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While previous work on the climatology of Northern China has focused on mean wind speed, wind gusts have received comparatively less attention but are equally important to various users. In this paper, an observed hourly maximum gust wind speeds (HMGS) dataset across North China has been created by using time series from 174 meteorological stations. The dataset offers superior quality, high spatiotemporal near-surface HMGS series for North China spanning from 2015 to 2022. The objective of this study is first to improve our understanding of the spatiotemporal gusts climatology in North China by analyzing the observed gust data. Second, we aim to supplement the observational data by using gust analysis and forecast data with a high spatial–temporal resolution from model simulations. The spatial characteristics of the seasonal cycle of the simulated analysis of mean HMGS and the performance in predicting gusts based on the geographical locations and elevations of the validation stations were investigated by comparing it with the observations. Results indicate the following: 1) Wind direction and intensity are affected by the terrain and climate conditions of different weather stations. Stations situated along the Bohai Bay coastal region and at higher-elevation areas of North China exhibit a higher mean HMGS than those located in the coastal and inland plains. 2) The probability density function curves for wind speed and wind direction exhibit notable variations across different elevation intervals. The contribution of moderate and strong gust wind speeds increases gradually with increasing altitude, while the gust directions in mountainous areas exhibit relatively consistent patterns due to the increased exposure to synoptic-scale forcing at higher elevations. 3) The nowcasting prediction system analysis of mean HMGS provides a higher horizontal resolution that is capable of capturing the contrasts between land and sea, as well as the influence of high HMGS associated with large-scale circulations in high-elevation regions. Significance Statement: The purpose of this study is to better understand the spatiotemporal gust climatology in North China and the performance of the model-simulated gust analysis and forecast data. This is important because gusts conditions differ due to varying topographic and climatic conditions of different weather stations. Our results provide a valuable insight into the climatological variations of HMGS, their drivers, and identify the deficiencies in the model-simulation gusts. [ABSTRACT FROM AUTHOR]

Drought is a common natural disaster that greatly affects the crop yield and water supply in China. However, the spatiotemporal characteristics of drought in China are not well understood. This paper explores the spatial and temporal distributions of droughts in China over the past 40 years using multiscale standardized precipitation evapotranspiration index (SPEI) values calculated by monthly precipitation and temperature data from 612 meteorological stations in China from 1980 to 2019 and combines the space–time cube (STC), Mann–Kendall test, emerging spatiotemporal hot-spot analysis, spatiotemporal clustering, and local outliers for the analysis. The results were as follows: 1) the drought frequency and STC show that there is a significant difference in the spatiotemporal distribution of drought in China, with the most severe drought in Northwest China, followed by the western part of Southwest China and the northern part of North China. 2) The emerging spatiotemporal hot-spot analysis of SPEI6 over the past 40 years reveals two cold spots in subregion 4, indicating that future droughts in the region will be more severe. 3) A local outlier analysis of the multiscale SPEI yields a low–low outlier in western North China, indicating relatively more severe year-round drought in this area than in other areas. The low–high outlier in central China indicates that this region was not dry in the past and that drought will become more severe in this region in the future. [ABSTRACT FROM AUTHOR]

Inland flooding and mudslides from tropical cyclone (TC) rainstorms are among the most destructive natural hazards in China, resulting in considerable direct economic losses and large numbers of fatalities. In this paper, a TC precipitation model (TCPM) is improved by incorporating the effects of complex terrain through a set of new parameters (e.g., slope, roughness, and attenuation distance) for a more accurate assessment of TC rainfall hazards in China. Moreover, by introducing parameterized spiral rainbands, the model could more accurately capture the intensity of extreme precipitation. The model comprehensively considers dynamic and thermodynamic precipitation factors and is adept at capturing the climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China. The model is verified by providing two comparisons. One is analysis including detailed results of three typical TC cases, and the other uses empirical cumulative distribution functions for extreme observations and simulations of historical landfalling TCs in China during the period 1960–2018. The comparisons reveal that the TCPM shows impressive performance for strong TCs with heavy precipitation within 200–300 km of the TC center. Moreover, both the modeled extreme hourly and total TC precipitation probability distributions are consistent with the observations. However, the model needs to be further improved for TCs with dispersive or long-distance precipitation. Significance Statement: In this paper, an optimized and physics-based model for the simulation of tropical cyclone precipitation is described and used to estimate the risk of TC rainfall hazards in China. The work is innovative in that it considers the effect of complex terrain from three perspectives, including slope, roughness, and attenuation distance. The simulations demonstrated that the model is adept at capturing the main climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China, which is simple to run several hundred thousand times, with bright application prospects in catastrophe risk assessment. [ABSTRACT FROM AUTHOR]

The southwest vortex (SWV) is a critical weather system in China, but our knowledge of this system remains incomplete. Here, we investigate the cloud properties in the SWV. First, we search for the SWVs with time steps and center locations that are consistent between the SWV yearbook and ERA-Interim reanalysis data. Second, we supplement these SWVs' life spans and movement paths. Third, we relocate the Fengyun (FY) satellite FY-4A cloud retrievals in the 10° × 10° region centered on each SWV and analyze the cloud occurrence frequency (COF), cloud-top height (CTH), and cloud optical thickness (COT). A distribution mode of cloud types is summarized from the COFs, with water clouds, supercooled clouds, mixed clouds, ice clouds, cirrus clouds, and overlap clouds occurring sequentially from west to east. The CTH probability density (PD) distribution features a significant north–south difference. In addition, the COT PD distributions exhibit a common trend: with increasing COT, the PD increases rapidly and then slowly before peaking, whereupon the PD decreases abruptly. From spring to summer, the region with the highest convective COF shifts from the northeast to the northwest, and an east–west gradient of the convective COF appears in autumn and winter. Furthermore, we investigate the cloud properties during SWV-related heavy rainfall. Heavy rain occurs mainly in the west of the SWV, and convective clouds are mainly in the northwest, partly in the southwest and near the SWV center. The average CTH in heavy rainfall is generally higher than 6 km, and the average COT is greater than 20. Significance Statement: The southwest vortex (SWV) is an important weather system in China. However, we do not yet comprehensively know this weather system. The cloud properties can indicate the structures of weather systems and are key parameters in numerical weather prediction (NWP) models. Thus, investigating cloud properties is necessary and meaningful to understand the SWV and accurately predict SWV-related precipitation in NWP models. In this paper, a typical distribution mode of six cloud types in the SWV is summarized from the cloud occurrence frequency, and the distribution features of convective clouds, cloud-top height, and cloud optical thickness in the SWV are analyzed. Furthermore, the cloud properties in SWV-related heavy rain are also studied. [ABSTRACT FROM AUTHOR]

Drought forecasts could effectively reduce the risk of drought. Data-driven models are suitable forecast tools because of theirminimal information requirements. Themotivation for this study is that because most data-driven models, such as autoregressive integrated moving average (ARIMA) models, can capture linear relationships but cannot capture nonlinear relationships they are insufficient for long-term prediction. The hybrid ARIMA-support vector regression (SVR) model proposed in this paper is based on the advantages of a linear model and a nonlinear model. The multiscale standard precipitation indices (SPI: SPI1, SPI3, SPI6, and SPI12) were forecast and compared using the ARIMA model and the hybrid ARIMA-SVR model. The performance of all models was compared using measures of persistence, such as the coefficient of determination, root-mean-square error, mean absolute error, Nash-Sutcliffe coefficient, and kriging interpolation method in the ArcGIS software. The results show that the prediction accuracies of the multiscale SPI of the combined ARIMA-SVR model and the single ARIMA model were related to the time scale of the index, and they gradually increase with an increase in time scale. The predicted value decreases with increase in lead time. Comparing the measured data with the predicted data from the model shows that the combined ARIMA-SVR model had higher prediction accuracy than the single ARIMA model and that the predicted results 1-2 months ahead show reasonably good agreement with the actual data. [ABSTRACT FROM AUTHOR]

In aiming for better access to climate change information and for providing climate service, it is important to obtain reliable high-resolution temperature simulations. Systematic comparisons are still deficient between statistical and dynamic downscaling techniques because of their inherent unavoidable uncertainties. In this paper, 20 global climate models (GCMs) and one regional climate model [Providing Regional Climates to Impact Studies (PRECIS)] are employed to evaluate their capabilities in reproducing average trends of mean temperature (Tm), maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), and extreme events represented by frost days (FD) and heat-wave days (HD) across China. It is shown generally that bias of temperatures from GCMs relative to observations is over ±1°C across more than one-half of mainland China. PRECIS demonstrates better representation of temperatures (except for HD) relative to GCMs. There is relatively better performance in Huanghuai, Jianghuai, Jianghan, south Yangzi River, and South China, whereas estimation is not as good in Xinjiang, the eastern part of northwest China, and the Tibetan Plateau. Bias-correction spatial disaggregation is used to downscale GCMs outputs, and bias correction is applied for PRECIS outputs, which demonstrate better improvement to a bias within ±0.2°C for Tm, Tmax, Tmin, and DTR and ±2 days for FD and HD. Furthermore, such improvement is also verified by the evidence of increased spatial correlation coefficient and symmetrical uncertainty, decreased root-mean-square error, and lower standard deviation for reproductions. It is seen from comprehensive ranking metrics that different downscaled models show the most improvement across different climatic regions, implying that optional ensembles of models should be adopted to provide sufficient high-quality climate information. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

The research and application of convolutional neural networks (CNNs) on statistical downscaling have been hampered by the fact that deep learning is highly dependent on sample size and is considered to be a black-box model. Therefore, a CNN model with transfer learning (CNN-TL) is proposed to study the pre-rainy season precipitation of South China. First, an augmented monthly dataset is created by sliding a fixed-length window over the daily circulation field and precipitation data for the entire year. Next, a base CNN network is pretrained on the augmented dataset, and then the network parameters are tuned on the actual monthly dataset from South China. Then, guided backpropagation is conducted to obtain the distribution regions of the key features and explain the net. The coefficient of determination R2 and root-mean-square error (RMSE) show that the CNN-TL model has higher explanatory power and better fitting performance than the feature extraction–based random forest. In comparison with the base CNN, the transfer learning approach can improve the explanatory power of the model by 10.29% and reduce the average RMSE by 6.82%. In addition, the interpretation results of the model show that the critical regions are primarily South China and its surrounding areas, including the Indochina Peninsula, the Bay of Bengal, and the South China Sea. Furthermore, the ablation experiments and composite analysis illustrate that these regions are very important. Significance Statement: To mitigate the challenges posed by small sample sizes and the transparency of deep learning in downscaling problems, we propose a convolutional neural network based on sample augmentation and transfer learning to study the monthly precipitation downscaling problem during the preflood period in South China. In comparison with random forests and conventional convolutional neural networks, our model achieves an optimal interpretation rate and stability. In addition, we explore the interpretability of the model using guided backpropagation to find the distribution of key features within the large-scale circulation field, thus increasing the credibility of the model. [ABSTRACT FROM AUTHOR]

The accurate real-time detection of turbulent airflow patterns near airports is important for safety and comfort in commercial aviation. In this paper, a method is developed to identify Lagrangian coherent structures (LCS) from horizontal lidar scans at Hong Kong International Airport (HKIA) in China. LCS are distinguished frame-independent material structures that create localized attraction, repulsion, or high shear of nearby trajectories in the flow. As such, they are the fundamental structures behind airflow patterns such as updrafts, downdrafts, and wind shear. Based on a recently developed finite-domain--finite-time Lyapunov exponent (FDFTLE) algorithm from Tang et al. and on new Lagrangian diagnostics presented in this paper that are pertinent to the extracted FDFTLE ridges, the authors differentiate LCS extracted from lidar data. It is found that these LCS derived from horizontal lidar scans compare well to convergence and divergence suggested by vertical slice scans. At HKIA, horizontal scans are predominant: they cover much bigger azimuthal ranges as compared with only two azimuthal angles from the vertical scans. LCS extracted from horizontal scans are thus advantageous in providing organizing turbulence structures over the entire observational domain as compared with a single line along the vertical scan direction. In Part II of this study, the authors will analyze the evolution of LCS and their impacts on landing aircraft based on recorded flight data. [ABSTRACT FROM AUTHOR]

The new-generation multisatellite precipitation algorithm, namely, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG), version 6, provides a high resolution and large spatial extent and can be used to offset the lack of surface observations. This study aimed to evaluate the precipitation detection capability of GPMIMERG V06 Final Run products in different climatic and topographical regions of China for the 2014-20 period. This study showed that 1) GPM-IMERG could capture the spatial and temporal precipitation distributions in China. At the annual scale, GPM-IMERG performed well, with a correlation coefficient R .0.95 and a relative bias ratio (RBias) between 15.38% and 23.46%. At the seasonal scale, GPM-IMERG performed best in summer. At the monthly scale, GPM-IMERG performed better during the wet season (April-September) (RBias 5 7.41%) than during the dry season (RBias 5 13.65%). 2) GPMIMERG performed well in terms of precipitation estimation in Southwest China, Central China, East China, and South China, followed by Northeast China and North China, but it performed poorly in Northwest China and Tibet. 3) The climate zone, followed by elevation, played a leading role in the GPM-IMERG accuracy in China, and the main sources of GPM-IMERG deviation in arid and semiarid regions were missed precipitation and false precipitation. However, the influences of missed precipitation and false precipitation gradually increased with increasing elevation. Despite the obvious differences between the GPM-IMERG and surface precipitation estimates, the study results highlight the potential of GPM-IMERG as a valuable resource for monitoring high-resolution precipitation information that is lacking in many parts of the world. [ABSTRACT FROM AUTHOR]

In this paper, an integrated indicator-based system is established to map the suitability of spring soybean cultivation in northeast China. The indicator system incorporates both biophysical and socioeconomic factors, including the effects of temperature, precipitation, and sunshine on the individual development stages of the spring soybean life cycle. Spatial estimates of crop suitability derived using this indicator system are also compared with spring soybean planting areas to identify locations where there is scope for structural adjustment in soybean farming. Results of this study indicate that northeast China is moderately suited to spring soybean cultivation. Areas classified as suitable, moderately suitable, and unsuitable for soybean cultivation, respectively, occupy approximately 9.09 × 104, 11.45 × 104, and 7.99 × 104 km2, accounting for 11.5%, 10.11%, and 14.49% of the total area of northeast China. The Songnen and Sanjiang Plains are identified as the most and least suitable places, respectively, for spring soybean growth. A comparative analysis indicates that the suitable, moderately suitable, and unsuitable areas account for 24.78%, 46.30%, and 28.92%, respectively, of the total area presently under soybean cultivation. The analysis suggests that soybean cultivation in Heilongjiang Province is generally unfavorable, with equivalent percentages of 15.39%, 51.70%, and 32.91%. Results suggest that agricultural structural adjustment may be required to encourage farmers to grow spring soybeans. It is anticipated that this study will provide a basis for follow-up studies on crop cultivation suitability. [ABSTRACT FROM AUTHOR]

Impacts of climate change on agriculture are a major concern worldwide, but uncertainties of climate models and emission scenarios may hamper efforts to adapt to climate change. In this paper, a probabilistic approach is used to estimate the uncertainties and simulate impacts of global warming on wheat production and water use in the main wheat cultivation regions of China, with a global mean temperature (GMT) increase scale relative to 1961-90 values. From output of 20 climate scenarios of the Intergovernmental Panel on Climate Change Data Distribution Centre, median values of projected changes in monthly mean climate variables for representative stations are adapted. These are used to drive the Crop Environment Resource Synthesis (CERES)-Wheat model to simulate wheat production and water use under baseline and global warming scenarios, with and without consideration of carbon dioxide (CO2) fertilization effects. Results show that, because of temperature increase, projected wheat-growing periods for GMT changes of 1°, 2°, and 3°C would shorten, with averaged median values of 3.94%, 6.90%, and 9.67%, respectively. There is a high probability of decreasing (increasing) changes in yield and water-use efficiency under higher temperature scenarios without (with) consideration of CO2 fertilization effects. Elevated CO2 concentration generally compensates for the negative effects of warming temperatures on production. Moreover, positive effects of elevated CO2 concentration on grain yield increase with warming temperatures. The findings could be critical for climate-change-driven agricultural production that ensures global food security. [ABSTRACT FROM AUTHOR]

Land surface evaporation is an important component of the earth's surface hydrological cycle, as well as in the atmospheric energy and water balances. In China, different instruments have been used over time to measure evaporation. A small pan with 20-cm diameter was used at most meteorological stations from 1951 to 2002. After 1998, large pans with areas of 3000 cm2 each were adopted at most stations. Collocated small- and large-pan observations of evaporation have been made at major stations from 1998 to 2002. This makes developing a homogenous time series of evaporation measurements difficult. This paper describes how surface evaporation data collected in the past are merged with more recent data collected by automated weather stations. A statistical model was set up on the basis of collocated small- and large-pan observations of evaporation, using a second-generation statistical regression technique [partial least squares (PLS)]. The model succeeds in generating daily large-pan evaporation estimates from small-pan evaporation data and selected meteorological parameters. Interpolation is used to replace missing data. The reconstructed large-pan evaporation dataset covers 751 weather stations across China from 1951 to 2005. Cross-validation tests show that the relative error of the daily estimated evaporation derived from the PLS regression model is 19% with a monthly mean error rate approaching 0 mm. The spatial distribution and interannual-interdecadal trends of the reconstructed large-pan evaporation dataset and small-pan observations are similar. [ABSTRACT FROM AUTHOR]

In this paper, the characteristics of urban heat island (UHI) and boundary layer structures in the Beijing area, China, are analyzed using conventional and Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model (UCM) is used to simulate these urban weather features for comparison with observations. WRF is also used to test the sensitivity of model simulations to different urban land use scenarios and urban building structures to investigate the impacts of urbanization on surface weather and boundary layer structures. Results show that the coupled WRF/Noah/UCM modeling system seems to be able to reproduce the following observed features reasonably well: 1) the diurnal variation of UHI intensity; 2) the spatial distribution of UHI in Beijing; 3) the diurnal variation of wind speed and direction, and interactions between mountain–valley circulations and UHI; 4) small-scale boundary layer convective rolls and cells; and 5) the nocturnal boundary layer lower-level jet. The statistical analyses reveal that urban canopy variables (e.g., temperature, wind speed) from WRF/Noah/UCM compare better with surface observations than the conventional variables (e.g., 2-m temperature, 10-m wind speed). Both observations and the model show that the airflow over Beijing is dominated by mountain–valley flows that are modified by urban–rural circulations. Sensitivity tests imply that the presence or absence of urban surfaces significantly impacts the formation of horizontal convective rolls (HCRs), and the details in urban structures seem to have less pronounced but not negligible effects on HCRs. [ABSTRACT FROM AUTHOR]

Water vapor plays a key role in the global hydrologic cycle and in climatic change. However, the distribution and variability of water vapor in the troposphere are not understood well—in particular, in China with the complex Tibetan Plateau and the influence of the Asian and Pacific monsoons. In this paper, continuous global positioning system (GPS) observations for 2004–07 in China are used to produce precipitable water vapor (PWV) measurements; these measurements constitute the first investigation of PWV distribution and variability over China. It has been found that the stronger water vapor values are in southeastern China and the lower water vapor values are in northwestern China. These distributions are mainly affected by the latitude, topographical features, the season, and the monsoon. Water vapor variations over China are mainly dominated by seasonal variations. The strong seasonal cycles are in summer with maximum water vapor and in winter with minimum water vapor. The PWV in southeastern China has an annual amplitude of about 15 mm, much larger than in northwestern China at about 4 mm, and meanwhile the time of peak water vapor content is one month earlier than in other regions, probably because of the known rainy season (mei-yu). In addition, significant diurnal variations of water vapor are found over all GPS stations, with a mean amplitude of about 0.7 mm, and the peak value occurs around noon or midnight, depending on geographic location and topographical features. The semidiurnal cycle is weaker, with a mean amplitude of about 0.3 mm, and the first peak PWV value appears around noon. [ABSTRACT FROM AUTHOR]

The long-term characteristics of four hydrometeor species (cloud water, cloud ice, rain, and snow) in precipitating clouds over eastern China (divided into South China, Jianghuai, and North China) and their relationships with surface rainfall are first investigated using the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) hourly dataset from May to August during 1979–2020. The results show that the cloud water path decreases significantly from south to north as a result of the large-scale circulation and water vapor distribution, with the maximum value of 180 g m−2 in South China and only one-half of that value in North China. The slope in linear relationship between rainwater path and precipitation intensity is at the maximum (5.68 h−1) in South China, implying the highest conversion rate from rainwater to precipitation in this region. When the precipitation rate exceeds 15 mm h−1, the ice-phase hydrometeor contents in South China become the largest among the three regions, indicating that the cold-rain process is crucial to heavy rainfall. The moisture-related processes play a dominant role in the precipitation intensity. Although the contribution of hydrometeor advection to precipitation is generally between −5% and 5%, we found that it can jointly modulate the location of heavy rainfall. In addition, the peaks of cloud water path commonly appear 2–3 h ahead of precipitation, whereas the peaks of ice-phase particles occur 2 and 1 h behind the afternoon precipitation onset in South China and Jianghuai, respectively, which is mainly attributed to the different upward velocity and water vapor convergence in the mid–upper troposphere. Significance Statement: Reanalysis data and satellite retrievals have been widely used in investigating cloud water and cloud ice in nonprecipitating clouds. However, studies on long-term characteristics of precipitating hydrometeors in precipitating clouds, which are directly connected and crucial to surface rainfall, are still very limited to date because of limitations in observations of precipitating clouds. In this study, the latest ERA5 reanalysis hourly dataset is first used to quantitatively explore the climatological characteristics of four hydrometeors (cloud water, cloud ice, rain, and snow) in precipitating clouds as well as their relationships with precipitation intensity over eastern China from 1979 to 2020. The results advance our understanding of precipitation mechanisms from the perspective of hydrometeor climatology. [ABSTRACT FROM AUTHOR]

Correlation analysis between precipitable water vapor (PWV) and precipitation over China was conducted by combining high-quality PWV data based on 1999–2015 ground-based global positioning system (GPS) observations with the measurements at matched meteorological stations in the same period. The mean correlation coefficient at all the stations is approximately 0.73, indicating that there is a significant positive correlation between PWV content and precipitation measurements, and the comparison of correlation among different climate types suggests that the distribution characteristics of the correlation coefficients are distinctively related to different climate types. There is also some positive correlation between PWV and precipitation long-term trends, with the correlation coefficients of monthly anomalies ranging generally from 0.2 to 0.6. Furthermore, the intensity of both PWV and precipitation extremes shows a long-term upward trend overall, with the most-intense events showing more significant increases. The extreme precipitation–temperature scaling rate of changes can reach above Clausius–Clapeyron (CC) scaling, whereas that of the extreme PWV-temperature is sub-CC overall, with regional differences in the specific scaling values. The correlation analysis in this work is of great significance for long-term climate analysis and extreme weather understanding, which provides a valuable reference for better utilizing the advantages of PWV data to carry out the studies above. Significance Statement: Atmospheric water vapor is crucial to the climate system, especially in the context of global warming, and accurate knowledge of the correlation between precipitable water vapor (PWV) and precipitation is of great significance for long-term climate analysis and extreme precipitation weather forecasting. We take full advantage of the long-term homogeneity of ground-based GPS to conduct long-term correlation analysis between GPS-derived PWV and precipitation over China. Results show a significant positive correlation between them, and the degree of correlation is related to different climate types. The correlation of monthly anomalies is also positive, and, over the long-term, both water vapor and precipitation extremes have been increasing in intensity, with more significant increases occurring in the most-intense events. Extreme precipitation might increase beyond thermodynamic expectations, whereas PWV increases below expectations. [ABSTRACT FROM AUTHOR]

Under the intensification of global warming, the characteristics of the Three Rivers source region (TRSR; i.e., headwaters of the Yellow River, the Yangtze River, and the Lancang River) in China were diagnosed in the summer season from 1979 to 2015 using observations and reanalysis data. The diagnoses indicate that summer precipitation decreased from 1979 to 2002 [by 9.01 mm day−1 (10 yr)−1; p < 0.05 by Student's t test] and increased significantly after 2002 [by 5.52 mm day−1 (10 yr)−1]. This abrupt change year (2002) was further confirmed by the cumulative anomaly method, the moving t-test method, and the Yamamoto method. By compositing the thermodynamics before and after the abrupt change year (2002), the results reveal that increased water vapor and more substantial lower-level convergence were present over the TRSR during 2003–15. This marked interdecadal variability in the TRSR summer precipitation responded to the interdecadal position and intensity of the large-scale forcing East Asian westerly jet (EAWJ), which is significantly modulated by the low-frequency variability associated with Southern Oscillation index. The connection between the interannual TRSR precipitation and the location and intensity of EAWJ was also explored. The position index of the EAWJ is negatively (with correlation coefficient R of −0.446; p < 0.05 by Student's t test) correlated with the precipitation over the TRSR, implying that southward and northward years of EAWJ are respectively associated with intensifying and weakening the TRSR summer precipitation, whereas the intensity of EAWJ is insignificantly correlated with the TRSR summer precipitation. [ABSTRACT FROM AUTHOR]

Reanalysis datasets have been widely used in meteorological research, including studies of Northeast China cold vortices (NCCVs), where these datasets act as effective substitutes for observations. However, to date, no studies have focused on their performance in reproducing NCCVs. To address this knowledge gap, we adopted an automatic three-step identification algorithm (TIA) and used it to detect NCCVs from ERA5 and MERRA-2 reanalysis datasets spanning 39 warm seasons (May–September) during the period from 1980 to 2018. A comparative method was employed for a rough verification of the characteristics of the reproduced NCCVs. Moreover, a dataset derived from 1370 Chinese ground-based observational stations was used to verify the performance of the reanalysis models in reproducing the precipitation and air temperature associated with NCCVs. The results show that the TIA identified the majority of NCCVs, with an accuracy of approximately 90% from ERA5 or MERRA-2. Both reanalysis models can reproduce the characteristics of NCCVs (including location, strength, and duration), and both replicate air temperature better than precipitation. ERA5 and MERRA-2 showed strong consistency in reproducing the central longitude, central latitude, central height, and range of NCCVs, with correlation coefficients of 0.974, 0.972, 0.996, and 0.919, respectively, at the 99.9% significance level. The daily average 2-m temperatures in both reanalysis datasets were in good agreement with observations; however, overestimations of approximately 7°–8°C arose in steep high-altitude regions. In addition, both models tended to overestimate light rain (≤5 mm day−1) by approximately 1.2 mm and underestimate heavy rain (≥20 mm day−1) by over 6.7 mm. [ABSTRACT FROM AUTHOR]

The prevalence of low clouds significantly affects flight safety in Southwest China. However, relevant cloud parameters, especially low cloud-base height (LCBH), lack accurate forecasts. Based on the hourly atmospheric vertical profiles of ERA5 from 2008 to 2019, we developed a new algorithm for estimating LCBH by combining relative humidity (RH) threshold methods with convective condensation level (CCL) (RHs-CCL). To evaluate the performance of RHs-CCL, we use it to estimate the hourly LCBH of airports in Southwest China and compare the results with those based on the ground-based observations and the ERA5 CBH data. Using the observations as a ground truth, we compare the RHs-CCL algorithm with several existing algorithms with the following findings: 1) The correlation coefficient between RHs-CCL and observations reaches 0.5 on average, and the error of RHs-CCL is smaller than those of existing algorithms, with the minimum mean absolute error and root-mean-square error at the four airports studies being able to reach 243 and 321 m. 2) The bias score of RHs-CCL is 0.97 on average, and low clouds classification utilizing RHs-CCL attains the highest accuracy, up to 86%. 3) The errors of ERA5 CBH are the largest when compared with the others. 4) By implementing convective cloud occurrence condition and CCL, RHs-CCL has better applicability in regions of enhanced convective activity. These results suggest the potential of RHs-CCL as an algorithm moving forward for improvement of the LCBH estimates based upon high-resolution reanalysis products and for better predictions of the LCBH utilizing outputs from numerical weather prediction models. Significance Statement: The new algorithm developed in this study can accurately estimate low cloud-base heights from vertical profiles of atmospheric variables. It provides us a much more computationally efficient approach for predicting low cloud-base height relative to running cloud models, which is critical for weather forecasting at locations lacking computational resources and/or cloud modeling capability. In areas such as Southwest China, low clouds are very common, and they pose major threats to aviation safety. The new algorithm has been successfully integrated into the daily operation at Guiyang Airport in Southwest China and demonstrated excellent skills in estimating cloud-base heights. The implementation of the algorithm in aviation forecasting over a broader region is on the horizon. [ABSTRACT FROM AUTHOR]

Downbursts can produce severe damage in near-ground areas and can also pose serious threats to aircraft in flight. In this study, a high-resolution boundary layer model—the Boundary Layer Above Stationary, Inhomogeneous Uneven Surface (BLASIUS) model—is used to simulate the evolution of a downburst. The observational data collected in Tazhong, China, located in hinterland of the Taklimakan Desert, during the Boundary Layer Comprehensive Observational Experiment on 27 July 2016 are used as the thermodynamic initial field for the BLASIUS model. In addition, the impacts of the terrain on the structure, turbulence intensity, and maximum wind speed of the downburst are also investigated. The results show that the BLASIUS model can simulate the structure and evolution characteristics of downbursts. The cold pool becomes warm if an isolated hill is implanted in the model under the same model conditions. Both the movement speed of the head and the average wind speed of the downburst decrease, while the maximum wind speed increases. The scale of the hill affects the dynamic and thermodynamic structures of the downburst through obstruction and entrainment mixing. The maximum wind speeds occur on the windward slope, and the downburst passes over the hill in the various tests with a hill. The head of the cold pool becomes narrow and tall for larger hill width cases. The Froude number generally decreases as the height of the hill increases, and the downburst can pass over the hill. The results are helpful to improve our understanding of the effects that terrain blocking on downburst structure and near-ground wind shear. Significance Statement: Downbursts have the potential to cause significant damage to building structures and agricultural production and to cause unpredictable serious disasters. It is particularly important to understand the structure and evolution of downbursts. In addition, the influence of the topography on the structure and intensity of turbulent vortices during a downburst remain unclear. The results show that the Boundary Layer Above Stationary, Inhomogeneous Uneven Surface (BLASIUS) model can simulate the structure and evolution characteristics of downbursts. The cold pool becomes warm if an isolated hill is implanted in the model. The scale of the hill affects the dynamic and thermodynamic structures of the downburst through obstruction and entrainment mixing. The Froude number generally decreases as the height of the hill increases, and the downburst can pass over the hill. [ABSTRACT FROM AUTHOR]

The evolution of the average freezing depth and maximum freezing depth of seasonal frozen soil and their correlations with the average winter half-year temperature in Heilongjiang Province in China are analyzed. Linear regression, the Mann–Kendall test, and kriging interpolation are applied to freezing depth data from 20 observation stations in Heilongjiang Province from 1972 to 2016 and daily average temperature data from 34 national meteorological stations collected in the winters of 1972–2020. The results show that the average freezing depth decreases at a rate of 4.8 cm (10 yr)−1 and that the maximum freezing depth decreases at a rate of 10.1 cm (10 yr)−1. The winter half-year average temperature generally shows a fluctuating upward trend in Heilongjiang Province, increasing at a rate of 0.3°C (10 yr)−1. The correlations between the average and maximum freezing depths and the winter half-year average temperature are −0.53 and −0.49, respectively. For every 1°C increase in the average temperature during the winter half of the year, the average freezing depth decreases by 3.85 cm and the maximum freezing depth decreases by 7.84 cm. The average freezing depth sequence mutated in 1987, and the maximum freezing depth sequence mutated in 1988. The average temperature in the winter half-year displayed multiple abrupt changes from 1972 to 2020. The spatial variations in the average and maximum freezing depths are basically consistent with those in the average winter half-year temperature. These research results provide a theoretical basis for the design and site selection of hydraulic structures in cold areas and for regional development and agricultural planning. Significance Statement: The freeze–thaw balance in the frozen soil environment has been disrupted in recent years, and various degrees of degradation have occurred in the frozen soil. The degradation of frozen soil will further aggravate the greenhouse effect, which in turn will affect the accumulation of water in the soil and will have a significant impact on local agricultural production. This article uses Heilongjiang Province in China as an example. The results show that 1) the temperature in the winter half-year has exhibited an upward trend in recent years, 2) the temperature in the winter half-year has a considerable impact on the frozen soil environment, and 3) the response of the spatial distribution of frozen soil to temperature changes in the winter half-year is revealed. [ABSTRACT FROM AUTHOR]

The mesoscale vortex (MV) is an important rain-producing system. In this study, the reanalysis data and satellite precipitation products are used to classify MVs into three categories: mesoscale convective vortex (MCV), mesoscale stratiform vortex (MSV), and mesoscale dry vortex (MDV). Then, these three categories of midlevel MVs in China from 2007 to 2016 are investigated. A total of 21 053 MVs are obtained. Most MVs form in the northwest of parent convection, and 45% of MVs generate secondary convection. The Tibetan Plateau is the main MV source region. Steered by the westerlies, MVs mainly move eastward. MCV is active in summer, MDV in winter, and MSV in spring and autumn. MCV diurnal variations are closely related to local topography, and MDVs mainly form around midnight. Composite analyses show that MCVs form near the high-value center of convective available potential energy at the development stage of parent convection. The composite MCV forms near the low pressure trough and the thermal ridge at 500 hPa, and a low-level jet exists to the south of the MCV center. At the initiation and maturity stages of MCV, strong convergence and divergence respectively exist at low levels and 400 hPa. The vortex circulation mainly locates near 500 hPa. Above the vortex is a warm core associated with the latent heat release, and below is a cold anomaly related to the cold pool. In the downshear region, there is strong low-level convergence and ascending motion, higher humidity, and greater latent heat release, which favor the formation of secondary convection. [ABSTRACT FROM AUTHOR]

An indirect radar reflectivity assimilation scheme has been developed within the Weather Research and Forecasting model three-dimensional data assimilation system (WRF 3D-Var). This scheme, instead of assimilating radar reflectivity directly, assimilates retrieved rainwater and estimated in-cloud water vapor. An analysis is provided to show that the assimilation of the retrieved rainwater avoids the linearization error of the Z- qr (reflectivity-rainwater) equation. A new observation operator is introduced to assimilate the estimated in-cloud water vapor. The performance of the scheme is demonstrated by assimilating reflectivity observations into the Rapid Update Cycle data assimilation and forecast system operating at Beijing Meteorology Bureau. Four heavy-rain-producing convective cases that occurred during summer 2009 in Beijing, China, are studied using the newly developed system. Results show that on average the assimilation of reflectivity significantly improves the short-term precipitation forecast skill up to 7 h. A diagnosis of the analysis fields of one case shows that the assimilation of reflectivity increases humidity, rainwater, and convective available potential energy in the convective region. As a result, the analysis successfully promotes the developments of the convective system and thus improves the subsequent prediction of the location and intensity of precipitation for this case. [ABSTRACT FROM AUTHOR]

In this study, the total days, mean duration, and intensity of extreme hot events over southern China during the 1971–2020 warm seasons are analyzed on the basis of daily maximum and minimum temperatures, by comparing the newly proposed independent hot day (IHD), independent warm night (IWN), and compound extreme (CMPD; i.e., the continuous occurrences of hot days and hot nights) with the traditionally defined hot day and warm night. Relationships between the hot extremes and urbanization are explored with 1-km-resolution population density data. Results show obvious differences in the spatial distributions among IHD, IWN, and CMPD over southern China. Positive correlations of 0.43, 0.41, and 0.37 are found between the population density and the total days, mean duration, and mean intensity of CMPD, respectively, which are qualitatively similar to those using the traditional hot days and warm nights. In contrast, negative correlations between the IHD and IWN indices and the population density are found, because those indices are more apparent over rural areas. Moreover, total days, mean duration, and mean intensity of CMPD increase significantly, with trends of approximately 103%, 21%, and 38% decade−1, respectively, during the rapid urbanization period from the mid-1990s to 2020, which are about 4.9, 2.1, and 2.4 times their counterparts from 1970 to the mid-1990s, and less significant and smaller differences between the two eras are found in IHD and IWN. These results will provide a new scientific basis for evaluating climate models of hot extremes in southern China and have important implications for the other urbanized regions as well. [ABSTRACT FROM AUTHOR]

It is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s, northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over mid- and high-latitude Eurasia acts as an important thermal background. It is characterized by two dominant modes, the "consistent cooling" pattern and the "warm high-latitude Eurasia and cold midlatitude Eurasia" pattern, from the mid-1990s to the early 2010s. The two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of the Arctic Oscillation (AO), Ural blocking (UB), and Siberian high (SH) are all highly correlated with the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO directly affects the occurrence of LTE because of its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of UB and SH. Further analyses show that the winter temperature in mid- and high-latitude Eurasia and the AO are independent factors that influence the increase of LTE in northern China from the mid-1990s to the early 2010s. [ABSTRACT FROM AUTHOR]

Based on daily meteorological observation data in South China (SC) from 1967 to 2018, the spatiotemporal characteristics of the precipitation in SC over the past 52 years were studied. Only 8% of the stations showed a significant increase in annual rainfall, and there was no significant negative trend at any weather stations at a confidence level of 90%. Monthly rainfall showed the most significant decreasing and increasing trends in April and November, respectively. During the entire flooding season from April to September, the monthly rainfall at the weather stations in the coastal areas showed almost no significant change. The annual rainfall gradually decreased toward the inland area with the central and coastal areas of Guangdong Province as the high-value rainfall center. By using the empirical orthogonal function decomposition method, it was found that the two main monthly rainfall modes had strong annual signals. The first modal spatial distribution was basically consistent with the average annual rainfall distribution. Based on the environmental background analysis, it was found that during the flooding season the main water vapor to SC was transported by the East Asian summer monsoon and the Indian summer monsoon. In late autumn and winter, the prevailing wind from northeastern China could not bring much water vapor to SC and led to little precipitation in these two seasons. The spatial distribution of precipitation in SC during summer was more consistent with the moisture flux divergence distribution of the bottom layer from 925 to 1000 hPa rather than that of the layer from 700 to 1000 hPa. [ABSTRACT FROM AUTHOR]

The outdoor events of the 2022 Winter Olympics and Paralympics will be held in the mountain areas of Beijing–Zhangjiakou, North China, where there is a complete reliance on artificial snow production owing to the dry and cold weather conditions. To assess how favorable the meteorological conditions are to snowmaking at the mountain venues, we reconstructed the daily wet-bulb temperature by adopting the thin-plate smoothing spline function method, and then we assessed the potential number of snowmaking days at eight weather stations (928–2098 m MSL) from October to the next April (i.e., the ski season) during the period 1978–2017. Results showed that artificial snow production would have been possible on 121 (±14) to 171 (±12) days on average at the stations with the increases of altitude, and the number of days decreased at rates of 4.3–5.1 days decade−1 across four decades of the study period. The cause of the decrease was the warming trend, which affected the number of days in low-altitude sites simultaneously, but the reduction was delayed with increased elevation. At monthly scale, the number of snowmaking days was robust in wintertime but reduced in other months of the ski season, particularly in March in more recent subperiods at high-altitude stations, which was determined by the increase in high values of daily mean wet-bulb temperature. Further improvements in assessing snowmaking conditions require detailed microclimatic studies to reduce the uncertainties caused by meteorological conditions as well as combination with model-based methods to determine potential future changes. [ABSTRACT FROM AUTHOR]

Quantitative knowledge of the water and energy exchanges in agroecosystems is vital for irrigation management and modeling crop production. In this study, the seasonal and annual variabilities of evapotranspiration (ET) and energy exchanges were investigated under two different crop environments—flooded and aerobic soil conditions—using three years (June 2014–May 2017) of eddy covariance observations over a rice–wheat rotation in eastern China. Across the whole rice–wheat rotation, the average daily ET rates in the rice paddies and wheat fields were 3.6 and 2.4 mm day−1, respectively. The respective average seasonal ET rates were 473 and 387 mm for rice and wheat fields, indicating a higher water consumption for rice than for wheat. Averaging for the three cropping seasons, rice paddies had 52% more latent heat flux than wheat fields, whereas wheat had 73% more sensible heat flux than rice paddies. This resulted in a lower Bowen ratio in the rice paddies (0.14) than in the wheat fields (0.4). Because eddy covariance observations of turbulent heat fluxes are typically less than the available energy (Rn− G; i.e., net radiation minus soil heat flux), energy balance closure (EBC) therefore does not occur. For rice, EBC was greatest at the vegetative growth stages (mean: 0.90) after considering the water heat storage, whereas wheat had its best EBC at the ripening stages (mean: 0.86). [ABSTRACT FROM AUTHOR]

High-density surface networks have become available in recent years in a number of regions throughout the world, but their utility in high-resolution dynamic downscaling has not been examined. As an attempt to fill such a gap, a suite of high-resolution (4 km) dynamical downscaling simulations is developed in this study with the Weather Research and Forecasting (WRF) Model and observation nudging over Liaoning in northeastern China. Three experiments, including no nudging (CTL), analysis nudging (AN), and combined analysis nudging and observation nudging with surface observations (AON), are conducted to downscale the CFSv2 reanalysis with the WRF Model for the year 2015. The three 1-yr regional climate simulations were compared with the independent surface observations. The results show that observational nudging can improve the simulation of surface variables, including temperature, wind speed, humidity, and pressure, more than nudging large-scale driving data with AN alone. The two nudging simulations can improve the cold bias for the temperature of the WRF Model. For precipitation, both the simulations with AN and observation nudging can capture the pattern of precipitation; however, with the introduction of small-scale information at the surface, AON cannot further improve the simulation of precipitation. [ABSTRACT FROM AUTHOR]

Because downscaling tools are needed to support climate change mitigation and adaptation practices, the guarantee of their credibility is of vital importance. To evaluate downscaling results, one needs to select a set of effective and nonoverlapping indices that reflect key system attributes. However, this subject is still insufficiently researched. With this study, we propose a diagnostic framework that evaluates the credibility of precipitation downscaling using five different attributes: spatial, temporal, trend, extreme, and climate event. A daily variant of the bias-corrected spatial downscaling approach is used to downscale daily precipitation from the GFDL-ESM2G climate model at 148 stations in the Yangtze River basin in China. Results prove that this framework is effective in systematically evaluating the performance of downscaling across the Yangtze River basin in the context of climate change and exacerbating climate extremes. Moreover, results also indicate that the downscaling approach adopted in this study yields good performance in correcting spatiotemporal bias, preserving trends, approximating extremes, and characterizing climate events across the Yangtze River basin. The proposed framework can be beneficial to planners and engineers facing issues relevant to climate change assessment. [ABSTRACT FROM AUTHOR]

This study investigated heavy frontal rainfall that occurred on 13–14 October 2011 over the Pearl River Delta (PRD) in China. The frontal rainstorm was simulated using the WRF-ARW Model (version 3.3), which included its urban canopy model. Although the model-simulated convection occurred 2 h early and the second precipitation peak was underestimated, the model represented the formation, development, and extinction of the frontal rainfall and captured the distribution of the peak value. In addition, the averaged value of 49.7 W m−2 was taken as the anthropogenic heat flux (AHF) of the PRD, and two land-use datasets were adopted: one for 1992 and the other for 2011. The simulation revealed that AHF and urban land-use change (ULUC) increased the total rainfall over the PRD by 6.3% and 7.4% and increased the maximum hourly rainfall intensity by 24.6% and 21.2%, respectively. Furthermore, to elucidate the mechanism of AHF and ULUC influence, the rainstorm structure, low-level jet (LLJ), and CAPE of the rainfall event were analyzed. It was found that AHF and ULUC enhanced two strong southward LLJs located over the urban areas, which carried abundant water vapor to the PRD and generated additional upper-level CAPE. This not only sustained steady ascent of the air, but it also created conditions favorable for downward motion, resulting in large persistent convective clouds and heavy frontal rainfall. [ABSTRACT FROM AUTHOR]

A dataset of convection initiation (CI) is of great value in studying the triggering mechanisms of deep moist convection and evaluating the performances of numerical models. In recent years, the data quality of the operationally generated radar mosaics over China has been greatly improved, which provides an opportunity to retrieve a CI dataset from that region. In this work, an attempt is made to reveal the potential of applying a simple framework of objective CI detection for the study of CI climatology in China. The framework was tested using radar mosaic maps in South China that were accessible online. The identified CI events were validated in both direct and indirect ways. On the basis of a direct manual check, nearly all of the identified CI cells had an organized motion. The precipitation echoes of the cells had a median duration of approximately 2.5 h. The CI occurrences were further compared with rainfall estimates to ensure physical consistency. The diurnal cycle of CI occurrence exhibits three major modes: a late-night-to-morning peak at the windward coasts and offshore, a noon-to-late-afternoon peak on the coastal land, and an evening-to-early-morning peak over the northwestern highland. These spatial modes agree well with those of rainfall, indirectly suggesting the reliability of the CI statistics. By processing radar mosaic maps, such a framework could be applied for studying CI climatology over China and other regions. [ABSTRACT FROM AUTHOR]

An integrated winter field campaign was conducted to investigate the atmospheric boundary layer structure and PM2.5 concentration at three sites over the Yangtze River delta (YRD) in China: Shouxian (a rural area), a site in a northern suburb of Nanjing, and Dongshan (a residential area). Two temperature inversion layers and air pollution events occurred simultaneously from 30 to 31 December 2016, local time, over the YRD. It was found that the two inversion layers were related to the presence of a high pressure system, resulting in divergence in the upper boundary layer and radiative cooling near the ground at night. Dominated by agricultural and residential biomass burning, the surface emission sources from the Shouxian rural area were moderately strong. After the formation of the two inversions, the vertical distribution of PM2.5 concentration below the upper inversion layer was uniform as a result of thorough boundary layer mixing in the earlier hours. During nighttime at the Nanjing site, air pollutant plumes from nearby elevated point sources could not easily diffuse downward/upward between the two inversion layers, which led to a distinct peak in the PM2.5 concentration. At the Dongshan site, the emission sources were weak and the nighttime PM2.5 concentration above 100 m was high. The surface PM2.5 concentration gradually increased from early morning to noon, which was attributed to emissions related to the local residents. The results indicated that the vertical distribution of pollutants was affected by a combination of local emissions, vertical boundary layer structure, and horizontal and vertical transports. [ABSTRACT FROM AUTHOR]

A Met Office Hadley Centre regional climate model, HadRM3P, is used to dynamically downscale the NOAA Twentieth Century Reanalysis, version 2c (20CRv2c), to generate a fine-resolution reconstruction of China's climate from 1851 to 2010. The downscaled dataset has a small warm and seasonal wet bias (1.4°C; 0.9 mm day−1) relative to recent observations but otherwise represents spatial and temporal trends realistically. Analysis focused on temperature and precipitation shows that downscaling 20CRv2c is found to improve its representation of China's climatological annual cycle, particularly over areas with sparse observational coverage such as the Tibetan Plateau. The downscaled dataset better represents the interannual variability and trends in observed temperature since 1901 and suggests that China has experienced a significant and sustained increase in temperature of 0.05°C (10 yr)−1 since the 1850s. Chinese precipitation trends have not changed significantly in the recent past or over the past 160 years. This analysis serves as an initial yet imperative step toward improving in-depth understanding of the characteristics and multidecadal drivers of high-impact events over China such as heat waves, droughts, and extreme precipitation. [ABSTRACT FROM AUTHOR]

The Northeast Farming Region (NFR) of China is a critically important area of maize cultivation accounting for ~30% of national production. It is predominantly rain fed, meaning that adverse climate conditions such as drought can significantly affect productivity. Forewarning of such events, to improve contingency planning, could therefore be highly beneficial to the agricultural sector. For this, an improved estimate of drought exposure, and the associated large-scale circulation patterns, is of critical importance. We address these important questions by employing a large ensemble of initialized climate model simulations. These simulations provide 80 times as many summers as the equivalent observational dataset and highlight several limitations of the recent observational record. For example, the chance of a drought greater in area than any current observed event is approximately 5% per year, suggesting the risk of a major drought is significantly underestimated if based solely on recent events. The combination of a weakened East Asian jet stream and intensified subpolar jet are found to be associated with severe NFR drought through enhanced upper-level convergence and anomalous descent, reducing moisture and suppressing precipitation. We identify a strong 500-hPa geopotential height anomaly dipole pattern as a useful metric to identify this mechanism for relevance to seasonal predictability. This work can inform policy planning and decision-making through an improved understanding of the near-term climate exposure and form the basis of new climate services. [ABSTRACT FROM AUTHOR]

Understanding changes in subdaily rainfall extremes is critical to urban planners for building more sustainable and resilient cities. In this study, the hourly precipitation data in 1971–2016 from 61 rain gauges are combined with historical land-use change data to investigate changes in extreme hourly precipitation (EXHP) in the Pearl River delta (PRD) region of South China. Also, 120 extreme rainfall events (EXREs) during 2011–16 are analyzed using observations collected at densely distributed automatic weather stations and radar network. Statistically significant increase of hourly precipitation intensity leads to higher annual amounts of both total and extreme precipitation over the PRD urban cluster in the rapid urbanization period (about 1994–2016) than during the preurbanization era (1971 to about 1993), suggesting a possible link between the enhanced rainfall and the rapid urbanization. Those urbanization-related positive trends are closely related to more frequent occurrence of abrupt rainfall events with short duration (≤6 h) than the continuous or growing rainfall events with longer duration. The 120 EXREs in 2011–16 are categorized into six types according to the originating location and movement of the extreme-rain-producing storms. Despite the wide range of synoptic backgrounds and seasons, rainfall intensification by the strong urban heat island (UHI) effect is a clear signal in all the six types, especially over the inland urban cluster with prominent UHIs. The UHI thermal perturbation probably plays an important role in the convective initiation and intensification of the locally developed extreme-rain-producing storms during the daytime. [ABSTRACT FROM AUTHOR]

Haze days induced by aerosol pollution in North and East China have posed a persistent and growing problem over the past few decades. These events are particularly threatening to densely populated cities such as Beijing. While the sources of this pollution are predominantly anthropogenic, natural climate variations may also play a role in allowing for atmospheric conditions conducive to formation of severe haze episodes over populated areas. Here, an investigation is conducted into the effects of changes in global dynamics and emissions on air quality in China's polluted regions using 35 simulations developed from the Community Earth Systems Model Large Ensemble (CESM LENS) run over the period 1920–2100. It is shown that internal variability significantly modulates aerosol optical depth (AOD) over China; it takes roughly a decade for the forced response to balance the effects from internal variability even in China's most polluted regions. Random forest regressions are used to accurately model (R2 > 0.9) wintertime AOD using just climate oscillations, the month of the year, and emissions. How different phases of each oscillation affect aerosol loading is projected using these regressions. AOD responses are identified for each oscillation, with particularly strong responses from El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO). As ENSO can be projected a few months in advance and improvements in linear inverse modeling (LIM) may yield a similar predictability for the PDO, results of this study offer opportunities to improve the predictability of China's severe wintertime haze events and to inform policy options that could mitigate subsequent health impacts. [ABSTRACT FROM AUTHOR]

The planetary boundary layer (PBL) controls the exchange of momentum and energy between the ground surface and the free troposphere, but few studies have been involved in the connection of the PBL with the development and extinction of tropical cyclones (TCs). Studies on the PBL usually need high-resolution soundings in the lowest troposphere that are otherwise quite rare with traditional technology. Here, 1-s resolution L-band radiosonde data are acquired to study the variations in PBL characteristics associated with the development of TCs in eastern China. The strong variations in the vertical profiles of temperature, relative humidity, and wind speed in the PBL during the landfall of a TC are revealed. In addition, four typical methods, including the virtual potential temperature method, Holzworth method, bulk Richardson number method, and potential temperature gradient method, are applied to estimate the PBL height (PBLH). The results indicate that the PBLHs derived by these methods vary by several hundred meters, which may be related to their different definitions of kinetic or thermodynamic theories. Furthermore, the PBLH was found to display a slight upward tendency during the landfall of TC. [ABSTRACT FROM AUTHOR]

Climate Generator (CLIGEN) is a stochastic weather generator that has been widely used to generate daily precipitation and storm patterns for hydrological and erosion prediction models. Rainfall data with measurement intervals # 30 min are required to compute two parameters for generating storm patterns, namely, the cumulative distribution of the time to peak rainfall intensity (TimePk) and the mean daily maximum 30-min rainfall intensity (MX.5P). High-resolution rainfall data, however, are not widely available around the world. One-minute precipitation data for 18 stations in eastern and central China were aggregated into hourly intervals to evaluate methods to optimally prepare TimePk and MX.5P for CLIGEN. Four sets of the two parameters were used to run CLIGEN for comparison: C0, using the original 1-min data; C1, replacing TimePk with those computed with hourly data; C2, replacing MX.5P with those computed with hourly data with an adjustment factor; and C3, replacing both parameters with those computed with hourly data, and the MX.5P was adjusted as for C2. Results showed that 1) MX.5P computed with hourly data was systematically lower than that computed with the 1-min data, and the bias could be corrected by multiplying by an adjustment factor of 1.40; 2) the difference in generated storm patterns between C0 and C1 was insignificant; and 3) results from C2 and C3 agreed well with those generated from C0. Hourly precipitation data can be used to prepare CLIGEN input parameter values for generating storm patterns for sites where only hourly data are available. [ABSTRACT FROM AUTHOR]

Land surface models (LSMs) have been widely used to provide objective monitoring of soil moisture during drought, but large uncertainties exist because of the different parameterizations in LSMs. This study aims to evaluate the ability to monitor soil moisture drought over three key regions in China by using the Noah LSM from the Global Land Data Assimilation System, version 2 (GLDASv2), and the Community Atmosphere Biosphere Land Exchange (CABLE) model that is currently used at the China Meteorological Administration. The modeled soil moisture drought indices were verified against the standardized precipitation evapotranspiration index (SPEI), which served as a reference drought indicator over northern China (NC), northwestern China (NWC), and southwestern China (SWC) from 1961 to 2010. The results show that the precipitation forcing data that drive both LSMs have high accuracy when compared with local observational data. GLDASv2/Noah outperforms CABLE in capturing soil moisture anomalies and variability, especially in SWC, but both show good correlations with the 3-month SPEI (SPEI3) in NC, NWC, and SWC. The autumn drought of 2002 and spring drought of 2010 were selected for the comparison of the modeled drought categories with the SPEI3 drought category, where GLDASv2/Noah performed slightly better than CABLE. This work demonstrates that the choice of LSM is crucial for monitoring soil moisture drought and that the GLDASv2/Noah LSM can be a good candidate for the development of a new operational drought-monitoring system in China. [ABSTRACT FROM AUTHOR]

Cool roofs and green roofs are two important methods used to mitigate the urban heat island (UHI) effect. The Weather Research and Forecasting Model was used to investigate the UHI effect and the effectiveness of cool and green roof mitigation strategies in the Suzhou-Wuxi-Changzhou metropolitan area during an extreme heat wave episode in the summer of 2013. Both urban land-cover change and anthropogenic heat releases exacerbated high temperatures in the urban area. Notably, urban land-cover change and anthropogenic heat release were responsible for 64% and 36% of the UHI intensity, respectively. Both cool and green roofs decreased near-surface air temperatures. The most dramatic decrease in near-surface air temperature occurred in the late morning; nocturnal air temperature decreased slightly because of the decrease in urban heat storage associated with the cool roof strategy. In addition, the UHI mitigation strategies affected the entire urban boundary layer. The decrease in the potential temperature and static stability created a stable urban boundary layer in which turbulent kinetic energy (TKE) decreased simultaneously. Analysis of an urban belt near a large water body showed that the decrease in the surface skin temperature difference between land and the water body weakened the daytime lake breeze. This effect was observed in both the inflow in the boundary layer and the return flow above the boundary layer, and it decreased the heat and moisture exchange between the lake and land boundary layers. [ABSTRACT FROM AUTHOR]

Winter (December-February) haze days in the North China Plain (WHDNCP) have recently dramatically increased. In addition to human activities, climate change and variability also contributed to the severe situation and supported the possibility of seasonal predictions. In this study, using the generalized additive model (GAM), the sea surface temperature around the Alaska Gulf and sea ice area of the Beaufort Sea were selected as the predictors to establish a statistical prediction model (SPM). The difference between the current and previous year of WHDNCP (WDY) was predicted first and was then added to the observation of the previous year to obtain the final predicted WHDNCP. For WDY prediction, the root-mean-square error of the SPM using GAM was 3.01 days. In addition to the annual variation, the tropospheric biennial oscillation features and the dramatically increasing trend after 2010 were both captured successfully. Furthermore, for the final predicted WHDNCP anomalies, the long-term trend and turning points were simulated well, and the percentage of the same mathematical sign was 91.7%. Independent prediction tests were performed for 2014 and 2015, and the forecast bias was 0.86 and 0.19 days, respectively. To assess the predictive ability, recycling independent tests (including real-time hindcasts for the period 2005-15) were also applied, and the percentage of the same sign was 100%. [ABSTRACT FROM AUTHOR]

The diurnal variation of rainfall over China associated with landfalling tropical cyclones (TCs) is investigated using hourly rain gauge observations obtained from 2425 conventional meteorological stations in China. Records between 12 h prior to landfall and 12 h after landfall of 450 landfalling TCs in China from 1957 to 2014 are selected as samples. The harmonic analysis shows an obvious diurnal signal in TC rainfall with a rain-rate peak in the early morning and a minimum in the afternoon. The diurnal cycle in the outer region (between 400- and 900-km radii from the storm center) is found to be larger than in the core region (within 400 km of the storm center). This could be attributed to the effect of land on the inner core of the storms as the diurnal cycle is distinct in the core region well before landfall. As the result of this diurnal cycle, TCs making landfall at night tend to have cumulative precipitation, defined as the precipitation cumulated from the time at landfall to 12 h after landfall, about 30% larger than those making landfall around noon or afternoon. Moreover, the radial propagation of the diurnal cycle in TC rain rate, which has been a controversial phenomenon in some previous studies with remote sensing observations, was not present in this study that is based on rain gauge observations. Results also show that the diurnal signal has little dependence on the storm intensity 12 h prior to landfall. [ABSTRACT FROM AUTHOR]

Drought disasters cause great economic losses in China every year, especially in its southwest, and they have had a major influence on economic development, lives, and property. In this study, precipitation and drought hazards were examined for a region covering Yunnan, Guizhou, and Guangxi Provinces to assess the spatial and temporal distribution of different drought hazard grades in this region. Annual precipitation data from 90 meteorological stations in or around the study area were collected and organized for the period of 1964-2013. A spatiotemporal covariance model was calculated and fitted. The Bayesian maximum entropy (BME) method, which considers physical knowledge bases to reduce errors, was used to provide an optimal estimation of annual precipitation. Regional annual precipitation distributions were determined. To analyze the spatiotemporal patterns of the drought hazard, the annual standardized precipitation index was used to measure drought severity. A method that involves space-time scan statistics was used to detect the most likely spatiotemporal clusters of the drought hazards. Test-significance p values for all of the calculated clusters were less than 0.001, indicating a high significance level. The results showed that Yunnan Province was a drought-prone area, especially in its northwest and center, followed by Guizhou Province. In addition, Yunnan and Guizhou Provinces were cluster areas of severe and extreme drought. The most likely cluster year was 1966; it was clustered five times during the study period. In this study, the evolutionary process of drought hazards, including spatiotemporal distribution and spatiotemporal clustering characteristics, was considered. The results may be used to provide support for prevention and mitigation of drought in the study area such as optimizing the distribution of drought-resisting resources, drought monitoring, and evaluating potential drought impacts. [ABSTRACT FROM AUTHOR]

Management of water resources may benefit from seasonal precipitation forecasts, but for obtaining high enough resolution, dynamical downscaling is necessary. This study investigated the downscaling capability of the Weather Research and Forecasting (WRF) Model ARW, version 3.5, on seasonal precipitation forecasts for the Hanjiang basin in China during 2001-09, which was the water source of the middle route of the South-to-North Water Diversion Project (SNWDP). The WRF Model is forced by the National Centers for Environmental Prediction Operational Climate Forecast System, version 2 (CFSv2), and it performs at a high horizontal resolution of 10 km with four selected convection schemes. The National Oceanic and Atmospheric Administration's Climate Prediction Center global daily precipitation data were employed to evaluate the WRF Model on multiple scales. On average, when large biases were removed, the WRF Model slightly outperformed the CFSv2 in all seasons, especially summer. In particular, the Kain-Fritsch convective scheme performed best in summer, whereas little difference was found in winter. The WRF Model showed similar results in monthly precipitation, but no time-dependent characteristics were observed for all months. The spatial anomaly correlation coefficient showed greater uncertainty than the bias and the temporal correlation coefficient. In addition, the performance of the WRF Model showed considerable regional variations. The upper basin always showed better agreement with observations than did the middle and lower parts of the basin. A comparison of the forecast and observed daily precipitation revealed that the WRF Model can provide more accurate extreme precipitation information than the CFSv2. [ABSTRACT FROM AUTHOR]

Drought is a typical disaster in the main soybean production area of northeast China. The spatiotemporal variations of drought related to soybean production based on a crop water deficit index (CWDI) and sensitivity to meteorological variables were investigated in northeast China using daily meteorological data from 87 weather stations from 1981 to 2010. Statistical analysis revealed that precipitation could not meet the water demands of soybeans during the seedling-branching, filling, and maturing stages, and excessive drought occurred more often in northeast China. The Mann-Kendall test indicated that the soybean CWDI significantly increased during the filling stage. Kriging spatial analysis showed that the most drought-prone area was located in the west of northeast China. Explanations for the spatiotemporal variations of the drought for soybean production were explored in terms of meteorological variables. Statistical analysis showed that the crop evapotranspiration, air temperature, wind speed, and number of sunshine hours were significantly higher and the precipitation and relative humidity were significantly lower in the drought-prone area than in the dry area less prone to droughts. An explored method of sensitive analysis quantitatively revealed that precipitation and humidity negatively affected the CWDI, whereas temperature, wind speed, and number of sunshine hours positively affected the CWDI. The CWDI was most sensitive to precipitation. These results not only provide valuable information for soybean planning and management but also produce important background and physical evidence for the influence of climate on the drought related to soybean production in northeast China. [ABSTRACT FROM AUTHOR]

In this study, the spaliolemporal characteristics of cloud-to-ground (CG) and intracloud (IC) lightning flashes observed by Surveillance et Alerte Foudre par Inlerferometrie Radioelectrique (SAFIR)-3000 over the Beijing metropolitan region (BMR) during 2005-07 were investigated. The results showed the presence of 299 lightning days with 241 688 flashes, most of which were IC lightning flashes. Only 19% of the total flashes were CG lightning flashes; 14% of these CG flashes were positive. Most lightning activity occurred during the summer months (June-August), with a major diurnal peak around 1900 Beijing standard time (BST) and a secondary peak around 2300 BST. Spatial variations in flash density and lightning days both exhibited an obvious southeastwardly increasing pattern, with higher flash densities or more lightning days occurring in the southeastern plains and lower values distributed on the northwestern mountains. The Z ratio (IC/CG lightning flashes) exhibited a similar spatial pattern, but the percentage of positive CG lightning flashes showed an almost opposite pattern. The results also showed significant topographic effects on the spatiotemporal variations in lightning activity. That is, flash counts on the northeastern and southwestern mountains peaked in the afternoon, whereas those on the southeastern plains peaked in the late night to early morning, which could be attributed to the propagation of thunderstorms from the mountains to the plains. The results showed that the SAFIR-3000 lightning data are more useful than CG lightning data alone for forecasting the development and propagation of thunderstorms over the BMR. [ABSTRACT FROM AUTHOR]

The rainfall data of 20 rain gauge stations are used for analysis on the spatiotemporal characteristics of rainstorm-induced hazards in Beijing. A local model used to calculate rainstorm hazards index values (RHIVs) has been developed to reflect the degree of rainstorm-induced hazards. The Mann-Kendall test on the RHIVs series recognizes 1984 as the changepoint in the series, which is shortly after the beginning of a rapid urban expansion period in 1981. The RHIV trend analysis reveals that the trends indices of all stations are negative before 1984 but mostly positive after 1984. Although the climate in north China shows drought conditions, and the annual rainfalls have decreased in recent years, no relationship is implied to a reduction in rainstorm-induced hazards. By using the lognormal distribution model, the probability analysis on the RHIVs of 20 stations indicates that very extreme precipitation occurred in increasing frequency after 1984. Moreover, the estimated spatial distributions of 100-, 150-, and 200-mm daily rainfall exceedance probabilities (EPs) indicate that these EPs have increased mainly in the urban areas and northward, which are the downwind of the summer monsoon, whereas the EPs to the south of the urban areas have decreased since 1984. Such spatiotemporal characteristics of the RHIVs can be attributed to modification of precipitation by the changed land use and land cover in urban areas. Moreover, the urban-induced rainfall downwind of the urban areas enhanced the rain intensity and rain rate, which led to an increase in RHIVs and contributed to the frequent occurrences of flash floods in Beijing metropolis. [ABSTRACT FROM AUTHOR]

The WRF-Noah-urban canopy model (UCM) coupled modeling system is used to investigate the influence of urbanization on a typical frontal rainfall event that occurred in June 2008 over the greater Beijing metropolitan area (GBMA). The comparison between results of two experiments with and without the presence of urban areas suggests that more precipitation can be induced over and in the area downwind of Beijing because of the urbanization effects while less rainfall is found in the upwind region of central urban areas. The urbanization effects delay the onset of precipitation over Beijing but keep it sustained for a longer period with stronger rainfall intensity. The underlying urban surface not only retards the cold-frontal movement but also favors the development of a wet and unstable atmosphere. This explains why the precipitation can be sustained for a longer time with higher rainfall intensity over urban areas. From analyses of a density-current speed equation, it is found that the abrupt pressure jump during the frontal passage has a significant influence on the cold-frontal movement. A method derived from the surface pressure tendency equation is used to explore the mechanism of urban effects on the cold-frontal system. The cold advection is less intense in the experiment with urban land surface than in the experiment with urban areas replaced by cropland. Hence, the weaker-than-normal cold advection and subsequent smaller pressure jump during the frontal passage over the GBMA are the major mechanisms behind the urbanization effects, which lead to the retardation of the cold-frontal movement and late onset of precipitation over the GBMA. [ABSTRACT FROM AUTHOR]