Estimation of Latent Heat Profiles Using TRMM Combined Radar/Radiometer Measurements
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microwave radiometer raindrop size distribution (D↗
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Backscattering enhancement for Marshall-Palmer distributed rains for a W-band nadir-pointing radar with a finite beam width
In this paper, we expand the previous theory to be applied to a generic drop size distribution with spheroidal raindrops including spherical raindrops. Results will be used to discuss the multiple scattering effects on the backscatter measurements acquired by a W-band nadir-pointing radar.
weather radar↗
Evaluation of Cloud-Resolving and Limited Area Model Intercomparison Simulations Using TWP-ICE Observations: Precipitation Microphysics - Part 2
Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (mu) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a mu of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing mu to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.
three dimensional models↗
Rain-Mapping Radar
Orbiting radar system measures rates of rainfall from 0.5 to 60 mm/h. Radar waves scattered and absorbed by rainfall to extents depending on wavelength, polarization, rate of rainfall, and distribution of sizes and shapes of raindrops. Backscattered radar signal as function of length of path through rain used to infer detailed information about rain. Accumulated radar return signals processed into global maps of monthly average rainfall for use in climatological studies.
Im, K. E.↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fewer droplets, larger sized develop due to the greater condensational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fever droplets, larger size develop due to greater condencational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.
Tao, Wei-Kuo↗
The Role of Aerosols on Precipitation Processes
Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.
Tao, Wei-Kuo↗
The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.
Tao, Wei-Kuo↗
Hail Size Distribution Mapping
A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at . 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, ). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.
Source record↗
A new radar technique for satellite rainfall algorithm development
A potential new radar parameter was investigated for measuring rainfall, namely the summation of the phase shifts at horizontal and vertical polarizations due to propagation through precipitation. The proposed radar technique has several potential advantages over other approaches because it is insensitive to the drop size distribution and to the shapes of the raindrops. Such a parameter could greatly assist the development of satellite rainfall estimation algorithms by providing comparative measurements near the ground. It could also provide hydrologically useful information for such practical applications as urban hydrology. Results of the investigation showed that the parameters can not be measured by radar. However, a closely related radar parameter, propagation differential phase shift, can be readily measured using a polarization diversity radar. It is recommended that propagation differential phase shift be further investigated and developed for radar monitoring of rainfall using a polarization agile radar. It is also recommended that a prototype multiple frequency microwave link be constructed for attenuation measurements not possible by existing radar systems.
Jameson, Arthur R.↗
Estimating the path-average rainwater content and updraft speed along a microwave link
There is a scarcity of methods for accurately estimating the mass of rainwater rather than its flux. A recently proposed technique uses the difference between the observed rates of attenuation A with increasing distance at 38 and 25 GHz, A(38-25), to estimate the rainwater content W. Unfortunately, this approach is still somewhat sensitive to the form of the drop-size distribution. An alternative proposed here uses the ratio A38/A25 to estimate the mass-weighted average raindrop size Dm. Rainwater content is then estimated from measurements of polarization propagation differential phase shift (Phi-DP) divided by (1-R), where R is the mass-weighted mean axis ratio of the raindrops computed from Dm. This paper investigates these two water-content estimators using results from a numerical simulation of observations along a microwave link. From these calculations, it appears that the combination (R, Phi-DP) produces more accurate estimates of W than does A38-25. In addition, by combining microwave estimates of W and the rate of rainfall in still air with the mass-weighted mean terminal fall speed derived using A38/A25, it is possible to detect the potential influence of vertical air motion on the raingage-microwave rainfall comparisons.
Jameson, Arthur R.↗
Comparison of two different raindrop disdrometers
Different types of impact sensors, used for the measurement of drop size distribution, are described and compared. All of them generate an electrical output which is to a first order a function of the velocity and mass of impacting drops within the size range of 0.25 to 5.0 mm. The disdrometers discussed include an active styrofoam disdrometer, a passive plexiglass sensor, and a cast epoxy disdrometer sensor. The sensors are calibrated by dropping water drops of known size on the sensor, and using an oscilloscope to measure peak amplitude. Similar response characteristics are observed for the active styrofoam disdrometer and the passive plexiglass and brass sensors. The cast epoxy impact sensor is noted to have a faster response and to be more sturdy than the styrofoam or plexiglass sensors.
Rowland, J. R.↗
Assessment of the contribution of differential polarization to improved rainfall measurements
A measurement technique employing the differential reflectivity factor Z(DR) and the horizontal polarization reflectivity factor Z(H) is the basis of the present study of the effects of variations in the shape or breadth of the drop size distribution (DSD) on rainfall parameters. Theoretical expressions are derived for rainfall rate, liquid water content W, and median volume diameter D(O) in terms of Z(DR), Z(H), and size distribution-dependent factors. The latter calculations assume backscattering cross sections for oblate, nonoscillating raindrops falling in still air with equilibrium shapes. These expressions are used to quantitatively assess the effects of changes in DSD breadth on values of R, W, and D(O) deduced from Z(DR) and Z(H).
Ulbrich, C. W.↗
A Summary of Large Raindrop Observations from GPM GV Field Campaigns
NASA's Global Precipitation Measurement Mission (GPM) has conducted as series of Ground Validation (GV) studies to assist algorithm development for the GPM core satellite. Characterizing the drop size distribution (DSD) for different types of precipitation systems is critical in order to accurately estimate precipitation across the majority of the planet. Thus far, GV efforts have sampled DSDs in a variety of precipitation systems from Finland to Oklahoma. This dataset consists of over 33 million raindrops sampled by GPM GV's two‐dimensional video disdrometers (2DVD) and includes RSD observations from the LPVEx, MC3E, GCPEx, HyMEx and IFloodS campaigns as well as from GV sites in Huntsville, AL and Wallops Island, VA. This study focuses on the larger end of the raindrop size spectrum, which greatly influences radar reflectivity and has implications for moment estimation. Thus knowledge of the maximum diameter is critical to GPM algorithm development. There are over 24,000 raindrops exceeding 5 mm in diameter contained within this disdrometer dataset. The largest raindrops in the 2DVD dataset (>7‐8 mm in diameter) are found within intense convective thunderstorms, and their origins are believed to be hailstones. In stratiform rainfall, large raindrops have also been found to fall from lower and thicker melting layers. The 2DVD dataset will be combined with that collected by dual‐polarimetric radar and aircraft particle imaging probes to "follow" the vertical evolution of the DSD tail (i.e., retrace the large drops from the surface to their origins aloft).
Gatlin, Patrick N.↗