Update README.md with introductory information for viewers

README.md

@@ -1,22 +1,53 @@
 # Sea Surface Temp Visualization
 
-This python code downloads daily worldwide sea surface temp datasets
-and visualizes them either as a world map on a given day, or as a time
-series per year.
+Sea Surface Temperatures are a key indicator of climate change. The
+world's oceans are a significant reservoir of heat, warming and
+cooling much more slowly than the atmosphere. Ocean heat drives larger
+storms, adds more moisture to the air above the ocean, and affects sea
+life and ocean chemistry. Monitoring ocean temperature is important to
+understand the drivers and impacts of climate change.
 
-It downloads the sea surface temp data from
-https://www.ncei.noaa.gov/data/sea-surface-temperature-optimum-interpolation/v2.1/access/avhrr.
-That contains daily HDF datasets containing .25° lat/lon cells over
-the entire Earth surface for each day since 1982, including temp and
-temperature anomaly compared to the historical mean for that date.
+NOAA's [National Centers for Environmental
+Information](https://www.ncei.noaa.gov/) maintains datasets of daily
+global ocean temperatures, derived mostly from satellites and updated
+using ship and buoy based observations. The raw data is filtered and
+resampled onto a 1/4-degree grid over the whole globe, and is
+available for every day from 1981 through the present at [their
+website](https://www.ncei.noaa.gov/products/climate-data-records/sea-surface-temperature-optimum-interpolation)
+with one or two days lag. It is an amazing testament to the incredible
+work of scientists and engineers worldwide that we have access to
+real-time data like this.
 
-This code processes those datasets into maps for any given day, or
-line charts with temp per day for the entire time period. The processing steps include:
-- limiting to +/- 60° latitude, to ignore the polar regions
-- removing cells containing > 50% ice cover
-- weighting each cell by its actual area (cells closer to the poles are smaller)
+This tool produces a set of visualizations of that data: maps of the
+latest temperature, and a set of time series of average temps for all
+years. For each of those, it shows the actual temperatures as well as
+the variance or "anomaly" from the mean value from the 1971-2000 time
+period. The anomalies are computed cell by cell by subtracting the
+mean value at that grid cell over the 1971-2000 period.
+
+Several things stand out from the time series graphs:
+
+- Ocean temperatures have been steadily increasing over the 40-year
+  recorded time span, visible in the graph as the later years are
+  shaded darker blue.
+- Sea surface temperatures have been rising significantly since 2023,
+  reaching daily records every day since spring of that year. (This
+  acceleration beyond the global climate change signal is largely due
+  to [El Niño](https://oceanservice.noaa.gov/facts/ninonina.html), but
+  also somewhat to the underwater eruption of the [Hunga-Tonga
+  volcano](https://volcano.si.edu/volcano.cfm?vn=243040) in 2022 and
+  slightly affected by the 2020 [regulation of
+  sulfur](https://www.imo.org/en/MediaCentre/PressBriefings/pages/02-IMO-2020.aspx)
+  in marine fuels, which had been masking temperature rises.)
+- The all-time record for temperature was set in Feb 2024, and the
+  all-time record for temperature variance from the mean was set in
+  January 2024. Both records are likely to be broken as 2024
+  progresses.
+
+For technical details on data sources and how this code works, see [below](#technical-details).
+
+Here are the latest files, auto-produced daily by a github action. You can use these directly on the web via these URLs:
 
-Latest files, auto-produced daily by a github action. You can use these directly via these URLs:
 - https://github.com/garyo/sea-surface-temp-viz/releases/latest/download/sst-map.png
 - https://github.com/garyo/sea-surface-temp-viz/releases/latest/download/sst-anom-map.png
 - https://github.com/garyo/sea-surface-temp-viz/releases/latest/download/sst-all.png
@@ -29,3 +60,26 @@ Latest files, auto-produced daily by a github action. You can use these directly
 
 For older examples, see the `doc` subdir.
 
+# Technical Details
+
+This python code downloads daily worldwide sea surface temp datasets
+and visualizes them either as a world map on a given day, or as a time
+series per year.
+
+It downloads the sea surface temp data from
+https://www.ncei.noaa.gov/data/sea-surface-temperature-optimum-interpolation/v2.1/access/avhrr.
+That contains daily HDF datasets containing .25° lat/lon cells over
+the entire Earth surface for each day since 1982, including temp and
+temperature anomaly compared to the historical mean for that date.
+
+It processes those datasets into maps for any given day, or
+line charts with temp per day for the entire time period. The processing steps include:
+- limiting to +/- 60° latitude, to ignore the polar regions
+- removing cells containing > 50% ice cover
+- weighting each cell by its actual area (cells closer to the poles are smaller)
+
+Because it takes a while to download all the datasets, it keeps a disk
+cache in `./sst-data-cache.json`. If you want to re-run from scratch,
+just delete that file. It does process datasets in parallel using
+`asyncio` but to get all the global datasets since 1981 takes around
+20 minutes on my machine.