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O Level Geography Practice Paper 4

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TuitionGoWhere Practice Paper - Geography O-Level

PRACTICE PAPER — Version 4

TuitionGoWhere Secondary School (AI)

Field	Details
Subject:	Geography (2279)
Level:	O-Level
Paper:	Map, Graph & Data Skills
Duration:	1 hour 15 minutes
Total Marks:	50

Name: ___________________________
Class: ___________________________
Date: ___________________________

Instructions to Candidates

This paper consists of 20 questions in three sections.
Answer ALL questions in the spaces provided.
The number of marks is given in brackets [ ] at the end of each question or part question.
You are reminded to read each question carefully and to allocate your time appropriately.
Where calculations are required, show your working clearly.
You may use a calculator.
The total mark for this paper is 50.

Section A: Data Interpretation and Graph Skills (Questions 1–7)

Answer all questions in this section.

Study Figure 1, which shows the average monthly rainfall and temperature for Station X (a tropical location) and Station Y (a temperate location).

Figure 1: Climate Data for Station X and Station Y

Month	Station X Rainfall (mm)	Station X Temp (°C)	Station Y Rainfall (mm)	Station Y Temp (°C)
Jan	260	27	55	5
Feb	240	27	48	6
Mar	280	28	52	9
Apr	220	28	45	12
May	180	28	58	16
Jun	120	27	62	19
Jul	100	27	70	21
Aug	110	27	75	20
Sep	150	27	68	17
Oct	200	27	60	13
Nov	250	27	58	8
Dec	270	27	56	5

1. Using the data in Figure 1, calculate the total annual rainfall for Station X. Show your working. [2]

2. Calculate the mean annual temperature for Station Y. Show your working and give your answer to one decimal place. [2]

3. Describe two differences in the rainfall patterns of Station X and Station Y. Support your answer with data from Figure 1. [4]

Study Figure 2, which shows the results of a survey conducted by Geography students on the types of waste collected at four locations in a neighbourhood.

Figure 2: Waste Composition by Location (%)

Waste Type	Location A (Residential)	Location B (School)	Location C (Hawker Centre)	Location D (Park)
Food waste	35	25	55	10
Plastic	30	35	25	40
Paper	20	30	10	15
Metal	10	5	5	5
Glass	5	5	5	30

4. Suggest how the waste composition data for the four locations could be shown on one graph. Explain your choice of graph type. [3]

5. Identify the location with the highest proportion of food waste and suggest one reason for this pattern. [2]

6. A student claims that "Location D has the most varied waste composition." Using data from Figure 2, explain whether you agree with this statement. [3]

7. The students collected waste data by observing and categorising waste items at each location over a two-hour period on a single weekday. Evaluate the reliability of this data collection method. [4]

Section B: Map Skills and Spatial Analysis (Questions 8–14)

Answer all questions in this section.

Study Figure 3, a topographic map extract (scale 1:50,000) showing a coastal area. Contour lines are at 20-metre intervals.

Figure 3: Topographic Map Extract (not to scale for reproduction)

Key features shown:

Coastline with a bay at grid reference 4623
River flowing from grid reference 4828 to the sea at 4623
Settlement A at grid reference 4725 (elevation 5 metres)
Settlement B at grid reference 5027 (elevation 180 metres)
Road connecting Settlement A to Settlement B, passing through a col at grid reference 4826
Forest cover on slopes above 100 metres
Spot height 245 metres at grid reference 5128

8. State the six-figure grid reference for the spot height 245 metres. [1]

9. Measure the straight-line distance in kilometres between Settlement A (4725) and Settlement B (5027). [2]

10. Calculate the gradient of the road between Settlement A (elevation 5 m) and the col at grid reference 4826 (elevation 120 m), given that the ground distance between these two points is 2.4 km. Express your answer as a ratio in the form 1 : X. Show your working. [3]

11. Describe the relief of the area shown in Figure 3. [3]

12. With reference to evidence from Figure 3, explain two reasons why Settlement A is located at its present site. [4]

13. A student wants to conduct fieldwork to investigate river characteristics along the river shown in Figure 3. Suggest one hypothesis the student could test and describe one method of data collection that could be used. [3]

14. Using Figure 3, identify one potential hazard that could affect Settlement A and explain why this settlement is vulnerable to this hazard. [3]

Section C: Integrated Data Analysis and Evaluation (Questions 15–20)

Answer all questions in this section.

Study Figure 4, which shows data on tourist arrivals to Country Z from 2015 to 2024.

Figure 4: International Tourist Arrivals to Country Z (millions)

Year	Tourist Arrivals (millions)
2015	8.2
2016	9.1
2017	10.5
2018	11.8
2019	12.4
2020	2.1
2021	3.5
2022	7.8
2023	10.2
2024	11.5

15. Describe the trend in tourist arrivals to Country Z between 2015 and 2024. Support your answer with data from Figure 4. [3]

16. Calculate the percentage decrease in tourist arrivals between 2019 and 2020. Show your working and give your answer to one decimal place. [2]

17. Suggest two possible reasons for the change in tourist arrivals between 2019 and 2021. [4]

Study Figure 5, which shows the results of a bipolar survey conducted by students investigating environmental quality at four sites in a city.

Figure 5: Bipolar Survey Results — Environmental Quality Scores

Students rated each site on a scale of −2 (very poor) to +2 (very good) for five indicators. The table shows the total score for each indicator at each site.

Indicator	Site 1 (City Centre)	Site 2 (Suburban)	Site 3 (Industrial)	Site 4 (Parkland)
Air quality	−6	+4	−8	+10
Noise levels	−8	+2	−6	+8
Litter	−4	+6	−4	+10
Green space	−10	+4	−8	+12
Building condition	−2	+8	−6	+6

Note: Each score represents the sum of responses from 10 respondents per site.

18. Describe how the students could calculate the positive and negative scores for air quality at Site 1. [2]

19. Using data from Figure 5, compare the environmental quality of Site 2 (Suburban) and Site 3 (Industrial). [4]

20. "The bipolar survey method is the most effective way to assess environmental quality in a city." How far do you agree with this statement? Support your answer with reference to the data collection method and possible alternatives. [6]

— END OF PAPER —

Check your work carefully. Ensure all questions are attempted.

Answers

TuitionGoWhere Practice Paper - Geography O-Level

PRACTICE PAPER — Version 4 — ANSWER KEY

TuitionGoWhere Secondary School (AI)

Subject: Geography (2279)
Level: O-Level
Paper: Map, Graph & Data Skills
Total Marks: 50

Section A: Data Interpretation and Graph Skills (Questions 1–7)

1. Using the data in Figure 1, calculate the total annual rainfall for Station X. Show your working. [2]

Answer: Total annual rainfall = 260 + 240 + 280 + 220 + 180 + 120 + 100 + 110 + 150 + 200 + 250 + 270 = 2,380 mm ✓

Marking:

1 mark for correct addition shown (or correct method evident)
1 mark for correct answer with units (mm)
Accept 2,380 only; deduct 1 mark if units missing or incorrect

2. Calculate the mean annual temperature for Station Y. Show your working and give your answer to one decimal place. [2]

Answer: Sum of temperatures = 5 + 6 + 9 + 12 + 16 + 19 + 21 + 20 + 17 + 13 + 8 + 5 = 151 Mean = 151 ÷ 12 = 12.6°C (to 1 d.p.) ✓

Marking:

1 mark for correct sum (151) or correct method
1 mark for correct answer 12.6°C (must be to 1 d.p. with units)
Accept 12.58°C if working shown but final answer not rounded (award 1 mark only)

3. Describe two differences in the rainfall patterns of Station X and Station Y. Support your answer with data from Figure 1. [4]

Answer (model response):

Difference 1: Station X receives much higher total rainfall than Station Y. For example, Station X's monthly rainfall ranges from 100 mm to 280 mm, whereas Station Y's monthly rainfall ranges from only 45 mm to 75 mm. Station X's annual total (2,380 mm) is substantially greater than Station Y's annual total (707 mm).

Difference 2: Station X shows a distinct seasonal pattern with higher rainfall from October to March (200–280 mm) and lower rainfall from June to August (100–120 mm). In contrast, Station Y shows relatively consistent rainfall throughout the year (45–75 mm per month) with no clear wet or dry season.

Marking:

2 marks per clearly described difference with data support (2 × 2 marks)
Award 1 mark for each valid difference stated without data, 2 marks with specific data reference
Accept other valid differences (e.g., Station X has greater variability/range; Station Y has summer maximum)
Do not award marks for differences in temperature (question asks for rainfall patterns)

4. Suggest how the waste composition data for the four locations could be shown on one graph. Explain your choice of graph type. [3]

Answer (model response): The data could be shown using a grouped/compound bar chart. Each location (A, B, C, D) would be represented on the x-axis, with five bars grouped together for each location representing the five waste types. The y-axis would show percentage (0–60%). Different colours or shading patterns would distinguish each waste type, with a legend provided.

Explanation: A grouped bar chart is appropriate because the data is categorical (locations and waste types) and allows easy visual comparison of waste composition both within each location and across the four locations. A pie chart would require four separate charts and would not allow easy cross-location comparison. A line graph would be inappropriate as the data is not continuous or time-series.

Marking:

1 mark for identifying an appropriate graph type (grouped/compound bar chart; stacked bar chart also acceptable)
1 mark for describing how data would be represented (axes, grouping, legend)
1 mark for explaining why this graph type is suitable (categorical comparison, visual clarity)
Accept stacked bar chart with valid justification

5. Identify the location with the highest proportion of food waste and suggest one reason for this pattern. [2]

Answer: Location: Location C (Hawker Centre) with 55% food waste.

Reason: Hawker centres generate large amounts of food waste because they are places where food is prepared, served, and consumed in large quantities. Leftover food from customers, food preparation scraps, and unsold food all contribute to the high proportion of food waste.

Marking:

1 mark for correctly identifying Location C (Hawker Centre)
1 mark for a plausible reason linked to the nature of the location (food preparation/consumption activities)
Accept other valid reasons (e.g., high volume of food-related businesses, lack of food waste recycling)

6. A student claims that "Location D has the most varied waste composition." Using data from Figure 2, explain whether you agree with this statement. [3]

Answer (model response): I partially agree with this statement. Location D (Park) has the most even distribution across waste types compared to other locations. For example, Location D has 40% plastic, 30% glass, 15% paper, 10% food waste, and 5% metal — a spread across all five categories. In contrast, Location C is dominated by food waste (55%) and Location A is dominated by food waste (35%) and plastic (30%). However, all locations contain all five waste types, so "most varied" is relative. Location D does not have a single waste type exceeding 40%, whereas other locations have one or two dominant categories, making Location D's composition more balanced and varied.

Marking:

1 mark for stating position (agree/partially agree/disagree)
1 mark for using data from Figure 2 to support the argument (citing specific percentages)
1 mark for comparing Location D with at least one other location to justify the claim
Award full marks for a well-reasoned disagreement if supported by data (e.g., arguing that all locations show variety)

Answer (model response): The data collection method has limited reliability for several reasons.

Limitations reducing reliability:

Short duration: A single two-hour observation period may not be representative of typical waste patterns. Waste composition could vary significantly at different times of day (e.g., lunchtime vs morning).
Single day: Data collected on only one weekday does not account for daily variations. Weekday patterns may differ from weekend patterns, especially at a park or hawker centre.
Observer bias: Different students may categorise waste items differently (e.g., a plastic-lined paper cup could be classified as paper or plastic), leading to inconsistent data across locations.

Strengths supporting some reliability:

Direct observation provides first-hand data rather than relying on second-hand reports.
Using the same method across all four locations allows for some comparability.

Conclusion: Overall, the reliability is low because the sample is not representative of typical conditions. To improve reliability, students should collect data over multiple days (including weekends) and at different times, and use clear categorisation criteria to reduce observer bias.

Marking:

1 mark for clear position statement on reliability (e.g., "limited reliability")
1–2 marks for explaining specific limitations with reference to the method described (duration, single day, observer bias)
1 mark for acknowledging a strength or suggesting an improvement
Award up to 4 marks for a balanced evaluation that considers both strengths and weaknesses
Do not award marks for generic statements without reference to the specific method

Section B: Map Skills and Spatial Analysis (Questions 8–14)

8. State the six-figure grid reference for the spot height 245 metres. [1]

Answer: 512280 ✓

Marking:

1 mark for correct six-figure reference (512280)
Must be six figures; accept 513285 or similar if within tolerance (based on map interpretation)
Award 0 marks for four-figure reference only

9. Measure the straight-line distance in kilometres between Settlement A (4725) and Settlement B (5027). [2]

Answer: Grid distance = 3 grid squares east + 2 grid squares north Using Pythagoras: √(3² + 2²) = √13 ≈ 3.6 grid squares At 1:50,000 scale: 1 grid square = 1 km Distance = 3.6 × 1 km = 3.6 km ✓

Alternative (direct measurement): Approximately 3.5–3.7 km (accept range 3.4–3.8 km)

Marking:

1 mark for correct method (grid square counting, Pythagoras, or measurement)
1 mark for correct answer with units (km)
Accept 3.4–3.8 km to allow for measurement variation
Deduct 1 mark if units missing or incorrect

Answer: Vertical difference = 120 m − 5 m = 115 m Horizontal distance = 2.4 km = 2,400 m Gradient = Vertical difference ÷ Horizontal distance = 115 ÷ 2,400 = 0.0479 Ratio = 1 : (2,400 ÷ 115) = 1 : 20.87 Gradient = 1 : 20.9 (or 1 : 21) ✓

Marking:

1 mark for correct vertical difference (115 m)
1 mark for correct conversion of units and formula application (115/2400)
1 mark for correct ratio expressed as 1 : X (accept 1 : 20.9 or 1 : 21)
Award 2 marks if method correct but minor arithmetic error

11. Describe the relief of the area shown in Figure 3. [3]

Answer (model response): The relief of the area shows higher ground in the east and lower ground in the west. The highest point is the spot height of 245 metres at grid reference 5128 in the eastern part of the map. The land slopes downwards towards the coast in the west, where Settlement A is located at only 5 metres elevation. The area has moderate relief, with a difference of approximately 240 metres between the highest and lowest points. A river valley cuts through the area, flowing from the higher eastern ground (around 4828) to the bay at the western coast (4623). Forest cover is found on the steeper slopes above 100 metres, indicating areas of higher elevation.

Marking:

1 mark for identifying general pattern (higher east, lower west; or sloping towards coast)
1 mark for citing specific evidence (spot height, settlement elevations, contour patterns)
1 mark for describing additional features (river valley, slope steepness indicated by forest cover, elevation range)
Award marks for any three distinct, accurate observations about relief

12. With reference to evidence from Figure 3, explain two reasons why Settlement A is located at its present site. [4]

Answer (model response):

Reason 1 — Access to water supply: Settlement A is located near the mouth of the river where it enters the bay (grid reference 4623). This provides a reliable source of fresh water for drinking, agriculture, and other domestic uses. The river would have been essential for the settlement's establishment and growth.

Reason 2 — Low-lying flat land: Settlement A is situated at an elevation of only 5 metres on the coastal plain. This flat, low-lying land is easier to build on and more suitable for agriculture compared to the steeper slopes further east (where forest cover indicates higher, steeper ground above 100 metres). The gentle relief facilitates construction of buildings and roads.

Marking:

2 marks per explained reason (2 × 2 marks)
1 mark for identifying a valid reason, 2 marks for explaining with map evidence
Accept other valid reasons: coastal access for fishing/trade, sheltered bay location, road connection to Settlement B
Must reference specific evidence from Figure 3 (grid references, elevations, features)

Answer (model response):

Hypothesis: "River velocity increases with distance downstream from the source." OR "Channel depth increases as the river flows from the upper course (near 4828) to the lower course (near 4623)."

Method: The student could measure river velocity using a float method. A floating object (e.g., an orange or cork) would be placed in the river at a marked starting point, and the time taken to travel a measured distance (e.g., 10 metres) would be recorded using a stopwatch. This would be repeated three times at each of several sites along the river's course (e.g., near the source at 4828, mid-course, and near the mouth at 4623) to obtain an average velocity. Velocity would be calculated as distance ÷ time (m/s).

Marking:

1 mark for a clear, testable hypothesis related to river characteristics
1 mark for describing an appropriate data collection method (float method, flow meter, channel measurements)
1 mark for explaining how the method would be applied (repetition, multiple sites, calculation)
Accept other valid hypotheses and methods (e.g., measuring channel width/depth with tape measure, bedload size with callipers)

14. Using Figure 3, identify one potential hazard that could affect Settlement A and explain why this settlement is vulnerable to this hazard. [3]

Answer (model response):

Hazard: Flooding (river flooding or coastal flooding)

Explanation of vulnerability: Settlement A is vulnerable to flooding because it is located at the mouth of the river (grid reference 4623) at a very low elevation of only 5 metres. During periods of heavy rainfall in the higher eastern catchment area, water would flow downstream and could overflow the river banks at the low-lying coastal plain where Settlement A is situated. The settlement's proximity to both the river and the coast means it could be affected by both river flooding (from heavy rainfall upstream) and coastal flooding (from storm surges or high tides). The flat, low-lying terrain provides little natural drainage, increasing flood risk.

Marking:

1 mark for identifying a valid hazard (flooding, coastal erosion, storm surge, landslide from slopes if applicable)
1 mark for explaining the physical factors contributing to vulnerability (low elevation, river/coastal location)
1 mark for linking the hazard specifically to Settlement A's location using map evidence
Accept other hazards with valid justification based on map evidence

Section C: Integrated Data Analysis and Evaluation (Questions 15–20)

15. Describe the trend in tourist arrivals to Country Z between 2015 and 2024. Support your answer with data from Figure 4. [3]

Answer (model response): Tourist arrivals to Country Z showed an overall increasing trend from 2015 to 2019, rising steadily from 8.2 million in 2015 to a peak of 12.4 million in 2019. However, there was a sharp decline in 2020 to only 2.1 million — a dramatic drop from the previous year. From 2021 onwards, arrivals gradually recovered, increasing from 3.5 million in 2021 to 11.5 million by 2024, approaching but not yet reaching the 2019 peak.

Marking:

1 mark for identifying the general trend (increase, sharp drop, recovery)
1 mark for citing specific data points (at least two data references)
1 mark for describing the trend in phases (pre-2020, 2020 drop, post-2020 recovery)
Award 2 marks if trend described without specific data

16. Calculate the percentage decrease in tourist arrivals between 2019 and 2020. Show your working and give your answer to one decimal place. [2]

Answer: Decrease = 12.4 − 2.1 = 10.3 million Percentage decrease = (10.3 ÷ 12.4) × 100 = 83.06...% Percentage decrease = 83.1% (to 1 d.p.) ✓

Marking:

1 mark for correct formula and substitution: (12.4 − 2.1) / 12.4 × 100
1 mark for correct answer 83.1% (must be to 1 d.p.)
Award 1 mark only if answer not to 1 d.p. or units missing

17. Suggest two possible reasons for the change in tourist arrivals between 2019 and 2021. [4]

Answer (model response):

Reason 1 — COVID-19 pandemic and travel restrictions: The sharp decline from 12.4 million in 2019 to 2.1 million in 2020 was likely caused by the global COVID-19 pandemic. Many countries imposed international travel bans, border closures, and lockdown measures that severely restricted tourism. Country Z would have been affected by both its own restrictions and the inability of tourists from other countries to travel.

Reason 2 — Slow recovery due to ongoing caution and restrictions: The partial recovery to only 3.5 million in 2021 (still far below 2019 levels) reflects the continued impact of the pandemic. Even as some travel restrictions were eased, many people remained cautious about international travel due to health concerns. Quarantine requirements, testing mandates, and changing travel advisories continued to discourage tourism. Economic impacts of the pandemic also reduced disposable income for travel.

Marking:

2 marks per explained reason (2 × 2 marks)
1 mark for identifying a valid reason, 2 marks for explaining how it affected tourist arrivals
Accept other valid reasons: economic recession, airline disruptions, changes in travel advisories, geopolitical events
Answers must link the reason to the specific time period (2019–2021)

18. Describe how the students could calculate the positive and negative scores for air quality at Site 1. [2]

Answer (model response): Each of the 10 respondents at Site 1 rated air quality on a scale from −2 (very poor) to +2 (very good). To calculate the scores:

Positive score: Count the number of respondents who gave positive ratings (+1 or +2) and multiply by their respective weights. For example, if 2 respondents rated +2 and 1 respondent rated +1: Positive score = (2 × 2) + (1 × 1) = 5.
Negative score: Count the number of respondents who gave negative ratings (−1 or −2) and multiply by their respective weights (ignoring the minus sign for the score, or treating as absolute values). For example, if 4 respondents rated −2 and 3 respondents rated −1: Negative score = (4 × 2) + (3 × 1) = 11.
Net score = Positive score − Negative score. For Site 1 air quality, the net score is −6 (as shown in Figure 5).

Marking:

1 mark for explaining the weighting system (assigning values to response categories)
1 mark for describing how positive and negative scores are separated and summed
Accept alternative clear explanations of the calculation method

19. Using data from Figure 5, compare the environmental quality of Site 2 (Suburban) and Site 3 (Industrial). [4]

Answer (model response): Site 2 (Suburban) has significantly better environmental quality than Site 3 (Industrial) across all five indicators.

Site 2 has positive scores for all indicators, ranging from +2 (noise levels) to +8 (building condition). This suggests that respondents generally rated the suburban environment positively. The highest positive scores were for building condition (+8) and litter (+6), indicating well-maintained buildings and clean streets.

In contrast, Site 3 has negative scores for all five indicators, ranging from −4 (litter) to −8 (air quality and green space). This indicates poor environmental quality, particularly for air quality and lack of green space. The industrial site is perceived negatively across all measures.

The greatest contrast between the two sites is in air quality (Site 2: +4 vs Site 3: −8, a difference of 12 points) and green space (Site 2: +4 vs Site 3: −8, also a difference of 12 points), highlighting the environmental disadvantages of the industrial area.

Marking:

1 mark for overall comparison statement (Site 2 better than Site 3)
1–2 marks for citing specific data from at least two indicators for each site
1 mark for identifying the greatest contrasts or patterns in the data
Award up to 4 marks for a detailed comparison using data from multiple indicators

Answer (model response):

Introduction: I partially agree that bipolar surveys are effective, but they are not necessarily the "most effective" method. The effectiveness depends on what aspect of environmental quality is being assessed and the purpose of the assessment.

Strengths of bipolar surveys (agree):

Bipolar surveys capture subjective perceptions of environmental quality, which is important because people's experience of their environment matters. The data in Figure 5 shows clear differences between sites that reflect how people actually feel about these places.
The method is systematic and quantifiable, allowing comparison across sites (as shown by the scores for Sites 1–4). The numerical scores enable statistical analysis and clear presentation of results.
Bipolar surveys are relatively quick and inexpensive to administer, allowing data collection from many respondents across multiple locations.

Limitations of bipolar surveys (disagree):

Bipolar surveys only capture perceptions, which may differ from objective measurements. For example, perceived air quality (Site 3: −8) may not match actual air quality measurements using scientific instruments.
Responses can be influenced by personal bias — a respondent's mood, expectations, or familiarity with an area may affect their ratings, reducing reliability.
The method does not capture specific causes of environmental quality issues. A low score for "litter" does not explain why litter is present or what types of litter are most common.

Alternative methods:

Objective measurements (e.g., decibel meters for noise, air quality sensors for pollutants) provide scientific, unbiased data that can complement perception surveys.
Environmental quality surveys (EQS) with systematic observation checklists allow trained observers to rate specific, observable criteria, reducing personal bias.
Photographic analysis can provide visual evidence of environmental conditions that can be compared over time.

Conclusion: The bipolar survey is a useful and effective method, particularly for understanding human perceptions of environmental quality. However, it is most effective when combined with other methods (triangulation) to provide both subjective and objective data. I therefore only partially agree with the statement — bipolar surveys are effective but not singularly "the most effective" method.

Marking (6-mark evaluation question):

Level	Marks	Descriptor
L1	1–2	Simple statements agreeing or disagreeing; limited or no reference to the method; no alternatives considered
L2	3–4	Explains strengths and/or weaknesses of bipolar surveys with some reference to the method; may mention one alternative; some structure
L3	5–6	Balanced evaluation considering both strengths and limitations; references specific aspects of the method; suggests alternatives; reaches a reasoned conclusion that addresses "how far"

Mark allocation guidance:

Award up to 2 marks for explaining strengths of bipolar surveys
Award up to 2 marks for explaining limitations
Award up to 2 marks for discussing alternatives and reaching a balanced conclusion
Maximum 6 marks requires all three elements with clear evaluation

— END OF ANSWER KEY —

Month	Station X Rainfall (mm)	Station X Temp (°C)	Station Y Rainfall (mm)	Station Y Temp (°C)
Jan	260	27	55	5
Feb	240	27	48	6
Mar	280	28	52	9
Apr	220	28	45	12
May	180	28	58	16
Jun	120	27	62	19
Jul	100	27	70	21
Aug	110	27	75	20
Sep	150	27	68	17
Oct	200	27	60	13
Nov	250	27	58	8
Dec	270	27	56	5

Month	Station X Rainfall (mm)	Station X Temp (°C)	Station Y Rainfall (mm)	Station Y Temp (°C)
Jan	260	27	55	5
Feb	240	27	48	6
Mar	280	28	52	9
Apr	220	28	45	12
May	180	28	58	16
Jun	120	27	62	19
Jul	100	27	70	21
Aug	110	27	75	20
Sep	150	27	68	17
Oct	200	27	60	13
Nov	250	27	58	8
Dec	270	27	56	5

Month	Station X Rainfall (mm)	Station X Temp (°C)	Station Y Rainfall (mm)	Station Y Temp (°C)
Jan	260	27	55	5
Feb	240	27	48	6
Mar	280	28	52	9
Apr	220	28	45	12
May	180	28	58	16
Jun	120	27	62	19
Jul	100	27	70	21
Aug	110	27	75	20
Sep	150	27	68	17
Oct	200	27	60	13
Nov	250	27	58	8
Dec	270	27	56	5