The estimation of convective mass flux from radar reflectivities

Atmospheric Chemistry and Physics, 2014

In this study the density of ice hydrometeors in tropical clouds is derived from a combined analysis of particle images from 2-D-array probes and associated reflectivities measured with a Doppler cloud radar on the same research aircraft. Usually, the mass-diameter m(D) relationship is formulated as a power law with two unknown coefficients (pre-factor, exponent) that need to be constrained from complementary information on hydrometeors, where absolute ice density measurement methods do not apply. Here, at first an extended theoretical study of numerous hydrometeor shapes simulated in 3-D and arbitrarily projected on a 2-D plan allowed to constrain the exponent βof the m(D) relationship from the exponent σ of the surface-diameter S(D) relationship, which is likewise written as a power law. Since S(D) always can be determined for real data from 2-D optical array probes or other particle imagers, the evolution of the m(D) exponent can be calculated. After that, the pre-factor α of m(D) is constrained from theoretical simulations of the radar reflectivities matching the measured reflectivities along the aircraft trajectory. The study was performed as part of the Megha-Tropiques satellite project, where two types of mesoscale convective systems (MCS) were investigated: (i) above the African continent and (ii) above the Indian Ocean. For the two data sets, two parameterizations are derived to calculate the vertical variability of m(D) coefficients α and β as a function of the temperature. Originally calculated (with T-matrix) and also subsequently parameterized m(D) relationships from this study are compared to other methods (from literature) of calculating m(D) in tropical convection. The significant benefit of using variable m(D) relations instead of a single m(D) relationship is demonstrated from the impact of all these m(D) relations on Z-CWC (Condensed Water Content) and Z-CWC-T-fitted parameterizations.

Vertical distribution of intense convective clouds over Indonesia has been studied using radar reflectivity factor (dBZ) data gathered from the latest 2A25 TRMM-Precipitation Radar (PR) product over a 10-year (1998-2007). The vertical distribution of dBZ at the PR pixel scale has been classified into two type of convective cells, i.e., cumulonimbus tower (CbT) and intense convective clouds (ICC) following the classification proposed by some previous studies. The CbT contains Z threshold 20 dBZ at 12 km altitude with at least 9 km deep and the ICC contains Z threshold 30 and 41 dBZ at 8 and 3 km, respectively. It is found that intense convective cloud is more frequently observed over land such as Sumatra, Kalimantan and Jawa than over ocean areas. Downward increasing (DI) pattern of dBZ toward the surface found in CbT over coastal area of Sumatra and Indian ocean. ICC8 and ICC3 shows downward decreasing (DD) pattern for all locations.

IEEE Transactions on Geoscience and Remote Sensing, 2016

Journal of Geophysical Research, 2009

Over the last few years a new type of global climate model (GCM) has emerged in which a cloud-resolving model is embedded into each grid cell of a GCM. This new approach is frequently called a multiscale modeling framework (MMF) or superparameterization. In this article we present a comparison of MMF output with radar observations from the NASA CloudSat mission, which uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. We account for radar detection limits by simulating the 94 GHz radar reflectivity that CloudSat would observe from the high-resolution cloud-resolving model output produced by the MMF. Overall, the MMF does a good job of reproducing the broad pattern of tropical convergence zones, subtropical belts, and midlatitude storm tracks, as well as their changes in position with the annual solar cycle. Nonetheless, the comparison also reveals a number of model shortfalls including (1) excessive hydrometeor coverage at all altitudes over many convectively active regions, (2) a lack of low-level hydrometeors over all subtropical oceanic basins, (3) excessive low-level hydrometeor coverage (principally precipitating hydrometeors) in the midlatitude storm tracks of both hemispheres during the summer season (in each hemisphere), and (4) a thin band of low-level hydrometeors in the Southern Hemisphere of the central (and at times eastern and western) Pacific in the MMF, which is not observed by CloudSat. This band resembles a second much weaker ITCZ but is restricted to low levels.

Pure and Applied Geophysics, 2007

Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.

Abstract The daytime atmospheric convective boundary layer (CBL) is characterized by strong turbulence that is primarily caused by buoyancy forced from the heated underlying surface. The present study considers a combination of radar and large eddy simulation (LES) techniques to characterize the CBL. Data representative of the daytime CBL with wind shear have been generated by LES, and used in the virtual boundary layer radar (BLR) with multiple vertical and off-vertical beams.

Meteorology and Atmospheric Physics, 2010

This study examines the time–height variation and structure of a tropical mesoscale convective system (TMCS). Convection experiments using VHF (53 MHz) radar aimed at improving the understanding of the vertical structure of TMCS occurred over Gadanki (13.5°N, 79.2°E), India during 21–22 June 2000 has been selected for the study. The time–height variations of reflectivity and vertical velocity exhibits four distinct patterns and have been used to classify four subjectively identified types of echoes; viz., formative, mature, transition zone and stratiform regions associated with TMCS. Average vertical velocity profiles were distinctive for each region. The mean vertical motion is upward at all levels in the troposphere during the formative phase. The vertical motion in the mature region is downward in the lower troposphere and upward in the middle and upper troposphere. The maximum upward motion is found in the middle troposphere and secondary maxima near the tropopause level. The transition zone is characterized by strong downdraft in the lower troposphere with local pockets of updrafts in the middle and upper troposphere. The magnitude of the mean vertical motion is considerably reduced in the stratiform region and is downward in the lower troposphere and upward in the upper troposphere. Time–height variation of reflectivity has been analyzed separately for each region. The observed diminished echo zone and tropopause break/weakening during the mature phase and two enhanced reflectivity zone in the stratiform region is also observed. A Cloud System Resolving Model (CSRM) simulation of the same event has been carried out. The CSRM simulations were able to capture the structure of the storm and are consistent with the observations. The model output in conjunction with observations has been used to validate the hypothesis.

Monthly Weather Review, 2006

In this two-part paper, the impact of level-II Weather Surveillance Radar-1988 Doppler (WSR-88D) radar reflectivity and radial velocity data on the prediction of a cluster of tornadic thunderstorms in the Advanced Regional Prediction System (ARPS) model is studied. Radar reflectivity data are used primarily in a cloud analysis procedure that retrieves the amount of hydrometeors and adjusts in-cloud temperature, moisture, and cloud fields, while radial velocity data are analyzed through a three-dimensional variational (3DVAR) data assimilation scheme that contains a 3D mass divergence constraint in the cost function. In Part I, the impact of the cloud analysis and modifications to the scheme are discussed. In this part, the impact of radial velocity data and the mass divergence constraint in the 3DVAR cost function are studied.

Journal of Climate, 2001

A cumulus parameterization based on mass fluxes, convective-scale vertical velocities, and mesoscale effects has been incorporated in an atmospheric general circulation model (GCM). Most contemporary cumulus parameterizations are based on convective mass fluxes. This parameterization augments mass fluxes with convectivescale vertical velocities as a means of providing a method for incorporating cumulus microphysics using vertical velocities at physically appropriate (subgrid) scales. Convective-scale microphysics provides a key source of material for mesoscale circulations associated with deep convection, along with mesoscale in situ microphysical processes. The latter depend on simple, parameterized mesoscale dynamics. Consistent treatment of convection, microphysics, and radiation is crucial for modeling global-scale interactions involving clouds and radiation.