Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. The vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m-2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10-20 g m-2.

Improving weather and climate prediction with better representation of fast processes in atmospheric models Many atmospheric processes that influence Earth’s weather and climate occur at spatiotemporal scales that are too small to be resolved in large scale models. They must be parameterized, which means approximately representing them by variables that can be resolved by model grids. Fast Processes in Large-Scale Atmospheric Models: Progress, Challenges and Opportunities explores ways to better investigate and represent multiple parameterized processes in models and thus improve their ability to make accurate climate and weather predictions. Volume highlights include: Historical development of the parameterization of fast processes in numerical models Different types of major sub-grid processes and their parameterizations Efforts to unify the treatment of individual processes and their interactions Top-down versus bottom-up approaches across multiple scales Measurement techniques, observational studies, and frameworks for model evaluation Emerging challenges, new opportunities, and future research directions The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

"Low-level stratiform clouds remain one of the wildcards in future climate simulations. Despite their important role in the earth's radiation budget and the large number of dedicated field campaigns, several cloud-scale processes in marine stratocumulus clouds remain misrepresented. The 19-month-long deployment of the Atmospheric Radiation Measurement Program Mobile Facility in the Azores provided the longest and most comprehensive ground-based observational dataset of marine boundary layer clouds to date. The first objective of this project was the documentation of the frequency of occurrence of different cloud and precipitation systems in the Azores using a combination of passive and active measurements. The analysis indicates that, even though clouds were often observed (close to 80 % of the time), especially in the boundary layer (~50 %), a single-layer stratocumulus coverage rarely persisted more than a day. In fact, many stratocumulus clouds were observed to have cumulus clouds underneath them. This is linked to the nearly constant decoupled state of the boundary layer in the Azores, contrary to what has been observed in the Pacific decks. 35 cases of mostly single-layer persisting stratocumulus coverage were selected for further analysis. Results include similarities with other studies (e.g., maximum coverage at night, thicker clouds needed to drizzle, and importance of cloud-top radiative cooling at night), as well as differences (e.g., coherent structures account for a smaller fraction of the updraft mass flux). The second objective of this project was to revisit the detection of drizzle-size particles in stratocumulus clouds using radar observations. First, the cloud and drizzle size distributions are related theoretically to the radar measurements, including the effects of the dynamics. Then, a forward radar Doppler spectra model was developed to test the sensitivity of the radar measurements to modifications of the drizzle contribution. Finally, a simple 1-D steady-state model was exploited to simulate drizzle growth as it falls in a cloud, using the forward model to link the output back to the radar observations. Using that combination of models, some observed features of the drizzle evolution inside continental and maritime stratocumulus clouds were successfully investigated. Overall, it was found that the skewness of a radar Doppler spectrum is a good indicator of the presence of early drizzle droplets, while a reflectivity or Doppler velocity threshold indicates the change in dominance in the Doppler spectrum occurring when drizzle is well developed. The third and final objective of this project was to revisit another long-standing challenge: the retrieval of cloud microphysical properties using a combination of radar-radiometer measurements. A new technique was developed to retrieve the cloud particle size distribution in stratocumulus clouds, adding a microphysical condensational model under steady-state supersaturation conditions to a common retrieval method. The results appear reasonable in two nondrizzling marine stratocumulus clouds, and the derived cloud optical depth compares well with the one derived independently with another instrument. The errors of the retrievals were also estimated, demonstrating the added value of the new technique." --

Marine stratocumulus clouds (Sc) cover large areas of the Earth and have a substantial impact on the Earth's radiative balance by reflecting copious amounts of sunlight away from the Earth and emitting longwave radiation at a temperature close to surface. Cloud and precipitation (drizzle) liquid water content (hereafter CLWC and PLWC) are two of the most important microphysical properties of Sc which directly affect radiative transfer and the hydrological cycle, as well as play a critical role in many microphysical and planetary boundary layer processes. It is thus crucial to determine CLWC and PLWC accurately. Sc in many global climate models (GCMs) are found to precipitate too frequently and too lightly which is likely due in part to the lack of information on the subgrid variability in CLWC and PLWC in the calculation of autoconversion and accretion rates. In most GCMs, the effects of subgrid variability have been either completely ignored or incorporated by multiplying the autoconversion and accretion rates (based on grid-mean values) by an enhancement factor to account for the subgrid variability. This dissertation aims to retrieve CLWC and PLWC jointly for Sc based on a millimeter wavelength radar, and to examine the nature of spatial variability in CLWC and PLWC and its impact on the autoconversion and accretion rates. In particular, we derive enhancement factors for autoconversion and accretion rates based on the radar observations, and examine how the enhancement factors change with different factors such as the length scale (size of a GCM grid) and the frequency of below-cloud precipitation. In the first part of the dissertation (Chapter 2), the CLWC and PLWC are retrieved based on a combination of retrieval techniques including a novel Doppler spectra decomposition method that separates Doppler spectra into a cloud and a precipitation component. The radar Doppler spectra data from a vertically pointing Ka-band cloud radar, along with total liquid water path from a three-channel microwave radiometer (MWR) and radiosonde measurements are used in the retrievals. These observational data in this study were collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site. At the scale of a single radar volume, the uncertainty of our retrieved PLWC is about an order of magnitude. By comparing to in-situ aircraft observations, we find on average they are in a good agreement. On the scale of one day, the uncertainty in the mean CLWC is estimated to be within 30% and the systematic errors in the mean PLWC are estimated to be less than 75%. In the second part of the dissertation (Chapter 3), the variability in CLWC and PLWC and its effects on the grid-mean autoconversion and accretion rates are examined, specifically enhancement factors for autoconversion rate (E[subscript]auto) and accretion rate (E[subscript]accr). In many studies (and model implementations) enhancement factors are formulated under the assumption that variability in cloud and precipitation mixing ratio (water content divided by the air density) can be represented by a bivariate lognormal distribution with three key parameters: (i) the fractional standard deviation of the cloud-water mixing ratio, (ii) the fractional standard deviation of precipitating water mixing ratio, and (iii) the (cross) correlation coefficient (between cloud and precipitation mixing ratio). Therefore, both the enhancement factors and these three parameters are evaluated. Overall, we find that while our retrieved joint distribution is not truly a bivariate lognormal, this framework nonetheless works well given the correct values for the three key parameters. In general, we find that E[subscript]auto and E[subscript]accr increase with grid size and have a maximum when precipitation fraction is about 0.4 - 0.6 (depending somewhat on how precipitation occurrence is defined and grid size). E[subscript]auto stays relatively unchanged due to the assumption made in the retrievals that CLWC increases linearly with height in the cloud. E[subscript]accr generally decreases from cloud base to cloud top although an increase in correlation of q[subscript]c and q[subscript]p and a decrease in the magnitude of the subgrid variability of q[subscript]p have some offsetting effects. In addition, we find that E[subscript]auto and E[subscript]accr have little if any correlations with relative humidity (RH), lower tropospheric stability (LTS), and mean liquid water path (LWP) or mean cloud thickness. However, they are highly correlated with variability in of LWP, cloud thickness and cloud base, suggesting that any knowledge in subgrid variability might be useful in predicting E[subscript]auto and E[subscript]accr.

This 2001 book provides a detailed introduction to the principles of Doppler and polarimetric radar, focusing in particular on their use in the analysis of weather systems. The design features and operation of practical radar systems are highlighted throughout the book in order to illustrate important theoretical foundations. The authors begin by discussing background topics such as electromagnetic scattering, polarization, and wave propagation. They then deal in detail with the engineering aspects of pulsed Doppler polarimetric radar, including the relevant signal theory, spectral estimation techniques, and noise considerations. They close by examining a range of key applications in meteorology and remote sensing. The book will be of great use to graduate students of electrical engineering and atmospheric science as well as to practitioners involved in the applications of polarimetric radar systems.

This book presents current applications of remote sensing techniques for clouds and precipitation for the benefit of students, educators, and scientists. It covers ground-based systems such as weather radars and spaceborne instruments on satellites. Measurements and modeling of precipitation are at the core of weather forecasting, and long-term observations of the cloud system are vital to improving atmospheric models and climate projections. The first section of the book focuses on the use of ground-based weather radars to observe and measure precipitation and to detect and forecast storms, thunderstorms, and tornadoes. It also discusses the observation of clouds using ground-based millimeter radar. The second part of the book concentrates on spaceborne remote sensing of clouds and precipitation. It includes cases from the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) mission, using satellite radars to observe precipitation systems. Then, the focus is on global cloud observations from the ClaudSat, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), including a perspective on the Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) satellite. It also addresses global atmospheric water vapor profiling for clear and cloudy conditions using microwave observations. The final part of this volume provides a perspective into advances in cloud modeling using remote sensing observations.

Retrievals of cloud optical and microphysical properties for boundary layer clouds, including those widely used by ASR investigators, frequently assume that clouds are sufficiently horizontally homogeneous that scattering and absorption (at all wavelengths) can be treated using one dimensional (1D) radiative transfer, and that differences in the field-of-view of different sensors are unimportant. Unfortunately, most boundary layer clouds are far from horizontally homogeneous, and numerous theoretical and observational studies show that the assumption of horizontal homogeneity leads to significant errors. The introduction of scanning cloud and precipitation radars at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program sites presents opportunities to move beyond the horizontally homogeneous assumption. The primary objective of this project was to develop a 3D retrieval for warm-phase (liquid only) boundary layer cloud microphysical properties, and to assess errors in current 1D (non-scanning) approaches. Specific research activities also involved examination of the diurnal cycle of hydrometeors as viewed by ARM cloud radar, and continued assessment of precipitation impacts on retrievals of cloud liquid water path using passive microwaves.