Deep Convective Clouds Research Articles

The Global Nature of Early‐Afternoon and Late‐Night Convection Through the Eyes of the A‐Train

AbstractCharacterizing macrophysical properties of deep convective systems on a global scale is a precursor to understanding their influence on Earth's Energy Budget and Water Cycle. This study documents the properties of global convective objects (COs) in the early afternoon (1:30 p.m. local time; LT) and overnight (1:30 a.m. LT) measurements from the A‐Train satellite constellation. CloudSat measurements are used to identify convective cores and establish their intensity, while other A‐Train data sets define cloud structure, storm spatial extent, rainfall yield, and radiative effects of each CO. Global distributions of storm characteristics are consistent with previous studies in which the most intense convection is located over tropical land, particularly over the Amazon and Congo Basin, while the largest COs occur over the Maritime Continent. Despite their limited twice‐daily sampling, A‐Train measurements capture that early afternoon convection over tropical land is both more intense and produces heavier rainfall than nighttime land‐based convection, while the day‐night differences are minimal over the tropical ocean. High‐resolution estimates of updraft cores reveal that CO size increases as the number of distinct cores in a CO increases owing to an increase in nonconvective rain and anvil cloud area. Convective objects generally cool the environment, which is strongest over the Northern Hemisphere midlatitudes, but cooling weakens as the nonconvective cloud fraction increases such that 30% of COs actually exert a net warming effect. These results suggest that A‐Train measurements may capture bulk connections between deep convective cloud features, precipitation, and radiative effects despite a lack of complete diurnal sampling.

Cloud phase and macrophysical properties over the Southern Ocean during the MARCUS field campaign

Abstract. To investigate the cloud phase and macrophysical properties over the Southern Ocean (SO), the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF2) was installed on the Australian icebreaker research vessel (R/V) Aurora Australis during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign (41 to 69∘ S, 60 to 160∘ E) from October 2017 to March 2018. To examine cloud properties over the midlatitude and polar regions, the study domain is separated into the northern (NSO) and southern (SSO) parts of the SO, with a demarcation line of 60∘ S. The total cloud fractions (CFs) were 77.9 %, 67.6 %, and 90.3 % for the entire domain, NSO and SSO, respectively, indicating that higher CFs were observed in the polar region. Low-level clouds and deep convective clouds are the two most common cloud types over the SO. A new method was developed to classify liquid, mixed-phase, and ice clouds in single-layered, low-level clouds (LOW), where mixed-phase clouds dominate with an occurrence frequency (Freq) of 54.5 %, while the Freqs of the liquid and ice clouds were 10.1 % (most drizzling) and 17.4 % (least drizzling). The meridional distributions of low-level cloud boundaries are nearly independent of latitude, whereas the cloud temperatures increased by ∼8 K, and atmospheric precipitable water vapor increased from ∼5 mm at 69∘ S to ∼18 mm at 43∘ S. The mean cloud liquid water paths over NSO were much larger than those over SSO. Most liquid clouds occurred over NSO, with very few over SSO, whereas more mixed-phase clouds occurred over SSO than over NSO. There were no significant differences for the ice cloud Freq between NSO and SSO. The ice particle sizes are comparable to cloud droplets and drizzle drops and well mixed in the cloud layer. These results will be valuable for advancing our understanding of the meridional and vertical distributions of clouds and can be used to improve model simulations over the SO.

Diverse cloud radiative effects and global surface temperature simulations induced by different ice cloud optical property parameterizations

The representation of ice cloud optical properties in climate models has long been a difficult problem. Very different ice cloud optical property parameterization schemes developed based on very different assumptions of ice particle shape habits, particle size distributions, and surface roughness conditions, are used in various models. It is not clear as to how simulated climate variables are affected by the ice cloud optical property parameterizations. A total of five ice cloud optical property parameterization schemes, including three based on the ice habit mixtures suitable for general ice clouds, mid-latitude synoptic ice clouds, and tropical deep convective ice clouds, and the other two based on single ice habits (smooth hexagonal column and severely roughened column aggregate), are developed under a same framework and are implemented in the National Center for Atmospheric Research Community Atmospheric Model version 5. A series of atmosphere-only climate simulations are carried out for each of the five cases with different ice parameterizations. The differences in the simulated top of the atmosphere shortwave and longwave cloud radiative effects (CREs) are evaluated, and the global averaged net CRE differences among different cases range from − 1.93 to 1.03 Wm−2. The corresponding changes in simulated surface temperature are found to be most prominent on continental regions which amount to several degrees in Kelvin. Our results indicate the importance of choosing a reasonable ice cloud optical property parameterization in climate simulations.

Characterization of the on-orbit response versus scan angle for Terra MODIS SWIR bands in Collection 7

The Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua platforms has 20 reflective solar bands (0.4 to 2.1 μm), for which the on-orbit detector gain changes are tracked using the on-board solar diffuser (SD) and SD stability monitor. SD and lunar observation data, supplemented by Earth-view (EV) observations for some bands, are used to characterize the scan-mirror response versus scan angle (RVS). The short-wave infrared (SWIR) bands (1.2 to 2.1 μm) have issues, such as electronic crosstalk and an out-of-band optical leak from the thermal bands, which complicate the use of the Moon for reliably characterizing the on-orbit RVS. Before Collection 7 (C7), the pre-launch RVS was deemed sufficient for both Aqua and Terra MODIS SWIR bands throughout the missions. However, recent studies have found that the RVS behavior does change with time in some SWIR bands, up to 2% and 1% for Terra MODIS bands 5 and 26, respectively. We assess the residual RVS effects present in the current MODIS calibration at desert sites and deep convective clouds (DCC). Due to the large uncertainties caused by the water vapor absorption effects from desert sites, especially for band 26 (1.375 μm), EV observations from DCCs are chosen to characterize the on-orbit RVS behavior for the SWIR bands. A time-dependent RVS characterization method for the SWIR bands is described and assessed by comparing the results with Collection 6.1 (C6.1) Level 1B (L1B) reflectance products. This new algorithm will be used in the upcoming C7 L1B reprocessing for Terra MODIS, providing more stable and accurate SWIR band reflectance data over time and across the scan range compared with the C6.1 results. For Aqua MODIS SWIR bands, performance evaluations with desert and DCC data indicate stable performance, so the pre-launch RVS will continue to be used in C7.

Satellite‐Based Detection of Secondary Droplet Activation in Convective Clouds

AbstractWe present a new approach of analyzing and interpreting vertical profiles of cloud microstructure obtained by satellite remote sensing. The method is based on a spectral bin microphysics adiabatic parcel model and aims to elucidate the effects of aerosols on the evolution of convective clouds and related microphysical processes, including the activation of cloud condensation nuclei (CCN), the growth of cloud droplets, and the formation of precipitation. Characteristic features in the vertical profiles of effective radius (re) and temperature (T) reveal different microphysical zones in convective clouds related to the change increase of re with decreasing T. The classification of the different microphysical zones includes the (a) condensational growth of droplets, (b) growth by coalescence, (c) rainout, (d) secondary droplet activation zone (SAZ), (e) mixed‐phase of ice particles and water droplets, and (f) glaciation of the cloud. The detection of the SAZ is introduced here for the first time. This method allows us to identify the activation of aerosol particles above cloud base and their role in the invigoration of deep convective clouds.

Assessment of Terra/Aqua MODIS and Deep Convective Cloud Albedo Solar Calibration Accuracies and Stabilities Using Lunar Calibrated MERBE Results

Moon calibrated radiometrically stable and relatively accurate Earth reflected solar measurements from the Moon and Earth Radiation Budget Experiment (MERBE) are compared here to primary channels of coaligned Terra/Aqua MODIS instruments. A space-based climate observing system immune to untracked drifts due to varying instrument calibration is a key priority for climate science. Measuring these changes in radiometers such as MODIS and compensating for them is critical to such a system. The independent MERBE project using monthly lunar scans has made a proven factor of ten improvement in calibration stability and relative accuracy of measurements by all devices originally built for another project called ‘CERES’, also on the Terra and Aqua satellites. The MERBE comparison shown here uses spectrally invariant Deep Convective Cloud or DCC targets as a transfer, with the objective of detecting possible unknown MODIS calibration trends or errors. Most MODIS channel 1–3 collection 5 calibrations are shown to be correct and stable within stated accuracies of 3% relative to the Moon, much in line with changes made for MODIS collection 6. Stable lunar radiance standards are then separately compared to the sometimes used calibration metric of the coldest DCCs as standalone calibration targets, when also located by MODIS. The analysis overall for the first time finds such clouds can serve as an absolute solar target on the order of 1% accuracy and are stable to ±0.3% decade−1 with two sigma confidences, based on the Moon from 2000–2015. Finally, time series analysis is applied to potential DCC albedo corrected Terra data. This shows it is capable of beginning the narrowing of cloud climate forcing uncertainty before 2015; some twenty five years sooner than previously calculated elsewhere, for missions yet to launch.

Maintenance Mechanisms of the Wintertime Subtropical High over the South Indian Ocean

Abstract Climatologically the surface Mascarene high over the subtropical south Indian Ocean (SIO) shifts westward toward austral winter, and its strength as a planetary-wave component maximizes in late austral winter, unlike its counterpart over other subtropical oceans. The present study investigates the maintenance mechanisms for the wintertime Mascarene high with a linear atmospheric dynamical model (LBM) and an atmospheric general circulation model (AGCM). The LBM experiments reveal the importance of cross-equatorial tropical influences. Deep convection associated with the Asian summer monsoon acts not only to shift the Mascarene high westward as its direct influence but also to enhance midtropospheric subsidence and equatorward surface winds over the central and western portions of the subtropical SIO. The associated near-surface cold advection and subsidence promote (suppress) the formation of low-level (deep convective) clouds. The resultant enhanced radiative cooling and reduced deep condensation heating both reinforce the equatorward portion of the surface high. The LBM experiments also reveal that seasonally enhanced storm-track activity over the SIO is important for maintaining the poleward portion of the Mascarene high through eddy heat and vorticity fluxes. The AGCM experiments demonstrate that the Agulhas Current system and the associated sea surface temperature (SST) front reinforce the high by energizing the storm-track activity. The present study thus proposes that both the Asian summer monsoon and the enhanced storm-track activity maintained by the Agulhas SST front externally modulate the positively coupled system between the wintertime Mascarene high and low-level clouds to realize its unique seasonality.

Rain microphysical properties over the rain shadow region of India

The variability in the microphysical properties of raindrop size distribution (DSD) over the rain shadow region of Indian peninsula is investigated in this study. Simultaneous in-situ measurements of precipitating cloud systems by an impact disdrometer, Micro Rain Radar (24 GHz), and wind profiler (1.28 GHz) are used in this study. The normalized Gamma distribution parameters for five DSD clusters of precipitating systems, corresponding to the non-convective, deep convective, shallow convective, mixed-type, and stratiform rain types were obtained using the k-means clustering algorithm. Four DSDs are nearly bounded by shape parameters, −3 < μ < 25, except for stratiform DSDs (−3 < μ < 45) indicating a wide variation in DSD shape. Bimodal (mono-modal) distributions in terms of frequency of occurrence of Nw are observed in the non-convective, deep convective and shallow convective (stratiform and mixed) clouds. The bimodality is attributed to the large raindrops formed by the collision and coalescence (CC) process, and the small raindrops due to breakup that survive evaporation and reach the ground. The mono-modality of stratiform rain is attributed to the in-efficient CC and CC-breakup process. These rain microphysical processes are further characterized using the radar reflectivity factor (Z)-Rainfall Intensity (R) relationships of the form Z = aRb. Finally, we found that the convective DSDs over the region appear to be a composite of both maritime and continental characteristics.

ОПАСНЫЕ АТМОСФЕРНЫЕ ЯВЛЕНИЯ КОНВЕКТИВНОГО ХАРАКТЕРА В РОССИИ: НАБЛЮДАЕМЫЕ ИЗМЕНЕНИЯ ПО РАЗЛИЧНЫМ ДАННЫМ

Changes in the frequency and intensity of atmospheric severe convective events, including heavy rainfall, thunderstorm, hailstorm, squall, and tornado, in the Russian regions during the warm season are analyzed using different independent sources of information. Based on observations at Russian weather stations in 1966-2020, the frequency of thunderstorm, hailstorm, and strong wind, the contribution of extreme showers to total precipitation, and the cumulonimbus cloud fraction are estimated. Based on satellite data, the frequency and intensity of tornado and squall events that caused windthrows for 1986-2021 and the height of the top of deep convective clouds for 2002-2021 are also evaluated. The ERA5 reanalysis data are used to analyze the frequency of conditions favorable for the development of moderate and intense severe convective events in 1979-2020. The results indicate a general intensification of severe convective events in most Russian regions, except for a number of regions in the south of the European part of Russia. The frequency of moderate hazards has a decreasing trend, and the frequency of the most intense severe hazards has an increasing trend. It is reasonable to take the results into account when developing plans for the adaptation of Russian regions and industries to climate change.

Deep Convection Initiation, Growth, and Environments in the Complex Terrain of Central Argentina during CACTI

Abstract This study characterizes the wide range of deep convective cloud life cycles and their relationships with ambient environments observed during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign near the Sierras de Córdoba (SDC) range in central Argentina. We develop a novel convective cell tracking database for the entire field campaign using C-band polarimetric radar observations. The cell tracking database includes timing, location, area, depth, merge/split information, microphysical properties, collocated satellite-retrieved cloud properties, and sounding-derived environmental conditions. Results show that the SDC exerts a strong control on convection initiation (CI) and growth. CI preferentially occurs east of the SDC ridge during the afternoon, and cells often undergo upscale growth through the evening as they travel eastward toward the plains. Larger and more intense cells tend to occur in more unstable and humid low-level environments, and surface-based cells are stronger than elevated cells. Midtropospheric relative humidity and vertical wind shear also jointly affect the size and depth of the cells. Rapid cell area growth rates exhibit dependence on both large environmental wind shear and low-level moisture. Evolution of convective cell macro- and microphysical properties are strongly influenced by convective available potential energy and low-level humidity, as well as the presence of other cells in their vicinity. This cell tracking database demonstrates a framework that ties measurements from various platforms centering around convective life cycles to facilitate process understanding of factors that control convective evolution. Significance Statement The purpose of this study is to develop a framework that ties coordinated radar, satellite, and radiosonde measurements around tracking convective storm life cycles to facilitate process understanding of atmospheric environments that control storm evolution. The processes coupling storm life cycles and local environments remain inadequately understood and are poorly represented in weather and climate models. Our results demonstrate the importance of atmospheric instability, low- and midtropospheric moisture, changes of wind with height, and interactions among nearby storms in affecting the formation and growth of convective storms. The storm database developed in this work enables future studies for comprehensive exploration of processes that lead to improved mechanistic understanding of storm evolution and their representations in models.

Mind the Gap - Part 3: Doppler Velocity Measurements From Space

Convective motions and hydrometeor microphysical properties are highly sought-after parameters for evaluating atmospheric numerical models. With most of Earth’s surface covered by water, space-borne Doppler radars are ideal for acquiring such measurements at a global scale. While these systems have proven to be useful tools for retrieving cloud microphysical and dynamical properties from the ground, their adequacy and specific requirements for spaceborne operation still need to be evaluated. Comprehensive forward simulations enable us to assess the advantages and drawbacks of six different Doppler radar architectures currently planned or under consideration by space agencies for the study of cloud dynamics. Radar performance is examined against the state-of-the-art numerical model simulations of well-characterized shallow and deep, continental, and oceanic convective cases. Mean Doppler velocity (MDV) measurements collected at multiple frequencies (13, 35, and 94 GHz) provide complementary information in deep convective cloud systems. The high penetration capability of the 13 GHz radar enables to obtain a complete, albeit horizontally under-sampled, view of deep convective storms. The smaller instantaneous field of view (IFOV) of the 35 GHz radar captures more precise information about the location and size of convective updrafts above 5–8 km height of most systems which were determined in the portion of storms where the mass flux peak is typically located. Finally, the lower mean Doppler velocity uncertainty of displaced phase center antenna (DPCA) radars makes them an ideal system for studying microphysics in shallow convection and frontal systems, as well as ice and mixed-phase clouds. It is demonstrated that a 94 GHz DCPA system can achieve retrieval errors as low as 0.05–0.15 mm for raindrop volume-weighted mean diameter and 25% for rime fraction (for a −10 dBZ echo).

Investigation on the role of aerosols on precipitation enhancement over Kerala during August 2018

Previous studies based on satellite data and model analysis have shown that the dust over Arabian Sea correlates positively with the Indian summer monsoon. During August 2018, over a period of a few days from August 13, the state of Kerala experienced anomalous rainfall, which was followed by heavy floods. In the present study, the meteorological factors and the aerosol conditions during this event are investigated. MERRA 2 reanalysis data suggests that the dust loading over the Arabian Sea during the month of August, during which the anomalous event of rainfall took place, is the highest in the last decade. Using CALIPSO aerosol vertical profiles, OMI Absorbing Aerosol Index and the HYSPLIT back trajectory analysis, higher altitude dust transport from the arid gulf region towards the Arabian sea and near to Kerala coast is confirmed during the heavy precipitation days and even prior to that. Changes in cloud properties like Cloud Fraction (CF), Cloud Top Temperature (CTT), Cloud Water Liquid Water Path (CWLWP) and Cloud Condensation Nuclei (CCN) with AOD variations during the period clearly indicate that there is a close relation between the aerosols and the cloud properties over the region. Observed CWLWP in the study on August 14 and 15, 2018 was 80% higher than the monthly average value. CCN concentration was increased by 23 percent during the severe rainy days of August when the CTT was about 16 K lower than the monthly mean value. Dust aerosols at altitudes of 2–4 km and further higher at 10–15 km, along with the deep convective clouds, point to the possibility of aerosol-cloud-precipitation interaction under conducive meteorological conditions. INSAT- 3D temperature profiles show an interesting enhancement of temperature (∼1 K) at altitudes ∼ 3 km, where elevated dust layers are noticed. This elevated heating could pave the way for moisture convergence and it is further confirmed from the INSAT derived Relative Humidity profiles. Investigation of vertical winds shows strong updrafts over the region during the period of heavy precipitation, indicative of the coexistence of moisture and CCN at higher altitudes. The study infers that the moisture built up over the region was excessive, enough to overwhelm the commonly observed semi direct effect caused by aerosols, and in contradiction, the aerosols amplify the cloud cover and precipitation over the Kerala region during the period of study. Thus the heavy dust loading over the South Eastern Arabian Sea region, near the west coast of Kerala, together with the conducive meteorological conditions and orography of the region led to intensified precipitation over Kerala during the mid of August 2018.

Evaluation of the relation between the convection and the upper tropospheric humidity: A perspective from Indian Geostationary satellite ‘Kalpana-1’ observations

High spatial and temporal resolution measurements from the Indian Geostationary satellite ‘Kalpana-1’ have been utilized to find the relation between the convection and upper tropospheric humidity (UTH). The analysis reveals that the UTH leads deep convection by 2–4 h over Indian landmass, which is attributed to the advection associated with tropical easterly jet rather than the direct overshooting monsoon convection. In contradiction, the UTH lags convection by 2–6 h over nearby oceans, indicating that direct overshooting convection plays a major role in moistening the upper troposphere. A new mechanism is proposed in which, if the UTH leads to deep convection, thick and dense high-altitude clouds form that can lead to negative feedback to convection through radiative cooling. If UTH lags convection then thin clouds form, thereby can result in positive feedback for convection. However, this feedback to convection is controlled by the presence of the TEJ.

Boundary conditions representation can determine simulated aerosol effects on convective cloud fields

Anthropogenic aerosols effect on clouds remains a persistent source of uncertainty in future climate predictions. The evolution of the environmental conditions controlling cloud properties is affected by the clouds themselves. Hence, aerosol-driven modifications of cloud properties can affect the evolution of the environmental thermodynamic conditions, which in turn could feed back to the cloud development. Here, by comparing many different cloud resolving simulations conducted with different models and under different environmental condition, we show that this feedback loop is strongly affected by the representation of the boundary conditions in the model. Specifically, we show that the representation of boundary conditions strongly impacts the magnitude of the simulated response of the environment to aerosol perturbations, both in shallow and deep convective clouds. Our results raise doubts about the significance of previous conclusions of aerosol-cloud feedbacks made based on simulations with idealised boundary conditions.

Estimate of daytime single-layer cloud base height from advanced baseline imager measurements

Cloud base height (CBH) is an important parameter to describe cloud state and is highly related to the vertical motions in the atmosphere. CBH information is critical for both aviation safety and synoptic analysis. In this study, daytime CBH is estimated directly from Geostationary Operational Environmental Satellite-R Series (GOES-16) Advanced Baseline Imager (ABI) level 1b data and the European Centre for Medium-Range Weather Forecasts' (ECMWF) fifth generation reanalysis (ERA5) data using the Gradient Boosted Regression Trees (GBRT) machine learning technique. The CBH estimate algorithm, which is named as GETCBH, covers the same areal extent as the full disk of the ABI/GOES-16 and only for single-layer clouds. The 2-years of CBH measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite is used as the label (which is the true value/class of the model output for regression/classification problem in machine learning terminology). A quality flag algorithm using another machine learning technique, the Gradient Boosted Decision Trees machine learning technique is developed to provide a confidence level for the CBH estimate. The evaluations show an overall root mean square error (RMSE) of 1.87 km and Pearson's correlation coefficient (Pearson's r) of 0.92 before any quality control. After excluding CBH estimates with low confidence (19.2% of all samples), the RMSE is reduced to 1.14 km, Pearson's r increases to 0.97, and 96% of the estimates are within 2 km of the CALIOP results. By analyzing model bias and feature importance, cloud phase information has the biggest impact on the CBH estimate, although all input features have positive impact on the estimate accuracy. Limited by the penetrability of CALIOP, GETCBH is valid for clouds with COD < 8.5. The CBH estimates have reduced accuracy (Pearson's r of 0.88) for optically thin clouds (clouds with cloud optical depth [COD] < 0.1) where little cloud information is contained in the ABI measurements, as well as for optically thick clouds (clouds with COD ≥ 3) where a larger proportion of opaque clouds is excluded. Furthermore, for the GBTCBH model using 9 months of CloudSat measurements as label, the CBH estimates are improved with an RMSE of 1.41 km and Pearson's r of 0.92. In a case study of Hurricane Dorian, CBHs for most of the single-layer clouds are successfully estimated with small errors and flagged with high confidence, for both high and low clouds. Deep convective clouds and multi-layer clouds, both of which are not included in the training, are reasonably flagged as low confidence with large CBH estimate errors. In this particular case, 65% of cloudy pixels have CBH estimate with high confidence in the scene. Daytime CBH with high spatial (2 km) and temporal (10 min) resolution can be derived from ABI measurements using this methodology.

Occurrence and growth of sub-50 nm aerosol particles in the Amazonian boundary layer

Abstract. New particle formation (NPF), referring to the nucleation of molecular clusters and their subsequent growth into the cloud condensation nuclei (CCN) size range, is a globally significant and climate-relevant source of atmospheric aerosols. Classical NPF exhibiting continuous growth from a few nanometers to the Aitken mode around 60–70 nm is widely observed in the planetary boundary layer (PBL) around the world but not in central Amazonia. Here, classical NPF events are rarely observed within the PBL, but instead, NPF begins in the upper troposphere (UT), followed by downdraft injection of sub-50 nm (CN&lt;50) particles into the PBL and their subsequent growth. Central aspects of our understanding of these processes in the Amazon have remained enigmatic, however. Based on more than 6 years of aerosol and meteorological data from the Amazon Tall Tower Observatory (ATTO; February 2014 to September 2020), we analyzed the diurnal and seasonal patterns as well as meteorological conditions during 254 of such Amazonian growth events on 217 event days, which show a sudden occurrence of particles between 10 and 50 nm in the PBL, followed by their growth to CCN sizes. The occurrence of events was significantly higher during the wet season, with 88 % of all events from January to June, than during the dry season, with 12 % from July to December, probably due to differences in the condensation sink (CS), atmospheric aerosol load, and meteorological conditions. Across all events, a median growth rate (GR) of 5.2 nm h−1 and a median CS of 1.1 × 10−3 s−1 were observed. The growth events were more frequent during the daytime (74 %) and showed higher GR (5.9 nm h−1) compared to nighttime events (4.0 nm h−1), emphasizing the role of photochemistry and PBL evolution in particle growth. About 70 % of the events showed a negative anomaly of the equivalent potential temperature (Δθe′) – as a marker for downdrafts – and a low satellite brightness temperature (Tir) – as a marker for deep convective clouds – in good agreement with particle injection from the UT in the course of strong convective activity. About 30 % of the events, however, occurred in the absence of deep convection, partly under clear-sky conditions, and with a positive Δθe′ anomaly. Therefore, these events do not appear to be related to downdraft transport and suggest the existence of other currently unknown sources of sub-50 nm particles.

Percentage occurrence of global tilted deep convective clouds under strong vertical wind shear

The percentage occurrence of titled deep convective clouds (DCCs) is rarely examined but it is crucial to overcome the challenges of precise measurement of rainfall intensity and location during dreadful weather events. Present study is carried out with this objective and analysed 2451 globally distributed DCCs identified by Ku-band (13.6 GHz) radar reflectivity profiles of Dual-frequency Precipitation Radar aboard Global Precipitation Measurement mission under varying conditions of environmental vertical wind shear (EVWS) during 2018. Globally (tropics) 60.68% (55.29%) of DCCs that produced intense rain (>50 mm/hr) are strengthened under strong EVWS and thus may have possibility of vertically tilted structure. Substantial 60.49% of DCCs that developed under strong EVWS grow deeper (up to 12 km) in atmosphere. Statistics on the global distribution of DCCs developed in strong EVWS with different categories of rainfall and cloud height would be an important source of information for precise assessment of rainfall distribution, especially during extreme weather.

The Greater Mekong Subregion (GMS) and tropical expansion: A regional study of convection and precipitation

A series of data sets including brightness temperature from HIRS-UTWV, high cloud cover, precipitation and evaporation from ERA-Interim reanalysis data, and deep convective cloud from ISCCP were used to examine the latitudinal changes of the Hadley cell in the Greater Mekong Subregion (GMS) over the 1979–2018 period. In the study region, a pronounce poleward expansion was found during the winter season using three metrics of expansion: latitude of maximum brightness temperature associated with the anticyclonic center; latitude of zero crossing of precipitation minus evaporation, marking the extent of the tropical region; and latitude where high cloud cover reaches 50% of its maximum tropical value. However, no trends were discovered for the summer season. During the study period, there was an increase in equatorial convection as indicated by increased high cloud cover features. When precipitation minus evaporation was less than 0, there was diminishing dry zone evidence.

The Influence of Shallow Cloud Populations on Transitions to Deep Convection in the Amazon

Abstract In this study, a pair of convection-permitting (2-km grid spacing), month-long, wet-season Weather Research and Forecasting (WRF) Model simulations with and without the eddy-diffusivity mass-flux (EDMF) scheme are performed for a portion of the Green Ocean Amazon (GoAmazon) 2014/15 field campaign period. EDMF produces an ensemble of subgrid-scale convective plumes that evolve in response to the boundary layer meteorological conditions and can develop into shallow clouds. The objective of this study is to determine how different treatments of shallow cumulus clouds (i.e., with and without EDMF) impact the total cloud population and precipitation across the Amazonian rain forest, with emphasis on impacts on the likelihood of shallow-to-deep convection transitions. Results indicate that the large-scale synoptic conditions in the EDMF and control simulations are nearly identical; however, on the local scale their rainfall patterns diverge drastically and the biases decrease in EDMF. The EDMF scheme significantly increases the frequency of shallow clouds, but the frequencies of deep clouds are similar between the simulations. Deep convective clouds are tracked using a cloud-tracking algorithm to examine the impact of shallow cumulus on the surrounding ambient environment where deep convective clouds initiate. Results suggest that a rapid increase of low-level cloudiness acts to cool and moisten the low to midtroposphere during the day, favoring the transition to deep convection.

Environmental Response in Coupled Energy and Water Cloud Impact Parameters Derived from A-Train Satellites, ERA-Interim, and MERRA-2

Abstract Understanding the connections between latent heating from precipitation and cloud radiative effects is essential for accurately parameterizing cross-scale links between cloud microphysics and global energy and water cycles in climate models. Although commonly examined separately, this study adopts two cloud impact parameters (CIPs), the surface radiative cooling efficiency Rc and atmospheric radiative heating efficiency Rh, that explicitly couple cloud radiative effects and precipitation to characterize how efficiently precipitating cloud systems influence the energy budget and water cycle using A-Train observations and two reanalyses. These CIPs exhibit distinct global distributions that suggest cloud energy and water cycle coupling are highly dependent on cloud regime. The dynamic regime ω500 controls the sign of Rh, whereas column water vapor (CWV) appears to be the larger control on the magnitude. The magnitude of Rc is highly coupled to the dynamic regime. Observations show that clouds cool the surface very efficiently per unit rainfall at both low and high sea surface temperature (SST) and CWV, but reanalyses only capture the former. Reanalyses fail to simulate strong Rh and moderate Rc in deep convection environments but produce stronger Rc and Rh than observations in shallow, warm rain systems in marine stratocumulus regions. Although reanalyses generate fairly similar climatologies in the frequency of environmental states, the response of Rc and Rh to SST and CWV results in systematic differences in zonal and meridional gradients of cloud atmospheric heating and surface cooling relative to A-Train observations that may have significant implications for global circulations and cloud feedbacks. Significance Statement Studying climate change requires understanding coupled interactions between clouds, precipitation, and their environment. Here we calculate two parameters to reveal how efficiently clouds can heat the atmosphere or cool the surface per unit rain. The satellite observations and reanalyses show similar global patterns, but there are some differences in areas of deep convection and low cloud regions. Examination of these parameters as a function of their environment shows that reanalyses cool the atmosphere too much per unit rain in environments with low sea surface temperatures and water vapor. Vertical velocity determines whether clouds heat or cool the atmosphere. Both observations and reanalyses suggest that water vapor is the stronger control on how much clouds heat the atmosphere per unit rain.