Lab 5_ Field Trip and Data Analysis for Oakland Upper Air Radiosonde Launches

pdf

School

University of California, Berkeley *

*We aren’t endorsed by this school

Course

Subject

Chemistry

Date

Feb 20, 2024

Type

pdf

Pages

Uploaded by AdmiralGazelle4036

Salvatore Vallejo April 18, 2023 EPS/CHEM 182 Lab 5: Field Trip and Data Analysis for Oakland Upper Air Radiosonde Launches Part 1: Field Trip Write-up [For Spring 2023: Part 1 is eliminated.] Part 2: Predicting where a radiosonde may land Radiosondes use various computer systems and data analytics to measure atmospheric properties such as humidity, pressure, temperature, wind speed , and direction at various conditions. Radiosondes are attached to weather balloons that are launched into the atmosphere to collect data about the atmospheric conditions. Radiosondes consists of three components: a sensor package, a radio transmitter, and a power source. The sensor package has built in sensors to measure atmospheric variables, and the radio transmitter sends the collected data back to a ground station. The power source is a source of power and it provides energy to run the sensors and the transmitter. Radiosondes are launched twice daily, covering many different terrains. Data from radiosondes creates a vertical profile of the atmosphere which is important for weather forecasting and climate research. We used stratoflights trajectory over Oakland International Airport to conduct radiosonde data analysis. Parameters: launch site = Oakland International Airport, Flight Info: Helium, parachute = TA200, Totex parachute = 0.94 m; payload weight (0.4 kg =235 g of radiosonde plus associated line, train regulator, and parachute); nozzle life = 1.5 kg, default settings.

Figure 1 . Trajectory simulation at Oakland Airport. Prediction made on April 4, 2023 for a launch at 4:00 PM PDT on April 6, 2023 estimated that the launch altitude occurred at 100 m and ascended and descended at a right of 5 m/s in a south east direction landing near Newman county in San Francisco. Flight duration lasted 2 hours and 47 minutes for a 118 km distance traveled. Part 3: Radiosonde Data Analysis We conducted two trajectory launches on 2023-03-16-00Z (4 pm PDT launch 3/15/23 California time) and 2023-04-06-00Z (4 pm PDT launch 4/05/23 California time). Figure 2 shows that the temperature profiles from each launch are similar. On March 16, 2023, the ground temperature was 14 ºC at the time of launch, and the weather conditions were sunny with clear skies and a wind speed of S 10 mph. On April 6, 2023, the ground temperature was 12.8 ºC at the time of launch, and weather conditions were cloudy and a wind speed of S 11 mph. Although the temperature profiles are similar, there is a difference in relative humidity profiles because the weather conditions were different. April 6, 2023 has a greater disparity in relative humidity than March 16, 2023. Figure 2. Temperature Comparison for March 16, 2023 and April 6, 2023. Overall trends show similar temperature values across both dates. 3.1 Variation of Temperature and Relative Humidity with Altitude

Weather.uwyo.edu was used to construct and analyze data for the variation of temperature and relative humidity with altitude from March 16, 2023 and April 6, 2023. Set up included: Select "region=north america", "type of plot=text:list", "year=2023", "month=mar", and set date "from=16/00Z" and "to=16/00Z" for March 16th (06/00Z for April 6). "OAK" on the map was clicked with a site code of # 72493. Data was copied and imported to Excel for data analysis. Boering et al. describes the process of transferring data to Excel in the lab manual. Excel graphs were generated by plotting the altitude on the y-axis and temperature and relative humidity on the x-axis. Tropopause, 1976 Temperature, Typical Cruise altitude were also included. Figure 3 . March 16, 2023 Altitude vs Temperature and Relative Humidity graph. Blue line is a graph of temperature (x-axis) vs altitude (y-axis). Orange line is a graph of relative humidity (x-axis) vs altitude (y-axis). Grey line is a graph of 1976 Temperature (x-axis) vs altitude (y-axis). Yellow line is a graph of Typical Cruise Altitude (x-axis) vs altitude (y-axis). Skyblue line is a graph of tropopause (x-axis) vs altitude (y-axis). Figure 4. April 6, 2023 altitude vs temperature and relative humidity graph. Blue line is a graph of temperature (x-axis) vs altitude (y-axis). Orange line is a graph of relative humidity (x-axis) vs altitude (y-axis). Grey line is a graph of 1976 Temperature (x-axis) vs altitude (y-axis). Yellow line is a graph of Typical Cruise Altitude (x-axis) vs altitude (y-axis). Skyblue line is a graph of tropopause (x-axis) vs altitude (y-axis).

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

a.) Comment on the general trends in temperature and relative humidity as a function of altitude for the two flights and their likely causes. Temperature is the measure of average kinetic energy of particles in a certain space. From figure 3 and figure 4 we see that the overall trend of temperature is similar. Temperature decreases with an increase of altitude in the troposphere, but increases as altitude increases in the stratosphere. Our troposphere houses the storms, clouds, precipitation, where planes fly, and accounts for almost 80% of the mass of the entire atmosphere. This is due to what is actually happening in the atmosphere. There is rapid vertical convection in the troposphere. This is because cold and heavy air is found above warm and light air. There is also slow vertical mixing in the stratosphere, where warm and light air is more present at the top of the stratosphere. Temperature near the surface is higher because the earth's surface is heated by the sun. Other reasons are due to the greenhouse gas effects such as CO2, water vapor and other gasses which traps outgoing infrared radiation resulting in a heated surface affecting temperature. Figure 3 and figure 4 also support the observance, from the surface to the troposphere the temperature decreases and it stalls at the tropopause where it increases in the stratosphere due to the ozone layer absorbing solar heat. Relative humidity is the ratio of the amount of water vapor in the air to the amount of water vapor the air can hold at a particular temperature and pressure. Relative humidity decreases with an increase in altitude because the atmosphere becomes less dense, and colder air can hold less moisture (pressure is lower at higher altitudes). Gravity plays a role in tightly holding air molecules at lower altitudes. As a result, the capacity for air at higher altitude to hold water is lower. b.) If there are large fluctuations in relative humidity in either of the flights, what might be the reason? There are no large fluctuations in relative humidity on March 16, 2023. However, there are large fluctuations in relative humidity for April 6, 2023. There could be a number of reasons for the fluctuations. March 16, 2023 had sunny conditions, whereas April 6, 2023 had cloudy conditions. There could also be rapid vertical mixing in the troposphere. If we were to have the launch during the winter or summer we can see a change in relative humidity. For example, during summer, oceans release more water vapor during warmer months. We can also take a look at the dew point temperature. The dew point temperature is generally highest near earth’s surface and tends to decrease with increasing altitude in the stratosphere. We see a lot of variation in the dew point in the troposphere. Note that there is a continuous water cycle incorporating the condensation and evaporation of water with the addition of clouds in our troposphere. Our troposphere houses the storms, clouds, precipitation, where planes fly, and accounts for almost 80% of the mass of the entire atmosphere.

c.) Use the US Standard Atmosphere 1976 temperature profile data for midlatitudes from the excel file on bCourses and include these data on each of the 2 plots for the 2 flights. These data represent an annually-averaged "typical" temperature profile for midlatitudes. Compare and contrast the US Standard Atmosphere Profile with the actual profiles. Speculate (as a "non-meteorologist") on what might cause differences between the profiles we observed and a "typical" one. Note: The US Standard Atmosphere 1976 temperature profile data for midlatitudes consists of annually averaged measurements meaning that the temperatures from each season are included in the measurements. The temperature profiles for March 16, 2023 and April 6, 2023 have more fluctuations, similar tropospheric temperatures, but lower stratospheric temperatures than the US Standard Atmosphere 1976 temperature profile. Having an increase of variability on March 16, 2023 and April 6, 2023 compared to the US Standard Atmosphere 1976 data is expected because the data is not an average. The stratospheric temperatures are lower for March 16, 2023 and April 6, 2023 than in 1976 because of the thinning of the ozone layer( heats the stratosphere). The increase/effects of greenhouse gas emissions in the stratosphere depletes the ozone layer. This causes a decrease in stratospheric temperatures and an increase in tropospheric temperature. Other possible explanations can be due to local geography since the measurements were taken at mid latitudes For example, a region near the ocean may have a different temperature profile than a region located inland. Other factors can be climate patterns, natural climate oscillations, such as El Niño or low/high pressure systems. d.) Determine the altitude of the WMO-defined tropopause (given below) for each of the two flights you are analyzing (Note: there might be more than one tropopause for a given flight!) and mark it on your plots. It will be helpful for you to plot up the definitions given below along with the flight data in order to compare slopes (i.e., the lapse rates, −dT/dz). ● Lapse rate is defined as –dT/dz. ● The first tropopause (i.e., the conventional tropopause) is defined as the lowest level at which the lapse rate decreases to 2 K/km or less, and the average lapse rate from this level to any level within the next higher 2 km does not exceed 2 K/km. ● If above the first tropopause the average lapse rate between any level and all higher levels within 1 km exceeds 3 K/km, then a second tropopause is defined by the same criterion as under the statement above. This tropopause may be either within or above the 1 km layer. ● A level otherwise satisfying the definition of tropopause, but occurring at an altitude below that of the 500 mbar level will not be designated a tropopause unless it is the only level satisfying the destination and the average lapse rate fails to exceed 3 K/km over at least 1 km in a layer. We used excel to calculate the lapse rate for the data. Tropopause was found at 10,100 meters on March 16, 2023 and 10,550 meters on April 6, 2023. No second tropopause was found. There was no average lapse rate between any level above the first tropopause and all higher levels within 1 km exceeded 3 K/km. Excel was used to calculate the lapse rate for all the data. A trendline was added.

e.) Also plot on your figures the cruise altitude of a typical commercial passenger jet (~35,000 ft or 10,600 m). Is there concern over whether or not jets spend a lot of time above or below the tropopause? Why or why not? A typical commercial passenger jet spends its time in the troposphere, upper tropopause, and lower stratosphere (tropopause height changes with the different seasons). There is concern over whether or not jets spend a lot of time above or below the tropopause, because 10% of the ozone layer is found in the tropopause and 90% of the ozone layer is found in the stratosphere. Air in the stratosphere does not circulate as much as it does compared to the troposphere because of slower vertical mixing. The release of chemicals like nox and greenhouse gasses in the stratosphere remain in the stratosphere for longer periods of time and has a greater impact on ozone layer depletion than the release of nox and greenhouse gasses in the troposphere. 3.2 Variation of Pressure with Altitude To measure the variation of pressure with altitude we took various equations to answer the questions listed below. Because a planet’s atmosphere is in the planet’s gravitational field, its density will fall with altitude. Since vertical motion is generally very small, the assumption of static equilibrium is a good starting point. If 𝝆 is the density and p the pressure at altitude z measured vertically upwards from the surface, we have dp(z) = – 𝝆 (z)gdz (1) (Hydrostatic equation) where g is the acceleration due to gravity at Earth’s surface (9.807 ms –2 ). From the equation of state for an ideal gas of molecular weight M r (28.97 g mol –1 for “air”) and temperature T: 𝝆 = M r p/RT (2) (Ideal gas law) where R is the gas constant (8.314 J mol –1 K –1 ). Equation (1) can be rearranged to give dp(z)/p(z) = –dz/H(z) which on integration gives, for the pressure p at altitude z : p(z) = p(0)exp{ (dz/H(z))} (3) − 0 𝑧 ∫ where p 0 is the pressure at z = 0 and H(z)=RT(z)/M r g, known as the “scale height,” is the increase in altitude necessary to reduce the pressure by a factor e . For the lower atmosphere of earth H varies between 6 km at T = 210 K to 8.5 km at T = 290 K. The temperature in the atmosphere varies by less than a factor of 2, while the pressure changes by six orders of magnitude. If the temperature can be taken to be approximately constant, just to obtain a simple approximate expression for p(z), then the pressure decrease with height is approximately exponential: p(z) = p 0 exp{–z/H} (4)

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

a.) For each of the two flights, plot measured pressure from the radiosonde data (x-axis) versus altitude. Figure 5. March 16, 2023 altitude vs pressure graph. Blue line is radiosonde pressure (x-axis) vs altitude (y-axis). Orange line is pressure changing with H (x-axis) vs altitude (y-axis). Grey line pressure with constant H (x-axis) vs altitude (y-axis). Yellow line is 1976 pressure (x-axis) vs altitude (y-axis). Figure 6 . April, 2023 altitude vs pressure graph. Blue line is radiosonde pressure (x-axis) vs altitude (y-axis). Orange line is pressure with constant H (x-axis) vs altitude (y-axis). Grey line

pressure changing with H (x-axis) vs altitude (y-axis). Yellow line is 1976 pressure (x-axis) vs altitude (y-axis). b.) Predict the pressure profile by using equation (4) above assuming that H is constant and equal to 8 km [Be sure to check units and do dimensional analysis!]. How well does (4) predict the measured pressure? Where is the largest discrepancy and what is its cause? We use equation 4 and substitute various values into the variables to calculate the pressure. An example calculation is done below. (4) 𝑃 = 𝑃 0 × 𝑒 −𝑧/𝐻 Assuming H = 8 km = 8000 m: 03-16-23: 𝑃 = 1000 × 𝑒 −𝑧/8000 𝑃 = 1001 × 𝑒 −3/8000 𝑃 = 997 ℎ𝑃𝑎 04-06-23: 𝑃 = 1000 × 𝑒 −𝑧/8000 𝑃 = 1000 × 𝑒 −27/8000 𝑃 = 996 ℎ𝑃𝑎 The equation predicts the measured pressure well at low altitudes and high pressures. However, at higher altitude and lower pressure there is some variation. At higher altitudes, temperature and scale height are not constant (as assumed in equation 4). The scale height is not uniform since the altitude required to decrease pressure by a factor of e rises at higher altitudes. The curve predicted by equation (4) with constant H is shifted upwards compared to the other curves at lower pressures and higher altitudes because the equation assumes H and temperature to be constant at all altitudes. At the highest altitudes, the temperature approaches the conditions of equation (4) . We see a closer relationship between the curves. c.) Now use equation (4) to predict the pressure as a function of altitude again, but this time let H vary as a function of measured T . Where is the largest discrepancy and what is its cause? [Hint: compare equations (3) and (4).] We use equation 4 and substitute various values into the variables to calculate the pressure. An example calculation is done below: 𝐻(𝑧) = 𝑅𝑇(𝑧)/𝑀 𝑟 𝑔 = [8. 314 × (𝑇(𝑧) + 273)]/(. 02897 × 9. 807) 𝐻(𝑧) = 𝑅𝑇(𝑧)/𝑀 𝑟 𝑔 = [8. 314 × (285. 95)]/(. 02897 × 9. 807) 𝐻(𝑧) = 𝑅𝑇(𝑧)/𝑀 𝑟 𝑔 = 8364 𝑚 03-16-23: 𝑃 = 1000 × 𝑒 −𝑧/[(8.314×(𝑇(𝑧)+273))/(.02897×9.807)] 03-16-23: 𝑃 = 1000 × 𝑒 [−3/8364] 03-16-23: 𝑃 = 999 ℎ𝑃𝑎 𝐻(𝑧) = 𝑅𝑇(𝑧)/𝑀 𝑟 𝑔 = [8. 314 × (𝑇(𝑧) + 273)]/(. 02897 × 9. 807) 𝐻(𝑧) = 𝑅𝑇(𝑧)/𝑀 𝑟 𝑔 = [8. 314 × (287. 15)]/(. 02897 × 9. 807) 𝐻(𝑧) = 𝑅𝑇(𝑧)/𝑀 𝑟 𝑔 = 8400 𝑚

04-06-23: 𝑃 = 1000 × 𝑒 −𝑧/[(8.314×(𝑇(𝑧)+273))/(.02897×9.807)] 04-06-23: 𝑃 = 1000 × 𝑒 [−3/8400] 04-06-23: 𝑃 = 999 ℎ𝑃𝑎 The curve predicted by equation (4) when H varies as a function of measured T is shifted down from the other pressure vs. altitude curves at low pressure and high altitudes. Mathematically equation (3) is more accurate because equation (4) assumes a constant H. Equation (3) calculates the integral of change of altitude over H. It depends on the calculation of H(z)=RT(z)/M r g. We assume that H is constant from equation (3) to equation (4) . In reality H depends on H(z)=RT(z)/M r g. The discrepancy happens at higher altitudes, we get lower H values because H decreases at higher altitudes (the calculated pressure values are lower compared to the pressure values for the other curves). Note: At the highest altitude and lowest pressure values, curves are similar because the temperature is relatively the same. d.) Now add the US Standard Atmosphere pressure versus altitude data. Is there much difference between the US Standard Atmosphere pressure profile and between the two pressure profiles for the two flights you’ve analyzed? Why do you think this is the case? [If you need a hint, skim the (former) website by M.J. Majoney, who used to measure vertical temperature profiles from aircrafts. (See bCourses for the content from the old website in a pdf document.)] The US Standard Atmosphere pressure versus altitude data aligns closely with the two pressure profiles for the two flights analyzed. Intuitively, pressure does not have much variability like conditions explained in previous parts. Pressure is essentially the weight of the air in the atmosphere. Pressure does not change throughout seasons or other effects like temperature.

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version