Incorporating original research in the classroom: A case study analyzing the influence of the Chesapeake Bay on local temperatures

Abstract

Maritime climates experience moderate temperatures due to the specific heat of the nearby water. The first objective of this study is to analyze the relationship between temperature (maximum, minimum, and range) and proximity to the Chesapeake Bay and Atlantic Ocean. Results show that the annual T_min (T_max) means are smaller (greater) at the most continental locations, while the maritime locations experience cooler days and warmer nights. This results in a smaller DTR in maritime locations. The most notable seasonal differences in the variables occur during the transitional seasons of spring and fall when the lag time of the water temperature change is more. It is difficult to discern whether the temperature of the bay-side localities is being influenced by the bay or the ocean, but the authors speculate that it is a combination thereof. The second objective of this study is to incorporate this research into the middle school classroom using an inquiry-based approach. This approach allows students to practice real-world science through a guided experiment that encourages critical thinking and lays the foundation for successful thinkers.

1. Introduction

As a dynamic system, the Earth is constantly changing. One change that is currently being discussed is climate change. But what is climate? As defined by NASA, climate is the long-standing weather patterns in a specific area (Gutro, 2005). While weather changes daily, climate is more stable, as it is an average of the weather that occurs over a number of years. When determining climate, surface temperature and precipitation for a certain area over a certain period of time, often 30 years, are taken into consideration (Glossary of Meteorology, 2012). As a general rule, climate is what you expect and weather is what you get.

There are many factors that govern the climate of an area, including latitude, land features such as water and mountains, winds, and ocean currents (Carbone, 2012). Latitude has a large effect on climate, as the angles of the sun will be different at different latitudes. This results in a variation of temperature and precipitation, among other features. The latitude of a place will not change, nor will the angle of the sun, so this is one of the more stable factors affecting climate. The currents of warm and cold water in the ocean are another factor, as warmer water results in warmer air temperatures. This work focuses on a third major factor, which is proximity to water (Carbone, 2012). A more “maritime” climate (one near water) will differ in precipitation and temperature when compared to a more “continental” climate (one more centralized on a continent). The maritime effect on precipitation is obvious, as an area near a large water source will generally have more evaporation and precipitation. The temperature of a coastal locality differs for a more complex reason, which is referred to as specific heat.

Specific heat is the amount of heat required to change a unit quantity of a substance by one degree in temperature (Weisstein, 2007). While one degree may not seem like a lot, it is quite a feat when one considers how much energy is required in order to obtain that raise. For water, it requires 4.186 joule/gram °C to raise it one degree Celsius, which is the highest specific heat of common substances (Nave, 2012). At 20°C, the specific heat of air is 1.01 joule/gram °C (Nave, 2012). This difference in specific heat between water and air has a large effect on climate. The specific heat of water is much greater than the specific heat of air.

Specific heat affects the climate of maritime locations because it takes longer for the water to heat up and longer for it to cool down (Science Encyclopedia). This in turn affects the air temperature above and around bodies of water, so that their highs and lows are more moderate than those of locations not near water. Continental climates have more fluctuation because they have no water to stabilize the temperatures. In theory, maritime locations have cooler (warmer) summer (winter) days, as the water remains cooler (warmer) than land. This will in turn affect the diurnal temperature range (DTR), or the difference between the daily maximum temperature (T_max) and daily minimum temperatures (T_min), with maritime locations having a smaller DTR due to the moderating effect that water has on temperature.

The type of water body near a maritime location also has an effect on temperature. Impurities, such as salt, in the water affect the specific heat slightly, making different bodies of water heat and cool at different rates. Another aspect of bodies of water that affects coastal temperatures is the depth of the water. For example, the Atlantic Ocean is 12, 881 feet deep on average (Enchanted Learning, 2010), while the Chesapeake Bay has an average depth of 21 feet. This means the water of the Chesapeake should be heated and cooled more quickly, and therefore the coastal temperatures should fluctuate more than a coastal area along the ocean.

The purpose of this research is twofold. First, we analyze the influence of the Atlantic Ocean and Chesapeake Bay on the temperature of adjacent locations. Second, we demonstrate how original research can be used to enrich the middle school science classroom by creating a meaningful lesson plan that incorporates the physical principles underlying this study.

2. Methods

The study analyzes the impact of the Chesapeake Bay and the Atlantic Ocean on the temperature of nearby locations by comparing temperature data from weather stations located across the area. Figure 1 shows the stations used in this study. The stations meet the following criteria:

• have data available for January 1–December 31, 2011
• are less than 150 m above sea level in order to account for elevation bias
• are located in an area with <30,000 people and a population density of <3,000pp/sq mi (according to 2010 census data) in order to account for urban bias.

The stations are divided into four location categories:

A.  “Near Atlantic”- This includes all stations on the Delmarva Peninsula due to their proximity to the ocean. While these  stations are also near the bay, the physical properties discussed in the previous chapter suggest that the ocean should have a stronger influence on these stations than the bay. 8 stations.
B.   “Near Chesapeake Bay”- This includes stations nearest the western shore of the bay. 7 stations.
C.   “Continental”- This includes locations relatively removed from either water source, as shown by the figure. 6 stations.
D.   “Distant continental”- This includes locations farther removed from either water source, as shown by the figure. 7 stations.

Figure 1. Location of weather stations used in the study. Near-Atlantic (A) stations are shown in blue, Near-Bay (B) in green, Continental (C) in red, and Distant-Continental (D) in purple.

While the climate of locations C and D are still likely influenced by the water sources, the effect should be less so than those in closer proximity. Stations farther west are not included because this will increase elevation differences between localities and introduce additional biases.

Daily T_max and T_min were acquired from the National Climatic Data Center for the year 2011 for the 28 stations, and used to calculate the DTR (T_max – T_min). Descriptive statistics and t-tests were used to analyze the differences between A, B, C, and D temperatures (T_max, T_min, and DTR) on an annual and seasonal basis.

3. Results

A. Mean annual temperatures

In this section the annual mean temperatures (T_max, T_min, and DTR) are compared between locations. The descriptive statistics of the temperature data are summarized in Table 1 and DTR values are displayed as boxplots in Figure 2. T_max is greater in continental locations while T_min is smaller, causing the greatest DTR in the D locations and the smallest in the A locations. This is consistent with the premise that the specific heat of water will cause maritime climates to have a smaller temperature range than those of continental climate. The standard deviation (Table 1) and interquartile range (Figure 2) also increase with distance from the ocean, showing more variability in DTR in continental climates.

Table 1: The station type (A–D) and corresponding annual temperature values (˚C) for 2011, including means and standard deviations (sd) of T_max, T_min, and DTR.

Figure 2: Boxplots of annual DTR values (˚C) for each station type (A–D).

Independent sample t-tests were used to test for a significant difference in the means. The results of the t-tests are shown in Table 2. Due to the large sample size, many of the differences are statistically significant (p<0.02); however, only some of those differences are large enough to consider notable. T_max of the maritime locations (A and B) are not different from each other, but are significantly smaller than T_max at the continental (C and D) locations, which are not different from each other. Thus, the locations farther from the water are slightly warmer on average. However, these differences are not as great as the T_min differences, which in several cases are twice as large. Maritime locations experienced higher T_min than the continental locations. All locations have statistically significantly different T_min except for B and C, which have the same value. All of the results of the DTR t-tests are statistically significant. The difference between A and D is the largest (3.2˚ C), followed by B and D (2.6˚ C). For the annual means it seems as though T_min has a larger influence on DTR differences between continental and maritime locations, while T_maxis not as important.

Table 2: T-test results comparing T_max, T_min, and DTR between station types (A–D). The numbers are the difference in the means (˚C), with a negative (positive) number indicating that the station listed in the row is less (greater) than the station listed in the column. A number marked with a * indicates a statistically significant difference (p<0.02).

B. Mean seasonal temperatures

As the water temperature slowly changes with the season, the impact of water on maritime temperatures should vary seasonally. In this section, the temperature data are divided into seasons to test for these differences. December through February are categorized as winter, March through May as spring, June through August as summer, and September through November as fall. The descriptive statistics of the temperature data are summarized in Table 3 and DTR values are displayed as boxplots in Figure 3. As we saw in the annual means, T_max is generally higher in the continental areas and T_minis generally lower. This results in the same DTR pattern, with DTR increasing with distance from the ocean. The boxplots show the smallest DTR range for every location occurs in the summer.

Table 3: Location type (A–D) and corresponding seasonal temperature means (˚C).

Figure 3: Boxplots of seasonal DTR values (˚C) for each location type.

Independent sample t-tests were used to test for a significant difference in the means. The results of the t-tests are shown in Tables 4 through 7. The largest differences in T_min and DTR occur between A and D locations in every season, with A locations being consistently warmer at night, regardless of season. The largest T_max differences occur between A and C locations (spring and summer) or B and C locations (winter and fall).

There are more significant differences (p<0.02) in T_min than T_max in every season except spring, which is when the greatest DTR differences occurred. The T_min differences were, on average, larger than the T_max differences except for the spring season, as well. While the annual means show T_min has a larger overall influence on DTR differences in the area, it is evident that T_max plays a larger role in spring DTR differences. This could be due to the increased solar radiation in the spring causing T_max to gradually increase throughout the season, making the lag between the water and air evident. This shines an interesting light on the “transitional seasons,” i.e. spring and fall. The opposite relationship is shown in the fall, where there are the greatest differences in T_min between locations. Here the land is cooling quickly with the diminishing solar radiation and longer nights, causing a quick decline in T_min over the land and making the cooling lag over the water more evident. This results in the transitional seasons having greater DTR differences between continental and maritime locations than during summer and winter, on average.

The differences between maritime locations (A and B) are minimal. A and B locations show no significant difference in T_max, and have no T_max or T_mindifference greater than 1˚ C. The differences between the two continental stations (C and D) are greater. This leads to speculation that while A is influenced greatly by the ocean, B may be influenced slightly by the ocean in combination with the bay. This in turn kept the B locations similar to the A locations in temperature, as compared to the differences between the other locations. However, this is only speculation based off of the results presented here, and to further analyze the impact of the bay on temperature, data from a larger number of stations between the bay and the ocean would be needed in order to analyze the microclimate of the peninsula.

Table 4: T-test results comparing T_max, T_min, and DTR between station types (A–D) during winter. The numbers are the difference in the means (˚C), with a negative (positive) number indicating that the station listed in the row is less (greater) than the station listed in the column. A number marked with a * indicates a statistically significant difference (P<0.02).

Table 5: The same as Table 4 but for spring.

Table 6: The same as Table 4 but for summer.

Table 7: The same as Table 4 but for fall.

4. Implementation in the classroom

This lesson uses a inquiry-based project approach to science learning. Not only are students doing an experiment, they are using their critical thinking skills in order to hypothesize and make conclusion. They are able to use the information they already know as well as information they learn through the lab time. Inquiry-based project learning creates a learning environment where students gain a better understanding of science concepts and skills along with learning cognitive, social, and communication skills (Kolodner et al., 2003). By incorporating inquiry-based project learning, teachers are “laying the foundation in middle school for students to be successful thinkers, learners, and decision makers throughout their lives and…learn the science they need to know to thrive in the modern world” (Kolodner et al., 2003).

Teacher(s):

Subject: Science

Grade: 6th

SOL(s):

6.1  The student will plan and conduct investigations in which

h) data are collected, recorded, analyzed, and reported using appropriate metric measurements;

i) data are organized and communicated through graphical representation (graphs, charts, and diagrams);

6.5  The student will investigate and understand the unique properties and characteristics of water and its roles in the natural and human-made environment. Key concepts include

d) the ability of large bodies of water to store heat and moderate climate;

General Objective(s): Students will:

• Create a hypothesis based off of previous knowledge.
• Follow instructions and conduct research about the given topic.
• Interpret their results.

Introduction:The teacher will explain to the students that today we are going to be discovering how land and water are different. We will be conducting an experiment to see which heats up faster and which cools slower (water or land). We will also be making hypothesis about how that affects the land around it. Does anybody have an idea on what will happen?

Specific Objectives: Students will:

• Hypothesize with their groups on if land or water heats up fastest.
• Conduct an experiment to test their hypothesis.
• Record the results of the experiment.
• Work as a group to graph their results and create a conclusion.
• Discuss as a class how they believe water temperature affects the surrounding areas and why.

Procedures: The Teacher will:

• Introduce the lesson and review the lab procedure and rules.
• Break the students into lab groups of 4 that will work well together.
• Describe to the students how the lab is going to run and explain where they can find all the materials they need in order to complete the lab.
• Circulate around the classroom to make sure all the students are on task while completing the experiment.
• Engage the students in conversation about their hypothesis while they are waiting for the water to warm up and cool down.
• Bring the students back and lead a discussion on how a water source will affect the temperature near it.

Closing: The teacher will bring the students back together and have them share their results. The teacher will then have the students hypothesize on how a water source will affect the temperature around it. The teacher should have the students focus in on the fact that since water takes longer to warm up and longer to cool down, the temperature in the surrounding areas will do the same.

Evaluation: The students will turn in a lab report and graph that they created during the lab time. The teacher will also ask questions throughout the entire lab and closing in order to ensure student understanding.

Materials:

• Lab Report sheet for each student
• Group paper for each student
• 3 identical waterproof containers per group (Large Styrofoam cups or plastic containers)
• 3 thermometers per group
• 1 heat lamp with at least 100-w bulb per group
• Black or very dark sand
• White sand
• Water
• Stop watches
• Colored Pencils

Assignments:

Using the internet or news, find one place near the Atlantic Ocean in Virginia and one in the middle of the state and compare and contrast the high and low temperatures for the day. (Finding the temperatures can happen before the students leave school if needed). Write a paragraph using the information you gained from today’s lab to explain why the temperatures are the way they are.

Extenders/Back-Up Activities:

• Have the students use the internet to look up temperatures across the state and have them look to see if the temperature is varying based on how far a place is from a body of water. (This can also be done as the students are working on their lab during their down time)
• For gifted students, have them design their own experiment.

Lab instructions:

Before you start: Fill one container about half-full with light sand, another with the dark sand, and the last with water. All of the containers should be filled to the same level. Place the thermometers upright into the sand and water. Make sure the ball of the thermometers is submerged into the sand or water.

Getting started: Place the containers under the light source so that they are all receiving equal amounts of rays.

Take the initial temperature of each material. If your sand and water temperatures are not the same, let the teacher know.

Turn on the light source and start your stop watch. Record the temperature of each material in Celsius every 5 minutes and record your data in the table below. After 40 minutes, turn off the light and let the water cool for the next 30 minutes while still recoding the temperature every 5 minutes. (The times can be adjusted based on the amount of class time).

Table 8: Sample table for students to record observations.

Conclusion: Use your table to create a graph based on your results. Graph the water, light sand, and dark sand temperatures on the same graph using different colors.

This lesson allows students to use their critical thinking skills in order to discover that the temperature surrounding a water source will heat up and cool down slower than the temperature of an area further from the same water source. It also incorporates math by having the students create and interpret a graph. Since this lesson is inquiry-based project learning students are gaining more skills than just science, they are also gaining life skills.

5. Conclusion

In this study, we compared the T_min, T_max and DTR of four location groups: Near Atlantic, Near Chesapeake Bay, Continental, and Distant Continental. We found that annual DTR mean and standard deviation increase as you move away from the water sources. This is consistent with the premise of specific heat and the ability for water to moderate nearby temperatures.

The same general pattern is seen seasonally, but there are variations between seasons. The transitional seasons (fall and spring) seem to highlight the lag time between the temperature changes of water and land. Spring is the season with the greatest DTR differences. Annually, T_min has a larger overall influence on DTR differences in the area; however, T_max differences are greater in the spring when the water is trying to warm up. This is the opposite in the fall, when the greatest T_min differences occur most likely because the water is still warm from its summertime heating. It is not obvious if the bay is able to moderate temperatures significantly on its own, or if the near-bay localities are being affected by their proximity to the ocean.

Original investigations such as this provide a unique opportunity to demonstrate real-world examples of classroom material. Creating an inquiry-based lesson plan based on research findings allows students to explore the world around them through guided, yet autonomous, investigations.

6. References

Glossary of Meteorology (retrieved 2012) Climate. American Meteorological Society.

Retrieved from http://amsglossary.allenpress.com

Carbone, J. G. (retrieved 2012) Climate Controls. University of South Carolina. Retrieved from http://people.cas.sc.edu/carbone/modules/mods4car/ccontrol/index.html

Enchanted Learning (2010) Earth’s Oceans. Retrieved from http://www.enchantedlearning.com/subjects/ocean/

Gutro, R. (2005) What’s the difference between weather and climate? NASA. Retrieved

from http://www.nasa.gov/mission_pages/noaa-n/climate/climate_weather.html

Kolodner, J. L., P. J. Camp, D. Crismond, B. Fasse, J. Gray, J. Holbrook, S. Puntambekar and M. Ryan (2003) Problem-based learning meets case-based reasoning in the middle-school science classroom: Putting learning by design into practice. J. Learning Sciences, 4, 495–547.

Nave, C. R. (2012) Specific Heat. Georgia State University. Retrieved from http://hyperphysics.phy-astr.gsu.edu/hbase/thermo/spht.html

Science Encyclopedia (retrieved 2012) Weather Affect of Ocean Waters. Retrieved from

http://science.jrank.org/pages/4826/Ocean-Weather-effects-ocean-waters.html

Weisstein, E.W. (2007) Specific Heat. Science World. Retrieved from http://scienceworld.wolfram.com/physics/SpecificHeat.html