2020, 25(5):457-468. DOI: 10.3878/j.issn.1006-9585.2019.19027
Abstract:The variation characteristics of the energy flux and meteorological elements of the underlying surface of the forest during the wet and dry seasons were compared and analyzed by using observation data obtained from November 2014 to May 2016 from the Zhuhai Phoenix Mountain Land-Atmosphere Interaction Observation Tower Station. The variation characteristics of the momentum and sensible heat exchange coefficients in three wind direction ranges (315°-45°, 45°-135°, and 135°-225°) along with the canopy-surface wind speed under different stability conditions, as well as the parameterizations of these coefficients were analyzed. The sensible heat and latent heat fluxes in the dry season were equivalent, whereas in the wet season latent heat is much higher than the sensible heat. Negative sensible heat occurs during the night in both the dry and wet seasons, with the sensible heat being transported from the atmosphere to the forest. The variation range of the relative humidity is large and is closely related to the meteorological conditions in the area. The vertical gradient of the relative humidity is larger at night and smaller during the day. The vertical gradient of the air temperature in the dry season is more significant than that in the wet season. The wind speed changes gently in winter but violently in summer. There is an obvious gradient in the low-level wind speed with height, whereas the high-level wind is chaotic. The wind direction at different heights does not differ significantly. In neutral and near-neutral states, the momentum exchange coefficients Cdn are 0.05, 0.0055, and 0.022, respectively, when the wind directions are 315°-45°, 45°-135°, and 135°-225°, and the sensible heat exchange coefficients Chn are 0.0055, 0.003, and 0.004, respectively. Under stable and unstable conditions, the momentum exchange coefficient Cd and the sensible heat exchange coefficient Ch obviously change with the wind velocity v on the canopy surface. Under stable conditions, Cd and Ch increase with increases in v, and under unstable conditions, Cd, and Ch decrease with increases in v. We fitted the relationships between Cd, Ch in the forest canopy and v under stable and unstable conditions in different wind directions, and obtained the parameterized formula.
2020, 25(5):469-482. DOI: 10.3878/j.issn.1006-9585.2020.19100
Abstract:The mechanisms involved in the development of high temperature anomalies in Northeast China during the summer of 2018 were studied using observational and reanalysis data. First, daily temperatures recorded at observation stations in the region throughout the summer were analyzed. Next, the excess heat factor index of the observation stations was calculated. July and August were the main anomaly high temperature periods when high temperature anomalies occurred in the southern part of Northeast China. The South Asia high (SAH) and western Pacific subtropical high (WPSH) were significantly intensified during this period, and overlapped with each other on different levels and extended northward. There was also an increase in the negative vorticity anomalies in the overlapping area of the SAH and WPSH, and the two northward extending systems continued to drive the negative vorticity anomalies. In addition, an abnormal down draft occurred over the southern part of Northeast China together with sinking adiabatic warming and clear-sky radiation warming, which may have been important factors involved in surface warming in this area. Furthermore, surface temperature anomalies were significantly correlated with negative vorticity anomalies at geopotential heights from 300 to 500 hPa during the summer of 2018 in this region. It was also determined that the quasi-stationary Rossby wave energy propagation in the summer subtropical westerly jet was closely related to the anomalous enhancement of the SAH and WPSH. Significant simultaneous warming of the western Pacific warm pool during the summer also promoted unusually strong convective activity in the Philippines. The Pacific-Japan (PJ) wave train was excited at a geopotential height field of 500 hPa, which also led to the enhancement and northward extension of the WPSH. In summary, the existence of the SAH and WPSH and their overlapping were the main causes of the high temperature anomalies in the southern part of Northeast China during July and August 2018.
2020, 25(5):483-498. DOI: 10.3878/j.issn.1006-9585.2019.19130
Abstract:Based on pan evaporation (PE) observations at 1302 weather stations in China for 1961-2013, in this paper, we present our analysis of the temporal and spatial characteristics and their impact on the climate factors of PE. The results indicate that both the annual and seasonal mean PE values from all stations show a significant downward trend, with an abrupt change occurring in 1978. The stations with a significant downward PE trend are mainly located in the North China Plain, Xinjiang, Guangdong, Guangxi, and Hainan provinces, whereas PE shows a significantly increasing trend in Fujian, Zhejiang, and Guizhou provinces. We performed empirical orthogonal function (EOF) analyses of the annual PE anomalies. For the first mode (EOF1), the time coefficient changes from positive to negative in 1981, and the variation of the EOF1 spatial pattern is similar as that of PE magnitude. The EOF2 mode presents opposite patterns in South and North China and after 2002, the PE decreased in North China, but increased in South China. Additionally, we calculated the partial correlation coefficients between PE and five climate elements, including precipitation, temperature, surface wind speed, relative humidity, and sunshine duration. The results show that except for precipitation, the other four variables are very well correlated with PE. The correlation between wind speed and PE is significantly positive, and the regions with the highest correlation are consistent with those with the largest EOF1 variability. The correlation between humidity and PE is significantly negative. The correlation between temperature and PE are positive overall, with the largest values appearing in areas where PE increases. The correlation coefficients between the sunshine duration and PE are greater than 0.6 in three seasons but not in spring. Moreover, we found that the linear trends of both wind speed and sunshine duration greatly impact their relationships with PE. Thus, we conclude that a decreasing trend in PE is largely because of decreasing wind speed and sunshine duration. Furthermore, when drought occurs, PE increases significantly, and the changes in precipitation, temperature, relative humidity, and sunshine duration also significantly contribute to the increases in PE. As such, PE could be a good indicator of drought.
2020, 25(5):499-509. DOI: 10.3878/j.issn.1006-9585.2020.19094
Abstract:China’s air quality has improved in recent years by the implementation of strict pollution control action plans such as the National “Ten Measures for Air” ratified by the Chinese State Council. To achieve sustained improvements in air quality and targeted pollution control in the coming years the effectiveness of these pollution control initiatives must be scientifically evaluated. Because air quality levels are strongly influenced and at times even dominated by meteorological conditions, a major difficulty of such analysis is quantifying the contributions of meteorological conditions and pollution control initiatives to variations in the respective pollutant concentrations. In this study, we assessed the effectiveness of pollution control efforts for one of the most heavily polluted areas in China—the Beijing-Tianjing-Heibei region—by analyzing (1) the time-frequency properties of the PM2.5 time series collected from 86 monitoring sites in 13 cities of this region during 2013-2018 and (2) the corresponding meteorological conditions retrieved from the reanalysis product of the European Center for Medium-range Weather Forecast (ECMWF). We used the Kolmogorov-Zurbenko filter to separate the original PM2.5 series into three components: Short-term weather-related variations, medium-term seasonal variations, and long-term trends. We constructed regression models to account for the influence of meteorological variables on the PM2.5 concentrations to distinguish their impacts on pollution abatement from those of the emission reduction actions. We found that during 2013-2018, the long-term trends of PM2.5 concentration over 13 cities decreased significantly (22.2%-58.0%), with Xingtai city experiencing the greatest decrease (58.0%). Both meteorological conditions and emission reduction actions contributed to the improvement of air quality, but emission reduction actions were the decisive factor in the significant improvement in air quality. The contributions of meteorological conditions and emission reduction actions were 18.5% and 81.5%, respectively. Among the 13 cities, the meteorological conditions were the most beneficial for Tangshan (29.2%) whereas emission reduction actions played the most important role for Hengshui (92.0%).
2020, 25(5):510-520. DOI: 10.3878/j.issn.1006-9585.2019.19060
Abstract:Based on the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) global reanalysis data, ground observation data, and automatic station precipitation data, this study analyzed circulation anomalies such as winter monsoon circulation and the South Branch trough in rare continuous rain and oligoscale weather in Zhejiang in the winter of 2018/2019. Moreover, the study investigated the causes of local circulation anomalies from aspects such as westerly wind fluctuation and sea temperature forcing. The results showed that in the winter of 2018/2019, the rainy days and sunshine hours surpassed the historical record, and the rainfall was significantly above normal. The main circulation anomalies were the abnormal northerly western North Pacific anomalous anticyclone (WNPAC). Meanwhile, the Aleutian low-pressure and the Siberian high-pressure systems were also northerly. There was a strong southerly wind anomaly south of 40°N in East Asia, and the winter monsoon was weak. The southern branch trough was stronger than the perennial, ensuring that there was a continuous water vapor and disturbance transport over Zhejiang. In the middle layer of the troposphere, a wave energy propagated along Europe to East Asia and the western Pacific. The wave energy spread southward to the south of 20°N in East Asia, which might lead to a significant north lift of the WNPAC and the strengthening of the southern branch trough. The El Niño-Southern Oscillation (ENSO) warm phase caused abnormal convective cooling in the maritime continent, while the convection over Zhejiang strengthened, and ENSO also had a significant effect on the activity intensity of the southern branch trough. The high sea surface temperature in the offshore waters of China was an important factor for the WNPAC and the Aleutian Low to significantly jump north. The abnormal circulation in the northern hemisphere in the winter of 2018/2019 might have been caused by ENSO and China’s offshore sea temperature collaborative forcing.
2020, 25(5):521-530. DOI: 10.3878/j.issn.1006-9585.2019.19114
Abstract:In this study, Beijing is selected as the research area to perform wind speed correction of the aerosol optical depth (AOD) data of the 440 nm band inversion of the CE-318 solar photometer provided by AERONET (Aerosol Robotic Network) in 2014-2017. Then, the seasonal correlation analysis and modeling of the corrected daily average AOD data and the same period ground monitoring station daily average PM2.5 concentration data are conducted. Then, the visibility factor is introduced and the generalized difference method is used to construct the ternary regression model of AOD, PM2.5, and visibility in Beijing from 2015 to 2017. Finally, the data of 2014 are divided into pollution and nonpollution days for the model tests. Results show a significant linear positive correlation between AOD and PM2.5. Moreover, the seasonal differences exhibit the strongest correlation in summer, followed by that in autumn, and the weakest correlation in spring and winter. After introducing the visibility factor and eliminating the autocorrelation, the relative error of the model in the four seasons is reduced, the goodness of fit of the model significantly improved, and the relative error ranges from 21% to 31%. Compared with the previous results, the accuracy of curve fitting has been significantly improved. Moreover, the simulation effect of the model is good for low PM2.5 concentration days but poor for high PM2.5 concentration days. This study is of scientific significance for the construction of the long-term historical data of PM2.5 in Beijing.
2020, 25(5):531-542. DOI: 10.3878/j.issn.1006-9585.2020.19185
Abstract:Based on the daily precipitation, relative humidity, and air temperature data during 1961-2017 from 96 stations in Northeast (NE) China, through trend analysis and the Mann-Kendall test method, the climate change characteristics of light rainfall, moderate rainfall, heavy rainfall, and torrential rainfall in summer and the causes of the decreasing trend of light rainfall frequency over NE China are analyzed. The main results are as follows: A significant positive correlation exists between the total precipitation over NE China and all types of precipitation frequency and contribution, and the total precipitation is mainly influenced by the frequency and contribution of heavy rain. The decrease in light rainfall and moderate rainfall is the main cause of the decrease in total precipitation in summer over NE China, and the torrential rainfall influenced by the increase in the torrential rainfall contribution shows a rising tendency. Furthermore, an interdecadal abrupt change in light rainfall and light rainfall contribution occurred around 1993, and the interdecadal abrupt change in light rainfall contribution has resulted in the interdecadal abrupt change in light rainfall. A certain decreasing trend of the total precipitation at 72 stations over NE China 85 stations showed a certain decreasing trend of the light rainfall, among which 25 stations show a significant decreasing trend; moreover, 70 stations show a certain decreasing trend of moderate rainfall, among which only nine stations show a significant decreasing trend; the number of stations that show an increasing trend of heavy rainfall is comparable to the number of those that show a decreasing trend, and the number of stations that show an increasing trend of the torrential rainfall is greater than the number of those that show a decreasing trend. Regarding cloud formation, the effects of the changes in water vapor, temperature, and aerosol concentration on the reduction in light rainfall in NE China are analyzed. The results show that the global temperatures rising and increased aerosol concentration are the main causes of the decreasing light rainfall in NE China.
2020, 25(5):543-554. DOI: 10.3878/j.issn.1006-9585.2020.20014
Abstract:Based on Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) downscaling data of simulations generated by five climate (Earth) system models in CMIP5, in this study, the multi-model collection was used to estimate the vegetation growing season and active accumulated temperature changes in the circum-Arctic region in the 21st century under various climate change scenarios. The research results show that: 1) Multi-model ensemble simulation can basically reproduce the observed spatial distribution characteristics of the initial and final frost days, length of the frost-free period, accumulated temperature of >10℃, and change trends of these indicators from 1979 to 2004. However, its ability to simulate the spatial differences and interannual variability of climate change is weak. 2) By the end of the 21st century, the final frost day will advance by up to 60 days, initial frost day will be delayed by 20-40 days, frost-free period will extend up to 100 days, and accumulated temperature will vary by 1000-1200℃. Each of these indicators undergoes the greatest change under the RCP8.5 scenario, and the least change under the RCP2.6 scenario. 3) The changes in the indicators have large spatial differences, with the changes in the central and western parts of the Eurasian continent being generally larger. With the warming of the climate, increases in the accumulated temperature>10℃ gradually show obvious zonality in the latitudinal direction, with a greater increase in the south.
2020, 25(5):555-574. DOI: 10.3878/j.issn.1006-9585.2020.20025
Abstract:This study aims to evaluate the effect of two, new, global soil datasets on global land surface simulation, based for the first time on the Common Land Model (CoLM). The effects of the two soil datasets, namely GSDE (Global Soil Dataset for Earth System Model) and Soil Grids (SG), on the model simulation results were studied. The differences between these two data sets were compared and analyzed for five soil properties, namely sand, clay, gravel, organic carbon, and bulk density, and the impact, caused by those differences, on the estimated soil characteristic parameters as well as the hydraulic and thermal variables in the model were discussed. The results show that the global spatial distribution of soil characteristic parameters is mainly influenced by soil particle size distribution (sand, silt, and clay), and also by gravel, organic matter, and bulk density. The effect of the soil datasets on the global simulation varies across different regions. Their effect on the hydrological variables (the maximum value of Re is ±100%) is greater than that on the soil thermodynamic variables (Re<±10%) and on the surface radiation variables (Re<±5%). The soil volumetric water content in central and northwest Canada, southeastern Russia, and midwest and central Australia is quite different, and the total runoff in low latitudes area shows great variance. Thermal variables show some differences in northern Africa, northwestern Canada, and north-central Russia. Comparing the simulated soil moisture with site observations, the performance of the two datasets is similar and there is a certain deviation from the site observations. More specifically, the values based on the SG data are closer to the observation values. The results show that there is an increase of about 0.01 to 0.02 using the SG data compared with the GSDE data at the Molly Caren site. This study shows that the model simulation results are significantly affected by different datasets and that soil data with higher accuracy, such as the SG data, are preferable for model use. Further studies on the effect of soil properties on land surface modeling are required.