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 Project based at\\ Project based at\\
 **University of Bonn, Phase 1**: [[https://www2.meteo.uni-bonn.de/spp2115/doku.php?id=researchers#prabhakarshrestha|Prabhakar Shrestha (PI)]] \\ **University of Bonn, Phase 1**: [[https://www2.meteo.uni-bonn.de/spp2115/doku.php?id=researchers#prabhakarshrestha|Prabhakar Shrestha (PI)]] \\
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 The Terrestrial Systems Modeling Platform (TSMP) was extended with a chemical transport model and was used at kilometer-scale (convection-permitting) resolution to jointly simulate the aerosol characteristics and polarimetric features of three summertime deep convective storms over Germany, which produced large hail, high precipitation, and severe damaging winds (Shrestha et al. 2022a/b). A polarimetric radar forward operator consistent with the model cloud microphysical scheme was used for model evaluation and process studies in radar observation space.\\ The Terrestrial Systems Modeling Platform (TSMP) was extended with a chemical transport model and was used at kilometer-scale (convection-permitting) resolution to jointly simulate the aerosol characteristics and polarimetric features of three summertime deep convective storms over Germany, which produced large hail, high precipitation, and severe damaging winds (Shrestha et al. 2022a/b). A polarimetric radar forward operator consistent with the model cloud microphysical scheme was used for model evaluation and process studies in radar observation space.\\
 \\ \\
-The ensemble model simulation was, in general, able to capture the storm structure, its evolution, and the spatial pattern of accumulated precipitation. However, the initial and lateral boundary conditions strongly impact the simulated cloud microphysical and macrophysical processes and hence the synthetic polarimetric variables. For all simulated convective cases using a two moment cloud microphysics scheme with fixed continental CN concentrations (1700 cm-3) over Germany, the model tended to underestimate the observed convective area fractions and the corresponding high precipitation amounts. While the model tends to simulate too high reflectivities in the downdraft region of the storm above the melting layer (mostly contributed by graupel), the model also simulates very weak polarimetric signatures in this region when compared to the radar observations. The above findings remained almost unchanged when using a more narrow cloud drop size distribution (CDSD) acknowledging the missing feedback between aerosol physical and chemical properties and CDSD shape parameters.\\+The ensemble model simulation was, in general, able to capture the storm structure, its evolution, and the spatial pattern of accumulated precipitation. However, the initial and lateral boundary conditions strongly impact the simulated cloud microphysical and macrophysical processes and hence the synthetic polarimetric variables. For all simulated convective cases using a two moment cloud microphysics scheme with fixed continental CN concentrations ($1700\,\mathrm{cm^{-3}}$) over Germany, the model tended to underestimate the observed convective area fractions and the corresponding high precipitation amounts. While the model tends to simulate too high reflectivities in the downdraft region of the storm above the melting layer (mostly contributed by graupel), the model also simulates very weak polarimetric signatures in this region when compared to the radar observations. The above findings remained almost unchanged when using a more narrow cloud drop size distribution (CDSD) acknowledging the missing feedback between aerosol physical and chemical properties and CDSD shape parameters.\\
 \\ \\
-Shrestha et al. (2022b) found that the model simulated weaker (in terms of inherent ZDR-values) synthetic ZDR columns compared to the observations. Strong updrafts in the convective core produced towerlike features with increased aerosol number concentrations and hence increased cloud droplet number concentration and reduced mean cloud drop size (see Fig. 1). This led to a reduced mean size of supercooled raindrops, which could be at least one reason for the described discrepancies between simulated and observed columns of enhanced differential reflectivity (ZDR) along the vicinity of convective. Assuming a more realistic, narrow cloud drop size distribution (CDSD) did increase the mean size of supercooled raindrops and improved the simulation of ZDR columns.\\ +Shrestha et al. (2022b) found that the model simulated weaker (in terms of inherent $Z_\mathrm{DR}$ values) synthetic $Z_\mathrm{DR}$ columns compared to the observations. Strong updrafts in the convective core produced towerlike features with increased aerosol number concentrations and hence increased cloud droplet number concentration and reduced mean cloud drop size (see Fig. 1). This led to a reduced mean size of supercooled raindrops, which could be at least one reason for the described discrepancies between simulated and observed columns of enhanced differential reflectivity ($Z_\mathrm{DR}$) along the vicinity of convective. Assuming a more realistic, narrow cloud drop size distribution (CDSD) did increase the mean size of supercooled raindrops and improved the simulation of $Z_\mathrm{DR}$ columns.\\
-\\ +
-The study shows the importance of including a chemistry transport model for evaluating current NWP models with polarimetric radar forward operators. And, it allows us to better constrain the traditional two-moment bulk cloud microphysical schemes used in the numerical weather prediction models for weather and climate.\\ +
-\\ +
-{{ ilacpr_1.png?direct&750 }}\\ +
-<WRAP tablewidth 60% center>**Figure 1:** Plan view (left column) and vertical cross section (right column) of a polarimetric variable, hydrometeors, and aerosols. The plan views are shown at 6 km height, and all cross sections along the solid line indicated in the plan view. The 0o and 10 o C isotherms are also shown in all cross sections. (a, b) Synthetic differential reflectivity ZDR (color fill) is shown together with updrafts (solid/dashed red lines) and downdrafts (solid/dashed blue lines). The vertical wind speed contours are shown at the following intervals (-7.0, -5.0, -3.0, -1.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0) in meters per second. (c, d) Rain and hail mixing ratios and (e, f) aerosol and cloud number concentrations are shown in filled and solid line contours, , respectively. The cloud number concentration is contoured at an interval of 500 cm-3, with a minimum of 100 cm-3. The chemical transport model consists of 12 modes of aerosols, namely nucleation and accumulation mode for pure and mixed aerosol particles (sulfate, ammonium, nitrate, organic compounds, water, and soot), small, medium, and large particles for dust and sea salt, soot particles, and coarse particles (not used for the nucleation parameterization). Here, the aerosol concentration is shown for the pure and mixed nucleation and accumulation model aerosols only.</WRAP>+
 \\ \\
 +The study shows the importance of including a chemistry transport model for evaluating current NWP models with polarimetric radar forward operators. And, it allows us to better constrain the traditional two-moment bulk cloud microphysical schemes used in the numerical weather prediction models for weather and climate.
 +
 +<met figure
 +    src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:ilacpr_1.png"
 +    width="750"
 +    fit="responsive"
 +    title="Figure 1"
 +    caption="Plan view (left column) and vertical cross section (right column) of a polarimetric variable, hydrometeors, and aerosols. The plan views are shown at $6\,\mathrm{km}$ height, and all cross sections along the solid line indicated in the plan view. The $0^\circ\mathrm{C}$ and $10^\circ\mathrm{C}$ isotherms are also shown in all cross sections. (a, b) Synthetic differential reflectivity $Z_\mathrm{DR}$ (color fill) is shown together with updrafts (solid/dashed red lines) and downdrafts (solid/dashed blue lines). The vertical wind speed contours are shown at the following intervals (-7.0, -5.0, -3.0, -1.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0) in meters per second. (c, d) Rain and hail mixing ratios and (e, f) aerosol and cloud number concentrations are shown in filled and solid line contours, , respectively. The cloud number concentration is contoured at an interval of $500\,\mathrm{cm^{-3}}$, with a minimum of $100\,\mathrm{cm^{-3}}$. The chemical transport model consists of 12 modes of aerosols, namely nucleation and accumulation mode for pure and mixed aerosol particles (sulfate, ammonium, nitrate, organic compounds, water, and soot), small, medium, and large particles for dust and sea salt, soot particles, and coarse particles (not used for the nucleation parameterization). Here, the aerosol concentration is shown for the pure and mixed nucleation and accumulation model aerosols only."
 +    caption-align="left"
 +    load-animation="zoom-in"
 +    background="white"
 +    zoomable lightbox>
 +
  
 Sensitivity experiments with land-cover type changes produced similar patterns of precipitation but a general decrease in high precipitation and corresponding increase in low precipitation was observed for all enhanced human disturbance (EHD) experiments. The conversion of forested areas into agriculture and grasslands (EHD) lowered the total turbulent energy fluxes, besides lowering the Bowen ratio slightly. This change in surface energy fluxes is responsible for differences in the precipitation frequency distribution. Sensitivity experiments with land-cover type changes produced similar patterns of precipitation but a general decrease in high precipitation and corresponding increase in low precipitation was observed for all enhanced human disturbance (EHD) experiments. The conversion of forested areas into agriculture and grasslands (EHD) lowered the total turbulent energy fluxes, besides lowering the Bowen ratio slightly. This change in surface energy fluxes is responsible for differences in the precipitation frequency distribution.
 Sensitivity experiments with large-scale aerosol perturbations revealed an impact on the partitioning of high/low precipitation but were found to be also dependent on the large-scale lateral boundary conditions. Thus, no conclusions can be drawn yet. Interestingly, the use of maritime aerosols with low ice nuclei concentration produced convective area fraction closer to observations.\\ Sensitivity experiments with large-scale aerosol perturbations revealed an impact on the partitioning of high/low precipitation but were found to be also dependent on the large-scale lateral boundary conditions. Thus, no conclusions can be drawn yet. Interestingly, the use of maritime aerosols with low ice nuclei concentration produced convective area fraction closer to observations.\\
 \\ \\
-In close collaboration with the project Operation Hydrometeors, model evaluation was also performed for a wintertime stratiform precipitation event over the Bonn radar domain exploiting both the radar observation space and radar-derived hydrometeor partitioning ratios (Shrestha et al., 2022c). A sensitivity modeling study with perturbed parameters for the ice self-collection (aggregation) and riming processes improved the ice/snow partitioning above 4 km and suppressed excessive graupel production without affecting the accumulated precipitation at model resolvable scales. However, the model still exhibited a low bias (lower magnitude than observation) in simulated polarimetric moments at lower levels above the melting layer (-3 to -13°C) where snow was found to dominate. Sensitivity studies with different combinations of aspect ratios and widths of the canting angle distribution in the forward operator could not explain this model bias. Accordingly, this study suggests shortcomings in the forward operator and necessitates more reliable snow scattering models.+In close collaboration with the project Operation Hydrometeors, model evaluation was also performed for a wintertime stratiform precipitation event over the Bonn radar domain exploiting both the radar observation space and radar-derived hydrometeor partitioning ratios (Shrestha et al., 2022c). A sensitivity modeling study with perturbed parameters for the ice self-collection (aggregation) and riming processes improved the ice/snow partitioning above $4\,\mathrm{km}$ and suppressed excessive graupel production without affecting the accumulated precipitation at model resolvable scales. However, the model still exhibited a low bias (lower magnitude than observation) in simulated polarimetric moments at lower levels above the melting layer ($-3$ to $-13^\circ\mathrm{C}$) where snow was found to dominate. Sensitivity studies with different combinations of aspect ratios and widths of the canting angle distribution in the forward operator could not explain this model bias. Accordingly, this study suggests shortcomings in the forward operator and necessitates more reliable snow scattering models.
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 <WRAP BOX> <WRAP BOX>
 === Status 2021 === === Status 2021 ===
-{{ figure_01.ilacpr2021.png?direct&750  }}\\ 
-<WRAP tablewidth 60% center>**Figure 1:** Cross-sections of observed and synthetic radar data of summertime convective storm. Also shown is the modeled hydrometeors in the lower panel, including 0 𝐶 line showing location of melting layer, hail mixing ratio in solid lines with QG. The blue arrow indicates the location of maximum vertical velocity.</WRAP>\\ 
  
-Evaluation of synthetic radar data (processed using B-PRO) with observations provides valuable insights to the microphysical processes of the summertime convective storms. The simulated ZDR column is primarily contributed by rain drops (with size > 1 mm). Graupel dominates the frozen hydrometeor categories above the melting layer. Low concentration of hail is present on the adjacent size of the peak updraft, but dominates much of the radar reflectivities. +<met figure 
-\\+    src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:figure_01.ilacpr2021.png" 
 +    width="800" 
 +    fit="responsive" 
 +    title="Figure 1" 
 +    caption="Cross-sections of observed and synthetic radar data of summertime convective storm. Also shown is the modeled hydrometeors in the lower panel, including $0^\circ\mathrm{C}$ line showing location of melting layer, hail mixing ratio in solid lines with $Q_\mathrm{g}$. The blue arrow indicates the location of maximum vertical velocity." 
 +    caption-align="left" 
 +    load-animation="zoom-in" 
 +    background="white" 
 +    zoomable lightbox>
  
-{{ figure_02.ilacpr2021.png?direct&750  }}\\+Evaluation of synthetic radar data (processed using B-PRO) with observations provides valuable insights to the microphysical processes of the summertime convective storms. The simulated $Z_\mathrm{DR}$ column is primarily contributed by rain drops (with size $> 1\,\mathrm{mm}$). Graupel dominates the frozen hydrometeor categories above the melting layer. Low concentration of hail is present on the adjacent size of the peak updraft, but dominates much of the radar reflectivities.
  
-<WRAP tablewidth 60% center>**Figure 2:** Ensemble frequency distribution for different land-cover types with low (10 mm) and high (> 10 mm) accumulated precipitation.</WRAP>+<met figure 
 +    src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:figure_02.ilacpr2021.png" 
 +    width="800" 
 +    fit="responsive" 
 +    title="Figure 2" 
 +    caption="Ensemble frequency distribution for different land-cover types with low ($10\,\mathrm{mm}$) and high ($> 10\,\mathrm{mm}$) accumulated precipitation." 
 +    caption-align="left" 
 +    load-animation="zoom-in" 
 +    background="white" 
 +    zoomable lightbox>
  
-\\ 
 Sensitivity experiments with large scale aerosol perturbations and land-cover change was found to have less impact on the statistics of domain average precipitation, but effects the partitioning of low and high precipitation. It’s effect on polarimetric variables is currently being processed using the recently released EMVORADO-Pol with lookup tables. Sensitivity experiments with large scale aerosol perturbations and land-cover change was found to have less impact on the statistics of domain average precipitation, but effects the partitioning of low and high precipitation. It’s effect on polarimetric variables is currently being processed using the recently released EMVORADO-Pol with lookup tables.
 The TerrSysMP was also updated to include the chemical transport model ART (Aerosols and Reactive Trace gases). The ensemble simulations with TerrSysMP-ART for the summertime convective storm cases are currently ongoing at JSC supercomputers. The TerrSysMP was also updated to include the chemical transport model ART (Aerosols and Reactive Trace gases). The ensemble simulations with TerrSysMP-ART for the summertime convective storm cases are currently ongoing at JSC supercomputers.
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 <WRAP BOX> <WRAP BOX>
 === Status 2020 === === Status 2020 ===
-\\ + 
-\\ +<met figure 
-{{  figure_01ilacpr2020.png?direct&900 }}\\ +    src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:figure_01ilacpr2020.png" 
-<WRAP tablewidth 60% center>**Figure 1:** Spatial patterns of topography and vegetation cover for the Bonn Radar domain. The major cities and the stream networks derived from the topography using pre-processing tools for the [[https://doi.org/10.5880/TR32DB.37|model]] are also shown.</WRAP>\\ +    width="800" 
-\\ +    fit="responsive" 
-A new input data for a model domain (see Fig. 1) covering the extent of the BoxPol was prepared. The data consists of land-use and subsurface representation in terms of [[https://doi.org/10.5067/MODIS/MCD12Q1.006|vegation types]], multiple year [[https://doi.org/10.5067/MODIS/MCD15A2H.006|phenology]], [[http://www.cosmo-model.org/content/model/modules/externalParams/default.htm|soil texture]], [[http://www.bgr.bund.de/EN/Themen/Wasser/Produkte/produkte_node_en.html|aquifers]] and slopes derived from [[https://lta.cr.usgs.gov/SRTM|topography]]. The hydrological component of the model was used to generate initial soil-vegetation-groundwater states for multiple years using a recursive and transient spinup.\\ +    title="Figure 1" 
-\\ +    caption="Spatial patterns of topography and vegetation cover for the Bonn Radar domain. The major cities and the stream networks derived from the topography using pre-processing tools for the <a href='https://doi.org/10.5880/TR32DB.37'>model</a> are also shown." 
-{{  figure_02.ilacpr2020.png?direct&900  }}\\ +    caption-align="left" 
-<WRAP tablewidth 60% center>**Figure 2:** CFADs of horizontal and differential reflectivity for one ensemble member of Terrestrial Systems Modeling Platform (TSMP).</WRAP>\\ +    load-animation="zoom-in" 
-\\+    background="white" 
 +    zoomable lightbox> 
 + 
 +A new input data for a model domain (see Fig. 1) covering the extent of the BoxPol was prepared. The data consists of land-use and subsurface representation in terms of [[https://doi.org/10.5067/MODIS/MCD12Q1.006|vegation types]], multiple year [[https://doi.org/10.5067/MODIS/MCD15A2H.006|phenology]], [[http://www.cosmo-model.org/content/model/modules/externalParams/default.htm|soil texture]], [[http://www.bgr.bund.de/EN/Themen/Wasser/Produkte/produkte_node_en.html|aquifers]] and slopes derived from [[https://lta.cr.usgs.gov/SRTM|topography]]. The hydrological component of the model was used to generate initial soil-vegetation-groundwater states for multiple years using a recursive and transient spinup. 
 + 
 +<met figure 
 +    src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:figure_02.ilacpr2020.png" 
 +    width="800" 
 +    fit="responsive" 
 +    title="Figure 2" 
 +    caption="CFADs of horizontal and differential reflectivity for one ensemble member of Terrestrial Systems Modeling Platform (TSMP)." 
 +    caption-align="left" 
 +    load-animation="zoom-in" 
 +    background="white" 
 +    zoomable lightbox> 
 Using the spinup soil-vegetation states, diurnal scale ensemble simulation with data from COSMO-DE Ensemble Prediction System (EPS) was conducted for a hail storm event. Statistical properties of polarimetric quantities were evaluated using Contoured Frequency Altitude Diagrams (see Fig. 2). Additional ensemble sensitivity simulations were conducted for the same storm case using large scale aerosol perturbations and landuse change. Further, additional simulations for multiple storms are under progress to generalize the findings.\\ Using the spinup soil-vegetation states, diurnal scale ensemble simulation with data from COSMO-DE Ensemble Prediction System (EPS) was conducted for a hail storm event. Statistical properties of polarimetric quantities were evaluated using Contoured Frequency Altitude Diagrams (see Fig. 2). Additional ensemble sensitivity simulations were conducted for the same storm case using large scale aerosol perturbations and landuse change. Further, additional simulations for multiple storms are under progress to generalize the findings.\\
 \\ \\
  • projects/ilacpr.txt
  • Last modified: 2026/09/12 20:17
  • by ayush