中国东部层积云发展过程中云微物理特征的演变

基于2007—2010年的CloudSat卫星观测数据,以云层液态水路径为指标将层积云的发展过程划分为五个阶段,对比研究了中国东部降水与非降水层积云发展过程中云微物理特征和云微物理机制的演变,并分析了其海陆差异.研究表明:非降水层积云中,云滴增长主要通过凝结过程完成,但云滴的凝结增长有限,难以形成降水,在非降水层积云发展的旺盛阶段,云层中上部云滴发生较弱的碰并过程.降水层积云中云滴碰并增长活跃,当云层液态水路径小于500 g·m~(-2)时,云滴在从云顶下落至云底的过程中持续碰并,并在云底附近出现云水向雨水的转化;当降水层积云液态水路径超过500 g·m~(-2)时,云滴碰并增长主要发生在云层上部,在云层中部,云液态水含量、液态粒子数浓度和液态粒子有效半径达到最大,云水向雨水的转化最为活跃.层积云微物理特征的海陆差异主要是由海陆上空气溶胶浓度和云中上升气流强度不同导致的.在非降水层积云中下部,陆地丰富的气溶胶为云滴凝结增长提供了充足的云凝结核,因而云微物理量的量值在陆地上空更大,而在云层中上部,云滴凝结增长达到极限,海洋充足的水汽输送使云微物理量的量值在海洋上空更大.当降水层积云液态水路径大于500 g·m~(-2)时,陆地层积云中更强的上升气流使大量云滴在云层中上部累积滞留,云滴碰并增长活跃,云层中上部云微物理量的量值在陆地上空更大.     

Determination of magnetic cloud parameters and prediction of magnetic storm intensity

A program for identifying magnetic clouds in patrol satellite data, which recorded the interplanetary medium parameters near the magnetosphere, has been developed based on the cloud model in the form of a force-free cylindrical flux tube. The program makes it possible to also determine the entire magnetic field distribution in a cloud that approaches the Earth, using the initial satellite measurements. For this purpose, a model cloud (which has the maximal correlation coefficient with an analyzed cloud with respect to three magnetic field vector components and minimal rms deviations of the magnetic field and velocity components) is selected from the preliminarily created database including 2 million model clouds. The obtained magnetic field distribution in a cloud will make it possible to predict the intensity of a magnetic storm that this cloud will cause.     

Cloud-Radiation Studies During the European Cloud and Radiation Experiment (EUCREX)

The dominant role of clouds in modulating and interacting with radiative energy transports within the atmosphere, in providing precipitation, transporting water and influencing air-chemical processes is still not understood well enough to be accurately represented within atmospheric circulation and climate models over all regions of the globe. Also the extraction of real-world cloud properties from satellite measurements still contains uncertainties. Therefore, various projects have been developed within the Global Energy and Water Cycle Experiment (GEWEX), to achieve more accurate solutions for this problem by direct measurements within cloud fields and other complementary studies. They are based on the hypothesis, that most relevant properties of cloud fields can be parametrized on the basis of the prognostic field variables of atmospheric circulation models, and that the cloud microphysical properties can directly be related – with additional parameters on the particle shapes etc. – to the radiative transfer properties.One of these projects has been the European Cloud and Radiation Experiment (EUCREX) with its predecessor ICE (International Cirrus Experiment).The EUCREX and ICE provided a common platform for research groups from France, Germany, Sweden and the United Kingdom to concentrate their efforts primarily on high, cold cirrus. They showed, with data from satellites, that this cloud species enhances the atmospheric greenhouse-effect. Numerical mesoscale models were used in sensitivity studies on cloud developments. In-situ measurements of cloud properties were made during more than 30 aircraft missions, where also in-flight comparisons of various instruments were made to ensure the quality of data sets measured from different aircraft. The particle sampling probes, used for in-cloud measurements, showed a disagreement in total number density in all ranges between about 20–50%, while all other instruments agreed quite satisfactorily. A few measured holographic data provided information on typical ice-crystal shapes, which were used in numerical simulations of their absorption and scattering properties.Several new instruments for both in-situ and remote measurement, such as a polar nephelometer, a chopped pyrgeometer and an imaging multispectral polarimeter (POLDER) for cloud and radiation measurements were tested and improved. New algorithms were developed for cloud classifications in multispectral satellite images and also for simulations of the scattering of radiation by non-spherical particles.This paper primarily summarizes the EUCREX results obtained between 1989 and 1996, and provides examples of the many results which have been obtained so far. It is not a complete review of the world-wide state in this field, but it tries to place the EUCREX results into the world-wide development. Therefore many references are made to the results of other groups, which in turn influenced the work within EUCREX.     

The Clouds of the Middle Troposphere: Composition, Radiative Impact, and Global Distribution

The clouds of the middle troposphere span the temperature range where both ice and liquid water in a supercooled state can exist. However, because one phase tends to dominate, of the two midlevel cloud types, altostratus are deep ice-dominated, while altocumulus are shallow water-dominated, mixed-phase clouds with ice crystal virga typically trailing below. Multiple remote sensor examples of these cloud types are given to illustrate their main features, and the radiative consequences of the different cloud microphysical compositions are discussed. Spaceborne radar and lidar measurements using the CloudSat and CALIPSO satellites are analyzed to determine the global distributions of cloud frequencies and heights of these clouds. It is found that together these little-studied clouds cover ~25% of the Earth’s surface, which is about one-third of the total cloud cover, and thus represent a significant contribution to the planet’s energy balance.     

Preliminary laboratory studies of the optical scattering properties of the crystal clouds

Ice crystal clouds have an influence on the radiative budget of the earth; however, the exact size and nature of this influence has yet to be determined. A laboratory cloud chamber experiment has been set up to provide data on the optical scattering behaviour of ice crystals at a visible wavelength in order to gain information which can be used in climate models concerning the radiative characteristics of cirrus clouds. A PMS grey-scale probe is used to monitor simultaneously the cloud microphysical properties in order to correlate these closely with the observed radiative properties. Preliminary results show that ice crystals scatter considerably more at 90° than do water droplets, and that the halo effects are visible in a laboratorygenerated cloud when the ice crystal concentration is sufficiently small to prevent masking from multiple scattering.     

Daytime precipitation identification scheme based on multiple cloud parameters retrieved from visible and infrared measurements

Visible and infrared (VIR) measurements and the retrieved cloud parameters are commonly used in precipitation identification algorithms, since the VIR observations from satellites, especially geostationary satellites, have high spatial and temporal resolutions. Combined measurements from visible/infrared scanner (VIRS) and precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite are analyzed, and three cloud parameters, i.e., cloud optical thickness (COT), effective radius (Re), and brightness temperature of VIRS channel 4 (BT4), are particularly considered to characterize the cloud status. By associating the information from VIRS-derived cloud parameters with those from precipitation detected by PR, we propose a new method for discriminating precipitation in daytime called Precipitation Identification Scheme from Cloud Parameters information (PISCP). It is essentially a lookup table (LUT) approach that is deduced from the optimal equitable threat score (ETS) statistics within 3-dimensional space of the chosen cloud parameters. South and East China is selected as a typical area representing land surface, and the East China Sea and Yellow Sea is selected as typical oceanic area to assess the performance of the new scheme. It is proved that PISCP performs well in discriminating precipitation over both land and oceanic areas. Especially, over ocean, precipitating clouds (PCs) and non-precipitating clouds (N-PCs) are well distinguished by PISCP, with the probability of detection (POD) near 0.80, the probability of false detection (POFD) about 0.07, and the ETS higher than 0.43. The overall spatial distribution of PCs fraction estimated by PISCP is consistent with that by PR, implying that the precipitation data produced by PISCP have great potentials in relevant applications where radar data are unavailable.     

Diagnosis of cirrus cloud occurrence using large-scale analysis data and a cloud-scale model

The development of cirrus clouds is governed by large-scale synoptic movements such as updraft regions in convergence zones, but also by smaller scale features, for instance microphysical phenomena, entrainment, small-scale turbulence and radiative field, fall-out of the ice phase or wind shear. For this reason, the proper handling of cirrus life cycles is not an easy task using a large-scale model alone. We present some results from a small-scale cirrus cloud model initialized by ECMWF first-guess data, which prove more convenient for this task than the analyzed ones. This model is Starr’s 2-D cirrus cloud model, where the rate of ice production/destruction is parametrized from environmental data. Comparison with satellite and local observations during the ICE89 experiment (North Sea) shows that such an efficient model using large-scale data as input provides a reasonable diagnosis of cirrus occurrence in a given meteorological field. The main driving features are the updraft provided by the large-scale model, which enhances or inhibits the cloud development according to its sign, and the water vapour availability. The cloud fields retrieved are compared to satellite imagery. Finally, the use of a small-scale model in large-scale numerical studies is examined.     

Correlation between clouds at different altitudes and solar activity: Fact or Artifact?

Studies of the relation between cosmic rays (CR) (solar activity) and atmospheric cloudiness are mostly based on the satellite ISCCP cloud data. However, doubts have been cast that these relations can be an artifact of instrumental effects, i.e., of the masking/obscuring low clouds by higher clouds in the satellite view. If this is the case, most of the earlier results based on ISCCP data would be devaluated. Here, we reanalyze the ISCCP cloud coverage data and its relation with the cosmic ray-induced ionization, and show that the correlation between low clouds and CR is affected by higher clouds in some geographical regions, but not everywhere. In turn, our results show that low clouds also may affect the relation of higher clouds with CR in some regions. Accordingly, correlation analysis can be performed only when the strong relation between clouds of different types is taken into account. In particular, studies based on global or latitudinal (zonally averaged) cloud data should be revised.     

Near-real-time volcanic ash cloud detection: Experiences from the Alaska Volcano Observatory

Volcanic eruptions produce ash clouds, which are a major hazard to population centers and the aviation community. Within the North Pacific (NOPAC) region, there have been numerous volcanic ash clouds that have reached aviation routes. Others have closed airports and traveled for thousands of kilometers. Being able to detect these ash clouds and then provide an assessment of their potential movement is essential for hazard assessment and mitigation. Remote sensing satellite data, through the reverse absorption or split window method, is used to detect these volcanic ash clouds, with a negative signal produced from spectrally semi-transparent ash clouds. Single channel satellite is used to detect the early eruption spectrally opaque ash clouds. Volcanic Ash Transport and Dispersion (VATD) models are used to provide a forecast of the ash clouds' future location. The Alaska Volcano Observatory (AVO) remote sensing ash detection system automatically analyzes satellite data of volcanic ash clouds, detecting new ash clouds and also providing alerts, both email and text, to those with AVO. However, there are also non-volcanic related features across the NOPAC region that can produce a negative signal. These can complicate alerts and warning of impending ash clouds. Discussions and examples are shown of these non-volcanic features and some analysis is provided on how these features can be discriminated from volcanic ash clouds. Finally, there is discussion on how information of the ash cloud such as location, particle size and concentrations, could be used as VATD model initialization. These model forecasts could then provide an improved assessment of the clouds' future movement.     

Identification of eruption clouds with the landsat satellites

Landsat satellite images were selected for the analysis of a tephraladen eruption cloud and a volcanic fume cloud. A 35 km long eruption plume from Sakurazima Volcano, Kyushu, Japan was viewed by the satellite on December 2, 1972. Multispectral Scanner (MSS) band 4 was density sliced into eight levels. Grey levels over the tephra-laden cumulus, which had formed at the terminus of the eruption plume, were distinct from most of the nearby cumulus clouds. MSS band 4 is the key band for identifying eruption clouds in overcast volcanic regions. A lume cloud from Stromboli, Italy was studied in the same manner. It is easily identified over land areas and for 8 km over water in areas of clear sky, but cannot be distinguished from banks of cumulus clouds.     

Comparison between satellite and in situ sea surface temperature data in the Western Mediterranean Sea

A comparison between in situ and satellite sea surface temperature (SST) is presented for the Western Mediterranean Sea during 1999. Several international databases are used to extract in situ data (World Ocean Database, MEDAR/Medatlas, Coriolis Data Center, International Council for the Exploration of the Sea and International Comprehensive Ocean-Atmosphere Data Set). The in situ data are classified into different platforms or sensors (conductivity–temperature–depth, expendable bathythermographs, drifters, bottles, and ships), in order to assess the relative accuracy of these type of data with respect to Advanced Very High Resolution Radiometer SST satellite data. It is shown that the results of the error assessment vary with the sensor type, the depth of the in situ measurements, and the database used. Ship data are the most heterogeneous data set, and therefore present the largest differences with respect to in situ data. A cold bias is detected in drifter data. The differences between satellite and in situ data are not normally distributed. However, several analysis techniques, as merging and data assimilation, usually require Gaussian-distributed errors. The statistics obtained during this study will be used in future work to merge the in situ and satellite data sets into one unique estimation of the SST.     

卫星-地基-模式统一的自动观测云分类原则和标准的研究

随着空基、地基云状观测自动化进程的推进,国际通用的人工观测云分类标准不再适用于自动观测.本文提出了适用于自动观测的卫星观测、地基观测和数值预报模式统一的云分类原则和分类标准,依据大气代表性原则、仪器观测可行性原则、历史继承性原则和可扩展性原则,不考虑云的高度,沿用形态学和发生学理论,将云分为卷云、层状云、波状云和积状云4属,更细分为薄卷云、密卷云、波云、雨波云、层云、雨层云、浅积云和深积云8类,列出了各类云特征的定性描述,为自动观测、预报保障和模式评估提供参考.     

A review of the estimation of downward surface shortwave radiation based on satellite data: Methods,progress and problems

The estimation of downward surface shortwave radiation(DSSR) is important for the Earth's energy budget and climate change studies. This review was organised from the perspectives of satellite sensors, algorithms and future trends,retrospects and summaries of the satellite-based retrieval methods of DSSR that have been developed over the past 10 years. The shortwave radiation reaching the Earth's surface is affected by both atmospheric and land surface parameters. In recent years,studies have given detailed considerations to the factors which affect DSSR. It is important to improve the retrieval accuracy of cloud microphysical parameters and aerosols and to reduce the uncertainties caused by complex topographies and high-albedo surfaces(such as snow-covered areas) on DSSR estimation. This review classified DSSR retrieval methods into four categories:empirical, parameterisation, look-up table and machine-learning methods, and evaluated their advantages, disadvantages and accuracy. Further efforts are needed to improve the calculation accuracy of atmospheric parameters such as cloud, haze, water vapor and other land surface parameters such as albedo of complex terrain and bright surface, organically combine machine learning and other methods, use the new-generation geostationary satellite and polar orbit satellite data to produce highresolution DSSR products, and promote the application of radiation products in hydrological and climate models.     

Impact of Doppler Radar Wind in Simulating the Intensity and Propagation of Rainbands Associated with Mesoscale Convective Complexes Using MM5-3DVAR System

Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.     

偏振激光雷达探测的北京地区云的统计特性分析

本文给出了CALIPSO卫星偏振激光雷达自2006年6月至2010年3月间探测的北京地区大气云层的统计特性,并根据理论研究结果对激光雷达探测的云进行了分类,当云的温度低于0℃时发现了过冷水的存在.统计结果表明:温度在0℃以上时,大气中的云大部分为水云;温度在0℃至-25℃之间时,大气中会有过冷水和水平导向的片状晶体的冰...     

An estimate of the suspended particulate matter (SPM) transport in the southern North Sea using SeaWiFS images,in situ measurements and numerical model results

A study is presented where satellite images (SeaWiFS), in situ measurements (tidal cycle and snapshot) and a 2D hydrodynamic numerical model have been combined to calculate the long term SPM (Suspended Particulate Matter) transport through the Dover Strait and in the southern North Sea. The total amount of SPM supplied to the North Sea through the Dover Strait is estimated to be 31.74×10⁶ t. The satellite images provide synoptic views of SPM concentration distribution but do not take away the uncertainty of SPM transport calculation. This is due to the fact that SPM concentration varies as a function of tide, wind, spring-neap tidal cycles and seasons. The short term variations (tidal, spring-neap tidal cycle) have not been found in the satellite images, however seasonal variations are clearly visible. Furthermore the SPM concentration in the satellite images is generally lower than in the in situ measurements. The representativness of SPM concentration maps derived from satellites for calculating long term transports has therefore been investigated by comparing the SPM concentration variability from the in situ measurements with those of the remote sensing data. The most important constraints of satellite images are related to the fact that satellite data is evidence of clear sky conditions, whereas in situ measurements from a vessel can be carried out also during rougher meteorological conditions and that due to the too low time resolution of the satellite images the SPM concentration peaks are often missed. It is underlined that SPM concentration measurements should be carried out during at least one tidal cycle in high turbidity areas to obtain representative values of SPM concentration.     

Cosmic Rays and Climate

Among the most puzzling questions in climate change is that of solar-climate variability, which has attracted the attention of scientists for more than two centuries. Until recently, even the existence of solar-climate variability has been controversial—perhaps because the observations had largely involved correlations between climate and the sunspot cycle that had persisted for only a few decades. Over the last few years, however, diverse reconstructions of past climate change have revealed clear associations with cosmic ray variations recorded in cosmogenic isotope archives, providing persuasive evidence for solar or cosmic ray forcing of the climate. However, despite the increasing evidence of its importance, solar-climate variability is likely to remain controversial until a physical mechanism is established. Although this remains a mystery, observations suggest that cloud cover may be influenced by cosmic rays, which are modulated by the solar wind and, on longer time scales, by the geomagnetic field and by the galactic environment of Earth. Two different classes of microphysical mechanisms have been proposed to connect cosmic rays with clouds: firstly, an influence of cosmic rays on the production of cloud condensation nuclei and, secondly, an influence of cosmic rays on the global electrical circuit in the atmosphere and, in turn, on ice nucleation and other cloud microphysical processes. Considerable progress on understanding ion–aerosol–cloud processes has been made in recent years, and the results are suggestive of a physically-plausible link between cosmic rays, clouds and climate. However, a concerted effort is now required to carry out definitive laboratory measurements of the fundamental physical and chemical processes involved, and to evaluate their climatic significance with dedicated field observations and modelling studies.     

The dynamics and thermodynamics of precipitation loading

A one-dimensional, time-dependent numerical cloud model is used to analyze the factors in the dynamic and thermodynamic equations which lead to a steady-state or nonsteady-state solution for the cloud vertical motion, buoyancy, precipitation, and cloud water fields. ‘Bulk water’ microphysical techniques are used for the cloud, rain, and hail variables. An atmospheric sounding from a severe storm situation is used as initial and environmental conditions, yielding model updrafts of 40 m sec^?1 maximum and more than 10 m sec^?1 over the entire cloud region. ‘Early conversion’ of the cloud water to rain leads to loading of lower portions of the updraft by rain, the formation of appreciable amounts of hail by freezing of the supercooled rain, and subsequent loading of the middle and upper portions of the updraft so that the updraft erodes throughout the cloud depth and the cloud dissipates, yielding a vigorous rain shower. A delay in the conversion of the cloud water to rain results in a steady-state solution, no rain or hail falling through the updraft. A two-dimensional cloud simulation of this same case shows rain and hail in the upper cloud regions recycled in the two-dimensional flow into the updraft near cloud base and a breakdown of the updraft with resultant rainout (negligible hail reaching the ground). The breakdown of the updraft has profound effects on the temperature field within the cloud, causing the lapse rate to deviate from the steady-state condition and approach the initial environmental conditions. The results emphasize the fact that the local change in temperature (and other dependent variables as well) is not independent of the vertical velocity, in general. This has implications for the interpretation of measurements made within clouds.     

A method for solving relative dispersion of the cloud droplet spectra

The relative dispersion of the cloud droplet spectra or the shape parameter is usually assumed to be a constant in the two-parameter cloud microphysical scheme, or is derived through statistical analysis. However, observations have revealed that the use of such methods is not applicable for all actual cases. In this study, formulas were derived based on cloud microphysics and the properties of gamma function to solve the average cloud droplet radius and the cloud droplet spectral shape parameter. The gamma distribution shape parameter, relative dispersion, and cloud droplet spectral distribution can be derived through solving the droplet spectral shape parameter equation using the average droplet radius, volume radius, and their ratio, thereby deriving an analytic solution. We further examined the equation for the droplet spectral shape parameter using the observational droplet spectral data, and results revealed the feasibility of the method. In addition, when the method was applied to the two-parameter cloud microphysical scheme of the Weather Research and Forecast(WRF) model to further examine its feasibility, the modeling results showed that it improved precipitation simulation performance, thereby indicating that it can be utilized in two-parameter cloud microphysical schemes.