Abstract:The aerosol single-scattering albedo (SSA) refer to the characterization of aerosol absorption, which determines the positive and negative aerosol radiative forcing and accurate assessment of aerosol radiative forcing in climate change is of great significance. Based on AERONET (AERosol RObotic NETwork) and OMI (Ozone Monitoring Instrument) data from October 2004 to December 2016, the trend of aerosol SSA and comparison agreement with AERONET and OMI in the north of China (Beijing, Xianghe, Xinglong, and Lanzhou) were analyzed. The SSA annual mean of four sites were: Beijing 0.89±0.04 (AERONET) and 0.90±0.04 (OMI); Xianghe 0.89±0.04 (AERONET) and 0.91±0.04 (OMI); Xinglong 0.92±0.04 (AERONET) and 0.91±0.04 (OMI); Lanzhou 0.91±0.04 (AERONET) and 0.90±0.04 (OMI). All four sites showed the same seasonal variations, with high values in summer and low values in winter. Due to the limited data, the monthly average can not simply use to analyze the annual trend, we need to screen the data and remove the seasonal variation. The result showed that ground-based network and satellite had different time scales in both Beijing and Xianghe, while the OMI in Xinglong and AERONET in Lanzhou were meet the data requirements for trend analysis. The SSA of all four sites had the significant increases, indicating that the absorption of aerosol in the northern China have weaken and scattering have been enhanced in recent years. In particular, the AERONET and OMI retrievals of SSA were found an upward trend in four seasons at Beijing, but the absorption in autumn and winter was enhanced at Xianghe. In addition, due to the slight difference between AERONET and OMI, the data of AERONET and OMI were compared to accuracy of the results. The data of Xianghe revealed much bigger gap between the two inversions, which 30% of data agree within the absolute difference of ±0.03, and 55% agree within the difference of ±0.05; and 46% of Beijing data within ±0.03 and 68% within ±0.05, Xinglong 50% within ±0.03 and 78% within ±0.05; the data of Lanzhou was much better consistent, which 51% (86%) of data made agreement within the difference of ±0.03 (±0.05). In total, the data at sites which were more affected by human activities were consistently poor.

Abstract:The rate of atmospheric CO₂ has exceeded the atmospheric system’s natural ability to efficiently absorb it, thereby gradually affecting global climatic warming. The use of model simulations has become essential to help us improve our understanding of the carbon cycle. We simulated CO₂ concentration using the atmospheric chemical transport model GEOS-Chem driven by Biosphere Model SiB3 (Simple Biosphere version 3) and optimized Carbon Tracker 2016 (CT2016) terrestrial biospheric carbon fluxes for 2008-2010. Knowing the importance of improving carbon flux inversion accuracy in terrestrial ecosystems through analysis of the spatial distribution and seasonal variation in simulated CO₂ concentrations can deepen our understanding of global carbon source distribution and explore the impact of carbon flux uncertainty on simulation results. SiB3 and the optimized CT2016 terrestrial ecosystem carbon flux show obvious seasonal changes, but are opposite in European regions and there is great uncertainty about the global total and spatial distribution. Simulation results show that the carbon flux of terrestrial ecosystems are found to be key in the distribution of CO₂ concentration near the ground in areas of less human activity, particularly in the southern hemisphere and Europe. Seasonal differences in the simulation re sults rely on the seasonal variations in the terrestrial biospheric carbon fluxes. Simulation results are compared with the data of nine observation sites to select the suitable terrestrial ecosystem carbon flux for improving the accuracy of the GEOS-Chem simulated CO₂ concentration. Experimental results indicated that two kinds of simulation results can significantly simulate the peak and valley of seasonal change of CO₂ concentration, although the simulated CO₂ concentration using CT2016 is close to the observation data with a high simulation accuracy at most stations.

Abstract:Data from the microwave limb sounder (MLS) has better vertical resolution and inversion accuracy but intersects with measurements of pollution in the troposphere (MOPITT) data from the upper troposphere-lower stratosphere (UT-LS) region. In this paper, we compare MOPITT CO data with MLS CO data at 200 hPa. The results indicate that the CO distributions of both are similar in the middle and low latitudes, and high CO concentrations occur in Midwest, South-Central, and South-East Asia. In general, the concentration values of MOPITT CO are higher than those of MLS, and MOPITT CO shows a global system bias of about 35 ppb (10^-6) at low latitudes. The difference between MOPITT and MLS CO values was analyzed using CALIOP cloud data, and it was found that the occurrence of high CO concentration zones is related to strong convection.

Abstract:A Calibration error is among the main causes of errors in the quantitative application of radar reflectivity. In this study, the stable and continue doperation of along-term space-borne radar (Precipitation Radar carried by the Tropical Rainfall Measuring Mission satellite, TRMM/PR) was verified. Reflectivity data from the space-borne radar were converted from Ku-band to S-band. By comparing the reflectivity data gathered from the space-borne radar and Nanjing radarover the same period for different types of precipitation (stratiform or convective) at different altitudes (relative to the position of melting layer, ML), it was determined that there was a high correlation between the two radars' observations and a stable difference in stratiform precipitation below the ML. Further, the regression relationship between reflectivity factor values observed by the PR and Nanjing radar was obtained by comparing and analyzing the reflectivity factors of stratiform precipitation under the ML. Consequently, the regression between the two radar reflectivity factors provided a linear correction which was then applied to the reflectivity of the Nanjing radar. Rain gage data employed to verify this correction revealed that the precipitation estimated using GR reflectivity data with correction was closer to the rain gage observations than without.

Abstract:Fog is a severe weather hazard that greatly influences traffic and daily life, potentially contributing to heavy economic losses. Based on the observed fog data from 1958 to 2007, using correlation coefficient analysis and composite analysis, the temporal and spatial characteristics of fog days in winter were analyzed. It was found that fog in winter frequently occurred, and the interannual variability in winter fog days was relatively strong, mainly over southwestern China, northern China, and Fujian. According to the distribution patterns of the winter fog days, we defined three relatively independent fog areas. The influence of regional climatic conditions on local fog formation mechanisms is discussed from the aspects of water vapor transport, atmospheric stability, and atmospheric circulation. There was a significant difference in climatic conditions for winter fog formation among the different regions. Winter fog formation over southwestern China was less affected by water vapor transport, while more affected by the atmospheric stability and the southward cold air. Winter fog formation over northern China was affected by water vapor transport; they occurred more frequently when water vapor was transported farther north and convective instability occurred over the middle and lower Yangtze River. Meanwhile, the formation and maintenance of winter fog days over southern China were also found to be influenced by vapor transport; when water vapor was transported farther south, the fog occurred more frequently. In terms of atmospheric circulation, winter fog formation was mainly affected by the deepening high-pressure ridge, east of the Balkhash Lake over southwestern China, weakening of East Asia trough and Siberian High over northern China, and the weakening of the Siberian High over southern China.

Abstract:This paper represents statistical analysis of the convective activities and surface sensible heat fluxes from May to August in North China and its surrounding areas based on meteorological satellite and reanalysis data from 2006 to 2017. The results show that the daytime average sensible heat flux is closely related to the topography in North China and its surrounding areas. The sensible heat flux is stronger in the central and southeastern Inner Mongolia and the northern and the western mountainous areas of North China. The strongest sensible heat flux occurs in May and June whereas it obviously weakens in July and August. The higher convection frequency corresponding to the intensity of the sensible heat flux also occurs in May and June. In May, most of the convections are weak. The deep convections are most active in the north-central part of North China in June and are relatively frequent in the area around the Bohai Sea from June to July. The trend of the corresponding relationship between the daily average sensible heat flux and convection frequency shows consistent weakening from May to August. In the morning, sensible heat causes various degrees of convergence and warming in the lower troposphere below 700 hPa in the Western and Northern Hebei Province. The ascending motion reaches the middle troposphere, and the compensating descending motions occur in the eastern plains. The warming up and ascending motion trigger convection, which can develop rapidly when it moves eastward under favorable conditions. The diurnal variation in convection frequencies in different months and regions obviously differs. In June, the diurnal variation in the convection frequencies is significant, whereas it is the weakest in August. Regionally, the diurnal variation in the convection frequencies in mountainous areas is significant, whereas it is the weakest in the eastern Bohai Sea and its surrounding areas. Both the monthly mean distribution and diurnal variation in the convection frequency have a close relationship with the surface sensible heat flux generated by the topography.

Abstract:Through the use of C-band dual-polarization radar datasets from the Third Tibetan Plateau Atmospheric Scientific Experiment, ERA-Interim 0.125°(latitude)×0.125°(longitude) reanalysis data, and conventional meteorological radiosonde data, the diagnostic analysis and radar echo feature extraction of a hailstorm severe convective weather process in the Naqu area of Tibet on the afternoon of 30 Jul 2014 are conducted. Results show that: 1) The hailstorm severe convective weather process occurs during the eastward movement of a plateau vortex accompanied by shear lines. The forward-tilting shear lines at the rear of the vortex provide energy and water vapor for this process. 2) The water vapor provided for the severe convective weather mainly comes from the Bay of Bengal, India, and Nepal, which strengthens significantly before the severe convective weather. The water vapor in the lower layer concentrates below 400 hPa, with obvious convergence and upward transportation. 3) Under the obvious convective instability, energy accumulation, and dynamic uplift conditions below 400 hPa in Naqu, the overlap area of the pseudo-equivalent potential temperature decreases with the height, horizontal convergence, and upward movement. 4) The radar echo images show that the severe convective weather is obviously local and is mainly caused by multiple γ mesoscale isolated convection cells, the movement path of which is consistent with the southwest airflow in front of shear lines. Most of the cells have small horizontal scales and short life, whereas some cells have large horizontal scales and long life. Local airflow convergence may cause the production of new cells, and the occurrence, development, and maintenance of cells depend on the low-level airflow convergence to provide dynamic conditions. 5) The range height indicator shows the characteristics of a weak hail cloud, with the top reaching approximately 16 km but not breaking through the top of the troposphere, which is higher than the general convective clouds in plain areas, and the 0℃ layer being lower than that in plain areas. The cloud indicates deep strong convective precipitation, and the precipitation center is located at the bottom of the cloud, including precipitation and hail dominated by radon particles. Strong inflows and updrafts occur in the vertical direction. The suspended echoes appear above the inflowing updrafts, with the airflow sinking zone below the middle-level convergence zone corresponding to the hail zone. The combination of the middle-level convergence and high-level divergence leads to the upward growth and strong development of convective storms.

Abstract:In this study, strong precipitation generated by the landing of typhoon Fung-Wong in 2008 was simulated using WRF WDM6 double-moment cloud microphysics scheme. The model simulations were evaluated by statistical methods using cloud top brightness temperature (TBB) and precipitation radar reflectivity data from MTSAT-1R, TRMM satellite, and the Satellite Data Simulator Unit. To reduce the difference between the simulation results and satellite observations, sensitivity experiments were conducted in relation to autoconversion rate of cloud water to rain, ice nucleation, terminal velocity, and slopes of snow and graupel. The results show that the precipitation, strong convective cloud system, and convective columnar radar echo simulated by the WDM6 scheme are in agreement with observations, however, showing stronger results in some areas. The WDM6 scheme simulation produced more shallow convective clouds and underestimated the frequency of convective cloud systems. The radar echoes simulated by different cloud types are all strong, and the vertical distribution of the convective cloud radar echoes is close to observation. The experimental results show that modifying the production rate for the autoconversion of cloud water to rain in the WDM6 scheme effectively improves the simulation results. Simultaneously, it is found that the concentration of initial cloud droplets affects the production rate for the autoconversion of cloud water to rain and ultimately affects the simulation results of the cloud structure and radar reflectivity. A high concentration of initial cloud droplets will worsen the simulation result.

Abstract:Using ERA-Interim and APHRO_MA data, the spring precipitation decadal trend in the western Tibetan Plateau during 1979-2007 and its possible causes were analyzed. The results indicate that the change in spring precipitation in the western Qinghai-Tibet Plateau presented a significant decreasing trend, which is clearly related to both the convergence rising in the southwestern Tibetan Plateau and water vapor transport from the northern Arabian Sea. A significant convergence anomaly was found to be generated when the negative high-level (500 hPa) geopotential height field and negative low-level convergence (850 hPa) were occupied, which provided the dynamic conditions for spring precipitation in the southwestern Tibetan Plateau. Moreover, the location of the negative high-level geopotential height field anomaly was consistent with the cyclonic anomaly center in the wind field, while that of the low-level convergence was relatively weak. The spring precipitation anomaly was accompanied by both specific humidity anomalies at the high- and low-level geopotential height fields in the northern Arabian Sea; however, the positive specific humidity anomalies of the lower layers were more significant. The water vapor transport in the northern Arabian Sea accounted for 55.3% of the total spring precipitation change in the southwestern Tibetan Plateau. The study shows that the decreasing trend of spring precipitation in the southwestern Tibetan Plateau from 1979 to 2007 was mainly caused by the decreasing water vapor transport from the lower layer of the northern Arabian Sea to the Indian subcontinent and the weakening high-level convergence of the southern Tibetan Plateau. The consistency of trend in spring precipitation in the western Tibetan Plateau and water vapor changes in related areas can provide guidance to analyze the climate change in the Tibetan Plateau.

Abstract:Aerosol lidar and radiosonde are the two main methods used to detect planetary boundary layer (PBL) height. Based on three consecutive months of lidar and radiosonde data from November 2017 to January 2018 in Beijing, the detection methods and calculation results of PBL height were analyzed and compared for three kinds of weather conditions, that is clear, hazy, and cloudy. The results show that the three methods (gradient, standard deviation, and wavelet transformation methods) based on the lidar extinction coefficient extracted the PBL heights well. The PBL heights calculated by the standard deviation method in clear sky were higher than those calculated by the gradient and wavelet methods. The average PBL heights obtained by radiosonde at 0800 LST and 2000 LST were 1176 m and 1224 m, respectively. On polluted days, the calculated results of the standard deviation method were lower than those of the gradient and wavelet methods. The average PBL height obtained by radiosonde on polluted days was about 956 m, which is a decrease of more than 200 m compared to clear days. In heavily polluted days, the lowest PBL height was 562 m. There was an obvious inverse correlation between inversion height and the PM2.5 concentration. During cloudy days, the PBL heights determined by the gradient and wavelet methods were very close to the cloud height, and the results calculated by the standard deviation method were slightly lower. In general, the height of the boundary layer calculated by aerosol lidar did not decrease significantly with increases in the pollution level. In contrast, this height increased in heavy pollution, which may be due to the continuous accumulation of pollutants. The standard deviation method was not susceptible to the influence of the pollutant transport process, whereas the PBL height determined by the gradient method was susceptible to the influence of pollutant transport, with the results being slightly higher than the inversion layer. When the PBL height determined by lidar was affected by the residual layer, it was also higher than the inversion layer.