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--- projects:fragile [2024/10/24 00:01] – ayush
+++ projects:fragile [2026/09/08 03:12] (current) – ayush
@@ Line 1: / Line 1: @@
  ~~NOTOC~~
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 <WRAP tablewidth 90% center>
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 ===Abstract===
-In the project FRAGILE, we want to continue the successful combination of spectral multi-frequency and polarimetric cloud radar observations with novel Lagrangian super-particle modeling to investigate ice microphysical processes. In agreement with previous studies, we find indications of new particle formation especially within the dendritic growth zone. Fragmentation of ice and snow particles has been debated for many years as potential candidate to explain those radar features. In FRAGILE, we aim now to perform new laboratory experiments including studies in a wind tunnel, to directly observe possible fragmentation of snowflakes or rimed particles. The results from the lab will be used to refine model parameterizations which will then be constrained by comparing the forward modelled radar signatures with our existing multi-months polarimetric cloud radar dataset. Once a certain level of convergence is reached with the 1D Lagrangian model, we will apply machine learning methods to derive parameterizations for bulk schemes implemented in the ICON model.\\
+In the project FRAGILE, we want to continue the successful combination of spectral multi-frequency and polarimetric cloud radar observations with novel Lagrangian super-particle modeling to investigate ice microphysical processes. In agreement with previous studies, we find indications of new particle formation especially within the dendritic growth zone. Fragmentation of ice and snow particles has been debated for many years as potential candidate to explain those radar features. In FRAGILE, we aim now to perform new laboratory experiments including studies in a wind tunnel, to directly observe possible fragmentation of snowflakes or rimed particles. The results from the lab will be used to refine model parameterizations which will then be constrained by comparing the forward modelled radar signatures with our existing multi-months polarimetric cloud radar dataset. Once a certain level of convergence is reached with the 1D Lagrangian model, we will apply machine learning methods to derive parameterizations for bulk schemes implemented in the ICON model.
-\\
-{{ fragile_fig1_2022.png?direct&600  }}
-\\
-<WRAP tablewidth 40% center>**Figure 1:** Dendritic ice crystals grown on the surface of a graupel particle in a walk-in cold chamber.</WRAP>\\
+<met figure
+    src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:fragile_fig1_2022.png"
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+    title="Figure 1"
+    caption="Dendritic ice crystals grown on the surface of a graupel particle in a walk-in cold chamber."
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