Deep Convective Clouds Research Articles

The New Potential of Deep Convective Clouds as a Calibration Target for a Geostationary UV/VIS Hyperspectral Spectrometer

As one of geostationary earth orbit constellation for environmental monitoring over the next decade, the Geostationary Environment Monitoring Spectrometer (GEMS) has been designed to observe the Asia-Pacific region to provide information on atmospheric chemicals, aerosols, and cloud properties. In order to continuously monitor sensor performance after its launch in early 2020, we suggest in this paper deep convective clouds (DCCs) as a possible target for the vicarious calibration of the GEMS, the first ultraviolet and visible hyperspectral sensor onboard a geostationary satellite. The Tropospheric Monitoring Instrument (TROPOMI) and the Ozone Monitoring Instrument (OMI) are used as a proxy for GEMS, and a conventional DCC-detection approach applying a thermal threshold test is used for DCC detection based on collocations with the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. DCCs are frequently detected over the GEMS observation area at an average of over 200 pixels within a single observation scene. Considering the spatial resolution of the GEMS (3.5 × 8 km2), which is similar to the TROPOMI and its temporal resolution (eight times a day), the availability of DCCs is expected to be sufficient for the vicarious calibration of the GEMS. Inspection of the DCC reflectivity spectra estimated from OMI and TROPOMI data also shows promising results. The estimated DCC spectra are in good agreement within a known uncertainty range with comparable spectral features even with different observation geometries and sensor characteristics. When DCC detection is improved further by applying both visible and infrared tests, the variability of DCC reflectivity from TROPOMI data is reduced from 10% to 5%. This is mainly due to the efficient screening out of cold, thin cirrus clouds in the visible test and of bright, warm clouds in the infrared test. Precise DCC detection is also expected to contribute to the accurate characterization of cloud reflectivity, which will be investigated further in future research.

Deep Neural Network Cloud-Type Classification (DeepCTC) Model and Its Application in Evaluating PERSIANN-CCS

Satellite remote sensing plays a pivotal role in characterizing hydrometeorological components including cloud types and their associated precipitation. The Cloud Profiling Radar (CPR) on the Polar Orbiting CloudSat satellite has provided a unique dataset to characterize cloud types. However, data from this nadir-looking radar offers limited capability for estimating precipitation because of the narrow satellite swath coverage and low temporal frequency. We use these high-quality observations to build a Deep Neural Network Cloud-Type Classification (DeepCTC) model to estimate cloud types from multispectral data from the Advanced Baseline Imager (ABI) onboard the GOES-16 platform. The DeepCTC model is trained and tested using coincident data from both CloudSat and ABI over the CONUS region. Evaluations of DeepCTC indicate that the model performs well for a variety of cloud types including Altostratus, Altocumulus, Cumulus, Nimbostratus, Deep Convective and High clouds. However, capturing low-level clouds remains a challenge for the model. Results from simulated GOES-16 ABI imageries of the Hurricane Harvey event show a large-scale perspective of the rapid and consistent cloud-type monitoring is possible using the DeepCTC model. Additionally, assessments using half-hourly Multi-Radar/Multi-Sensor (MRMS) precipitation rate data (for Hurricane Harvey as a case study) show the ability of DeepCTC in identifying rainy clouds, including Deep Convective and Nimbostratus and their precipitation potential. We also use DeepCTC to evaluate the performance of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) product over different cloud types with respect to MRMS referenced at a half-hourly time scale for July 2018. Our analysis suggests that DeepCTC provides supplementary insights into the variability of cloud types to diagnose the weakness and strength of near real-time GEO-based precipitation retrievals. With additional training and testing, we believe DeepCTC has the potential to augment the widely used PERSIANN-CCS algorithm for estimating precipitation.

African summer monsoon active and break spells cloud properties: Insight from CloudSat-CALIPSO

Abstract This paper investigates the variability of monsoon clouds properties over the South African summer monsoon core zone (SAM: 20°-5°S; 12°-40°E) during the active and break spells of the monsoon seasons and compare the results to those Efon et al. (2016) observed over the West African summer monsoon (WAM) using CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites merged data products. We first computed rainfall anomalies from the Tropical Rainfall Measuring Mission (dataset: TRMM-3B42) rainfall estimates for 1998–2016 to identify the active and break spells of the summer monsoon seasons. More break than active spells, especially in June occur over WAM, and over SAM, active spells are more common, especially in the month of January. Prolonged and successive rainfall can cause floods as observed in the 2010/2011 monsoon season over SAM. A comprehensive assessment is made of cloud properties during active and break spells. Both CBH and CTH exhibit trimodal distribution over SAM. Thicker clouds (with ΔH ≥ 3 km) occur more during the active than break spells. More cirrus cloud cells occur during the active spells (53%) than break spells (43%) over SAM and lesser deep convective clouds occur over SAM compared to WAM during the active spells. Mid-level clouds over SAM have more LWC and Rliq compare to those occurring over WAM. High-level clouds over SAM are richer in IWC, INC and Rice in both monsoons spells than those over WAM. Deep clouds over SAM have larger Rliq and Rice than those occurring over WAM. More atmospheric heating due to clouds in the active spells occur over WAM than SAM in the lower troposphere, and in the upper atmosphere, more heating of the atmosphere takes place SAM compare to WAM. This study has application in representing clouds better in regional weather and or climate models.

Methodology development for calibration assessment using quasi-deep convective clouds with application to Aqua MODIS TEB.

Deep convective clouds (DCC) are identified by using a combination of brightness temperature (BT) and visible reflectance thresholds. Moreover, it is common practice to use daytime DCC measurements for the calibration assessment of reflective solar and longwave infrared (LWIR) bands. The DCC cold core is suitable for the MODIS Thermal Emissive Bands (TEB) calibration assessment; more specifically, for the offset effect in the quadratic calibration function. However, the reflected solar radiance in the daytime DCC measurements affects the midwave infrared (MWIR) bands. Thus, an assessment over low BT measurements is not applicable to these bands. Because of this, a quasi-DCC (qDCC) technique is developed for the MWIR bands calibration assessment. The feasibility of using nighttime DCC measurements is demonstrated by comparing the DCC and daytime qDCC techniques. A DCC normalization method is also developed to remove the DCC fluctuation impact and enhance the assessment accuracy. The DCC measurements' distribution is asymmetrical for all TEB, and their BT ranges fluctuate around 20 K. An empirical model is developed and applied to normalize the measurements over DCC to a reference temperature. After the normalization, the DCC and qDCC measurements' distributions are close to symmetrical and Gaussian in shape. These improvements are applied to the Aqua MODIS instrument. The calibration stability, noise performance, and consistency are evaluated for all Aqua MODIS TEB. Lastly, the Aqua MODIS formatter reset effect on the calibration offset bias between two mirror sides is analyzed, and a calibration coefficient correction is proposed for future calibration improvements.

Investigating Aerosol Effects on Maritime Deep Convective Clouds Using Satellite and Reanalysis Data

Investigating Aerosol Effects on Maritime Deep Convective Clouds Using Satellite and Reanalysis Data

Evaluation of NOAA-20 VIIRS Reflective Solar Bands Early On-Orbit Performance Using Daily Deep Convective Clouds Recent Improvements

The visible infrared imaging radiometer suite (VIIRS) onboard the National Oceanic and Atmospheric Administration - 20 (NOAA-20) satellite was successfully launched in November 2017. During the NOAA-20 VIIRS postlaunch test [(PLT) or extensive cal/val, launch—April 30, 2018], a daily deep convective cloud (DCC) method was developed to support the timely decision making of reflective solar bands (RSBs) on-orbit calibration updates. Different from its predecessor, the VIIRS onboard the Suomi National Polar-Orbiting Partnership (S-NPP) satellite, NOAA-20 VIIRS RSBs have been calibrated using constant calibration factors since April 27, 2018, with the assumption that no significant instrument responsivity change occurs. In this study, the daily DCC method was further refined for evaluating NOAA-20 VIIRS RSB performance after two years on-orbit. An annual cycle climatology for DCC was developed to reduce uncertainty in the trend analysis. NOAA-20 VIIRS observations during the PLT were reprocessed to generate consistent data records. Two-year trends (January 6, 2018–January 5, 2020) were analyzed using consolidated (reprocessed + operational) NOAA-20 daily DCC time series and compared with S-NPP. NOAA-20 daily DCC time series for the visible and near-infrared bands shows small upward trends (up to 0.4%/year in M1), while no significant trend was observed in S-NPP. Moreover, NOAA-20 I 3 and M10 exhibit larger than the expected interchannel inconsistency (∼1.2%) compared with S-NPP. NOAA-20 RSBs are biased ∼1.5%–4.5% lower than S-NPP, generally consistent with results from other methods.

Relationship between airborne electrical and total water content measurements in ice clouds

Abstract During the High Altitude Ice Crystal -High Ice Water Content (HAIC-HIWC) project, instrumented aircraft were flown in the vicinity and inside deep tropical convective clouds. Among the probes installed on one of these aircraft, were the Isokinetic Probe (IKP2), to retrieve the cloud total water content (TWC) and the AMPERA (Atmospheric Measurement of Potential and Electric field on Aircraft) system to provide information on the electrostatic state of the atmosphere and the aircraft. AMPERA is an electric field mill network which locally measures the electrostatic field at the aircraft fuselage. The distribution and amplitude of the electrostatic field on the aircraft skin depends on the atmospheric electrostatic field around the aircraft and the net electric charge of the aircraft. This latter parameter depends on the balance between the triboelectric current due to the impact of the cloud particles on the aircraft fuselage, the current due to the charged particles emitted by the engines, and the corona current emitted by the aircraft. Based on the flights of the HAIC-HIWC campaigns, which were conducted almost exclusively in cloud composed of ice particles, a comparison between the total water content recorded by microphysical sensor and the aircraft net charge has highlighted the possibility of deducing an estimate of the TWC from the aircraft electrical potential. In contrast to conventional TWC probes which sample a local area of the atmosphere, the AMPERA system uses the aircraft as a sensor and provides an overall estimation of its net TWC exposure. This study provides the first results of the efficacy of the electrostatic method through comparisons with direct in-situ bulk TWC measurements in ice clouds.

Assessment of MODIS thermal emissive bands calibration performance using deep convective clouds

The core of deep convective clouds (DCC) is one of the most consistent Earth targets. When viewed from space, the measurements have minimal impact from water vapor and aerosols and have been used as invariant scenes for calibration assessment for reflectance solar bands. DCC is also one of the coldest targets and can be used for assessing the calibration and product stability for infrared thermal emissive bands (TEB). The stability from the years 2003 to 2019 is analyzed for both Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) long-wave infrared bands. Most bands exhibit very stable long-term trending. Terra band 30 shows the largest rate of change of 0.19 K / year. The Terra–Aqua difference is also analyzed. In general, for both Terra and Aqua, the long-wave infrared bands show good and stable detector uniformity. The impact of response change due to anomalies and events has been analyzed. Since the measurement bias over cold DCC is dominated by the offset term in the calibration equation, an assessment model is developed to estimate the offset bias between the mirror sides. The impact model is also developed to estimate the impact on higher brightness temperature measurements. The offset bias from the assessment modeling in this analysis is used as the input for impact modeling. The measurements over Dome-C, Ocean, and desert scenes are used to verify the impact model. These assessments are very helpful for MODIS TEB calibration and look-up table update procedure improvements.

Effects of Aerosols as Ice Nuclei on the Dynamics, Microphysics and Precipitation of Severe Storm Clouds

The Regional Atmospheric Modeling System (RAMS) is used to investigate the effect of aerosols acting as ice nuclei (IN) on the formation and growth of hydrometeor particles as well as on the dynamics and precipitation of a severe storm in Northern China. The focus of this study is to determine how the overall dynamics and microphysical structure of deep convective clouds are influenced if IN concentrations are somehow altered in a storm environment that is otherwise unchanged. Ice mixing ratios tend to increase and liquid mixing ratios tend to decrease with increasing IN concentrations. High concentrations of IN reduce the mean hail diameter and hail particles with smaller diameters melt more easily, which leads to a decrease in ground hailfall and an increase in surface rainfall. Liquid water plays a more important role in the process of hail formation, while the role of ice particles in the process of hail formation decreases with higher IN concentrations. The role of small cloud droplets in the formation of raindrops is increased and the role of hail melting in the process of raindrops formation is weakened with enhanced IN concentrations. Both latent heat release and absorption significantly increase with increasing IN concentrations. Increasing the concentration of IN by an appropriate amount is beneficial for increasing the total water content and strengthening the updraft, leading to enhancement of a storm, but excessive IN concentrations will inhibit the development of a storm.

Response Versus Scan-Angle Assessment of MODIS Reflective Solar Bands in Collection 6.1 Calibration

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Aqua and Terra satellites have been operated for nearly two decades, producing high-quality earth observation data sets suitable for a broad range of scientific studies regarding the earth’s land, ocean, and atmospheric processes. The high radiometric accuracy of MODIS reflective solar band (RSB) calibration has also served as benchmark measurements for on-orbit cross-calibration studies. As the two MODIS instruments have operated well beyond their design lifespan of six years, the measurements from the onboard calibrators alone become inadequate to characterize the sensor’s response at all scan angles, as evinced by long-term drifts observed at certain scan positions of the Aqua-MODIS 0.64- and 0.86- $\mu \text{m}$ bands in Collection 6 (C6) data set. The latest MODIS Level 1B C6.1 data set incorporates earth-view response trending from invariant desert sites as supplemental inputs to characterize the scan-angle calibration dependencies for all RSB. This article presents a deep convective cloud (DCC)-based calibration approach for an independent evaluation of the MODIS RSB response versus scan-angle (RVS) performance in C6.1. The long-term calibration stability and RVS differences in C6.1 have been significantly improved for Aqua-MODIS RSB. The observed RVS differences of more than 2% in Aqua-MODIS C6 bands 1 and 2 have been reduced to within 1% in C6.1. Some RSBs of Terra-MODIS have suffered temporal drifts up to ~2% and calibration shifts up to 3%, particularly around 2016 when the Terra satellite entered into safe mode. The DCC approach has been found very effective in tracking the on-orbit RVS changes over time.

Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN

AbstractHypotheses have been proposed for decades about the effect of activated cloud condensation nuclei (CCN) on delaying the warm rain process, invigorating deep convective cloud vertical development, and enhancing mixed‐phase processes. Observational support has been only qualitative with mixed results due to the lack of regional measurements of CCN concentration (NCCN), while simulations have not produced a robust consensus. Quantitative assessments of these relationships became possible with the advent of NCCN retrievals from satellites; when combined with measurements by polarimetric radar and Lightning Mapping Array (LMA), tracking convective cells observed on radar and examining precipitation properties throughout the cells' life cycle has permitted the study of the impact of NCCN on cloud and precipitation characteristics. We composited more than 2,800 well‐tracked cells in the Houston region and stratified them by NCCN, convective available potential energy (CAPE), and urban/rural locations. The results show that increased NCCN invigorates the convection until saturation near NCCN = 1,000 cm3; increasing NCCN from ~400 to an optimum of ~1,000 cm3 increases lightning activity by an order of magnitude. A further increase in CCN decreases lightning rates. Adding CAPE enhances lightning only under low NCCN (e.g., less than 500 cm3). The presence of the urban area enhances lightning for similar NCCN concentrations, although this applies mainly under low NCCN conditions. The urban heat island as manifested by cloud base height cannot explain this observation. It is suspected that the urban ultrafine aerosols contribute to the storm electrification.

Diurnal variation of high-level clouds from the synergy of AIRS and IASI space-borne infrared sounders

Abstract. By covering about 30 % of the Earth and by exerting a strong greenhouse effect, high-level clouds play an important role in the energy balance of our planet. Their warming and cooling effects within the atmosphere strongly depend on their emissivity. The combination of cloud data from two space-borne infrared sounders, the Atmospheric InfraRed Sounder, AIRS, and the Infrared Atmospheric Sounding Interferometer, IASI, which observe the Earth four times per day, allows us to investigate the diurnal variation of these high-level clouds by distinguishing between high opaque, cirrus, and thin cirrus clouds. We demonstrate that the diurnal phase and amplitude of high-level clouds can be estimated from these measurements with an uncertainty of 1.5 h and 20 %, respectively. By applying the developed methodology to AIRS and IASI cloud observations for the period of 2008–2015, we obtained monthly geographical distributions of diurnal phase and amplitude at a spatial resolution of 1∘ latitude ×1∘ longitude. In agreement with other studies, the diurnal cycle of high-level clouds is the largest over land in the tropics. At higher latitudes, their diurnal cycle is the largest during the summer. For selected continental regions we found diurnal amplitudes of cloud amount of about 7 % for high opaque clouds and for thin cirrus, and 9 % for cirrus. Over ocean, these values are 2 to 3 times smaller. The diurnal cycle of tropical thin cirrus seems to be similar over land and over ocean, with a minimum in the morning (09:00 LT) and a maximum during the night (01:00 LT). Tropical high opaque clouds have a maximum in the evening (21:00 LT over land), a few hours after the peak of convective rain. This lag can be explained by the fact that this cloud type includes not only the convective cores, but also part of the thicker anvils. Tropical cirrus show maximum coverage during the night (01:00 LT over land). This lag indicates that they are part of the deep convective cloud systems. However, the peak local times also vary regionally. We are providing a global monthly database of detected diurnal cycle amplitude and phase for each of these three high-level cloud types.

Observations on the distribution of precipitation over northern India using joint CloudSat, CALIPSO and TRMM measurements

ABSTRACTClouds and precipitation are closely associated with each other, and a baseline understanding of such meteorological parameters on various scales including their regional climatology is essentially needed. The present article deals with the annual and seasonal distribution of different forms of precipitation (liquid, solid and drizzle) and their association with the different cloud types over the northern states of India (NSI). Synergic estimates of precipitation obtained with raDAR-liDAR (DARDAR) and Tropical Rainfall Measuring Mission over a decade (2007–2016) are used to elucidate the same. The study on different forms of precipitation over NSI region exhibits opposite circulation of its solid (increase) and liquid (decrease) forms in westward or north-westward. The association of deep convective (DC) and nimbostratus (Ns) cloud types with solid precipitation on an annual scale is observed as 1.6% and 76% of their total co-occurrences, respectively. On the other hand, their association with liquid precipitation is found to be 98.4% and 23.7%, respectively, thereby implying that nimbostratus and DC clouds are the main contributors of solid and liquid precipitations, respectively, over the NSI region during the last decade.

Dusty Deep Convection in the Mars Year 34 Planet-Encircling Dust Event.

Dusty convection, convective activity powered by radiative heating of dust, is a ubiquitous phenomenon in Mars's atmosphere but is especially deep (that is, impactful on the middle atmosphere) and widespread during planet-encircling dust events (PEDE) that occur every few Mars Years (MY). Yet the relative roles of dusty deep convection and global dynamics, such as the principal meridional overturning cell (PMOC) and the radiative tides, in dust storm development and the vertical transport of dust and water are still unclear. Here, observations from the Mars Climate Sounder on board Mars Reconnaissance Orbiter (MRO-MCS) are used to study dusty deep convection and its impact on middle atmospheric water content during the MY 34 PEDE (commenced June 2018). Additional context is provided by MRO-MCS observations of the MY 28 PEDE (commenced June 2007). This investigation establishes that a few, localized centers of dusty deep convection in the tropics formed in the initial phases of both PEDE simultaneously with a substantial increase in middle atmospheric water content. The growth phase of the MY 34 PEDE was defined by episodic outbreaks of deep convection along the Acidalia and Utopia storm tracks as opposed to less episodic, more longitudinally distributed convective activity during the MY 28 PEDE. The most intense convection during both PEDE was observed in southern/eastern Tharsis, where MRO-MCS observed multiple instances of deep convective clouds transporting dust to altitudes of 70-90 km. These results suggest that Martian PEDE typically contain multiple convectively active mesoscale weather systems.

Atmospheric Dynamics from Synoptic to Local Scale During an Intense Frontal Dust Storm over the Sistan Basin in Winter 2019

The Sistan Basin has been recognized as one of the most active dust sources and windiest desert environments in the world. Although the dust activity in Sistan maximizes during the summer, rare but intense dust storms may also occur in the winter. This study aims to elucidate the atmospheric dynamics related to dust emission and transport, dust-plume characteristics, and impacts on aerosol properties and air quality during an intense dust storm over Sistan in February 2019. The dust storm was initiated by strong northerly winds (~20 ms−1) associated with the intrusion of a cold front from high latitudes. The upper-level potential vorticity (PV)-trough evolved into a cut-off low in the mid and upper troposphere and initiated unstable weather over Afghanistan and northern Pakistan. At the surface, density currents emanating from deep convective clouds and further strengthened by downslope winds from the mountains, caused massive soil erosion. The passage of the cold front reduced the temperature by ~10 °C and increased the atmospheric pressure by ~10 hPa, while the visibility was limited to less than 200 m. The rough topography played a major role in modulating the atmospheric dynamics, wind field, dust emissions, and transport pathways. Meso-NH model simulates large amounts of columnar mass dust loading (> 20 g m−2) over Sistan, while the intense dust plume was mainly traveling below 2 km and increased the particulate matter (PM10) concentrations up to 1800 µg m−3 at Zabol. The dust storm was initially moving in an arc-shaped pathway over the Sistan Basin and then it spread away. Plumes of dust covered a large area in southwest Asia, reaching the northern Arabian Sea, and the Thar desert one to two days later, while they strongly affected the aerosol properties at Karachi, Pakistan, by increasing the aerosol optical depth (AOD > 1.2) and the coarse-mode fraction at ~0.7.

Environmental impacts on the flux of mass through deep convection

AbstractThough deep convective clouds are important to numerous aspects of the climate system, they remain a source of much uncertainty. The varying large‐scale dynamics, relatively short development time, range of spatial scales, and complex microphysics involved in deep convection lead to difficulty in both observation of these clouds and modelling their impacts on larger spatial and longer temporal scales. This study utilizes an ensemble of high‐resolution cloud‐resolving simulations of deep convection forming in a spectrum of different environments to explore the sensitivity of deep convection, and in particular convective mass flux to changes in the initial conditions. We find that convection strength is strongly sensitive to small perturbations in the environment, specifically the convective available potential energy (CAPE) and boundary‐layer humidity. That storm effects on the environment, such as mass transport and tropospheric moistening through detrainment, are sensitive to these initial conditions points to the importance of better representing such parameters in global models.

Pair Correlations and Spatial Statistics of Deep Convection over the Tropical Atlantic

AbstractOver the tropical oceans, the large-scale, meridional circulation drives the accumulation of moist and warm air, leading to a relatively narrow, convectively active band. Therein, deep moist convection interacts with its heterogeneous environment—the intertropical convergence zone (ITCZ)—and organizes into multiscale structures that strongly impact Earth’s hydrological cycle and radiation budget. Understanding the spatial correlations and interactions among deep convective clouds is important, but challenging. These clouds are investigated in this study with the help of large-domain, storm-resolving simulations over the tropical Atlantic. Based on vertically integrated mass flux fields, deep convective updraft cells are identified with object-based techniques and analyzed with respect to their structural behavior and spatial arrangement. The pair-correlation method, which compares simulated pair numbers as a function of pair distance to an appropriately chosen reference, is applied and extended to allow for spatial statistics in a heterogeneous environment (i.e., the ITCZ). Based on pair-correlation analysis, the average probability is enhanced to find an updraft cell pair within 100 km compared to a random distribution. Additionally, the spatial arrangement of larger or stronger cells deviates more from randomness compared to smaller or weaker cells, which might be related to their stronger dynamical interaction mechanisms. Using simplified equilibrium statistics of interacting cells, several spatial characteristics of the storm-resolving simulations can be reproduced.

Evaluation of turbulence parametrizations in convective clouds and their environment based on a large‐eddy simulation

The representation of deep convective clouds by convection‐permitting models could be improved by parametrizing the subgrid turbulent fluxes better. Following the work of Verrelle et al., a large‐eddy simulation (LES) of a population of convective clouds at 50‐m grid spacing was explored during the cloud life cycle to characterize the second‐order moment turbulent fluxes. The reference turbulence fields were deduced by coarse‐graining the LES outputs at horizontal grid resolutions of 500 m and 1 and 2 km. The ability of three parametrizations—the traditional K‐gradient model of Cuxart et al. (CBR), the Smagorinsky formulation, and the Moeng approach (MOENG) based on the horizontal gradients of the resolved variables—to reproduce the thermodynamical and dynamical fluxes was assessed in an offline configuration via a comparison with the reference fields. MOENG was the most appropriate scheme to represent the vertical and horizontal heat fluxes at all grid spacings in the clouds and their environment over the entire cloud life cycle, including the appropriate representation of countergradient areas. It also represented the vertical and horizontal moisture fluxes at 1‐km and 500‐m grid spacings best, while its advantage was reduced at a grid spacing of 2 km, as CBR performed slightly better for the statistical scores. MOENG was also able to represent the dynamical covariances well at grid spacings of 1 km and 500 m, even though the statistical scores were not as good as those obtained for the thermodynamical fluxes. The dynamical variances were well represented by CBR; however, for this offline evaluation, the subgrid turbulent kinetic energy, present in CBR formulations, is computed directly from the LES outputs, giving CBR an advantage over the two other diagnosed parametrizations. Also, the reference fluxes revealed an anisotropic deformation of turbulence throughout the troposphere, which was only captured by MOENG.

The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity

Abstract. The global aerosol–climate model ECHAM6.3–HAM2.3 (E63H23) as well as the previous model versions ECHAM5.5–HAM2.0 (E55H20) and ECHAM6.1–HAM2.2 (E61H22) are evaluated using global observational datasets for clouds and precipitation. In E63H23, the amount of low clouds, the liquid and ice water path, and cloud radiative effects are more realistic than in previous model versions. E63H23 has a more physically based aerosol activation scheme, improvements in the cloud cover scheme, changes in the detrainment of convective clouds, changes in the sticking efficiency for the accretion of ice crystals by snow, consistent ice crystal shapes throughout the model, and changes in mixed-phase freezing; an inconsistency in ice crystal number concentration (ICNC) in cirrus clouds was also removed. Common biases in ECHAM and in E63H23 (and in previous ECHAM–HAM versions) are a cloud amount in stratocumulus regions that is too low and deep convective clouds over the Atlantic and Pacific oceans that form too close to the continents (while tropical land precipitation is underestimated). There are indications that ICNCs are overestimated in E63H23. Since clouds are important for effective radiative forcing due to aerosol–radiation and aerosol–cloud interactions (ERFari+aci) and equilibrium climate sensitivity (ECS), differences in ERFari+aci and ECS between the model versions were also analyzed. ERFari+aci is weaker in E63H23 (−1.0 W m−2) than in E61H22 (−1.2 W m−2) (or E55H20; −1.1 W m−2). This is caused by the weaker shortwave ERFari+aci (a new aerosol activation scheme and sea salt emission parameterization in E63H23, more realistic simulation of cloud water) overcompensating for the weaker longwave ERFari+aci (removal of an inconsistency in ICNC in cirrus clouds in E61H22). The decrease in ECS in E63H23 (2.5 K) compared to E61H22 (2.8 K) is due to changes in the entrainment rate for shallow convection (affecting the cloud amount feedback) and a stronger cloud phase feedback. Experiments with minimum cloud droplet number concentrations (CDNCmin) of 40 cm−3 or 10 cm−3 show that a higher value of CDNCmin reduces ERFari+aci as well as ECS in E63H23.

Effects of Sea Spray on Microphysics and Intensity of Deep Convective Clouds Under Strong Winds

AbstractDeep convective clouds similar to those arising in the tropical cyclone eyewall are simulated using a parcel model and 2‐D slab symmetric cloud model with spectral bin microphysics (the Hebrew University Cloud Model). The size distribution of sea spray particles (SSPs) at cloud base is calculated using the Lagrangian‐Eulerian bin microphysics model. The model describes the SSP production, advection, and formation of the size distribution of SSP in the hurricane atmospheric boundary layer at different strong wind speeds. The SSP distributions calculated by the Lagrangian‐Eulerian bin microphysics model are used in the parcel model and the Hebrew University Cloud Model to investigate the microphysical and dynamical effects of SSP on clouds. The SSPs ascending in cloud updrafts dramatically increase the number concentration of cloud drops within a wide range of drop sizes. As a result, sea spray creates clouds with unique property combinations of both maritime and continental types. These clouds have droplet size distributions characterized by a high drop concentration and a low effective radius, as in continental clouds. At the same time, the presence of SSP of a few hundred microns in radii triggers intense rain just above the cloud base, which is typical of extreme maritime clouds. In the presence of large sea spray drops, the smallest cloud condensational nuclei, including the smallest SSP, are activated, giving rise to the permanent in‐cloud nucleation of small droplets, which produce a high concentration of small ice crystals above the level of homogeneous freezing. We showed that the SSP substantially increased the maximum vertical velocity, cloud water content, and mass contents of ice particles. The results are compared with available observed data.