Readers may remember a couple of weeks back when I lamented that the downward economy had finally caught up to me and my little weather business. I asked readers if they’d mind if I’d showcase a weather station or two to help drum up some business. Nobody objected and many readers were very helpful and sympathetic. Thank you sincerely.
I always like to find ways to bring meteorological and climate science to the layman, hence this blog. My specialty is instrumentation, and readers may recall back in fall 2008 when I rigged up my vehicle with an NIST calibrated data logger, window mounted Gill IR shield, and a live connection to my laptop and drove a transect to measure the surface temperature. The result was this first ever graph of Reno’s UHI (Urban Heat Island) signature:
Click for larger image
That little experiment garnered quite a few comments, and I always wanted to find an inexpensive way for others to recreate what I did without having to invest in a high priced NIST calibrated probe, IR shield, datalogger, and laptop, all told which would run about $1200. That’s beyond the means of many people who might take an interest. It’s also well beyond the means of most students who might want to do something like this for their local science fair in their own hometown.
I’m pleased to say I have devised a solution for about 1/10th the cost, and I’ve just finished testing it in my hometown of Chico, CA. The results follow.
As many readers know, I sell some nifty USB dataloggers, and you may have seen this ad on the right sidebar which links to my online store.
The dataloggers are inexpensive, mostly under $100, and work great for various monitoring applications where you want to gather and evaluate temperature data. Problem is, they had no way to be mounted to anything easily, and I couldn’t see an easy way to mount one to a vehicle like I did with the IR Gill shield:
The NIST calibrated temperature sensor (inside the Gill IR shield) mounted on the vehicle using an improvised window mount., Cable goes to datalogger inside, and datalogger connected to laptop.
My goal has always been to recreate this inexpensively and reliably so many of you could map UHI in your own city. Making this within reach of students and their parents was the ultimate goal. How does $84.95 sound compared to $1200? You don’t even need to take a laptop in the vehicle with you.
Some days, serendipity strikes. A discussion about US flags with fellow blogger Russ Steele made me think about this idea of using the window flag mounts commonly seen en-route to football and baseball games:
Except my version has no team flag, it flies a datalogger instead:
How’s that for simple?
I spent today working this product idea out and testing it to make sure it is simple enough for anyone to recreate anywhere. Then I ran some road tests. Here’s how it works.
First we start with the USB-2 Temperature and Humidity datalogger. The reason I chose this unit over a temperature-only USB-1 version is that it already has a built in mini IR shield that allows free airflow. It reacts faster for that reason.
Next I provide a modified vehicle window mount and mounting hardware specifically to keep the USB-2 datalogger affixed, click images to enlarge:
Adhesive Velcro strip plus a removable secure strap worked best:
I ran some tests to see if I could fling the datalogger off the end. It held even after inflicting a few G’s on it at arms length.
Here’s the finished product:
The next test was to see if the datalogger was far enough out of the vehicle slipstream to prevent any temperature contamination while moving. That was evident from the data right away.
I did four daytime driving transects of my town to see if there were any hiccups or gotchas with install, driving, removal, and data download. Finding none, I wrote up some instructions:
Measuring UHI in your city:
- Install the software on your Windows PC (or laptop if you bring it with you in the car). Experiment with and familiarize yourself with the datalogger.
- Choose a route you can drive in your town that provides a good north-south and/or east-west driving transect from country, through suburbs, downtown, and back to countryside again. Use Google Earth or a similar mapping tool to assist in planning your route. Try to choose a route that will not take any more than 30 minutes to minimize ambient temperature change that may occur.
- Choose a clear night with no wind or light wind if possible. Later at night like 11PM-midnight is best so as to have minimum traffic and stoplights.
- Set the data logger to start logging either immediately or at some start time in the future. Put the waterproof cap back on
- Affix the datalogger to the vehicle mount using the strap provided.
- Put the vehicle mount on the top edge of your vehicle window and close it for a tight fit.
- Drive to the start point, Either wait for the pre-programmed start time or trigger the data logger to start from your laptop. It is always best to start on an easy to check period like top of the hour, quarter hour, or half hour.
- Drive the route, trying to maintain a fixed speed.
- Have your passenger note landmarks/locations in a logbook as you drive so that you can correlate with temperatures later.
- Optional – take a logging GPS unit with you if you want exact positions and time.
- Once completing the first transect, turn around and drive it again. You may wish to do several transects if time allows so that you can create an average profile later.
- Remove the USB-2 datalogger from the vehicle mount, plug into your PC, launch the included software and plot your results! Export the data to a spreadsheet for further analysis.
Saturday night, April 3rd, I ran my first for real UHI transect on Highway 99 from Garner Lane North of town to Neal Road South of town. I chose these points because they were safe places to turnaround and because they were both well enough removed from the population center that I expected they would approximate “rural” conditions.
After driving a transect and reverse driving it again, here is what the datalogger showed from the program that ships with the datalogger:
As you can see, the red temperature curve shows two humps, these are the two transects mirrored. First one was driving NW to SE, and the reverse (second) was SE to NW. Humidity and dewpoint are also displayed. The temperature looks a little blocky becuase the resolution of the datalogger is 0.5°C. However, given the world’s surface data is measured to the nearest degree, this is more than adequate for the purpose.
My home weather station (in town) showed light winds less than 5mph from the southeast and 50°F (10°C) when I left. Skies were clear. It was a good evening to measure UHI.
I took a voice recorder with me to note the time I started driving and the time I turned around and reversed the transect. I drove the reverse transect about 10mph faster because the first transect I didn’t want to pass a semi truck (speed limit 55mph for trucks through town) and pick up any waste heat, so I held well behind it.
Next I exported that data into my favorite graphing program ( DPlot ) and edited the starting and ending data times based on my recorder notes. I had set the datalogger at home to automatically start at 8:45 PM and I hadn’t reached my Garner lane start point yet. My actual transect began at 8:47 PM from Garner Lane at Highway 99 intersection.
Then I pulled up my Google Earth and started exporting some images for reference. Here’s the normal map view of the transect with starting and ending points:
And here’s the NW to SE driving transect overlaid onto a Google Earth 3D image looking NE so that Highway 99 appears as a “x- axis”:
As you can see, the graph matches the infrastructure character of the town fairly well, with the peak coinciding with the center of town (marked by the crosshair and label). The temperature is less in the rural outskirts of town.
So there we have it, it appears that my small college town of ~ 80,000 people has a UHI value of about 1.5°C (2.7°F) via this transect. The second return transect from SE to NW has the same magnitude, but is offset due to ambient temperature drop that occurred during the drive. When I returned home at 9:30PM, and hour later my home weather station had dropped to 44°F.
So would you like to do this for your hometown? Do you have a son/daughter nephew/niece that would benefit from a weekend science project learning about how to measure temperature and graph it to show UHI? Or, maybe you just want to do it yourself for fun and quantify what you’ve noticed for years via your automobile thermometer.
I’ll be happy to post any results here.
The only real caveat to this experiment is: don’t stop your vehicle if you can help it. Without a constant airstream, some waste heat from the vehicle might make its way to the sensor. Choose your driving route to avoid long stoplights, and I’ve found that in many cities after 11PM certain thoroughfares are “greenlighted”.
If you like this little idea or know somebody who would, please feel free to buy my little UHI measurement kit at a price most anyone can afford: $84.95 It helps me and provides more data that shows UHI to be a real, measurable, effect.
Here is the link to purchase the kit: http://weathershop.com/usb2-UHI.htm
And yes, I do ship internationally.
Thanks for your consideration, happy motoring! – Anthony
UPDATE: Hu McCulloch reminds me of the similar experiment Warren Meyer and his son did a couple of years ago which you can read about here:
http://www.climate-skeptic.com/2008/02/measureing-the.html
Some commenters were concerned about contamination of the data due to the vehicle. This is possible, even likely, at a dead stop. But at highway speeds of 60 mph or even street speeds of 30 mph any such contamination gets swept away in the slipstream. Essentially the thermometer has turbocharged aspiration, and is measuring the true temperature of the air being intersected. There may be issues with wast heat from vehicles ahead, but if you drive carefully and avoid tailgating, this can be avoided. Doing multiple transsects over time and averagign the runs is another way to minimize such biases.
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The raw data from the USB datalogger is below, note the date format is dd/mm/yyyy.
ChicoUHILogger,Time,Celsius(°C),Humidity(%rh),dew point(°C),Serial Number 1,03/04/2010 20:45:00,9.5,58.5,1.8,010004039 2,03/04/2010 20:45:10,9.5,59.0,1.9 3,03/04/2010 20:45:20,9.5,59.5,2.0 4,03/04/2010 20:45:30,9.5,59.5,2.0 5,03/04/2010 20:45:40,9.0,60.5,1.8 6,03/04/2010 20:45:50,9.0,60.5,1.8 7,03/04/2010 20:46:00,9.0,61.0,1.9 8,03/04/2010 20:46:10,9.0,60.5,1.8 9,03/04/2010 20:46:20,9.0,61.0,1.9 10,03/04/2010 20:46:30,9.0,61.0,1.9 11,03/04/2010 20:46:40,9.0,61.5,2.0 12,03/04/2010 20:46:50,9.0,61.5,2.0 13,03/04/2010 20:47:00,8.5,62.5,1.8 14,03/04/2010 20:47:10,8.5,63.0,1.9 15,03/04/2010 20:47:20,8.5,63.0,1.9 16,03/04/2010 20:47:30,8.5,62.5,1.8 17,03/04/2010 20:47:40,8.5,62.0,1.6 18,03/04/2010 20:47:50,8.5,60.5,1.3 19,03/04/2010 20:48:00,8.5,60.5,1.3 20,03/04/2010 20:48:10,8.5,60.5,1.3 21,03/04/2010 20:48:20,9.0,60.0,1.7 22,03/04/2010 20:48:30,9.0,59.5,1.5 23,03/04/2010 20:48:40,9.0,59.0,1.4 24,03/04/2010 20:48:50,9.0,58.5,1.3 25,03/04/2010 20:49:00,9.0,58.0,1.2 26,03/04/2010 20:49:10,9.0,58.0,1.2 27,03/04/2010 20:49:20,9.5,57.5,1.5 28,03/04/2010 20:49:30,9.5,57.0,1.4 29,03/04/2010 20:49:40,9.5,57.0,1.4 30,03/04/2010 20:49:50,9.5,56.5,1.3 31,03/04/2010 20:50:00,9.5,56.5,1.3 32,03/04/2010 20:50:10,9.5,56.5,1.3 33,03/04/2010 20:50:20,10.0,56.5,1.8 34,03/04/2010 20:50:30,10.0,56.5,1.8 35,03/04/2010 20:50:40,10.0,56.0,1.6 36,03/04/2010 20:50:50,10.0,55.5,1.5 37,03/04/2010 20:51:00,10.0,55.5,1.5 38,03/04/2010 20:51:10,10.0,55.5,1.5 39,03/04/2010 20:51:20,10.0,55.5,1.5 40,03/04/2010 20:51:30,10.0,55.5,1.5 41,03/04/2010 20:51:40,10.0,55.5,1.5 42,03/04/2010 20:51:50,10.0,56.0,1.6 43,03/04/2010 20:52:00,10.0,56.5,1.8 44,03/04/2010 20:52:10,10.0,56.0,1.6 45,03/04/2010 20:52:20,10.0,56.5,1.8 46,03/04/2010 20:52:30,10.0,56.0,1.6 47,03/04/2010 20:52:40,10.0,55.5,1.5 48,03/04/2010 20:52:50,10.0,55.0,1.4 49,03/04/2010 20:53:00,10.0,54.5,1.3 50,03/04/2010 20:53:10,10.0,54.5,1.3 51,03/04/2010 20:53:20,10.0,54.5,1.3 52,03/04/2010 20:53:30,10.0,55.0,1.4 53,03/04/2010 20:53:40,10.0,54.5,1.3 54,03/04/2010 20:53:50,10.0,54.5,1.3 55,03/04/2010 20:54:00,10.0,54.5,1.3 56,03/04/2010 20:54:10,10.0,55.0,1.4 57,03/04/2010 20:54:20,10.0,55.5,1.5 58,03/04/2010 20:54:30,10.0,55.5,1.5 59,03/04/2010 20:54:40,10.0,57.0,1.9 60,03/04/2010 20:54:50,10.0,57.0,1.9 61,03/04/2010 20:55:00,10.0,57.5,2.0 62,03/04/2010 20:55:10,9.5,58.0,1.7 63,03/04/2010 20:55:20,9.5,58.0,1.7 64,03/04/2010 20:55:30,9.5,58.0,1.7 65,03/04/2010 20:55:40,9.5,57.5,1.5 66,03/04/2010 20:55:50,9.5,57.5,1.5 67,03/04/2010 20:56:00,9.5,58.5,1.8 68,03/04/2010 20:56:10,9.5,58.5,1.8 69,03/04/2010 20:56:20,9.5,59.5,2.0 70,03/04/2010 20:56:30,9.5,60.0,2.1 71,03/04/2010 20:56:40,9.0,60.5,1.8 72,03/04/2010 20:56:50,9.0,60.5,1.8 73,03/04/2010 20:57:00,9.0,61.0,1.9 74,03/04/2010 20:57:10,9.0,61.0,1.9 75,03/04/2010 20:57:20,9.0,61.0,1.9 76,03/04/2010 20:57:30,9.0,61.5,2.0 77,03/04/2010 20:57:40,9.0,61.5,2.0 78,03/04/2010 20:57:50,9.0,61.5,2.0 79,03/04/2010 20:58:00,9.0,61.0,1.9 80,03/04/2010 20:58:10,9.0,61.0,1.9 81,03/04/2010 20:58:20,9.0,61.0,1.9 82,03/04/2010 20:58:30,9.0,61.0,1.9 83,03/04/2010 20:58:40,9.0,60.5,1.8 84,03/04/2010 20:58:50,9.0,61.0,1.9 85,03/04/2010 20:59:00,9.0,60.5,1.8 86,03/04/2010 20:59:10,9.0,60.5,1.8 87,03/04/2010 20:59:20,8.5,61.0,1.4 88,03/04/2010 20:59:30,8.5,62.0,1.6 89,03/04/2010 20:59:40,8.5,62.5,1.8 90,03/04/2010 20:59:50,8.5,62.5,1.8 91,03/04/2010 21:00:00,8.5,62.5,1.8 92,03/04/2010 21:00:10,8.5,62.5,1.8 93,03/04/2010 21:00:20,8.5,63.0,1.9 94,03/04/2010 21:00:30,8.5,63.0,1.9 95,03/04/2010 21:00:40,8.5,64.0,2.1 96,03/04/2010 21:00:50,8.5,64.5,2.2 97,03/04/2010 21:01:00,8.5,64.0,2.1 98,03/04/2010 21:01:10,8.5,64.0,2.1 99,03/04/2010 21:01:20,8.5,64.0,2.1 100,03/04/2010 21:01:30,8.0,64.5,1.7 101,03/04/2010 21:01:40,8.0,65.0,1.8 102,03/04/2010 21:01:50,8.0,65.5,1.9 103,03/04/2010 21:02:00,8.0,66.0,2.0 104,03/04/2010 21:02:10,8.0,66.0,2.0 105,03/04/2010 21:02:20,8.0,66.5,2.2 106,03/04/2010 21:02:30,8.0,65.5,1.9 107,03/04/2010 21:02:40,8.0,64.5,1.7 108,03/04/2010 21:02:50,8.0,65.0,1.8 109,03/04/2010 21:03:00,8.0,66.0,2.0 110,03/04/2010 21:03:10,8.0,66.0,2.0 111,03/04/2010 21:03:20,8.0,66.0,2.0 112,03/04/2010 21:03:30,8.0,66.0,2.0 113,03/04/2010 21:03:40,8.0,65.0,1.8 114,03/04/2010 21:03:50,8.0,64.0,1.6 115,03/04/2010 21:04:00,8.0,63.5,1.5 116,03/04/2010 21:04:10,8.0,63.0,1.4 117,03/04/2010 21:04:20,8.0,62.0,1.2 118,03/04/2010 21:04:30,8.5,61.0,1.4 119,03/04/2010 21:04:40,8.5,61.5,1.5 120,03/04/2010 21:04:50,8.5,61.0,1.4 121,03/04/2010 21:05:00,8.5,60.5,1.3 122,03/04/2010 21:05:10,8.5,60.5,1.3 123,03/04/2010 21:05:20,8.5,60.0,1.2 124,03/04/2010 21:05:30,9.0,60.5,1.8 125,03/04/2010 21:05:40,9.0,61.5,2.0 126,03/04/2010 21:05:50,9.0,61.0,1.9 127,03/04/2010 21:06:00,9.0,61.0,1.9 128,03/04/2010 21:06:10,9.0,61.0,1.9 129,03/04/2010 21:06:20,9.0,61.0,1.9 130,03/04/2010 21:06:30,9.0,60.5,1.8 131,03/04/2010 21:06:40,9.0,60.0,1.7 132,03/04/2010 21:06:50,9.0,59.5,1.5 133,03/04/2010 21:07:00,9.0,59.0,1.4 134,03/04/2010 21:07:10,9.0,59.0,1.4 135,03/04/2010 21:07:20,9.0,59.0,1.4 136,03/04/2010 21:07:30,9.0,58.5,1.3 137,03/04/2010 21:07:40,9.0,58.5,1.3 138,03/04/2010 21:07:50,9.0,58.5,1.3 139,03/04/2010 21:08:00,9.0,58.0,1.2 140,03/04/2010 21:08:10,9.5,58.0,1.7 141,03/04/2010 21:08:20,9.5,57.5,1.5 142,03/04/2010 21:08:30,9.5,57.5,1.5 143,03/04/2010 21:08:40,9.5,57.0,1.4 144,03/04/2010 21:08:50,9.5,57.0,1.4 145,03/04/2010 21:09:00,9.5,57.0,1.4 146,03/04/2010 21:09:10,9.5,57.0,1.4 147,03/04/2010 21:09:20,9.5,57.0,1.4 148,03/04/2010 21:09:30,9.5,57.0,1.4 149,03/04/2010 21:09:40,9.5,57.0,1.4 150,03/04/2010 21:09:50,9.5,57.0,1.4 151,03/04/2010 21:10:00,9.5,56.5,1.3 152,03/04/2010 21:10:10,9.5,57.0,1.4 153,03/04/2010 21:10:20,9.5,57.0,1.4 154,03/04/2010 21:10:30,9.5,57.0,1.4 155,03/04/2010 21:10:40,9.5,59.0,1.9 156,03/04/2010 21:10:50,9.5,61.0,2.4 157,03/04/2010 21:11:00,9.5,61.5,2.5 158,03/04/2010 21:11:10,9.0,61.0,1.9 159,03/04/2010 21:11:20,9.0,61.0,1.9 160,03/04/2010 21:11:30,9.0,61.0,1.9 161,03/04/2010 21:11:40,9.0,62.0,2.1 162,03/04/2010 21:11:50,8.5,62.0,1.6 163,03/04/2010 21:12:00,8.5,62.5,1.8 164,03/04/2010 21:12:10,8.5,63.0,1.9 165,03/04/2010 21:12:20,8.5,63.5,2.0 166,03/04/2010 21:12:30,8.5,64.0,2.1 167,03/04/2010 21:12:40,8.5,63.5,2.0 168,03/04/2010 21:12:50,8.0,63.5,1.5 169,03/04/2010 21:13:00,8.0,64.0,1.6 170,03/04/2010 21:13:10,8.0,64.0,1.6 171,03/04/2010 21:13:20,8.0,64.5,1.7 172,03/04/2010 21:13:30,8.0,65.5,1.9 173,03/04/2010 21:13:40,8.0,65.0,1.8 174,03/04/2010 21:13:50,8.0,64.0,1.6 175,03/04/2010 21:14:00,8.0,63.5,1.5 176,03/04/2010 21:14:10,8.0,63.0,1.4 177,03/04/2010 21:14:20,8.0,62.5,1.3
Have you allowed for possible cooling effects on the sensor of varying ground-speeds (and effective “airspeeds”) of the vehicle? Or is the fact that your UHI effect was measured at 1.5C both ways considered sufficient proof that this changes nothing?
REPLY: AT 60 mph it becomes a turbocharged aspirated thermometer. If you’ve ever ridden a motorcycle at night you’ll understand this experiment better. – Anthony
Re 899 (02:28:44) :
Nice idea except for one thing: BIASES introduced by the surroundings.
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But more data is better than less data for understanding and quantifying UHI effects, especially as the current approved methods are very crude.
I like the idea of getting these fitted to fleets. Government vehicles could be a good candidate, especially if they’re already fitted with GPS trackers and time/location can be correlated with the temperature sensor data. This seems a low cost method of gaining data, especially given the funding for global warming being thrown around.
Chris Wright (04:26:54) :
A really great idea. As TJA says, it would be really useful to monitor UHI for the stations documented by SurfaceStations.
As far as I understand it, the IPCC effectively discounts UHI, possibly on the basis of a paper by Parker that used wind monitoring. To use such an indirect method seems bizarre when it’s so easy to measure UHI directly.
Anthony measured a UHI of 1.5 degrees. The presenter of the BBC Climate Wars series measured a UHI of several degrees at Las Vegas.
These UHI measurements are consistently much larger than the total claimed global warming of 0.7 degrees. Houston, we have a problem….
We know that the UHI effect exists. Most of us have experienced it at sometime in our lives, particularly during very hot or very cold weather. During hot wearther, night-time temperatures in urban areas are often several degrees higher than rural areas. This, however, is not the issue.
The real question is whether the UH effect has contaminated the readings at the same location over the last 50 to 100 years and whether this has had a significant influence on the global surface temperature trend. The evidence suggests not.
1. The oceans (i.e. ~70% of the earths surface), which are not subject to UHI effects, have warmed.
2. The satellite (LT) temperature trends broadly agree with the surface temperature trends.
It’s unlikely that a UH effect can account for any more than a couple of hundredths of a degree in the global trend. Just after the climategate episode, I warned that sceptics were tending to focus far too much on the validity of the surface records and that this might result in a lost opportunity. The recent UK enquiry suggests I was right. The world has warmed over the past several decades. Arguing against this fact is futile.
899:
What do you think UHI stands for?
Great idea. The temp reading build in my car varies as much as 8-9 degrees. It really drops when leaving a paved road.
I’ll need one of those global warming grants.
Off subject…but possibly applicable regarding light winds observed at airports.
For Mr. Watt’s consideration… Wind data from ASOS observation sites…taken by the new ultrasonic Ice Free Wind Sensors…are being messed up by birds and possibly bats. I have to edit the data frequently during light wind conditions, when a Hawk, or other Raptor perches on the top of the sensor head, then dives down to catch its prey. So a lot of gusts of 40 to 70 mph when prevailing winds (2 minute) are running 3 to 7 mph are due to the birds, rather the true wind flow. We don’t have time to correct each site’s data in our area…so try to do so with our primary climate sites only. It is time consuming…and we aren’t always able to do so…(eyeball adjustments???)
Just thought you would like to know. The FAA and NWS are looking into trying to fix the problem…but so far nothing has worked. They are aware of what has been going on…but still haven’t come up with an answer. Also, this has been going on without letting the public know what is going on… Oh, for the old days, when you just had to determine whether the winds were light or calm…or the cups had become frozen… Back in the days of the F420 wind set… Just a heads up…
From an HMT somewhere along the east edge of the Rockies.
Anthony,
Despite the silly response by 899, this type of geographical observation has been used to study temperature change over various terrain, for instance, Karlsson 2000. TJA’s suggestion (measuring the areas around USHCN stations) should be taken seriously and added to the surfacestations.org database, similar to what CDRG called for here:
http://home.earthlink.net/~ponderthemaunder/id35.html
Set them up with connections to sensors in swimming pools and watch the temp. in the pool water world wide, the pools will show up via google maps.
The locations will be able to be known by all.
The small weather station can be away from the pool area.
It is a great idea to sell weather stations to raise money for this blog.
Be sure the govt./govt’s are not messing with the supply of insturments.
I for one would not put it past them to rig the thermometers and or other
insturments to “hide their decline”.
Out in the “outback” , “ranch land” , and or no pool areas use stock tanks, tanks by water wells that serve livestock.
Never allow goverments to do those things you can do for yourself and you will remin free.
They can not fight say, 500,000 independent data sources that can be proved up as true and correct.
IMHO
All merchent ships could be also rigged up with water temp. insturments and gather data from the ocean areas.
May I assume that this experiment would be invalid if conducted in direct sunlight? I would think that the absolute values would be off. I am not sure what the theory would say about relative values.
REPLY: At 60 mph highway speed or even at street speeds of 30 mph biasing effects of sunlight on the sensor housing would be negligible as any localized heating is carried off in the airstream. If your vehicle stops at a stoplight, then yes you’d have an issue but it will disappear once moving again. -A
Ecotretas (01:38:15) :
See :
http://www.gpsvisualizer.com/convert_input
This website converts a standard gpx file to a text file, including the time stamp. You could read the converted gpx file & data logger file both into Excel , sort on the time data & pair the lat longs with the temp data.
Then see this link:
http://www.gpsvisualizer.com/map_input?form=data
This link has the format you will need, which could be generated out of Excel easily & allow you to plot the temp data on a map.
In general, I think the GPS Visualizer site has all the tools you need.
Anthony, if this UHI experiment takes off amongst the community, you might want to contact the guy who run the GPS Visualizer site (link on the website) & set up a little custom app to do all of this. You could set it up on the WUWT site as a separate page which users could both upload & visualize their data, as well as other datasets from around the world. With all those datasets, it might be possible to create a much better UHI correction (relating to town size, distance from center, time of day, etc).
Neat, I love ‘kiss’
lots of people will have time/distance datalogger they use when running/cycling. These tend to have a standard time/position dump that can be read by google maps/earth.
There’s an app for that too on iPhone etc (free & paid) …
So it is comparatively easy to get route/speed/velocity data & then just mash them all together.
And all you hams – this looks an ideal APRS project : strip the datalogs via APRS mesage……
Next step is obviusly to merge the temp/humidiy (what chance pressure ? ) with gps.
Anyone think of doing runs that take in (multiple) weather reporting stations ?
BTW here in the UK we are not allowed to drive any distance without having to stop; our traffic planners seem to think the best way to control traffic is to make it stop, especially on empty roads late at night
You could sell the info to “Lloyds of London”, Ins. exchange , as they need the real data info for setting ins. rates, it being the data they now recive is bs from goverments.
Others in need or real data would also be your customers.
Anthony you say : And yes, I do ship internationally.
But your indicative international postal charges are very scary.
It does say that there will be an e-mail approval but it is only that I trust you, after so long on this board, that I will send in an “179.95$ finalize sale” for a 79.95 item.
I often get stuff from Amazon.com and the postal rates are given on the spot while ordering, and are nowhere near 100$. For example for 3 books they are around 12euros.
If you want international customers you should get something like that.
REPLY: Yes sometimes the shipping calculator gets whacked. We’ll correct it. – Anthony
Good stuff but surely what is at issue are two things: has UHI changed over time for a given thermometer (so giving misleading anomalies); and has the decline in rural stations produced false average anomalies because UHI absolutes have been under (or over/sarc) estimated (and corrected for properly)?
All data is useful, but measurements over a long time would be needed, really.
REPLY: And there’s no reason why the same transect can’t be driven many times at different times of the year. – A
If a few thousand people got these and someone set up a database where the information could be collected, it could be a tremendous source of valuable data.
Chico UHI numbers are very similar to what I typically see in Fort Collins.
When people start using these, it is important to take transects in a way that does not introduce systematic bias. Like in to downtown in the morning and out in evening, which would both tend to make downtown look warmer due to morning heating and evening cooling. The best approach is to transect the entire city like Anthony did.
I do my transects on a bicycle, which has the advantage of very low thermal mass, and I ride on devoted bike trails where I almost never have to stop.
Data can be obtained with older cheaper off the shelf instruments.
example google operation igloowhite
a electronic data collection system set up
in a jungle, in a war zone, in the rain of monsoons
it worked then, something like it can be done now in this case
under wiki
here http://www.operationigloowhite.com
igloowhite (06:15:27) :
All merchent ships could be also rigged up with water temp. insturments and gather data from the ocean areas.
*************************************
If (a big if) “they” wanted to instrument a merchant ship for both sea temperature and air temperature, it would be relatively simple. (or navy ships for that matter.)
Both steam and diesel powered ships use prodigous amounts of sea water for cooling. It would be necessary to prove that the quantity of water flow through the cooling system while at sea was enough to prevent a measurable thermal contamination, but should that prove to be the case, installing a termal probe would be simple. I would mount it in the intake piping between the main sea suction valve and the sea water circulating pump. Alternately, you could mount it on a manhole cover on the inlet of the largest cooler availavble, although you should prove first that there is little or no thermal contamination that far into the ship.
The air probe could be mounted on the radar/radio mast and it would be perhaps 100 feet above ocean surface.
An interesting project.
Regards,
Steamboat Jack
What a fantastic thing to do, Anthony!
I’d like to help out and suggest that for anyone needing to do a clever ‘trick’ and splice data, Scotch brand Magic Tape is available at Walgreens for only $1.99. And just like the algorithms used by NOAA, CRU and all the others for adjusting data, Scotch Magic Tape is invisible.
Seriously though, I think this is one of those simple groundbreaking ideas that could crumble an AGW house of cards.
For me here in Reno, it could be very interesting to transect I-80 and 395 at 5pm, and 5am.
Anthony,
Slightly OT:
Given, as you say, the world’s surface data is measured to the nearest degree, how can they measure global anomalies of fractions of a degree?
John Finn (05:42:45)
“The real question is whether the UH effect has contaminated the readings at the same location over the last 50 to 100 years and whether this has had a significant influence on the global surface temperature trend. The evidence suggests not.
Surely the lesson of climategate is that the “evidence” has been comprehensively manipulated (homogenized) by propagandists.
That being the case, it makes a great deal of sense to collect data first hand as Anthony has done here. There are, after all, good reasons to suspect the 100 year record has been inflated by UHI, since during that time:
– world population has multiplied by a factor of about 4
– world GDP has multiplied by a factor of about 40
Both increases have largely been concentrated in cities.
My RHT-10 from Extech looks a whole lot like the one from Anthony’s store (got it before I started lurking here) but the software reads out in 0.1 degrees C. Cost the same, so perhaps 0.5C is only a software limit? The sample rate is programmable and the unit can hold 16,000 readings, all with nice time stamps. My USB gps unit coupled to a netbook can do the same, so no distractions while driving. Set it and go. Post process on a spreadsheet, the GPS data should allow removal or at least take note of any stops. Set the logger’s time from the PC (Windows now sync’s up with NIST, so the clock should be good), the GPS will have exact time, all should tally.
My only complaint is I didn’t think of doing this. 🙁
A new task for Anthony’s Army: let’s verify just what the hockey stick is going on. We’re pretty sure UHI is real, now we can get hard data.
Steve Goddard (06:40:07) :
When people start using these, it is important to take transects in a way that does not introduce systematic bias. Like in to downtown in the morning and out in evening, which would both tend to make downtown look warmer due to morning heating and evening cooling. The best approach is to transect the entire city like Anthony did.
—
I think some of that is data vs analysis. If this could be widespread, then one source of data may be from people’s commutes. Those generally would be pretty consistent for time of day, route and provide data over a wider timespan than more formal survey type transects. With enough loggers, that should give a higher resolution heat map than we have currently. Seems a great way to improve data collection to me, if there’s an easy way to upload it for interested parties to crunch.
I just ordered mine. Anthony, what an awesome idea; can’t wait until my arrives.