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At least 19 records

Transport and chemistry of isoprene and its oxidation products in deep convective clouds

Deep convective clouds can transport trace gases from the planetary boundary layer into the upper troposphere where subsequent chemistry may impact aerosol particle formation and growth. In this modelling study, we investigate processes that affect isoprene and its oxidation products injected into the upper troposphere by an isolated deep convective cloud in the Amazon. We run a photochemical box model with coupled cloud microphysics along hundreds of individual air parcel trajectories sampled from a cloud-resolving model simulation of a convective event. The box model simulates gas-phase chemical reactions, gas scavenging by liquid and ice hydrometeors, and turbulent dilution inside a deep convective cloud. The results illustrate the potential importance of gas uptake to anvil ice in regulating the intensity of the isoprene oxidation and associated low volatility organic vapour concentrations in the outflow. Isoprene transport and fate also depends on the abundance of lightning-generated nitrogen oxide radicals (NO x = NO + NO 2 ). If gas uptake on ice is efficient and lightning activity is low, around 30% of the boundary layer isoprene will survive to the cloud outflow after approximately one hour of transport, while all the low volatile oxidation products will be scavenged by the cloud hydrometeors. If lightning NO x is abundant and gas uptake by ice is inefficient, then all isoprene will be oxidised during transport or in the immediate outflow region, while several low volatility isoprene oxidation products will have elevated concentrations in the cloud outflow. Reducing uncertainties associated with the uptake of vapours on ice hydrometeors, especially HO 2 and oxygenated organics, is essential to improve predictions of isoprene and its oxidation products in deep convective outflows and their potential contribution to new particle formation and growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Observational Comparison of Level of Neutral Buoyancy and Level of Maximum Detrainment in Tropical Deep Convective Clouds

Tropical deep convective clouds are important drivers of large-scale atmospheric circulation representing the main vertical transport pathway through the depth of the troposphere for heat, momentum, water, and chemical species. The strength and depth of this transport are impacted by the convective updraft size and intensity that are driven by buoyancy, dynamical forcing, and mixing of environmental air, i.e., entrainment. In this paper, we identify tropical deep convective systems with well-defined forward anvils using Atmospheric Radiation Measurement (ARM) ground-based profiling radars, at three ARM fixed-sites in the Tropical Western Pacific (TWP; i.e., Manus, Nauru, Darwin) and three ARM Mobile Facility deployments in Niamey, Niger; Gan Island, Maldives; and Manacapuru, Brazil. We use the difference between the level of neutral buoyancy (LNB) and the level of maximum detrainment (LMD) as a proxy for the effective bulk convective entrainment (εproxy). The LNB, the theoretical height that a parcel raised above the level of free convection would reach with no mixing, is calculated based on pre-convection radiosonde measurements using parcel theory. The LMD is the height of the maximum reflectivity observed in forward anvil clouds by profiling radars. Deep convective systems over the TWP show higher LNBs that extend to 16.3 km on average and larger εproxy (median LNB minus LMD up to 6.5 km) compared to their continental counterparts in the Amazon and West Africa. Oceanic conditions show larger convective available potential energy (CAPE) coupled with higher moisture at low levels which favors larger εproxy. In contrast, continental cases initiate and develop under high convective inhibition, steeper environmental lapse rate, and high wind shear conditions, which show smaller offset between LNB and LMD. Deep convective cases that promote significant cold pools at the surface experience less εproxy. Using a Random Forest regression algorithm, CAPE is associated with the highest feature importance score for predicting convective εproxy, followed by low-level relative humidity. For continental cases, the low-level wind shear also indicates higher importance.

54 ENVIRONMENTAL SCIENCES↗

Impacts of cloud microphysics parameterizations on simulated aerosol–cloud interactions for deep convective clouds over Houston

Aerosol–cloud interactions remain largely uncertain with respect to predicting their impacts on weather and climate. Cloud microphysics parameterization is one of the factors leading to large uncertainty. Here, we investigate the impacts of anthropogenic aerosols on the convective intensity and precipitation of a thunderstorm occurring on 19 June 2013 over Houston with the Chemistry version of Weather Research and Forecast model (WRF-Chem) using the Morrison two-moment bulk scheme and spectral bin microphysics (SBM) scheme. We find that the SBM predicts a deep convective cloud that shows better agreement with observations in terms of reflectivity and precipitation compared with the Morrison bulk scheme that has been used in many weather and climate models. With the SBM scheme, we see a significant invigoration effect on convective intensity and precipitation by anthropogenic aerosols, mainly through enhanced condensation latent heating. Such an effect is absent with the Morrison two-moment bulk microphysics, mainly because the saturation adjustment approach for droplet condensation and evaporation calculation limits the enhancement by aerosols in (1) condensation latent heat by removing the dependence of condensation on droplets and aerosols and (2) ice-related processes because the approach leads to stronger warm rain and weaker ice processes than the explicit supersaturation approach.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Varying Concentrations of Cloud Condensation Nuclei On Deep Convective Cloud Updrafts – A Multimodel Assessment

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations amongst seven, state-of-the-art, cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced, updraft changes. The models show several consistent trends. In general, the changes between the High- CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5-15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~-5-0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

deep convective cloud updrafts↗

Impacts of Varying Concentrations of Cloud Condensation Nuclei on Deep Convective Cloud Updrafts—A Multimodel Assessment

Abstract This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations among seven state-of-the-art cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas, are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced updraft changes. The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5%–15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~−5% to 0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

54 ENVIRONMENTAL SCIENCES↗

Alabama Ground Operations during the Deep Convective Clouds and Chemistry Experiment

The Deep Convective Clouds and Chemistry (DC3) field campaign investigates the impact of deep, midlatitude convective clouds, including their dynamical, physical and lighting processes, on upper tropospheric composition and chemistry. DC3 science operations took place from 14 May to 30 June 2012. The DC3 field campaign utilized instrumented aircraft and ground ]based observations. The NCAR Gulfstream ]V (GV) observed a variety of gas ]phase species, radiation and cloud particle characteristics in the high ]altitude outflow of storms while the NASA DC ]8 characterized the convective inflow. Groundbased radar networks were used to document the kinematic and microphysical characteristics of storms. In order to study the impact of lightning on convective outflow composition, VHF ]based lightning mapping arrays (LMAs) provided detailed three ]dimensional measurements of flashes. Mobile soundings were utilized to characterize the meteorological environment of the convection. Radar, sounding and lightning observations were also used in real ]time to provide forecasting and mission guidance to the aircraft operations. Combined aircraft and ground ]based observations were conducted at three locations, 1) northeastern Colorado, 2) Oklahoma/Texas and 3) northern Alabama, to study different modes of deep convection in a variety of meteorological and chemical environments. The objective of this paper is to summarize the Alabama ground operations and provide a preliminary assessment of the ground ]based observations collected over northern Alabama during DC3. The multi ] Doppler, dual ]polarization radar network consisted of the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR), the UAHuntsville Mobile Alabama X ]band (MAX) radar and the Hytop (KHTX) Weather Surveillance Radar 88 Doppler (WSR ]88D). Lightning frequency and structure were observed in near real ]time by the NASA MSFC Northern Alabama LMA (NALMA). Pre ]storm and inflow proximity soundings were obtained with the UAHuntsville mobile sounding unit and the Redstone Arsenal (QAG) morning sounding.

Carey, Lawrence↗

Properties of deep convective clouds in the ISCCP Pilot Data Set

Statistics on tropical deep convective clouds in the International Satellite Cloud Climatology Project Pilot Data Set are compiled by binning daytime data over areas of 2 X 2.5, 4 X 5, and 8 X 10 degrees. To isolate the convective clouds, only pixels with minimum visible optical thickness of 32 and maximum cloud top pressure of 550 mb are considered. Maps of convective cloud cover and frequency of convective events and frequency histograms of deep convective cloud pixels and cloud top pressures are presented.

Del Genio, Anthony D.↗

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗

Simulation of Shallow Cumuli and Their Transition to Deep Convective Clouds by Cloud-resolving Models with Different Third-order Turbulence Closures

The abilities of cloud-resolving models (CRMs) with the double-Gaussian based and the single-Gaussian based third-order closures (TOCs) to simulate the shallow cumuli and their transition to deep convective clouds are compared in this study. The single-Gaussian based TOC is fully prognostic (FP), while the double-Gaussian based TOC is partially prognostic (PP). The latter only predicts three important third-order moments while the former predicts all the thirdorder moments. A shallow cumulus case is simulated by single-column versions of the FP and PP TOC models. The PP TOC improves the simulation of shallow cumulus greatly over the FP TOC by producing more realistic cloud structures. Large differences between the FP and PP TOC simulations appear in the cloud layer of the second- and third-order moments, which are related mainly to the underestimate of the cloud height in the FP TOC simulation. Sensitivity experiments and analysis of probability density functions (PDFs) used in the TOCs show that both the turbulence-scale condensation and higher-order moments are important to realistic simulations of the boundary-layer shallow cumuli. A shallow to deep convective cloud transition case is also simulated by the 2-D versions of the FP and PP TOC models. Both CRMs can capture the transition from the shallow cumuli to deep convective clouds. The PP simulations produce more and deeper shallow cumuli than the FP simulations, but the FP simulations produce larger and wider convective clouds than the PP simulations. The temporal evolutions of cloud and precipitation are closely related to the turbulent transport, the cold pool and the cloud-scale circulation. The large amount of turbulent mixing associated with the shallow cumuli slows down the increase of the convective available potential energy and inhibits the early transition to deep convective clouds in the PP simulation. When the deep convective clouds fully develop and the precipitation is produced, the cold pools produced by the evaporation of the precipitation are not favorable to the formation of shallow cumuli.

Cheng, Anning↗

Aerosol Radiative Effects on Deep Convective Clouds and Associated Radiative Forcing

The aerosol radiative effects (ARE) on the deep convective clouds are investigated by using a spectral-bin cloud-resolving model (CRM) coupled with a radiation scheme and an explicit land surface model. The sensitivity of cloud properties and the associated radiative forcing to aerosol single-scattering albedo (SSA) are examined. The ARE on cloud properties is pronounced for mid-visible SSA of 0.85. Relative to the case excluding the ARE, cloud fraction and optical depth decrease by about 18% and 20%, respectively. Cloud droplet and ice particle number concentrations, liquid water path (LWP), ice water path (IWP), and droplet size decrease significantly when the ARE is introduced. The ARE causes a surface cooling of about 0.35 K and significantly high heating rates in the lower troposphere (about 0.6K/day higher at 2 km), both of which lead to a more stable atmosphere and hence weaker convection. The weaker convection and the more desiccation of cloud layers explain the less cloudiness, lower cloud optical depth, LWP and IWP, smaller droplet size, and less precipitation. The daytime-mean direct forcing induced by black carbon is about 2.2 W/sq m at the top of atmosphere (TOA) and -17.4 W/sq m at the surface for SSA of 0.85. The semi-direct forcing is positive, about 10 and 11.2 W/sq m at the TOA and surface, respectively. Both the TOA and surface total radiative forcing values are strongly negative for the deep convective clouds, attributed mostly to aerosol indirect forcing. Aerosol direct and semi-direct effects are very sensitive to SSA. Because the positive semi-direct forcing compensates the negative direct forcing at the surface, the surface temperature and heat fluxes decrease less significantly with the increase of aerosol absorption (decreasing SSA). The cloud fraction, optical depth, convective strength, and precipitation decrease with the increase of absorption, resulting from a more stable and dryer atmosphere due to enhanced surface cooling and atmospheric heating.

Fan, J.↗

Saharan Dust Aerosols Change Deep Convective Cloud Prevalence, Possibly by Inhibiting Marine New Particle Formation

Deep convective clouds (DCCs) are important to global climate, atmospheric chemistry, and precipitation. Dust, a dominant aerosol type over the tropical North Atlantic, has potentially large microphysical impacts on DCCs over this region. However, dust effects are difficult to identify, being confounded by co-varying meteorology and other factors. Here, a method is developed to quantify DCC responses to dust and other aerosols at large spatial and temporal scales despite these uncertainties. Over 7 million tropical North Atlantic cloud, aerosol, and meteorological profiles from CloudSat satellite data and MERRA-2 reanalysis products are used to stratify cloud observations into meteorological regimes, objectively select a priori assumptions, and iteratively test uncertainty sensitivity. Dust is robustly associated with a 54% increase in DCC prevalence. However, marine aerosol proxy concentrations are five times more predictive of dust-associated increases in DCC prevalence than the dust itself, or any other aerosol or meteorological factor. Marine aerosols are also the most predictive factor for the even larger increases in DCC prevalence (61-87%) associated with enhanced dimethyl sulfide and combustion and sulfate aerosols. Dust-associated increases in DCC prevalence are smaller at high dust concentrations than at low concentrations. These observations suggest that not only is dust a comparatively ineffective CCN source, but it may also act as a condensation/coagulation sink for chemical precursors to CCN, reducing total CCN availability over large spatial scales by inhibiting new particle formation from marine emissions. These observations represent the first time this rocess, previously predicted by models, is supported and quantified by measurements.

Aerosol-cloud interactions↗

Application of Quasi-Deep Convective Clouds Method for VIIRS and MODIS TEB Calibration Assessments

A technique that utilizes quasi-deep convective clouds (qDCC) for the calibration assessment of the thermal emissive bands (TEB) on remote sensing instruments has been proven viable. The Terra and Aqua MODIS and S-NPP and NOAA-20 VIIRS TEB calibration uses a nonlinear algorithm whose nonlinear coefficients rely on on-orbit blackbody (BB) warm-up and cooldown operations for updates. However, a limited BB temperature range affects the calibration’s accuracy particularly for cold scenes. The deep convective clouds (DCC) core, one of the coldest Earth scenes, is suitable for MODIS calibration assessments; more specifically, for the evaluation of the offset term’s effect in its TEB quadratic calibration function. Moreover, nighttime qDCC measurements provide with the advantage of removing solar reflectance effects during daytime, thus enhancing the assessment’s accuracy for the midwave infrared TEB. In this paper, this qDCC method is applied to the Terra MODIS and VIIRS TEB; and their stabilities are assessed using long-term qDCC trending measurements over the instruments’ missions. The measurements from bands with an 11-μm wavelength are used to identify the DCC pixels. The 11-μm bands, MODIS band 31 and VIIRS bands M15 and I5, are stable throughout the MODIS and VIIRS missions and have shown excellent calibration accuracy and noise performance. Hence, using these bands as references, a normalization method is employed to enhance the accuracy of the stability and consistency assessments. The S-NPP VIIRS TEB show stable trends over the instrument’s mission. The S-NPP-to-N20 VIIRS comparison shows their TEB measurements are consistent over qDCC. The Terra MODIS TEB also show stable performance – except for bands 27, 29, and 30. Terra MODIS band 30 shows a large downward trend throughout the mission, while bands 27 and 29 show slight, upward drifts. Lastly, a calibration correction using qDCC assessments is discussed and intended to be used in a future calibration algorithm collection.

MODIS↗

VIIRS Reflective Solar Band Radiometric and Stability Evaluation Using Deep Convective Clouds

This work takes advantage of the stable distribution of deep convective cloud (DCC) reflectance measurements to assess the calibration stability and detector difference in Visible Infrared Imaging Radiometer Suite (VIIRS) reflective bands. VIIRS Sensor Data Records (SDRs) from February 2012 to June 2015 are utilized to analyze the long-term trending, detector difference, and half angle mirror (HAM) side difference. VIIRS has two thermal emissive bands with coverage crossing 11 microns for DCC pixel identification. The comparison of the results of these two processing bands is one of the indicators of analysis reliability. The long-term stability analysis shows downward trends (up to approximately 0.4 per year) for the visible and near-infrared bands and upward trends (up to 0.5per year) for the short- and mid-wave infrared bands. The detector difference for each band is calculated as the difference relative to the average reflectance overall detectors. Except for the slightly greater than 1 difference in the two bands at 1610 nm, the detector difference is less than1 for other solar reflective bands. The detector differences show increasing trends for some short-wave bands with center wavelengths from 400 to 600 nm and remain unchanged for the bands with longer center wavelengths. The HAM side difference is insignificant and stable. Those short-wave bands from 400 to 600 nm also have relatively larger HAM side difference, up to 0.25.Comparing the striped images from SDR and the smooth images after the correction validates the analyses of detector difference and HAM side difference. These analyses are very helpful for VIIRS calibration improvement and thus enhance product quality

VIIRS↗

On the Use of Deep Convective Clouds to Calibrate AVHRR Data

Remote sensing of cloud and radiation properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellites requires constant monitoring of the visible sensors. NOAA satellites do not have onboard visible calibration and need to be calibrated vicariously in order to determine the calibration and the degradation rate. Deep convective clouds are extremely bright and cold, are at the tropopause, have nearly a Lambertian reflectance, and provide predictable albedos. The use of deep convective clouds as calibration targets is developed into a calibration technique and applied to NOAA-16 and NOAA-17. The technique computes the relative gain drift over the life-span of the satellite. This technique is validated by comparing the gain drifts derived from inter-calibration of coincident AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) radiances. A ray-matched technique, which uses collocated, coincident, and co-angled pixel satellite radiance pairs is used to intercalibrate MODIS and AVHRR. The deep convective cloud calibration technique was found to be independent of solar zenith angle, by using well calibrated Visible Infrared Scanner (VIRS) radiances onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which precesses through all solar zenith angles in 23 days.

Doelling, David R.↗

Behavior of deep convective clouds in the tropical Pacific deduced from ISCCP radiances

The characteristic features, the diurnal cycle, and the spatial distribution of deep convection over the equatorial Pacific and the relationship of deep convection to SST and surface-wind convergence were examined using a combined visible-IR (VS-IR) threshold method and an IR-only threshold method for diagnosing deep convection clouds (DCCs). Results suggest that deep convection is latitudinally confined to a much smaller spatial scale than that suggested by maps of outgoing long-wave radiation. The results suggested that there are two types of relationships between deep convection, SST, and surface-wind convergence: the west Pacific type and the east Pacific type. The latter relationship is observed in the east Pacific only when SST is not abnormally warm.

Fu, Rong↗

The Characterization of Deep Convective Clouds as an Invariant Calibration Target and as a Visible Calibration Technique

Deep convective clouds (DCCs) are ideal visible calibration targets because they are bright nearly isotropic solar reflectors located over the tropics and they can be easily identified using a simple infrared threshold. Because all satellites view DCCs, DCCs provide the opportunity to uniformly monitor the stability of all operational sensors, both historical and present. A collective DCC anisotropically corrected radiance calibration approach is used to construct monthly probability distribution functions (PDFs) to monitor sensor stability. The DCC calibration targets were stable to within 0.5% and 0.3% per decade when the selection criteria were optimized based on Aqua MODerate Resolution Imaging Spectroradiometer 0.65-micrometer-band radiances. The Tropical Western Pacific (TWP), African, and South American regions were identified as the dominant DCC domains. For the 0.65-micrometer band, the PDF mode statistic is preferable, providing 0.3%regional consistency and 1%temporal uncertainty over land regions. It was found that the DCC within the TWP had the lowest radiometric response and DCC over land did not necessarily have the highest radiometric response. For wavelengths greater than 1 micrometer, the mean statistic is preferred, and land regions provided a regional variability of 0.7%with a temporal uncertainty of 1.1% where the DCC land response was higher than the response over ocean. Unlike stratus and cirrus clouds, the DCC spectra were not affected by water vapor absorption.

Doelling, David R.↗