Hi there 😊

I apply advanced statistical and numerical models to solve real-world problems.

Following is a list of major academic projects I’ve worked on:

Parameters estimation of CESM model with Machine Learning emulators (Gaussian Process, Sensitivity Analysis)
Investigating teleconnections between snow cover forcing and precipitation (Singular Value Decomposition and Linear Baroclinic Model)
Assessing impact of different boundry-layer parameterizations on dry deposition in WRF-Chem model
Simulation of wind environment and resources using WRF model

These projects led to my Master of Science, focusing on applying and calibrating numerical models.
Here is a collection of my technical notes for sharing and discussion.
Hope you enjoy reading these challenges as much as I am working ~~

[Demo] A Benchmark for Data-Driven Climate Projections

This is a analytic walk-through of the following paper: ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections https://doi.org/10.1029/2021MS002954 (Watson-Paris et al., 2022) conda environment The analysis was conducted under a conda virtual environment (esem). I’ll attached the .yml file of the environment together with the assignment, you can install it with conda env create -f esem.yml. Or if you prefer to install it manually, here are the commands I used:...

Work with Canadian Census data

This is a course assignment demo (GG606 Scientific Data Wrangling) cancensus is a R package that can assess Statistics Canada Census data for Census year 1996, 2001, 2006, 2011, 2016 and 2021. The datasets present information from the Census of Population for various levels of geography, including provinces and territories, census metropolitan areas, communities and census tracts. 1. Installation and retrieve the data vectors list (API key required) install....

Earthquakes data analysis demo

This is a course assignment for analyze and visualize earthquake data 1. Read the data in and clean it for analysis, used the readr package functions for reading and parsing data. [5 marks] My answer is written here and is explains what I did and why. #code library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ ggplot2 3.4.0 ✔ purrr 1.0.0 ## ✔ tibble 3....

Generate Short/Long Perturbed Parameter Ensembles (PPE) with CESM

1. Main Settings Experiment name: f.e12.FAMIPCN.f19_f19 f f compset; “F” compsets use CAM,CLM, CICE(prescribed-thermo), DOCN(prescribed-SST). e12 cesm1.2.2 (model version) FAMIPCN AMIP run for CMIP5 protocol with CLM/CN: AMIP_CAM4_CLM40%CN_CICE%PRES_DOCN%DOM_RTM_SGLC_SWAV AMIP: time, AMIP runs CAM4: atmosphere model CAM4 CLM40: land model, clm4.0 CN (carbon-nitrogen) model version: a biogeochemistry model that simulates the carbon and nitrogen cycles CICE%PRES: prescribed sea ice DOCN%DOM: DOCN data ocean mode RTM: river transport model, land river runoff...