Data analysis & visualization

Data analysis, visualization, and science


Work and project pages Research: atmospheric science MS thesis (low-res, high-res) Atmospheric and Earth science data NASA JPL ECOSTRESS CDC VAERS NASA CRYSTAL FACE Meteorology, SJSU Cloud modeling, UCSC Cryptocurrency sentiment analysis Wind resource assessment		Atmospheric science essentials Thermodynamics Radiation Dynamic meteorology Stratospheric ozone Cloud physics Numerical methods & modeling

Images and links below open PDFs, interactive figures, and related conferences/publications.
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*I contributed in varying capacities to all projects except those marked with * (e.g. Atmospheric CO₂ concentration, NCA5, VAERS, ..), i.e. no direct connection with those latter groups, but I wrote programs to analyze and visualize their data for informational purposes.

Fortran, Interactive data language (IDL), Python, scikit-learn, SciPy, statsmodels, Matplotlib, R, ggplot2
American Geophysical Union, 2019

Python, Plotly*
Open in new tab: 3D, 2D
References: IPCC, 2021; Bereiter et al., 2015; Jouzel et al., 2007; Keeling et al., 2005; Jones et al., 1999
Data: IPCC; Antarctic CO₂; Antarctic Δ T; Mauna Loa CO₂; NOAA Δ T

Python, scikit-learn, SciPy, statsmodels, Plotly
Open in new tab

ECOSTRESS land surface temperature, Silicon Valley, CA, USA – 2020.08.03

HDFView, Python, QGIS, GDAL, OpenLayers, JavaScript, ESRI
GIS maps with NASA JPL ECOSTRESS land surface temperature data
Open in new tab

Santa Cruz County, Voronoi polygons from USGS landslide points; average annual precipitation, 1971–2000

QGIS, GDAL, ESRI*
References: Landslides, Precipitation

ECOSTRESS_2020.08.14

HDFView, Python, QGIS, GDAL
GIS maps with NASA JPL ECOSTRESS land surface temperature data

Climate data and projections, Santa Cruz County, USA

ArcGIS, ESRI*
Open in new tab: map, dashboard
References: IPCC, 2013; IPCC, 2021; Fifth National Climate Assessment (NCA5)

ESRI, QGIS, Python, Bokeh, Holoviews, Panel*
References: Fifth National Climate Assessment

Climate projections (temperature and precipitation), global

ArcGIS, ESRI*
Open in new tab
References: IPCC, 2013; IPCC, 2021; Fifth National Climate Assessment

IDL, Python, SciPy, statsmodels, Pingouin, Matplotlib
American Geophysical Union, 2019

Python



Python, SciPy, Plotly* Open in new tab: ρ comparison, u₀ = 0, v₀ = 1, w₀ = 1.05 Time animation, u₀ = 0.1, v₀ = 1.2, w₀ = 1.13 Deterministic nonperiodic flow (Lorenz, 1963)

Python, Matplotlib

Python, Matplotlib

Python, Matplotlib

Python, Matplotlib

Fortran, IDL, Adobe Illustrator
American Geophysical Union, 2015, 2016

Fortran, IDL, Adobe Illustrator
American Geophysical Union, 2015; Mars Atmosphere Workshop 4, 2011 (paper)

Fortran, IDL, Adobe Illustrator
American Geophysical Union, 2019; Eighth International Conference on Mars, 2014 (poster, paper)

Python, SciPy, statsmodels, Pingouin, Matplotlib
R, ggplot2 (Mirror kernel density estimates)
American Geophysical Union, 2019

IDL, R, ggplot2
American Geophysical Union, 2019

Python, Matplotlib*

Python, Matplotlib

IDL
Eighth International Conference on Mars, 2014 (poster, paper)

Python, Bokeh, Holoviews, Panel*
Edge color = vaccination date. Clicking on nodes/edges dims unconnected nodes and edges.
Open in new tab: small, medium, large

Python, scikit-learn, Plotly*
Open in new tab

Fortran, IDL
MS thesis (low-res, high-res)

Python, Matplotlib, spaCy*
All CDC VAERS figures

IDL

IDL

Python, Bokeh, Holoviews, Panel*
Open in new tab: small, medium, large

IDL

Python, Bokeh, Holoviews, Panel*
Edge color = vaccination date. Clicking on nodes/edges dims unconnected nodes and edges.
Open in new tab

IDL

Fortran, IDL
MS thesis (low-res, high-res)

Planewave form of the geostrophic streamfunction

• IDL

IDL

MATLAB
Arctic warming feedbacks and amplifications. 2009, Earth 254, UCSC
References: Understanding Climate Change Feedbacks. 2003, NRC

Fortran, OpenDX

Fortran, Explicit mixing parcel model, MATLAB

Fortran, Explicit mixing parcel model, MATLAB

IDL, Fortran (Numerical model of the equatorial stratosphere)

MICRODEM, WindPro, WindSim
Preliminary wind resource assessment

Fortran, GrADS
American Meteorological Society, 2005

Fortran, GrADS
American Meteorological Society, 2005

Python, Bokeh, Holoviews, Panel*
Open in new tab

Python, Vega, Altair, Holoviz, Panel*
Open in new tab

ECOSTRESS land surface temperature distribution, kernel density estimation, 2020.08.03



	Python, QGIS, GDAL, Plotly GIS maps with NASA JPL ECOSTRESS land surface temperature data North Fair Oaks land parcels (8 MB)

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