11 resultados para Drizzle
em CentAUR: Central Archive University of Reading - UK
Resumo:
A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 μm, which leads to a different backscatter cross section for water drops larger than ≈50 μm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio) provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 μm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC) and other moments of the drizzle drop distribution. The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m) profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R) and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here). Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.
Resumo:
We have extensively evaluated the response of cloud-base drizzle rate (Rcb; mm day–1) in warm clouds to liquid water path (LWP; g m–2) and to cloud condensation nuclei (CCN) number concentration (NCCN; cm–3), an aerosol proxy. This evaluation is based on a 19-month long dataset of Doppler radar, lidar, microwave radiometers and aerosol observing systems from the Atmospheric Radiation Measurement (ARM) Mobile Facility deployments at the Azores and in Germany. Assuming 0.55% supersaturation to calculate NCCN, we found a power law , indicating that Rcb decreases by a factor of 2–3 as NCCN increases from 200 to 1000 cm–3 for fixed LWP. Additionally, the precipitation susceptibility to NCCN ranges between 0.5 and 0.9, in agreement with values from simulations and aircraft measurements. Surprisingly, the susceptibility of the probability of precipitation from our analysis is much higher than that from CloudSat estimates, but agrees well with simulations from a multi-scale high-resolution aerosol-climate model. Although scale issues are not completely resolved in the intercomparisons, our results are encouraging, suggesting that it is possible for multi-scale models to accurately simulate the response of LWP to aerosol perturbations.
Resumo:
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. Specifically, 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.
Resumo:
The ability of six scanning cloud radar scan strategies to reconstruct cumulus cloud fields for radiation study is assessed. Utilizing snapshots of clean and polluted cloud fields from large eddy simulations, an analysis is undertaken of error in both the liquid water path and monochromatic downwelling surface irradiance at 870 nm of the reconstructed cloud fields. Error introduced by radar sensitivity, choice of radar scan strategy, retrieval of liquid water content (LWC), and reconstruction scheme is explored. Given an in␣nitely sensitive radar and perfect LWC retrieval, domain average surface irradiance biases are typically less than 3 W m␣2 ␣m␣1, corresponding to 5–10% of the cloud radiative effect (CRE). However, when using a realistic radar sensitivity of ␣37.5 dBZ at 1 km, optically thin areas and edges of clouds are dif␣cult to detect due to their low radar re-ectivity; in clean conditions, overestimates are of order 10 W m␣2 ␣m␣1 (~20% of the CRE), but in polluted conditions, where the droplets are smaller, this increases to 10–26 W m␣2 ␣m␣1 (~40–100% of the CRE). Drizzle drops are also problematic; if treated as cloud droplets, reconstructions are poor, leading to large underestimates of 20–46 W m␣2 ␣m␣1 in domain average surface irradiance (~40–80% of the CRE). Nevertheless, a synergistic retrieval approach combining the detailed cloud structure obtained from scanning radar with the droplet-size information and location of cloud base gained from other instruments would potentially make accurate solar radiative transfer calculations in broken cloud possible for the first time.
Resumo:
During the VOCALS campaign spaceborne satellite observations showed that travelling gravity wave packets, generated by geostrophic adjustment, resulted in perturbations to marine boundary layer (MBL) clouds over the south-east Pacific Ocean (SEP). Often, these perturbations were reversible in that passage of the wave resulted in the clouds becoming brighter (in the wave crest), then darker (in the wave trough) and subsequently recovering their properties after the passage of the wave. However, occasionally the wave packets triggered irreversible changes to the clouds, which transformed from closed mesoscale cellular convection to open form. In this paper we use large eddy simulation (LES) to examine the physical mechanisms that cause this transition. Specifically, we examine whether the clearing of the cloud is due to (i) the wave causing additional cloud-top entrainment of warm, dry air or (ii) whether the additional condensation of liquid water onto the existing drops and the subsequent formation of drizzle are the important mechanisms. We find that, although the wave does cause additional drizzle formation, this is not the reason for the persistent clearing of the cloud; rather it is the additional entrainment of warm, dry air into the cloud followed by a reduction in longwave cooling, although this only has a significant effect when the cloud is starting to decouple from the boundary layer. The result in this case is a change from a stratocumulus to a more patchy cloud regime. For the simulations presented here, cloud condensation nuclei (CCN) scavenging did not play an important role in the clearing of the cloud. The results have implications for understanding transitions between the different cellular regimes in marine boundary layer (MBL) clouds.
Resumo:
A set of high-resolution radar observations of convective storms has been collected to evaluate such storms in the UK Met Office Unified Model during the DYMECS project (Dynamical and Microphysical Evolution of Convective Storms). The 3-GHz Chilbolton Advanced Meteorological Radar was set up with a scan-scheduling algorithm to automatically track convective storms identified in real-time from the operational rainfall radar network. More than 1,000 storm observations gathered over fifteen days in 2011 and 2012 are used to evaluate the model under various synoptic conditions supporting convection. In terms of the detailed three-dimensional morphology, storms in the 1500-m grid-length simulations are shown to produce horizontal structures a factor 1.5–2 wider compared to radar observations. A set of nested model runs at grid lengths down to 100m show that the models converge in terms of storm width, but the storm structures in the simulations with the smallest grid lengths are too narrow and too intense compared to the radar observations. The modelled storms were surrounded by a region of drizzle without ice reflectivities above 0 dBZ aloft, which was related to the dominance of ice crystals and was improved by allowing only aggregates as an ice particle habit. Simulations with graupel outperformed the standard configuration for heavy-rain profiles, but the storm structures were a factor 2 too wide and the convective cores 2 km too deep.
Resumo:
We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signals that are previously unwanted and need to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40 % and at least 10 % higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds and a positive correlation in non-drizzling clouds, where, for large optical depths, it asymptotes to 10 μm. This asymptotic behaviour in non-drizzling clouds is found in both the droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.
Resumo:
The Jülich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Jülich in the most western part of Germany, is a recently established platform for cloud research. The main objective of JOYCE is to provide observations, which improve our understanding of the cloudy boundary layer in a midlatitude environment. Continuous and temporally highly resolved measurements that are specifically suited to characterize the diurnal cycle of water vapor, stability, and turbulence in the lower troposphere are performed with a special focus on atmosphere–surface interaction. In addition, instruments are set up to measure the micro- and macrophysical properties of clouds in detail and how they interact with different boundary layer processes and the large-scale synoptic situation. For this, JOYCE is equipped with an array of state-of-the-art active and passive remote sensing and in situ instruments, which are briefly described in this scientific overview. As an example, a 24-h time series of the evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models.
Resumo:
The co-polar correlation coefficient (ρhv) has many applications, including hydrometeor classification, ground clutter and melting layer identification, interpretation of ice microphysics and the retrieval of rain drop size distributions (DSDs). However, we currently lack the quantitative error estimates that are necessary if these applications are to be fully exploited. Previous error estimates of ρhv rely on knowledge of the unknown "true" ρhv and implicitly assume a Gaussian probability distribution function of ρhv samples. We show that frequency distributions of ρhv estimates are in fact highly negatively skewed. A new variable: L = -log10(1 - ρhv) is defined, which does have Gaussian error statistics, and a standard deviation depending only on the number of independent radar pulses. This is verified using observations of spherical drizzle drops, allowing, for the first time, the construction of rigorous confidence intervals in estimates of ρhv. In addition, we demonstrate how the imperfect co-location of the horizontal and vertical polarisation sample volumes may be accounted for. The possibility of using L to estimate the dispersion parameter (µ) in the gamma drop size distribution is investigated. We find that including drop oscillations is essential for this application, otherwise there could be biases in retrieved µ of up to ~8. Preliminary results in rainfall are presented. In a convective rain case study, our estimates show µ to be substantially larger than 0 (an exponential DSD). In this particular rain event, rain rate would be overestimated by up to 50% if a simple exponential DSD is assumed.