ENHANCEMENT OF ATMOSPHERIC LIQUID WATER ESTIMATION USING SPACE-BORNE REMOTE SENSING DATA

Clouds strongly affect the energy balance and water cycle, two dominant processes in the climate system. Low-level liquid clouds have the most significant influence on cloud radiative forcing due to their areal extent and frequency. Estimation of atmospheric liquid water contained in low-level clouds and the precipitation underneath them is very important in meteorology, hydrology, and climatology. Space-borne remote sensing data are widely used for global estimation of atmospheric liquid water, given that they have a wider spatial coverage than other data sources and are spanning many years. However, previous space-borne remote sensing techniques have some limitations for estimation of atmospheric liquid water in low-level liquid clouds, namely, the vertical variation of droplet effective radius (DER) is neglected in the calculation of cloud liquid water path (LWP) and the rain underneath low-level liquid clouds can be overlooked. Comprising many state-of-art passive and active instruments, the recently launched NASA A-Train series of satellites provides comprehensive simultaneous information about cloud and precipitation processes. Utilizing A-Train satellite data and ship-borne data from the East Pacific Investigation of Climate (EPIC) campaign, in this study investigated is the estimation of liquid water in low-level liquid clouds, and assessed is the potential of cloud microphysical parameters in the estimation of rain from low-level liquid clouds. This study demonstrates that assuming a constant cloud DER can cause biases in the calculation of LWP. It is also shown that accounting for the vertical variation of DER can reduce the mean biases. This study shows that DER generally increases with height in non-drizzling clouds, consistent with aircraft observations. It is found that in drizzling clouds, the vertical gradient of DER is significantly smaller than that in non-drizzling clouds, and it can become negative when the drizzle is heavier than approximately 0.1 mm hr-1. It is shown that the warm rain underneath low-level liquid clouds accounts for 45.0% of occurrences of rain and 27.5% of the rainfall amount over the global ocean areas. Passive microwave techniques underestimate the warm rain over oceans by nearly 48%. Among the cloud microphysical parameters, LWP calculated with DER profile shows the best potential for estimating warm rain, which is neglected by traditional techniques of precipitation estimation

Microphysical and macrophysical responses of marine stratocumulus polluted by underlying ships

2012 Summer.Includes bibliographical references.Multiple sensors flying in the A-train constellation of satellites were used to determine the extent to which aerosol plumes from ships passing below marine stratocumulus alter the microphysical and macrophysical properties of the clouds. Aerosol plumes generated by ships sometimes influence cloud microphysical properties (effective radius) and, to a largely undetermined extent, cloud macrophysical properties (liquid water path, coverage, depth, precipitation, and longevity). Aerosol indirect effects were brought into focus, using observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the 94-GHZ radar onboard CloudSat. To assess local cloud scale responses to aerosol, the locations of over one thousand ship tracks coinciding with the radar were meticulously logged by hand from the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. MODIS imagery was used to distinguish ship tracks that were embedded in closed, open, and unclassifiable mesoscale cellular cloud structures. The impact of aerosol on the microphysical cloud properties in both the closed and open cell regimes were consistent with the changes predicted by the Twomey hypothesis. For the macrophysical changes, differences in the sign and magnitude of these properties were observed between cloud regimes. The results demonstrate that the spatial extent of rainfall (rain cover fraction) and intensity decrease in the clouds contaminated by the ship plume compared to the ambient pristine clouds. Although reductions of precipitation were common amongst the clouds with detectable rainfall (72% of cases), a substantial fraction of ship tracks (28% of cases) exhibited the opposite response. The sign and strength of the response was tied to the type of stratocumulus (e.g., closed vs open cells), depth of the boundary layer, and humidity in the free-troposphere. When closed cellular clouds were identified, liquid water path, drizzle rate, and rain cover fraction (an average relative decrease of 61%) was significantly smaller in the ship-contaminated clouds. Differences in drizzle rate resulted primarily from the reductions in rain cover fraction (i.e., fewer pixels were identified with rain in the clouds polluted by the ship). The opposite occurred in the open cell regime. Ship plumes ingested into this regime resulted in significantly deeper and brighter clouds with higher liquid water amounts and rain rates. Enhanced rain rates (average relative increase of 89%) were primarily due to the changes in intensity (i.e., rain rates on the 1.1 km pixel scale were higher in the ship contaminated clouds) and, to a lesser extent, rain cover fraction. One implication for these differences is that the local aerosol indirect radiative forcing was more than five times larger for ship tracks observed in the open cell regime (-59 W m-2) compared to those identified in the closed cell regime (-12 W m-2). The results presented here underline the need to consider the mesoscale structure of stratocumulus when examining the cloud dynamic response to changes in aerosol concentration. In the final part of the dissertation, the focus shifted to the climate scale to examine the impact of shipping on the Earth's radiation budget. Two studies were employed, in the first; changes to the radiative properties of boundary layer clouds (i.e., cloud top heights less than 3 km) were examined in response to the substantial decreases in ship traffic that resulted from the recent world economic recession in 2008. Differences in the annually averaged droplet effective radius and top of atmosphere outgoing shortwave radiative flux between 2007 and 2009 did not manifest as a clear response in the climate system and, was probably masked either due to competing aerosol cloud feedbacks or by interannual climate variability. In the second study, a method was developed to estimate the radiative forcing from shipping by convolving lanes of densely populated ships onto the global distributions of closed and open cell stratocumulus clouds. Closed cells were observed more than twice as often as open cells. Despite the smaller abundance of open cells, a significant portion of the radiative forcing from shipping was claimed by this regime. On the whole, the global radiative forcing from ship tracks was small (approximately -0.45 mW m-2) compared to the radiative forcing associated with the atmospheric buildup of anthropogenic CO2

Identification of precipitation onset based on Cloudsat observations

AbstractObservations of cloud vertical structure by Cloud Profiling Radar on CloudSat satellite provide a unique opportunity to globally identify the onset of precipitation. In this study, based on a conceptual model for an adiabatic cloud, a new method to determine the onset of precipitation in marine warm clouds is developed. The new method uses the slope of radar reflectivities near the cloud top, which gradually reverses its signs as drizzle occurs. By analyzing multiyear CloudSat data, it is found that globally the radar reflectivity threshold for precipitation onset varies from −18 to −13dBZ with an average value of −16dBZ. The corresponding liquid water path threshold for precipitation onset is also studied by analyzing satellite microwave observations collocated with CloudSat data. Results show that the liquid water path threshold is 190gm−2 as a global mean, varying from 150 to over 300gm−2 depending on regions

Investigating Aerosol Effects on Clouds, Precipitation and Regional Climate in US and China by Means of Ground-based and Satellite Observations and a Global Climate Model

Aerosols affect climate by scattering/absorbing radiation and by acting as cloud condensation nuclei (CCN) or ice nuclei (IN). One of the least understood but most significant aspects of climate change is the aerosol effect on cloud and precipitation. A hypothesis has recently been proposed that, in addition to reducing cloud effective radius and suppressing precipitation, aerosols may also modify the thermodynamic structure of deep convective clouds and lead to enhanced precipitation when complex thermodynamic processes are involved. Taking advantage of the long-term and extensive ground-based observations at the US Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, we thoroughly tested such a hypothesis and provide direct evidence of it. Moreover, the hypothesis is also supported by analysis of satellite-based observations over tropical regions from multiple sensors in the A-Train satellites constellation. Extensive analyses of the long-term ground-based and large-scale data reveal significant increases in rain rate or frequency and cloud top heights with increasing aerosol loading for mix-phase deep convective clouds, decreases rain frequency for low liquid clouds, but little impact on cloud height for liquid clouds. Rigorous tests are conducted to investigate any potential artifacts and influences of meteorological conditions. Large-scale circulation patterns and monsoon systems can be changed by scattering and absorption of solar radiation by aerosols. By means of model simulations with the National Center for Atmospheric Research Community Climate Model (NCAR/CCM3), we found that the increase of aerosol loading in China contributes to circulation changes, leading to more frequent occurrence of fog events in winter as observed from meteorological records. The increase in atmospheric aerosols over China heats the atmosphere and generates a cyclonic circulation anomaly over eastern-central China. This circulation anomaly leads to a reduction in the influx of dry and cold air over that area during winter. Weakening of the East Asian winter monsoon system may also contribute to these changes. All these changes favor the formation and maintenance of fog over this region. The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol products used in the above studies are validated using ground-based measurements from the Chinese Sun Hazemeter Network (CSHNET). Overall, substantial improvement was found in the current version of aerosol products relative to the previous one. At individual sites, the improvement varies with surface and atmospheric conditions

Doctor of Philosophy

dissertationMany studies have examined both the modeling and observational aspects of aerosol-cloud interactions. The effect of the surrounding environment on individual clouds makes it difficult to isolate the signal of invigoration or suppression by aerosols, particularly at larger spatial and temporal scales. This study uses observations from the Tropical Rainfall Measuring Mission (TRMM), CloudSat, and Aqua satellites to identify convective clouds systems in clean and dirty environments. The MODerate Resolution Imaging Spectroradiometer (MODIS) aerosol index is collocated with radar precipitation features (RPFs) from TRMM and congestus cloud features (CFs) from CloudSat. Congestus clouds are also defined using Visible and Infrared Scanner (VIRS) infrared brightness temperature and radar-detected surface rainfall from 14 years of TRMM data. Using these definitions, the regional and seasonal variations of the population of congestus are presented globally. General differences are found between the properties of congestus over land and over ocean, especially the shapes of congestus. Ocean congestus are more bell-shaped, while land congestus tend to have flatter sides and larger area above the freezing level. This population of congestus is then used to examine the characteristics of clouds occurring in clean and dirty environments in different parts of the world. The ERA-Interim, which is paired with RPFs and CFs, is used to examine the environment in which these clouds occur. Aerosols are found to have different effects on clouds in different parts of the world. In some regions, such as Africa, environmental differences could possibly explain "invigoration" that has been attributed to aerosol effects. In other regions, such as the Amazon, environmental differences between clean and dirty cloud features remain small, indicating that aerosols could be causing at least part of the observed differences in cloud properties. Differences in clean and dirty congestus are very small and are limited to differences in the profiles of maximum reflectivity. The signal of the aerosol indirect effect is so small that it is very difficult to detect confidently using these methods. The environment must be considered in any study of the aerosol indirect effect, as important environmental changes can occur as aerosols are introduced to an air mass

A machine learning based 24-h-technique for an area-wide rainfall retrieval using MSG SEVIRI data over Central Europe

The aim of the present study was to develop a 24-h-technique for the process-related and quantitative estimation of precipitation in connection with extra-tropical cyclones in the mid-latitudes based on MSG SEVIRI data using the machine learning algorithm random forest. The algorithms and approaches needed were successfully developed and implemented within three working packages: (WP1) The cloud property retrieval SLALOM, first developed for Terra MODIS, was successfully transferred and adapted to the specific requirements of the SEVIRI system and an extensive validation study was carried out. The cloud optical properties retrieved by SLALOM, namely cloud effective radius and cloud optical thickness that were needed for satellitebased rainfall estimation in WP2 and WP3, were compared against the well known and validated NASA MODIS cloud property product (MODIS 06) as well as the cloud optical depth product (2B-TAU) of CloudSat. The suitability of SLALOM has been shown over the North Atlantic and over the European continent (chapter 3). (WP2) A new 24-h-technique for rainfall rate assignment was developed for MSG SEVIRI using the machine learning algorithm random forest as fundamental prediction algorithm. Based on the precipitation processes in connection with extra-tropical cyclones, rainfall rates were assigned to advectivestratiform and convective precipitating areas by means of individual RF models. As predictor variables for the RF models satellite-based information on cloud top height, cloud top temperature, cloud phase and cloud water path were chosen. The different illumination conditions (daytime, twilight and night-time) were taken into account with a proper SEVIRI spectral channel selection as surrogates for theses cloud physical parameters. The development was realised in three steps: First, an extensive tuning study was carried out to customise each of the RF models. Secondly, the RF models were trained using the optimum model parameter values found in the tuning study. Finally, the final RF models were used to predict rainfall rates using an independent validation data set and the results were validated against co-located rainfall rates observed by the RADOLAN RW product of the DWD. The outstanding validation results during all times of the day confirmed the ability of RF as tool for the rainfall rate assignment technique from MSG SEVIRI data (chapter 4). (WP3) A new coherent daytime, twilight and night-time rainfall retrieval was developed for MSG SEVIRI. The technique aims to retrieve rainfall rates for precipitation events in connection with extra-tropical cyclones in the midlatitudes in a continuous manner resulting in a 24 hour prediction. Based on the dominant precipitation processes, the proposed rainfall retrieval consists of three steps which are applied consecutively by means of individual RF models to get the final product: (i) Identification of precipitating cloud areas. (ii) Separation of precipitating areas into predominately convective and advective-stratiform cloud regions. (iii) Individual process-oriented assignment of rainfall rates to these cloud areas. Again, the relationship between cloud top temperature, cloud top height, cloud water path and cloud phase was used to retrieve information about precipitation and according to the illumination conditions, a suitable selection of the predictor variables were taken into account as input to the RF models (chapter 5). The newly developed rainfall retrieval technique was tested in an extensive validation study over Germany using the radar-based RADOLAN RW product as reference data. The validation results show reliable performance of the new technique concerning rain area detection, rain process separation as well as rainfall rate assignment during all times of the day which enables the estimation of precipitation for 24 hours of a day. Hereby, the twilight applicability of the technique as well as good rainfall rate prediction performances even on an hourly basis are particularly remarkable and set this study apart from other rainfall retrievals. For the first time, a 24-h precipitation monitoring becomes possible for precipitating clouds of not only convective but also of advective-stratiform character, opening many areas of application

Cloud Occurrences and Cloud Radiative Effects (CREs) from CCCM and CloudSat Radar-Lidar (RL) Products

Two kinds of radar-lidar synergy cloud products are compared and analyzed in this study; CERES-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar (RL) product such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF LIDAR, CCCM has more low-level ( 40). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar, which may be related to precipitation. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found over three regions. First, CCCM has larger shortwave (SW) and longwave (LW) CREs than FXLHR-LIDAR along the west coasts of Africa and America. This might be caused by missing small-scale marine boundary layer clouds in FLXHR-LIDAR. Second, over tropical oceans where precipitation frequently occurs, SW and LW CREs from FLXHR-LIDAR are larger than those from CCCM partly because FLXHR-LIDAR algorithm includes the contribution of rainwater to total liquid water path. Third, over midlatitude storm-track regions, CCCM shows larger SW and LW CREs than FLXHR-LIDAR, due to CCCM biases caused by larger cloud optical depth or higher cloud effective height

Cumulo: A Dataset for Learning Cloud Classes

One of the greatest sources of uncertainty in future climate projections comes from limitations in modelling clouds and in understanding how different cloud types interact with the climate system. A key first step in reducing this uncertainty is to accurately classify cloud types at high spatial and temporal resolution. In this paper, we introduce Cumulo, a benchmark dataset for training and evaluating global cloud classification models. It consists of one year of 1km resolution MODIS hyperspectral imagery merged with pixel-width 'tracks' of CloudSat cloud labels. Bringing these complementary datasets together is a crucial first step, enabling the Machine-Learning community to develop innovative new techniques which could greatly benefit the Climate community. To showcase Cumulo, we provide baseline performance analysis using an invertible flow generative model (IResNet), which further allows us to discover new sub-classes for a given cloud class by exploring the latent space. To compare methods, we introduce a set of evaluation criteria, to identify models that are not only accurate, but also physically-realistic. CUMULO can be download from https://www.dropbox.com/sh/6gca7f0mb3b0ikz/AADq2lk4u7k961Qa31FwIDEpa?dl=0

Ice microphysical processes exert a strong control on the simulated radiative energy budget in the tropics

Simulations of the global climate system at storm-resolving resolutions of 2 km are now becoming feasible and show promising realism in clouds and precipitation. However, shortcomings in their representation of microscale processes, like the interaction of cloud droplets and ice crystals with radiation, can still restrict their utility. Here, we illustrate how changes to the ice microphysics scheme dramatically alter both the vertical profile of cloud-radiative heating and top-of-atmosphere outgoing longwave radiation (terrestrial infrared cooling) in storm-resolving simulations over the Asian monsoon region. Poorly-constrained parameters in the ice nucleation scheme, overactive conversion of ice to snow, and inconsistent treatment of ice crystal effective radius between microphysics and radiation alter cloud-radiative heating by a factor of four and domain-mean infrared cooling by 30 W m−2. Vertical resolution, on the other hand, has a very limited impact. Even in state-of-the-art models then, uncertainties in microscale cloud properties exert a strong control on the radiative budget that propagates to both atmospheric circulation and regional climate. These uncertainties need to be reduced to realize the full potential of storm-resolving models