Zhe Feng

Advection, moistening, and shallow‐to‐deep convection transitions during the initiation and propagation of Madden‐Julian Oscillation

Using observations from the 2011 AMIE/DYNAMO field campaign over the Indian Ocean and a high-resolution regional model simulation, the processes that lead to the rapid shallow-to-deep convection transitions associated with the initiation and eastward propagation of the Madden-Julian Oscillation (MJO) are examined. By tracking the evolution of the depth of several thousand individual model simulated precipitation features, the role of and the processes that control the observed midtropospheric moisture buildup ahead of the detection of deep convection are quantified at large and convection scales. The frequency of shallow-to-deep convection transitions is found to be sensitive to this midlevel moisture and large-scale uplift. This uplift along with the decline of large-scale drying by equator-ward advection causes the moisture buildup leading to the initiation of the MJO. Convection scale moisture variability and uplift, and large-scale zonal advection play secondary roles.

Top‐of‐atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems

[1] A new hybrid classification algorithm to objectively identify Deep Convective Systems (DCSs) in radar and satellite observations has been developed. This algorithm can classify the convective cores (CC), stratiform rain (SR) area and nonprecipitating anvil cloud (AC) from the identified DCSs through an integrative analysis of ground-based scanning radar and geostationary satellite data over the Southern Great Plains. In developing the algorithm, AC is delineated into transitional, thick, and thin components. While there are distinct physical/dynamical differences among these subcategories, their top-of-atmosphere (TOA) radiative fluxes are not significantly different. Therefore, these anvil subcategories are grouped as total anvil, and the radiative impact of each DCS component on the TOA radiation budget is quantitatively estimated. We found that more DCSs occurred during late afternoon, producing peak AC fraction right after sunset. AC covers 3 times the area of SR and almost an order of magnitude larger than CC. The average outgoing longwave (LW) irradiances are almost identical for CC and SR, while slightly higher for AC. Compared to the clear-sky average, the reflected shortwave (SW) fluxes for the three DCS components are greater by a factor of 2–3 and create a strong cooling effect at TOA. The calculated SW and LW cloud radiative forcing (CRF) of AC contribute up to 31% of total NET CRF, while CC and SR contribute only 4 and 11%, respectively. The hybrid classification further lays the groundwork for studying the life cycle of DCS and improvements in geostationary satellite IR-based precipitation retrievals.

Constructing a Merged Cloud–Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

AbstractTo improve understanding of the convective processes key to the Madden–Julian oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and the Atmospheric Radiation Measurement Program (ARM) MJO Investigation Experiment (AMIE) collected 4 months of observations from three radars—the S-band dual-polarization Doppler radar (S-Pol), the C-band Shared Mobile Atmospheric Research and Teaching Radar (SMART-R), and Ka-band ARM zenith radar (KAZR)—along with radiosonde and comprehensive surface meteorological instruments on Addu Atoll, Maldives, in the tropical Indian Ocean. One DYNAMO/AMIE hypothesis suggests that the evolution of shallow and congestus cloud populations is essential to the initiation of the MJO. This study focuses on evaluating the ability of these three radars to document the full spectrum of cloud populations and to construct a merged cloud–precipitation radar dataset that can be used to test this hypothesis. Comparisons between collocated observations from the three radars show ...

Life cycle of midlatitude deep convective systems in a Lagrangian framework

Deep Convective Systems (DCSs) consist of intense convective cores (CC), large stratiform rain (SR) regions, and extensive non-precipitating anvil clouds (AC). This study focuses on the evolution of these three components and the factors that affect convective AC production. An automated satellite tracking method is used in conjunction with a recently developed multi-sensor hybrid classification to analyze the evolution of DCS structure in a Lagrangian framework over the central United States. Composite analysis from 4221 tracked DCSs during two warm seasons (May-August, 2010-2011) shows that maximum system size correlates with lifetime, and longer-lived DCSs have more extensive SR and AC. Maximum SR and AC area lag behind peak convective intensity and the lag increases linearly from approximately 1-hour for short-lived systems to more than 3-hours for long-lived ones. The increased lag, which depends on the convective environment, suggests that changes in the overall diabatic heating structure associated with the transition from CC to SR and AC could prolong the system lifetime by sustaining stratiform cloud development. Longer-lasting systems are associated with up to 60% higher mid-tropospheric relative humidity and up to 40% stronger middle to upper tropospheric wind shear. Regression analysis shows that the areal coverage of thick AC is strongly correlated with the size of CC, updraft strength, and SR area. Ambient upper tropospheric wind speed and wind shear also play an important role for convective AC production where for systems with large AC (radius greater than 120-km) they are 24% and 20% higher, respectively, than those with small AC (radius=20 km).

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

The changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in the central United States are dominated by mesoscale convective systems (MCSs), the largest type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms.

Substantial convection and precipitation enhancements by ultrafine aerosol particles

Up with ultrafine aerosol particles Ultrafine aerosol particles (smaller than 50 nanometers in diameter) have been thought to be too small to affect cloud formation. Fan et al. show that this is not the case. They studied the effect of urban pollution transported into the otherwise nearly pristine atmosphere of the Amazon. Condensational growth of water droplets around the tiny particles releases latent heat, thereby intensifying atmospheric convection. Thus, anthropogenic ultrafine aerosol particles may exert a more important influence on cloud formation processes than previously believed. Science, this issue p. 411 Water droplet condensation by ultrafine aerosol particles fuels more intense atmospheric convection. Aerosol-cloud interactions remain the largest uncertainty in climate projections. Ultrafine aerosol particles smaller than 50 nanometers (UAP<50) can be abundant in the troposphere but are conventionally considered too small to affect cloud formation. Observational evidence and numerical simulations of deep convective clouds (DCCs) over the Amazon show that DCCs forming in a low-aerosol environment can develop very large vapor supersaturation because fast droplet coalescence reduces integrated droplet surface area and subsequent condensation. UAP<50 from pollution plumes that are ingested into such clouds can be activated to form additional cloud droplets on which excess supersaturation condenses and forms additional cloud water and latent heating, thus intensifying convective strength. This mechanism suggests a strong anthropogenic invigoration of DCCs in previously pristine regions of the world.

Evaluation of convection-permitting model simulations of cloud populations associated with the Madden-Julian Oscillation using data collected during the AMIE/DYNAMO field campaign

Regional convection-permitting model simulations of cloud populations observed during the 2011 Atmospheric Radiation Measurement (ARM) Madden-Julian Oscillation Investigation Experiment/Dynamics of the Madden-Julian Oscillation Experiment (AMIE/DYNAMO) field campaign are evaluated against ground-based radar and ship-based observations. Sensitivity of model simulated reflectivity, surface rain rate, and cold pool statistics to variations of raindrop breakup/self-collection parameters in four state-of-the-art two-moment bulk microphysics schemes in the Weather Research and Forecasting (WRF) model is examined. The model simulations generally overestimate reflectivity from large and deep convective cells, and underestimate stratiform rain and the frequency of cold pools. In the sensitivity experiments, introduction of more aggressive raindrop breakup or decreasing the self-collection efficiency increases the cold pool occurrence frequency in all of the simulations, and slightly reduces the reflectivity and precipitation statistics bias in some schemes but has little effect on the overall mean surface precipitation. Both the radar observations and model simulations of cloud populations show an approximate power law relationship between convective echo-top height and equivalent convective cell radius.

Environment and the Lifetime of Tropical Deep Convection in a Cloud-Permitting Regional Model Simulation

AbstractBy applying a cloud-tracking algorithm to tropical convective systems in a regional high-resolution model simulation, this study documents the environmental conditions before and after convective systems are initiated over ocean and land by following them during their lifetime. The comparative roles of various mechanisms of convection–environment interaction on the longevity of convective systems are quantified. The statistics of lifetime, maximum area, and propagation speed of the simulated deep convection agree well with geostationary satellite observations.Among the environmental variables considered, lifetime of convective systems is found to be most related to midtropospheric moisture before as well as after the initiation of convection. Over ocean, convective systems enhance surface fluxes through the associated cooling and drying of the boundary layer as well as increased wind gusts. This process appears to play a minor positive role in the longevity of systems. For systems of equal lifetim...

Simulations of Cloud-Radiation Interaction Using Large-Scale Forcing Derived from the CINDY/DYNAMO Northern Sounding Array

The recently completed CINDY/DYNAMO field campaign observed two Madden-Julian oscillation (MJO) events in the equatorial Indian Ocean from October to December 2011. Prior work has indicated that the moist static energy anomalies in these events grew and were sustained to a significant extent by radiative feedbacks. We present here a study of radiative fluxes and clouds in a set of cloud-resolving simulations of these MJO events. The simulations are driven by the large-scale forcing data set derived from the DYNAMO northern sounding array observations, and carried out in a doubly periodic domain using the Weather Research and Forecasting (WRF) model. Simulated cloud properties and radiative fluxes are compared to those derived from the S-PolKa radar and satellite observations. To accommodate the uncertainty in simulated cloud microphysics, a number of single-moment (1M) and double-moment (2M) microphysical schemes in the WRF model are tested. The 1M schemes tend to underestimate radiative flux anomalies in the active phases of the MJO events, while the 2M schemes perform better, but can overestimate radiative flux anomalies. All the tested microphysics schemes exhibit biases in the shapes of the histograms of radiative fluxes and radar reflectivity. Histograms of radiative fluxes and brightness temperature indicate that radiative biases are not evenly distributed; the most significant bias occurs in rainy areas with OLR less than 150 W/m2 in the 2M schemes. Analysis of simulated radar reflectivities indicates that this radiative flux uncertainty is closely related to the simulated stratiform cloud coverage. Single-moment schemes underestimate stratiform cloudiness by a factor of 2, whereas 2M schemes simulate much more stratiform cloud.

Convective cloud vertical velocity and mass‐flux characteristics from radar wind profiler observations during GoAmazon2014/5

A radar wind profiler (RWP) dataset collected during the two-year DOE ARM Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign is used to estimate convective cloud vertical velocity, area fraction and mass flux profiles. Vertical velocity observations are presented using cumulative frequency histograms and weighted-mean profiles to provide insights in a manner suitable for GCM-model scale comparisons (spatial domains from 20 km to 60 km). Convective profile sensitivity to changes in environmental conditions and seasonal regime controls is also considered. Aggregate and ensemble average vertical velocity, convective area fraction and mass flux profiles, as well as magnitudes and relative profile behaviors, are found consistent with previous studies. Updrafts and downdrafts increase in magnitude with height to mid-levels (6 to 10 km), with updraft area also increasing with height. Updraft mass flux profiles similarly increase with height, showing a peak in magnitude near 8 km. Downdrafts are observed to be most frequent below the freezing level, with downdraft area monotonically decreasing with height. Updraft and downdraft profile behaviors are further stratified according to environmental controls. These results indicate stronger vertical velocity profile behaviors under higher CAPE and lower low-level moisture conditions. Sharp contrasts in convective area fraction and mass flux profiles are most pronounced when retrievals are segregated according to Amazonian wet and dry season conditions. During this deployment, wet season regimes favored higher domain mass flux profiles, attributed to more frequent convection that offsets weaker average convective cell vertical velocities.