A new present weather identifier(PWI) based on occlusion and scattering techniques is presented in the study. The present weather parameters are detectable by the meteorological optical range(MOR) approximately up to ...A new present weather identifier(PWI) based on occlusion and scattering techniques is presented in the study. The present weather parameters are detectable by the meteorological optical range(MOR) approximately up to 50 km and by droplets with diameters ranging from 0.125 mm to 22 mm with velocities up to 16 m s-1. The MOR error is less than 8% for the MOR within 10 km and less than 15% for farther distances. Moreover, the size errors derived from various positions of the light sheet by the particles were checked within ± 0.1 mm ± 5%. The comparison shows that the MOR, in a sudden shower event, is surprisingly consistent with those of the sentry visibility sensors(SVS) with a correlation coefficient up to 98%. For the rain amounts derived from the size and velocity of the droplets, the daily sums by the PWI agree within 10% of those by the Total Rain Weighing Sensor(TRwS205) and the rain gauge. Combined with other sensors such as temperature, humidity, and wind, the PWI can serve as a present weather sensor to distinguish several weather types such as fog, haze, mist, rain, hail, and drizzle.展开更多
Knowing crop water uptake each day is useful for developing irrigation scheduling. Many technologies have been used to estimate daily crop water use. Sap flow is one of the technologies that measure water flow through...Knowing crop water uptake each day is useful for developing irrigation scheduling. Many technologies have been used to estimate daily crop water use. Sap flow is one of the technologies that measure water flow through the stem of a plant and estimate daily crop water uptake. Sap flow sensor is an effective direct method for measuring crop water use, but it is relatively expensive and requires frequent maintenance. Therefore, alternative methods, such as evapotranspiration based on FAO 56 Penman-Monteith equation and other weather parameters were evaluated to find the correlation with sap flow. In this study, Dynamax Flow 32-1K sap flow system was utilized to monitor potato water use. The results show sap flow has a strong correlation with evapotranspiration (RMSE = 1.34, IA = 0.89, MBE = -0.83), solar radiation (RMSE = 2.25, IA = 0.72, MBE = -1.80), but not with air temperature, relative humidity, wind speed, and vapor pressure. It is worth noting that the R<sup>2</sup> between sap flow and relative humidity was 0.55. This study has concluded that daily evapotranspiration and solar radiation can be used as alternative methods to estimate sap flow.展开更多
Surface weather parameters detain high socioeconomic impact and strategic insights for all users,in all domains(aviation,marine traffic,agriculture,etc.).However,those parameters were mainly predicted by using determi...Surface weather parameters detain high socioeconomic impact and strategic insights for all users,in all domains(aviation,marine traffic,agriculture,etc.).However,those parameters were mainly predicted by using deterministic numerical weather prediction(NWP)models that include a wealth of uncertainties.The purpose of this study is to contribute in improving low-cost computationally ensemble forecasting of those parameters using analog ensemble method(AnEn)and comparing it to the operational mesoscale deterministic model(AROME)all over the main airports of Morocco using 5-yr period(2016-2020)of hourly datasets.An analog for a given station and forecast lead time is a past prediction,from the same model that has similar values for selected predictors of the current model forecast.Best analogs verifying observations form AnEn ensemble members.To picture seasonal dependency,two configurations were set;a basic configuration where analogs may come from any past date and a restricted configuration where analogs should belong to a day window around the target forecast.Furthermore,a new predictors weighting strategy is developed by using machine learning techniques(linear regression,random forest,and XGBoost).This approach is expected to accomplish both the selection of relevant predictors as well as finding their optimal weights,and hence preserve physical meaning and correlations of the used weather variables.Results analysis shows that the developed AnEn system exhibits a good statistical consistency and it significantly improves the deterministic forecast performance temporally and spatially by up to 50%for Bias(mean error)and 30%for RMSE(root-mean-square error)at most of the airports.This improvement varies as a function of lead times and seasons compared to the AROME model and to the basic AnEn configuration.The results show also that AnEn performance is geographically dependent where a slight worsening is found for some airports.展开更多
This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state fo...This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state for the period from 1998 to 2008. In addition, sea surface temperatures （SSTs） over equatorial Pacific Ocean were integrated in the analysis. The association between each of the meteorological-biometeorological parameters and clinical-reported malaria cases was examined by using Poisson distribution and log as link function between the two categories of dataset. The next step was the building of a model by using Poisson multiple regression models （GLMs） in order to know the weather variables that lead to statistically changes in clinical-reported malaria cases. The study revealed that an increase of I m.s1 of wind speed can lead to an increase of about 164% and 171% in the monthly occurrence of malaria at 95% confidence interval in derived savanna and humid forest zone respectively. Also, an increase of I ℃ in air temperature and sea surface temperature is associated with 53.4% and 29% increase in monthly malaria occurrence （CI： 95%） in derived savanna while an increase of 1 ℃ in air temperature and sea surface temperature is associated with 56.4% and 15.4% increase in monthly malaria occurrence at 95% confidence interval in humid forest zone of Ondo State展开更多
[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with soundi...[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with sounding data, the physical quantities and radar parameter of hail shooting and heavy convective rainfall weather are compared and analyzed. [Result] The smaller Sl is conducive to the generation of hail weather. When K〉 35 ~C, the probability for occurrence of heavy rainfall weather is significantly increased; when K〈20 ^（3, the probability for occurrence of heavy rainfall weather is significantly decreased. When CAPE value is greater than 1 500 J/KG, the probability for occurrence of hail weather is significantly decreased, while the probability for occurrence of heavy rainfall weather is significantly in- creased. The possibility for occurrence of hail monomer is small when the wind shear is less than 5 m/s; and it is large while wind shear is greater than 20 m/s. The radar forecasting indexes of hail monomer is as follows： VIL value reaches 35 kg/m2 （May）, 43 kg/m2 （June and July）, the monomer height is greater than 9 km, the maximum reflectivity factor is larger than 60 dBz, strong center height reaches 3.3 km （May）, 4.3 km （June） and 5.5 km （July）; VlL value of heavy rainfall monomer generally is below 25 kg/m2. [Conclusion] The paper provides basis form prediction of hail and heavy rainfall.展开更多
This study deals with the climatic parameters and the climatic differences in Elazig and its close regions (cities of Malatya, Tunceli, Bing?l, Erzincan). Data on mean monthly temperature, daily maximum-minimum temper...This study deals with the climatic parameters and the climatic differences in Elazig and its close regions (cities of Malatya, Tunceli, Bing?l, Erzincan). Data on mean monthly temperature, daily maximum-minimum temperature, rela-tive humidity, pressure, wind speed, rainfall, solar radiation and sunshine duration were analyzed and modeled for 10-year period, from 1994 to 2003. Malatya city was the hottest area whole period, while the Erzincan city was the coldest area. Maximum temperatures were at highest values in Tunceli. Minimum temperatures reached the warmest values in the Malatya. Erzincan city was the most humid area almost throughout the period while Malatya was the least humid area. Wind speed reached the highest values in the Elazig and the lowest values in the Tunceli. Pressure reached the highest values in the Malatya and the lowest values in the Erzincan. Direct solar radiation reached the highest val-ues in the Tunceli and the lowest values in the Erzincan. Sunshine duration reached the highest values in the Malatya and the lowest values in the Erzincan. A regression analysis was carried out by using the linear regression technique to model the climatic parameters. The models developed can be used in any study related to climatic and its effect on the environment and energy. The models developed in this study can be used for future predictions of the climatic parame-ters and analysing the environmental and energy related issues in Elazig and its close regions (cities of Malatya, Tun-celi, Bing?l, Erzincan).展开更多
The distinct element method（DEM） incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the...The distinct element method（DEM） incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the changing laws of microscopic parameters from observed decaying properties of rocks during weathering. The changing laws of macroscopic mechanical properties of typical rocks were summarized based on the existing research achievements. Parametric simulations were then conducted to analyze the relationships between macroscopic and microscopic parameters, and to derive the changing laws of microscopic parameters for the DEM model. Equipped with the microscopic weathering laws, a series of DEM simulations of basic laboratory tests on weathered rock samples was performed in comparison with analytical solutions. The results reveal that the relationships between macroscopic and microscopic parameters of rocks against the weathering period can be successfully attained by parametric simulations. In addition, weathering has a significant impact on both stressestrain relationship and failure pattern of rocks.展开更多
The tea crop provides income and employment to rural populations in many countries. In Kenya, tea, which is the leading export commodity crop, is grown in highlands east and west of the Rift Valley at altitudes rangin...The tea crop provides income and employment to rural populations in many countries. In Kenya, tea, which is the leading export commodity crop, is grown in highlands east and west of the Rift Valley at altitudes ranging from 1300 m to 2700 m above mean sea level. Variable responses of tea genotypes to different environments have been demonstrated. This affects the growth, productivity, and quality of tea. However, most tea husbandry practices are uniform across tea growing regions leading to variations in yields and quality in the different environments. Understanding causes of variations in tea growth parameters and yields to varying environments is vital to optimizing husbandry practices for maximization of productivity. The responses in growth and yield parameters of clonal tea to locations of production and their contribution to yields were compared. A genotype × environment trial was conducted in three sites (Kangaita, Timbilil and Kipkebe). At each site, a trial comprising 20 cultivars was laid in a randomized complete design replicated 3 times. Yields, yield components and climatic data were collected then subjected to analysis of variance and regression analysis. There were significant (p ≤ 0.05) yield variations between clones and locations. Yields ranged from 5162 kg mt/ha on clone TRFK 303/577 at Kipkebe to 935 kg mt/ha/year on clone TRFK 7/3 in Kangaita, surpassing the maximum variation possible postulated in earlier studies. The responses of the tea yield components to weather parameters varied with genotypes and environments. Shoot growth rates in Timbilil (r = 0.476)) and shoot density (Kangaita (r = 0.652) significantly (p ≤ 0.05)) correlated with yields. Yield components and weather parameters contribution to the total yield also varied with locations. The variations demonstrated that not all yield components can be used universally as yield indicators for clonal selection in different locations. For optimal production, selected tea clones should therefore be tested before adoption for commercial planting in other locations.展开更多
Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions b...Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.展开更多
基金supported by Automatic Observation System for Cloud, Visibility and Weather Phenomena (Grant No. GYHY200806031)Carbon Satellites Verification Systems and Comprehensive Observations (Grant Nos. GJHZ1207 and XDA05040302)
文摘A new present weather identifier(PWI) based on occlusion and scattering techniques is presented in the study. The present weather parameters are detectable by the meteorological optical range(MOR) approximately up to 50 km and by droplets with diameters ranging from 0.125 mm to 22 mm with velocities up to 16 m s-1. The MOR error is less than 8% for the MOR within 10 km and less than 15% for farther distances. Moreover, the size errors derived from various positions of the light sheet by the particles were checked within ± 0.1 mm ± 5%. The comparison shows that the MOR, in a sudden shower event, is surprisingly consistent with those of the sentry visibility sensors(SVS) with a correlation coefficient up to 98%. For the rain amounts derived from the size and velocity of the droplets, the daily sums by the PWI agree within 10% of those by the Total Rain Weighing Sensor(TRwS205) and the rain gauge. Combined with other sensors such as temperature, humidity, and wind, the PWI can serve as a present weather sensor to distinguish several weather types such as fog, haze, mist, rain, hail, and drizzle.
文摘Knowing crop water uptake each day is useful for developing irrigation scheduling. Many technologies have been used to estimate daily crop water use. Sap flow is one of the technologies that measure water flow through the stem of a plant and estimate daily crop water uptake. Sap flow sensor is an effective direct method for measuring crop water use, but it is relatively expensive and requires frequent maintenance. Therefore, alternative methods, such as evapotranspiration based on FAO 56 Penman-Monteith equation and other weather parameters were evaluated to find the correlation with sap flow. In this study, Dynamax Flow 32-1K sap flow system was utilized to monitor potato water use. The results show sap flow has a strong correlation with evapotranspiration (RMSE = 1.34, IA = 0.89, MBE = -0.83), solar radiation (RMSE = 2.25, IA = 0.72, MBE = -1.80), but not with air temperature, relative humidity, wind speed, and vapor pressure. It is worth noting that the R<sup>2</sup> between sap flow and relative humidity was 0.55. This study has concluded that daily evapotranspiration and solar radiation can be used as alternative methods to estimate sap flow.
文摘Surface weather parameters detain high socioeconomic impact and strategic insights for all users,in all domains(aviation,marine traffic,agriculture,etc.).However,those parameters were mainly predicted by using deterministic numerical weather prediction(NWP)models that include a wealth of uncertainties.The purpose of this study is to contribute in improving low-cost computationally ensemble forecasting of those parameters using analog ensemble method(AnEn)and comparing it to the operational mesoscale deterministic model(AROME)all over the main airports of Morocco using 5-yr period(2016-2020)of hourly datasets.An analog for a given station and forecast lead time is a past prediction,from the same model that has similar values for selected predictors of the current model forecast.Best analogs verifying observations form AnEn ensemble members.To picture seasonal dependency,two configurations were set;a basic configuration where analogs may come from any past date and a restricted configuration where analogs should belong to a day window around the target forecast.Furthermore,a new predictors weighting strategy is developed by using machine learning techniques(linear regression,random forest,and XGBoost).This approach is expected to accomplish both the selection of relevant predictors as well as finding their optimal weights,and hence preserve physical meaning and correlations of the used weather variables.Results analysis shows that the developed AnEn system exhibits a good statistical consistency and it significantly improves the deterministic forecast performance temporally and spatially by up to 50%for Bias(mean error)and 30%for RMSE(root-mean-square error)at most of the airports.This improvement varies as a function of lead times and seasons compared to the AROME model and to the basic AnEn configuration.The results show also that AnEn performance is geographically dependent where a slight worsening is found for some airports.
文摘This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state for the period from 1998 to 2008. In addition, sea surface temperatures （SSTs） over equatorial Pacific Ocean were integrated in the analysis. The association between each of the meteorological-biometeorological parameters and clinical-reported malaria cases was examined by using Poisson distribution and log as link function between the two categories of dataset. The next step was the building of a model by using Poisson multiple regression models （GLMs） in order to know the weather variables that lead to statistically changes in clinical-reported malaria cases. The study revealed that an increase of I m.s1 of wind speed can lead to an increase of about 164% and 171% in the monthly occurrence of malaria at 95% confidence interval in derived savanna and humid forest zone respectively. Also, an increase of I ℃ in air temperature and sea surface temperature is associated with 53.4% and 29% increase in monthly malaria occurrence （CI： 95%） in derived savanna while an increase of 1 ℃ in air temperature and sea surface temperature is associated with 56.4% and 15.4% increase in monthly malaria occurrence at 95% confidence interval in humid forest zone of Ondo State
基金Supported by Science and Technology Development Project of Shandong Science and Technology Hall(2010GSF10805)National Natural Science Foundation of China(41140036)~~
文摘[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with sounding data, the physical quantities and radar parameter of hail shooting and heavy convective rainfall weather are compared and analyzed. [Result] The smaller Sl is conducive to the generation of hail weather. When K〉 35 ~C, the probability for occurrence of heavy rainfall weather is significantly increased; when K〈20 ^（3, the probability for occurrence of heavy rainfall weather is significantly decreased. When CAPE value is greater than 1 500 J/KG, the probability for occurrence of hail weather is significantly decreased, while the probability for occurrence of heavy rainfall weather is significantly in- creased. The possibility for occurrence of hail monomer is small when the wind shear is less than 5 m/s; and it is large while wind shear is greater than 20 m/s. The radar forecasting indexes of hail monomer is as follows： VIL value reaches 35 kg/m2 （May）, 43 kg/m2 （June and July）, the monomer height is greater than 9 km, the maximum reflectivity factor is larger than 60 dBz, strong center height reaches 3.3 km （May）, 4.3 km （June） and 5.5 km （July）; VlL value of heavy rainfall monomer generally is below 25 kg/m2. [Conclusion] The paper provides basis form prediction of hail and heavy rainfall.
文摘This study deals with the climatic parameters and the climatic differences in Elazig and its close regions (cities of Malatya, Tunceli, Bing?l, Erzincan). Data on mean monthly temperature, daily maximum-minimum temperature, rela-tive humidity, pressure, wind speed, rainfall, solar radiation and sunshine duration were analyzed and modeled for 10-year period, from 1994 to 2003. Malatya city was the hottest area whole period, while the Erzincan city was the coldest area. Maximum temperatures were at highest values in Tunceli. Minimum temperatures reached the warmest values in the Malatya. Erzincan city was the most humid area almost throughout the period while Malatya was the least humid area. Wind speed reached the highest values in the Elazig and the lowest values in the Tunceli. Pressure reached the highest values in the Malatya and the lowest values in the Erzincan. Direct solar radiation reached the highest val-ues in the Tunceli and the lowest values in the Erzincan. Sunshine duration reached the highest values in the Malatya and the lowest values in the Erzincan. A regression analysis was carried out by using the linear regression technique to model the climatic parameters. The models developed can be used in any study related to climatic and its effect on the environment and energy. The models developed in this study can be used for future predictions of the climatic parame-ters and analysing the environmental and energy related issues in Elazig and its close regions (cities of Malatya, Tun-celi, Bing?l, Erzincan).
基金funded by the National Basic Research Programs of China(Grant Nos.2011CB013504 and 2014CB046901)the National Funds for Distinguished Young Scientists of China(Grant No.51025932)the National Nature Science Foundation of China(Grant No.41372272)
文摘The distinct element method（DEM） incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the changing laws of microscopic parameters from observed decaying properties of rocks during weathering. The changing laws of macroscopic mechanical properties of typical rocks were summarized based on the existing research achievements. Parametric simulations were then conducted to analyze the relationships between macroscopic and microscopic parameters, and to derive the changing laws of microscopic parameters for the DEM model. Equipped with the microscopic weathering laws, a series of DEM simulations of basic laboratory tests on weathered rock samples was performed in comparison with analytical solutions. The results reveal that the relationships between macroscopic and microscopic parameters of rocks against the weathering period can be successfully attained by parametric simulations. In addition, weathering has a significant impact on both stressestrain relationship and failure pattern of rocks.
文摘The tea crop provides income and employment to rural populations in many countries. In Kenya, tea, which is the leading export commodity crop, is grown in highlands east and west of the Rift Valley at altitudes ranging from 1300 m to 2700 m above mean sea level. Variable responses of tea genotypes to different environments have been demonstrated. This affects the growth, productivity, and quality of tea. However, most tea husbandry practices are uniform across tea growing regions leading to variations in yields and quality in the different environments. Understanding causes of variations in tea growth parameters and yields to varying environments is vital to optimizing husbandry practices for maximization of productivity. The responses in growth and yield parameters of clonal tea to locations of production and their contribution to yields were compared. A genotype × environment trial was conducted in three sites (Kangaita, Timbilil and Kipkebe). At each site, a trial comprising 20 cultivars was laid in a randomized complete design replicated 3 times. Yields, yield components and climatic data were collected then subjected to analysis of variance and regression analysis. There were significant (p ≤ 0.05) yield variations between clones and locations. Yields ranged from 5162 kg mt/ha on clone TRFK 303/577 at Kipkebe to 935 kg mt/ha/year on clone TRFK 7/3 in Kangaita, surpassing the maximum variation possible postulated in earlier studies. The responses of the tea yield components to weather parameters varied with genotypes and environments. Shoot growth rates in Timbilil (r = 0.476)) and shoot density (Kangaita (r = 0.652) significantly (p ≤ 0.05)) correlated with yields. Yield components and weather parameters contribution to the total yield also varied with locations. The variations demonstrated that not all yield components can be used universally as yield indicators for clonal selection in different locations. For optimal production, selected tea clones should therefore be tested before adoption for commercial planting in other locations.
基金supported by the Special Fund for Meteorological Scientific Research in the Public Interest (Grant No. GYHY201506002, CRA40: 40-year CMA global atmospheric reanalysis)the National Basic Research Program of China (Grant No. 2015CB953703)+1 种基金the Intergovernmental Key International S & T Innovation Cooperation Program (Grant No. 2016YFE0102400)the National Natural Science Foundation of China (Grant Nos. 41305052 & 41375139)
文摘Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.
