Moment 6-class scheme (WSM6), and the Goddard microphysics outstand the other 11 microphysics parameterizations, where the highest daily average matching rate is 64.2%. The Mellor–Yamada Nakanishi Niino (MYNN) 2 and MYNN3 schemes give better results compared to the other 8 planetary boundary layer schemes, and Grell 3D (Grell-3) works generally well with the above mentioned physical schemes. Overall, the combination of Goddard and MYNN3 produces the greatest spread comparing to the lowest spread (Morrison 2-moment & GFS) by 40%.</p>

Measurements and Comparative Air Quality Analysis of a Goat Farm Operation

2019 ◽  
Vol 62 (6) ◽  
pp. 1723-1733
Author(s):  
Arndreya Howard ◽  
Venkata S. V. Botlaguduru ◽  
Hongbo Du ◽  
Raghava R. Kommalapati ◽  
Ziaul Huque
Keyword(s):  
Hydrogen Sulfide ◽  
Air Quality ◽  
Solar Radiation ◽  
Multiple Regression ◽  
Air Pollutants ◽  
Emission Rate ◽  
Particle Diameter ◽  
Ambient Air ◽  
Meteorological Conditions ◽  
Goat Farm

Abstract. Air pollutants such as hydrogen sulfide, ammonia, particulate matter (PM10 and PM2.5), methane, and volatile organic compounds (VOCs) are harmful to the respiratory systems of humans and animals. Livestock facilities have been documented as a major source of dangerous air pollutants; however, there is a lack of data on the emissions from goat farms. This study investigated a goat farm in Texas to evaluate the emission levels and determine the correlation of meteorological conditions with these pollutants. Two locations on the goat farm were selected for monitoring: inside a goat barn, and at a manure lagoon. The monitoring campaign was conducted over a 53-day period during winter and summer seasons. Carbon dioxide, ozone, nitrous oxide, ammonia, PM10, PM2.5, hydrogen sulfide, methane, and VOCs were measured to determine hourly average concentrations using chemiluminescent instruments. An analysis of meteorological conditions using multiple regression was conducted to investigate probable correlations between emission rates and characteristic climate data, such as temperature, humidity, barometric pressure, and solar radiation. Particle size distributions of PM10 and PM2.5 were evaluated for the two monitoring locations during the different seasons to determine the typical particle diameter and the impact of season on particle diameter. The highest emission rate of 364.4 ±50 g m-2 d-1 occurred at the manure lagoon for methane, which contributed the most to the overall emissions at this animal operation. The regression results for the manure lagoon had the highest positive correlations for ozone with temperature and solar radiation. The outdoor meteorological conditions had the most significant influence on pollutants at both locations. Therefore, meteorological conditions are instrumental in the intensity of the air pollutants found on animal farms. The particle diameters ranged from 0.1 to 6.0 µm in the goat barn and from 0.3 to 1.0 µm at the manure lagoon. Even though moderate levels of emissions were monitored at this facility, the emissions from the goat farm do not pose a risk to human health and do not significantly impact the ambient air quality when compared to other livestock facilities.HighlightsEmissions from a goat farm were measured inside a goat barn and at a manure lagoon over summer and winter seasons.The highest methane emission rate of 364.4 ±50 g m-2 d-1 occurred at the manure lagoon during summer.Meteorological conditions significantly influenced emissions at both locations, especially for O3 at the manure lagoon.Emissions from goat farm operations are much lower than those from cow, swine, and chicken farm operations. Keywords: Air quality, Ammonia, Emissions, Goat farm, Methane, Multiple regression analysis.

scholarly journals Sensitivity of Surface Ozone Simulation to Cumulus Parameterization

2008 ◽  
Vol 47 (5) ◽  
pp. 1456-1466 ◽  
Author(s):  
Zhining Tao ◽  
Allen Williams ◽  
Ho-Chun Huang ◽  
Michael Caughey ◽  
Xin-Zhong Liang
Keyword(s):  
Cloud Cover ◽  
Surface Ozone ◽  
Meteorological Conditions ◽  
Cumulus Parameterization ◽  
Daily Maximum ◽  
Boundary Layer Height ◽  
Ozone Concentrations ◽  
Simulated Precipitation ◽  
Cumulus Schemes ◽  
The Impact

Abstract Different cumulus schemes cause significant discrepancies in simulated precipitation, cloud cover, and temperature, which in turn lead to remarkable differences in simulated biogenic volatile organic compound (BVOC) emissions and surface ozone concentrations. As part of an effort to investigate the impact (and its uncertainty) of climate changes on U.S. air quality, this study evaluates the sensitivity of BVOC emissions and surface ozone concentrations to the Grell (GR) and Kain–Fritsch (KF) cumulus parameterizations. Overall, using the KF scheme yields less cloud cover, larger incident solar radiation, warmer surface temperature, and higher boundary layer height and hence generates more BVOC emissions than those using the GR scheme. As a result, the KF (versus GR) scheme produces more than 10 ppb of summer mean daily maximum 8-h ozone concentration over broad regions, resulting in a doubling of the number of high-ozone occurrences. The contributions of meteorological conditions versus BVOC emissions on regional ozone sensitivities to the choice of the cumulus scheme largely offset each other in the California and Texas regions, but the contrast in BVOC emissions dominates over that in the meteorological conditions for ozone differences in the Midwest and Northeast regions. The result demonstrates the necessity of considering the uncertainty of future ozone projections that are identified with alternative model physics configurations.

scholarly journals Comparisons on Calculating Methods of Total Daily Global Solar Radiation in Urban Area Based on Panoramic Images

2019 ◽  
Vol 136 ◽  
pp. 05010
Author(s):  
Moyan Zhang ◽  
Yan Liu ◽  
Ruixin Chen ◽  
Xiangfei Guo ◽  
Weiqing Yuan ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Morphological Characteristics ◽  
Global Solar Radiation ◽  
View Factor ◽  
Sky View Factor ◽  
Panoramic Images ◽  
Rayman Model ◽  
Morphology Characteristics ◽  
Tree View

In this paper, the total daily global solar radiation is tested at 18 locations with different morphological characteristics in Xi’an University of Architecture and Technology. PTgui is used to convert the panoramic pictures from Baidu Street Map to fisheye images. Sky view factor (SVF) and tree view factor (TVF) are calculated by Rayman model with fisheye images. SVF is used to calculate the total daily global solar radiation at the 18 locations with two different methods and TVF is used to classify the locations. The calculations and testing results are compared and combined the morphological characteristics. Then it is found that using suitable methods on different locations is necessary to obtain more accurate results whether the TVF (tree view factor) is more than 0.3 or less. To obtain solar radiation at different locations in the urban area, the calculating methods should be carefully chosen based on the morphology characteristics of the location.

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