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Climatology of Cloud-base Height from Long-term Radiosonde Measurements in China

doi: 10.1007/s00376-017-7096-0

  • Clouds are critical to the global radiation budget and hydrological cycle, but knowledge is still poor concerning the observed climatology of cloud-base height (CBH) in China. Based on fine-resolution sounding observations from the China Radiosonde Network (CRN), the method used to estimate CBH was modified, and uncertainty analyses indicated that the CBH is good enough. The accuracy of CBH estimation is verified by the comparison between the sounding-derived CBHs and those estimated from the micro-pulse lidar and millimeter-wave cloud radar. As such, the CBH climatology was compiled for the period 2006-16. Overall, the CBH exhibits large geographic variability across China, at both 0800 Local Standard Time (LST) and 2000 LST, irrespective of season. In addition, the summertime cloud base tends to be elevated to higher altitudes in dry regions [i.e., Inner Mongolia and the North China Plain (NCP)]. By comparison, the Tibetan Plateau (TP), Pearl River Delta (PRD) and Sichuan Basin (SCB) have relatively low CBHs (<2.4 km above ground level). In terms of seasonality, the CBH reaches its maximum in summer and minimum in winter. A low cloud base tends to occur frequently (>70%) over the TP, PRD and SCB. In contrast, at most sites over the Yangtze River Delta (YRD) and the NCP, about half the cloud belongs to the high-cloud category. The CBH does not exhibit marked diurnal variation in summer, throughout all CRN sites, probably due to the persistent cloud coverage caused by the East Asia Summer Monsson. To the best of our knowledge, this is the first CBH climatology produced from sounding measurements in China, and provides a useful reference for obtaining observational cloud base information.
    摘要: 云的观测对于全球辐射平衡和水循环至关重要, 目前我国对于云底高度(CBH)的气候特征分析还较为缺乏. 基于中国探空观测网络(CRN)的高分辨率长期(2006-2016年)探空观测资料, 我们提出了改进的相对湿度阈值法, 借助2016年夏季邢台增强观测试验期间获取的云雷达, 微脉冲激光雷达计算得到的CBH, 进行了算法验证, 效果良好. 分析了2006-2016年的云底高度气候特征, 总体而言, 不同季节的CBH在中国区域均存在较大的地域差异. 此外, 夏季在干旱地区(如内蒙古和华北平原)云底抬升的更高, 而在青藏高原, 珠江三角洲及四川盆地云底高度相对较低(距离地面 2.4 km). 季节分布上, 云底高度夏季最高, 冬季最低. 低云发生频率( 70%)多数出现在青藏高原, 珠江三角洲及四川盆地. 相反, 长江三角洲和华北平原出现的云约有一半是高云. 夏季, 所有观测站的云底高度并未表现出明显的日变化, 可能是由于夏季14时的探空观测主要用于改善高影响天气的预报, 导致所观测到的低层大气容易出现湿度较大现象引起. 据我们所知, 这是中国第一个基于高空探测资料建立的云底高度气候产品, 可用于准确估算云对人类气候系统的辐射强迫.
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    Li, Z. Q., Coauthors, 2016: Aerosol and Monsoon Climate Interactions over Asia.Rev. Geophys.,54,866-929, increasing severity of droughts/floods and worsening air quality from increasing aerosols in Asia monsoon regions are the two gravest threats facing over 60% of the world population living in Asian monsoon regions. These dual threats have fueled a large body of research in the last decade on the roles of aerosols in impacting Asian monsoon weather and climate. This paper provides a comprehensive review of studies on Asian aerosols, monsoons, and their interactions. The Asian monsoon region is a primary source of emissions of diverse species of aerosols from both anthropogenic and natural origins. The distributions of aerosol loading are strongly influenced by distinct weather and climatic regimes, which are, in turn, modulated by aerosol effects. On a continental scale, aerosols reduce surface insolation and weaken the land-ocean thermal contrast, thus inhibiting the development of monsoons. Locally, aerosol radiative effects alter the thermodynamic stability and convective potential of the lower atmosphere leading to reduced temperatures, increased atmospheric stability, and weakened wind and atmospheric circulations. The atmospheric thermodynamic state, which determines the formation of clouds, convection, and precipitation, may also be altered by aerosols serving as cloud condensation nuclei or ice nuclei. Absorbing aerosols such as black carbon and desert dust in Asian monsoon regions may also induce dynamical feedback processes, leading to a strengthening of the early monsoon and affecting the subsequent evolution of the monsoon. Many mechanisms have been put forth regarding how aerosols modulate the amplitude, frequency, intensity, and phase of different monsoon climate variables. A wide range of theoretical, observational, and modeling findings on the Asian monsoon, aerosols, and their interactions are synthesized. A new paradigm is proposed on investigating aerosol-monsoon interactions, in which natural aerosols such as desert dust, black carbon from biomass burning, and biogenic aerosols from vegetation are considered integral components of an intrinsic aerosol-monsoon climate system, subject to external forcing of global warming, anthropogenic aerosols, and land use and change. Future research on aerosol-monsoon interactions calls for an integrated approach and international collaborations based on long-term sustained observations, process measurements, and improved models, as well as using observations to constrain model simulations and projections.
    Marchand, R., G. G. Mace, T. Ackerman, G. Stephens, 2008: Hydrometeor detection using Cloudsat-an earth-orbiting 94-GHz cloud radar.J. Atmos. Oceanic Technol.,25,519-533,
    Martucci G., C. Milroy, and C. D. O'Dowd, 2010: Detection of cloud-base height using Jenoptik CHM15K and Vaisala CL31 ceilometers.J. Atmos. Oceanic Technol.,27,305-318, Twelve case studies of multilayer cloud-base height (CBH) retrievals from two collocated ceilometers (Vaisala CL31 and Jenoptik CHM15K) have been analyzed. The studies were performed during the period from September to December 2008 at the Mace Head Atmospheric Research Station in Ireland. During the period of measurement, the two instruments provided vertical profiles of backscattered laser signal as well as the manufacturer's operational cloud-base product. The cases selected covered a diverse range of cloud-cover conditions, ranging from single to multiple cloud layers and from cloud-base heights varying from only a few hundreds meters per day up to 3-5 km in a few hours. The results show significant offsets between the two manufacturer-derived CBHs along with a considerable degree of scatter. Using a newly developed temporal height-tracking (THT) algorithm applied to both ceilometers, significant improvement in the correlation between CBH derived from both instruments results in a correlation coefficient increasing to R 2 = 0.997 (with a slope of 0.998) from R 2 = 0.788 (with an associated slope of 0.925). Also, the regression intercept (offset) is reduced from 160 m to effectively zero (-3 m). For the worst individual case study, using the THT algorithm resulted in the correlation coefficient improving from R 2 = 0.52, using the manufacturer's output, to R 2 = 0.97 with a reduction in the offset reducing from 569 to 32 m. Applying the THT algorithm to the backscatter profiles of both instruments led to retrieved cloud bases that are statistically consistent with each other and ensured reliable detection of CBH, particularly when inhomogeneous cloud fields were present and changing rapidly in time. The THT algorithm also overcomes multiple false cloud-base detections associated with the manufacturer's output of the two instruments.
    Miao Y. C., J. P. Guo, S. H. Liu, H. Liu, Z. Q. Li, W. C. Zhang, and P. M. Zhai, 2017: Classification of summertime synoptic patterns in Beijing and their association with boundary layer structure and aerosol pollution.Atmos. Chem. Phys.17,3097-3110, conditions within the planetary boundary layer (PBL) are closely governed by large-scale synoptic patterns and play important roles in air quality by directly and indirectly affecting the emission, transport, formation, and deposition of air pollutants. Partly due to the lack of long-term fine-resolution observations of the PBL, the relationships between synoptic patterns, PBL structure, and aerosol pollution in Beijing have not been well understood. This study applied the obliquely rotated principal component analysis in T-mode to classify the summertime synoptic conditions over Beijing using the National Centers for Environmental Prediction reanalysis from 2011 to 2014, and investigated their relationships with PBL structure and aerosol pollution by combining numerical simulations, measurements of surface meteorological variables, fine-resolution soundings, the concentration of particles with diameters less than or equal to 2.5 m, total cloud cover (CLD), and reanalysis data. Among the seven identified synoptic patterns, three types accounted for 67 % of the total number of cases studied and were associated with heavy aerosol pollution events. These particular synoptic patterns were characterized by high-pressure systems located to the east or southeast of Beijing at the 925 hPa level, which blocked the air flow seaward, and southerly PBL winds that brought in polluted air from the southern industrial zone. The horizontal transport of pollutants induced by the synoptic forcings may be the most important factor affecting the air quality of Beijing in summer. In the vertical dimension, these three synoptic patterns featured a relatively low boundary layer height (BLH) in the afternoon, accompanied by high CLD and southerly cold advection from the seas within the PBL. The high CLD reduced the solar radiation reaching the surface, and suppressed the thermal turbulence, leading to lower BLH. Besides, the numerical sensitive experiments show that cold advection induced by the large-scale synoptic forcing may have cooled the PBL, leading to an increase in near-surface stability and a decrease in the BLH in the afternoon. Moreover, when warm advection appeared simultaneously above the top level of the PBL, the thermal inversion layer capping the PBL may have been strengthened, resulting in the further suppression of PBL and thus the deterioration of aerosol pollution levels. This study has important implications for understanding the crucial roles that meteorological factors (at both synoptic and local scales) play in modulating and forecasting aerosol pollution in Beijing and its surrounding area.
    Minnis P., E. F. Harrison, 1984: Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data. Part I: Analysis method. J. Climate Appl. Meteor., 23, 993-1011, <0993:DVORCA>2.0.CO;2.10.1175/1520-0450(1984)0232.0.CO; hybrid bispectral threshold method (HBTM) is developed for hourly regional cloud and radiative parameters from geostationary satellite visible and infrared radiance data. The quantities derived with the HBTM include equivalent blackbody temperatures for clear skies, for the total cloud cover and for the cloud cover at three levels in the atmosphere; the total fractional cloud cover and the fractional cloud amounts at three altitudes; and the clear-sky and total cloud reflectance characteristics. Geostationary satellite data taken during November 1978 are analyzed. A minimum reflectance technique is used to determine clear-sky brightness. A visible bidirectional reflectance model is derived for clear ocean areas. Clear-sky radiative temperature is found with a bispectral clear radiance technique during daylight hours. An empirical model is derived to predict clear-sky temperature at night. A combination of previously published infrared threshold and bispectral techniques is used to determine the remaining parameters. Sources of uncertainty are discussed and means to minimize them are proposed. Monthly mean, regional fractional cloudiness determined with this method agrees well with more conventional subjective techniques. On the average, the present results are approximately 0.05 less than corresponding surface observations; this is consistent with previous comparisons of satellite- and surface-based nephanalyses. Comparisons between subjective analyses of satellite photographs and the HBTM yielded average differences in mean regional cloudiness, mean hourly cloudiness and instantaneous cloud amounts of 0.04, 0.05 and 0.11 respectively. Root-mean-square differences in these same quantities derived by two satellite data analysts were 0.03, 0.04 and 0.08 respectively.
    Morel C., S. Senesi, 2002: A climatology of mesoscale convective systems over Europe using satellite infrared imagery.I: Methodology. Quart. J. Roy. Meteor. Soc.,128,1953-1971,
    Myers T. A., J. R. Norris, 2015: On the relationships between subtropical clouds and meteorology in observations and CMIP3 and CMIP5 models.J. Climate28,2945-2967, Climate models' simulation of clouds over the eastern subtropical oceans contributes to large uncertainties in projected cloud feedback to global warming. Here, interannual relationships of cloud radiative effect and cloud fraction to meteorological variables are examined in observations and in models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively). In observations, cooler sea surface temperature, a stronger estimated temperature inversion, and colder horizontal surface temperature advection are each associated with larger low-level cloud fraction and increased reflected shortwave radiation. A moister free troposphere and weaker subsidence are each associated with larger mid- and high-level cloud fraction and offsetting components of shortwave and longwave cloud radiative effect. It is found that a larger percentage of CMIP5 than CMIP3 models simulate the wrong sign or magnitude of the relationship of shortwave cloud radiative effect to sea surface temperature and estimated inversion strength. Furthermore, most models fail to produce the sign of the relationship between shortwave cloud radiative effect and temperature advection. These deficiencies are mostly, but not exclusively, attributable to errors in the relationship between low-level cloud fraction and meteorology. Poor model performance also arises due to errors in the response of mid-and high-level cloud fraction to variations in meteorology. Models exhibiting relationships closest to observations tend to project less solar reflection by clouds in the late twenty-first century and have higher climate sensitivities than poorer-performing models. Nevertheless, the intermodel spread of climate sensitivity is large even among these realistic models.
    Naud C. M., A. D. D. Genio, M. Bauer, and W. Kovari, 2010: Cloud vertical distribution across warm and cold fronts in CloudSat-CALIPSO data and a General Circulation Model.J. Climate23,3397-3415, 10.1175/ vertical distributions across extratropical warm and cold fronts are obtained using two consecutive winters of –Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations and National Centers for Environmental Prediction reanalysis atmospheric state parameters over the Northern and Southern Hemisphere oceans (30°–70°N/S) between November 2006 and September 2008. These distributions generally resemble those from the original model introduced by the Bergen School in the 1920s, with the following exceptions: 1) substantial low cloudiness, which is present behind and ahead of the warm and cold fronts; 2) ubiquitous high cloudiness, some of it very thin, throughout the warm-frontal region; and 3) upright convective cloudiness near and behind some warm fronts. One winter of GISS general circulation model simulations of Northern and Southern Hemisphere warm and cold fronts at 2° × 2.5° × 32 levels resolution gives similar cloud distributions but with much lower cloud fraction, a shallower depth of cloudiness, and a shorter extent of tilted warm-frontal cloud cover on the cold air side of the surface frontal position. A close examination of the relationship between the cloudiness and relative humidity fields indicates that water vapor is not lifted enough in modeled midlatitude cyclones and this is related to weak vertical velocities in the model. The model also produces too little cloudiness for a given value of vertical velocity or relative humidity. For global climate models run at scales coarser than tens of kilometers, the authors suggest that the current underestimate of modeled cloud cover in the storm track regions, and in particular the 50°–60°S band of the Southern Oceans, could be reduced with the implementation of a slantwise convection parameterization.
    Poore K. D., J. H. Wang, and W. B. Rossow, 1995: Cloud layer thicknesses from a combination of surface and upper-air observations. J. Climate, 8, 550-568, 1520-0442(1995)008<0550:CLTFAC>2.0.CO;2.10.1175/1520-0442(1995)0082.0.CO; layer thicknesses are derived from base and top altitudes by combining 14 years (19751988) of surface and upper-air observations at 63 sites in the Northern Hemisphere. Rawinsonde observations are employed to determine the locations of cloud-layer top and base by testing for dewpoint temperature depressions below some threshold value. Surface observations serve as quality cheeks on the rawinsonde-determined cloud properties and provide cloud amount and cloud-type information. The dataset provides layer-cloud amount, cloud type, high, middle, or low height classes, cloud-top heights, base heights and layer thicknesses, covering a range of latitudes from 0℃ to 80℃N. All data comes from land sites: 34 are located in continental interiors, 14 are near coasts, and 15 are on islands. The uncertainties in the derived cloud properties are discussed. For clouds classified by low-, mid-, and high-top altitudes, there are strong latitudinal and seasonal variations in the layer thickness only for high clouds. High-cloud layer thickness increases with latitude and exhibits different seasonal variations in different latitude zones: in summer, high-cloud layer thickness is a maximum in the Tropics but a minimum at high latitudes. For clouds classified into three types by base altitude or into six standard morphological types, latitudinal and seasonal variations in layer thickness are very small. The thickness of the clear surface layer decreases with latitude and reaches a summer minimum in the Tropics and summer maximum at higher latitudes over land, but does not vary much over the ocean. Tropical clouds occur in three base-altitude groups and the layer thickness of each group increases linearly with top altitude. Extratropical clouds exhibit two groups, one with layer thickness proportional to their cloud-top altitude and one with small (鈮1000 m) layer thickness independent of cloud-top altitude.
    Sassen K., Z. E. Wang, 2008: Classifying clouds around the globe with the CloudSat radar: 1-year of results.Geophys. Res. Lett.,35,L04805, supports a 94 GHz cloud profiling radar as part of the innovative A-train formation of satellites studying the Earths clouds and atmosphere. Using the vertical profiles of clouds and precipitation, an algorithm has been developed to determine the type of clouds present. Because cloud type corresponds to specific cloud physical properties, this step is needed to apply other algorithms to derive quantitative cloud content and radiative data. This cloud type algorithm is applied to the initial 1-year of radar data to obtain the global distribution of various cloud types over the land and ocean. These initial results appear consistent with previous global cloud type distributions, but with some differences that provide insights into the limitations of CloudSat measurements.
    Sharma S., R. Vaishnav, M. V. Shukla, P. Kumar, P. Kumar, P. K. Thapliyal, S. Lal, and Y. B. Acharya, 2016: Evaluation of cloud base height measurements from Ceilometer CL31 and MODIS satellite over Ahmedabad,India. Atmospheric Measurement Techniques, 9, 711-719, amt-9-711-2016.10.5194/ play a tangible role in the Earth's atmosphere and in particular, the cloud base height (CBH) which is linked to cloud type is one of the important characteristic to describe the influence of clouds on the environment. In present study, CBH observations from ceilometer CL31 have been extensively studied during May 2013 to January 2015 over Ahmedabad (23.03℃ N, 72.54℃ E), India. A detail comparison has been performed with the use of ground-based CBH measurements from ceilometer CL31 and CBH retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard Aqua and Terra satellite. Some interesting features of cloud dynamics viz. strong downdraft and updraft have been observed over Ahmedabad which revealed different cloud characteristics during monsoon and post-monsoon periods. CBH shows seasonal variation during Indian summer monsoon and post-monsoon period. Results indicate that ceilometer is one of the excellent instruments to precisely detect low and mid-level clouds and MODIS satellite provides accurate retrieval of high-level clouds over this region. The CBH algorithm used for MODIS satellite is also able to capture the low-level clouds.
    Shonk J. K. P., R. J. Hogan, and J. Manners, 2012: Impact of improved representation of horizontal and vertical cloud structure in a climate model.Climate Dyn.,38,2365-2376, studies have investigated the effects that misrepresentation of sub-grid cloud structure can have on the radiation budget. In this study, we perform 20-year simulations of the current climate using an atmosphere-only version of the Met Office Unified Model to investigate the effects of cloud approximation on model climate. We apply the “Tripleclouds” scheme for representing horizontal cloud inhomogeneity and “exponential-random” overlap, both separately and in combination, in place of a traditional plane-parallel representation with maximum-random overlap, to the clouds within the radiation scheme. The resulting changes to both the radiation budget and other meteorological variables, averaged over the 2002years, are compared. The combined global effect of the parameterizations on top-of-atmosphere short-wave and long-wave radiation budget is less than 102W02m 612 , but changes of up to 1002W02m 612 are identified in marine stratocumulus regions. A cooling near the surface over the winter polar regions of up to 3°C is also identified when horizontal cloud inhomogeneity is represented, and a warming of similar magnitude is found when exponential-random overlap is implemented. Corresponding changes of the same sign are also found in zonally averaged temperature, with maximum changes in the upper tropical troposphere of up to 0.5°C. Changes in zonally averaged cloud fraction in this location were of opposite sign and up to 0.02. The individual effects on tropospheric temperature of improving the two components of cloud structure are of similar magnitudes to about 2% of the warming created by a quadrupling of carbon dioxide.
    Stephens G. L., 2005: Cloud feedbacks in the climate system: A critical review.J. Climate18,237-273,
    Stephens, G. L., Coauthors, 2002: The CloudSat Mission and the A-Train: A new dimension of space-based observations of clouds and precipitation.Bull. Amer. Meteor. Soc.,83,1771-1790, is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASA's Aqua and Aura satellites, a NASA-CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the CALIPSO lidar footprint and the other measurements of the constellation. The precision and near simultaneity of this overlap creates a unique multisatellite observing system for studying the atmospheric processes essential to the hydrological cycle.The vertical profiles of cloud properties provided by CloudSat on the global scale fill a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring these profiles requires a combination of active and passive instruments, and this will be achieved by combining the radar data of CloudSat with data from other active and passive sensors of the constellation. This paper describes the underpinning science and general overview of the mission, provides some idea of the expected products and anticipated application of these products, and the potential capability of the A-Train for cloud observations. Notably, the CloudSat mission is expected to stimulate new areas of research on clouds. The mission also provides an important opportunity to demonstrate active sensor technology for future scientific and tactical applications. The CloudSat mission is a partnership between NASA's JPL, the Canadian Space Agency, Colorado State University, the U.S. Air Force, and the U.S. Department of Energy.
    Stephens, G. L., Coauthors, 2012: An update on Earth's energy balance in light of the latest global observations.Nature Geoscience5,691-696, change is governed by changes to the global energy balance. A synthesis of the latest observations suggests that more longwave radiation is received at the Earth's surface than previously thought, and that more precipitation is generated.
    Sun B. M., T. R. Karl, and D. J. Seidel, 2007: Changes in cloud-ceiling heights and frequencies over the United States since the early 1950s.J. Climate20,3956-3970, U.S. weather stations operated by NOAA's National Weather Service (NWS) have undergone significant changes in reporting and measuring cloud ceilings. Stations operated by the Department of Defense have maintained more consistent reporting practices. By comparing cloud-ceiling data from 223 NWS first-order stations with those from 117 military stations, and by further comparison with changes in physically related parameters, inhomogeneous records, including all NWS records based only on automated observing systems and the military records prior to the early 1960s, were identified and discarded. Data from the two networks were then used to determine changes in daytime ceiling height (the above-ground height of the lowest sky-cover layer that is more than half opaque) and ceiling occurrence frequency (percentage of total observations that have ceilings) over the contiguous United States since the 1950s. Cloud-ceiling height in the surface-3.6-km layer generally increased during 1951-2003, with more significant changes in the period after the early 1970s and in the surface-2-km layer. These increases were mostly over the western United States and in the coastal regions. No significant change was found in surface-3.6-km ceiling occurrence during 1951-2003, but during the period since the early 1970s, there is a tendency for a decrease in frequency of ceilings with height below 3.6 km. Cloud-ceiling heights above 3.6 km have shown no significant changes in the past 30 yr, but there has been an increase in frequency, consistent with the increase in ceiling height below 3.6 km. For the surface-3.6-km layer, physically consistent changes were identified as related to changes in ceiling height and frequency of occurrence. This included reductions in precipitation frequency related to low ceiling frequency, and surface warming and decreasing relative humidity accompanying increasing ceiling heights during the past 30 yr.
    Wang, F., Coauthors, 2015: Multi-sensor quantification of aerosol-induced variability in warm cloud properties over eastern China.Atmos. Environ.,113,1-9, .10.1016/ (AC) interactions remain uncharacterized due to difficulties in obtaining accurate aerosol and cloud observations. In this study, we quantified the aerosol indirect effects (AIE) on warm clouds over Eastern China based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO, and CPR/CLOUDSAT between June 2006 and December 2010. The seasonality of aerosols from ground-based PM 10 (aerosol particles with diameter of 10m or less) significantly differed from that estimated using MODIS aerosol optical depth (AOD). This result was supported by the lower level frequency profile of aerosol occurrence from CALIOP, indicative of the significant role of CALIOP in the AC interaction. To focus on warm clouds, cloud layers with base (top) altitudes above 7 (10) km were excluded. The combination of CALIOP and CPR was applied to determine the exact position of warm clouds relative to aerosols out of the following six scenarios in terms of AC mixing states: 1) aerosol only (AO); 2) cloud only (CO); 3) single aerosol layer-single cloud layer (SASC); 4) single aerosol layer-double cloud layers (SADC); 5) double aerosol layers - single cloud layer (DASC); and 6) others. The cases with vertical distance between aerosol and cloud layer less (more) than 100m (700m) were marked mixed (separated), and the rest as uncertain. Results showed that only 8.95% (7.53%) belonged to the mixed (separated and uncertain) state among all of the collocated AC overlapping cases, including SASC, SADC, and DASC. Under mixed conditions, the cloud droplet effective radius (CDR) decreased with increasing AOD at moderate aerosol loading (AOD<0.4), and then became saturated at an AOD of around 0.5, followed by an increase in CDR with increasing AOD, known as boomerang shape. Under separated conditions, no apparent changes in CDR with AOD were observed. We categorized the AC dataset into summer- and winter-season subsets to determine how the boomerang shape varied with season. The response of CDR to AOD in summer exhibited similar but much more deepened boomerang shape, as compared with the all year round case. In contrast, CDR in winter did not follow the boomerang shape for its continued decreasing with increasing AOD, even after the saturation zone (AOD around 0.5) of a cloud droplet.
    Wang J. H., W. B. Rossow, 1995: Determination of cloud vertical structure from upper-air observations. J. Appl. Meteor., 34, 2243-2258, <2243:DOCVSF>2.0.CO;2.10.1175/1520-0450(1995)0342.0.CO; method is described to use rawinsonde data to estimate cloud vertical structure, including cloud-top and cloud-base heights, cloud-layer thickness, and the characteristics of multilayered clouds. Cloud-layer base and top locations are identified based on three criteria: maximum relative humidity in a cloud of at least 87%, minimum relative humidity of at least 84%, and relative humidity jumps exceeding 3% at cloud-layer top and base, where relative humidity is with respect to liquid water at temperatures greater than or equal to 0°C and with respect to ice at temperatures less than 0°C. The analysis method is tested at 30 ocean sites by comparing with cloud properties derived from other independent data sources. Comparison of layer-cloud frequencies of occurrence with surface observations shows that rawinsonde observations (RAOBS) usually detect the same number of cloud layers for low and middle clouds as the surface observers, but disagree more for high-level clouds. There is good agreement between the seasonal variations of RAOBS-determined top pressure of the highest cloud and that from the International Satellite Cloud Climate Project (ISCCP) data. RAOBS-determined top pressures of low and middle clouds agree better with ISCCP, but RAOBS often fail to detect very high and thin clouds. The frequency of multilayered clouds is qualitatively consistent with that estimated from surface observations. In cloudy soundings at these ocean sites, multilayered clouds occur 56% of the time and are predominately two layered. Multilayered clouds are most frequent (≈70%) in the Tropics (10°S0210°N) and least frequent at subtropical eastern Pacific stations. The frequency of multilayered clouds is higher in summer than in winter at low-latitude stations (30°S0230°N), but the opposite variation appears at the two subtropical stations. The frequency distributions of cloud top, cloud base, and cloud-layer thickness and cloud occurrence as a function of height are also presented. The lowest layer of multilayered cloud systems is usually located in the atmospheric boundary layer.
    Warren S. G., R. M. Eastman, and C. J. Hahn, 2007: A survey of changes in cloud cover and cloud types over land from surface observations,1971-96.J. Climate,20,717-738, the middle latitudes of both hemispheres, seasonal anomalies of cloud cover are positively correlated with surface temperature in winter and negatively correlated in summer, as expected if the direction of causality is from clouds to temperature.
    Warren S. G., C. J. Hahn, J. London, R. M. Chervin, and R. L. Jenne, 1986: Global distribution of total cloud cover and cloud type amounts over land. NCAR Technical Note NCAR/ TN-273+STR, National Center for Atmospheric Research, Boulder, CO, 29 pp,
    Warren S. G., C. J. Hahn, J. London, R. M. Chervin, and R. L. Jenne, 1988: Global distribution of total cloud cover and cloud type amounts over the ocean.NCAR Technical Note NCAR/TN-317+STRNational Center for Atmospheric Research,Boulder,CO,42pp, is the fourth of a series of atlases to result from a study of the global cloud distribution from ground-based observations. The first two atlases (NCAR/TN-201+STR and NCAR/TN-241+STR) described the frequency of occurrence of each cloud type and the co-occurrence of different types, but included no information about cloud amounts. The third atlas (NCAR/TN-273+STR) described, for the land areas of the earth, the average total cloud cover and the amounts of each cloud type, and their geographical, diurnal, seasonal, and interannual variations, as well as the average base heights of the low clouds. The present atlas does the same for the ocean areas of the earth.
    Wild M., 2012: New Directions: A facelift for the picture of the global energy balance.Atmos. Environ.,55,366-367, Available
    Zelinka M. D., S. A. Klein, K. E. Taylor, T. Andrews, M. J. Webb, J. M. Gregory, and P. M. Forster, 2013: Contributions of different cloud types to feedbacks and rapid adjustments in CMIP5.J. Climate26,5007-5027, five climate model simulations of the response to an abrupt quadrupling of CO2, the authors perform the first simultaneous model intercomparison of cloud feedbacks and rapid radiative adjustments with cloud masking effects removed, partitioned among changes in cloud types and gross cloud properties. Upon CO2 quadrupling, clouds exhibit a rapid reduction in fractional coverage, cloud-top pressure, and optical depth, with each contributing equally to a 1.1 W m(-2) net cloud radiative adjustment, primarily from shortwave radiation. Rapid reductions in midlevel clouds and optically thick clouds are important in reducing planetary albedo in every model. As the planet warms, clouds become fewer, higher, and thicker, and global mean net cloud feedback is positive in all but one model and results primarily from increased trapping of longwave radiation. As was true for earlier models, high cloud changes are the largest contributor to intermodel spread in longwave and shortwave cloud feedbacks, but low cloud changes are the largest contributor to the mean and spread in net cloud feedback. The importance of the negative optical depth feedback relative to the amount feedback at high latitudes is even more marked than in earlier models. The authors show that the negative longwave cloud adjustment inferred in previous studies is primarily caused by a 1.3 W m(-2) cloud masking of CO2 forcing. Properly accounting for cloud masking increases net cloud feedback by 0.3 W m(-2) K-1, whereas accounting for rapid adjustments reduces by 0.14 W m(-2) K-1 the ensemble mean net cloud feedback through a combination of smaller positive cloud amount and altitude feedbacks and larger negative optical depth feedbacks.
    Zhang J. Q., H. B. Chen, Z. Q. Li, X. H. Fan, L. Peng, Y. Yu, and M. Cribb, 2010: Analysis of cloud layer structure in Shouxian,China using RS92 radiosonde aided by 95 GHz cloud radar.J. Geophys. Res.,115,D00K30,[1] The Atmospheric Radiation Measurement Mobile Facility (AMF) was deployed in Shouxian, Anhui Province, China from 14 May to 28 December 2008. Radiosonde data obtained during the AMF campaign are used to analyze cloud vertical structure over this area by taking advantage of the first direct measurements of cloud vertical layers from the 95 GHz radar. Single-layer, two-layer, and three-layer clouds account for 28.0%, 25.8%, and 13.9% of all cloud configurations, respectively. Low, middle, high and deep convective clouds account for 20.1%, 19.3%, 59.5%, and 1.1% of all clouds observed at the site, respectively. The average cloud base height, cloud top height, and cloud thickness for all clouds are 5912, 7639, and 1727 m, respectively. Maximum cloud top height and cloud thickness occurred at 1330 local standard time (LST) for single-layer clouds and the uppermost layer of multiple layers of cloud. For lower layer clouds in multiple-layer cloud systems, maximum cloud top height and cloud thickness occurred at 1930 LST. Diurnal variations in the thickness of upper level clouds are larger than those of lower level clouds. Multilayer clouds occurred more frequently in the summer. The absolute differences in cloud base heights from radiosonde and micropulse lidar/ceilometer comparisons are less than 500 m for 77.1%/68.4% of the cases analyzed.
    Zhang J. Q., X. A. Xia, and H. B. Chen, 2017a: A comparison of cloud layers from ground and satellite active remote sensing at the Southern Great Plains ARM site.Adv. Atmos. Sci.,34,347-359, the data collected over the Southern Great Plains ARM site from 2006 to 2010, the surface Active Remote Sensing of Cloud (ARSCL) and CloudSat-CALIPSO satellite (CC) retrievals of total cloud and six specified cloud types [low, mid-low (ML), high-mid-low (HML), mid, high-mid (HM) and high] were compared in terms of cloud fraction (CF), cloud-base height (CBH), cloud-top height (CTH) and cloud thickness (CT), on different temporal scales, to identify their respective advantages and limitations. Good agreement between the two methods was exhibited in the total CF. However, large discrepancies were found between the cloud distributions of the two methods at a high (240-m) vertical grid spacing. Compared to the satellites, ARSCL retrievals detected more boundary layer clouds, while they underestimated high clouds. In terms of the six specific cloud types, more low- and mid-level clouds but less HML- and high-level clouds were detected by ARSCL than by CC. In contrast, the ARSCL retrievals of ML- and HM-level clouds agreed more closely with the estimations from the CC product. Lower CBHs tended to be reported by the surface data for low-, ML- and HML-level clouds; however, higher CTHs were often recorded by the satellite product for HML-, HM- and high-level clouds. The mean CTs for low- and ML-level cloud were similar between the two products; however, the mean CTs for HML-, mid-, HM- and high-level clouds from ARSCL were smaller than those from CC.
    Zhang L., X. Q. Dong, A. Kennedy, B. K. Xi, and Z. Q. Li, 2017b: Evaluation of NASA GISS post-CMIP5 single column model simulated clouds and precipitation using ARM Southern Great Plains observations.Adv. Atmos. Sci.,34,306-320, planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 200208. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.
    Zhou C., M. D. Zelinka, and S. A. Klein, 2016: Impact of decadal cloud variations on the Earth's energy budget.Nature Geoscience9,871-874, feedbacks strongly influence the magnitude of global warming. Climate model simulations show that these feedbacks vary strongly as the spatial patterns of sea surface temperatures change over time.
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Manuscript History

Manuscript received: 15 April 2017
Manuscript revised: 07 September 2017
Manuscript accepted: 09 October 2017
通讯作者: 陈斌,
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Climatology of Cloud-base Height from Long-term Radiosonde Measurements in China

  • 1. Meteorological Observation Center, China Meteorological Administration, Beijing 100081, China
  • 2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 3. Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 4. National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China
  • 5. College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China

Abstract: Clouds are critical to the global radiation budget and hydrological cycle, but knowledge is still poor concerning the observed climatology of cloud-base height (CBH) in China. Based on fine-resolution sounding observations from the China Radiosonde Network (CRN), the method used to estimate CBH was modified, and uncertainty analyses indicated that the CBH is good enough. The accuracy of CBH estimation is verified by the comparison between the sounding-derived CBHs and those estimated from the micro-pulse lidar and millimeter-wave cloud radar. As such, the CBH climatology was compiled for the period 2006-16. Overall, the CBH exhibits large geographic variability across China, at both 0800 Local Standard Time (LST) and 2000 LST, irrespective of season. In addition, the summertime cloud base tends to be elevated to higher altitudes in dry regions [i.e., Inner Mongolia and the North China Plain (NCP)]. By comparison, the Tibetan Plateau (TP), Pearl River Delta (PRD) and Sichuan Basin (SCB) have relatively low CBHs (<2.4 km above ground level). In terms of seasonality, the CBH reaches its maximum in summer and minimum in winter. A low cloud base tends to occur frequently (>70%) over the TP, PRD and SCB. In contrast, at most sites over the Yangtze River Delta (YRD) and the NCP, about half the cloud belongs to the high-cloud category. The CBH does not exhibit marked diurnal variation in summer, throughout all CRN sites, probably due to the persistent cloud coverage caused by the East Asia Summer Monsson. To the best of our knowledge, this is the first CBH climatology produced from sounding measurements in China, and provides a useful reference for obtaining observational cloud base information.

摘要: 云的观测对于全球辐射平衡和水循环至关重要, 目前我国对于云底高度(CBH)的气候特征分析还较为缺乏. 基于中国探空观测网络(CRN)的高分辨率长期(2006-2016年)探空观测资料, 我们提出了改进的相对湿度阈值法, 借助2016年夏季邢台增强观测试验期间获取的云雷达, 微脉冲激光雷达计算得到的CBH, 进行了算法验证, 效果良好. 分析了2006-2016年的云底高度气候特征, 总体而言, 不同季节的CBH在中国区域均存在较大的地域差异. 此外, 夏季在干旱地区(如内蒙古和华北平原)云底抬升的更高, 而在青藏高原, 珠江三角洲及四川盆地云底高度相对较低(距离地面 2.4 km). 季节分布上, 云底高度夏季最高, 冬季最低. 低云发生频率( 70%)多数出现在青藏高原, 珠江三角洲及四川盆地. 相反, 长江三角洲和华北平原出现的云约有一半是高云. 夏季, 所有观测站的云底高度并未表现出明显的日变化, 可能是由于夏季14时的探空观测主要用于改善高影响天气的预报, 导致所观测到的低层大气容易出现湿度较大现象引起. 据我们所知, 这是中国第一个基于高空探测资料建立的云底高度气候产品, 可用于准确估算云对人类气候系统的辐射强迫.

1. Introduction
  • Cloud plays a significant role in the Earth's energy budget by reflecting and absorbing incoming solar radiation and reducing outgoing thermal radiation (Stephens et al., 2012; Zhou et al., 2016). The impacts of cloud on the radiation balance of the Earth-atmosphere system depend not only on the vertical structure and distribution of the cloud but also on its base and top heights and optical properties (Wild, 2012; Zhang et al., 2017a). Cloud radiative forcings, especially those induced by aerosol-cloud interaction (Wang et al., 2015; Guo et al., 2016a, 2017), further contribute to uncertainties in weather forecasting and climate prediction (Li et al., 2016). Cloud properties have changed and will continue to change in a warming climate, including changes in cloud height, cloud cover, and morphology (Eastman and Warren, 2013). For decades, both observations and models have been extensively used to elucidate the characteristics of cloud and their corresponding changes on the daily, seasonal and yearly time scales (Klein and Hartmann, 1993; Baker and Peter, 2008; Clement et al., 2009; Davies and Molloy, 2012; Shonk et al., 2012; Zelinka et al., 2013; Myers and Norris, 2015; Miao et al., 2017).

    The properties of cloud are generally associated with cloud types, and the climate effects caused by various cloud types differ greatly; in some circumstances they are even totally opposite. For instance, high cloud has a warming effect on the surface, as opposed to the cooling effect of low-level clouds (IPCC, 2013). Unfortunately, cloud profiles are poorly understood at present and remain a primary source of uncertainty in global weather and climate studies (Stephens, 2005).

    The retrieval of cloud profiles relies primarily on satellite- (e.g., Minnis and Harrison, 1984; Morel and Senesi, 2002) and surface-based observations (e.g., Dong et al., 2006). The advent of spaceborne active cloud radar (e.g., CloudSat) has allowed for a better portrayal of cloud vertical structure on both regional and global scales, making it one of the most popular data sources for cloud studies (Stephens et al., 2002; Sassen and Wang, 2008; Naud et al., 2010; Evan and Norris, 2012; Chen et al., 2016).

    Cloud-base height (CBH) is an important cloud macrophysical parameter, strongly affecting the energy exchanges between the cloud layer and the ground surface (Wild, 2012). Using the cloud profiles and CBH data determined from the active-sounding measurements of CloudSat and CALIPSO has helped resolve the long-standing debate over the underestimation of thermal back-radiation, which has been updated from the previous estimate of 324 W m-2 (Kiehl and Trenberth, 1997) to around 345-350 W m-2 (Kato et al., 2011; Stephens et al., 2012). However, thin clouds cannot be accurately identified by the cloud profiling radar onboard CloudSat (Marchand et al., 2008). A recent study indicated that large uncertainties exist in the CBH from CloudSat-CALIPSO data, based on comparison with ground-based active remote sensing of cloud (Zhang et al., 2017b).

    In comparison to satellite measurements, ground-based cloud observations based on instruments such as cloud radars, lidars (e.g., Borg et al., 2011) and ceilometers (e.g., Martucci et al., 2010; Costa-Surós et al., 2009), can provide CBH measurements with higher accuracy and continuous temporal coverage (Sharma et al., 2016). In North America, an automated observation system employs ceilometers to observe cloud. However, these ceilometers observe cloud at a cutoff range, generally lower than 4 km (Dai et al., 2006). In other parts of the world, these instruments are generally deployed at very few locations. Fortunately, radiosondes can also penetrate cloud layers to provide in-situ measurements such as temperature, relative humidity and pressure, which are fundamental to estimating the profiles of atmospheric and cloud properties (Poore et al., 1995; Zhang et al., 2010). More importantly, operational radiosonde networks make it possible to retrieve the CBH over a large scale. For example, (Wang and Rossow, 1995) successfully obtained the cloud vertical structure based on relative humidity (RH) sounding data alone, and (Chernykh et al., 2001) analyzed worldwide long-term cloud-base and -top height trends based on RH and temperature sounding data.

    Warren et al. (1986, 1988) produced a database from surface land stations and ship measurements and compiled a climatology of CBH over land and ocean by focusing on different cloud types (Warren et al., 2007; Eastman et al., 2011; Eastman and Warren, 2014). (Sun et al., 2007) comprehensively analyzed the temporal trend of cloud-top heights and frequencies over the United States since the early 1950s, based mainly on human observations at weather stations. (An et al., 2017) interpreted the diurnal, seasonal and interannual variability of the CBH over the contiguous United States based on an automated surface observing system.

    However, notwithstanding a few CBH studies (e.g., Zhang et al., 2010) that were limited to a specific region of interest in China, no attempt (to the best of our knowledge) has been made to examine the climatology of CBH across China from long-term sounding observations from the China Radiosonde Network (CRN; Guo et al., 2016b). Accordingly, the main goals of the present study were to estimate the CBH with a robust method, and then elucidate the spatial and temporal characteristics of the CBH across China based on long-term soundings from the CRN. The remainder of the paper is organized as follows: Section 2 describes the data and the methods employed in this study. The uncertainty of the CBH estimation method is analyzed and discussed in section 3, followed in the same section by an analysis of the climatology, diurnal variation and seasonal differences of the CBH across China. The main conclusions are summarized in section 4.

2. Data and methods
  • The operational CRN consists of 120 sites equipped with L-band sounding systems, including GFE (L) 1 secondary wind radar and GTS1 digital electronic radiosondes (Guo et al., 2016b). The new-generation GTS1 digital radiosonde takes measurements of temperature, pressure, RH, wind speed, and wind direction twice a day [at 0800 Local Standard Time (LST, UTC+8) and 2000 LST], with a sampling frequency of once every 1.2 seconds. The vertical resolution varies from site to site, and from sounding to sounding at the same radiosonde site. A previous intercomparison of GTS1 against Vaisala RS80 indicated that they are in good agreement in terms of their profile measurements in the troposphere, despite a large bias in the upper atmospheric levels (Bian et al., 2011).

    The setup of CRN dates back to 2002 when the China Meteorological Administration decided to upgrade existing radiosonde instruments; however, the GTS1 radiosonde at 14 sites only officially came into operation in 2006, as illustrated in Fig. 1. The L-band sounding systems with GTS1 radiosondes began to be widely deployed in 2007 across China, and had gradually expanded to 120 operational radiosonde stations by 2011. As such, each site of the CRN with GTS1 radiosonde data differs in their period of coverage (Fig. 1b). Overall, roughly 60% (97%) of radiosonde sites have more than 10 (6) years of L-band sounding data, which provides an even distribution across China and sufficient samples to characterize the climatology of the CBH from sounding data.

    Figure 1.  (a) Spatial distribution of 120 sounding sites (colored circles) of the CMA over China. The different colors correspond to the year when the next-generation L-band radiosonde was first launched operationally. (b) Time series of the number of stations in the sounding sites dataset over China. The number of stations increased sharply in 2007, and reached 120 in 2011.

    Therefore, the sounding data collected from the CRN during the period 1 December 2006 to 31 December 2016 were used to estimate the CBH across China. In summer (June-July-August), two additional soundings were launched (at 0200 LST and 1400 LST) to improve the predictability of high-impact weather at selected sites of the CRN, depending on the locations of large-scale synoptic weather systems. In this way, we in total made use of 421 729 profiles across China, including 1979 profiles at 0200 LST, 208 445 profiles at 0800 LST, 9726 profiles at 1400 LST, and 201 579 profiles at 2000 LST.

  • Cloud generally forms at an RH of about 100%. It is, however, rarely observed in radiosonde observations for the reasons listed in (Wang and Rossow, 1995). In particular, the thermal lag tends to result in lower-than-normal RH values by about 3%, which is mainly caused by the temperature in the hygristor element being roughly 1°C above the ambient temperature as the radiosonde passes through the cloud layer (Garand et al., 1992). Regarding the hygristor inside the GTS1 of the CRN, the abovementioned thermal lag is too serious to be used to detect the cloud top (Bian et al., 2011). This is why the cloud top height was not investigated in this study.

    In our analysis, the method proposed by (Wang and Rossow, 1995) was modified to better detect the cloud base, given the high temporal vertical resolution (1.2 s). First, the soundings under rainy conditions (rainfall amount >0.1 mm) were excluded from the cloud-base detection. On average, 6.49% of all soundings witnessed valid precipitating events for all of the sounding hours during the period 2006-16 [Fig. S1 in electronic supplementary material (ESM)]. Therefore, the treatment of rainy sounding at missing value is reasonable. Then, the cloud base was determined by taking the following three steps: (1) the base of the lowest moist layer was determined as the average altitude where the minimum RH greater than 84% reached for at least four consecutive valid measurements; (2) an at least 3% jump in the RH could be seen from the adjacent lower level; and (3) the minimum CBH was set to 600 m above ground level (AGL) to avoid the noise caused by drizzle or rainfall below the cloud. In this way, RH profiles for all valid soundings were examined from 600 m AGL to the top to determine cloud bases.

    Figure 2.  Scatterplots showing CBH computed using (a) 84% and 83% and (b) 84% and 85% as the critical RH, both of which are based on 39 1552 soundings across China in summer during the period 2006-16. (c, d) The 50th and 75th percentile values of (c) absolute uncertainty and (d) relative uncertainty using 83% and 85% as the critical RH. The correlation coefficients (R) are given in the top panels, where an asterisk indicates the value is statistically significant (p<0.05).

    To understand the frequency distribution of cloud with various CBH, the sounding-derived CBH retrievals were grouped into three height intervals: 0.6-2 km; 2-3.6 km; and above 3.6 km, with the 0.6-2-km category representing low cloud (Sun et al., 2007). Due to the spatial inhomogeneity, all sites were interpolated onto a regular 5°× 5° grid. Then, the CBH for each grid was calculated by simply averaging the available site data within the grid. In this way, any potential biases resulting from the spatial inhomogeneity of the radiosonde sites was minimized (Fig. 1a).

3. Results and discussion
  • The estimated CBH depends on the RH threshold values, which inevitably induces uncertainty in the CBH climatology. Uncertainty analysis, therefore, is imperative, and this is achieved by investigating the magnitude of changes in the CBH due to the selection of various critical RH thresholds.

    Accordingly, scatterplots were produced that compare the CBH calculated using 84% and 83% as the critical RH versus those calculated using 84% and 85%. As expected, Figs. 2a and b show that the CBH based on RH = 85% (83%) is typically higher (lower) than that based on RH = 84%. However, the CBHs calculated using various RH thresholds are significantly correlated (R=0.987). Figures 2c and d illustrate the absolute and relative uncertainties, respectively, as a function of CBH (RH = 84%). Most of the 50th and 75th percentile values of the absolute uncertainties are <0.02 km and <0.03 km, respectively; and the 50th and 75th percentile values of the corresponding relative uncertainties are both <10% for CBH (RH = 84%) >2 km, and <20% for CBH (RH = 84%) within 1-2 km. In this sense, the uncertainty induced by the selection of the RH threshold is negligible.

    But what about the accuracy of the CBH estimated from the chosen RH threshold? Based on a field campaign carried out by our group last summer in Xingtai (37.05°N, 114.48°E), Hebei Province, China, we took the CBH retrievals for May 2016 from the micro-pulse lidar (MPL) and millimeter-wave cloud radar (MMCR) implemented at Xingtai and compared them with the estimated CBHs from the radiosonde data. Figure S2 shows a comparison between the CBHs retrieved from MPL and MMCR and those from the radiosonde data on 25 May 2016. It can be seen that the difference in the CBH between the two data sources is quite small during the daytime, and in both cases the sky turns overcast after 2000 LST, suggesting a dominance of stratus cloud. Therefore, the CBH detected by radiosonde is comparable to that derived from the MPL under this condition. More specifically, the CBH from MPL is 5156 m when averaged over the three minutes centered on the minute when the radiosonde detects the CBH, with a value of 4950 m. Therefore, the CBH results are in good agreement. Other cases throughout the field campaign at Xingtai from 15 May to 15 June 2016 were also examined (Fig. S3), the results of which verify that the CBH retrievals from MPL and radiosonde observations are consistent (R=0.998).

  • Figure 3 presents the geographic distribution of CBH derived from the 0800 LST radiosonde observations for the whole period from 2006 to 2016. Clearly, the CBH at 0800 LST does not exhibit strong latitudinal dependence. However, some strong spatial and seasonal variation stands out. On average, the CBH reaches its peak (2.99 1.2 km) in summer, followed by spring and fall, whereas the lowest CBH (2.38 1.1 km) is observed in winter. The strong contrast in CBH between summer and winter could be caused by the discrepancy in solar radiation reaching the surface. In addition, the lowest mean CBH found in winter is likely associated with the lowest temperature, which makes it easy for water vapor to condense or coalesce/collide to form cloud droplets under upward motion conditions, leading to a low cloud-top height.

    Figure 3.  Spatial distribution of CBH (color shaded) for each 5°× 5° grid across China at 0800 LST in (a) spring, (b) summer, (c) fall, and (d) winter, for the period 2006-16. Note that CBH for each 5°× 5° grid is calculated as the averaged CBH over all radiosonde sites within each grid.

    Figure 4.  As in Fig. 2 but for the spatial distribution of CBH at 2000 LST.

    Spatially, most sites in southwestern China, including the Tibetan Plateau (TP), Pearl River Delta (PRD) and Sichuan Basin (SCB), have a relatively low CBH (<2.4 km AGL). Most sites in the Yangtze River Delta (YRD) and North China Plain (NCP) have a CBH greater than 3.6 km AGL in spring and summer, which is on average 0.6 km lower than that in fall and winter. In Northeast China, the summertime cloud can form at altitudes greater than 3.0 km——higher than the cloud in spring, fall and winter. Likewise, a peak in CBH can be seen in Inner Mongolia in summer, which is generally higher than 3.0 km AGL.

    Similar to 0800 LST, the spatial variation of CBH at 2000 LST also does not exhibit distinct latitudinal dependence. Moreover, the spatial distributions of the 2000 LST CBH bear resemblance to those of the 0800 LST CBH, and the magnitude of the mean CBH in the four seasons changes little (Fig. 4). In terms of CBH seasonality, the springtime mean CBH is 2.86 km, which is slightly lower than that in summertime (2.92 km), and most radiosonde sites in winter have the lowest CBH. More specifically, the PRD has the lowest CBH in winter, and the CBH in NCP is highest in spring. The CBH diurnal and seasonal features in China are generally consistent with those obtained in the contiguous United States (An et al., 2017), which means that the geographic distribution of CBH in different seasons and at different times of the day have similar patterns.

  • Figure 5 shows the spatial distributions of CBH frequency for cloud bases within various altitudes at 0800 LST and 2000 LST during the period 2006-16. One striking feature is that the TP, PRD, and SCB are characterized by a high frequency (>70%) of low cloud base (0.6 km < CBH<2.0 km), suggesting cloud tends to form at low altitude. In contrast, at most sites of the YRD and NCP, about 40%-50% of cloud starts to develop at altitudes greater than 3.6 km AGL, for both the 0800 and 2000 LST observations, indicating it is difficult for cloud to form in the lower atmospheric boundary layer. Mid-level cloud (2.0 km < CBH<3.6 km) can be frequently (about 40%-50%) observed at most sites in Xinjiang Uygur Autonomous Region (Figs. 4c-d). For almost all sites in Southeast China, less than 30% of CBHs belong to mid-level cloud, at both 0800 and 2000 LST, due to their CBHs ranging between 2.0 km and 3.6 km AGL.

    To improve the forecasting accuracy of high-impact stormy weather in summer, atmospheric profile measurements at 0200 LST and 1400 LST are required at most sites of the CRN, in addition to the usual operational soundings at 0800 LST and 2000 LST. Figure 6 presents frequency histograms for the CBHs at 0200 LST, 0800 LST, 1400 LST, and 2000 LST during the period 2006-16 for all radiosonde sites in China. As also can be seen, 50% of valid CBH retrievals are less than 2.4 km AGL, which is slightly higher than 2.0 km for the CBHs at 2000 LST. On average, the frequency distribution of CBHs at 0200 LST is quite similar to that at 1400 LST. That is, about half of the CBHs are less than 1.6 km AGL.

    Figure 5.  Spatial distribution of the occurrence frequency for CBH within 0.6-2.0 km AGL at (a) 0800 LST and (b) 2000 LST, within 2.0-3.6 km AGL at (c) 0800 LST and (d) 2000 LST, and at higher than 3.6 km AGL at (e) 0800 LST and (f) 2000 LST, all of which are averaged over the period of 2006-16.

    Figure 6.  Histogram of CBH at (a) 0200 LST, (b) 0800 LST, (c) 1400 LST, and (d) 2000 LST, during 2006-16, for all radiosonde sites in China. The red curves indicate the accumulated frequency, whereas vertical green lines indicate the frequency of 50%.

  • The additional one or two soundings (i.e., 0200 LST and 1400 LST) at some sites of the CRN provide us with a unique opportunity to investigate the diurnal cycle of CBH across China from a radiosonde perspective. Figure 7 shows the spatial distributions of average CBH at 0200 LST, 0800 LST, 1400 LST and 2000 LST for the period 2006-16. Overall, the average CBH at 0200 LST and 1400 LST is slightly lower that that at 0800 LST and 2000 LST. Our understanding is that the soundings at 0200 LST and 1400 LST are mainly launched under atmospheric conditions favorable for the initiation and development of precipitation, which will inevitably lead to the more frequent occurrence of low precipitating cloud. This at least accounts for the lower CBH observed at 1400 LST despite the stronger solar-radiation induced convection in summer.

    Interestingly, we can still see a distinct spatial discrepancy in the CBH at 1400 LST, which is the same as that obtained at 0800 LST and 2000 LST. For instance, most of the sites on the NCP, and in Xinjiang, are characterized by high CBH, which is generally greater than 3.0 km AGL. The lowest CBH at 1400 LST tends to occur in the PRD, which is lower than 1.2 km AGL.

    As for the annual average CBH at 0800 LST, the maximum CBH tends to occur on the NCP and in the YRD, as opposed to the minimum CBH seen on the TP. In terms of the geographic distribution of the annual average CBH at 2000 LST, the contrast does not change too much.

    Accounting for the large longitudinal difference (63°E) between the radiosonde sites of the CRN, the time when the CBH is calculated had to be converted to LST, which should better represent the diurnal cycle of CBH. Putting all the CBHs together, the height-resolved frequency distributions of CBH during the course of a day for the period of 2006-16 were calculated for all radiosonde sites of the CRN (Fig. 8). On the whole, a gap exists due to the scarcity of valid CBH retrievals at 0300, 0400, 1000, 1600, 2200, 2300 and 2400 LST. In particular, more low cloud (CBH <2.0 km) tends to form at 0100, 0800, 1400, 1900 and 2000 LST, as compared with that at other times. The frequency distribution more or less reveals the zonal distribution of the radiosonde sites of the CRN.

    Figure 7.  Spatial distribution of annual-mean CBH for each 5°× 5° grid across China at (a) 0200 LST, (b) 0800 LST, (c) 1400 LST, and (d) 2000 LST, for the period 2006-16, and the mean CBH and its corresponding standard deviation (lower-left corner of each panel).

    Figure 8.  Height-resolved frequency of CBH retrieved from all valid soundings in China during the course of a day (in LST) in summer during 2006-16.

4. Concluding remarks
  • Taking advantage of extensive high-resolution radiosonde measurements acquired from 120 sites of the CRN during 2006-16, we produced a climatology of CBH in China by applying an RH threshold method to 421 729 individual radiosonde atmospheric profiles. The statistics regarding the CBH at diurnal and seasonal time scales across China have been presented. To the best of our knowledge, the climatology of CBH produced in this study is the first to elucidate the spatial and temporal distribution of CBH in China from a large-scale sounding perspective.

    Overall, CBH does not show any distinct latitudinal dependence; rather, it exhibits large spatial variability across China, at both 0800 LST and 2000 LST, for all seasons. In particular, the highest cloud tends to occur in relatively dry regions, such as Inner Mongolia, Xinjiang, and the NCP. In contrast, the TP, YRD and SCB have relatively low CBH (<2.4 km AGL). Meanwhile, the CBH also exhibits large seasonal variability; peak CBH is found at most sites of the CRN in summer, followed by spring and fall, with the lowest CBH observed in winter. On average, roughly 70% of cloud belongs to low cloud over the TP, YRD and SCB, due to the mean CBH being less than 2.0 km AGL. In contrast, at most sites of the YRD and NCP, about 40%-50% of cloud develops to high altitude. Interestingly, no marked diurnal cycle can be found for CBH across all sites of the CRN, most likely due to the extra soundings at 1400 LST in summertime launched for improving the numerical forecasting of high-impact weather.

    This study is just the first step in an attempt to fully understand the spatial and temporal distribution of CBH in China, which will provide a viable approach to obtain observational cloud-base information. Such information will in turn assist in better quantifying the cloud response to the increased aerosol pollution in recent years (Guo et al., 2011). However, the factors accounting for such a large spatial discrepancy have not been fully analyzed, which merits further detailed investigation in the future. In addition, more insight should be gained into the true diurnal cycle of CBH if more routine 1400 LST sounding observations become available.




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