Dengue Fever Epidemiological Status and Relationship with Meteorological Variables in Guangzhou, Southern China, 2007-2012

Ecological methodology plus negative binomial regression were used to identify dengue fever （DF） epidemiological status and its relationship with meteorological variables. From 2007 to 2012, annual incidence rate of DF in Guangzhou was 0.33, 0.11, 0.15, 0.64, 0.45, and 1.34 （per 100 000） respectively, showing an increasing trend. Each 1℃ rise of temperature corresponded to an increase of 10.23% （95% CI 7.68% to 12.83%） in the monthly number of DF cases, whereas l hPa rise of atmospheric pressure corresponded to a decrease in the number of cases by 5.14% （95% CI： 7.10%-3.14%）. Likewise, each one meter per second rise in wind velocity led to an increase by 43.80% or 107.53%, and one percent rise of relative humidity led to an increase by 2.04% or 2.19%.

Variation trends of meteorological variables and their impacts on potential evaporation in Hailar region

Evaporation, which is an important factor in the water balance at the basin scale, is a critical variable in the determination of local available water resources. Since the potential evaporation is mainly influenced by meteorological variables, it is necessary to investigate the extent to which different meteorological variables affect the potential evaporation. The aim of this study was to explore the variation trends of different meteorological variables, and their impacts on the potential evaporation. This study selected the Hailar Meteorological Station of the Hailar region, which is situated in a cold, semi-arid, and sub-humid region, as a case study site. Based on observed daily meteorological data from 1951 to 2009, the potential evaporation was calculated with the Penman formula, and the variations of meteorological variables were investigated with the nonparametric Mann-Kendall test. The correlation between the potential evaporation and each meteorological variable at annual and seasonal scales was also analyzed. The results show that the annual and seasonal potential evaporation and air temperature present increasing trends, whereas the wind speed, sunshine duration, and relative humidity present decreasing trends. Among the meteorological variables, the air temperature and relative humidity are the key factors that affect potential evaporation at different time scales, and the impacts of other meteorological variables on the potential evaporation are not significant and vary with time scales.

Temporal variations of CO_2 concentration near land surface and its response to meteorological variables in Heihe River Basin, northwest China

Atmospheric CO2 concentration （CC） near land surface and meteorological variables have been measured at four sites, named Yeniugou （alpine meadow and permafrost）, Xishui （mountainous forest）, Linze （oasis edge） and Ejina （lower desert）, respectively, in Heihe River Basin, northwest China. The results showed that, the half hourly CC at night was larger than in daytime, and the daily averaged CC was the largest in winter. The averaged CC of 932 d at the Linze was about 418 ppm, was about 366 ppm in the 762 d at the Ejina. In the same period from September 23 to November 9, 2004, the averaged CC was about 625,334, 436 and 353 ppm, at Yeniugou, Xishui, Linze and Ejina, respectively. The linear relationship between daily averaged CC and air temperature T was negative, between CC and relative humidity （RH） was positive. The linear CC-atmospheric pressure （A P） relationship was negative at the Linze and Yeniugou, was positive at the Ejina. The relationship between CC and global radiation R was exponent, and soil temperature Ts was negative linear, and soil water content was complex. The correlation between CC and wind speed was not existent. Using meteorological variables together to simulate CC, could give good results.

Temperature Inversions,Meteorological Variables and Air Pollutants and Their Influence on Acute Respiratory Disease in the Guadalajara Metropolitan Zone,Jalisco,Mexico

The presence of temperature inversions (TI), concentration of air pollutants (AP) and meteorological variables (MV) affect the welfare of the population, creating public health problems (acute respiratory diseases ARDs, among others). The Guadalajara Metropolitan Zone (GMZ) experiences high levels of air pollution, which associated with the presence of temperature inversions and meteorological variations is conducive to the incidence of ARDs in children. The aim of this work is to evaluate the TI, MV, AP and their influence on the ARDs in children under five years in the GMZ from 2003 to 2007. In this period, the moderate and strong TI are the most frequent presenting from November to May. The AP shows a variable behavior during the year and between years, with the highest concentration of particles less than 10 microns (PM10), followed by ozone (O3), nitrogen dioxide (NO2), nitrogen oxides (NOX), carbon monoxide (CO) and sulfur dioxide (SO2), the most affected areas are the southeast of the GMZ. Annual arithmetic mean is 213,510 ± 41,209 ARDs consultations. The most important diseases are acute respiratory infections (98.0%), followed by pneumonia and bronchopneumonia (1.1%), asthma and status asthmaticus (0.5%) and streptococcal pharyngitis and tonsillitis (0.4%). Months with most inquiries were from October to March, mainly in the southeast, south and center of the city, coinciding with high levels of AP. Statistical analysis shows that the TI have significant correlation with ARDs in three years, temperature (Temp) in two, relative humidity (RH) in two, wind speed (WS) in three, wind direction (WD) in two, while that air pollutants NOX and NO2 showed significant correlation with ARDs throughout the period. CO and SO2 showed significance in two years, while the PM10 and O3 in one.

Association between the incidence of typhoid and paratyphoid fever and meteorological variables in Guizhou, China

Background Typhoid/paratyphoid fever （TPF） is endemic in Guizhou.We conducted wavelet analysis and Spearman＇s rank correlation analysis to explore the impact of meteorological variations on TPF infection in Guizhou,in an attempt to assess the risk factors associated with TPF epidemics.Methods We examined the association between TPF incidence in Guizhou and temperature,precipitation and relative humidity using 24 years of data from 1984 to 2007.Periodicities of TPF incidence and the impact of climate factors on the TPF were detected by Spearman＇s rank correlation and wavelet analysis,Results Temperature and precipitation with a 1-month lag were positively correlated with the monthly incidence of TPF.The multiyear incidence pattern of TPF in Guizhou was explicitly periodic.Moreover,the association and driving effect of precipitation on TPF were observed,and the results showed that the incidence of TPF in Guizhou had a closer correlation with precipitation than with temperature.Conclusions Safe water supply is the key issue for TPF control in Guizhou.Moreover,climate variation might impact the enteric infections,which may inform policy assessment for TPF control in Guizhou.

Data Quality Control Method of a New Drifting Observation Technology Named Drifting Air-Sea Interface Buoy

An integral quality control(QC)procedure that integrates various QC methods and considers the design indexes and operational status of the instruments for the observations of drifting air-sea interface buoy was developed in the order of basic in-spection followed by targeted QC.The innovative method of combining a moving Hampel filter and local anomaly detection com-plies with statistical laws and physical processes,which guarantees the QC performance of meteorological variables.Two sets of observation data were used to verify the applicability and effectiveness of the QC procedure,and the effect was evaluated using the observations of the Kuroshio Extension Observatory buoy as the reference.The results showed that the outliers in the time series can be correctly identified and processed,and the quality of data improved significantly.The linear correlation between the quality-controlled observations and the reference increased,and the difference decreased.The correlation coefficient of wind speed before and after QC increased from 0.77 to 0.82,and the maximum absolute error decreased by approximately 2.8ms^(-1).In addition,air pressure and relative humidity were optimized by 10^(-3)–10^(-2) orders of magnitude.For the sea surface temperature,the weight of coefficients of the continuity test algorithm was optimized based on the sea area of data acquisition,which effectively expanded the applicability of the algorithm.

Dew amount and its long-term variation in the Kunes River Valley,Northwest China

Dew is an essential water resource for the survival and reproduction of organisms in arid and semi-arid regions.Yet estimating the dew amount and quantifying its long-term variation are challenging.In this study,we elucidate the dew amount and its long-term variation in the Kunes River Valley,Northwest China,based on the measured daily dew amount and reconstructed values(using meteorological data from 1980 to 2021),respectively.Four key results were found:(1)the daily mean dew amount was 0.05 mm during the observation period(4 July-12 August and 13 September-7 October of 2021).In 35 d of the observation period(i.e.,73%of the observation period),the daily dew amount exceeded the threshold(>0.03 mm/d)for microorganisms;(2)air temperature,relative humidity,and wind speed had significant impacts on the daily dew amount based on the relationships between the measured dew amount and meteorological variables;(3)for estimating the daily dew amount,random forest(RF)model outperformed multiple linear regression(MLR)model given its larger R^(2) and lower MAE and RMSE;and(4)the dew amount during June-October and in each month did not vary significantly from 1980 to the beginning of the 21^(st) century.It then significantly decreased for about a decade,after it increased slightly from 2013 to 2021.For the whole meteorological period of 1980-2021,the dew amount decreased significantly during June-October and in July and September,and there was no significant variation in June,August,and October.Variation in the dew amount in the Kunes River Valley was mainly driven by relative humidity.This study illustrates that RF model can be used to reconstruct long-term variation in the dew amount,which provides valuable information for us to better understand the dew amount and its relationship with climate change.

Under-ice ambient noise in the Arctic Ocean: observations at the long-term ice station

Under-ice ambient noise in the Arctic Ocean is studied using the data recorded by autonomous hydrophones at the long-term ice station during the 9th Chinese National Arctic Research Expedition.Time-frequency analysis of two 7-s-long ice-induced noise samples shows that both ice collision and ice breaking noise have many outliers in the time-domain(impulsive characteristic)and abundant frequency components in the frequency-domain.Ice collision noise lasts for several seconds while the duration of ice breaking noise is much shorter(i.e.,less than tens of milliseconds).Gaussian distribution and symmetric alpha stable(sαs)distribution are used in this paper to fit the impulsive under-ice noise.The sαs distribution can achieve better performance as it can track the heavy tails of impulsive noise while Gaussian distribution fails.This paper also analyzes the meteorological variables during the under-ice noise observation experiment and deduces that the impulsive ambient noise was caused by the combined force of high wind speed and increasing atmosphere temperature on the ice canopy.The Pearson correlation coefficients between long-term power spectral density variations of under-ice ambient noise and meteorological variables are also studied in this paper.

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

Long-term,ground-based daily global solar radiation (DGSR) at Zhongshan Station in Antarctica can quantitatively reveal the basic characteristics of Earth’s surface radiation balance and validate satellite data for the Antarctic region.The fixed station was established in 1989,and conventional radiation observations started much later in 2008.In this study,a random forest (RF) model for estimating DGSR is developed using ground meteorological observation data,and a highprecision,long-term DGSR dataset is constructed.Then,the trend of DGSR from 1990 to 2019 at Zhongshan Station,Antarctica is analyzed.The RF model,which performs better than other models,shows a desirable performance of DGSR hindcast estimation with an R^2 of 0.984,root-mean-square error of 1.377 MJ m^(-2),and mean absolute error of 0.828 MJ m^(-2).The trend of DGSR annual anomalies increases during 1990–2004 and then begins to decrease after 2004.Note that the maximum value of annual anomalies occurs during approximately 2004/05 and is mainly related to the days with precipitation (especially those related to good weather during the polar day period) at this station.In addition to clouds and water vapor,bad weather conditions (such as snowfall,which can result in low visibility and then decreased sunshine duration and solar radiation) are the other major factors affecting solar radiation at this station.The high-precision,longterm estimated DGSR dataset enables further study and understanding of the role of Antarctica in global climate change and the interactions between snow,ice,and atmosphere.

Daily variation of radon gas and its short-lived progeny concentration near ground level and estimation of aerosol residence time

Atmospheric concentrations of radon（^（222）Rn） gas and its short-lived progenies^（218）Po,^（214）Pb, and^（214）Po were continuously monitored every four hours at the ground level in Jeddah city, Kingdom of Saudi Arabia. The measurements were performed three times every week, starting from November 2014 to October 2015. A method of electrostatic precipitation of positively charged^（218）Po and ^（214）Po by a positive voltage was applied for determining^（222）Rn gas concentration. The short-lived^（222）Rn progeny concentration was determined by using a filter holder connected with the alpha-spectrometric technique. The meteorological parameters（relative air humidity, air temperature, and wind speed） were determined during the measurements of^（222）Rn and its progeny concentrations.^（222）Rn gas as well as its short-lived progeny concentration display a daily and seasonal variation with high values in the night and early morning hours as compared to low values at noon and in the afternoon. The observed monthly atmospheric concentrations showed a seasonal trend with the highest values in the autumn/winter season and the lowest values in the spring/summer season. Moreover, and in parallel with alphaspectrometric measurements, a single filter-holder was used to collect air samples. The deposited activities of^（214）Pb and the long-lived^（222）Rn daughter ^（210）Pb on the filter were measured with the gamma spectrometric technique. The measured activity concentrations of^（214）Pb by both techniques were found to be relatively equal largely. The highest mean seasonally activity concentrations of ^（210）Pb were observed in the autumn/winter season while the lowest mean were observed in the spring/summer season. The mean residence time（MRT） of aerosol particles in the atmospheric air could be estimated from the activity ratios of ^（210）Pb/^（214）Pb.

Study on the Applicability of ERA5 Reanalysis Data at Lake Taihu

Lakes are an important component of the earth climate system. They play an important role in the study of basin weather forecasting, air quality forecasting, and regional climate research. The accuracy of driving variables is the basic premise to ensure the rationality of lake mode simulation. Based on the in-situ observations at Bifenggang site of the Lake Taihu Eddy flux Network from 2012 to 2017, this paper investigated temporal variations in temperature, relative humidity, wind speed, radiation components at different time scales (hourly, seasonal and interannual). ERA5 reanalysis data were compared with in-situ observation to quantify the error and evaluate the performance of reanalysis data. The results show that: 1) On the hourly scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. 2) On the seasonal variation scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. However, the descriptions of wind speed, relative humidity and downward short-wave have large deviations. 3) On the interannual scale, the ERA5 reanalysis data show a good performance for temperature, followed by downward longwave radiation, downward shortwave radiation and relative humidity.

Different Patterns of Changes in the Dry Season Diameter at Breast Height of Dominant and Evergreen Tree Species in a Mature Subtropical Forest in South China

Information on changes in diameter at breast height （DBH） is important for net primary production （NPP） estimates, timing of forest inventory, and forest management. In the present study, patterns of DBH change were measured under field conditions during the dry season for three dominant and native tree species in a monsoon evergreen broad-leaved forest in the Dinghushan Biosphere Reserve. For each tree species, different patterns of DBH change were observed. In the case of the fast-growing tree species Castanopsis chinensis Hance, large diurnal fluctuations occur, with a peak DBH in the early morning （around 05：00 h） that decreases to a minimum by about 14：00 h. Both Schima superba Gardn. et Chemp and Cryptocarya chinensis （Hance） Hemsh exhibited less diurnal swelling and shrinkage. Diurnal fluctuations for these species were observed on a few occasions over the period of observation. Graphical comparisons and statistical analysis of changes in DBH with meteorological variables indicate that for different trees, the different changes in DBH observed responded to different meteorological variables. Large stem changes were found to occur for Ca. chinensis trees that were associated with variations in solar radiation. However, both S. superba and Cr. chinensis were found to be less sensitive to solar radiation. Changes in the DBH of these two species were found to be controlled mainly by soil temperature and soil moisture. During the later dry season, with a lower soil temperature and soil moisture, all three tree species stopped growing and only negligible shrinkage, expansion, or fluctuation occurred, suggesting that the optimum time to measure tree growth in the Dinghushan Biosphere Reserve is the later dry season.

CHANGES OF PAN EVAPORATION IN THE UPPER REACH OF THE YANGTZE RIVER

The upper reach of the Yangtze River, 4 511 km long from west to east, contains a great amount of water resources of the Yangtze River Basin. This article studies the characteristics of the pan evaporation, the related meteorological variables, and their effects on the pan evaporation, based on the data of the daily pan evaporation （1980-2008） and other meteorological variables （1961-2008）. The results show that the linear trend of the pan evaporation has remarkable regional features, i.e., the decrease trend in the southwest and the increase trend in the northeast of the investigated region, and the Yangtze River is approximately the boundary of these trends. The meteorological variables have different effects on the pan evaporation depending on the fact that they are in the category the thermal variables or the dynamic variables. The thermal meteorological variables （i.e., air temperature, diurnal temperature range, and sunshine duration） have positive partial correlations with the pan evaporation, while the dynamic ones （air pressure, rainfall, and relateive humidity） have negative correlations with the pan evaporation. The correlation of the wind speed remains to be investigated.

An optimized approach for estimating benzene in ambient air within an air quality monitoring network

Benzene is a carcinogenic air pollutant for which European legislation has set an annual limit and criteria for the number of fixed monitoring sites within air quality networks(AQMN).However,due to the limited number of fixed sites for benzene measurement,exposure data are lacking.Considering the relationship between benzene levels and other variables monitored within an AQMN,such as NO_(2),O_(3),temperature,solar radiation,and accumulated precipitation,this study proposes an approach for estimating benzene air concentrations from the related variables.Using the data of the aforementioned variables from23 fixed stations during 2016-2017,the proposed approach was able to forecast benzene concentration for 2018 with high confidence,providing enriched data on benzene exposure and its trends.Moreover,the spatial distribution of the estimated versus the most representative benzene levels was quite similar.Finally,an artificial neural network identified the most representative fixed benzene monitoring sites within the AQMN.

Gaseous pollutant transport from an underground parking garage in a Mediterranean multi-story building—Effect of temporal resolution under varying weather conditions

Indoor air dynamics and quality in high density residential buildings can be complex as it is affected by both building parameters,pollution sources,and outdoor meteorological conditions.The present study used CONTAM simulations to investigate the intra-building transport and concentration of an inert pollutant continuously emitted from an underground garage of a 15-floor building under moderate Mediterranean weather.The effects of outdoor meteorological conditions(air temperature,wind speed and direction)on indoor distribution of the emitted pollutant was tested under constant conditions.The importance of using actual transient meteorological data and the impact of their temporal resolution on calculated concentrations and exposure levels were also investigated.Vertical profiles of air exchange rate(AER)and CO concentration were shown to be sensitive to indoor-outdoor temperature difference,which controls the extent of the stack effect and its importance relative to wind effect.Even under constant conditions,transient mode simulations revealed that the time needed for pollutant distribution to reach steady state can be quite long(>24h in some cases).The temporal resolution(Ih vs.8h)of the meteorological data input was also found to impact calculated exposure levels,in an extent that varied with time,meteorological conditions and apartment position.