scholarly journals Hydrometeor Classification of Winter Precipitation in Northern China Based on Multi-Platform Radar Observation System

2021 ◽  
Vol 13 (24) ◽  
pp. 5070
Author(s):  
Yichen Chen ◽  
Xiang’e Liu ◽  
Kai Bi ◽  
Delong Zhao
Keyword(s):  
Numerical Simulations ◽  
Microwave Radiometer ◽  
Northern China ◽  
Winter Precipitation ◽  
Radar Observation ◽  
Cloud System ◽  
Observation System ◽  
Ice Crystal ◽  
Ka Band ◽  
Microphysical Processes

Hydrometeor classification remains a challenge in winter precipitation cloud systems. To address this issue, 42 snowfall events were investigated based on a multi-platform radar observation system (i.e., X-band dual-polarization radar, Ka-band millimeter wave cloud radar, microwave radiometer, airborne equipment, etc.) in the mountainous region of northern China from 2016 to 2020. A fuzzy logic classification method is proposed to identify the particle phases, and the retrieval result was further verified with ground-based radar observation. Moreover, the hydrometeor characteristics were compared with the numerical simulations to clarify the reliability of the proposed hydrometeor classification approach. The results demonstrate that the X-/Ka- band radars are capable of identifying hydrometeor phases in winter precipitation in accordance with both ground observations and numerical simulations. Three particle categories, including snow, graupel and the mixture of snow and graupel are also detected in the winter precipitation cloud system, and there are three vertical layers identified from top to bottom, including the ice crystal layer, snow-graupel mixed layer and snowflake layer. Overall, this study has the potential for improving the understanding of microphysical processes such as freezing, deposition and aggregation of ice crystal particles in the winter precipitation cloud system.

Exploring the representation of clouds and humidity in the Arctic with cloud-resolving simulations using ICON-LEM

2021 ◽  
Author(s):  
Theresa Kiszler ◽  
Giovanni Chellini ◽  
Kerstin Ebell ◽  
Stefan Kneifel ◽  
Vera Schemann
Keyword(s):  
Microwave Radiometer ◽  
Remote Sensing Data ◽  
Large Data ◽  
Research Unit ◽  
Rain Gauge ◽  
The Arctic ◽  
Arctic Amplification ◽  
Data Set ◽  
Microphysical Processes ◽  
Mixed Phase Clouds

<p>The discussions around Arctic Amplification have led to extensive research, as done in the transregional collaboration (AC)³. One focus are the feedback mechanisms that are strengthening or weakening the warming. Several of these feedbacks involve moisture in the atmosphere in all phases. To understand these better we have been running and analysing daily cloud-resolving simulations. We performed these simulations for a region more strongly affected by the warming around Ny-Ålesund (Svalbard), which is challenging due to its diverse surface properties and mountainous surrounding. We have created an outstandingly large data set of several months of these simulations with 600 m resolution, using the Icosahedral non-hydrostatic model in the large-eddy mode (ICON-LEM).</p> <p>To gain some understanding of how well the model can represent such a complex location, we evaluated the performance of the model. For this, we used a range of observations from the measurement super-site located at Ny-Ålesund. This included radiosondes [1], a rain gauge, a microwave radiometer and further processed remote sensing data. Combining the measurements and simulations enables us to provide thorough statistics for different variables connected to clouds and to establish an understanding of how well they are represented.</p> <p>We show that the model is capable of simulating the two distinct flow regimes in the boundary layer and the free troposphere. Further, we found a tendency in the model to misrepresent liquid and mixed-phase clouds as purely ice clouds. Though the water vapour is well captured, we found further steps in the chain towards precipitation formation are insufficiently represented. Through the use of forward simulations and expanded model output, we can continue to get a better picture of possibilities to understand and improve the microphysical processes.</p> <p><em>This work was supported by the</em><em> DFG funded Transregio-project TR 172 “Arctic Amplification </em>(AC)3<em>“.</em></p> <p><strong>References</strong></p> <p>[1] M. Maturilli, High resolution radiosonde measurements from station Ny-Ålesund (2017-04 et seq). <em>Alfred</em> <em>Wegener Institute - Research Unit Potsdam, PANGAEA</em>, https://doi.org/10.1594/PANGAEA.914973 (2020)</p>

scholarly journals Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

2015 ◽  
Vol 8 (9) ◽  
pp. 3685-3699 ◽  
Author(s):  
A. Chandra ◽  
C. Zhang ◽  
P. Kollias ◽  
S. Matrosov ◽  
W. Szyrmer
Keyword(s):  
Rain Rate ◽  
Tropical Indian Ocean ◽  
Rain Gauge ◽  
Signal Attenuation ◽  
Ka Band ◽  
Automated Algorithm ◽  
Atmospheric Radiation Measurement ◽  
Microphysical Processes ◽  
The Tropics ◽  
Rain Rates

Abstract. The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong signal attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-band (35-GHz) ARM (Atmospheric Radiation Measurement) zenith radars (KAZR). A 1-dimensional, simple, steady state microphysical model is used to estimate impacts of microphysical processes and attenuation on the profiles of radar observables at 35-GHz and thus provide criteria for identifying situations when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for signal saturation and wet radome effects. The algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity–rain rate (Ze–R) relation. Observations collected by the KAZR, rain gauge, disdrometer and scanning precipitating radars during the DYNAMO/AMIE field campaign at the Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The differences in the rain accumulation from the proposed algorithm are quantified. The results indicate that the proposed algorithm has a potential for deriving continuous rain rate statistics in the tropics.

Exploring the Diabatic Role of Ice Microphysical Processes in Two North Atlantic Summer Cyclones

2016 ◽  
Vol 144 (4) ◽  
pp. 1249-1272 ◽  
Author(s):  
C. Dearden ◽  
G. Vaughan ◽  
T. Tsai ◽  
J.-P. Chen
Keyword(s):  
Crystal Habit ◽  
Ice Crystal ◽  
Heating And Cooling ◽  
First Case ◽  
Storm Evolution ◽  
In Situ Observations ◽  
Microphysical Processes ◽  
Ice Production ◽  
The Impact

Abstract Numerical simulations are performed with the Weather Research and Forecasting Model to elucidate the diabatic effects of ice phase microphysical processes on the dynamics of two slow-moving summer cyclones that affected the United Kingdom during the summer of 2012. The first case is representative of a typical midlatitude storm for the time of year, while the second case is unusually deep. Sensitivity tests are performed with 5-km horizontal grid spacing and at lead times between 1 and 2 days using three different microphysics schemes, one of which is a new scheme whose development was informed by the latest in situ observations of midlatitude weather systems. The effects of latent heating and cooling associated with deposition growth, sublimation, and melting of ice are assessed in terms of the impact on both the synoptic scale and the frontal scale. The results show that, of these diabatic processes, deposition growth was the most important in both cases, affecting the depth and position of each of the low pressure systems and influencing the spatial distribution of the frontal precipitation. Cooling associated with sublimation and melting also played a role in determining the cyclone depth, but mainly in the more intense cyclone case. The effects of ice crystal habit and secondary ice production are also explored in the simulations, based on insight from in situ observations. However in these two cases, the ability to predict changes in crystal habit did not significantly impact the storm evolution, and the authors found no obvious need to parameterize secondary ice crystal production at the model resolutions considered.

scholarly journals Retrieval of cloud liquid water distributions from a single scanning microwave radiometer aboard a moving platform – Part 1: Field trial results from the Wakasa Bay experiment

2009 ◽  
Vol 9 (3) ◽  
pp. 12027-12064 ◽  
Author(s):  
D. Huang ◽  
A. Gasiewksi ◽  
W. Wiscombe
Keyword(s):  
Data Collection ◽  
Liquid Water ◽  
Microwave Radiometer ◽  
Three Dimensional ◽  
Observation System ◽  
Mobile Cloud ◽  
The Sea Of Japan ◽  
Inversion Algorithm ◽  
Cloud Liquid Water ◽  
Wakasa Bay

Abstract. Tomographic methods offer a new promise for retrieving three-dimensional distributions of cloud liquid water from path-integrated radiometric measurements by passive sensors. A mobile cloud tomography system using only a single scanning microwave radiometer has many advantages over a fixed system using multiple distinctly-located radiometers, e.g., efficient and flexible data collection. Part 1 (this paper) examines the results from a limited cloud tomography trial carried out during the 2003 AMSR-E validation campaign at Wakasa Bay of the Sea of Japan. During the tomographic test, the Polarimetric Scanning Radiometer (PSR) and Microwave Imaging Radiometer (MIR) aboard the NASA P-3 research aircraft scanned through a system of low-level clouds and thus provided a useful dataset for testing the cloud tomography method. We conduct three retrieval runs with a constrained inversion algorithm using, respectively the PSR, MIR, and combined PSR and MSR data. The liquid water paths calculated from the PSR retrieval are consistent with that from the MIR retrieval. The retrieved cloud field based on the combined data appears to be physically plausible and consistent with the cloud image obtained by a cloud radar. It is unfortunate that there were no in-situ cloud measurements during the experiment that can be used to quantitatively validate the tomographic retrievals. Nevertheless, we find that some vertically-uniform clouds appear at high altitudes in the retrieved fields where the radar image shows clear sky. This is likely due to flawed data collection geometry, which, in turn, is determined by the radiometer scan strategy, and aircraft altitude and moving speed. This sets the stage for Part 2 of this study that aims at possible improvements of the mobile cloud tomography approach by a group of sensitivity studies using observation system simulation experiments.

scholarly journals Impacts of Radiation and Cold Pools on the Intensity and Vortex Tilt of Weak Tropical Cyclones Interacting with Vertical Wind Shear

2020 ◽  
Vol 77 (2) ◽  
pp. 669-689 ◽  
Author(s):  
Rosimar Rios-Berrios
Keyword(s):  
Numerical Simulations ◽  
Tropical Cyclones ◽  
Structural Changes ◽  
Prediction Models ◽  
Weather Prediction ◽  
Vertical Wind Shear ◽  
Unexpected Finding ◽  
Cold Pools ◽  
Tropical Depressions ◽  
Microphysical Processes

Abstract Idealized numerical simulations of weak tropical cyclones (e.g., tropical depressions and tropical storms) in sheared environments indicate that vortex tilt reduction and convective symmetrization are key structural changes that can precede intensification. Through a series of ensembles of idealized numerical simulations, this study demonstrates that including radiation in the simulations affects the timing and variability of those structural changes. The underlying reason for those effects is a background thermodynamic profile with reduced energy available to fuel strong downdrafts; such a profile leads to weaker lower-tropospheric ventilation, greater azimuthal coverage of clouds and precipitation, and smaller vortex tilt with radiation. Consequently, the simulations with radiation allow for earlier intensification at stronger shear magnitudes than without radiation. An unexpected finding from this work is a reduction of both vortex tilt and intensity variability with radiation in environments with 5 m s−1 deep-layer shear. This reduction stems from reduced variability in nonlinear feedbacks between lower-tropospheric ventilation, cold pools, convection, and vortex tilt. Sensitivity experiments confirm the relationship between those processes and suggest that microphysical processes (e.g., rain evaporation) are major sources of uncertainty in the representation of weak, sheared tropical cyclones in numerical weather prediction models.

A Parameterization of the Microphysical Processes Forming Many Types of Winter Precipitation

2010 ◽  
Vol 67 (5) ◽  
pp. 1492-1508 ◽  
Author(s):  
Julie M. Thériault ◽  
Ronald E. Stewart
Keyword(s):  
Liquid Fraction ◽  
Winter Precipitation ◽  
The Other ◽  
Mass Content ◽  
Microphysics Scheme ◽  
Winter Storms ◽  
Precipitation Characteristics ◽  
Wet Snow ◽  
Precipitation Type ◽  
Microphysical Processes

Abstract Several types of precipitation, such as freezing rain, ice pellets, and wet snow, are commonly observed during winter storms. The objective of this study is to better understand the formation of these winter precipitation types. To address this issue, detailed melting and refreezing of precipitation was added onto an existing bulk microphysics scheme. These modifications allow the formation of mixed-phase particles and these particles in turn lead to, or affect, the formation of many of the other types of precipitation. The precipitation type characteristics, such as the mass content, liquid fraction, and threshold diameters formed during a storm over St John’s, Newfoundland, Canada, are studied and compared with observations. Many of these features were reproduced by the model. Sensitivity experiments with the model were carried out to examine the dependence of precipitation characteristics in this event on thresholds of particle evolution in the new parameterization.

Sensitivity of Lake-Effect Cloud Microphysical Processes to Ice Crystal Habit and Nucleation during OWLeS IOP4

2019 ◽  
Vol 76 (11) ◽  
pp. 3411-3434 ◽  
Author(s):  
Lauriana C. Gaudet ◽  
Kara J. Sulia ◽  
Fangqun Yu ◽  
Gan Luo
Keyword(s):  
Cloud Condensation Nuclei ◽  
Cold Season ◽  
Crystal Habit ◽  
Shape Effect ◽  
Ice Crystal ◽  
Microphysical Process ◽  
Lake Effect ◽  
Time Period ◽  
Highly Sensitive ◽  
Microphysical Processes

Abstract Ice crystal habit significantly impacts ice crystal processes such as growth by vapor deposition. Despite this, most bulk microphysical models disregard this natural shape effect and assume ice to grow spherically. This paper focuses on how the evolution of ice crystal shape and choice of ice nucleation parameterization in the adaptive habit microphysics model (AHM) influence the lake-effect storm that occurred during intensive observing period 4 (IOP4) of the Ontario Winter Lake-effect Systems (OWLeS) field campaign. This localized snowstorm produced total accumulated liquid-equivalent precipitation amounts up to 17.92 mm during a 16-h time period, providing a natural laboratory to investigate the ice–liquid partitioning within the cloud, various microphysical process rates, the accumulated precipitation magnitude, and its associated spatial distribution. Two nucleation parameterizations were implemented, and aerosol data from a size-resolved advanced particle microphysics (APM) model were ingested into the AHM for use in parameterizing ice and cloud condensation nuclei. Simulations allowing ice crystals to grow nonspherically produced 1.6%–2.3% greater precipitation while altering the nucleation parameterization changed the type of accumulating hydrometeors. In addition, all simulations were highly sensitive to the domain resolution and the source of initial and boundary conditions. These findings form the foundational understanding of relationships among ice crystal habit, nucleation parameterizations, and resultant cold-season mesoscale precipitation within detailed bulk microphysical models allowing adaptive habit.

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