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Meccano has grown into The Meccanoid, a self-build robot for kid Wow, Meccano has certainly brought itself up to date with the Meccanoid. Meccano is the company that entertained generations of kids with metal strips, angles with holes and lots of nuts and bolts and wheels, axles and gears to make cars, cranes and… Read more »
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A Few Good Apps to Brighten Up the Day
Some apps just make you want to bang your head on a brick wall A round-up of eleven favourite apps among the millions on offer. They still keep coming because people still keep inventing them. People still keep downloading them either free or paying out for them. The world's love affair (obsession) with apps appears… Read more »
If You Like My Thoughts, You Must Be on the Facebook Telepathy Button!
Facebook could host telepathy in years to come! You may have missed the fuss, but Facebook's Mark Zuckerberg has set the cat among the pigeons with his views on the future direction of social media and how we'll be able to 'send emotions to each other online….' In an interview reported in the British… Read more »
Filling the Gaps in Britain's Coding Skills
BBC Micro creators with birthday cake in 2012 – now a new way of teaching coding is needed This autumn, digital literacy is going to be big on the agenda – particularly Britain's skills shortage in coding. It was getting on for 25 years ago that the BBC gave most schools in the UK… Read more »
Unconventional Computing Is the New Order of the Day
From unconventional computing by slime mould to mainstream future? Just as the world seems settled in its mastery of all things digital with a basic menu of silicon chips, the boffins at work on new and unconventional computing methods look set to give us all another massive shake-up. A book published in 2012 is being… Read more »


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OEM Configurer: Free Utility to Add OEM Information and Logo in System Properties of Windows XP, Vista and 7
We have posted tutorials for customizing System Properties window in Windows XP, Vista and 7:
- Add Customized Strings (OEM Information) in System Properties of Windows Vista and 7
- Add Customized Strings (OEM Information) and Logo in System Properties of Windows XP
The above tutorials inspired our reader "Masroor Aijaz aka JX Great" and he created an awesome portable utility "OEM Configurer" which allows you to customize Windows XP, Vista and 7 System Properties window look without any manual editing. You just need to enter desired text and select desired logo file and it'll do the rest automatically.
It also allows you to customize and change various items in System Properties window like Owner name, processor name, etc.
You can download it using following link:
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What makes you think the kid is mine? Funny pics, hilariousness, humour animal, jokes funny, funny cats …For the funniest pictures and jokes funny visit www.bestfunnyjokes4u.com/rofl-best-funny-joke-pic/
i had a mom and lil baby kitten that looked literally identical...like more then these two!
Funny pics, hilariousness, humour animal, jokes funny, funny cats …For the funniest pictures and jokes funny visit #cute cats #Baby Cats| http://baby-clothes-tavares.blogspot.com
What makes you think this kid is mine? Very cute too bad they're both female. (Calico cats are always female and the 2% that are male are born stetril.) Very cute tho!
Related Pins
"In order to keep a true perspective of one's importance, everyone should have a dog who adores him, and cat who ignores him." --Author Unknown
Half Portrait of Puss Pinner wrote: A second attempt at trying to transfer some standard portrait techniques resulted in this feline equivalent of the 'half portrait' shots that I've seen done quite well elsewhere. No portrait shoot is complete without the traditional black and whtie conversion and here I've used the conversion process to really pull out the contrast in the fur.
CAT ON A CHAIR LOOKING OUT ON THE BIG WORLD........LIKES HIS PROTECTED WORLD INSIDE SO MUCH BETTER, THANK YOU VERY MUCH........ccp
Workin' on a hairball... #cat #cats =^..^= www.zazzle.com/...
Tiny kittens! There are 3 of these about 6 wks. hanging around here now. they followed their half wild mama over here just this week! Getting bold already. Hope to tame them and find them homes ladies! One black, light orange striped and one looks like it will be a tabby point siamese like the mama. Just want all my Pinterest friends to be thinking about it. :)
Chris Illman....I'm going to sneak up on that mouse!
017/365 - Observándome des del hemisferio sur | Looking at me from the south hemisphere by Marc Mateos, via Flickr
Friends....., I trained my first rescue akita to let the cats play with him because he had a fan club of two cats who loved walking with us when I walked him.
sweet tabby kitten white shirt cute. looks just like my baby girl.
[CasaGiardino] ♡ Cosette had always had trouble executing the perfect French knot, but her dear friend, Madame Puzzi-chat, told her not to fret and quickly, with deft paws, expertly twisted the blond strands into a tidy bun. Now...if only Cosette could get Madame to step down.


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Groupon snaps up Canadian grocery couponing app
Daily deals website Groupon says it has purchased SnapSaves, a Canadian-made couponing app that launched last year.
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Daily deals website Groupon says it has purchased SnapSaves, a Canadian-made couponing app that launched last year.
While the details of the transaction weren't revealed, including the price of the acquisition, it marks a sign of the growing popularity of smartphone apps in the grocery industry.
SnapSaves was created by Toronto-based company Buytopia, which has a deal-of-the-day business model similar to Groupon.
Shoppers can snap a picture of their grocery receipt using the app and receive money back on selected items that range from diapers and cereal to fresh produce and wine.
Once the redemptions cross a threshold, the user can request a cheque in the mail for the money they've saved.
The SnapSaves acquisition was completed on June 13, Groupon spokesman Bill Roberts said in an email on Monday.
"We're excited that SnapSaves is joining the Groupon family," he added.
SnapSaves says the deal will increase the variety of offers available, and expand its reach to Groupon's 52 million active customers across North America.
Other similar money-saving apps have appeared on the market in recent years, including Checkout 51, a Toronto-based startup founded two years ago.
Groupon is bulking up its mobile offerings after unveiling an app version of its website last fall. Since its debut, the app has spiked in popularity and amounted to more than half of the company's transactions during the first quarter, the company said.
Earlier this month, Groupon expanded its Freebies digital coupon feature onto smartphones in the United States.
Freebies lets users access more than 30,000 digital coupons, promotions and samples at major retailers like Target, Sears, Bath & Body Works and J. Crew through Apple's iPhone.
Groupon has plans to make Freebies available outside the U.S. by the end of the year.
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Click the ADD button and show us where you think the worst potholes are located. Use + and - to zoom in or out on the map. You can also upload photos and videos.
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Art + Soul: Sheila E., Lenny Williams and more top acts
The annuakl Oakland festival also features Family Stone, Caravan of Allstars and Edwin Hawkins' Gospel Showcase, among other attractions.
Train co-founder Hotchkiss back on track with new band
The Grammy singer-songwriter Rob Hotchkiss won as a founding member of the multiplatinum band Train sits inconspicuously on a shelf in the hillside house in Fairfax that he and his wife, Pam, recently moved into,returning to the Bay Area after years of semi-retirement on Vashon Island in Washington's Puget Sound.


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The Largest Arkansas Manufacturers list is ranked by number of employees. It includes most recent year's total and year-over-year change, Arkansas locations, line of business, top executive, and contact information. Updated 2/24/2014
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Futrell House Bed & Breakfast
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From Red Top Mtn. To Nashville, TN
I managed to get a really bad cold so spent the day feeling miserable. Weather was pretty bad as well as was the traffic. This just comes under the heading, "Some days are just like that!". I slept like the dead after going to bed around 9 PM. We only stopped at 7:30 PM cause I kept pulling over to take a power nap. Had a very quick dinner of roast chicken which we bought earlier in the day along with a few other ...
Kentucky Dam
We were only 4 miles away from the Kentucky Dam wen we stopped for lunch so we decided to take a little detour and visit. It was a nice day, but the smell of dead fish was a bit overwhelming when we walked down to the water. After exploring for a brief time we piled back in the car and headed on our way. ...
Travels with Nick and Nora
Nashville and Land Between the Lakes KY We spent two days in Nashville and were pleasantly surprised at how lovely it was. We took a tour which lasted about 5 hours and pretty much covered everything. The first thing that struck us was how clean the city is. We kept thinking it would be similar to Memphis but there is no comparison. There are many contemporary buildings and the older ones are kept in ...
JD Tour Day!..
... t sell them anymore. Someone saved themselves a lot of money! We are now heading back home. This trip is everything we thought RV life would be. Seeing beautiful country ( when we were on the back roads), experiencing new places and all the while having our dogs with us, no dogs left behind!!! Hope you enjoyed the first of our many trips and adventures! Next up, our float trip - hold on to your hats... P.S. We need a new awning but that's another story for another ...
Parker's Crossroads and Fort Donelson
After leaving Corinth, I drove through Tennessee to Parker's Crossroads, another Forrest battlefield at the meeting point of two highways. I followed the main stops of the driving tour and walked much of the preserved parts of the battlefield, which was effectively bisected along the east/west axis by the interstate. I noticed that this ...


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It's not just Bushie loyalists and Republicans who are gunning for more money to be poured (out of taxpayers' pockets) into the Iraq war chest. Take Sen. Joe Biden (D-Del.), who is aiming to double Bush's proposed $12 billion in funding for the rapid production of mine resistant ambush protected (MRAP) vehicles—a proposition which, Scheer argues, is about much more than the security of U.S. troops.
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OC3D Reviews ›› All
HIS Radeon 4670, 4830 & 4850 Mid Range Round-Up
GPU & Displays | 9th November 2008
HIS are at the top of their game at the moment, so when they offered us the 4670 & 4830 to review, we couldn't resist.
Far Cry 2 - A Far Cry From The Original?
Software | 6th November 2008
In conjunction with the release of the XFX GTX260 Black Edition we get to sample Far Cry 2 and give you the lowdown if its a worthy successor to the original.
Gigabyte 3D Aurora Case
Cases & Cooling | 5th November 2008
Overclock3D were given the opportunity to check out an oldie, but a goodie in the chassis department.
OC3D Articles ›› All
ASUS R9 Fury Strix listed online
Mark Campbell | 6th July 2015
The ASUS R9 Fury Strix has been listed online.
PS4 has a massive lead over Xbox One
Mark Campbell | 5th July 2015
According to sales figures the PS4 is dominating the console market, with the PS4 reportedly selling almost 2x the number of units as the Xbox One.
EVGA V2 SLI Bridge With Several Colour Options
Mark Campbell | 5th July 2015
EVGA have the V2 version of their SLI Bridge coming soon with Several Colour different colour options. Other Manufacturers really need to follow suit.
Super Mario Nvidia Flex Demo in Unreal Engine 4
Mark Campbell | 5th July 2015
Have a look at Super Mario running through an Nvidia Physx Flex Demo in Unreal Engine 4, it is even available to download for Nvidia users.
Gigabyte EP45-EXTREME
CPU & Mainboard | 4th November 2008
With a full copper heatpipe, massive air cooler and the optional watercooling block, the EP45- EXTREME certainly talks a good game but can it back up that talk with EXTREME performance?
Core i7 Nehalem Benchmarks Preview
CPU & Mainboard | 3rd November 2008
Finally the NDA has been lifted and today we can give you all exactly what you've been waiting for: Core i7 BENCHMARKS
XFX GTX260 896MB 'Black Edition'
GPU & Displays | 1st November 2008
More than a refresh, the GTX 260 Black Edition utilises NVidias 2nd generation Unified Architecture. With some stiff competition around at the moment, can it cut the mustard?
OCZ Behemoth Mouse Pad
Input Devices | 28th October 2008
Last month we took a look at OCZ's new Dominatrix Laser Mouse. This month we look at their gaming mouse pad to see how it performs.
ASUS Rampage II Extreme X58 Motherboard Preview
CPU & Mainboard | 24th October 2008
OC3D had the opportunity to take a look at the new ASUS Rampage II Extreme which is based upon the X58 chipset. What will it offer over current motherboards?
Minecraft: Windows 10 Edition Beta
Mark Campbell | 4th July 2015
Today, at Minecon 2015 it was announced that Minecraft: Windows 10 Edition Beta is coming.
Star Wars Battlefront Closed Alpha Screenshots 4K
Mark Campbell | 4th July 2015
Have a look at some new Star Wars Battlefront Closed Alpha Screenshots at 4K. What do you think of the game's visuals?
AMD R9 Fury Specs detailed
Mark Campbell | 4th July 2015
Specifications for AMD's R9 Fury have been detailed, making this $549 GPU look like a real GTX 980 killer.
Minecraft: Story Mode Trailer
Mark Campbell | 4th July 2015
A trailer for Minecraft: Story Mode has been released. It is a five-part episodic series that will take you to the Nether, the Farlands, the End, and beyond!
Nvidia HairWorks 1.1 Demo
Mark Campbell | 3rd July 2015
Nvidia's HairWorks may have some bad press, but you have to admit that it looks great. Have a look at Nvidia HairWorks 1.1
Intel Announces Leadership Changes
Mark Campbell | 3rd July 2015
Today Intel Corporation's CEO, Brian Krzanich, announced a series of leadership and organizational changes in a message to employees.


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Lil Wayne and 2 Chainz would go on to do plenty of collaborations, but this "Duffle Bag Boy" was the first big one, and it came back when Chainz was still Tity Boi.
Bump Hustla, the latest cut from Young Rhome featuring Playaz Circle on the assist. It was released on Tuesday, March 20th, 2012. Things are improving for Young Rhome with each new offering, and Hustla is certainly no exception.
Listen to Pain, the new track by Playaz Circle, which was dropped on Thursday, September 29th, 2011. Playaz Circle's odds keep getting better with each new leak, and Pain will undoubtedly improve his chances of winning.
Stream Issues (Prod By Drumma Boy), the newest drop from Playaz Circle which features Young Buck. The cut was released on Wednesday, July 28th, 2010.
Stream Juug, the newest drop from Playaz Circle. The cut was released on Thursday, July 15th, 2010. Things are looking better for Playaz Circle with each new release, which Juug has proven yet again.
Was the inclusion of Lil Wayne, Birdman a good call? Are y'all feeling this one? Hear more of Playaz Circle on Juug. Hit up Playaz Circle's profile page for the latest info, news, songs, and mixtapes. Remember to follow Playaz Circle on Twitter.
Stream Big Dawg, the newest drop from Playaz Circle which features Lil' Wayne, Birdman. The cut was released on Friday, December 11th, 2009. Playaz Circle continues to impress with each new leak, and Big Dawg is no exception.
Stream Can't Remember, the newest drop from Playaz Circle which features Bobby V. The cut was released on Friday, December 11th, 2009. Things are looking better for Playaz Circle with each new release, which Can't Remember has proven yet again.
Check out Stupid (Remix), the latest from Playaz Circle which features a guest appearance from Young Jeezy, Lil' Wayne on the assist. The track was released on Friday, December 11th, 2009.
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Free Shipping
Product Information:
This mirror features an impressive black frame with a distinctive raised surface.
Weights & Dimensions
|Mirror Type: Wall mirror
|Frame Shape: Rectangle
|Hanging Orientation: Both
|Frame Finish: Black
|Distressed: No
|Frame Material: Wood
|Hardware Material: Stainless steel
|Number of Items Included: 1
|Jewelry Storage Included: No
|Shelves Included: No
|Drawers Included: No
|Wall Mounting Hardware: No
|Stemware Storage Included: No
|Swing Arm Included: No
|Lighted: No
|Beveled Glass: Yes
|Tilt Mirror: No
|Life Stage: Adult
|Commercial Use: No
|Eco-Friendly: No
|Product Care: Simply dust the frame with a soft rag or duster to remove surface dust.
|Country of Manufacture: United States
|Assembly Required: No
|Installation Required: Yes
|Additional Parts Required: No
|Product Warranty: 30 Days
|ADA Compliant: No
About the ManufacturerNothing finishes a room better than adding framed art prints to your walls. Amanti Art has hundreds of mats and frames to choose from. Their quality meets or exceeds what you would get at your local frame shop, with prices significantly lower!
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We want you to love it. If you don't, you may return your purchase within 30 days of delivery. All you need to do is visit our Self-Service Return Center for instructions. Return credits are issued within 24 hours once the item is received and inspected. Please note that shipping charges are non-refundable. The cost of return shipping will be deducted from your refund. 30-Day Return Policy
Average Overall Rating (based on 3 reviews)
Exactly what I was looking for! Kathryn from Indianapolis, IN on 02/15/2015 – Verified Buyer
This mirror arrived within a short amount of time. Ordering on line was easy and the mirror is exactly as it was described and looked in the picture. It fits perfectly over my mantle and I could not have been happier with my purchase and Wayfair.com!
Mirror Karen H. from St. Louis, MO. on 04/21/2013
Beautiful mirror in black wood, just the right size to fit where I needed it. Basic black mirror to go anywhere.
Anonymous from Maryland on 10/21/2013
'Three Ages of Woman-Mother and Child (Detail IV)' by Gustav Klimt Framed Painting Print
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This bragging about your pile of spaghetti is really starting to frustrate me.<quoted text>
I believe in the only true God -- the only God for whom no soul has been killed or tortured. That's proof of my God.
Come to the light. He was boiled for you.
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By the way are you one of those male theologians that looks down on women???
Why is your spaghetti god male rather than bi-sexual??? For a change I demand equal treatment from the sky.


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Transcript of "De5.1 report"
1. Algorithms for QPE, 3D mosaic and hydrometeor classification Deliverable De5.1 L. Liu1 , H. Wang1 , Y. Xiao1 , Z. Hu1 1 Chinese Academy of Meteorological Sciences, CAS, P.R. China Dissemintation level: Programme Participants Lead beneficiary ID: CAMS
ISSN/ISBN: c 2010 Edited by the CEOP-AEGIS Project Office LSIIT/TRIO, University of Strasbourg BP10413, F-67412 ILLKIRCH Cedex, France Phone: +33 368 854 528; Fax: +33 368 854 531 e-mail: firstname.lastname@example.com part of this publication may be reproduced or published in any formor by any means, or stored in a database or retrieval system, without thewritten permission of the CEOP-AEGIS Project Office.
CEOP-AEGIS Report De 5.1 Table of content1.! Introduction ................................................................................................................................................... 2! 1.1.! Identification .......................................................................................................................................... 2! 1.2.! Overview ................................................................................................................................................ 2!2.! 2. Algorithm Description I (QPE and 3D mosaic)........................................................................................ 2! 2.1.! Introduction ............................................................................................................................................ 2! 2.2.! Targets to be observed ........................................................................................................................... 2! 2.3.! Observation radar system....................................................................................................................... 2! 2.4.! Coverage of radar network..................................................................................................................... 4! 2.5.! QC of radar data ..................................................................................................................................... 5! 2.6.! Remap of raw data ................................................................................................................................. 8! 2.7.! Mosaic .................................................................................................................................................. 10! 2.8.! Qualitative Precipitation estimation (QPE).......................................................................................... 11!3.! Algorithm Prototyping ................................................................................................................................ 13! 3.1.! Mountain blockage and radar coverage ............................................................................................... 13! 3.2.! Radar data Quality................................................................................................................................ 14! 3.3.! Remap of reflectivity............................................................................................................................ 15!4.! Validation Plan............................................................................................................................................ 15! 4.1.! Introduction .......................................................................................................................................... 15! 4.2.! Approach .............................................................................................................................................. 16! 4.3.! Validation Sites .................................................................................................................................... 16!5.! Ancillary Data ............................................................................................................................................. 16!6.! 6. Algorithm Description II (Hydrometeor classification).......................................................................... 16! 6.1.! Introduction .......................................................................................................................................... 16! 6.2.! Targets to be observed ......................................................................................................................... 16! 6.3.! Input and output ................................................................................................................................... 17! 6.4.! Inference............................................................................................................................................... 20! 6.5.! Aggregation.......................................................................................................................................... 20!7.! Algorithm Prototyping ................................................................................................................................ 20!8.! Validation Plan............................................................................................................................................ 21! 8.1.! Introduction .......................................................................................................................................... 21! 8.2.! Approach .............................................................................................................................................. 22! 8.3.! Validation Sites .................................................................................................................................... 22!9.! Ancillary Data ............................................................................................................................................. 22! 1
CEOP-AEGIS Report De 5.1!" #$%&()*%+$,, 1.1. Identification The Algorithm for Qualitative Precipitation Estimation (QPE), 3 Dimensional (3D)mosaic. Algorithm for hydrometeor type classification with polarimetric radar. 1.2. Overview In this report, the radar scan strategies and the associated beam geometry in Tibetanand Qinghai Province is first introduced. The following section (2 to 5) provides the radarcoverage in mountain regions, radar data quality, transformation of radar data fromspherical coordinate to Cartesian grid, mosaic of reflectivity. The fuzzy logic method for classification of hydrometeor type based on polarimetricradar measurements is described in sections 6 to 9.-" -",./0&+%12,345*&+6%+$,#,789:,;$(,<3,25;+*=, 2.1. Introduction The Algorithm for Quantitative Precipitation Estimation (QPE), 3 Dimensional (3D)mosaic include: (1) radar data quality control; (2) transformation of radar data fromspherical coordinate to Cartesian grid; (3) mosaic of reflectivity; (4) Z-R relationship andprecipitation estimation. 2.2. Targets to be observed The Algorithm is used to construct 3D reflectivity and precipitation estimation productswith high temporal and spatial resolutions. 2.3. Observation radar system In Tibetan Plateau, there are four C band Doppler radars, located in Lasa, Naqu, Rikezeand Linzhi, respectively. There are also 2 C band Doppler radars in Qinghai Province,located in Xining and. There radars do continuously 24h observation one day in summerwith volume scan 6 minute. The C band Doppler radar works on 5.5 cm wavelength withbeam width of 1.0°, and gate width of 250m. There radars performed volume scan with 14or 9 elevation angles once every 5 min which are similar with WSR-88D (Fig.2.1 ). 2
CEOP-AEGIS Report De 5.1 19.5 16.7 14 12 10 8.7 7.5 6.2 5.25 4.3 3.35 2.4 1.45 0.5 19.5 14.6 9.9 6.0 4.3 3.35 2.4 1.45 0.5 Fig.2.1 The volume scans of VCP11 top and VCP21 bottom) The radar data analyses should provide end users with high-resolution radar reflectivitydata fields that are comparable to the raw data with the advantage of a Cartesian coordinatesystem (longitude, latitude, altitude (above mean sea level (MSL) ). A Cartesian coordinatesystem provides a common framework in which other observational datasets, such asprecipitation data, can be merged and cross-correlated. 3
CEOP-AEGIS Report De 5.1 2.4. Coverage of radar network The mountain blockages to radar network were analyze with ground surface altitude data,and the radar data for precipitation cases were used in examining the mountain blockage forradar beams. The beam blockage by mountain was calculated using an algorithm that usedhigh resolution DEM digital elevation model data, radar beam pattern (Gaussian beamapproximation), and radar beam propagation path (assuming radar beams propagate understandard atmospheric refraction conditions). Assuming the ground target position is defined , the radar position is . The distance along the earth surface, azimuth and elevation of groundtarget with radar are calculated by: 2.1 2.2 2.3Where is earth radius is equivalent radius is linear distance fromradar to ground target, which is got by: 2.4 The altitude of ground target is got with DEM data. According to the calculation results, we can get the hybrid scan for each scan. The hybridscan mean that for each radar beam and gate, it defines as the lowest elevation angle with nomountain blockage for echo azimuth, using hybrid scan data for each radar, we can definethe radar coverage and reflectivity for QPE. 4
CEOP-AEGIS Report De 5.1 2.5. QC of radar data The fuzzy logical based algorithm is used to detect the anomalous propagation groundclutter. Briefly, a fuzzy logic classifier uses various derived fields (formally known as"features") as input, scales them to a common reference frame by use of a "membershipfunction," and then computes a weighted sum of the resultant "interest" fields. Afterapplication of a threshold, the final output product of the detection algorithm is obtained andcontains the locations of the AP ground clutter. The general schematic of AP clutterdetection algorithms is shown in Fig. 2.2. The reflectivity, radial velocity and spectrumwidth in polar coordinate are input into the "feature generator" for calculation of thefeatures. The features used in the software includes: texture of the reflectivity (TdBZ), thevertical difference of the reflectivity (GDBZ) between two elevation angles, the medianradial velocity (MVE) and spectrum width (MSW), the standard deviation of radial velocity(SDEV), Percent of all of possible differences, that exceed the minimum differencethreshold (SPIN) and mean sign of reflectivity change along range (SIGN). The TDBZ,SDEV and RGDZ are defined as: (2.5) (2.6)where the Ngates and Nbeams are range and azimuth interval to defined a regional area. Forfeatures derived from reflectivity, Ngates=5 and Nbeams=5, for radial velocity andspectrum width, the Ngates=9 and Nbeams=5. (2.7)where Rangewet defined in Fig.2 (H) is range weighting function. (2.8) where the ALL_counts is toll number of radar data in specified area . SPINchang_countsand All_counts is calculated as: 5
CEOP-AEGIS Report De 5.1 (2.9) The value of Zthresh=2dBZ for WSR-88D is suitable to separate the AP clutter fromprecipitation echo (Sterner and Smith, 2002). (2.10) where: (2.11) The MDVE and MDSW are calculated by median filtering along the range for 7 gates.Three features from reflectivity, two features from velocity, one from spectrum width andone from vertical structure of reflectivity are used in the software to detect AP clutter. Theseven features calculated gate by gate are input to the memberships to calculate the interests,respectively. Fig.2.3 shows the memberships for the seven features. The echo with lowradial velocity and spectrum width, high horizontal and vertical spatial gradient, has highlikelihood to be AP clutter. The difference between this algorithm described in this paperand method proposed by Kessinge are that the median velocity and spectrum are used in thismodel, instead of mean velocity and spectrum, considering the velocity folding and noise ofthe data. All of memberships are given a equal weight when calculating the interest field of APclutter, and 0.5 is the threshold to detect the AP clutter. Fig. 2.2 The general schematics of AP clutter detection algorithms. 6
CEOP-AEGIS Report De 5.1 a b c d e f Fig 2.3 The membership functions of MDVE a SDVE b SW c TDBZ d GDBZ e SPIN f for ground clutter detection. 7
CEOP-AEGIS Report De 5.1 2.6. Remap of raw data The transformation of radar data from a spherical coordinate to a Cartesian gridprovides a more direct approach of combining multiple radars onto a common grid. Thisprovides the ability to integrate the full-resolution base-level data from multiple radars ontoa common 3D framework. The 3D mosaic grid can benefit forecasters, meteorologists, andresearchers with a wide variety of products and displays, including flexible horizontal orvertical cross sections in addition to regional rainfall maps. High-resolution reflectivityanalyses can also serve as an important source in data assimilations for convective-scalenumerical weather modeling over large domains and for merging conventional datasets withthe radar data. Four interpolation approaches were investigated to remap raw radar reflectivity fieldsonto a 3D Cartesian grid with high resolution. (1)Nearest-neighbor mapping The nearest neighbor mapping (NNM) uses the value of the closest radar bin to grid cell,where distance is evaluated using the location of the centers of the radar bins. (2)nearest neighbor on range-azimuth planes combined with a linear interpolation invertical direction NVI The Fig. 2.4 shows the schedule of the approach. For each grid ( )in smallelevation angles (<20°), Find two observations of radar raw data points( , ) on the two adjacent tilts below and above the grid cell, respectively,and at the same range and azimuth as the grid cell. 2.12Here are the interpolation weights given to the he reflectivity observations belowand above the grid cell, respectively. The weights are determined by : 2.13 8
CEOP-AEGIS Report De 5.1 2.14where !i, !o1, and !o2 represent elevation angles of the grid cell and the radar bins below andabove, respectively. 3 Linear interpolation in vertical direction plus a horizontal interpolation VHI Fig.5 shows the VHI approach. For the grid cell , the four reflectivityobservations are ,the analysisformula for the vertical and horizontal interpolation (VHI) scheme is 2.15Here are nterpolation weights given to the he reflectivity observations 2.16 2.17 (4) Dual linear interpolation As shown in Fig. are 8 reflectivityobservations near the grid cell , the analysis values is : (2.18) 2.19 2.20 In this study, the third approach is used to remap the raw radar data to 3D grid data. Figure 2.5 dual linear interpolation 9
CEOP-AEGIS Report De 5.1 2.7. Mosaic In addition to remapping single radar reflectivity fields, one must consider a multipleradar scenario where more than one radar collects reflectivity data for the same point inspace. The 4DDG provides a methodology that takes advantage of multiple observationswhile handling those observations that do not agree with each other. Some grid cells are sampled by more than one radar bin. The mosaic approach is tocalculated a final reflectivity value for grid cells oversampled by radar bins. Threeapproaches of combining multiple-radar reflectivity fields were investigated. They aremaximum reflectivity, Nearest-neighbor reflectivity and distance weighted means. Results have shown the distance- exponential-weighted mean scheme provided a spatiallyconsistent reflectivity mosaics while retaining the magnitude of the observations from theclose radar. Mosaics could mitigate various problems that caused by the geometry of radarbeam such as data voids with the cone of silence above the radar and in regions below thelowest beam. (1) Nearest-neighbor mosaic approach In this approach, the analysis value from the closest radar is assigned to the grid cell.The nearest-neighbor method does not impose any smoothing when creating a mosaic frommultiple radars. However, discontinuities may appear at the equidistant lines between radarsin the mosaicked field. 2 Maximum reflectivity This mosaicking method simply uses the maximum reflectivity value among themultiple observations that cover the same grid cell. This method does not involve smoothingand it retains the highest reflectivity intensities in the data fields. 3) Distance weighted means The mosaic method considered is a weighted mean, whereby the weight is based on thedistance between an individual grid cell and the radar location. Two weighting functionswere tested; both monotonically decrease with range, that is exponential weighting functionand Cressman weight function are used in this study. These distance weighted means takeadvantage of multiple observations while handling those observations that do not agree witheach other. The shape of an exponential weighting function is easily adjustable to achieve arapid decrease with range while retaining a positive weight value. Thus, an exponentially 10
CEOP-AEGIS Report De 5.1decaying function is especially useful for radar analysis and is employed in the algorithm.The two functions are expressed as following: 2.21 Here r is the distance of the observation from its respective radar and R is an adaptablelength scale (i.e., 100 km). 2.22Where is effective radius (i.e. 300 km) and r is the distance of the observation from itsrespective radar. The shape of an exponential weighting function is easily adjustable to achieve a rapiddecrease with range while retaining a positive weight value. Thus, an exponentiallydecaying function is especially useful for radar analysis and is employed in the algorithm. 2.8. Qualitative Precipitation estimation (QPE) The QPE Algorithm in this study is based on 3D mosaic. It composed of five mainscientific processing components and one external support functions. The five scientificsubalgorithms are identified as follows: 1) preprocessing 2) rain rate estimation, 3)accumulation , 4) adjustment , and 5) products ). The two support functions, precipitationdetection and rain gauge data acquisition.(1) Rain gauge data acquisition The external support function within the QPE is called the rain gauge data acquisitionfunction. It receives the rain gauge reports. In order to deal with all of kinds of rain gaugedata, the precipitation rate is transfer into unit structures, which include the position ofraingauge, beginning and end of time, precipitation amount.(2) Reflectivity preprocessing The CAPPI of 3D mosaic reflectivity between 2-5 km (MSL) is chosen to calculate theprecipitation. The altitude of CAPPI depend on the domain for QPE, the blockage of radarbeam, the precipitation system (deeply or shallow developed ) . The horizontal and verticalresolution of 3D grid data are 2km and 0.5km, respectively. Because the blockage of radarbeam in Tibetan is very serious, the compositive reflectivity will be used. This quality control step removes reflectivity data that are abnormally large inmagnitude but small in area, such as those associated with nonmeteorological targets 11
CEOP-AEGIS Report De 5.1(airplanes, anomalous propagation returns, or residual ground clutter). Two reflectivitythresholds are used here. Isolated sample bins are defined as grids with reflectivities thatexceed a certain threshold (an adaptable parameter currently set at 15 dBZ) and for which nomore than one of the eight surrounding neighbors is also above that same threshold. Isolatedbins are replaced with a valid reflectivity. A second maximum reflectivity threshold parameter (currently set at 65 dBZ) is used toquality control the extremely large point outlier reflectivity bins typically associated withresidual ground clutter or anomalous propagation that have not previously been removed byAP detection . If a grid has a reflectivity that exceeds this threshold, it is replaced with eitheran average of surrounding values if none of them are above the same threshold, or otherwiseit is assigned a very small value (7 dBZ; an adaptable parameter). This step will not removeall occurrences of residual clutter or anomalous propagation, and hence additional qualitycontrol steps are necessary.(3) Rain rate conversion from reflectivity It converts reflectivity factor data from the CAPPI of reflectivity in 3D mosaic into rainrates using a standard Z–R power law relationship derived from the empirical relationshipbetween the two variables. The current default equation is Z = 300R1.4 2.23where Z has units of mm6 m"3 and R in mm h"1. The Z–R parameter settings are designed tobe adjustable at each site. In this work, we design method to form Z-R relationship every volume scan. The rain rateand respective reflectivity are matched to fitting the Z-R relationship under the assumptionof Z–R power law relationship. The reflectivity stronger than 55dBZ are considered as hail cores of thunderstorms, it isnecessary to cap them at a maximum value expected to be associated with rain only. The"hail cap" threshold, an adaptable parameter representing the maximum expectedinstantaneous, rain rate, has typical values ranging from about 75 mm h"1 (3 in. h"1) to about150 mm h"1 (6 in. h"1) except in highly unusual events. (4) Gauge–radar adjustment A temporally fixed Z–R relationship, as is the current design of the PPS, will not beappropriate for all rainfall events. Because it is not currently feasible to manually adjust theZ–R parameters in real time due to the lack of proven, robust, and objective criteria valid 12
CEOP-AEGIS Report De 5.1over a broad range of rainfall types, it is useful to make automated adjustments to therainfall estimates by comparing them with real-time rain gauge data on an hourly time step.Real-time rain gauge data can be used to adjust the radar rainfall estimates in the algorithm.Optimal interpolation (OI) analysis is used in this QPE.<" ./0&+%12,9&%%>6+$0, 3.1. Mountain blockage and radar coverage The mountain blockages for radars in Tibetan and Qinghai are calculated. Figure 3.1shows the example of blockage of radar. The heavy rainfall case is used to examine thecoverage of the radar (Fig. 3. 2) Fig. 3.1 the blockage of Xining radar 13
CEOP-AEGIS Report De 5.1 Fi.g 3.2 the CAPPI of reflectivity at 3.0km 3.2. Radar data Quality The ground clutter and radio noise distinguish with the radar QC algorithm are shown inFig. 3.3 and 3.4 Fig. 3.3 The raw data and after QC data at 11:43, July 15, 2008 in Henan Province 14
CEOP-AEGIS Report De 5.1 Fig. 3.4 The raw data and after QC data at 14:46, July 15, 2008 in Jiangsu Province 3.3. Remap of reflectivity (a) (b) Fig. 3.5 the CAPPI of reflectivity in Xining Fig. 3.5 shows the CAPPI of reflectivity at 3km.?" @;/+(;%+$,9/;$,, 4.1. Introduction In mountain areas, radar observations are often contaminated by echoes from groundclutter, high-speed moving vehicles and by point-wise ground clutter under either normalpropagation (NP) or anomalous propagation (AP) conditions. Many factors can introducedthe bias of reflectivity measurement, such as transmitter power, noise figure variations.Transformation of radar data from spherical coordinate to Cartesian grid can also producehorizontal and vertical structures variations of reflectivity. The reflectivity bias betweendifferent radars can affect the 3-D mosaic. 15
CEOP-AEGIS Report De 5.1 4.2. Approach In order to validate the algorithm, the ground data, raw data display are compared withthe products from the algorithm. The experts can distinguish the ground clutter and radionoise pixels of radar each, this data is used to examine the radar data QC. 4.3. Validation Sites Chinese Academy of Meteor. Sciences.A" .$*+//;&>,3;%;,, The raw radar data from Qinghai Province and Tibetan; Raingauge data rom Qinghai Province and Tibetan; Processing radar data and provide 3D reflectivity data to WP5. Grid Reflectivity inQinghai from 18 July 2008 -21 July 2008 were product with spatial and temporalresolution (0.01°#0.01°#0.5km#5min), the radar data in Tibetan from 18 June 2008 to19June 2008, 18 July 2008 to 20 July 2008 were provide.B" B",./0&+%12,345*&+6%+$,##,7C>(&24%4&,*/;55+D+*;%+$=, 6.1. Introduction There are several methods that can be potentially used for hydrometeor identification,such as classification using differential reflectivity (ZDR) classification using lineardepolarization ratio (LDR), classification using specific differential propagation phase (KDP)and coefficient ($HV), classic statistical decision theory, neural networks, and fuzzy logic.Fuzzy logic is used in this study for classification because it has many inherent advantagesover other methods. Many polarimetric radar measurements lie in a limited measurementspace for each hydrometeor type. The fuzzy logic system possesses the ability to reachdistinct decisions based on overlapping and "noise contaminated" data. The fuzzy logicmethod for classification of hydrometeor type based on polarimetric radar is developed byChinese Academy of Meteorological Sciences. 6.2. Targets to be observed Algorithm for hydrological classification with polarimetric radar can generate thehydrological classification products (rain, snow, crystal, hail and graupel) from polarimetricradar raw data. A fuzzy logic method for classification of hydrometeor type based onpolarimetric radar measurements is described in this report. 16
CEOP-AEGIS Report De 5.1 First, the four radar measurements and altitude are fuzzified by using membershipfunctions. There are 10 membership functions for each of the input variables in the system.After fuzzification, then the membership functions are aggregated from each hydrometeortype. The last step is defuzzification, which can convert aggregation result to a singlehydrometeor type. The following provides detailed description of the steps used in theclassification process. 6.3. Input and output Four radar measurements, namely, horizontal reflectivity (ZH), differential reflectivity(ZDR), differential propagation phase shift (KDP) and correlation coefficient ["HV] have beenused as input variables to the fuzzy logical hydrometeors classification. ZH for horizontally and vertically polarized waves are proportional to the hydrometeor'scross section integrated over a volume. ZDR can be related to the axis ratio and size ofhydrometeors. The differential phase KDP is the difference between propagation constantsfor horizontally and vertically polarized waves .In the region filled with horizontallyoriented hydrometeors such as rain or ice crystals, a horizontally polarized wave has largerphase shifts (per unit length) and propagates more slowly than a vertically polarized wavedoes; the opposite holds for vertically oriented hydrometeors. In theory, KDP allowsdiscrimination between statistically isotropic and anisotropic hydrometeors; isotropichydrometeors produce similar phase shifts for horizontally and vertically polarized waves. The degree of decorrelation as measured using the correlation coefficient at zero lag $HVbetween horizontally and vertically polarized echoes results. Decorrelation physicallyoccurs if the horizontal and vertical backscatter fields do not vary similarly. $HV decreaseswith increasing diversity of hydrometeor orientations and shapes. When particles are wet orwhen they are large and irregular in shape. Moreover, $HV is lower when there are mixturesof hydrometeor types rather than when just one type is present. The output of the neuro-fuzzy system is one of the many possible hydrometeor types:1) drizzle, 2) rain, 3) dry and low density snow, 4) dry and high-density crystals, 5) wet andmelting snow, 6) dry graupel, 7) wet graupel, 8) small hail, 9) large hail, and 10) a mixtureof rain and hail. 17
CEOP-AEGIS Report De 5.1 Table 6.1 Output of the Algorithm for hydrological classification Hydrometer type Classify output Hydrometer type Classify output DRizzle(DR) 1 Dry Graupel(DG) 6 RAin(RA) 2 Wet Graupel 7 (WG) Dry Snow(DS) 3 Small Hail(SH) 8 Dry Cristal(DC) 4 Large Hail(LH) 9 Wet Snow (WS) 5 Hail Rain(HR) 10 The function of the "fuzzification" is to convert the crisp inputs (or precisemeasurements) to the fuzzy sets ( 0-1 ) with a corresponding membership degree. A specificcrisp input can be to different fuzzy sets but with different membership degrees (or truthvalue). The most important component in fuzzification is the membership function, which isused to describe the relationship of the crisp input and the fuzzy sets in the input domain.The definition of membership function is as follows: T(x) is called membership function offuzzy set A (for a fuzzy variable x), whose value is the degree to which x is a member offuzzy set A. (6.1) We can define the functions MBFi-j for each polarization variables i and hydrometeortypes. Fig. 6.1 shows the member function for polarization variables and hydrometeorclassifications. 18
CEOP-AEGIS Report De 5.1 (a) (b) (c) (d) 19
CEOP-AEGIS Report De 5.1 6.4. Inference In a fuzzy logic system, rules are used to describe linguistically the complex relationshipbetween the input and output fuzzy variables in the form of IF–THEN statements. Typically,the rule is composed of several antecedents in the IF statement and one or severalconsequents in the THEN statement. The process of deducing the "strength" of theseconsequents from the strength of the antecedents is called rule inference. The mostcommonly used inference methods are correlation minimum, correlation product, and MIN–MAX. The total contributions of polarization variables to the hydrometeor type are definedas: (6.2)Here Ai is coefficient weight for ith polarization variables. AZH=AZDR=1 AKDP=0.8A$HV=0.5. 6.5. Aggregation We can use the inference methods to derive the strength of each rule, then theaggregation method can be used to determine an overall fuzzy region. Two commonly usedaggregation methods are additive aggregation and MAX Aggregation, which mean that themaximum values of RSj is the hydrometeor type.E" ./0&+%12,9&%%>6+$0, The Koun radar in USA for hail storm is used to examine the algorithm. Figure 7.1 showsthe radar measurement. Figure 7. 2 shows the hydrometric classification results. 20
CEOP-AEGIS Report De 5.1 (a) (b) (c) (d) Figure 7.1 Four PPI image at 0.5 of the Oklahoma City tornado on 10 May2003 1903 UTC.Radar is located at the central point of half circle. (a) ZH (dBZ) (b)ZDR(dB) (c) DP(deg Km-1) (d) HV (a) (b) Figure 7.2 Two kinds of hydrometeor type classification results at 19:03 UTC by different inference rules: (a) PSi-j multiply (b) PSi-j plusF" @;/+(;%+$,9/;$,, 8.1. Introduction Knowing what precipitation type is reaching the ground is a fundamental prerequisite foraccurate determination of amount. Thus, for quantitative precipitation estimation (QPE),first a correct classification needs to be made so that appropriate semiempirical relations can 21
CEOP-AEGIS Report De 5.1be chosen to estimate the corresponding rates and/or accumulations. Because of sensitivityto hydrometeor concentration, shape, orientation, dielectric constant, and size, polarimetricvariables have emerged as leading discriminators of precipitation type. The situ observationwith aircraft is simpler means to develop and evaluate the algorithm, we also rely on spatialcontinuity, height above ground, and comparison with conceptual models to qualify thealgorithms performance. 8.2. Approach The radar observation will be compared with model output, the results are analyze toexamine the algorithm performance. 8.3. Validation Sites Chinese Academy of Meteor. Sciences.G" .$*+//;&>,3;%;,, The raw radar data from C band polarimetric radar; 22
CEOP-AEGIS Report De 5.1ReferencesBrandes, E. A., A. V. Ryzhkov, and D. S. Zrnic, 2001: An evaluation of radar rainfall estimates from specific differential phase. J. Atmos. Oceanic Technol., 18, 363–375.Doviak, R., V. N., Bringi, A. Ryzhkov, A. Zahrai and D. Zrnic, 2000: Consideration for polarimetric upgrades to WSR-88D radar. J. Atmos. Oceanic Technol. 17, 257-278.Doviak., R. J., and D. S. Zrinc, 1993: Doppler radar and weather observation. Academic Press, 562 pp.Fulton, R. A., J. P. Breidenbach, D. J. Seo, D. A. Miller, and T. OBannon, 1998: The WSR- 88D rainfall algorithm. Weather Forecasting, 13, 377–395.Gorgucci, E., V. Chandrasekar, V. N. Bringi, and G. Scarchilli, 2002: Estimation of raindrop size distribution parameters from polarimetric radar measurements. J. Atmos. Sci., 59, 2373–2384.Joss, J., and R. W. Lee, 1995: The application of radar–gauge comparisons to operational precipitation profile corrections. J. Appl. Meteorol., 34, 2612–2630.Kessinger, C., S. Ellis, J. Vanandel, and J. Yee, 2003: The AP clutter mitigation scheme for the WSR-88D. Preprints, 31st conference on radar meteorology, Seattle WA, Amer. Meteor. Soc, 526-529.Ryzhkov, A. V., and D. S. Zrnic, 1996: Assessment of rainfall measurement that uses specific differential phase. J. Appl. Meteor. 35, 2080–2090Schuur, T. A. Ryzhkov , P. Heinselman, D. S. Zrnic, D. Burgess and K. Scharfenberg, 2003: Observations and classification of echoes with polarimetric WSR-88D radar, Report of National Severe Storm Laboratory, Norman, OK. 46pp.Vivekanandan J., S. M. Ellis, R. Oye, D. S. Zrnic, A. V. Ryzhkov, and J. Straka, 1999: Cloud microphysics retrieval using S-band dual-polarization radar measurements. Bull. Amer. Meteor. Soc., 80, 381–388 23
AcknowledgmentsThe work described in this publication has been supported by the EuropeanCommission (Call FP7-ENV-2007-1 Grant nr. 212921) as part of the CEOP-AEGIS project (http://www.ceop-aegis.org) coordinated by the Universityof Strasbourg, France.


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Hey guys my name is Terry and I live in the beautiful foothills of western North Carolina. I started doing photography about 30 years ago. I went to our local community college to learn how to use a camera I had bought. Ever since then I have been doing photography. I like landscapes,flowers and old barnes and churches. Since I have retired I can go and photograph just about anytime I want to. I think I live in the greatest place on earth. We are not far from The Blueridge Parkway or the beach about five hours away. Keep posting those pictures and I will keep looking. I enjoy this site. Lots of fun. Keep shooting
WunderPhotos Upload
looking west
Uploaded by: terrya
Friday May 9, 2014
Pea Ridge in Polk County, NC (Current Weather Conditions)
Caption: looks like we may get a little rain in the bucket
Image Width: 5472
Image Length: 3648
Bits per Sample: 8, 8, 8
Photometric Interpretation: RGB
Manufacturer: Canon
Model: Canon EOS 6D
Orientation: top - left
Samples per Pixel: 3
x-Resolution: 72.00
y-Resolution: 72.00
Resolution Unit: Inch
Software: Adobe Photoshop Elements 12.0 Windows
YCbCr Positioning: co-sited
Compression: JPEG compression
Exposure Time: 1/100 sec.
FNumber: f/4.0
Exposure Program: Aperture priority
ISO Speed Ratings: 100
Exif Version: Unknown Exif Version
Components Configuration: Y Cb Cr -
Shutter speed: 6.62 EV (APEX: 9, 1/98 sec.)
Aperture: 4.00 EV (f/4.0)
Exposure Bias: 0.00 EV
MaxApertureValue: 4.00 EV (f/4.0)
Metering Mode: Pattern
Flash: Flash did not fire, compulsory flash mode.
Focal Length: 55.0 mm
User Comment:
SubsecTime: 00
SubSecTimeOriginal: 00
SubSecTimeDigitized: 00
FlashPixVersion: FlashPix Version 1.0
Color Space: sRGB
PixelXDimension: 5472
PixelYDimension: 3648
Focal Plane x-Resolution: 3810.58
Focal Plane y-Resolution: 3815.90
Focal Plane Resolution Unit: Inch
Custom Rendered: Normal process
Exposure Mode: Auto exposure
White Balance: Auto white balance
Scene Capture Type: Standard
GPS tag version: 0x02, 0x03, 0x00, 0x00
InteroperabilityIndex: R98
InteroperabilityVersion: 0100
May 9, 2014 Photo Series
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