From edalgo at uw.edu Thu Nov 2 11:00:23 2023 From: edalgo at uw.edu (Emily Dalgo) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] NOAA Weather Data Help Message-ID: Good morning all, I am working on a MA thesis related to the association between weather patterns and mortality. Ideally, I would like to have daily high temperatures for all zip codes in the state of Washington for all days between 2016 and 2021 (years for which I have mortality data). I have been doing data entry by hand using the search tool at https://www.ncdc.noaa.gov/cdo-web/search . The tool does not give weather data for zip codes containing no weather station, so I have been manually hand coding the nearest weather station using the the tools at https://www.ncei.noaa.gov/maps/daily-summaries/ I spoke to people at NOAA who said the data I need might be in the files at https://www.ncei.noaa.gov/data/daily-summaries/access/ but I have had no luck accessing the files because of their massive size. Do you have any tips for working with the NOAA metadata? If not, do you know of a different easily-accessible source of data on high temperatures by day (or even by weather station that can be linked to zip codes)? Thanks in advance for any ideas about this. Emily Dalgo -- *Emily Dalgo* Graduate Student, Department of Sociology University of Washington edalgo@uw.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From lwrogers at uw.edu Thu Nov 2 11:04:33 2023 From: lwrogers at uw.edu (Luke Rogers) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] NOAA Weather Data Help In-Reply-To: References: Message-ID: You might try Climate NA or Prism. https://climatena.ca/ http://www.prism.washington.edu/home -Luke From: Uw-gis-l On Behalf Of Emily Dalgo Sent: Thursday, November 2, 2023 11:00 AM To: uw-gis-l@u.washington.edu Subject: [UW-GIS-L] NOAA Weather Data Help Good morning all, I am working on a MA thesis related to the association between weather patterns and mortality. Ideally, I would like to have daily high temperatures for all zip codes in the state of Washington for all days between 2016 and 2021 (years for which I have mortality data). I have been doing data entry by hand using the search tool at https://www.ncdc.noaa.gov/cdo-web/search. The tool does not give weather data for zip codes containing no weather station, so I have been manually hand coding the nearest weather station using the the tools at https://www.ncei.noaa.gov/maps/daily-summaries/ I spoke to people at NOAA who said the data I need might be in the files at https://www.ncei.noaa.gov/data/daily-summaries/access/ but I have had no luck accessing the files because of their massive size. Do you have any tips for working with the NOAA metadata? If not, do you know of a different easily-accessible source of data on high temperatures by day (or even by weather station that can be linked to zip codes)? Thanks in advance for any ideas about this. Emily Dalgo -- Emily Dalgo Graduate Student, Department of Sociology University of Washington edalgo@uw.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From lwrogers at uw.edu Thu Nov 2 12:17:20 2023 From: lwrogers at uw.edu (Luke Rogers) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] NOAA Weather Data Help In-Reply-To: References: Message-ID: Thank you to Steven Walters for pointing out that this is the wrong PRISM! Here is the correct one: https://www.prism.oregonstate.edu/ -Luke From: Uw-gis-l On Behalf Of Luke Rogers Sent: Thursday, November 2, 2023 11:05 AM To: Emily Dalgo ; uw-gis-l@u.washington.edu Subject: Re: [UW-GIS-L] NOAA Weather Data Help You might try Climate NA or Prism. https://climatena.ca/ http://www.prism.washington.edu/home -Luke From: Uw-gis-l > On Behalf Of Emily Dalgo Sent: Thursday, November 2, 2023 11:00 AM To: uw-gis-l@u.washington.edu Subject: [UW-GIS-L] NOAA Weather Data Help Good morning all, I am working on a MA thesis related to the association between weather patterns and mortality. Ideally, I would like to have daily high temperatures for all zip codes in the state of Washington for all days between 2016 and 2021 (years for which I have mortality data). I have been doing data entry by hand using the search tool at https://www.ncdc.noaa.gov/cdo-web/search. The tool does not give weather data for zip codes containing no weather station, so I have been manually hand coding the nearest weather station using the the tools at https://www.ncei.noaa.gov/maps/daily-summaries/ I spoke to people at NOAA who said the data I need might be in the files at https://www.ncei.noaa.gov/data/daily-summaries/access/ but I have had no luck accessing the files because of their massive size. Do you have any tips for working with the NOAA metadata? If not, do you know of a different easily-accessible source of data on high temperatures by day (or even by weather station that can be linked to zip codes)? Thanks in advance for any ideas about this. Emily Dalgo -- Emily Dalgo Graduate Student, Department of Sociology University of Washington edalgo@uw.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From phil at philhurvitz.com Sun Nov 5 12:47:39 2023 From: phil at philhurvitz.com (phil philhurvitz.com) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] NOAA Weather Data Help In-Reply-To: References: Message-ID: Emily, You could use a R framework for doing a mostly automated method of handling the data that the NOAA people told you about. Documentation here: https://www1.ncdc.noaa.gov/pub/data/ghcn/daily/readme.txt indicates there is a list of stations, https://www.ncei.noaa.gov/data/daily-summaries/doc/ghcnd-stations.txt. The first one listed for Seattle is US1WAKG0006. It would be possible to parse that file and turn the lat/long values into points and then select the ones within WA. Then using that list of records, download the daily files for each station, then extract data from each file. You would still need to deal with linking these points with ZIP codes, which is not really a straightforward process for various reasons it is probably not worth going into at this time. However, I think the NOAA folks may have steered you wrong ? unless there is a different set of files that are known to have temperature values. Here is a worked up example in R library(curl) library(R.utils) library(tools) # temp dir setwd(Sys.getenv("TEMP")) f <- function(url){ # get the file name from the URL myGzFname <- basename(url) # strip the GZ myFname <- file_path_sans_ext(myGzFname) # dowload and gunzip if necessary if(!file.exists(myFname)){ # get a file curl_download(url = myUrl, destfile = myGzFname) # gunzip it gunzip(myGzFname) } # read it in x <- read.csv(myFname, header = FALSE) # look at it a bit message("first lines") print(head(x)) # what is in V3? message("what is in V3?") print(table(x$V3)) } The function downloads, unzips, and loads a file, then prints the first few lines and also prints a count of the climate variable records by measurement type. Run on a few files: > f(ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/by_station/US1WAKG0006.csv.gz) first lines V1 V2 V3 V4 V5 V6 V7 V8 1 US1WAKG0006 20080605 PRCP 3 NA N 700 2 US1WAKG0006 20080606 PRCP 38 NA N 700 3 US1WAKG0006 20080607 PRCP 20 NA N 530 4 US1WAKG0006 20080608 PRCP 0 TRUE N 700 5 US1WAKG0006 20080609 PRCP 0 NA N 650 6 US1WAKG0006 20080610 PRCP 33 NA N 700 what is in V3? DAPR MDPR PRCP SNOW SNWD WESD WESF 7 7 283 274 87 93 75 There is no ?TMAX? here, so maximum daily temperature seems to be missing. Same for this: > f(ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/by_station/US1WAKG0020.csv.gz) first lines V1 V2 V3 V4 V5 V6 V7 V8 1 US1WAKG0020 20080619 PRCP 3 NA N 700 2 US1WAKG0020 20080620 PRCP 0 NA N 805 3 US1WAKG0020 20080622 PRCP 0 NA N 810 4 US1WAKG0020 20080623 PRCP 0 NA N 705 5 US1WAKG0020 20080624 PRCP 0 NA N 654 6 US1WAKG0020 20080625 PRCP 0 NA N 700 what is in V3? DAPR MDPR PRCP SNOW 58 58 391 250 So, unless there is some way of knowing which files contain max temperature values, this approach, while workable, doesn?t look like it will give you the data you are interested in. ________________________________ Phil Hurvitz phil@philhurvitz.com ________________________________ From: Uw-gis-l On Behalf Of Luke Rogers Sent: Thursday, November 2, 2023 12:17 To: uw-gis-l@u.washington.edu Subject: Re: [UW-GIS-L] NOAA Weather Data Help Thank you to Steven Walters for pointing out that this is the wrong PRISM! Here is the correct one: https://www.prism.oregonstate.edu/ -Luke From: Uw-gis-l > On Behalf Of Luke Rogers Sent: Thursday, November 2, 2023 11:05 AM To: Emily Dalgo >; uw-gis-l@u.washington.edu Subject: Re: [UW-GIS-L] NOAA Weather Data Help You might try Climate NA or Prism. https://climatena.ca/ http://www.prism.washington.edu/home -Luke From: Uw-gis-l > On Behalf Of Emily Dalgo Sent: Thursday, November 2, 2023 11:00 AM To: uw-gis-l@u.washington.edu Subject: [UW-GIS-L] NOAA Weather Data Help Good morning all, I am working on a MA thesis related to the association between weather patterns and mortality. Ideally, I would like to have daily high temperatures for all zip codes in the state of Washington for all days between 2016 and 2021 (years for which I have mortality data). I have been doing data entry by hand using the search tool at https://www.ncdc.noaa.gov/cdo-web/search. The tool does not give weather data for zip codes containing no weather station, so I have been manually hand coding the nearest weather station using the the tools at https://www.ncei.noaa.gov/maps/daily-summaries/ I spoke to people at NOAA who said the data I need might be in the files at https://www.ncei.noaa.gov/data/daily-summaries/access/ but I have had no luck accessing the files because of their massive size. Do you have any tips for working with the NOAA metadata? If not, do you know of a different easily-accessible source of data on high temperatures by day (or even by weather station that can be linked to zip codes)? Thanks in advance for any ideas about this. Emily Dalgo -- Emily Dalgo Graduate Student, Department of Sociology University of Washington edalgo@uw.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From zhaobo at uw.edu Thu Nov 16 14:46:06 2023 From: zhaobo at uw.edu (Bo Zhao) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] Announcement: Winners of the GeoAI Prompt Contest Message-ID: Hello everyone, We are thrilled to announce the results of our recent GeoAI prompt contest, a remarkable event that witnessed wide participation from the University of Washington community. This year, we received a total of 56 submissions, featuring an array of artworks from undergraduate students, graduate students, staff, and faculty members. *By harnessing generative Artificial Intelligence, the contest fosters deep reflection and artistic expression concerning pressing issues such as climate change, food security, social and economic inequality, globalization, and more. * Organizing and judging an AI art contest presents unique challenges, given the complexity and depth of each piece. The artworks submitted were not only visually stunning but also carried profound meanings, making the selection process incredibly difficult. Our panel of judges, composed of undergraduate students, graduate students, staff, and faculty with expertise in Geography, GIS and AI, meticulously evaluated each submission. They based their decisions on a range of criteria, including Originality, Relevance to Theme, Artistic Expression, Technical Proficiency, and Emotional Impact & Message Conveyance. It?s important to acknowledge that art is subjective, and each judge brought their own preferences and biases to the table. However, after careful consideration and spirited discussion, we have identified the top three winners and 20 honorable mentions *1st Place - Buy Now, Get Newer - Tomorrow. Worry-Free Returns.*[image: 1.jpeg] By *Michael Lieue* using Bing Image Creator. *Prompt: *In hyperrealism style, heap of Factories labeled ?fast fashion inc.? and ?new stuff,? churning mountains of consumable which delivered by huge airplane, rockets, ships, trains, and lined trucks congesting highway to landfill. All buildings and vehicles produce smoke. Tents next to landfill. Digital billboards and trucks show ?don?t fix.? ?New now!? and, ?One day deliver!? ?Own today!? ?Trending!? orange smog and seawater. *Description: *Humanity?s supply chain struggles keeping pace with the latest iteration of the globalized e-commerce economy. Digitized advertisements further our insatiable demand for latest products and doorstep delivery convenience - in turn flooding our skies, oceans, and landscape with energy-intensive logistics traffic - while simultaneously accelerating the rate at which formerly-trendy products are disposed. The carbon-intensive factories and retailers produce economic growth which is irresistible to society as a means of increasing wealth and representation?which is in reality, distributed with inequality. While wealth allows the corporate to ?find higher ground? away from the rising and polluted waters with international mobility of titanic proportions, the majority of individuals across all species must settle in the wash zone created by climate change. The relatively few tents in scene illustrate the growing phenomenon of corporate land-grab for real estate purposes, and full time employees being paid less than a living wage. The conveyed informational power of an image is beyond words, and in this case, I hope to give the reader a detailed view of the actual consequences of using one-day delivery to keep up with online trends while fully understanding the challenge it takes for and individual to complete the challenge of leading by example of resisting the trend and allures of buying newness. *Judges? Comments: *this artwork is a compelling and impactful visualization of the current issues of overconsumption and the environmental impacts of our global supply chain. The intricate details and the overwhelming representation of the supply chain, from factories to landfills, brilliantly illustrate the unsustainable pace of our consumerist lifestyle. The dark humor embedded in the title and the imagery, as well as the choice to overcrowd the scene, powerfully conveys the pressing nature of these issues. *2nd Place - Modern Loneliness*[image: 2.jpeg] By *Logan Hosoda* using Bing Image Creator. *Prompt:* never ending relapsing addiction to technology, photorealism *Description: *I wanted to create an image that depicts how technology, while innovative has also led to social isolation, digital addiction, and sedentary behaviors. As someone who experienced an increase in technology reliance throughout the introduction to cellular devices and global pandemic, I thought it was important to convey that technological addiction often detracts from everyday routines. I hope that when others view the image they stop and reflect on their own usage of technology, serving as a reminder to look at life beyond the screen. *Judges? Comments:*This entry compellingly captures the paradox of our digital era. Its photorealistic portrayal of technology addiction and social isolation resonates deeply, reflecting a universal challenge of the modern world. This artwork, with its evocative and visually striking composition, effectively invites viewers to contemplate the impact of digital life on our daily existence. *3rd Place - A Detached Glimpse* [image: 3.jpeg] By *Paula Zhong *using Bing Image Creator. *Prompt: *tiny cartoon human trapped in glass box with bright screen glaring into glass box, box in vast room full of looming news headlines and stacks of newspapers and walls of text, disconcerting *Description:* Viewing the world solely through the words and perspectives of other people is limiting if there is no balance with our own thought. When there are heavy events happening around the world, I feel there can be a lack of empathy and humanity in our responses to them. A disconnect. Headlines and breaking news stories blare at us and regarding events from afar makes it easy to be detached and apathetic. *Judges? Comments:* We are impressed by this artwork for its powerful visual narrative and its relevance to the theme of information overload in our digital age. This piece brilliantly encapsulates the paradox of our times: being bombarded with information while feeling increasingly detached. It serves as a poignant reminder of the need for empathy in our responses to global events, making it a deserving recipient of third place in the contest. You can visit either the UW Geography Department page or this github page to view the artworks from the 20 honorable mentions. *Acknowledgements: *We extend our heartfelt gratitude to the many individuals and organizations that made this event possible. Firstly, we would like to acknowledge the invaluable support from the University of Washington Department of Geography, UW eScience Institute, and Urban@UW. Their contributions were pivotal in bringing this contest to fruition. A special thank you to GeoDat and the geography department for their collaborative efforts in organizing this event. Their dedication and hard work were key to its success. We are immensely grateful to geography staff members Nell Gross, Emily Uematsu, Lindsay Cael, Lisa Sturdivant and Parwati Martin for their exceptional coordination and organizational skills. Their commitment and attention to detail were instrumental in ensuring a smooth and successful contest. Our thanks also go to Jayden Fenske, Akshay K. Mehra, Emma Esteban, Liz Peng, Gunwha Oh, Michael Brown, Sarah Elwood, Sarah A. Stone, Jen Davison, Chloe Abrahams, and Andres S. Rovalo. Each of you has played a crucial role, and your contributions have been vital to the success of this event. -- Bo Zhao (he/him) Associate Professor in Geography University of Washington - Seattle Smith Hall 412e, Box 353550 (206) 685-3846 | hgis.uw.edu Request an appointment *The University of Washington acknowledges the Coast **Salish people of this land, the land which touches the **shared waters of all tribes and bands within the Suqua**mish, Tulalip, and Muckleshoot nations.* -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 1.jpeg Type: image/jpeg Size: 335105 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 2.jpeg Type: image/jpeg Size: 202463 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 3.jpeg Type: image/jpeg Size: 175911 bytes Desc: not available URL: From ashep at uw.edu Mon Nov 27 13:09:53 2023 From: ashep at uw.edu (A. Shepherd) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] ArcGIS license server reboots today 2pm and 230pm Message-ID: I will be rebooting lib-licensing at 2pm and lib-licensing2 at 230pm today. If you have all license servers configured, you will not see an impact for these downtimes. Shepherd -- A. Shepherd UW Libraries Information Technology Services & Digital Strategies ashep@uw.edu BLACK LIVES MATTER -------------- next part -------------- An HTML attachment was scrubbed... URL: From dpham at uw.edu Tue Nov 28 14:18:31 2023 From: dpham at uw.edu (David T. Pham) Date: Sun Mar 24 20:49:15 2024 Subject: [UW-GIS-L] lib-licensing will be reboot at 2:30PM Nov 28th, 2023 (EOM) Message-ID: -------------- next part -------------- An HTML attachment was scrubbed... URL: