update paper pdf draft file

Author: levuvietphong

joss/paper.md

@@ -58,10 +58,11 @@ Tropical cyclones (TCs) -- that is, hurricanes and tropical storms -- are among
 The ability of ESMs to simulate climate extremes has substantially improved over the past few decades.
 These models have become key tools used for exploring the effect of global warming on precipitation and climate variability [@Emanuel:2021;@Le:2021;@Le:2023].
 While high-resolution ESMs have enhanced the representation of TCs [@Haarsma:2016;@Li:2018], they remain computationally intensive to conduct, so that only a limited number of simulations can be performed.
-This constrains their application in risk analysis of TC rainfall, which requires extensive sampling of extreme events [@Emanuel:2008].
-`pyTCR` responds to this need with an easy-to-use and fast tool that facilitates TC-driven rainfall analysis across scales.
-It leverages a synthetic downscaling approach that uses simpler embedded models and thermodynamic and kinematic statistics derived from ESM outputs or reanalysis data to generate large (~10$^3$-10$^4$) numbers of synthetic TCs [@Emanuel:2006b;@Lin:2023].
-This enables `pyTCR` to produce statistically robust estimates of the probability distributions of storms for risk assessment.
+This constrains their application in TC rainfall risk analysis, which requires extensive sampling of extreme events [@Emanuel:2008].
+`pyTCR` addresses this need with an easy-to-use and fast tool that facilitates TC-driven rainfall analysis across scales.
+Specifically, it leverages a synthetic downscaling approach that combines statistical track generation with simple deterministic intensity modeling.
+This approach uses thermodynamic and kinematic statistics, derived from ESM outputs or reanalysis data, to generate large (~10$^3$-10$^4$) numbers of synthetic TCs [@Emanuel:2006b;@Lin:2023].
+As a result, `pyTCR` produces statistically robust estimates of the probability distributions of storms for risk assessment.
 
 
 # Mathematical Approach