scholarly journals Impacts of cloud and precipitation processes on maritime shallow convection as simulated by an LES model with bin microphysics

2014 ◽  
Vol 14 (13) ◽  
pp. 19837-19873 ◽  
Author(s):  
W. W. Grabowski ◽  
L.-P. Wang ◽  
T. V. Prabha
Keyword(s):  
Remote Sensing ◽  
Cloud Droplet ◽  
Convective Cloud ◽  
Collision Kernel ◽  
Small Scale ◽  
Shallow Convection ◽  
Precipitation Processes ◽  
Macrophysical Properties ◽  
Bin Microphysics ◽  
The Impact

Abstract. This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large-eddy model applying warm-rain bin microphysics. Simulations with and without collision-coalescence are considered with CCN concentrations of 30, 60, 120, and 240 mg−1. Simulations with collision-coalescence include either the traditional gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts model results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the impact of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. We document a clear feedback between cloud-scale processes and the mean environmental profiles that increases with the amount of drizzle/rain. Model results show a systematic shift in the cloud top height distributions, with an increasing contributions of deeper clouds and an overall increase of the number of cloudy columns for stronger precipitating cases. We argue that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013) namely, the increase of drizzle/rain leading to a more efficient condensate off-loading in the upper parts of the cloud field. An additional effect involves suppressing cloud droplet evaporation near cloud edges in low-CCN simulations as documented in previous studies. We pose a question whether the effects of cloud turbulence on drizzle/rain formation can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.

scholarly journals Macroscopic impacts of cloud and precipitation processes on maritime shallow convection as simulated by a large eddy simulation model with bin microphysics

2015 ◽  
Vol 15 (2) ◽  
pp. 913-926 ◽  
Author(s):  
W. W. Grabowski ◽  
L.-P. Wang ◽  
T. V. Prabha
Keyword(s):  
Remote Sensing ◽  
Cloud Condensation Nuclei ◽  
Collision Kernel ◽  
Small Scale ◽  
Shallow Convection ◽  
Large Eddy Simulation Model ◽  
Large Eddy ◽  
Precipitation Processes ◽  
Bin Microphysics ◽  
The Impact

Abstract. This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision–coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg−1. Simulations with collision–coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts model results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.

Comparison of Bulk and Bin Warm-Rain Microphysics Models Using a Kinematic Framework

2007 ◽  
Vol 64 (8) ◽  
pp. 2839-2861 ◽  
Author(s):  
Hugh Morrison ◽  
Wojciech W. Grabowski
Keyword(s):  
Atmospheric Aerosols ◽  
Cloud Droplet ◽  
Convective Cloud ◽  
Number Concentration ◽  
Comprehensive Treatment ◽  
Advective Transport ◽  
Mixing Ratios ◽  
Warm Rain ◽  
Bin Microphysics ◽  
The Impact

This paper discusses the development and testing of a bulk warm-rain microphysics model that is capable of addressing the impact of atmospheric aerosols on ice-free clouds. Similarly to previous two-moment bulk schemes, this model predicts the mixing ratios and number concentrations of cloud droplets and drizzle/raindrops. The key elements of the model are the relatively sophisticated cloud droplet activation scheme and a comprehensive treatment of the collision–coalescence mechanism. For the latter, three previously published schemes are selected and tested, with a detailed (bin) microphysics model providing the benchmark. The unique aspect of these tests is that they are performed using a two-dimensional prescribed-flow (kinematic) framework, where both advective transport and gravitational sedimentation are included. Two quasi-idealized test cases are used, the first mimicking a single large eddy in a stratocumulus-topped boundary layer and the second representing a single shallow convective cloud. These types of clouds are thought to be the key in the indirect aerosol effect on climate. Two different aerosol loadings are considered for each case, corresponding to either pristine or polluted environments. In general, all three collision–coalescence schemes seem to capture key features of the bin model simulations (e.g., cloud depth, droplet number concentration, cloud water path, effective radius, precipitation rate, etc.) for the polluted and pristine environments, but there are detailed differences. Two of the collision–coalescence schemes require specification of the width of the cloud droplet spectrum, and model results show significant sensitivity to the specification of the width parameter. Sensitivity tests indicate that a one-moment version of the bulk model for drizzle/rain, which predicts rain/drizzle mixing ratio but not number concentration, produces significant errors relative to the bin model.

scholarly journals Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization

2019 ◽  
Vol 12 (2) ◽  
pp. 1183-1206 ◽  
Author(s):  
Florian Ewald ◽  
Tobias Zinner ◽  
Tobias Kölling ◽  
Bernhard Mayer
Keyword(s):  
Remote Sensing ◽  
Solar Radiation ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Properties ◽  
Trade Wind ◽  
Small Scale ◽  
Passive Remote Sensing ◽  
Remote Sensing Techniques

Abstract. Convective clouds play an essential role for Earth's climate as well as for regional weather events since they have a large influence on the radiation budget and the water cycle. In particular, cloud albedo and the formation of precipitation are influenced by aerosol particles within clouds. In order to improve the understanding of processes from aerosol activation, from cloud droplet growth to changes in cloud radiative properties, remote sensing techniques become more and more important. While passive retrievals for spaceborne observations have become sophisticated and commonplace for inferring cloud optical thickness and droplet size from cloud tops, profiles of droplet size have remained largely uncharted territory for passive remote sensing. In principle they could be derived from observations of cloud sides, but faced with the small-scale heterogeneity of cloud sides, “classical” passive remote sensing techniques are rendered inappropriate. In this work the feasibility is demonstrated to gain new insights into the vertical evolution of cloud droplet effective radius by using reflected solar radiation from cloud sides. Central aspect of this work on its path to a working cloud side retrieval is the analysis of the impact unknown cloud surface geometry has on effective radius retrievals. This study examines the sensitivity of reflected solar radiation to cloud droplet size, using extensive 3-D radiative transfer calculations on the basis of realistic droplet size resolving cloud simulations. Furthermore, it explores a further technique to resolve ambiguities caused by illumination and cloud geometry by considering the surroundings of each pixel. Based on these findings, a statistical approach is used to provide an effective radius retrieval. This statistical effective radius retrieval is focused on the liquid part of convective water clouds, e.g., cumulus mediocris, cumulus congestus, and trade-wind cumulus, which exhibit well-developed cloud sides. Finally, the developed retrieval is tested using known and unknown cloud side scenes to analyze its performance.

The Strong Impact of Weak Horizontal Convergence on Continental Shallow Convection

2020 ◽  
Vol 77 (9) ◽  
pp. 3119-3137
Author(s):  
Marcin J. Kurowski ◽  
Wojciech W. Grabowski ◽  
Kay Suselj ◽  
João Teixeira
Keyword(s):  
Large Scale ◽  
Cloud Microphysics ◽  
Cloud Base ◽  
Small Scale ◽  
Strong Impact ◽  
Shallow Convection ◽  
Liquid Water Path ◽  
Strong Response ◽  
The Impact ◽  
Benchmark Solutions

Abstract Idealized large-eddy simulation (LES) is a basic tool for studying three-dimensional turbulence in the planetary boundary layer. LES is capable of providing benchmark solutions for parameterization development efforts. However, real small-scale atmospheric flows develop in heterogeneous and transient environments with locally varying vertical motions inherent to open multiscale interactive dynamical systems. These variations are often too subtle to detect them by state-of-the-art remote and in situ measurements, and are typically excluded from idealized simulations. The present study addresses the impact of weak [i.e., O(10−6) s−1] short-lived low-level large-scale convergence/divergence perturbations on continental shallow convection. The results show a strong response of shallow nonprecipitating convection to the applied weak large-scale dynamical forcing. Evolutions of CAPE, mean liquid water path, and cloud-top heights are significantly affected by the imposed convergence/divergence. In contrast, evolving cloud-base properties, such as the area coverage and mass flux, are only weakly affected. To contrast those impacts with microphysical sensitivity, the baseline simulations are perturbed assuming different observationally based cloud droplet number concentrations and thus different rainfall. For the tested range of microphysical perturbations, the imposed convergence/divergence provides significantly larger impact than changes in the cloud microphysics. Simulation results presented here provide a stringent test for convection parameterizations, especially important for large-scale models progressing toward resolving some nonhydrostatic effects.

scholarly journals Bridging the condensation-collision size gap: a direct numerical simulation of continuous droplet growth in turbulent cloud

2018 ◽  
Author(s):  
Sisi Chen ◽  
Man-Kong Yau ◽  
Peter Bartello ◽  
Lulin Xue
Keyword(s):  
Positive Impact ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Droplet Growth ◽  
Small Scale ◽  
Combined Processes ◽  
The Individual ◽  
Condensational Growth ◽  
The Impact ◽  
Rain Formation

Abstract. In most previous DNS studies on droplet growth in turbulence, condensational growth and collisional growth were treated separately. Studies in recent decades have postulated that small-scale turbulence may accelerate droplet collisions when droplets are still small when condensational growth is effective. This implies that both processes should be considered simultaneously to unveil the full history of droplet growth and rain formation. This paper introduces the first DNS approach to explicitly study the continuous droplet growth by condensation and collisions inside an adiabatic ascending cloud parcel. Results from the condensation-only, collision-only, and condensation-collision experiments are compared to examine the contribution to the broadening of droplet size distribution by the individual process and by the combined processes. Simulations of different turbulent intensities are conducted to investigate the impact of turbulence on each process and on the condensation-induced collisions. The results show that the condensational process promotes the collisions in a turbulent environment and reduces the collisions when in still air, indicating a positive impact of condensation on turbulent collisions. This work suggests the necessity to include both processes simultaneously when studying droplet-turbulence interaction to quantify the turbulence effect on the evolution of cloud droplet spectrum and rain formation.

Using remote sensing to monitor peatland fire occurrence and recovery

2020 ◽  
Author(s):  
Kirsten Lees ◽  
Josh Buxton ◽  
Chris Boulton ◽  
Tim Lenton
Keyword(s):  
Remote Sensing ◽  
Great Britain ◽  
Management Practice ◽  
Google Earth ◽  
Small Scale ◽  
Fire Occurrence ◽  
Wildfire Occurrence ◽  
Visual Record ◽  
Remote Sensing Methods ◽  
The Impact

<p>Many peatland areas in Great Britain are managed as grouse moors, with regular burns as part of management practice to encourage heather growth. Remote sensing has the potential to monitor the size, location, and impact of these burns using new fine resolution satellites such as Sentinel-2. Google Earth Engine allows large areas to be analysed at small scale over several years, building up a visual record of fire occurrence. This study uses satellite data to map managed burns on several areas of moorland around Great Britain, and uses remote sensing methods to assess the impact of this management strategy on vegetation cover. The project also considers how areas subject to managed burns react to wildfire occurrence, with the 2018 Saddleworth wildfire as a case study.</p>

scholarly journals River Flood Detection Using Passive Microwave Remote Sensing in a Data-Scarce Environment: A Case Study for Two River Basins in Malawi

2021 ◽  
Vol 9 ◽  
Author(s):  
Lone C. Mokkenstorm ◽  
Marc J. C. van den Homberg ◽  
Hessel Winsemius ◽  
Andreas Persson
Keyword(s):  
Remote Sensing ◽  
River Discharge ◽  
Spatial Scales ◽  
Time Lag ◽  
Microwave Remote Sensing ◽  
River Basins ◽  
Passive Microwave ◽  
Small Scale ◽  
Passive Microwave Remote Sensing ◽  
The Impact

Detecting and forecasting riverine floods is of paramount importance for adequate disaster risk management and humanitarian response. However, this is challenging in data-scarce and ungauged river basins in developing countries. Satellite remote sensing data offers a cost-effective, low-maintenance alternative to the limited in-situ data when training, parametrizing and operating flood models. Utilizing the signal difference between a measurement (M) and a dry calibration (C) location in Passive Microwave Remote Sensing (PMRS), the resulting rcm index simulates river discharge in the measurement pixel. Whilst this has been demonstrated for several river basins, it is as of yet unknown at what ratio of the spatial scales of the river width vs. the PMRS pixel resolution it remains effective in East-Africa. This study investigates whether PMRS imagery at 37 GHz can be effectively used for flood preparedness in two small-scale basins in Malawi, the Shire and North Rukuru river basins. Two indices were studied: The m index (rcm expressed as a magnitude relative to the average flow) and a new index that uses an additional wet calibration cell: rcmc. Furthermore, the results of both indices were benchmarked against discharge estimates from the Global Flood Awareness System (GloFAS). The results show that the indices have a similar seasonality as the observed discharge. For the Shire River, rcmc had a stronger correlation with discharge (ρ = 0.548) than m (ρ = 0.476), and the former predicts discharge more accurately (R2 = 0.369) than the latter (R2 = 0.245). In Karonga, the indices performed similarly. The indices do not perform well in detecting individual flood events when comparing the signal to a flood impact database. However, these results are sensitive to the threshold used and the impact database quality. The method presented simulated Shire River discharge and detected floods more accurately than GloFAS. It therefore shows potential for river monitoring in data-scarce areas, especially for rivers of a similar or larger spatial scale than the Shire River. Upstream pixels could not directly be used to forecast floods occurring downstream in these specific basins, as the time lag between discharge peaks did not provide sufficient warning time.

scholarly journals The effects of turbulent collision–coalescence on precipitation formation and precipitation-dynamical feedbacks in simulations of stratocumulus and shallow cumulus convection

2014 ◽  
Vol 14 (13) ◽  
pp. 6557-6570 ◽  
Author(s):  
C. N. Franklin
Keyword(s):  
Cloud Droplet ◽  
Shallow Convection ◽  
Microphysics Scheme ◽  
Droplet Collision ◽  
Shallow Cumulus ◽  
Turbulence Effects ◽  
Double Moment ◽  
Sensitivity Studies ◽  
Microphysical Processes ◽  
The Impact

Abstract. A double moment warm rain scheme that includes the effects of turbulence on droplet collision rates has been implemented in a large-eddy model to investigate the impact of turbulence effects on clouds and precipitation. Simulations of shallow cumulus and stratocumulus show that different precipitation-dynamical feedbacks occur in these regimes when the effects of turbulence are included in the microphysical processes. In both cases inclusion of turbulent microphysics increases precipitation due to a more rapid conversion of cloud water to rain. In the shallow convection case, the greater water loading in the upper cloud levels reduces the buoyancy production of turbulent kinetic energy and the entrainment. The stratocumulus case on the other hand shows a weak positive precipitation feedback, with enhanced rainwater producing greater evaporation, stronger circulations and more turbulence. Sensitivity studies in which the cloud droplet number was varied show that greater number concentrations suppress the stratocumulus precipitation leading to larger liquid water paths. This positive second indirect aerosol effect shows no sensitivity to whether or not the effects of turbulence on droplet collision rates are included. While the sign of the second indirect effect is negative in the shallow convection case whether the effects of turbulence are considered or not, the magnitude of the effect is doubled when the turbulent microphysics are used. It is found that for these two different cloud regimes turbulence has a larger effect than cloud droplet number and the use of a different bulk microphysics scheme on producing rainfall in shallow cumuli. However, for the stratocumulus case examined here, the effects of turbulence on rainfall are not statistically significant and instead it is the cloud droplet number concentration or the choice of bulk microphysics scheme that has the largest control on the rain water.

Comparison of Eulerian Bin and Lagrangian Particle-Based Microphysics in Simulations of Nonprecipitating Cumulus

2020 ◽  
Vol 77 (11) ◽  
pp. 3951-3970
Author(s):  
Wojciech W. Grabowski
Keyword(s):  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Spectral Width ◽  
Diffusional Growth ◽  
Spectral Evolution ◽  
Numerical Diffusion ◽  
Fourfold Increase ◽  
Bin Microphysics ◽  
The Impact ◽  
Lagrangian Scheme

AbstractA single nonprecipitating cumulus congestus setup is applied to compare droplet spectra grown by the diffusion of water vapor in Eulerian bin and particle-based Lagrangian microphysics schemes. Bin microphysics represent droplet spectral evolution applying the spectral density function. In the Lagrangian microphysics, computational particles referred to as superdroplets are followed in time and space with each superdroplet representing a multiplicity of natural cloud droplets. The same cloud condensation nuclei (CCN) activation and identical representation of the droplet diffusional growth allow the comparison. The piggybacking method is used with the two schemes operating in a single simulation, one scheme driving the dynamics and the other one piggybacking the simulated flow. Piggybacking allows point-by-point comparison of droplet spectra predicted by the two schemes. The results show the impact of inherent limitations of the two microphysics simulation methods, numerical diffusion in the Eulerian scheme and a limited number of superdroplets in the Lagrangian scheme. Numerical diffusion in the Eulerian scheme results in a more dilution of the cloud upper half and thus smaller cloud droplet mean radius. The Lagrangian scheme typically has larger spatial fluctuations of droplet spectral properties. A significantly larger mean spectral width in the bin microphysics across the entire cloud depth is the largest difference between the two schemes. A fourfold increase of the number of superdroplets per grid volume and a twofold increase of the spectral resolution and thus the number of bins have small impact on the results and provide only minor changes to the comparison between simulated cloud properties.

scholarly journals A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

2015 ◽  
Vol 8 (2) ◽  
pp. 409-429 ◽  
Author(s):  
L. K. Berg ◽  
M. Shrivastava ◽  
R. C. Easter ◽  
J. D. Fast ◽  
E. G. Chapman ◽  
...  
Keyword(s):  
Deep Convection ◽  
Trace Gases ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Convective Cloud ◽  
Cumulus Parameterization ◽  
Sulfate Production ◽  
Shallow Clouds ◽  
The Impact ◽  
Wet Removal

Abstract. A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as −50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.

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