My town of choice was Lisbon, Portugal. The longitude is -9.139337 and the latitude is 38.722252. It is the capital and the largest city in Portugal, with a population of 552,700. It is the 11th most populous urban area in the European Union. It is continental Europe's westernmost capital city and the only one along the Atlantic coast. It is one of the oldest cities in the world, and is recognized as a global city because of its importance in finance, commerce, media, entertainment, arts, international trade, education and tourism. I chose Lisbon because I traveled there one year ago, and I fell in love with the rich history and vibrant atmosphere of the city. I visited in August, and the weather was nearly perfect for the week that I was there. I loved it so much that I would like to live there someday. Knowing the temperature trends would only give me more knowledge about what it will be like to live in this dream of a city.
Satellites use passive microwave radiometry to measure temperatures. The measurements are derived from emissions that appear when a particular set of constraints are applied, using something called selective absorption. The advantage of satellite datasets is that the coverage is global which provides a layer (mass) weighted average. Ground station temperatures are unable to evaluate the polar regions, vast areas of ocean, and regions that are inaccessible by foot. However, satellites are not perfect and they come with their own disadvantages. For example, it is sensing from a remote place rather than being in the actual site. The presence of clouds and rain also affect the amount of energy that is emitted to the sensor. Any alterations in orbits, instrument integrity, or erroneous conversion of data to temperature can all lead to mis-readings as well. When comparing the two graphs about Lisbon, there was a clear climate change trend which showed the temperature has been rising as more years pass by. When comparing the running temperatures with the average temperatures, we see that the running temperatures show a drawn-out pattern that is more detailed and meticulous in the charts that show the temperatures from the year 1980 to 2005. While the maximum temperatures in a 5-year running period for July were rising steadily, the minimum temperatures in February were actually fluctuating within just the 5-year running period. The average winter temperature is 5 degrees Celsius, while the average summer temperature is 27 degrees Celsius.
When comparing the 5-year running averages of temperature to the average temperature graphs, we see that the average minimum temperature in February from 1980 to 2005 show a pattern of moving up and down every decade or so, which is mirrored the 5-year running period. On the other side of the coin, when comparing the same charts regarding the average maximum temperature in July from 1980 to 2005, we see that this shows much more consistency and is again reflected in the 5-year running period. Running averages are useful because they give a good guideline for measuring particular patterns in shorter time spans, to see if there were any dramatic changes that stand out when compared to the running averages. When examining 5-year running averages, we see that most often they mirror in a simpler format the same information that is shown in the data sets that are more longer spread.
The differences between the different sized running averages (5 year, 11 year, and 21 year) are that they allow us to see whether there is a continuing pattern that remains all throughout the decades, or if there was one particular time period that experienced either dramatic decreases or dramatic increases in temperature. Being able to pinpoint exactly where these fluctuations took place helps to give us information about that time period and why there were discrepancies in just that segment of time. The advantage of using a smaller sized average is that we get a very clear indication of the pattern that was occurring within a small time period. The disadvantage, however, is that it can be very limited in evaluating a more general perspective on environmental occurrences during that time.
When comparing my charts with a student whose city was in Goa, India, we saw strikingly different measurements. This was due to the extreme differences in climate and location on the globe. While their maximum summer temperature averages were well over 30 degrees Celsius, the maximum summer temperature average for Lisbon was more than 5 degrees Celsisus lower. Their minimum winter temperatures of 25 degrees Celsius was actually closer to the average maximum summer temperature in Lisbon.
Through this exercise, I learned that there is much more to reading temperature than just looking at measurements made from the ground. I saw that there are distinct patterns that arise when you examine a long stretch of data regarding temperatures in both the summer and in the winter. I saw that in order to get an accurate read on a place's climate and average temperatures, you must examine not only ground station temperatures but also satellite-gathered information in order to see where both bodies of information overlap. The overlap is where you will find the most accurate data regarding the patterns that take place in a certain city. When examining climate change in the future, I will keep in mind that measurements made by only one kind of data will not be sufficient to get the most accurate read.
Average Minimum Temperatures in Lisbon
Average Maximum Temperatures in Lisbon
February Minimum Average Temperatures
February Minimum 5-Year Running Temperature
July Maximum Average Temperature
July Maximum 5-Year Running Temperature
URLs
http://www.latlong.net/
https://eosweb.larc.nasa.gov/cgi-bin/sse/interann.cgi
https://data.giss.nasa.gov/gistemp/station_data/
