An assessment of aerosol‐cloud interactions in marine stratus clouds based on surface remote sensing

An assessment of aerosol-cloud interactions (ACI) from ground-based remote sensing under coastal stratiform clouds is presented. The assessment utilizes a long-term, high temporal resolution data set from the Atmospheric Radiation Measurement (ARM) Program deployment at Pt. Reyes, California, United States, in 2005 to provide statistically robust measures of ACI and to characterize the variability of the measures based on variability in environmental conditions and observational approaches. The average ACIN (= dlnNd/dlna, the change in cloud drop number concentration with aerosol concentration) is 0.48, within a physically plausible range of 0–1.0. Values vary between 0.18 and 0.69 with dependence on (1) the assumption of constant cloud liquid water path (LWP), (2) the relative value of cloud LWP, (3) methods for retrieving Nd, (4) aerosol size distribution, (5) updraft velocity, and (6) the scale and resolution of observations. The sensitivity of the local, diurnally averaged radiative forcing to this variability in ACIN values, assuming an aerosol perturbation of 500 c-3 relative to a background concentration of 100 cm-3, ranges betwee-4 and -9 W -2. Further characterization of ACI and its variability is required to reduce uncertainties in global radiative forcing estimates.

Retrievals of thick cloud optical depth from the Geoscience Laser Altimeter System (GLAS) by calibration of solar background signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS 532-nm channel, the primary channel for atmospheric products. Solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (i) calibration with coincident airborne and GLAS observations, (ii) calibration with coincident Geostationary Opera- tional Environmental Satellite (GOES) and GLAS observations of deep convective clouds, and (iii) cali- bration from first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retriev- als is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Cloud optical depth retrievals from solar background "signals" of micropulse lidars

Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here, we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10%–15% for overcast stratus and broken clouds. In fact, for broken cloud situations, one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

Remote sensing of cloud properties using ground-based measurements of zenith radiance

We have conducted the first extensive field test of two new methods to retrieve optical properties for overhead clouds that range from patchy to overcast. The methods use measurements of zenith radiance at 673 and 870 nm wavelengths and require the presence of green vegetation in the surrounding area. The test was conducted at the Atmospheric Radiation Measurement Program Oklahoma site during September–November 2004. These methods work because at 673 nm (red) and 870 nm (near infrared (NIR)), clouds have nearly identical optical properties, while vegetated surfaces reflect quite differently. The first method, dubbed REDvsNIR, retrieves not only cloud optical depth τ but also radiative cloud fraction. Because of the 1-s time resolution of our radiance measurements, we are able for the first time to capture changes in cloud optical properties at the natural timescale of cloud evolution. We compared values of τ retrieved by REDvsNIR to those retrieved from downward shortwave fluxes and from microwave brightness temperatures. The flux method generally underestimates τ relative to the REDvsNIR method. Even for overcast but inhomogeneous clouds, differences between REDvsNIR and the flux method can be as large as 50%. In addition, REDvsNIR agreed to better than 15% with the microwave method for both overcast and broken clouds. The second method, dubbed COUPLED, retrieves τ by combining zenith radiances with fluxes. While extra information from fluxes was expected to improve retrievals, this is not always the case. In general, however, the COUPLED and REDvsNIR methods retrieve τ to within 15% of each other.

The effect of surface heterogeneity on cloud absorption estimates

This study presents a systematic and quantitative analysis of the effect of inhomogeneous surface albedo on shortwave cloud absorption estimates. We used 3D radiative transfer modeling over a checkerboard surface albedo to calculate cloud absorption. We have found that accounting for surface heterogeneity enhances cloud absorption. However, the enhancement is not sufficient to explain the reported difference between measured and modeled cloud absorption.

An enhancement of the ionospheric sporadic‐E layer in response to negative polarity cloud‐to‐ground lightning

Lightning data, collected using a Boltek Storm Tracker system installed at Chilton, UK, were used to investigate the mean response of the ionospheric sporadic-E layer to lightning strokes in a superposed epoch study. The lightning detector can discriminate between positive and negative lightning strokes and between cloud-to-ground ( CG) and inter-cloud ( IC) lightning. Superposed epoch studies carried out separately using these subsets of lightning strokes as trigger events have revealed that the dominant cause of the observed ionospheric enhancement in the Es layer is negative cloud-to-ground lightning.

Influence of dynamics on the changes in tropical cloud radiative forcing during the 1998 El Niño

Satellite measurements of the radiation budget and data from the U.S. National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis are used to investigate the links between anomalous cloud radiative forcing over the tropical west Pacific warm pool and the tropical dynamics and sea surface temperature (SST) distribution during 1998. The ratio, N, of the shortwave cloud forcing (SWCF) to longwave cloud forcing (LWCF) (N = −SWCF/LWCF) is used to infer information on cloud altitude. A higher than average N during 1998 appears to be related to two separate phenomena. First, dynamic regime-dependent changes explain high values of N (associated with low cloud altitude) for small magnitudes of SWCF and LWCF (low cloud fraction), which reflect the unusual occurrence of mean subsiding motion over the tropical west Pacific during 1998, associated with the anomalous SST distribution. Second, Tropics-wide long-term changes in the spatial-mean cloud forcing, independent of dynamic regime, explain the higher values of N during both 1998 and in 1994/95. The changes in dynamic regime and their anomalous structure in 1998 are well simulated by version HadAM3 of the Hadley Centre climate model, forced by the observed SSTs. However, the LWCF and SWCF are poorly simulated, as are the interannual changes in N. It is argued that improved representation of LWCF and SWCF and their dependence on dynamical forcing are required before the cloud feedbacks simulated by climate models can be trusted.

Comments on “An ensemble cumulus convection parameterization with explicit cloud treatment”

Wagner and Graf (2010) derive a population evolution equation for an ensemble of convective plumes, an analogue with the Lotka–Volterra equation, from the energy equations for convective plumes provided by Arakawa and Schubert (1974). Although their proposal is interesting, as the present note shows, there are some problems with their derivation.

Cloud-resolving simulations of deep convection over a heated mountain

Cloud-resolving numerical simulations of airflow over a diurnally heated mountain ridge are conducted to explore the mechanisms and sensitivities of convective initiation under high pressure conditions. The simulations are based on a well-observed convection event from the Convective and Orographically Induced Precipitation Study (COPS) during summer 2007, where an isolated afternoon thunderstorm developed over the Black Forest mountains of central Europe, but they are idealized to facilitate understanding and reduce computational expense. In the conditionally unstable but strongly inhibited flow under consideration, sharp horizontal convergence over the mountain acts to locally weaken the inhibition and moisten the dry midtroposphere through shallow cumulus detrainment. The onset of deep convection occurs not through the deep ascent of a single updraft but rather through a rapid succession of thermals that are vented through the mountain convergence zone into the deepening cloud mass. Emerging thermals rise through the saturated wakes of their predecessors, which diminishes the suppressive effects of entrainment and allows for rapid glaciation above the freezing level as supercooled cloud drops rime onto preexisting ice particles. These effects strongly enhance the midlevel cloud buoyancy and enable rapid ascent to the tropopause. The existence and vigor of the convection is highly sensitive to small changes in background wind speed U0, which controls the strength of the mountain convergence and the ability of midlevel moisture to accumulate above the mountain. Whereas vigorous deep convection develops for U0 = 0 m s−1, deep convection is completely eliminated for U0 = 3 m s−1. Although deep convection is able to develop under intermediate winds (U0 = 1.5 m s−1), its formation is highly sensitive to small-amplitude perturbations in the initial flow.

Physics-based modelling for remote sensing of snow

Remote sensing is the only practicable means to observe snow at large scales. Measurements from passive microwave instruments have been used to derive snow climatology since the late 1970’s, but the algorithms used were limited by the computational power of the era. Simplifications such as the assumption of constant snow properties enabled snow mass to be retrieved from the microwave measurements, but large errors arise from those assumptions, which are still used today. A better approach is to perform retrievals within a data assimilation framework, where a physically-based model of the snow properties can be used to produce the best estimate of the snow cover, in conjunction with multi-sensor observations such as the grain size, surface temperature, and microwave radiation. We have developed an existing snow model, SNOBAL, to incorporate mass and energy transfer of the soil, and to simulate the growth of the snow grains. An evaluation of this model is presented and techniques for the development of new retrieval systems are discussed.

Observations of ice multiplication in a weakly convective cell embedded in supercooled mid-level stratus

Simultaneous observations of cloud microphysical properties were obtained by in-situ aircraft measurements and ground based Radar/Lidar. Widespread mid-level stratus cloud was present below a temperature inversion (~5 °C magnitude) at 3.6 km altitude. Localised convection (peak updraft 1.5 m s−1) was observed 20 km west of the Radar station. This was associated with convergence at 2.5 km altitude. The convection was unable to penetrate the inversion capping the mid-level stratus. The mid-level stratus cloud was vertically thin (~400 m), horizontally extensive (covering 100 s of km) and persisted for more than 24 h. The cloud consisted of supercooled water droplets and small concentrations of large (~1 mm) stellar/plate like ice which slowly precipitated out. This ice was nucleated at temperatures greater than −12.2 °C and less than −10.0 °C, (cloud top and cloud base temperatures, respectively). No ice seeding from above the cloud layer was observed. This ice was formed by primary nucleation, either through the entrainment of efficient ice nuclei from above/below cloud, or by the slow stochastic activation of immersion freezing ice nuclei contained within the supercooled drops. Above cloud top significant concentrations of sub-micron aerosol were observed and consisted of a mixture of sulphate and carbonaceous material, a potential source of ice nuclei. Particle number concentrations (in the size range 0.1cloud in concentrations of ~25 cm−3. Ice crystal concentrations in the cloud were constant at around 0.2 L−1. It is estimated that entrainment of aerosol particles into cloud cannot replenish the loss of ice nuclei from the cloud layer via precipitation. Precipitation from the mid-level stratus evaporated before reaching the surface, whereas rates of up to 1 mm h−1 were observed below the convective feature. There is strong evidence for the Hallett-Mossop (HM) process of secondary ice particle production leading to the formation of the precipitation observed. This includes (1) Ice concentrations in the convective feature were more than an order of magnitude greater than the concentration of primary ice in the overlaying stratus, (2) Large concentrations of small pristine columns were observed at the ~−5 °C level together with liquid water droplets and a few rimed ice particles, (3) Columns were larger and increasingly rimed at colder temperatures. Calculated ice splinter production rates are consistent with observed concentrations if the condition that only droplets greater than 24 μm are capable of generating secondary ice splinters is relaxed. This case demonstrates the importance of understanding the formation of ice at slightly supercooled temperatures, as it can lead to secondary ice production and the formation of precipitation in clouds which may not otherwise be considered as significant precipitation sources.

Solar physics: shining a light on solar impacts

Comparing changes in temperature and solar radiation on centennial timescales can help to constrain the Sun’s impact on climate. New findings regarding the minimum activity level of the Sun reveal that comparisons made so far may have been too simplistic.

Fair weather atmospheric electricity

Abstract. Not long after Franklin’s iconic studies, an atmospheric electric field was discovered in “fair weather” regions, well away from thunderstorms. The origin of the fair weather field was sought by Lord Kelvin, through development of electrostatic instrumentation and early data logging techniques, but was ultimately explained through the global circuit model of C.T.R. Wilson. In Wilson’s model, charge exchanged by disturbed weather electrifies the ionosphere, and returns via a small vertical current density in fair weather regions. New insights into the relevance of fair weather atmospheric electricity to terrestrial and planetary atmospheres are now emerging. For example, there is a possible role of the global circuit current density in atmospheric processes, such as cloud formation. Beyond natural atmospheric processes, a novel practical application is the use of early atmospheric electrostatic investigations to provide quantitative information on past urban air pollution.

Combining satellite data and models to estimate cloud radiative effect at the surface and in the atmosphere

Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of shortwave radiation dominates over the longwave heating effect, resulting in a net cooling of the climate system of –21 Wm-2. The shortwave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact longwave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.