scholarly journals Estimation water vapor content using the mixing ratio method and validated with the ANFIS PWV model

2017 ◽  
Vol 852 ◽  
pp. 012041 ◽  
Author(s):  
W Suparta ◽  
K M Alhasa ◽  
M S J Singh
Keyword(s):  
Water Vapor ◽  
Water Vapor Content ◽  
Ratio Method ◽  
Mixing Ratio

Long-term variation of water vapor content and precipitation in the Haihe river basin

2014 ◽  
Vol 6 (2) ◽  
pp. 341-351 ◽  
Author(s):  
Chun Chang ◽  
Ping Feng ◽  
Fawen Li ◽  
Yunming Gao
Keyword(s):  
Water Vapor ◽  
River Basin ◽  
Reanalysis Data ◽  
Water Vapor Content ◽  
Haihe River Basin ◽  
Haihe River ◽  
Annual Water ◽  
Environmental Prediction ◽  
High Consistency ◽  
The Haihe River Basin

Based on the Haihe river basin National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data from 1948 to 2010 and the precipitation data of 53 hydrological stations during 1957–2010, this study analyzed the variation of water vapor content and precipitation, and investigated the correlation between them using several statistical methods. The results showed that the annual water vapor content decreased drastically from 1948 to 2010. It was comparatively high from the late 1940s to the late 1960s and depreciated from the early 1970s. From the southeast to the northwest of the Haihe river basin, there was a decrease in water vapor content. For vertical distribution, water vapor content from the ground to 700 hPa pressure level accounted for 72.9% of the whole atmospheric layer, which indicated that the water vapor of the Haihe river basin was mainly in the air close to the ground. The precipitation in the Haihe river basin during 1957–2010 decreased very slightly. According to the correlation analysis, the precipitation and water vapor content changes showed statistically positive correlation, in addition, their break points were both in the 1970s. Furthermore, the high consistency between the precipitation efficiency and precipitation demonstrates that water vapor content is one of the important factors in the formation of precipitation.

Subcloud and Cloud-Base Latent Heat Fluxes during Shallow Cumulus Convection

2019 ◽  
Vol 77 (3) ◽  
pp. 1081-1100 ◽  
Author(s):  
Neil P. Lareau
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Latent Heat ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Cloud Base ◽  
Cumulus Convection ◽  
Mixing Ratio ◽  
Convective Boundary ◽  
Water Vapor Mixing Ratio

Abstract Doppler and Raman lidar observations of vertical velocity and water vapor mixing ratio are used to probe the physics and statistics of subcloud and cloud-base latent heat fluxes during cumulus convection at the ARM Southern Great Plains (SGP) site in Oklahoma, United States. The statistical results show that latent heat fluxes increase with height from the surface up to ~0.8Zi (where Zi is the convective boundary layer depth) and then decrease to ~0 at Zi. Peak fluxes aloft exceeding 500 W m−2 are associated with periods of increased cumulus cloud cover and stronger jumps in the mean humidity profile. These entrainment fluxes are much larger than the surface fluxes, indicating substantial drying over the 0–0.8Zi layer accompanied by moistening aloft as the CBL deepens over the diurnal cycle. We also show that the boundary layer humidity budget is approximately closed by computing the flux divergence across the 0–0.8Zi layer. Composite subcloud velocity and water vapor anomalies show that clouds are linked to coherent updraft and moisture plumes. The moisture anomaly is Gaussian, most pronounced above 0.8Zi and systematically wider than the velocity anomaly, which has a narrow central updraft flanked by downdrafts. This size and shape disparity results in downdrafts characterized by a high water vapor mixing ratio and thus a broad joint probability density function (JPDF) of velocity and mixing ratio in the upper CBL. We also show that cloud-base latent heat fluxes can be both positive and negative and that the instantaneous positive fluxes can be very large (~10 000 W m−2). However, since cloud fraction tends to be small, the net impact of these fluxes remains modest.

Design of Highway Construction Mixing Materials Ratio Based on Genetic Algorithm

2013 ◽  
Vol 367 ◽  
pp. 308-311
Author(s):  
Li Ping Li ◽  
Guang Li Xu ◽  
Xiao Li Lu
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Highway Construction ◽  
Computer Application ◽  
Ratio Method ◽  
Mixing Ratio ◽  
Ratio Calculation ◽  
Economic Program ◽  
Material Mixing ◽  
Design Construction

The manual work or Excel based material mixing ratio method has low computer application level and lays high computer capacity on design construction workers. It is difficult to obtain the most optimal technical and economic program from a number of optional programs. The paper built mathematical model of materials mixing ratio based on genetic and identified constraint conditions. Data pre-processing was performed according to the constructed model. According to specific circus of material mixing ratio calculation, the fitness function and various operators were designed and parameters of model were also configured. At the same time of meeting requirements of project quality, multiple target optimizations were considered to give new model and constraints. The highway construction mixing materials ratio calculation based on genetic algorithm achieves expected goal and improve accuracy and efficiency of operations.

Variational Assimilation of Radar Data and GLM Lightning-Derived Water Vapor for the Short-Term Forecasts of High-Impact Convective Events

2019 ◽  
Vol 147 (11) ◽  
pp. 4045-4069 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Yunheng Wang ◽  
Jidong Gao ◽  
Edward R. Mansell
Keyword(s):  
Water Vapor ◽  
Radar Data ◽  
The United States ◽  
High Impact ◽  
Added Value ◽  
Mixing Ratio ◽  
Short Term ◽  
Short Term Forecast ◽  
Term Forecast ◽  
Vapor Mass

Abstract The assimilation of water vapor mass mixing ratio derived from total lightning data from the Geostationary Lightning Mapper (GLM) within a three-dimensional variational (3DVAR) system is evaluated for the analysis and short-term forecast (≤6 h) of a high-impact convective event over the northern Great Plains in the United States. Building on recent work, the lightning data assimilation (LDA) method adjusts water vapor mass mixing ratio within a fixed layer depth above the lifted condensation level by assuming nearly water-saturated conditions at observed lightning locations. In this algorithm, the total water vapor mass added by the LDA is balanced by an equal removal outside observed lightning locations. Additional refinements were also devised to partially alleviate the seasonal and geographical dependence of the original scheme. To gauge the added value of lightning, radar data (radial velocity and reflectivity) were also assimilated with or without lightning. Although the method was evaluated in quasi–real time for several high-impact weather events throughout 2018, this work will focus on one specific, illustrative severe weather case wherein the control simulation—which did not assimilate any data—was eventually able to initiate and forecast the majority of the observed storms. Given a relatively reasonable forecast in the control experiment, the GLM and radar assimilation experiments were still able to improve the short-term forecast of accumulated rainfall and composite radar reflectivity further, as measured by neighborhood-based metrics. These results held whether the simulations made use of one single 3DVAR analysis or high-frequency (10 min) successive cycling over a 1-h period.

Effect of water vapor content during the solid state synthesis of manganese-doped magnesium fluoro-germanate phosphor on its chemistry and photoluminescent properties

2020 ◽  
Vol 99 ◽  
pp. 109572 ◽  
Author(s):  
Amjad Ali ◽  
Liudmyla M. Chepyga ◽  
Laraib Sarfraz Khanzada ◽  
Andres Osvet ◽  
Christoph J. Brabec ◽  
...  
Keyword(s):  
Water Vapor ◽  
Solid State ◽  
Water Vapor Content ◽  
Solid State Synthesis ◽  
Effect Of Water

scholarly journals A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals

2019 ◽  
Vol 12 (7) ◽  
pp. 3943-3961 ◽  
Author(s):  
Ali Jalali ◽  
Shannon Hicks-Jalali ◽  
Robert J. Sica ◽  
Alexander Haefele ◽  
Thomas von Clarmann
Keyword(s):  
Water Vapor ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Mixing Ratio ◽  
A Priori Information ◽  
Fine Grid ◽  
Large Power ◽  
Priori Information ◽  
Water Vapor Mixing Ratio

Abstract. Lidar retrievals of atmospheric temperature and water vapor mixing ratio profiles using the optimal estimation method (OEM) typically use a retrieval grid with a number of points larger than the number of pieces of independent information obtainable from the measurements. Consequently, retrieved geophysical quantities contain some information from their respective a priori values or profiles, which can affect the results in the higher altitudes of the temperature and water vapor profiles due to decreasing signal-to-noise ratios. The extent of this influence can be estimated using the retrieval's averaging kernels. The removal of formal a priori information from the retrieved profiles in the regions of prevailing a priori effects is desirable, particularly when these greatest heights are of interest for scientific studies. We demonstrate here that removal of a priori information from OEM retrievals is possible by repeating the retrieval on a coarser grid where the retrieval is stable even without the use of formal prior information. The averaging kernels of the fine-grid OEM retrieval are used to optimize the coarse retrieval grid. We demonstrate the adequacy of this method for the case of a large power-aperture Rayleigh scatter lidar nighttime temperature retrieval and for a Raman scatter lidar water vapor mixing ratio retrieval during both day and night.

scholarly journals Aerosol hygroscopic growth, contributing factors, and impact on haze events in a severely polluted region in northern China

2019 ◽  
Vol 19 (2) ◽  
pp. 1327-1342 ◽  
Author(s):  
Jun Chen ◽  
Zhanqing Li ◽  
Min Lv ◽  
Yuying Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Water Vapor ◽  
Chemical Properties ◽  
Water Vapor Content ◽  
Growth Effect ◽  
Chemical Components ◽  
Hygroscopic Growth ◽  
Contributing Factors ◽  
Total Particulate Matter ◽  
Size Category ◽  
The Impact

Abstract. This study investigates the impact of the aerosol hygroscopic growth effect on haze events in Xingtai, a heavily polluted city in the central part of the North China Plain (NCP), using a large array of instruments measuring aerosol optical, physical, and chemical properties. Key instruments used and measurements made include the Raman lidar for atmospheric water vapor content and aerosol optical profiles, the PC-3016A GrayWolf six-channel handheld particle and mass meter for atmospheric total particulate matter (PM) that has diameters less than 1 and 2.5 µm (PM1 and PM2.5, respectively), the aerosol chemical speciation monitor (ACSM) for chemical components in PM1, and the hygroscopic tandem differential mobility analyzer (H-TDMA) for aerosol hygroscopicity. The changes in PM1 and PM2.5 agreed well with that of the water vapor content due to the aerosol hygroscopic growth effect. Two cases were selected to further analyze the effects of aerosol hygroscopic growth on haze events. The lidar-estimated hygroscopic enhancement factor for the aerosol backscattering coefficient during a relatively clean period (Case I) was lower than that during a pollution event (Case II) with similar relative humidity (RH) levels of 80 %–91 %. The Kasten model was used to fit the aerosol optical hygroscopic growth factor (GF) whose parameter b differed considerably between the two cases, i.e., 0.1000 (Case I) versus 0.9346 (Case II). The aerosol acidity value calculated from ACSM data for Case I (1.35) was less than that for Case II (1.50) due to different amounts of inorganics such as NH4NO3, NH4HSO4, and (NH4)2SO4. Model results based on H-TDMA data showed that aerosol hygroscopic growth factors in each size category (40, 80, 110, 150, and 200 nm) at different RH levels (80 %–91 %) for Case I were lower than those for Case II. For similar ambient RH levels, the high content of nitrate facilitates the hygroscopic growth of aerosols, which may be a major factor contributing to heavy haze episodes in Xingtai.

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