Meteorological Information Center Research Articles

Risk effects of meteorological factors on human brucellosis in Jilin province, China, 2005–2019

BackgroundThe impact of climate on zoonotic infectious diseases (or can be referred to as climate-sensitive zoonotic diseases) is confirmed. Yet, research on the association between brucellosis and climate is limited. We aim to understand the impact of meteorological factors on the risk of brucellosis, especially in northeastern China. MethodsMonthly incidence data for brucellosis from 2005 to 2019 in Jilin province was obtained from the China Information System for Disease Control and Prevention (CDC). Monthly meteorological data (average temperature (°C), wind velocity (m/s), relative humidity (%), sunshine hours (h), air pressure (hPa), and rainfall (mm)) in Jilin province, China, from 2005 to 2019 were collected from the China Meteorological Information Center (http://data.cma.cn/). The Spearman's correlation was used to choose among the several meteorological variables. A distributed lag non-linear model (DLNM) was used to estimate the lag and non-linearity effect of meteorological factors on the risk of brucellosis. ResultsA total of 24,921 cases of human brucellosis were reported in Jilin province from 2005 to 2019, with the peak epidemic period from April to June. Low temperature and low sunshine hours were protective factors for the brucellosis, where the minimum RR values were 0.50 (95 % CI = 0.31–0.82) for −13.7 °C with 1 month lag and 0.61 (95 % CI = 0.41–0.91) for 110.5h with 2 months lag, respectively. High temperature, high sunshine hours, and low wind velocity were risk factors for brucellosis. The maximum RR values were 2.91 (95 % CI = 1.43–5.92, lag = 1, 25.7 °C), 1.85 (95 % CI = 1.23–2.80, lag = 2, 332.6h), and 1.68 (95 % CI = 1.25–2.26, lag = 2, 1.4 m/s). The trends in the impact of extreme temperature and extreme sunshine hours on the transmission of brucellosis were generally consistent. ConclusionHigh temperature, high sunshine hours, and low wind velocity are more conducive to the transmission of brucellosis with an obvious lag effect. The results will deepen the understanding of the relationship between climate and brucellosis and provide a reference for formulating relevant public health policies.

Evaluation and comparison of 11 sets of gridded precipitation products over the Qinghai-Tibet Plateau

The Qinghai Tibet Plateau (QTP) poses challenges in developing high-quality gridded precipitation data with high spatial and temporal resolution due to its complex terrain, harsh weather conditions, and sparse gauge observations. Previous research showed that gridded precipitation products from remote sensing satellites, reanalysis, and merged data are useful over the QTP. However, the precipitation products were usually calibrated against ground meteorological stations, so the evaluation based on these stations might be misleading. This study collected 11 sets of gridded precipitation products on the QTP, and evaluated them by using 53 independent rain gauges obtained from the hydrological yearbook (HY). The results showed that the CMFD precipitation product performed better than other products at meteorological sites from the National Meteorological Information Center (NMIC), with average daily and monthly correlation coefficients (CCs) of 0.55 and 0.94 and root mean square errors (RMSEs) of 3.78 and 0.44 mm/d, respectively. Following closely is CLDAS. In contrast, MSP performed best at HY sites, with average CCs of 0.70 and 0.91 and RMSEs of 2.47 and 0.65 mm/d, respectively. The following are TPHiPr, GSMAP, and CLDAS. Some global products, such as CHIPRS and CMORPH, performed poorly over the QTP. Most products overestimated the frequency of light precipitation (0.1– 0.5 mm/d) and underestimated the frequency of heavy precipitation. The fluctuation amplitudes of relative deviations for all precipitation products are markedly greater at hydrological sites compared to that at meteorological sites. Therefore, it is essential to consider correcting magnitude deviations before using these products. Based on independent assessment, this study suggests that further improvements are still needed for precipitation products on the QTP.

Spatial analysis of the prevalence of abdominal obesity in middle-aged and older adult people in China: exploring the relationship with meteorological factors based on gender differences.

In recent years, the incidence of abdominal obesity among the middle-aged and older adult population in China has significantly increased. However, the gender disparities in the spatial distribution of abdominal obesity incidence and its relationship with meteorological factors among this demographic in China remain unclear. This gap in knowledge highlights the need for further research to understand these dynamics and inform targeted public health strategies. This study utilized data from the 2015 China Health and Retirement Longitudinal Study (CHARLS) to analyze the incidence of abdominal obesity among the middle-aged and older adult population in China. Additionally, meteorological data were collected from the National Meteorological Information Center. Using Moran's I index and Getis-Ord Gi* statistical methods, the spatial distribution characteristics of abdominal obesity incidence were examined. The influence of various meteorological factors on the incidence of abdominal obesity in middle-aged and older adult males and females was investigated using the q statistic from the Geodetector method. Furthermore, Multi-Scale Geographically Weighted Regression (MGWR) analysis was employed to explore the impact of meteorological factors on the spatial heterogeneity of abdominal obesity incidence from a gender perspective. The spatial distribution of abdominal obesity among middle-aged and older adult individuals in China exhibits a decreasing trend from northwest to southeast, with notable spatial autocorrelation. Hotspots are concentrated in North and Northeast China, while cold spots are observed in Southwest China. Gender differences have minimal impact on spatial clustering characteristics. Meteorological factors, including temperature, sunlight, precipitation, wind speed, humidity, and atmospheric pressure, influence incidence rates. Notably, temperature and sunlight exert a greater impact on females, while wind speed has a reduced effect. Interactions among various meteorological factors generally demonstrate bivariate enhancement without significant gender disparities. However, gender disparities are evident in the influence of specific meteorological variables such as annual maximum, average, and minimum temperatures, as well as sunlight duration and precipitation, on the spatial heterogeneity of abdominal obesity incidence. Meteorological factors show a significant association with abdominal obesity prevalence in middle-aged and older adults, with temperature factors playing a prominent role. However, this relationship is influenced by gender differences and spatial heterogeneity. These findings suggest that effective public health policies should be not only gender-sensitive but also locally adapted.

Spatiotemporal Variation in the Meteorological Drought Comprehensive Index in the Beijing–Tianjin–Hebei Region during 1961–2023

It is crucial to investigate the characteristics of meteorological drought in the Beijing–Tianjin–Hebei (BTH) region to improve the accuracy of agriculture and water resource monitoring and management. In this study, using instrumental observation data from 85 meteorological stations in the BTH region during 1961–2023 derived from the National Meteorological Information Center, we first calculated the meteorological drought comprehensive index (MCI) and analyzed the spatiotemporal characteristics of the MCI. In the BTH region, the MCI intensity from May to June was the most severe in the intraseasonal variation. The trend of the decreasing drought intensity in May–June has occurred for the past 60 years. The southern region in the BTH region was more likely to experience droughts. Next, the spatial patterns of the top two EOF modes of the May–June MCI were depicted. The primary spatial pattern of the BTH, which was characterized by consistent changes in the MCI throughout the entire BTH region, could be represented by the first mode’s R2 of 69.01%. Then, we compared the spatial pattern of the MCI intensity under different return periods. Using the May–June MCI of 1961–2023, the drought intensity gradually increased from northwest to southeast for the 10-, 20-, and 50-year return periods. However, the drought intensity decreased and then increased from northwest to southeast based on the 1991–2023 MCI. Notably, a 20-year return period of severe drought affected Beijing and northern Hebei in 2023. Finally, we discussed the linkages of drought in the BTH region and atmospheric circulation/sea surface temperature (SST) anomalies, which were calculated using the Pearson correlation coefficient and wavelet coherence. We suggest that the MCI variations in the BTH region may be related to the SST anomalies of the Indian Ocean in 1961–1990 and the Pacific Ocean in 1991–2023, respectively. The abovementioned studies have enlightened us to focus on predicting the Pacific SST for drought, which will facilitate agricultural production and water resource management in the BTH region.

Extreme heat events in mainland China from 1981 to 2015: Spatial patterns, temporal trends, and urbanization impacts

Extreme heat events have raised public concerns due to their severe adverse effects on both natural and human systems, particularly in urban areas, where they interact with urban heat island effects. Here, we used spatial grouping and statistical models to quantify the spatial patterns, temporal trends, and influencing factors of extreme heat events in mainland China from 1981 to 2015 based on data from 828 weather stations that were downloaded from the National Meteorological Information Center of China. Extreme heat events were defined as days when the heat index exceeded 40.6 °C, at which health risks reach a dangerous level. We found weather stations can be spatially categorized into four groups based on the characteristics of heat events: few events, high frequency, high intensity, and long duration from north to south. Temporal trends in extreme heat events vary across biomes, and the most significant increasing trends were found in Tropical & Subtropical Moist Broadleaf Forests and Temperate Broadleaf & Mixed Forests. Urbanization positively affected the increase in hot days, while station relocation partially offset the effects because stations were moved to less urbanized areas. Results provide valuable insights for public health interventions and the design of sustainable cities and society.

Research on Guangdong Province Meteorological Data Analysis System under Hadoop Environment

In order to better monitor and manage the real-time transmission of meteorological information in Guangdong Province and improve communication quality, the Guangdong Meteorological Information Center has organized the development of the Guangdong Meteorological Data Analysis System. The system has the characteristics of intuitive and easy to use, strong real-time performance, and convenient query and statistics, which better meets the real-time monitoring and time management requirements of meteorological information transmission in Guangdong Province. Hadoop is a popular big data computing oriented, open-source big data processing system. Its characteristics of high throughput, high fault tolerance and easy expansion make it widely used in all walks of life. Therefore, this article focuses on the characteristics of real-time reception of meteorological information in Guangdong Province, and introduces the development ideas, use of some new technologies, and page implementation of the Guangdong Meteorological Data Analysis System under Hadoop environment. In the Hadoop environment, it is possible to dynamically exchange data with the server without refreshing the entire page, improving the efficiency of data transmission between the server and client, making browsing more intuitive and convenient. Enriched the methods and capabilities of data processing.

Effects of ambient temperature and relative humidity on preterm birth during early pregnancy and before parturition in China from 2010 to 2018: a population-based large-sample cohort study.

The progression of global warming and increase in instances of extreme weather have received considerable attention. We conducted a cohort study on women of childbearing age in Yunnan Province, examined the association between ambient temperature and humidity on preterm birth and evaluated the effects of extreme weather during early pregnancy and before parturition on preterm birth. We conducted a population-based cohort study on women of childbearing age 18-49 years who participated in National Free Preconception Health Examination Project (NFPHEP) in Yunnan Province from January 1, 2010, to December 31, 2018. Meteorological data, namely daily average temperature (°C) and daily average relative humidity (%), were obtained from China National Meteorological Information Center. Four exposure windows were explored: 1 week of pregnancy, 4 weeks of pregnancy, 4 weeks before delivery, and 1 week before delivery. We used a Cox proportional hazards model and adjusted the potential risk factors for preterm birth to obtain the effects of exposure to temperature and humidity on preterm birth among the stages of pregnancy. At 1 week of pregnancy and at 4 weeks of pregnancy, the association between temperature and preterm birth was U-shaped. The correlation between relative humidity and the risk of preterm birth was n-type at 1 week of pregnancy. The correlation between preterm birth and temperature and relative humidity at 4 weeks before delivery and at 1 week before delivery is J-shaped. Low temperature and low humidity were protective factors against preterm birth, whereas high temperature and high humidity were risk factors for preterm birth.The effects of high temperature and extremely high temperature were the strongest at 4 weeks before delivery, with HRs of 1.417 (95% CI: 1.362-1.474) and 1.627 (95% CI: 1.537-1.722), respectively. The effects of extremely low humidity and low humidity were strongest at 1 week before delivery, with HRs of 0.681 (95% CI: 0.609-0.761) and 0.696 (95% CI: 0.627-0.771), respectively. Temperature and relative humidity affect preterm birth differently for each pregnancy stage. The effects of meteorological factors on pregnancy outcomes such as premature birth should not be ignored.

A Modified RNN-Based Deep Learning Method for Prediction of Atmospheric Visibility

Accurate atmospheric visibility prediction is of great significance to public transport safety. However, since it is affected by multiple factors, there still remains difficulties in predicting its heterogenous spatial distribution and rapid temporal variation. In this paper, a recursive neural network (RNN) prediction model modified with the frame-hopping transmission gate (FHTG), feature fusion module (FFM) and reverse scheduled sampling (RSS), named SwiftRNN, is developed. The new FHTG is used to accelerate training, the FFM is used for extraction and fusion of global and local features, and the RSS is employed to learn spatial details and improve prediction accuracy. Based on the ground-based monitoring data of atmospheric visibility from the China Meteorological Information Center during 1 January 2018 to 31 December 2020, the SwiftRNN model and two traditional ConvLSTM and PredRNN models are performed to predict hourly atmospheric visibility in central and eastern China at a lead of 12 h. The results show that the SwiftRNN model has better performance in the skill scores of visibility prediction than those of the ConvLSTM and PredRNN model. The averaged structural similarity (SSIM) of predictions at a lead up to 12 h is 0.444, 0.425 and 0.399 for the SwiftRNN, PredRNN and ConvLSTM model, respectively, and the averaged image perception similarity (LPIPS) is 0.289, 0.315 and 0.328, respectively. The averaged critical success index (CSI) of predictions over 1000 m fog area is 0.221, 0.205 and 0.194, respectively. Moreover, the training speed of the SwiftRNN model is 14.3% faster than the PredRNN model. It is also found that the prediction effect of the SwiftRNN model over 1000 m medium grade fog area is significantly improved along with lead times compared with the ConvLSTM and PredRNN model. All above results demonstrate the SwiftRNN model is a powerful tool in predicting atmospheric visibility.

Change in mean and extreme precipitation in eastern China since 1901

Extreme precipitation in the monsoon region of China can cause a variety of weather and climate disasters, and its long-term change has a significant impact on human life and social production. However, due to the lack of high-resolution precipitation data for the early 20th century, the variation characteristics and causes or mechanisms of extreme precipitation change in eastern China in the last 100 yr or more are still unclear. Based on the ‘daily precipitation dataset of 60 city stations in mainland China from 1901 to 2020’ developed by the National Meteorological Information Center, China Meteorological Administration, the main characteristics of extreme precipitation changes at 38 stations in eastern China during a recent 120 yr period (1901-2020) are analyzed in this paper. The results show that: (1) From 1901 to 2020, there was no significant trend in precipitation amount and precipitation days in the region, but a quasi-period of about 15 to 20 yr or longer existed during the period. (2) The average daily precipitation intensity and most of the extreme precipitation indices first decreased and then increased over the whole time period. In the period 1901-1950, which has rarely been studied in the past, most of the extreme precipitation indices, including intense rainfall, rainstorms, and the maximum precipitation within 1 day, 3 consecutive days, and 5 consecutive days, showed a significant decreasing trend. Since 1951, however, various indices have tended to increase. (3) From 1901 to 2020, the precipitation and extreme precipitation indices to the north of 35° N generally decreased, while they consistently increased in the south. The spatial pattern of extreme precipitation changes for the first half of 20th century was also quite different from that of the last 70 yr. Overall, the mean and extreme precipitation change trends in eastern China were not consistent in different sub-periods during the past century.

Influence of Atmospheric 10–20 Day Low Frequency Oscillation on Regional Strong Cooling Events in the Winter of Northern China over the Past 40 Years

Using daily minimum temperature data at 2481 stations provided by the National Meteorological Information Center (China) and the daily reanalysis data from NCEP/NCAR during the period from 1980 to 2019, the effects of atmospheric low frequency oscillations (LFOs) on the regional strong cooling events (RSCEs) in the winter of northern China are investigated, and the extended range forecast signals of the RSCEs are extracted. The results show that: (1) The frequency of RSCEs is higher before the year 2000 and then decreases, but its interannual variability increases. There are 10–20, 20–30 and 30–60 d significant low frequency periods in the regional average minimum temperature in northern China, and the low frequency oscillation with a period of 10–20 d is the most significant. (2) The low frequency key systems affecting RSCEs in the west, middle, and east of northern China are the Ural blocking high and the trough of Lake Balkhash-Baikal (Lake Ba-Bei), the blocking high in the northwest and the low trough in the southeast of Lake Ba-Bei, the Lake Ba-Bei blocking high and the East Asian trough, respectively, and the Siberian High (SH) that expands and moves with the blocking high all the time. The low frequency jets at the upper level are weaker in the north and stronger in the south. (3) The low frequency high potential vorticity (PV) center in the lower stratosphere moves eastward and southward along the 315 K isentropic surface via the north of Lake Ba-Bei, southern Lake Baikal and Northeast China to the Sea of Japan, causing the 2 PVU line to move southward and then the above-mentioned high PV center in the mid-high troposphere to extend vertically. Meanwhile, under the influence of gradually increasing upper level jets and vertical meridional circulation, the high PV column continues to propagate downward to the mid-low troposphere at lower latitudes along the 300–315 K isentropic surfaces, which enhances the low frequency positive vorticity and deepens the key trough. In addition, the convergence in the upper troposphere, the divergence in the lower layer, and the development of descending motion behind the trough lead to the development and southward movement of the SH. (4) At −10 d, the positive and negative low frequency anomalies at 500 hPa geopotential height appearing in the East European Plain and Western Siberian Plain are the extended range forecast signals for RSCEs in the winter of northern China, respectively.

Effects of Low-Frequency Oscillation at Different Latitudes on Summer Precipitation in Flood and Drought Years in Southern China

Based on the daily precipitation data from 753 meteorological stations provided by the National Meteorological Information Center (China) and the daily reanalysis data from NCEP/NCAR and ERA5 during the period from 1980 to 2020, the low-frequency (LF) precipitation characteristics of the typical summer flood and drought years in southern China and their relation to the LF atmospheric circulation at different latitudes are compared and analyzed, and extended-range forecasting signals are given. The results show that: (a) In both flood and drought years, summer precipitation in southern China is controlled by 10–20 day oscillation (quasi-biweekly oscillation, QBWO); (b) LF convection is active in southern China in both flood and drought years, but the convective center is southward in flood years, and the vertical meridional circulation is stronger. The key circulation systems of 500 hPa LF height field in flood and drought years include LF “two ridges and one trough” and LF “+”, “−”, “+” East Asia Pacific (EAP) teleconnection wave train in mid-high latitudes of Eurasia. However, the “two ridges and one trough” in flood years are more westward and meridional than in drought years, and the LF Subtropical High is stronger and more extensive, with more significant westward extension; (c) In flood (drought) years, there is northerly and then westerly (central westerly) dry-cold, northeasterly wet-cold, southwesterly (none), and southeasterly (including southerly across the equator) wet-warm water vapor channels. The sources of dry and wet cold air in flood (drought) years are located near Novaya Zemlya (the eastern West Siberian Plain), the Yellow Sea, and the Bohai Sea (Sea of Japan). Additionally, the sources of wet-warm water vapor include the Arabian Sea, the Bay of Bengal, the western Pacific Ocean, and the sea area of northeastern Australia (the western Pacific Ocean and the northern sea area of Australia); and (d) The LF predictive signals of outgoing longwave radiation (OLR) appear on −11 days, while the signals of the 500 hPa height field are on −9 days. There are both westward and eastward propagation predictive signals in flood years, and only westward spread signals in drought years.

Quality Evaluation of the 0.01° Multi-Source Fusion Precipitation Product and Its Application in Extreme Precipitation Event

High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the development of modern meteorological business. The 0.01° multi-source fusion precipitation product is the latest precipitation product developed by the National Meteorological Information Center to meet the above needs. Taking the hourly precipitation observation data of 2400 national automatic stations as the evaluation base, independent and non-independent test methods are used to evaluate the 0.01° multi-source fusion precipitation product in 2020. The product quality differences between the 0.01° precipitation product and the 0.05° precipitation product are compared, and their application in extreme precipitation events are analyzed. The results show that, in the independent test, the product quality of the 0.01° precipitation product and the 0.05° precipitation product are basically the same, which is better than that of each single input data source, and the product quality in winter and spring is slightly lower than that in summer, and both products have better quality in the east in China. The evaluation results of the 0.01° precipitation product in the non-independent test are far better than that of the 0.05° product. The root mean square error and the correlation coefficient of the 0.01° multi-source fusion precipitation product are 0.169 mm/h and 0.995, respectively. In the extreme precipitation case analysis, the 0.01° precipitation product, which is more consistent with the station observation values, effectively improves the problem that the extreme value of the 0.05° product is lower than that of station observation values and greatly improves the accuracy of the precipitation extreme value in the product. The 0.01° multi-source fusion precipitation product has better spatial continuity, a more detailed description of precipitation spatial distribution and a more accurate reflection of precipitation extreme values, which will better provide precipitation data support for refined meteorological services, major activity support, disaster prevention and reduction, etc.

Impact of the coronavirus disease 2019 interventions on the incidence of hand, foot, and mouth disease in mainland China

SummaryBackgroundIn early 2020, non-pharmaceutical interventions (NPIs) were implemented in China to reduce and contain the coronavirus disease 2019 (COVID-19) transmission. These NPIs might have also reduced the incidence of hand, foot, and mouth disease (HFMD).MethodsThe weekly numbers of HFMD cases and meteorological factors in 31 provincial capital cities and municipalities in mainland China were obtained from Chinese Center for Disease Control and Prevention (CCDC) and National Meteorological Information Center of China from 2016 to 2020. The NPI data were collected from local CDCs. The incidence rate ratios (IRRs) were calculated for the entire year of 2020, and for January–July 2020 and August–December 2020. The expected case numbers were estimated using seasonal autoregressive integrated moving average models. The relationships between kindergarten closures and incidence of HFMD were quantified using a generalized additive model. The estimated associations from all cities were pooled using a multivariate meta-regression model.FindingsStringent NPIs were widely implemented for COVID-19 control from January to July 2020, and the IRRs for HFMD were less than 1 in all 31 cities, and less than 0·1 for 23 cities. Overall, the proportion of HFMD cases reduced by 52·9% (95% CI: 49·3−55·5%) after the implementation of kindergarten closures in 2020, and this effect was generally consistent across subgroups.InterpretationThe decrease in HFMD incidence was strongly associated with the NPIs for COVID-19. HFMD epidemic peaks were either absent or delayed, and the final epidemic size was reduced. Kindergarten closure is an intervention to prevent HFMD outbreaks.FundingThis research was supported by the National Natural Science Foundation of China (81973102 & 81773487), Public Health Talents Training Program of Shanghai Municipality (GWV-10.2-XD21), the Shanghai New Three-year Action Plan for Public Health (GWV-10.1-XK16), the Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China (2021YFF0306000), 13th Five-Year National Science and Technology Major Project for Infectious Diseases (2018ZX10725-509) and Key projects of the PLA logistics Scientific research Program (BHJ17J013).

Analysis of Cold Weather Process in the North China during October 20 to 23, 2020

To help the forecast of cold weather activity, the cold weather process in the North China from October 20 to 23, 2020 was analyzed by the methods of utilizing statistical analysis, such as composite, differential analysis and correlation analysis, and by using the data from the National Meteorological Information Center of China, the National Climate Center of China and the NECP data from NOAA Physical Sciences Laboratory. The results show that: 1) the cold air started from Siberia, took the east path to move southward, and finally affected most part of North China. 2) Almost no obvious weather occurred during the process. 3) The cold air mainly moved along with the form and development of the trough and ended when the trough got weaken.

Impact of dam construction on precipitation: a regional perspective

Context Numerous dams have been built in China to develop hydropower, a sustainable and clean energy source. In recent years, the impact of dam construction on the regional climate has gradually attracted the attention of researchers. Aims This study has evaluated the impact of large-scale dam construction on regional precipitation. Methods This paper used the precipitation data of more than 2400 national stations of the China National Meteorological Information Center from 1990 to 2012. The regional precipitation data before and after the construction of the Xiaolangdi Dam and the Three Gorges Dam on the Yangtze River were analysed using geostatistical tools. Wavelet transform and Yamamoto signal-to-noise ratio analysis were further adopted. Key results Analysis of the variation points of precipitation characteristics confirmed the correlation between dam construction and regional precipitation; the precipitation values in the two dam study areas had an increasing trend after the completion of the dams, and the fitting trend line showed an obvious increasing trend. Conclusions According to the analysis of precipitation variation points, it can be concluded that the establishment of the dam affected the precipitation in the area of ∼200 km upstream and increased the precipitation value in this area. The study showed that dam construction has a strong correlation with regional precipitation. Implications It is speculated that the construction of super dams will have a greater impact on precipitation.

Statistical analysis of regional air temperature characteristics before and after dam construction

Dam construction brings both benefits and harms to the ecological environment. This paper focuses on the impact of the construction of mega-dams on regional climate. Based on the national precipitation and temperature data from 1990 to 2012 from more than 2400 national stations of the National Meteorological Information Center, this paper analyzes Xiaolangdi Dam's influence on the Yellow River's climate and the Three Gorges Dam of the Yangtze River with geostatistics knowledge. The following results are obtained. (1) According to the analysis of the climate time and space distribution in the Yellow River Basin and the Yangtze River Basin, the dam's construction caused a drop in temperature in the reservoir area, which decreased by about 0.12 °C. On the other hand, the dam's construction also caused the temperature in the downstream area to rise by about 0.6 °C. (2) According to the analysis of regional climate correlation, the rise of the dam's water level will cause the temperature of the reservoir area to drop to a certain extent. The correlation between the temperature in the Three Gorges and the water level changes in the Three Gorges reaches −0.578. (3) According to regional climate statistics analysis, the dam's construction has reduced the temperature difference in the reservoir area.

Climate Change is Likely to Alter Sheep and Goat Distributions in Mainland China

Climate change endangers food security worldwide, especially in developing countries. Livestock husbandry is one of the essential livelihoods for farmers and herders in remote arid and semiarid regions. However, it remains unclear how climate change will impact livestock husbandry in the future. This study collected sheep and goat distributions from the “gridded livestock of the world” (GLW) dataset for 1943 counties in Mainland China. Current climate data include precipitation and temperature from the National Meteorological Information Center (NMIC). We disentangled the effects of precipitation and temperature on current distributions of sheep and goats with the Bayesian Hierarchical Model by Integrated Nest Laplace Approximation (INLA). Further, we forecasted the potential sheep and goat distributions in 2030 and 2050 under Coupled Model Intercomparison Project (CMIP) scenarios. Our result showed that sheep distribution is significantly correlated with elevation, slope, market density, and highway distance, with absolute correlation coefficients ranging from 0.019 to 0.411. In addition to elevation, slope, and market density, goat distribution is also affected by gain production, with a correlation coefficient of 0.055. There is a dynamic correlation of temperature and precipitation with sheep and goat density. The sheep density distribution is predicted to increase in Northwest China, while the goat density distribution might increase in farming areas under climate change. Finally, this study suggests for the sheep and goat breeding industry to respond to climate change.

Estimation of ecological water supplement for typical bird protection in the Yellow River Delta wetland

With abundant resources in the wetland, the Yellow River Delta provides important habitats for various kinds of rare bird species. However, due to climate change and human water withdrawal activities, no-flow events of the Yellow River occurred frequently since the 1970s, resulting in serious wetland degradation and biodiversity losses. Ecological water supplement has been regarded as one of the most effective measures to cope with these environmental problems. Accordingly, how much water is required for the ecological restoration becomes an essential question to be answered. Since the primary function of the Yellow River Delta Natural Reserve (YRDNR), the typical wetland in the Yellow River Delta, is to provide suitable habitats for various rare birds, the purpose of this paper is to propose a method based on water balance analysis to specify monthly ecological water supplement for the habitats of typical birds in the YRDNR. Specifically, three typical birds were selected as the protection objects, including Grus japonensis, Ciconia boyciana, and Larus saundersi. Monthly water supplement was determined by monthly long-term time series data (2003–2018) of evapotranspiration product derived from remote sensing and meteorological data (precipitation and pan evaporation) acquired from National Meteorological Information Center. The results showed that the annual ecological water supplement for 10 km2 ideal habitats was 666.17×104 m3, 1165.22×104 m3, and 664.48×104 m3 for G. japonensis, C. boyciana, and L. saundersi, respectively. Besides, it was found that annual precipitation generally had a significant negative relation with annual ecological water supplement, which suggested that local precipitation should be considered as a key factor in determining the amount of annual water supplement. The frequency analysis was then implemented to provide reasonable scheme of actual ecological water supplement under different precipitation scenarios. The results indicated that annual ecological water supplement for the whole YRDNR was 1.81×108 m3, 1.94×108 m3, 2.10×108 m3 and 2.25×108 m3 respectively under wet, average, dry and extreme dry conditions. If water storage measurements are implemented to store surplus precipitation under rainy season, the average volume would reduce by nearly 10%.

Design and Implementation of the Inner Mongolia Meteorological Service Intranet APP

The new media platform based on internet, like WeChat and other mobile phone applications (APPs), can provide meteorological information to users more conveniently and efficiently than the traditional platforms, such as TV, telephone, short message, etc. Therefore, an intranet APP is developed in Inner Mongolia Meteorological Information Center to realize the rapid acquisition of meteorological information in the 70th anniversary celebration of the Inner Mongolia Autonomous Region. Based on user experience and user demands, the APP offers multiple meteorological service products covering meteorological observations and forecasts. It quickly displays the data from the critical regional automatic stations and mobile meteorological stations for relevant users. In this way, it provides seamless, all-round, refined and targeted meteorological services throughout the celebration.

Short-term effects of ambient temperature and road traffic accident injuries in Dalian, Northern China: A distributed lag non-linear analysis

BackgroundAlthough traffic accidents cause considerable economic losses and injuries to individuals, families, and communities, little is known about the impact of meteorological factors on the incidence of traffic accident injuries (TAIs). Therefore, a time-series study was conducted to explore the effect of meteorological variables on TAIs in Dalian, Northern China. MethodsPoisson generalized linear models (PGLM) combined with distributed lag nonlinear models (DLNM) were used to estimate the association between daily TAIs and ambient temperature in Dalian, China, 2015–2017. The injury data collected by Dalian national injury surveillance hospitals, and meteorological data were extracted and accumulated from the National Meteorological Information Center. Modified the model with variables such as pressure, humidity, precipitation, PM2.5, SO2, O3, day of the week, seasonality, and time trend. In the subgroup analysis, the modification effects of gender and age were also examined. ResultsBoth high temperatures (RR = 1.198, 95％CI：1.017–1.411) and low temperatures (RR = 1.017, 95％CI：1.001–1.035) increased the risk of TAIs. The cumulative lag effect would last until after the 7th day. While the 40−59 years subgroup seemed to be more vulnerable in high temperature environments, those who are more than 60 years showed higher TAIs in low temperatures for both single-day and cumulative TAI risks. ConclusionsIdentifying the association between ambient temperature and traffic injuries could provide needed scientific evidence for relevant public health actions.