Chuanfeng Zhao

Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-Based Measurements

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Aerosol and Monsoon Climate Interactions over Asia

The 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.

Sensitivity of CAM5-Simulated Arctic Clouds and Radiation to Ice Nucleation Parameterization

AbstractSensitivity of Arctic clouds and radiation in the Community Atmospheric Model, version 5, to the ice nucleation process is examined by testing a new physically based ice nucleation scheme that links the variation of ice nuclei (IN) number concentration to aerosol properties. The default scheme parameterizes the IN concentration simply as a function of ice supersaturation. The new scheme leads to a significant reduction in simulated IN concentration at all latitudes while changes in cloud amounts and properties are mainly seen at high- and midlatitude storm tracks. In the Arctic, there is a considerable increase in midlevel clouds and a decrease in low-level clouds, which result from the complex interaction among the cloud macrophysics, microphysics, and large-scale environment. The smaller IN concentrations result in an increase in liquid water path and a decrease in ice water path caused by the slowdown of the Bergeron–Findeisen process in mixed-phase clouds. Overall, there is an increase in the ...

Intensification of aerosol pollution associated with its feedback with surface solar radiation and winds in Beijing

Beijing has been experiencing serious air pollution in recent years, resulting in serious impacts on the local environment and climate and on human health. In addition to individual pollution sources and weather systems, feedback between aerosols and downwelling solar radiation (DSR) and between aerosols and winds also contribute to heavy aerosol pollution. By using atmospheric visibility (VIS) to represent the relative amount of aerosol pollution during a 5 week observation around the Asia-Pacific Economic Cooperation (APEC) period (22 October to 25 November 2014) over a site in south Beijing, China, we show clear positive relationships between DSR and VIS and between winds and VIS. The sensitivities of daily DSR and surface winds to VIS are approximately 15.42 W/m2/km and 0.068 m/s/km, respectively. The strengthening contributions to atmospheric visibility by surface DSR-VIS interactions and between surface wind-aerosol interactions are estimated at approximately 15% and 12%, respectively, in south Beijing around the APEC period.

A new cloud and aerosol layer detection method based on micropulse lidar measurements

This paper introduces a new algorithm to detect aerosols and clouds based on micropulse lidar measurements. A semidiscretization processing technique is first used to inhibit the impact of increasing noise with distance. The value distribution equalization method which reduces the magnitude of signal variations with distance is then introduced. Combined with empirical threshold values, we determine if the signal waves indicate clouds or aerosols. This method can separate clouds and aerosols with high accuracy, although differentiation between aerosols and clouds are subject to more uncertainties depending on the thresholds selected. Compared with the existing Atmospheric Radiation Measurement program lidar-based cloud product, the new method appears more reliable and detects more clouds with high bases. The algorithm is applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu sites. At the SGP site, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring and shows bimodal vertical distributions with maximum occurrences at around 3–6 km and 8–12 km. The annual averaged cloud frequency is about 50%. The dominant clouds are stratiform in winter and convective in summer. By contrast, the cloud frequency at the Taihu site shows no clear seasonal variation and the maximum occurrence is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at the SGP site. A seasonal analysis of cloud base occurrence frequency suggests that stratiform clouds dominate at the Taihu site.

Quantifying uncertainties of cloud microphysical property retrievals with a perturbation method

Quantifying the uncertainty of cloud retrievals is an emerging topic important for both cloud process studies and modeling studies. This paper presents a general approach to estimate uncertainties in ground-based retrievals of cloud properties. This approach, called the perturbation method, quantifies the cloud retrieval uncertainties by perturbing the cloud retrieval influential factors (like inputs and parameters) within their error ranges. The error ranges for the cloud retrieval inputs and parameters are determined by either instrument limitations or comparisons against aircraft observations. With the knowledge from observations and the retrieval algorithms, the perturbation method can provide an estimate of the cloud retrieval uncertainties, regardless of the complexity (like nonlinearity) of the retrieval algorithm. The relative contribution to the uncertainties of retrieved cloud properties from the inputs, assumptions, and parameterizations can also be assessed with this perturbation method. As an example, we apply this approach to the Atmospheric Radiation Measurement Program baseline retrieval, MICROBASE. Only nonprecipitating single-phase (liquid or ice) clouds have been examined in this study. Results reveal that different influential factors play the dominant contributing role to the uncertainties of different cloud properties. To reduce uncertainties in cloud retrievals, future efforts should be emphasized on the major contributing factors for considered cloud properties. This study also shows high sensitivity of cloud retrieval uncertainties to different cloud types, with the largest uncertainties for deep convective clouds. Limitations and further efforts for this uncertainty quantification method are discussed.

Can MODIS cloud fraction fully represent the diurnal and seasonal variations at DOE ARM SGP and Manus sites

Though cloud fraction (CF) from Moderate Resolution Imaging Spectroradiometer (MODIS) has been widely used, it remains unclear whether it can fully represent the diurnal variations. This study evaluates the time representation (i.e. satellite passes’ mean value per day to represent daily average value) error in MODIS CF by using day-time-only total sky cover (TSC) and continuous day-and-night radar/lidar CF (Active Remote Sensing of Clouds product, ARSCL) from 2000 to 2010 for two Atmospheric Radiation Measurement (ARM) program climate regime sites of Southern Great Plains (SGP) and Manus. By comparing the daily averaged CFs from ARSCL between using all hourly and using the MODIS-passing-time observations, it shows a correlation coefficient of 0.93 (0.88) and Root Mean Square Deviation (RMSD) of 12.68% (13.27%) over SGP (Manus) site for daily averaged CFs. Differently, it shows a better correlation coefficient of 0.97 (0.97) and smaller RMSD of 2.98% (3.97%) over SGP (Manus) site for monthly averaged CFs. These suggest that considerable errors could be introduced while using the MODIS CF observed at several fixed time points a day to represent average CF at different time scales. Monthly time representation errors have also been evaluated for day time only and night time only, which show even larger values. A further analysis shows that uncertainties caused by the time representation account for about 23% (21%) of the total differences between surface and MODIS CFs over SGP (Manus) site at monthly time scale.

Opposite effects of absorbing aerosols on the retrievals of cloud optical depth from spaceborne and ground‐based measurements

Absorbing aerosols above or within cloud layers have drawn much attention in recent years due to substantially enhanced absorption of solar radiation that may affect reflection at the top of the atmosphere. The retrieval of cloud properties is usually conducted without any regard to aerosols. This study illustrates that retrievals of cloud optical depth (τc) from spaceborne and ground-based sensors are both affected by such aerosols and lead to opposite biases. A ground-based retrieval algorithm is developed for the simultaneous retrieval of τc and cloud droplet effective radius using spectral irradiance measurements from a multifilter rotating spectroradiometer and liquid water path (LWP) data from a microwave radiometer deployed in China. The algorithm is applied to data acquired from 17 May 2008 to 12 May 2009 at a heavily polluted site in the heart of the Yangtze delta region in China. The ground-based retrieval of cloud droplet effective radius increases with increasing LWP. Moderate Resolution Imaging Spectroradiometer retrievals tend to overestimate (underestimate) LWP when cloud LWP is less (greater) than about 200 g/m2. Model tests show strong sensitivities to the retrieval of τc from ground and spaceborne sensors under varying absorption, loading, and vertical distribution conditions. For absorbing aerosol mixed with cloud, τc tends to be underestimated from space, but overestimated from the ground, leading to very poor agreement between ground-based and Moderate Resolution Imaging Spectroradiometer retrievals. Their differences increase with increasing τc. This finding suggests that in a turbid atmosphere with absorbing aerosols, the aerosol effect should be considered, or it would mislead any validation using satellite and ground-based retrievals.

Toward Understanding the Properties of High Ice Clouds at the Naqu Site on the Tibetan Plateau Using Ground-Based Active Remote Sensing Measurements Obtained during a Short Period in July 2014

AbstractThis study describes the microphysical properties of high ice clouds (with bases above 5 km) using ground-based millimeter cloud radar cirrus-mode observations over the Naqu site of the Tibetan Plateau (TP) during a short period from 6 to 31 July 2014. Empirical regression equations are applied for the cloud retrievals in which the parameters are given on the basis of a review of existing literature. The results show a unimodal distribution for the cloud ice effective radius re and ice water content with maximum frequencies around 36 μm and 0.001 g m−3, respectively. Analysis shows that clouds with high ice re are more likely to occur at times from late afternoon until nighttime. The clouds with large (small) re mainly occur at low (high) heights and are likely orographic cumulus or stratocumulus (thin cirrus). Further analysis indicates that ice re decreases with increasing height and shows strong positive relationships between ice re (μm) and depth h (m), with a regression equation of re = 35.45...

Application and Evaluation of an Explicit Prognostic Cloud‐Cover Scheme in GRAPES Global Forecast System

An explicit prognostic cloud‐cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle‐range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud‐cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large‐scale stratiform condensation processes. Our simulation results show that clouds in mid‐high latitudes arise mainly from large‐scale stratiform condensation processes, while cumulus convection and large‐scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA‐Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud‐cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.