Weather data

gocek.org is pleased to present weather observations and forercasts with custom software developed in a living room. Visitors can retrieve information on named places and zip codes in the US and Puerto Rico. Hourly forecasts for temperatures, precipitation and other values are presented. NOAA point forecasts are provided for latitude/longitude location.

Why is one location forecast different than a neighboring location? NOAA provides customized forecasts for each reagion on a grid, with an accuracy of a few kilometers, so the forecast at a point may be different than the forecast for, say, the closest airport. Forecasts are updated periodically during each day.

What places can I rquest forecasts for? Cities and towns, military bases, lakes, mountains, shools, churhes, fire departments, etc. The USGS feature list (see below) contains over two million entries. In most cases, USGS does not use abbreviations, so you'll have a better chance with "Saint John's High School" than "St. Johns HS". Hawaiian and Rican names can contain diacritical marks.

Latitude and longitude? When the search page loads, your browser will attempt to load your device's location, if you allow it. Any latitude and longitude can be entered. You can usually find these values on internet maps. Sometimes OpenStreetMap (see below) can't find the named location (city, etc.) for your spot, and you'll see an error message.

Some forecast values seem odd: Sometimes NOAA does not provide hourly values for every attribute for a whole week. You might see (later in your seven day period) a high chance of rain, but with 0.0 predicted inches. Or you might see a rainy day with a high cloud ceiling. gocek.org can only report what NOAA returns, and there is no way for gocek.org to know if that zero rain prediction is correct or "not applicable". The forecast for the first couple of days should be fully correct. Sometimes NOAA reports the rain amount across a multi-hour period (such as 1" over 3 hours). The best gocek.org can do is spread the total across each hour.

Gary's weather station: By the way, here is a page with lots of data from my Davis Vantage Vue weather station.
currentweather.aspx

gocek.org uses data from a few locations to be able to find named places and weather stations with observations:
* United State Geological Survey (USGS)
* United State Geological Survey (USGS)
* International Civil Aviation Organization (ICAO)
ICAO provides a list of each registered aviation station (airport) around the world with its latitude and longitude. Many American stations feed weather observations to the National Oceanic and Atmospheric Administration (NOAA), which provides XML observations in the form of and forecasts via an Application Programming Interface (API).
The United States Census Bureau [reviously offered downloadable files containing ZIP codes, but that seems to have ended around 2015.
gocek.org collected and cross-referenced these various downloads so that visitors can request observations and forecasts by zip code and place name. There are commercial feeds that are more robust in some ways, but I figure that we taxpayers are paying for the government data, and there's more data that I can display on my site, so I have stayed with the government feeds. Overall, it's pretty reliable.

gocek.org uses data from OpenStreetMap.org.

Statistics: There are approximately 2.2 million place names with latitude and longitude available from USGS in the 50 ststers plus DC and PR. Lat and lon are needed for the weather forecast API. To get a feel for the way the USGS data is provided, use the gocek,org weather page to get a forecast for FIRST BAPTIST CHURCH, AR. You will see dozens of churches, but each one is listed with a map location (that's how to tell one from another). There are about 42000 zip codes for which lat and lon are available. There are about 4000 American weather stations reporting current conditions. gocek.org has cross-refernced the locations and zip codes with the weather stations so that a user can search for a location and get current nearby observations.

A while back, this site presented "Gary's Snowfall Formula (GSF)", an attempt to calculate predicted snowfall based on other available predictions. This turned out to be unreliable, but here are some historical notes.

blizzard-20071216

Through various measurements, forecasters predict liquid precipitation which falls as snow during cold weather. The amount of snow per amount of water is the snow ratio. Traditionally, a 10:1 ratio (10 inches of snow per inch of liquid precipitation) has been used as an approximation, but the actual ratio depends on several factors and can be much lower or higher. Ratios higher than 20:1 are unusual, but not unprecedented in western NY. Dense (wet, heavy) snow produces less snow per amount of liquid precipitation than low density (light, fluffy) snow. In 2002, Roebber et al described a neural network method that results in a table of probabilities, e.g., an 80% chance of an inch of snow and a 20% chance of two inches, and the snow ratio is now calculated with this and similar complex formulas.

The US National Weather Service sometimes provides a liquid precipitation prediction with no snowfall prediction, even when the predicted temperature is below freezing. In these cases, I still want my table to show a snowfall prediction. The Roebber method uses match techniques that are more sophisticated than I have been willing to code up to now, so I developed a custom formula (Gary's Snow Formula, GSF) based on Roebber's principles. In practice, GSF shows lower predictions than the NWS. Actual snowfall is difficult to measure in the first place due to settling, melting and sublimation (the process by which ice and snow change directly to water vapor without first melting, i.e., icicles can disappear when the temperature is below freezing). The snow ratio can vary widely across a small geographic area, and large bodies of water affect the ratio, also known as "lake effect snow".

The big northeast storms of February, 2007 buried the Tug Hill plateau north of Syracuse, and later Chicago and Cleveland. The earlier lake effect storms largely spared my webcam location, and the NWS point forecasts over-predicted snowfall. The point forecasts for the later Nor'easter (in which warm, moist, southerly air pushed into an arctic cold front) predicted a 30:1 snow ratio. My lat/lon observation was that the NWS over-predicted the early-storm snowfall, under-predicted the late-storm snowfall, and slightly over-predicted the total. My GSF badly under-predicted the snowfall from the unusual combination of single-digit temperatures and near-100% humidity.


                GSF first calculates a predicted snow density factor.

                Begin with 1 for Jan/Feb, 2 for Nov/Dec/Mar/Apr, 3 for Oct, 4 for May/Jun/Jul/Aug/Sep.

                Add [((temperature + 15) * 2) / 25]

                Add [relHum / 25]

                Add [(windSpd * 2) / 25]

                To account for the effect of the Great Lakes, subtract 1 from the density if
                the wind direction is nearly NW, and subtract 0.5 if the direction is between
                WNW and N, but this is admittedly an approximation and is optimized for
                Rochester.

                Based on expectations of maximum and minimum temperatures and wind speeds, the
                density should be between 0 and 16, and the resulting snow ratio is based on a
                typical ratio of 9 inches of snow per inch of water.

                ratio = 81 / density

                snowfall = predicted liquid * ratio