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Social pension is a new supporting method for the elderly from family to society. Its solutions integrate many kinds of social services in the community and the surrounding areas, which can effectively make up for the deficiencies of various existing pension models. Although the exploration of the community pension model has been continuously deepened, the problem of population aging is becoming increasingly intractable. There are also some problems in the community socialized pension, causing a vigorous discussion on its feasibility and consciousness. In this context, this work investigated the feasibility and consciousness of community social endowment. Based on the discussion of community pension consciousness, the feasibility and effective way of community endowment were analyzed, which can promote the construction of social pension service system and provide corresponding theoretical and practical guidance for social pension practice.

Desert steppe soil security issues have been the focus of attention. Therefore, to understand the impact of industrial activities on the soil quality of desert grasslands, this experiment investigated the Gaoshawo Industrial Concentration Zone in Yanchi County. Based on the distance and direction from the industrial park, sample plots were established at intervals of 1–2 km. A total of 82 surface soil samples (0–20 cm) representing different pollution sources were collected. The samples were analysed for pH, total nitrogen, total phosphorus, available phosphorus, available potassium, organic matter, copper (Cu), cadmium (Cd), chromium (Cr), lead (Pb), and zinc (Zn). The desert steppe soil quality was analysed based on the integrated fertility index (IFI) and the Nemerow pollution index (PN), followed by the calculation of the comprehensive soil quality index (SQI), which considers the most suitable soil quality indicators through a geostatistical model. The results showed that the IFI was 0.393, indicating that the soil fertility was relatively poor. Excluding the available potassium, the nugget coefficients of the fertility indicators were less than 25% and showed strong spatial autocorrelation. The average values of Cu, Cd, Cr, Pb and Zn were 21.64 ± 3.26, 0.18 ± 0.02, 44.99 ± 21.23, 87.18 ± 25.84, and 86.63 ± 24.98 mg·kg−1, respectively; the nugget coefficients of Cr, Pb and Zn were 30.79–47.35%. Pb was the main element causing heavy metal pollution in the study area. Higher PN values were concentrated north of the highway in the study area, resulting in lower soil quality in the northern region and a trend of decreasing soil quality from south to north. The results of this research showed that the average SQI was 0.351 and the soil quality was extremely low. Thus, industrial activities and transportation activities in the Gaoshawo Industrial Zone significantly impact the desert steppe soil quality index.

Millimeter-wave cloud radar (MMCR) provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds. Therefore, MMCR has been widely applied in cloud observations. However, due to the influence of non-meteorological factors such as insects, the cloud observations are often contaminated by non-meteorological echoes in the clear air, known as clear-air echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The characteristics of clear-air echoes are studied here by combining data from four devices: an MMCR, a laser-ceilometer, an L-band radiosonde, and an all-sky camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions. The recognition accuracy can reach up to 95.86% for the simple cases when cloud echoes and clear-air echoes are separate, and 88.38% for the complicated cases when low cloud echoes and clear-air echoes are mixed.

Frequent emergency room (ER) visits occur for acute symptoms of hypertension or related complications in Beijing, China. Among the meteorological variables, atmospheric pressure directly relates to weather conditions and is hardly affected by artificial factors. In the studies of weather conditions and hypertension-related risks, atmospheric pressure is rarely found in literatures. Based on records of ER visit related to hypertension from three major hospitals in Beijing, from 2008 to 2012, the daily maximum (Pmax) and minimum (Pmin) atmospheric pressures were investigated in this study to identify the influences of air pressure on ER visits. Advanced time series models were utilized in quantifying their associations. In addition, major air pollutants and other meteorological variables including temperature, solar duration, and humidity were incorporated in the multivariate models to reveal the independent association between atmospheric pressure and ER visits. The results indicated the following: 1. The number of ER visits positively correlates with all atmospheric pressure metrics in both bivariate and partial correlation analyses. 2. The estimated relative risk (RR) corresponding to 1 hPa change in Pmax indicated a significant effect (Pmax = 1029 hPa, RR = 1.107, 95% CIs: 1.034-1.185) from high Pmax on short lag terms. RR for males and the elders grew prominently at lag 1 d, whereas females responded to Pmax at lag 4 d. 3. The middle-aged group (45–65 years) was threatened by extremely low Pmin with one day lag. 4. As for young (< 45 years) hypertensive patients, no effect from atmospheric pressure was identified. This study may provide new evidence that extreme atmospheric pressure is an independent inducer of hypertension-related symptoms or complications.

Previous studies seldom touch on aspects of psychotherapeutic encounters between therapists and clients with particular disorders (such as depression). Little attention has been paid to the sequence organization of psychotherapeutic interaction between therapists and clients with depression in Chinese medical settings. By adopting conversation analysis, we investigated the specifics of psychotherapeutic encounters, specifically, the transformative sequences of psychotherapeutic interaction between therapists and Chinese adolescents with depression. We identified the fourth aspect of clients’ experience transformed in the Chinese psychotherapeutic interaction with adolescents with depression: cognition, and described how the sequential organization of therapists’ actions facilitates the momentary transformation of clients’ experience (i.e., the transformation of cognition, referent, emotion, and relation) in the psychotherapeutic processes. This study not only adds to the conversation analytic study on the transformative sequences in psychotherapeutic interaction but also sheds some light on the study of how therapists transform clients’ experience in Chinese psychotherapeutic interaction.

Ambient air temperature is a key index that affects human health, including mortality risks of cardiovascular disease (CVD). This study quantitatively investigated CVD mortality burden with respect to various segments across the climatic temperature range. Daily data on average temperature and CVD deaths in nine Chinese cities during 2010–2016 were collected for the study. The association between temperature and city-specific CVD mortality was investigated with a distributed lag nonlinear model across lag 0–21 days for cold temperature and lag 0–2 days for hot temperature, and then pooled the association results in a multivariate meta-analysis to derive the pooled estimates of temperature on CVD mortality at national level. Attributable fractions of CVD mortality to cold- and heat-related (i.e., at temperatures below and above the minimum mortality temperature [MMT]) were calculated. In addition, temperature was further separated at 1 °C intervals of ambient temperature and the attributable fractions of each range were calculated. The results showed that the MMT varied from the 71th to 79th percentiles of temperature in nine Chinese cities, centering at 76th at national level. In total, 16.88% of CVD mortality was attributable to nonoptimal temperature, ranging from 9.73% in Hefei to 24.48% in Nanjing. Cold temperature was responsible for most CVD death burden, with a fraction of 14.62%, compared with 2.26% CVD mortality for heat at overall level. The results of temperature stratification suggested that the highest CVD deaths due to temperature fall within moderate cold. Specifically, the highest attributable fractions were at 7 °C, 7 °C, 8 °C, 4 °C, 5 °C, 4 °C, 4 °C, 5 °C, and 6 °C for Harbin, Changchun, Shenyang, Beijing, Shijiazhuang, Nanjing, Hefei, Shanghai, and Chengdu, respectively. Furthermore, the highest CVD deaths due to temperature were near at the start and end time of heating for five northern cities (Harbin, Changchun, Shenyang, Beijing, and Shijiazhuang). Hence, moderately cold temperature plays a noticeable role in impact mortality. Although moderate cold had a slightly lower relative risk than extreme cold, it occurred on more days than did extreme cold. Finally, the cumulative total counts of CVD deaths caused by moderate cold were the largest. We should pay more attention to the adverse health effects of moderate cold in the future. Additionally, the government and heating departments should slow down the rate of increase (or decrease) temperature at the start (or end) time of heating during moderate time in northern China. The findings have important implications for health promotion and disease prevention strategies of adverse temperatures.

Based on Kirchhoff approximation, a prediction method on the echo characteristics of a SCUBA diver was presented. Since a scuba diver needs to swing his large fins to overcome the water resistance caused by their diving equipment. As a result, the swing process of the fins may affect the backscattering characteristic significantly. Therefore, a 3D dynamic model of a SCUBA diver’s single swing fins was built. The motion process of the diver’s single swinging fins is split into 200 frames. The postures of the diver are different in the 200 frames, especially that of the fins. Six typical frames are selected among the 200 frames, which are frames 0, 40, 80, 120, 160, 200 and can represent the whole swing process. The echo waves and surface highlights of different postures at two incidence angles are compared. The study shows that for the head incidence (θ 0 = 00)the acoustic contribution is mainly from body and fins, and the acoustic scattering echo amplitude of the fins varies periodically, since the cross section of the fins varies periodically as the diver swing. For left side incidence the acoustic contribution is mainly from the diver’s leg and air cylinder. Besides that, there is almost no change in the echo characteristics change little for different postures.

Understanding the extent to which demographic changes may affect the prospects of sustainable development is a priority for both academics and policy makers. Accordingly, we attempted to explore the population growth limit of the Xihaigu Mountain area in China. To analyze the optimum population at the county level, the relationship curve between population size and environmental quality was fitted using panel data (2009–2018). The sustainable population size of each county was determined by integrating the population carrying capacity of land resources and optimum population. The results show that the relationship between regional population size and environmental quality conforms to an inverted N-shaped curve. To maintain sustainable development, the population size of Tongxin, Xiji, and Haiyuan should be in the range of 320,800–379,800, 315,800–416,900, and 333,500–416,900, respectively. The current population size of other counties should be maintained, and their surplus construction lands are acceptable to be used for environmentally friendly industries rather than population expansion. We demonstrated a practical approach to calculate a dynamic range of population size under the dual constraints of resource and environment, which overcomes the shortcoming of only considering the maximum carrying capacity to a limited extent. We also identified the population boundary in a “steady-state economy” and quantified planetary boundaries of population in Xihaigu Mountain area using a dynamic sustainable population size. The findings provide decision-making references for the local government.

An error decomposition method is used to analyze and track seasonal error sources of the Integrated Multi‐satellitE Retrievals for the Global Precipitation Measurement (IMERG) Version 05 daily precipitation estimations, including Early‐, Late‐, and Final‐run products (IMERG‐DE, IMERG‐DL, and IMERG‐DF, respectively) over the Sichuan Basin of China from January 2016 to December 2018. The method decomposes the total errors into hit bias, missed precipitation, and false precipitation, which can be attributed to the satellite retrieval processes. Results show that in spring, all the estimations had serious overestimation in the northwest of the basin. The major error source is the hit bias of the intensity over 25 mm/day. In summer, the three IMERG estimations overestimated the precipitation in almost the entire Sichuan Basin, especially in the south and southwest. The principal determinants of the error sources are missed and false light precipitation (

Temperature change between neighboring days (TCN) is an important trigger for cardiovascular diseases, but the modulated effects by seasonal temperature trends have been barely taken into account. A quantified comparison between impacts of positive TCNs (temperature rise) and negative situations (temperature drop) is also needed. We evaluated the associations of TCNs with emergency room (ER) visits for coronary heart disease (CHD) and cerebral infarction (CI) in Beijing, China, from 2008 to 2012. A year was divided into two segments dominated by opposite temperature trends, quasi-Poisson regression with distributed lag nonlinear models estimating TCN-morbidity relations were employed, separately for each period. High morbidities of CHD and CI both occurred in transitional seasons accompanied by large TCNs. Under warming backgrounds, positive TCNs increased CHD risk in patients younger than 65 years, and old people showed limited sensitivity. In the cooling periods, negative TCNs induced CHD risk in females and the elderly; the highest RR showed on lag 6 d. In particular, a same diurnal temperature decrease (e.g., - 2°C) induced greater RR (RR = 1.113, 95% CIs: 1.033-1.198) on old people during warming periods than cooling counterparts (RR = 1.055, 95% CIs: 1.011-1.100). Moreover, positive TCNs elevated CI risk regardless of background temperatures, and males were particularly vulnerable. Seasonal temperature trends modify TCN-cardiovascular morbidity associations significantly, which may provide new insights into the health impact of unstable weathers.

A study area was selected from the industrial region of Gaoshawo Town, Yanchi County, Ningxia, to explore the level of heavy metal pollution in desert grasslands due to industrial activities. A total of 82 surface soils were collected, and the concentration of heavy metals, namely, Cu, Cd, Cr, Pb, Zn, Mn, and Co, was determined by ICP-AES (atomic emission spectrometer) (HK-8100); the average values were 21.64 ± 3.26, 0.18 ± 0.02, 44.99 ± 21.23, 87.18 ± 25.84, 86.63 ± 24.98, 570.49 ± 171.57, and 17.96 ± 9.96 mg kg−1. The single-factor, Nemerow pollution, and potential ecological risk index methods were used to evaluate the status of soil heavy metal pollution and the contribution from the major sources identified by the receptor model. The results showed that 9.09% of the samples were slightly polluted, 32.47% of the samples were moderately polluted, and 58.41% of the samples were heavily polluted. The comprehensive potential ecological risk index indicated that 90.79% of the samples had moderate ecological risk. It was verified from the models and spatial distribution maps that Cr, Co, Zn, and Mn are mainly contributed by the industrial sources that account for 55.04%, 92.13%, 50.05%, and 48.77% of these heavy metals, respectively. The heavily contaminated areas are distributed around the industrial park. A total of 70.63% and 77.83% of Cu and Pb are contributed by transportation sources, respectively, with the concentrations decreasing from southwest to northeast. The contribution from agricultural activities to Cd is 77.02%, with concentrations largely distributed in the north of the highway. This study showed that the existence of the Gaoshawo Industrial Zone and the corresponding industrial and transportation activities have a significant impact on the grassland soil environment.

The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation (QPE) based on the Z–R (reflectivity factor–rain rate) relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity (VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands (S-, C- and X-band) of dual-polarized radars and to reduce overestimation errors in Z–R relationship–based QPEs. After the reflectivity was corrected by the algorithms using average VPR (AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient (AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z–R relationship–based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE (root-mean-square error), RMAE (relative mean absolute error) and RMB (relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.

Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land–atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.

Annual precipitation anomalies over eastern China are characterized by a north–south dipole pattern, referred to as the “southern flooding and northern drought” pattern (SF/ND), fluctuating on decadal time scales. Previous research has suggested possible links with oceanic forcing, but the underlying physical mechanisms by which sea surface temperature (SST) variability impacts the dipole pattern remains unclear. Idealized atmospheric general circulation model experiments conducted by the U.S. CLIVAR Drought Working Group are used to investigate the role of historical SST anomalies associated with Pacific El Niño–Southern Oscillation (ENSO)-like and the Atlantic multidecadal oscillation (AMO) patterns in this dipole pattern. The results show that the Pacific SST pattern plays a dominant role in driving the decadal variability of this dipole pattern and the associated atmospheric circulation anomalies, whereas the Atlantic SST pattern contributes to a much lesser degree. The direct atmospheric response to the Pacific SST pattern is a large-scale cyclonic or anticyclonic circulation anomaly in the lower troposphere occupying the entire northern North Pacific. During the warm phase of the Pacific SST pattern, it is cyclonic with northwesterly wind anomalies over northern China pushing the monsoon front to the south and consequently SF/ND. During the cold phase of the Pacific SST pattern, the circulation anomaly reverses with southeasterly winds over northern China allowing the monsoon front and the associated rainband to migrate northward, resulting in southern drought and northern flooding. The Atlantic SST pattern plays a supplementary role, enhancing the dipole pattern when the Pacific SST and Atlantic SST patterns are in opposite phases and weakening it when the phases are the same.

Doppler Weather Radar (DWR) observations of a severe hailstorm were assimilated in the Weather Research and Forecasting (WRF) model, the three dimensional variational (3D-Var) assimilation is the more common approach. The hailstorm occurred in Bayannur, Inner Mongolia, China, during August 9-10, 2019. The processes of formation, development, and dissipation of the hail-cloud were analyzed, simulated, and discussed in this study. The simulation and assimilation results were verified against X-band dual-linear polarization radar observations. The Morrison and Milbrandt parameterization scheme is applied to simulate synoptic process. In this paper, comparative experiments are set to analysis the impact with and without assimilation of doppler weather radar data on hail simulation:1) control experiment (CTL): without data assimilation; 2) assimilate reflectivity and radial velocity together. The result shows that the Morrison and Milbrandt parameterization scheme can simulate the hail weather process well; at the time when hail occurred, there were strong vertical wind shear, small precipitation amount, low freezing layer, the potential temperature decreases with the height, and the radar echo intensity was around 60dBZ. The hail simulation is improved significantly after assimilation of doppler radar reflectivity and radial velocity

In this study, the Weather Research and Forecasting (WRF) model is used to simulate a severe convective process in Hainan, China on September 16, 2019. For the purpose of improving precipitation simulation and forecast, the WRF model’s three-dimensional Variational (3DVAR) assimilation system is used to assimilate CINRAD/SA Weather radar data. The assimilation results and precipitation forecast are compared and analyzed in order to study the influence of weather radar data assimilation on precipitation prediction. Four experiments of assimilation are carried out: 1) Control experiment: no assimilation of any data; 2) Only radar reflectivity data is assimilated; 3) Assimilating the radar radial velocity data; 4) Simultaneously assimilating the radar reflectivity and radial velocity data. The results show that the assimilation of the reflectivity data from the weather radar can effectively adjust the spatial distribution and magnitude of water vapor and temperature field in the background field. Assimilating the radar radial velocity data mainly improves the wind field of initial field. The assimilation of reflectivity can better adjust the precipitation forecast compared with the assimilation of radial velocity. Assimilating both reflectivity and radial velocity at the same time shows the best positive effect on precipitation forecast.

The intricately fluctuating onset of respiratory and circulatory diseases displays rhythms of multi-scaled meteorological conditions due to their sensitivity to weather changes. The intrinsic meteorological rhythms of these diseases are revealed in this bio-meteorological study via Fourier decomposition and harmonic analysis. Daily emergency room (ER) visit data for respiratory and circulatory diseases from three comprehensive hospitals in Haidian district of Beijing, China were used in the analysis. Meteorological data included three temperature metrics, relative humidity, sunshine duration, daily mean air pressure, and wind speed. The Fourier decomposition and harmonic analysis on ER visits and meteorological variables involve frequency, period, and power of all harmonics. The results indicated that: i) for respiratory morbidity, a strong climatic annual rhythm responding to annual temperature change was firstly revealed; its ratio of spectral density was 16–33%. Moreover, significant correlations existed between the high-frequency fluctuations (, Harmonic spectrum; Fourier decomposition; Chronic disease; Climatic cycle; Short-term weather; Meteorology; Climatology; Environmental health; Epidemiology; Circulatory system; Respiratory system, Environmental science.

Worldwide epidemiological studies have demonstrated that short-term associations of particulate matter (PM), might be further complicated by ambient temperatures, and increase human mortality. In China, among various PM indices, the health effects of black carbon (BC) are less understood due to the lack of data availability. Additionally, it is unclear how temperature modifies simultaneous and adverse effects of BC, and fine (PM size 28 °C. Harmful effects were estimated for increases in non-accidental, respiratory, and cardiovascular mortality per interquartile increments in BC (4.11 μg/m3), PM2.5 (62.37 μg/m3), and PM2.5-10 (46.71 μg/m3) concentrations from the moving average of current and previous day (lag01) under high temperature (>28 °C). Mortality increases in non-accidental, respiratory, and cardiovascular categories were 5.12% (95% confidence interval [CI]: 4.79, 5.45), 7.41% (95%CI: 6.42, 8.40), and 6.36% (95%CI: 2.45, 10.3) for BC; 3.85% (95%CI: 3.27, 4.43), 6.64% (95%CI: 5.63, 7.65), and 4.54% (95%CI: 3.31, 5.78) for PM2.5; and 2.56% (95%CI: 1.45, 3.67), 3.41% (95%CI: 1.53, 5.29), and 3.19% (95%CI: 2.44, 3.94), for PM2.5-10, respectively. These findings suggest that controlling the emission of ambient particles, especially BC, and improving air quality during summer would substantially benefit population health. Furthermore, BC should be considered as a crucial air quality indicator to reflect PM health risk.

This study presents a temperature indicator for heavy air pollution risks (TIP). This TIP indicator is a temperature threshold, at which the concentrations of air pollutants and air pollution indices easily reach their maxima. A connotation discussion ascertains that TIP is intrinsically associated with the atmospheric structure and static stability in the planetary boundary layer, especially during stagnant weather and moderately cold temperatures. Thus, TIP offers a simple measure of meteorological conditions that reflect the boundary layer static characteristics. It therefore provides a simple measure of air pollution potential, and can be used to quantify the potential air pollution severity for a given pollution emission level. From the data collected in China, TIP increases gradually from north to south and decreases slightly from east to west, which essentially indicates a function of latitude and altitude. A simple regressive function is built for TIP, and the resulting TIP index further confirms that it is indicative of the potential heavy air pollution events across the country. Being an easy-to-obtain and simple-to-use meteorological parameter, TIP can be used for air pollution potential assessment and prediction, as well as pollution prevention and control applications.

The risks of emergency room (ER) visits for cerebral infarction (CI) and intracerebral hemorrhage (ICH) is found to differ in different age groups under different climatic thermal environments. Based on CI and ICH related ER-visit records from three major hospitals in Beijing, China, from 2008 to 2012, the advanced Universal Thermal Climate Index (UTCI), was adopted in this study to assess the climatic thermal environment. Particularly, daily mean UTCI was used as a predictor for the risk of ER visits for CI and ICH. A generalized quasi-Poisson additive model combined with a distributed lag non-linear model was performed to quantify their association. The results indicated that (i) the highest growth rate of ER visits for ICH occurred in age 38 to 48, whereas an increasing ER admissions for CI maintained at age 38 to 78. (ii) The frequency distribution of UTCI in Beijing peaked at −8 and 30 °C, corresponding to moderate cold stress and moderate heat stress, respectively. (iii) Correlation analysis indicated that ICH morbidity was negatively correlated with UTCI, whereas occurrence of CI showed no significant association with UTCI. (iv) The estimated relative risk of ER visits corresponding to 1 °C change in UTCI, which was then stratified by age and gender, indicated that all sub-groups of ICH patients responded similarly to thermal stress. Namely, there is an immediate ICH risk (UTCI = −13 °C, RR = 1.35, 95% CIs: 1.11–1.63) from cold stress on the onset day, but non-significant impact from heat stress. As for CI occurrences, no effect from cold stress was identified, except for only those aged 45 to 65 were threatened by heat stress (UTCI = 38 °C, RR = 1.64, 95% CIs: 1.10–2.44) on lag 0–2 d.

In the southeastern United States, drought can pose a significant threat to forests by reducing the amount of available water, thereby stressing trees. Destructive changes in crown conditions provide the first visible indication of a problem in a forested area, making it a useful indicator for problems within an ecosystem. Forest Health and Monitoring (FHM) and Palmer's Drought Severity Index (PDSI) data from 11 states in the southeastern United States were obtained in an effort to determine the role that drought, forest type, and ecoregion have in indicating differences in crown dieback. Analyses were conducted by species groups using classification and regression tree (CART) analysis. The greatest amount of total relative crown dieback occurred in red oak (18%), followed by other hardwoods (14%), and white oak (11%). Relative crown dieback varied by forest type and ecoregion with a relationship to drought in both red oak and white oak. This information will be useful for focusing future research and modeling efforts to predict forest health conditions affected by changing climate variables.

Particulate matter (PM) has been proven to cause health risks and may result in hospital emergency room visits (ERVs), which might be complicated by extreme temperature events. However, it remains unclear how temperature modulates the effect of different-sized particles on ERVs. This study used three separate time series analyses (2009–2011) to explore such temperature modulation effect in Beijing, China. The analytical approaches included a bivariate response surface model, a non-stratification parametric model, and a stratification parametric model. Results showed that the average daily concentrations of PM10 and PM2.5 in Beijing were 110.16 and 67.89 μg/m3, respectively, during the study period, which were higher than in most Western countries. Our findings indicated that the temperature modulation effects of PM2.5 were more evident than that of PM10. The effects of PM on morbidity depend on temperature. The effects were estimated for the increases in total, respiratory, and cardiovascular ERVs per 10 μg/m3 increase in PM2.5 and PM10 concentrations at high temperature level (> 28 °C). The estimated increases in the three types of ERVs for PM2.5 were 0.15, 0.35, and 0.34%, respectively. For PM10, the increases were 0.12, 0.08, and 0.14%, respectively. In addition, the results showed that the elderly (age ≥ 65) and women are more vulnerable to PM at high temperatures. These findings may have implications for the health impact associated with both air pollution and global climate change.

The Global Precipitation Measurement (GPM) mission has generated global precipitation products of improved accuracy and coverage that are promising for advanced hydrological and meteorological studies. This study evaluates three Integrated Multi-satellitE Retrievals for GPM (IMERG) Hourly products, including the Early-, Late-, and Final-run products (IMERG-HE, IMERG-HL, and IMERG-HF, respectively), over Sichuan Basin of China. This highly complex terrain of the steep mountainous region offers further scrutiny on the quality and applicability of the data. The China Meteorological Precipitation Analysis (CMPA) data from January 2016 to December 2018 are used as the reference for the evaluation. Results show that: (1) At grid scale, IMERG-HL and IMERG-HF outperform IMERG-HE in terms of correlation coefficient (CC) and root-mean-square error (RMSE), but IMERG-HL has smaller relative bias (RB) than that of the IMERG-HF (by 21.16%). IMERG-HF presents the highest probability of detection (POD = 0.52) and critical success index (CSI = 0.32), except for high false alarm ratio (FAR) for light precipitation. (2) At regional scale, IMERG-HF outperforms IMERG-HE and IMERG-HL in annual evaluation in all the metrics except for the serious overestimation as shown in RB (20.18%, 3.84%, and 4.97%, respectively). Its accumulative precipitation deviation mainly comes from moderate precipitation events (1&ndash, 10 mm/h), while better detection capability is seen in light precipitation (&lt, 1 mm/h). Seasonally, IMERG-HF performs the best in winter, while IMERG-HL performs the best in the other seasons. (3) IMERG-HF captures the peak precipitation more accurately in all seasons. In reproducing the diurnal cycle, IMERG-HF performs better in winter, while IMERG-HL performs better in summer and autumn, and IMERG-HE in spring. However, all three products overestimate the early morning precipitation (01:00&ndash, 08:00 local standard time) of the diurnal cycle in spring, summer, and autumn.

Adverse environmental impacts from deforestation are a growing area of concern in climate change discussions. The Chinese government has implemented a series of policies, such as the Grain for Green Project, in an attempt to mitigate the impacts. This study takes a regional perspective to report land use/land cover changes over the Loess Plateau region from 2001 to 2009. MODIS data were used in analyzing both the conversions among and the resulting changes in different land types. Government statistical census data and observed climate data were also incorporated in the analysis. A general consistency is shown in both remotely sensed and census data. With the implementation of various projects, including the Grain for Green Project, the total areas covered by grassland, cropland, and forests have increased by 19.2 % (6.05 × 104 km2), 33.7 % (5.80 × 104 km2), and 19.6 % (3.08 × 104 km2), respectively, during the 9-year period. While climatic conditions, particularly annual precipitation totals, usually dominate the distribution of vegetation, it is found that socioeconomic polices and human activities contribute to the increase in overall greenness and to vegetation growth (e.g., LAI increased by 16.8 % (0.10) overall). However, the feedback of land use/land cover to regional climate is complicated and cannot be easily distinguished from natural climate variations based on short-term observational data alone. To better isolate the effects, further analysis and modeling studies are suggested.

To achieve a high-quality simulation of the surface wind field in the Chukchi/Beaufort Sea region, quick scatterometer (QuikSCAT) ocean surface winds were assimilated into the mesoscale Weather Research and Forecasting model by using its three-dimensional variational data assimilation system. The SeaWinds instrument on board the polar-orbiting QuikSCAT satellite is a specialized radar that measures ice-free ocean surface wind speed and direction at a horizontal resolution of 12.5 km. A total of eight assimilation case studies over two five-day periods, 1–5 October 2002 and 20–24 September 2004, were performed. The simulation results with and without the assimilation of QuikSCAT winds were then compared with QuikSCAT data available during the subsequent free-forecast period, coastal station observations, and North American Regional Reanalysis data. It was found that QuikSCAT winds are a potentially valuable resource for improving the simulation of ocean near-surface winds in the Chukchi/Beaufort Seas region. Specifically, the assimilation of QuikSCAT winds improved, (1) offshore surface winds as compared to unassimilated QuikSCAT winds, (2) sea-level pressure, planetary boundary-layer height, as well as surface heat fluxes, and (3) low-level wind fields and geopotential height. Verification against QuikSCAT data also demonstrated the temporal consistency and good quality of QuikSCAT observations.

Emergency room (ER) visits for accidental casualties, according to the International Classification of Deceases 10th Revision Chapters 19 and 20, include injury, poisoning, and external causes (IPEC). Annual distribution of 187,008 ER visits that took place between 2009 and 2011 in Beijing, China displayed regularity rather than random characteristics. The annual cycle from the Fourier series fitting of the number of ER visits was found to explain 63.2% of its total variance. In this study, the possible effect and regulation of meteorological conditions on these ER visits are investigated through the use of correlation analysis, as well as statistical modeling by using the Distributed Lag Non-linear Model and Generalized Additive Model. Correlation analysis indicated that meteorological variables that positively correlated with temperature have a positive relationship with the number of ER visits, and vice versa. The temperature metrics of maximum, minimum, and mean temperatures were found to have similar overall impacts, including both the direct impact on human mental/physical conditions and indirect impact on human behavior. The lag analysis indicated that the overall impacts of temperatures higher than the 50th percentile on ER visits occur immediately, whereas low temperatures show protective effects in the first few days. Accidental casualties happen more frequently on warm days when the mean temperature is higher than 14 °C than on cold days. Mean temperatures of around 26 °C result in the greatest possibility of ER visits for accidental casualties. In addition, males were found to face a higher risk of accidental casualties than females at high temperatures. Therefore, the IPEC-classified ER visits are not pure accidents; instead, they are associated closely with meteorological conditions, especially temperature.

Tornado hazards have caused frequent and severe damages to built environment and lives. The severity of the hazards directly relates to the strength of the tornadic events in terms of meteorological parameters, as well as the resistance of buildings to the strong tornadic impacts. The tornado hazards are reviewed from both meteorological and engineering perspectives in this study. For each of the perspectives, current status of tornado hazard studies including the observation, monitoring, analysis, numerical and laboratory simulations, and limitations and future demands of development are discussed. While the two disciplines are fast advancing individually, their interaction and interdependence are deemed prominent and imperative in the future interdisciplinary studies.

Soil temperature is a major variable in land surface models, representing soil energy status, storage, and transfer. It serves as an important factor indicating the underlying surface heating condition for weather and climate forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to study the impacts of changes to the surface heating condition, derived from soil temperature observations, on regional weather simulations. Large cold biases are found in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis project (ERA-40) soil temperatures as compared to observations. At the same time, a warm bias is found in the lower boundary assumption adopted by the Noah land surface model. In six heavy rain cases studied herein, observed soil temperatures are used to initialize the land surface model and to provide a lower boundary condition at the bottom of the model soil layer. By analyzing the impacts from the incorporation of observed soil temperatures, the following major conclusions are drawn: 1) A consistent increase in the ground heat flux is found during the day, when the observed soil temperatures are used to correct the cold bias present in ERA-40. Soil temperature changes introduced at the initial time maintain positive values but gradually decrease in magnitude with time. Sensible and latent heat fluxes and the moisture flux experience an increase during the first 6 h. 2) An increase in soil temperature impacts the air temperature through surface exchange, and near-surface moisture through evaporation. During the first two days, an increase in air temperature is seen across the region from the surface up to about 800 hPa (∼1450 m). The maximum near-surface air temperature increase is found to be, averaged over all cases, 0.5 K on the first day and 0.3 K on the second day. 3) The strength of the low-level jet is affected by the changes described above and also by the consequent changes in horizontal gradients of pressure and thermal fields. Thus, the three-dimensional circulation is affected, in addition to changes seen in the humidity and thermal fields and the locations and intensities of precipitating systems. 4) Overall results indicate that the incorporation of observed soil temperatures introduces a persistent soil heating condition that is favorable to convective development and, consequently, improves the simulation of precipitation.

A “hot start” technique is applied to the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) to dynamically assimilate cloud properties and humidity profiles retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the NASA Earth Observing System polar-orbiting satellites. The assimilation approach has been studied through extensive numerical experimentation for high-latitude rain events to demonstrate the feasibility and the benefit of the approach on the model cloud and precipitation simulation/forecast. The ingestion of MODIS-retrieved cloud and clear-air humidity information impacts MM5 cloud fields on both a microphysical and macrophysical level. From short-term (6–12 h) forecast experiments conducted for a preliminary test case and 16 extensive summer and winter experiments, the following primary conclusions have been reached. 1) It is feasible to introduce MODIS-retrieved cloud-top properties and humidity profiles into the MM5 model in a hot start mode without disrupting model stability and evolutionary continuity. 2) The introduction of high-resolution MODIS information produced more accurate humidity fields and resulted in increased mesoscale structure in the cloud and precipitation fields. 3) The opportunistic ingestion of MODIS data at its observation time into the model leads to improved 6–12-h model precipitation forecasts with respect to not only the frequency of occurrences, but also the magnitude of precipitation amounts. 4) Verification with three-dimensional analyses indicates some improvement in model forecasts of temperature, wind, pressure perturbation, and sea level pressure as well. 5) Verification with surface station observations indicates that model forecasts of 2-m temperature, 2-m relative humidity, 10-m winds, and sea level pressure are also improved, most notably for the summer cases. The largest improvement in forecast skill is for 2-m relative humidity (12%).

An atmosphere-land coupled simple climate model is constructed and its climatic properties are analyzed by introducing a global analysis method, cell mapping. The simple model is a nonlinear six order simplified climate model featured with chaotic dynamics, dissipation, and forcing source, which are the main features of the real climate system. The cell mapping method is applied with this coupled system. Numerical experiments are carried out for investigating the interactions between the fast-changing atmospheric variables and slow-changing underlying surface variables. The predictability of the system is also investigated via the global analysis, with which the evolution of the system is translated to the evolution of probability transition on a Markov Chain. An effective scheme is proposed for computing the probability transition matrix for the coupled system. Predictions can be made based on the combination of dynamics and statistics. The importance of constructing the coupled model is shown by globally analyzing the predictability of the coupled system. The coupling mechanism prolongs the memorization of initial information, and then the predictability as well.

The equation of one-dimensional thermal conduction and convection in soil is solved analytically by applying the traditional harmonic method (HM) and the Laplace transform method (LTM). A simple method to determine accurate values of soil heat diffusivity and liquid water flux density is given. Usin

In this paper, we construct a three order simplified climate model, undergoing chaotic dynamics. Generalized cell mapping, a global analysis method, is introduced to describe the global long-term behavior of the chaotic climate system, and to predict its global probability evolution. Numerical experiments are carried out for day-to-day prediction and temporal average prediction. Ways to enhance the prediction capability are suggested. The results shows that using the global analysis method to combine dynamic frames with statistical description is a promising method for climate prediction.

Using an observing system simulation experiment (OSSE), we investigate the potential soil moisture retrieval capability of the National Aeronautics and Space Administration (NASA) Aquarius radiometer (L-band 1.413 GHz) and scatterometer (L-band, 1.260 GHz). We estimate potential errors in soil moisture retrievals and identify the sources that could cause those errors. The OSSE system includes (i) a land surface model in the NASA Land Information System, (ii) a radiative transfer and backscatter model, (iii) a realistic orbital sampling model, and (iv) an inverse soil moisture retrieval model. We execute the OSSE over a 1000 × 2200 km2 region in the central United States, including the Red and Arkansas river basins. Spatial distributions of soil moisture retrieved from the radiometer and scatterometer are close to the synthetic truth. High root mean square errors (RMSEs) of radiometer retrievals are found over the heavily vegetated regions, while large RMSEs of scatterometer retrievals are scattered over the entire domain. The temporal variations of soil moisture are realistically captured over a sparely vegetated region with correlations 0.98 and 0.63, and RMSEs 1.28% and 8.23% vol/vol for radiometer and scatterometer, respectively. Over the densely vegetated region, soil moisture exhibits larger temporal variation than the truth, leading to correlation 0.70 and 0.67, respectively, and RMSEs 9.49% and 6.09% vol/vol respectively. The domain-averaged correlations and RMSEs suggest that radiometer is more accurate than scatterometer in retrieving soil moisture. The analysis also demonstrates that the accuracy of the retrieved soil moisture is affected by vegetation coverage and spatial aggregation.