Weather. Term Project Introduction to Weather and Climate Stage1 – Time-Series Plots Due: Monday, Mar. 19, 5:00 pm MST Stage 2 – Weather Diagnosis Due: Monday, Apr. 2, 5:00 pm MST PREFACE The term project constitutes 30% of your final course grade. Its successful completion is a mandatory prerequisite to passing the course. In other words: Passing the term project positions you to pass the course (earn a grade of D or higher), but failing it (combined score on Stage 1 and Stage 2 of <50%) guarantees that you do not pass course, regardless of your scores on quizzes and other assignments. There are two stages to the project. Each stage has its own separate due date and dropbox. The due date for Stage 1 is Monday, Mar. 19 by 5:00 pm MST. The due date for Stage 2 is Monday, Apr. 2 by 5:00 pm MST. The project is to be done as an individual, not as a member of a group. This means that you neither accept the aid of another nor give aid to another, outside of the bounds of the peer review. (See below.) This is your project. It must represent your work, and your work alone. LEARNING OUTCOMES 1) Accurate collection, organization and processing of current weather data. 2) Presentation of temporal data in graphical form. 3) Time-series analysis (e.g. variable correlation and identification of extremes/outliers). 4) Diagnosis of synergist weather phenomena in terms of course concepts. 5) Composition of a concise paper that addresses points 3) and 4) and follows the writing conventions of scientific publications. 6) Experience peer review. ANALYSIS OF SURFACE WEATHER OBSERVATIONS Stage I Over the next few weeks, you will access hourly weather observations for Dallas/Ft. Worth International Airport (KDFW: 32.9˚N/ 97.0˚W). You are to collect surface weather observations for an hour that is close to local solar noon. That hour for KDFW is 1800 UTC (Coordinated Universal Time)1, where UTC is standard time in London, United Kingdom. KDFW is located in the Central Time zone, which is UTC6 or six hours behind London time. 1800 UTC corresponds to 12:00 pm Central Standard Time (CST) or 1:00 pm Central Daylight Time2 (CDT), which is the GMT hour closest to solar noon at KDFW. The hourly observation is taken a few minutes before 1800 UTC. The typical time is 1753 UTC for KDFW, but you must check every time carefully as the observation time can vary by a few minutes each day. Do this for every even date for the period below. 1 UTC was formally termed Greenwich Mean Time (GMT). UTC is now commonly called Military Time or “Zulu” Time (or “Z” for short). “Z” often appears on weather products instead of “UTC”. 2 Daylight Time begins on the second Sunday in March and ends on the first Sunday in November 2 Daylight Time begins on the second Sunday in March and ends on the first Sunday in November in the United States. The states of Arizona (outside of the Navajo Nation) and Hawaii do not observe Daylight Time. 2 (Friday) Analysis period: Even dates from Feb. 2 to Mar. 16, inclusive. You must collect data for above period. I have done few dates to jumpstart your data collection. That leaves about 20 dates for you to record and plot. Your archive of surface weather observations for 1800 UTC must include: • Temperature︎ • Dew point • Relative humidity DATE TEMP DEW PT R.H. 2-Feb 47 17 30 4-Feb 59 44 58 6-Feb 44 33 65 8-Feb 52 32 46 10-Feb 33 28 81 12-Feb 36 26 67 Weather Data Access: Use the web site http://vortex.plymouth.edu/myo/sfc/statlog-a.html at Plymouth State University to get observations that are 24-36 hours or older. I show the web site below. The Plymouth State Weather archive has coded and decoded “METAR” (Meteorological Terminal Aviation Routine Weather Report) data, where METAR is the international code to report routine, hourly weather conditions at air terminals. You will select the “Type of Output” option that allows you to access data without learning the nuances of deciphering METAR code. Do the following to get the data that you need: Enter the station identifier (KDFW spring semester; KMSP fall semester) and select “Decoded Hourly & Special Obs Listing”. Set “Year”, “Month” and “Day” to their correct values, being extra careful that the time values are correct. When you click the "Click 3 Here to View Summary" button, it will produce a list of observations. I show in the figure that follows what the Plymouth State Weather site returns for Jan 11, 2018. You need to read the column TIME to find the time entry closest to local noon. I shade in blue observations for the time that is closest to 1800 UTC (1753). Record the temperature (T), dew point (TD) and relative humidity (RH). The other columns have sea-level pressure (SLP), wind direction (DIR) and speed (SPD), cloud cover (COV) for the time and date. (The link inside the red circle provides help on decoding text listings.) Moving from left to right, observations that you would need to record for 1753 UTC are: Temperature (T)=54˚F. Dew point (TD)=38˚F. Relative humidity (RH)=54% You do not need to collect observations in real-time. That said, I highly recommend that you do just that because you learn weather by following weather…every day. If you want observations for the current day, then go to http://vortex.plymouth.edu/myo/sfc/statlog.html. As before, enter the station identifier (KDFW) and select “Decoded Hourly & Special Obs Listing”, and the available observations up to the current hour are displayed in the same form as the above figure. A valuable learning experience is following weather maps in real-time as you gather data. Simultaneous data collection and monitoring of the maps enables you to associate trends and fluctuations in the time-series with surface weather features. To view or download animations of 3-days worth of prior surface maps, you can go to http://www.wpc.ncep.noaa.gov/html/sfcloop/namusloop_wbg_3day.html for analyses that have station plots and http://www.wpc.ncep.noaa.gov/html/sfcloop/radsfcus_exp_3day.html for maps that have radar imagery superimposed. Time Series Plots: You are to plot temperature, dew point and relative humidity on a graph for the even dates. Plot temperatures in degrees Fahrenheit on the left axis and relative humidity in percent on the 4 right axis. I encourage you to put all of the curves on the same plot. If you decide to put temperatures and RH on the same graph, you will need to use a different vertical axis scale for RH and to arrange the plot so the temperature curves and RH curves lines do not intersect. The end of this document shows Excel plots of daily time-series for KORD (Chicago IL) from the fall 2016 semester. Note how the dew point curve and RH bars only intersect on one date, and barely so at that. I urge that you use a spreadsheet program like Excel or online plotting tools such as Google Sheets (https://www.google.com/sheets/about/) or ChartGo (http://www.chartgo.com/en/chartline.jsp) to produce your graphs if you are comfortable using such software since the teaching team can offer no individualized help on the use of plotting software. For help with getting started on using plotting software, read the Appendix at the end of this document. Otherwise, scanned copies of accurate and neatly drawn plots on old-fashion graph paper are your only option. Whatever option you chose, you must provide data value on your graph at all of your data points. (See the Appendix.) The temperature/dew point/RH graph with data labels completes Step 1. Your graph must be submitted as a single pdf file. No other file type is acceptable. Upload your pdf to the dropbox before the deadline. Make certain your graph is properly oriented with its top at the top of the page. This may require that you rotate the pdf file, which is simple to do if you have Adobe Acrobat Reader (free from http://www.adobe.com) on your system. Plots that are not properly oriented will receive a deduction. Stage 2 Overview of the Weather and Climate for the Data Collection Period: Use the time series plots to determine whether there is a general upward or downward trend in data through the period. Write a brief (one but no more than 1½ pages double-spaced text) summary of the trends in the data. Did the temperature go down/up as we might expect during fall/spring season? Was there an apparent trend in the dew point or the relative humidity with time? How do the variables seem to correlate with each other? Comment on any interesting maxima and minima in the time series. Note periods of extended above or below average temperatures, and abrupt changes in the weather. Were there any record high or low temperatures? Were there any extreme weather events or extended periods of anomalous weather? Detailed Diagnosis of Significant Weather: I will identify for you (at a later date) a period of 2 or 3 consecutive days of “interesting weather” that will serve as the focus for your weather diagnosis. Broadly speaking, we can consider “interesting weather” to correspond to abrupt changes in surface conditions; record breaking events (always possible but not likely during our 50-day observation period); highly anomalous weather (extended heat wave or cold snap of a few days); strong winds (sustained winds faster than 20-25 mph or gusts faster than 35-40 mph); severe thunderstorms with hail or heavy rain (and especially tornadoes); flooding events; snow; etc. You will use course materials and other online weather resources to answer no more than three specific questions that I pose about the weather situation. The diagnosis portion of the project should not exceed 1½ to 2 pages. Specific instructions on the diagnosis component of Stage 2 will come when I announce the focus period and associated questions. All components of Stage 2 must be assembled into a single pdf file. Your complete project (Stage 2) must include each item in the following order: 1) Written analysis of time series. 2) Diagnosis of the weather over the 2- to 3-day focus period in terms of course concepts. 3) All images (e.g. weather maps, satellite, radar images, etc.) that support your diagnosis of the focus period. Make certain these plots are properly rotated. 4) References. Do not include a copy of the graph that you submitted in Stage 1. 5 Peer Review: Before you submit your project for grading, you will exchange your work to date for peer review. Your peers will read through your work to date and make corrections to spelling and grammar, and make comments and suggestions on how to improve your term project. This process is known as "peer review", and it constitutes an essential component of all scientific research. Specific instructions about the peer review will be given in a separate document, shortly before the due date. It is only after you thoughtfully consider and incorporate comments, suggestions and corrections of the peer reviews into your manuscript that you submit a version of the project for grading. GRADING RUBRIC Your grade will be based the following criteria. Point 3 is the most important to address and counts 40% of the Stage 2 grade. The other three points count 20% each. (1) Demonstration of a timely, complete and accurate collection of data as judged from your time-series plots. The evaluation of Stage 1 is independent of Stage 2. (2) Succinct overview of the weather and climate for the observation period. (3) Sound, succinct diagnosis of the weather during the focus period that is based on course concepts. This is the most important component of the project. Submissions that do not address the issue of the underlying physical reasons of “why the weather did what it did” will be subject to a major deduction as large as 25 points. (4) Organization, clarity, grammar, punctuation and overall sense of professionalism. For writing guidance, I recommend http://atmo.arizona.edu/~mullen/atmo170A1/project/Grammar_Girl.pdf or https://owl.english.purdue.edu/owl/section/1/, but there are dozens of other excellent online sites. Once I identify the focus period, you are to write a succinct summary of your conclusions. Your weather synopsis must: - Contain an overview of the time series plots. Note periods of above or below normal temperatures, precipitation events, strong winds, and of course any record events for the date. - Give a detailed description of the weather during the focus period that incorporates relevant weather maps, satellite and/or radar imagery, and supplemental surface data beyond the 1800 UTC surface data in your time-series plots. This will satisfy a portion of point (3). - Use course concepts to diagnose the weather during the interesting period. This will satisfy the bulk of point (3) - Contain high-quality writing that is coherent, succinct, organized and grammatically proper. You may include up to 4 supplementary figures to support your diagnosis of the weather during the focus period. Be certain that each figure has a caption (a tight description of the figure) and is assigned a figure number, where the number is determined by the order in which the figure is first referenced in the text. Pick your figures wisely; the teaching team will view unfavorably an excessive number of figures, ones of marginal value or ones not referenced in the text. Your write-up is to be no longer than three double-spaced pages of text using #12-point, Times New Roman font. The limit excludes references, tables, figures and figure captions. Three pages is very little space (about 1/3 of the words in this document) to write a summary of the time-series and present a detailed diagnosis of a weather event. But it is enough. Hence, it is critical that you make every word count. I suggest that you target one page but no more than 1.5 pages for the time-series analysis, and at least 1.5 pages but no more two for the weather diagnosis. I have posted in the D2L Content section the file “Example Term Project” from a prior class (when the project differed somewhat from yours). It is not a file for you to cut-and-paste portions thereof into your document, even if the specifics differ. I offer it as an example of “what” that I am confident you are capable of doing. Do take note how succinct the presentation is. I was able to satisfy the key criteria of the assignment in only two pages. 6 DUE DATES The due date for Stage 1 (completed graph only) is Monday, Mar. 19 by 5:00 pm MST. In view of the purpose of Stage 1, namely “a timely, complete and accurate collection of data as judged from your time-series plots”, late submissions of the graphs will not be accepted, regardless of circumstances. The due date for Stage 2 (complete project) is Monday, Apr. 2 by 5:00 pm MST. All components of Stage 2 must be assembled into a single pdf file. Your complete project (Stage 2) must include item in the following order: 1) Analysis of the time series, after you incorporate peer reviewers’ comments. 2) Diagnosis of the weather evolution over the 2- to 3-day focus period in terms of course concepts. 3) All images (e.g. weather maps, satellite, radar images, etc.) that support your diagnosis of the focus period. Make certain these plots are properly rotated. 4) References Do not include a copy of the graph that you submitted earlier. I will post a correct version of the timeseries graphs immediately after the due date for Stage 1 passes. Assignments can only be submitted to the appropriate D2L dropboxes. This means that you must either “scan” or take a digital picture of any hand drawn plots to put them into a format (.jpeg, .png) that can be imported into your word processing program. You should plan to complete your project at least two days prior to the due date to give yourself ample of time to make certain your materials are complete, proofed, properly assembled and can be uploaded to the D2L dropbox. Late Stage 2 submissions will accumulate a subtractive penalty of -10% per calendar day late. For example, if your project is 3 days, 30% is subtracted from your score. That means if your project is 5 days late, an “E” mark will be assigned to your project and course grade too. Extensions of the due date will not be granted under any circumstances beyond extenuating ones specified in the syllabus. I recommend that you finish Stage 2 long before the deadline. Besides, think how nice it would be to finish the project early so it does not conflict with end-of-semester requirements in other courses. WHEN TO EXPECT TO GET YOUR GRADE You should not expect to see your total score on the term project any earlier than the last week that classes meet. Please keep in mind that it takes time to assess hundreds of submissions. It takes a grader tens of hours to evaluate their share of the submissions, and their grading for our class must be worked around their graduate courses, research obligations and grading for other sections of ATMO 170A1. The teaching team is committed to complete the grading of project by “Dead Day”, which is sufficient time to decide whether you want to take the final or not. I close with one last request: please do not send emails of the ilk, “Where is the grade on my term project?” before I announce all of the projects are graded and scores are posted. Such emails will not be acknowledged since it would only serve to slow down the grading process. 7 Time series of surface weather elements for KORD (Chicago IL), valid at 2000 UTC, for Oct 2016. Temperature (red line) and dew point (blue line) in degrees Fahrenheit (left axis); relative humity (green bars) in percent (right axis). Relative humidity (green bars) in percent (right axis). 8 APPENDIX: HELP WITH PLOTTING You should use a spreadsheet program like Excel or an online plotting tool like Google Sheets to produce your plots. I give a link to a PowerPoint file where you just enter the temperature, dew point and relative humidity data. Click http://www.atmo.arizona.edu/~mullen/atmo170A1/project/Graph_DFW_Students.xlsx. If you have PowerPoint on your computer, the file might open automatically. If not, the file should download automatically to your computer where you can open it. Once the file is on your computer, PowerPoint can open it. The left axis has temperature and dew point, and the right axis has relative humidity. Also make note of the “Data Labels” just able the dots/bars that give the data values. (For illustrative purposes, I filled the data columns with fake data that you must change.) Pages (Apple) and LibreOffice (open source) should open the file too, as can Google Sheets (see next paragraph). I also provide a link to a Google Sheets program at the end of the paragraph that you can use as a template to make your graphs. Where you enter the data for a particular date is self-evident. Although you can enter the link into any mainstream browser, I recommend using Chrome (the native browser for Google) to minimize the likelihood of computing gremlins. (Aside: I do not own shares of GOOG.) https://docs.google.com/spreadsheets/d/1VTTZJjAUEdY64kKSYZhazOU48Lp2uC_GEU8es93u4gw/edit?usp=sharing Unfortunately, a shared link in Google Sheets cannot be edited by or downloaded to another Google account. You can, however, upload the Excel file of the first paragraph to Google Drive then edit it with Google Sheets. What initially opens in Google Sheets is a much too busy, three-line chart where the RH line crosses the temperature lines, but Google Sheets can be modified to look very similar to the combination lines/bar chart in Excel by putting RH on the right vertical axis and scaling it accordingly. Also note the data labels that appear above the dots. Google Sheets produced the graph on the next page. 9 A third option is to use an online plotting tool such as ChartGo. Cut and paste the following link into your browser: https://www.chartgo.com/share.do?id=98574fbbaa. (Apologies up front if clicking the link does not open for reasons I do not understand. Copying the link into your browser seems to work fine though.) When the page opens, you need to scroll down to Create your own chart and click the option. It is inside Create your own chart that you enter your values of temperature and add another column for dew point. I cannot figure out a way to produce a combination chart with relative humidity plotted as bars on the right vertical axis. 10 https://www.chartgo.com/get.do?id=98574fbb90 Below I show the settings that the produced the above chart at Chartgo. You might have to change the “Max Y” value depending on how high the warmest temperatures get, and you definitely need to change “Max Y” to 100 if you add a third line for relative humidity. Important: Whether you use plotting software (as I strongly urge) or draw graphs by hand, you must include labeling of every data point. Switching the Data Labels option to “On” enables the teaching team to assess the fidelity of your data accurately. In fact, the display of data values is so greatly faciliated by using plotting software that one benefit per se is a compelling enough reason to NOT draw graphs and labels by hand.

    Diagnosis and Overview of Region

    From 8th February to 4th Hesitate 2016, the KDFW daily deportment region observations were commemorative, and it was conclusive at 2200 UTC. The Cipher (1) deportment rank design was used to batch the recital efficiently. Additionally, Cipher (2a and 2b) basis was used to batch the graph using the age succession. Primarily, the age succession and the rank design are utilized to show the KDFW daily weather which was over the plummet balance values that had been regular 30 years past. This was among the month among 8th February and 4th Hesitate 2016 where towards the object of the month of February, the fruits were remarkable of the six-day purpose.

    On 10th February, the month launched impromptu with collected weathers which were remarkable, and they were on mean 73 degrees. With age the weather remained perpetual saving inhabitants from the complete collected splinter. Later, on 22nd February the weathers keep begun to refuse to 61 degrees. On 23nd February the weather degrees dropped exalt to 44°F. The weather was finally eminent than the MIN mean of the month with simply 5 °F precedently the weather abruptly rose to 60 °F at the object of the month. As observed, in the fostering three days precedently the object of the month of February the weather was under the MAX mean. Consequently, an anomalously eager purpose was then familiar with the 10 °F weather nature eminent in a couple purpose of sequable days.

    Notably, in 21st and 23rds Feb, the three days hold remarkable ascribable to the drown daily changes. It was recitaled that on the 22nd Feb the weather dropped from 61 °F to 44 °F on 27th Feb and finally on 24th Feb it abruptly eagered up to 60 °F. On 23rd Feb the wriggle was a part sustainable to 20 knots from the NW. However, noble wriggles were nature familiar in diverse days, and this was referable accruing to be remarkable past throughout the month there was wriggle.  Again, on 23rd Feb the SLP refused to 1006.2mb from 4mb which among that month it which was the last. In 24th Hesitate, it then rose to 13mb .in the anterior brace days on 21st and 23rd February the KDFW accepted subsidence where it accepted .1 and .3 respectively. Suggestively, the 3-day purpose should critically be examined to display its reason.

    In 22nd Feb 2016, the 1705 UTC composite deportment -satellite radar map was demonstrated in cipher 3. From the map, a glance collected face is seen moving North Wards over the Southern of the United States. In cipherure 4, it is picturesque how the face becomes the rankary with KDFW at 1705 UTC experiencing a cyclone. Accordingly, the low-pressure collected faces propel from Gulf Mexico towards the North Wards. This is in cabal with the weather that is under mean which is an indicator of El Nino. The month of January to hesitate is adventitious from nature the centre equableing months in which the El Nino struck the southern United States.

    Conclusion

    Conclusively, it self-evident that the month of February its where diverse weather changes occurred equable though the degrees were flatulating. Also, the changes of wriggle occurred in the selfselfsame month. Remarkedly, changes in weather fruit to the irrelative weather either violent, collected or eager. For issue, when the weather is under the climax mean, it may fruit to eager weather in the area.

    Works Cited

    Dallas, Texas Travel Region Means (Weatherbase). (n.d.). Retrieved from http://www.weatherbase.com/weather/weather.php3?s=95227&cityname=Dallas-Texas-United-States-of-America

    Index of /archive/sfc_map/1602. (n.d.). Retrieved from http://weather.unisys.com/archive/sfc_map/1602/

    Retrieved from https://weather.com/storms/winter/news/january-march-outlook-2016-noaa-wsi

    .

    Aspect 1

    Aspect 2

    Aspect 3

    Aspect 4