Meteorological Information Center Research Articles

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.

Integration, Quality Assurance, and Usage of Global Aircraft Observations in CRA

This paper presents a detailed description of integration, quality assurance procedure, and usage of global aircraft observations for China’s first generation global atmospheric reanalysis (CRA) product (1979–2018). An integration method named “classified integration” is developed. Aircraft observations from nine different sources are integrated into the Integrated Global Meteorological Observation Archive from Aircraft (IGMOAA), a new dataset from the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA). IGMOAA consists of global aircraft temperature, wind, and humidity data from the surface to 100 hPa, extending from 1973 to the present. Compared with observations assimilated in the Climate Forecast System Reanalysis (CFSR) of NCEP, the observation number of IGMOAA increased by 12.9% between 2010 and 2014, mainly as a result of adding more Chinese Aircraft Meteorological Data Relay (AMDAR) data. Complex quality control procedures for aircraft observations of NCEP are applied to detect data errors. Observations are compared with ERA-Interim reanalysis from 1979 to 2018 to investigate data quality of different types and aircraft, and subsequently to develop the blacklists for CRA. IGMOAA data have been assimilated in CRA in 2018 and are real-time updated at the CMA Data-as-a-Service (CMADaaS) platform. For CRA, the fits to observations improve over time. From 1994 to 2018, root-mean-square error (RMSE) of observations relative to CRA background decreases from 1.8 to 1.0°C for temperature above 300 hPa, and from 4.5 to 3 m s−1 for zonal wind. The RMSE for humidity appears to exhibit an apparent seasonal variation with larger errors in summer and smaller ones in winter.

Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Its Response to Climate Factors in the Ili River Valley Region of China.

Background: As the global climate changes, the number of cases of hand-foot-and-mouth disease (HFMD) is increasing year by year. This study comprehensively considers the association of time and space by analyzing the temporal and spatial distribution changes of HFMD in the Ili River Valley in terms of what climate factors could affect HFMD and in what way. Methods: HFMD cases were obtained from the National Public Health Science Data Center from 2013 to 2018. Monthly climate data, including average temperature (MAT), average relative humidity (MARH), average wind speed (MAWS), cumulative precipitation (MCP), and average air pressure (MAAP), were obtained from the National Meteorological Information Center. The temporal and spatial distribution characteristics of HFMD from 2013 to 2018 were obtained using kernel density estimation (KDE) and spatiotemporal scan statistics. A regression model of the incidence of HFMD and climate factors was established based on a geographically and temporally weighted regression (GTWR) model and a generalized additive model (GAM). Results: The KDE results show that the highest density was from north to south of the central region, gradually spreading to the whole region throughout the study period. Spatiotemporal cluster analysis revealed that clusters were distributed along the Ili and Gongnaisi river basins. The fitted curves of MAT and MARH were an inverted V-shape from February to August, and the fitted curves of MAAP and MAWS showed a U-shaped change and negative correlation from February to May. Among the individual climate factors, MCP coefficient values varied the most while MAWS values varied less from place to place. There was a partial similarity in the spatial distribution of coefficients for MARH and MAT, as evidenced by a significant degree of fit performance in the whole region. MCP showed a significant positive correlation in the range of 15–35 mm, and MAAP showed a positive correlation in the range of 925–945 hPa. HFMD incidence increased with MAT in the range of 15–23 °C, and the effective value of MAWS was in the range of 1.3–1.7 m/s, which was positively correlated with incidences of HFMD. Conclusions: HFMD incidence and climate factors were found to be spatiotemporally associated, and climate factors are mostly non-linearly associated with HFMD incidence.

Evaluation of the efficiency of the imperative ecological remediation regarding tree growth, root development, and edaphic properties after Typhoon Hato (2017) in Zhuhai, China.

Background: urban forest in coastal cities encounters multiple disturbances of frequent typhoon events caused by global change, under which ecological remediation can help to improve urban environment. We measured and analyzed the growth and ecosystem services of four newly-planted tree species in Zhuhai after Typhoon Hato (2017), aiming to evaluate the efficiency of the ecological remediation. Methods: National Meteorological Information Center of China supplied climate variables. From June 2018 to December 2019, we measured soil physical and chemical properties, above- and below-ground development regarding stem, tree height, and root growth of all the selected tree species. Results: Sl (Sterculia lanceolata Cav.), Ir (Ilex rotunda Thunb), Ss (Schima superba Gardn. et Champ.) could be more wind-resistant from the above-ground morphological perspective. For the below-ground process, Sl was the only tree species with continuous development, while Ir, Ss, and Es (Elaeocarpus sylvestris (Lour.) Poir.) decreased. Furthermore, Sl, Ir, and Ss maintained their investment in deep roots when Es had apparent deep root biomass reduction. The edaphic condition showed notable improvement in chemical properties rather than physical properties, especially for AN (available nitrogen), AK (available potassium), and SOM (soil organic matter). Conclusions: The ecological remediation in Zhuhai after Typhoon Hato (2017) was efficient, and in the future, tree species like Sl with advantages in root development and morphological profile were preferentially recommender for plantation in typhoon-affected areas.

Effects of meteorological factors on daily outpatient visits for skin diseases: a time series study in a Chinese population

Effects of meteorological factors on daily outpatient visits for skin diseases: a time series study in a Chinese population

Association between extreme heat and hospital admissions for cataract patients in Hefei, China

Cataract is the first cause of blindness and the major cause of visual impairment worldwide. Under conditions of global warming, researchers have begun to give attention to the influence of increasing temperature on cataract patients. Our paper aimed to investigate the association between extreme heat and hospital admissions for cataract in Hefei, China. Based on data from the New Rural Cooperative Medical System and National Meteorological Information Center, we used a generalized additive model and a distributed lag nonlinear model to examine the relationship between extreme heat and hospitalizations for cataract, with consideration of cumulative and lagged effects. When current mean temperature was above 28 °C, each 1 °C rise was associated with a 4% decrease in the number of cataract admissions (RR = 0.96, 95% CI = 0.94–0.98). The cumulative relative risk over 11 days of lag was the lowest, which indicated that every 1 °C increase in mean temperature above 28 °C was associated with a 19% decrease in the number of hospital admissions for cataract (RR = 0.81, 95% CI = 0.75–0.88). In subgroup analyses, the negative association between extreme heat and hospital admissions for cataract was stronger among patients who were not admitted to provincial-level hospitals. In conclusion, this paper found that extreme heat was negatively associated with cataract hospitalizations in Hefei, providing useful information for hospitals and policymakers.

Application of 4G IOT Card in Automatic Weather Station

The “Industry Application Card” (an SIM card of the 2G dedicated line network) for the automatic transmission of weather station data widely used by the meteorological department of Liaoning Province had been strictly investigated, and it was found that the “Industry Application Card” supports the access between the public network and the private network, and allows text messages to be sent to the “civil SIM card” of the public network through the private network, so it is the preferred SIM card for telecom fraudsters. The 4G IoT card solves these problems. Open the Ping Tester app after inserting the IoT SIM card into the tester mobile, then use it to ping the IP address of the server in Liaoning Meteorological Information Center. A successful connection would imply that the connection to the Liaoning Meteorological Information Center’s Intranet via IoT is functional, and that the IoT SIM card can be used to automatically transmit the meteorological station’s data. The automatic weather stations generally using the automatic weather station models of local meteorological bureaus in Liaoning Province can use “Huayun Shangtong local maintenance management software” for the parameters configuration of automatic weather stations. After the “Huayun Shangtong local maintenance management software” is connected to the port of the automatic weather station, by finding the matched automatic weather station type, entering the error diagnosis interface of the corresponding station type, clicking the “Start Monitoring” button to read the device status information.

Projection of heat wave in China under global warming targets of 1.5 °C and 2 °C by the ISIMIP models

Heat waves in China were projected under 1.5 °C and 2 °C of warming targets using the bias-adjusted simulations of 4 GCMs obtained from ISIMIP2b. The simulations of GCMs on heat wave over China during historical period of 1986–2005 were examined against daily gridded observation CN05 from National Meteorological Information Center of China. In this evaluation, three heat wave definitions respectively with absolute, relative and combined threshold were used. The results indicated that the spatial distribution of heat wave indices, including heat wave days and heat wave magnitude, could be reasonably reproduced by the simulations obtained from ISIMIP2b, and the centers over Xinjiang and Jianghuai areas could be well captured by the multi-model ensemble (MME). Among three definitions based on different thresholds, the heat wave definition based on combined threshold outperformed other two definitions with the higher correlation coefficient with observation, particularly the heat wave days (0.89) and heat wave duration (0.89). In addition, the temporal evolutions of simulated heat waves indices were generally in good agreement with observations, particular the heat wave magnitude, but with lower trend of heat wave days (0.72 days/decade) and duration (0.17 days/decade) than those in observation (1.73 days/decade and 0.41 days/decade) due to the positive bias before 1990s. The features of heat waves over China under 1.5 and 2 °C warming targets projected by the ISIMIP were explored further. The periods of 2020–2039 under RCP2.6 scenario and 2040–2059 under the RCP4.5 scenario were selected to represent the 1.5 °C and 2 °C warming targets, respectively. The MME suggested that the heat wave will increase significantly in terms of days, duration and magnitude over China. The averaged heat wave days and heat wave duration were projected to reach 10.8 days and 3.9 days under 1.5 °C warming target, which was around 1.86 and 1.56 times relative to those during historical period. Notably, the increases of heat wave were at a higher rate under 2 °C of warming target than 1.5 °C of warming target, with the heat wave days and heat wave duration were about 2.53 and 2.00 times of those during historical period. Moreover, the heat wave magnitude was projected to reach 35.2 °C and 35.4 °C, with the highest frequency fall in the range of 34.9–35.2 °C and 35.5–35.8 °C under 1.5 °C and 2 °C of warming targets, respectively.

Association between fine particle exposure and common test items in clinical laboratory: A time-series analysis in Changsha, China

Most studies on the health effects of PM2.5 (fine particulate matter with diameter smaller than 2.5 μm) use indirect indicators, such as mortality and number of hospital visits. Recent research shows that biomarkers can also be used to evaluate the health effects of PM2.5; however, these biomarkers are not very common. Clinical laboratories can provide a significant amount of test data that have been proven to have important diagnostic value. Therefore, we use big data analysis methods to find the associations between clinical laboratory common test items and PM2.5 exposure. Data related to air pollution and meteorological information between 2014 and 2016 were obtained from the China National Environmental Monitoring Centre and the China National Meteorological Information Center. Additionally, data of 27 common test items from the same period were collected from Changsha Central Hospital. Primary analyses included a generalized additive model to analyze the associations between PM2.5 concentration and common test items; the model was adjusted for time trends, weather conditions (temperature and humidity), and days of the week. Furthermore, we adjusted the effects of other air pollutants, such as PM10, SO2, NO2, CO, and O3. 17 items such as TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, LDL, WBC, K, Cl, Ca, TT, and FIB were significantly positively associated with PM2.5 concentration (P< 0.05) and have concentration-response relationship. After adjusting the effect of PM10+SO2+NO2+CO+O3, TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, WBC, Cl, and Ca were still significantly associated with PM2.5 concentration (P< 0.05). This current study suggested that clinical laboratory common test items may be used to assess and predict the health effects of PM2.5 on the population.

Monitoring of gamma radiation in aseismic region and its response to seismic events

The surface gamma dose was monitored by RS-230 gamma spectrometer in aseismic region from March 2018 to April 2019. The behavior of gamma radiation were analyzed, the results show that is obviously affected by rainfall. Based on the meteorological dataset provided by National Meteorological Information Center, the method for quantitative removal of rainfall interference is proposed. The statistical uncertainty is an intrinsic property of radionuclide and has a significant impact on gamma data. This paper proposed the method to remove statistical uncertainty of gamma radiation based on singular value decomposition and signal-to-noise ratio, which reduced the statistical uncertainty of radiation and preserves the interesting information. The characteristic response of gamma radiation monitoring to seismic activity is analyzed with the data provided by China Earthquake Data Center, and the result showed that the gamma radiation in aseismic region had a certain indication on seismic events.

Relationships between convective activity in the Maritime Continent and precipitation anomalies in Southwest China during boreal summer

Using the outgoing long-wave radiation (OLR) data from NOAA, the ERA-Interim reanalysis products from ECMWF, and daily observations at 756 stations provided by National Meteorological Information Center of China Meteorology Administration, we have examined the relationships of interannual variations of summer precipitation in Southwest China with the convective activity in the Maritime Continent (MC) region by employing the singular value decomposition (SVD) method and the regional climate model RegCM4.4. The first SVD mode (here after SVD1) indicates that high precipitation anomalies in Southwest China correspond to abnormally weak convective activity in northeastern MC and strong convective activity in Southwestern MC if the time-series of coefficients of SVD1 is in positive phase. When convective activity are anomalously strong in Southern MC, the anomalous divergence at 700 hPa and convergence at 200 hPa are observed over the tropical western Pacific and South China Sea. The propagation of wave energy at 700 hPa from Western Europe and the tropics provide a favorable condition for inducing more precipitation in most of Southwest China. The atmospheric water vapor transport from northern Indochina and the South China Sea to Southwest China intensifies while the western Pacific subtropical high is stronger than normal and extends more westward. All these results along with the simulations demonstrate that the summer precipitation in Southwest China is significantly affected by the convective activity over the MC region. These results above are helpful for our better understanding the role of the MC in regulating the summer climate in Southwest China.

Anomalous Circulation Patterns in Association with Summertime Regional Daily Precipitation Extremes over Northeast China

Based on the NCEP/NCAR daily reanalysis product, NOAA monthly sea surface temperature (SST) dataset, and daily precipitation data collected at observational stations provided by Meteorological Information Center of China Meteorological Administration, the present study analyzes characteristic circulation anomalies conducive to regional extreme daily precipitation in the summer over Northeast China. Results indicate that 26 extreme precipitation events occurred during the 36-year period of 1979–2014. The precipitation threshold for the 99th percentile is 22.2 mm/d, and the maximum extreme daily precipitation occurred in Liaoning Province. When extreme precipitation occurs, Northeast China is located to the southeast of an anomalous cyclonic circulation and northwest of an anomalous anticyclonic circulation, where a strong convergence zone is formed in the lower troposphere. The low-level convergence and upper-level divergence as well as the baroclinic circulation structure are favorable for the development of extreme daily precipitation. Meanwhile, there exist two symmetrical meridional circulations to the north and south of Northeast China. The two meridional circulations share the same ascending branch, which is conducive to the occurrence of precipitation. Located in the strong convergence zone to the southeast of the abnormal cyclonic circulation and northwest of the abnormal anticyclonic circulation, huge amounts of water vapor from the Inner Mongolia, Russia, the Japan Sea, and the mid-high latitudes of the Northwest Pacific are transported to Northeast China, providing sufficient water vapor condition for the occurrence of extreme daily precipitation in this region. In addition, daily extreme precipitation in Northeast China is also closely related to the accumulation and convergence of disturbance energy in Northeast China. It may also be related to the abnormal SST distribution that is high in the north and low in the south. Corresponding to extreme daily precipitation, SST anomaly in the Pacific Ocean is roughly characterized by the feature of “positive-north and negative- south” with the equator as the boundary.

Association between rainfall and readmissions of rheumatoid arthritis patients: a time-stratified case-crossover analysis.

It has been reported that local weather is associated with the symptoms of joint pain in patients with rheumatoid arthritis (RA), and many people believe their pain becomes worse when facing rainy days. However, limited studies explored the effects of weather on RA patients' healthcare-seeking behavior. Our study aimed to investigate the relationship between rainfall and readmission behavior of patients with RA in Hefei, China, based on hospitalization data from the First Affiliated Hospital of Anhui University of Chinese Medicine from May 2012 to June 2016 and weather data from National Meteorological Information Center during the same study period. Using a time-stratified case-crossover study design and conditional logistic regression, we found a negative association between current day rainfall and readmission (unadjusted: OR = 0.82, p < 0.05; adjusted: OR = 0.83, p < 0.1), which is contrary to our common belief. In lagged models, we observed that rainfall was significantly and positively associated with readmissions at lag 6days (unadjusted: OR = 1.12, p < 0.1; adjusted: OR = 1.17, p < 0.05) and lag 7days (unadjusted: OR = 1.13, p < 0.05; adjusted: OR = 1.21, p < 0.01). Additionally, stratified analyses showed the unanticipated finding was only statistically significant for younger patients (< 65years) and females. Our study adds new evidence that the association between the healthcare-seeking behavior of patients with RA and local rainfall may be different, compared with the positive relationship between symptoms of joint pain and rainfall.

Effects of Long-Term Exposure to Air Pollution on the Resurgence of Scarlet Fever in China: A 15-Year Surveillance Study

Background: Aimed to investigate the association between the resurgence of scarlet fever and long-term exposure to air pollutants and weather conditions in China. Methods: Data on scarlet fever were from the National Notifiable Disease Reporting System. Air pollutants were from the National Environmental Protection Department, and weather conditions were from the National Meteorological Information Center. A lag non-linear model (DLNM) was used to estimate the excess risk of scarlet fever associated with air pollutants and weather conditions. Findings: 655,039 scarlet fever cases were reported during 2004-18. It started to surge in 2011 (4.7638 per 100 000), and peaked in 2018 (5.6736 per 100 000). The average incidence in 2011-18 was twice that in 2004-10 (rate ratio=2.302; 95% CI: 2.289-2.314; p<0.001]. There was a lowmoderate correlation between scarlet fever and monthly NO2 concentration (r=0.21), sunlight (r=0.28), and wind speed (r=0.24), but the others were weak [PM10 (r=0.13), ozone (r=0.11), and PM2.5 (r=0.05)]. By contrast, it was inversely correlated with monthly relative humidity (RH, r=-0.37), precipitation (r=-0.24) and mean temperature (r=-0.2). A one-unit increment of NO₂ concentration was associated with scarlet fever increased (RR=1.5, 95% CI: 1.35-1.66). The RR was recorded at lag 0 at 42 μg/m3 NO2 concentration (RR=1.15). NO2 pooled estimates varied substantially across China (RR=1.02~4.16), but were higher in northern parts. Interpretation: Long-term exposure to ambient NOâ‚‚ was associated with scarlet fever resurgence, triggered by low RH, temperature, precipitation, and high wind speed and sunshine. Further interventions to reduce NO2 emissions might suppress the resurgence of scarlet fever. Funding Statement: National Science and Technology Major Project of China (Grant no. 2016YFC0202005) and the National Natural Science Foundation of China (Grant no. 41975165, Grant no. 31700320), key epidemiological disciplines of Zhejiang Provincial Health of China, and Shenzhen Science and Technology Innovation Committee (Grant no. JCYJ20160427155352873). Declaration of Interests: The authors declared that they did not have a conflict of interest. Ethics Approval Statement: This study was done according to the principles and guidelines of the Declaration of Helsinki, and was approved by the Research Ethics Committee of the Zhejiang Provincial Center for Disease Control and Prevention. All initial information identifying patients was anonymized in this study.

MLC-LSTM: Exploiting the Spatiotemporal Correlation between Multi-Level Weather Radar Echoes for Echo Sequence Extrapolation.

Weather radar echo is the data detected by the weather radar sensor and reflects the intensity of meteorological targets. Using the technique of radar echo extrapolation, which is the prediction of future echoes based on historical echo observations, the approaching short-term weather conditions can be forecasted, and warnings can be raised with regard to disastrous weather. Recently, deep learning based extrapolation methods have been proposed and show significant application potential. However, there are two limitations of existing extrapolation methods which should be considered. First, few methods have investigated the impact of the evolutionary process of weather systems on extrapolation accuracy. Second, current deep learning methods usually encounter the problem of blurry echo prediction as extrapolation goes deeper. In this paper, we aim to address the two problems by proposing a Multi-Level Correlation Long Short-Term Memory (MLC-LSTM) and integrate the adversarial training into our approach. The MLC-LSTM can exploit the spatiotemporal correlation between multi-level radar echoes and model their evolution, while the adversarial training can help the model extrapolate realistic and sharp echoes. To train and test our model, we build a real-life multi-level weather radar echoes dataset based on raw CINRAD/SA radar observations provided by the National Meteorological Information Center, China. Extrapolation experiments show that our model can accurately forecast the motion and evolution of an echo while keeping the predicted echo looking realistic and fine-grained. For quantitative evaluation on probability of detection (POD), false alarm rate (FAR), critical success index (CSI), and Heidke skill score (HSS) metrics, our model can reach average scores of 0.6538 POD, 0.2818 FAR, 0.5348 CSI, and 0.6298 HSS, respectively when extrapolating 15 echoes into the future, which outperforms the current state-of-the-art extrapolation methods. Both the qualitative and quantitative experimental results demonstrate the effectiveness of our model, suggesting that it can be effectively applied to operational weather forecasting practice.

Spatiotemporal precipitation variability and potential drivers during 1961–2015 over the Yellow River Basin, China

Precipitation is a crucial element in the study of climate change and is a key component of climate change processes and the hydrological cycle. Changes in precipitation therefore have wide ranging implications across various fields, including agriculture, ecology and economic development. Known as the ’Mother River of China’, the Yellow River is the sixth longest river in the world and the second‐longest in the country, and has a unique political, economic and cultural role in China. Flowing through arid, semi‐arid and semi‐humid regions, it is well known for its high sand content and limited water resources. Precipitation in the Yellow River Basin (YRB) directly affects not only water security, but also eco‐system health and socio‐economic development. As a climatic phenomenon with characteristics that vary across both space and time, precipitation pattern analysis requires the examination of spatiotemporal changes. This study made use of interpolation grids in the analysis of data from all rainfall gauges associated with the National Meteorological Information Center and China Meteorological Administration; this constitutes a new and more representative method of assessing the spatiotemporal distribution of precipitation over the entire Yellow River basin. Moreover, the precipitation records for the last decade – in which significant variation has been found – were reanalysed to assess changes in precipitation patterns over the region. The results showed a slight increase in precipitation in the upper reaches of the river and the northern part of the basin, along with a slight decrease in the southern part and a significant increasing trend from 1990 to 2009 for areal average annual precipitation. The locations of annual precipitation maxima shifted to the west, especially for the 400mm isoline. Relative to the 1956–2000 series, the new updated series showed a reverse movement for the 400mm precipitation contours. The Hurst exponent indicated the presence of a random series for the longitudinal movement data and a sustained state for the latitude data. The potential drivers of variation in precipitation over the YRB were also explored, and an increase in the extent of vegetation cover was identified as the dominant influencing factor. However, given the huge uncertainty in projections of future global warming, climate change impacts should also be considered; for example, rapid temperature increases might result in the degradation of vegetation cover. The results of the study indicate that there is the potential for an increased risk of both urban and rural flooding in the YRB, with its unique water–sediment conditions, along with negative outcomes for agriculture and the eco‐environment.

Evaluation of Multi-Reanalysis Solar Radiation Products Using Global Surface Observations

Solar radiation incident at the Earth’s surface is an essential driver of the energy exchange between the atmosphere and the surface and is also an important input variable in the research on the surface eco-hydrological process. The reanalysis solar radiation dataset is characterized by a long time series and wide spatial coverage and is used in the research of large-scale eco-hydrological processes. Due to certain errors in their production process of the reanalysis of solar radiation products, reanalysis products should be evaluated before application. In this study, three global solar-radiation reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) in different temporal scales and climate zones were evaluated using surface solar-radiation observations from the National Meteorological Information Center of the China Meteorological Administration (CMA, Beijing, China) and the Global Energy Balance Archive (GEBA, Zürich, Switzerland) from 2000 to 2009. All reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) overestimated with an annual bias of 14.86 W/m2, 22.61 W/m2, and 31.85 W/m2; monthly bias of 15.17 W/m2, 21.29 W/m2, and 36.91 W/m2; and seasonal bias of 15.08 W/m2, 21.21 W/m2, and 36.69 W/m2, respectively. In different Köppen climate zones, the annual solar radiation of ERA-Interim performed best in cold regions with a bias of 10.30 W/m2 and absolute relative error (ARE) of 8.98%. However, JRA-55 and NCEP-DOE showed the best performance in tropical regions with a bias of 20.08 W/m2 and −0.12 W/m2, and ARE of 11.00% and 9.68%, respectively. Overall, through the evaluations across different temporal and spatial scales, the rank of the three reanalysis products in order was the ERA-Interim, JRA-55, and NCEP-DOE. In addition, based on the evaluation, we analyzed the relationship between the error (ARE) of the reanalysis products and cloud cover, aerosol, and water vapor, which significantly influences solar radiation and we found that cloud was the main cause for errors in the three solar radiation reanalysis products. The above can provide a reference for the application and downscaling of the three solar radiation reanalysis products.

The definition of heat-wave based on mortality risk assessment in different regions of China

Objective: To identify the definition of heat wave based on mortality risk assessment in different regions of China. Methods: Daily mortality (from China Information System for Disease Control and Prevention) and meteorological data (from National Meteorological Information Center in China) from 66 counties with a population of over 200 000 were collected from 2006-2011. With the consideration of climate type and administrative division, China was classified as seven regions. Firstly, distributed lag non-linear model (DLNM) was used to estimate community-specific effects of temperature on non-accidental mortality. Secondly, a multivariate meta-analysis was applied to pool the estimates of community-specific effects to explore the region-specific temperature threshold and the duration for definition of heat wave. Results: We defined regional heat wave of Northeast, North, Northwest, East, Central and Southwest China as being two or more consecutive days with daily mean temperature higher than or equal to the P(64), P(71), P(85), P(67), P(75) and P(77) of warm season (May to October) temperature, respectively, while the thresholds of temperature were 21.6, 23.7, 24.3, 25.7, 28.0 and 25.3 ℃. The heat wave in South China was defined as five or more consecutive days with daily mean temperature higher than or equal to the P(93) (30.4 ℃) of warm season (May to October) temperature. Conclusion: The region-specific definition of heat wave developed in our study may provide local government with the guidance of establishment and implementation of early heat-health response systems to address the negative health outcomes due to heat wave.

Village-level supply reliability of surface water irrigation in rural China: effects of climate change

Abstract. Surface water, as the largest part of water resources, plays an important role on China's agricultural production and food security. And surface water is vulnerable to climate change. This paper aims to examine the status of the supply reliability of surface water irrigation, and discusses how it is affected by climate change in rural China. The field data we used in this study was collected from a nine-province field survey during 2012 and 2013. Climate data are offered by China's National Meteorological Information Center which contains temperature and precipitation in the past 30 years. A Tobit model (or censored regression model) was used to estimate the influence of climate change on supply reliability of surface water irrigation. Descriptive results showed that, surface water supply reliability was 74 % in the past 3 years. Econometric results revealed that climate variables significantly influenced the supply reliability of surface water irrigation. Specifically, temperature is negatively related with the supply reliability of surface water irrigation; but precipitation positively influences the supply reliability of surface water irrigation. Besides, climate influence differs by seasons. In a word, this paper improves our understanding of the impact of climate change on agriculture irrigation and water supply reliability in the micro scale, and provides a scientific basis for relevant policy making.