1872 — Page 247

The user wants me to proofread OCR output of a historical meteorological table from Hong Kong (Government Civil Hospital, 1872). The OCR is quite garbled. I need to reconstruct the table in Markdown format, preserving the data structure.

Let me analyze the OCR text carefully.

First, the title: "12.-TABLE showing the Asxvat. Mean State of the ArsosruERE, during the Year 1872, es recorded at the Goversmest Čivit. Hospitat, 86 feet above mean low level of Spring Tides."

Clearly: "12.-TABLE showing the Average Mean State of the Atmosphere, during the Year 1872, as recorded at the Government Civil Hospital, 86 feet above mean low level of Spring Tides."

Then column headers are messy. Let me parse:

"BAROMETER"

"Faunesheit ThermometeRA." -> "Fahrenheit Thermometer."

"HYGROMETER."

"WIND."

"1872."

"Corrected to 82° Fahrenheit and reduced to Mean Sea Level."

"Self registering in Sunde." -> "Self registering in Sun." (probably "Self-registering in Sun")

"Diy Dnib." -> "Dry Bulb." (Dry and Wet bulb)

"Wet Bulb."

"Max.! Max." -> "Max. Min."? Actually "Max. Min." for Dry Bulb? Let's see.

"Min."

"In Shude." -> "In Shade."

"נוןות" -> Hebrew? Probably "Mean." (OCR garbled)

"Mean."

"Max. Min."

"Sun Min. in noil Bulb Bulb" -> "Sun Max. Min. in Soil Bulb Bulb"? Actually "Sun Max. Min. in Soil, Bulb, Bulb"? Wait.

"t in ex- Grass, 'inchies Vacuo. posed." -> "Max. Min. in Grass, inches Vacuo. Exposed."? Hmm.

"deep."

"Quarter (prevailing.)"

"Move- inent during" -> "Movement during"

"24"

"In Shade."

"In Shade."

"hours,"

"in"

"Mostus." -> "Miles."

"Bain" -> "Rain"

"in Iscurs" -> "in Inches"

"DURING THE MONTH."

"No."

"OF"

"State of WEATHER."

"DAYS"

"HAV-"

"INO RALS." -> "HAVING RAINS."

"Average during the Month."

"9 A.M"

"3 P.M."

Then the data rows for each month.

The table seems to have many columns. Let me try to reconstruct the column structure from the header lines.

The header lines (multiple lines) seem to be:

Line 1: BAROMETER | Fahrenheit Thermometer. | HYGROMETER. | WIND. | 1872. | Corrected to 82° Fahrenheit and reduced to Mean Sea Level. | Self registering in Sun. | Dry Bulb. | Wet Bulb. | Max. Min. | In Shade. | Mean. | Max. Min. | Sun Max. Min. in Soil, Bulb, Bulb? | Max. Min. in Grass, inches Vacuo. Exposed. | deep. | Quarter (prevailing.) | Movement during 24 hours, in Miles. | Rain in Inches | DURING THE MONTH. | No. OF DAYS HAVING RAINS. | State of WEATHER. | Average during the Month. | 9 A.M. | 3 P.M.

But the OCR splits across lines. Let's look at the data rows to infer columns.

First data row: "January, 80.23 30.13 70.0 60.0 62.0 66.0 58.8 61.2 61.4 08. 75.6 53.7 67.6 58.5 GL.1 54.2 56,0 | E & NE | E & NE 190 0.08 2 Fine 12 days. Overcast 19 days. Fine 16 days. Overenst 15 days."

Wait, "80.23" and "30.13" - barometer readings? Usually barometer in inches of mercury. 30.13 is plausible. 80.23? Maybe 30.23? OCR misread 3 as 8? Actually "80.23" could be "30.23". The header says "Corrected to 82° Fahrenheit and reduced to Mean Sea Level." So two barometer columns? Maybe "Max." and "Min." barometer? Or "9 A.M." and "3 P.M."? The header shows "9 A.M. 3 P.M." at the end for barometer? Let's see.

The header: "BAROMETER ... Corrected to 82° Fahrenheit and reduced to Mean Sea Level. Self registering in Sun. Dry Bulb. Wet Bulb. Max. Min. In Shade. Mean. Max. Min. Sun Max. Min. in Soil, Bulb, Bulb? Max. Min. in Grass, inches Vacuo. Exposed. deep. Quarter (prevailing.) Movement during 24 hours, in Miles. Rain in Inches DURING THE MONTH. No. OF DAYS HAVING RAINS. State of WEATHER. Average during the Month. 9 A.M. 3 P.M."

But the data row has many numbers. Let's count numbers in January row:

"80.23 30.13 70.0 60.0 62.0 66.0 58.8 61.2 61.4 08. 75.6 53.7 67.6 58.5 GL.1 54.2 56,0" then wind directions "E & NE | E & NE" then "190 0.08 2" then weather text.

That's 17 numbers before wind. Let's list:

1. 80.23 (likely 30.23)
2. 30.13
3. 70.0
4. 60.0
5. 62.0
6. 66.0
7. 58.8
8. 61.2
9. 61.4
10. 08. (maybe 98.0? or 108.0? "08." could be "108."? But later "108.4" appears for October. For January, maybe "108.0"? But it's "08." Could be "98.0"?)
11. 75.6
12. 53.7
13. 67.6
14. 58.5
15. GL.1 (likely 61.1? or 51.1? "GL.1" OCR for "61.1"?)
16. 54.2
17. 56,0 (56.0)

Then wind: "E & NE | E & NE" (9am and 3pm prevailing wind quarters)

Then "190" (movement in miles)

Then "0.08" (rain in inches)

Then "2" (days having rain)

Then weather description.

But the header mentions "Average during the Month. 9 A.M. 3 P.M." at the end. That might be for barometer? Actually the last two columns "9 A.M. 3 P.M." might be for barometer readings at those times. But the first two numbers 30.23 and 30.13 could be the barometer at 9am and 3pm? But the header says "Corrected to 82° Fahrenheit and reduced to Mean Sea Level." That suggests the barometer readings are corrected. Then "Self registering in Sun." might be for thermometer.

Let's look at the second row: February: "30.23 30.14 68.0 43.5 60.4 62 4 55.9 58.7 69.1 101. 77.6 50.5 64.7 55.5 58.8 50.6 536E & NE|E & SE 176 0.66 14 17"

Numbers: 30.23, 30.14, 68.0, 43.5, 60.4, 62.4? "62 4" -> 62.4, 55.9, 58.7, 69.1, 101., 77.6, 50.5, 64.7, 55.5, 58.8, 50.6, 53.6? "536E" -> 53.6 then wind.

So 14 numbers before wind? Let's count: 1:30.23, 2:30.14, 3:68.0, 4:43.5, 5:60.4, 6:62.4, 7:55.9, 8:58.7, 9:69.1, 10:101., 11:77.6, 12:50.5, 13:64.7, 14:55.5, 15:58.8, 16:50.6, 17:53.6. That's 17 numbers again.

March: "20.10 30.00 78.0 40.0 69.3 57.4 64.9 66.0 67.7 113. 88.0 55.2 59.6 64.5 67.4 GILK 62.0 E & NEE & SE 151 0.00 H"

Numbers: 20.10? Should be 30.10. 30.00, 78.0, 40.0, 69.3, 57.4, 64.9, 66.0, 67.7, 113., 88.0, 55.2, 59.6, 64.5, 67.4, GILK->61.0? 62.0. That's 16 numbers? Let's count: 1:30.10, 2:30.00, 3:78.0, 4:40.0, 5:69.3, 6:57.4, 7:64.9, 8:66.0, 9:67.7, 10:113., 11:88.0, 12:55.2, 13:59.6, 14:64.5, 15:67.4, 16:61.0?, 17:62.0. Actually "GILK 62.0" maybe two numbers: 61.0 and 62.0? "GILK" could be "61.0" misread. So 17 numbers.

April: "80,00 20.03 844.5 62.0 77.6 70.8 73.4 70.6 70.6 126. 99.7 68.2 71.0 73.0 76.8 71.0 SE & |SE & SW. 135 0.09"

Numbers: 30.00? "80,00" -> 30.00. "20.03" -> 30.03. "844.5" -> 84.5? Actually 84.5. 62.0, 77.6, 70.8, 73.4, 70.6, 70.6, 126., 99.7, 68.2, 71.0, 73.0, 76.8, 71.0. That's 15 numbers? Let's count: 1:30.00, 2:30.03, 3:84.5, 4:62.0, 5:77.6, 6:70.8, 7:73.4, 8:70.6, 9:70.6, 10:126., 11:99.7, 12:68.2, 13:71.0, 14:73.0, 15:76.8, 16:71.0. 16 numbers. But earlier months had 17. Maybe one column missing? "Max. Min. in Grass" maybe two columns? Let's see header.

The header line: "Max. Min. in Shude. נוןות Mean. Max. Min. Sun Min. in noil Bulb Bulb t in ex- Grass, 'inchies Vacuo. posed. deep."

This is garbled. Let's parse: "Max. Min. in Shade. Mean. Max. Min. Sun Max. Min. in Soil Bulb Bulb? Max. Min. in Grass, inches Vacuo. Exposed. deep." Actually "Sun Min. in noil Bulb Bulb" -> "Sun Max. Min. in Soil Bulb Bulb"? "t in ex- Grass" -> "Max. Min. in Grass". "'inchies Vacuo. posed." -> "inches Vacuo. Exposed." "deep." -> "Deep." (maybe earth temperature at depth).

So columns for thermometer:

• Dry Bulb: Max, Min, Mean? Actually "Dry Bulb. Wet Bulb. Max. Min. In Shade. Mean." That's 6 columns? Let's see: Dry Bulb Max, Dry Bulb Min, Wet Bulb Max, Wet Bulb Min, In Shade Max, In Shade Min, Mean? Hmm.

Better to look at standard meteorological tables of that era. The Hong Kong Observatory records. This is from Government Civil Hospital, 1872. The table likely includes:

• Barometer: 9am, 3pm (corrected)
• Thermometer (Fahrenheit): Dry bulb 9am, 3pm? Or max/min? "Self registering in Sun." suggests max/min in sun. "Dry Bulb." "Wet Bulb." "Max. Min. In Shade." "Mean." "Max. Min. Sun" (maybe solar radiation thermometer max/min). "Max. Min. in Soil" (earth thermometer). "Max. Min. in Grass" (grass minimum). "inches Vacuo." (maybe vacuum thermometer?). "Exposed." "Deep." (earth at depth).

But the data shows many numbers. Let's count columns from the annual mean row at bottom: "Annual Mean,.. 30.01 29.02 82.1 62.7 70,7 69,8 72.7 75.3 70.4 124. | 100.8 65.9 60.6 72.4 75.0 67.8 69.7 223 62.92 107"

That's 20 numbers? Let's count: 30.01, 29.02, 82.1, 62.7, 70.7, 69.8, 72.7, 75.3, 70.4, 124., 100.8, 65.9, 60.6, 72.4, 75.0, 67.8, 69.7, 223, 62.92, 107. That's 20 numbers. Then "THERMOMETER, FAHRENHEIT." and a small table of yearly extremes and rainfall.

So the main table has 20 data columns per month (plus month name, wind, movement, rain, days rain, weather). The annual mean row has 20 numbers.

Let's map the 20 columns:

1. Barometer 9am (corrected)
2. Barometer 3pm (corrected)
3. Dry Bulb Max? Or 9am? "82.1" annual mean for third column. January third number is 70.0. February 68.0. March 78.0. April 84.5. May 81.0? Actually May row: "20.4 29.79 81.0 645 83.4 76.0 78.3 81.4 81.8 130.104.3 | 73.2 78.5 77.9 BLA 71.8 74.0". Let's parse May: "20.4" -> 30.04? "29.79" -> 29.79. "81.0" -> 81.0. "645" -> 64.5? "83.4" -> 83.4. "76.0" -> 76.0. "78.3" -> 78.3. "81.4" -> 81.4. "81.8" -> 81.8. "130.104.3" -> 130.0 and 104.3? Actually "130.104.3" might be two numbers: 130.0 and 104.3. Then "73.2", "78.5", "77.9", "BLA" -> 71.8? "71.8", "74.0". That's many numbers.

Let's systematically parse each month row by splitting on spaces but careful with merged numbers.

Better approach: The OCR text is a mess. I need to reconstruct the table as best as possible, aligning columns based on header clues and annual mean.

Given the complexity, I'll produce a Markdown table with the columns as they appear in the original printed table, using the header text to define columns. I'll clean the data for each month.

First, let's transcribe the header lines as they appear in the OCR, but corrected.

The OCR header lines:

"BAROMETER

Faunesheit ThermometeRA.

HYGROMETER.

WIND.

1872.

Corrected to 82° Fahrenheit and reduced to Mean Sea Level.

Self registering in Sunde.

Diy Dnib.

Wet Bulb.

Max.! Max.

Min.

In Shude.

נוןות

Mean.

Max. Min.

Sun Min. in noil Bulb Bulb

t in ex- Grass, 'inchies Vacuo. posed.

deep.

Quarter (prevailing.)

Move- inent during

24

In Shade.

In Shade.

hours,

in

Mostus.

Bain

in Iscurs

DURING THE MONTH.

No.

OF

State of WEATHER.

DAYS

HAV-

INO RALS.

Average during the Month.

9 A.M

3 P.M."

This seems to be a vertical list of column headers, possibly arranged in a multi-row header in the original. The original table likely has a header spanning multiple rows. For Markdown, I'll create a single header row with combined column names.

Let's interpret each line as a column header (some lines are sub-headers). But there are many lines. Let's count lines: 33 lines. But many are continuations. For example, "Move- inent during 24 hours, in Mostus." is one header: "Movement during 24 hours, in Miles." "Bain in Iscurs" -> "Rain in Inches". "DURING THE MONTH." might be a section header. "No. OF DAYS HAVING RAINS." "State of WEATHER." "Average during the Month. 9 A.M. 3 P.M." might be two columns for barometer average at 9am and 3pm? But the annual mean row has 20 numbers before the wind etc. The "Average during the Month. 9 A.M. 3 P.M." appears at the end of the header list, after "State of WEATHER." But in the data rows, the weather description is at the end. So maybe the "Average during the Month. 9 A.M. 3 P.M." are the last two data columns (barometer averages). But the annual mean row shows 20 numbers, then "223 62.92 107" which are movement, rain, days rain? Actually annual mean: "223 62.92 107" - 223 miles movement, 62.92 inches rain, 107 days rain. That matches "Movement during 24 hours, in Miles." "Rain in Inches" "No. OF DAYS HAVING RAINS." So those three are at the end. Then "State of WEATHER." is descriptive, not numeric.

Thus the numeric columns (17?) plus wind directions (2 columns: 9am and 3pm prevailing quarter), movement, rain, days rain = 22 numeric? But annual mean has 20 numbers before the three? Let's recount annual mean: "30.01 29.02 82.1 62.7 70,7 69,8 72.7 75.3 70.4 124. | 100.8 65.9 60.6 72.4 75.0 67.8 69.7 223 62.92 107". That's 20 numbers. The last three of those 20 are 223, 62.92, 107. So the first 17 are meteorological elements. Then wind directions (two) are not in annual mean? The annual mean row doesn't show wind. Then movement, rain, days rain are included as the last three of the 20. So the 17 meteorological columns are:

1. Barometer 9am
2. Barometer 3pm
3. Dry Bulb Max? Or something
4. Dry Bulb Min?
5. Wet Bulb Max?
6. Wet Bulb Min?
7. In Shade Max?
8. In Shade Min?
9. Mean?
10. Sun Max?
11. Sun Min?
12. Soil Bulb Max?
13. Soil Bulb Min?
14. Grass Max?
15. Grass Min?
16. Vacuo? (maybe inches of vacuum? or something)
17. Deep? (earth temperature at depth)

But the header lines: "Diy Dnib." (Dry Bulb), "Wet Bulb.", "Max.! Max." (maybe Max. Min. for Dry Bulb?), "Min." (maybe for Wet Bulb?), "In Shude." (In Shade), "נוןות" (Mean), "Max. Min." (for Sun?), "Sun Min. in noil Bulb Bulb" (Sun Max. Min. in Soil Bulb Bulb?), "t in ex- Grass, 'inchies Vacuo. posed." (Max. Min. in Grass, inches Vacuo. Exposed.), "deep." (Deep).

That suggests 10 thermometer-related columns: Dry Bulb Max, Dry Bulb Min, Wet Bulb Max, Wet Bulb Min, In Shade Max, In Shade Min, Mean, Sun Max, Sun Min, Soil Bulb Max, Soil Bulb Min, Grass Max, Grass Min, Vacuo, Exposed, Deep. That's too many.

Let's look at the data: January has 17 numbers before wind. February 17. March 17. April 16? May many. June: "29.81 29.72 89.5 76.0 86.2 79.6 82.8 84.8 85.3 186. 109.1 76.3 79.0 81.9 85.0 7900" -> 16 numbers? "7900" might be 79.00. July: "220,20 29.73 89.0 77.0 $7.1 79.0 83.2 86.2 85.7 148, 118.1 70.5 79.2 82 8 863 78,0 80.9" -> messy. August: "29.82 20.77 89.0 77.0 87.2 80.0 83.2 86.4 R5.8 145. │114.2 77.5 80.6 82.8 83.4 77.7 70.4" -> 17 numbers. September: "29.04 20.87 80.0 74.0 83.9 74.8 80.0 82.2 82.7 139.115.8 78.4 77.3 FO 3 K1.9 74.4 75.1" -> 16? October: "30.03 29.91 85.0 69.0 70.4 78.1 75.7 78.2 78.0 123.108.4 GR.G 72.5 75.7 77.8 71.1 72.4" -> 17? November: "30.14 60.03 $0.0 59.0 74.2 60.4 60.0 72.8 72.0 123. | 108.0 62.0 66.8 69.6 72.0 63.8 65.0" -> 17? December: "30.12 30.03 75,0 56.0 70.6 68.7 66.7 GO.8 68.7 114. 01.4 56.0 61.2 66.6 GR.4 63.8 64.2" -> 17.

So most months have 17 numeric columns before wind. Annual mean has 17 meteorological columns? But annual mean shows 20 numbers, but last three are movement, rain, days rain. So 17 meteorological + 3 = 20. Yes.

Thus the 17 meteorological columns are:

1. Barometer 9am (corrected)
2. Barometer 3pm (corrected)
3. Dry Bulb Max
4. Dry Bulb Min
5. Wet Bulb Max
6. Wet Bulb Min
7. In Shade Max
8. In Shade Min
9. Mean (of what? maybe mean temperature)
10. Sun Max
11. Sun Min
12. Soil Bulb Max (or "in Soil Bulb")
13. Soil Bulb Min
14. Grass Max
15. Grass Min
16. Vacuo (maybe "inches Vacuo" - could be evaporation?)
17. Deep (earth temperature at depth)

But the header mentions "Self registering in Sun." "Dry Bulb." "Wet Bulb." "Max. Min." "In Shade." "Mean." "Max. Min." "Sun Max. Min. in Soil Bulb Bulb" "Max. Min. in Grass, inches Vacuo. Exposed." "deep."

That matches:

• Self registering in Sun: probably the solar radiation thermometer (Sun Max, Sun Min)
• Dry Bulb: Max, Min
• Wet Bulb: Max, Min
• In Shade: Max, Min
• Mean: (maybe mean of dry bulb?)
• Sun Max, Min (again? duplicate)
• In Soil Bulb: Max, Min (two bulbs? "Bulb Bulb")
• In Grass: Max, Min
• Inches Vacuo: (maybe evaporation gauge)
• Exposed: (maybe another thermometer)
• Deep: earth temperature at depth.

But that would be more than 17. Let's count: Dry Bulb Max, Min (2), Wet Bulb Max, Min (2), In Shade Max, Min (2), Mean (1), Sun Max, Min (2), Soil Bulb Max, Min (2), Grass Max, Min (2), Vacuo (1), Exposed (1), Deep (1) = 18. Plus two barometer = 20. But we have 17 meteorological. So some are combined.

Maybe "Self registering in Sun" refers to the thermometer that registers max/min in sun (so Sun Max, Sun Min). "Dry Bulb" and "Wet Bulb" are at specific hours (9am, 3pm)? But the header says "Max. Min." for each. The data shows numbers like 70.0, 60.0 for January third and fourth. Those could be Dry Bulb Max and Min. Then 62.0, 66.0? That's Wet Bulb Max, Min? But Wet Bulb max higher than dry bulb? Unlikely. 62.0 and 66.0: wet bulb max 66, min 62? But dry bulb max 70, min 60. That's plausible. Then 58.8, 61.2: In Shade Max, Min? But in shade max lower than dry bulb? Actually dry bulb in shade? Hmm.

Let's check February: 68.0, 43.5 (Dry Bulb Max, Min), 60.4, 62.4 (Wet Bulb Max, Min? But wet bulb max 62.4 > dry bulb min 43.5, okay), 55.9, 58.7 (In Shade Max, Min?), 69.1, 101. (Sun Max, Min? Sun min 101? That's higher than max 69.1? No, 101 is max, 69.1 min? But "69.1 101." could be Sun Max 101, Sun Min 69.1? But order: Max then Min. So 69.1 max, 101 min? That's reversed. Maybe it's Sun Max 101, Sun Min 69.1? But the order in data is "69.1 101." So first is lower. Could be Min then Max? But header says "Max. Min." So maybe the columns are Min then Max? Let's check January: "70.0 60.0" - if Min then Max, min 70, max 60? No. So it's Max then Min. For Sun, January: "75.6 53.7" - max 75.6, min 53.7. That works. February: "77.6 50.5" - max 77.6, min 50.5. But the data shows "69.1 101." for February? Wait February numbers: after 58.7, we have "69.1 101." That would be Sun Max 69.1, Sun Min 101? No. Let's re-parse February row carefully.

February row from OCR: "February, 30.23 30.14 68.0 43.5 60.4 62 4 55.9 58.7 69.1 101. 77.6 50.5 64.7 55.5 58.8 50.6 536E & NE|E & SE 176 0.66 14 17"

Split:

1. 30.23
2. 30.14
3. 68.0
4. 43.5
5. 60.4
6. 62.4 (since "62 4" -> 62.4)
7. 55.9
8. 58.7
9. 69.1
10. 101.
11. 77.6
12. 50.5
13. 64.7
14. 55.5
15. 58.8
16. 50.6
17. 53.6 (from "536E" -> 53.6)

Then wind.

So columns 9 and 10: 69.1 and 101. Could be "Sun Max" and "Sun Min"? But 101 > 69.1, so if Max then Min, 69.1 max, 101 min impossible. So maybe columns 9 and 10 are "In Shade Max, Min"? But we already had 55.9, 58.7 for In Shade? Let's see header: "In Shude." then "נוןות" (Mean) then "Max. Min." then "Sun Min. in noil Bulb Bulb". So after "Mean" there is "Max. Min." (maybe for Sun), then "Sun Min. in noil Bulb Bulb" (maybe Soil Bulb Max Min). So column 9: Sun Max, column 10: Sun Min, column 11: Soil Bulb Max, column 12: Soil Bulb Min, column 13: Grass Max, column 14: Grass Min, column 15: Vacuo, column 16: Exposed, column 17: Deep.

But for February, column 9=69.1, column 10=101. Sun Max 69.1, Sun Min 101? No. Could be Sun Min, Sun Max? But header says Max. Min. So maybe the order is Min then Max for Sun? But for January, column 9=75.6, column 10=53.7 (if we align). January numbers: after 61.4 (column 8?), we have "08." (column 9?), "75.6" (10), "53.7" (11), "67.6" (12), "58.5" (13), "GL.1" (14), "54.2" (15), "56,0" (16). That's only 16 numbers? Let's index January properly.

January row: "January, 80.23 30.13 70.0 60.0 62.0 66.0 58.8 61.2 61.4 08. 75.6 53.7 67.6 58.5 GL.1 54.2 56,0 | E & NE | E & NE 190 0.08 2 Fine 12 days. Overcast 19 days. Fine 16 days. Overenst 15 days."

Numbers:

1. 80.23 -> 30.23
2. 30.13
3. 70.0
4. 60.0
5. 62.0
6. 66.0
7. 58.8
8. 61.2
9. 61.4
10. 08. (maybe 98.0? or 108.0? "08." could be "108." missing '1'? But annual mean column 10 is 124. So January column 10 should be around 124? Actually annual mean column 10 is 124. (Sun Max?). January column 10 = 08? No. Let's look at annual mean columns:
11. 30.01
12. 29.02
13. 82.1
14. 62.7
15. 70.7
16. 69.8
17. 72.7
18. 75.3
19. 70.4
20. 124.
21. 100.8
22. 65.9
23. 60.6
24. 72.4
25. 75.0
26. 67.8
27. 69.7
28. 223
29. 62.92
30. 107

So column 10 annual mean = 124. That is likely "Sun Max" (max solar radiation temperature). January column 10 should be around 124? But we have "08." which is 8. That can't be. Maybe "08." is actually "108."? 108 is plausible for January sun max. But OCR gave "08." Could be "108." with '1' missing. Or "108.0"? The OCR for September has "139.115.8" which is two numbers: 139. and 115.8. So column 10 and 11 for September are 139 and 115.8. Annual mean column 10=124, column 11=100.8. So September column 10=139 (higher), column 11=115.8 (higher). That matches Sun Max and Sun Min? But Sun Min 115.8 in September? That's high. Maybe column 10 is "Sun Max" and column 11 is "Sun Min"? But Sun Min should be lower. 115.8 is high. Could be "In Soil Bulb Max" and "In Soil Bulb Min"? But annual mean column 12=65.9, column 13=60.6. September column 12=78.4, column 13=77.3? Actually September: "78.4 77.3 FO 3 K1.9 74.4 75.1". Let's parse September later.

Given the difficulty, I think the best is to present the table as it appears in the OCR but cleaned up, with columns labeled as per the header lines, and data rows as parsed. Since the user wants proofreading, I should correct obvious OCR errors (like 80.23 -> 30.23, 20.10 -> 30.10, 80,00 -> 30.00, 20.03 -> 30.03, 20.4 -> 30.04, 220,20 -> 29.20? Actually July barometer: "220,20 29.73" -> 29.20 and 29.73? But "220,20" likely "29.20". August: "20.77" -> 29.77. September: "20.87" -> 29.87. October: "30.03 29.91" good. November: "60.03" -> 30.03. December: "30.12 30.03" good.

Also fix temperatures: "844.5" -> 84.5, "645" -> 64.5, "130.104.3" -> 130.0 and 104.3, "GL.1" -> 61.1, "GILK" -> 61.0, "BLA" -> 71.8? "7900" -> 79.00, "$7.1" -> 87.1, "R5.8" -> 85.8, "145. │114.2" -> 145.0 and 114.2, "139.115.8" -> 139.0 and 115.8, "FO 3" -> 70.3? "K1.9" -> 81.9? "GR.G" -> 71.1? "GR.4" -> 69.4? "01.4" -> 91.4? "GO.8" -> 60.8? "536E" -> 53.6, "223 62.92 107" at end of annual mean.

Also the small table at bottom: "THERMOMETER, FAHRENHEIT. + RAIN FALL IN INCHES. 1860. 1887. 1868. 1860. 1870. 1871. 1872. 1800. 1867. 1868. 1860. 1870. 1871. 1872. 03.0 92.0 88.0 89.0 89.5 89.0 80.5 Minuman, 15.0 41.0 42.0 43.0 40.0 36.0 43.5 77.49 80.80 88.04 63.71 56.07 09.24 62.02 Rangp 48.0 51.0 46.0 40.0 43.5 53.0 46.0 Total Total during during the the Year. Teng. C. J. WHARRY, M.n.. Superintendent."

This is a separate table showing yearly extremes and rainfall totals for years 1860-1872. The OCR is messy. "1887" should be 1867? Actually list: 1860, 1867, 1868, 1869, 1870, 1871, 1872. The OCR has "1860. 1887. 1868. 1860. 1870. 1871. 1872." and then "1800. 1867. 1868. 1860. 1870. 1871. 1872." So two rows of years. First row maybe for Thermometer max, second for min? Then numbers: "03.0 92.0 88.0 89.0 89.5 89.0 80.5" - these are max temps for each year? 1860: 93.0? "03.0" -> 93.0. 1867: 92.0, 1868: 88.0, 1869: 89.0, 1870: 89.5, 1871: 89.0, 1872: 80.5? But 1872 max was 89.5 from table. So maybe not.

"Minuman," -> "Minimum," then "15.0 41.0 42.0 43.0 40.0 36.0 43.5" - minimum temps.

Then "77.49 80.80 88.04 63.71 56.07 09.24 62.02" - rainfall totals for each year? 1860: 77.49, 1867: 80.80, 1868: 88.04, 1869: 63.71, 1870: 56.07, 1871: 69.24? "09.24" -> 69.24, 1872: 62.02.

Then "Rangp" -> "Range" then "48.0 51.0 46.0 40.0 43.5 53.0 46.0" - temperature range.

Then "Total Total during during the the Year. Teng." -> "Total during the Year." maybe for something else.

"C. J. WHARRY, M.n.. Superintendent." -> "C. J. WHARRY, M.D., Superintendent."

I'll reconstruct both tables.

Given the complexity, I'll produce a Markdown document with two tables: Table 12 (main) and a second table for yearly summary.

For Table 12, I'll define columns based on the header lines, merging multi-line headers. I'll use the corrected header names.

Let's list the header lines in order as they appear, but they seem to be arranged in a multi-row header. I'll interpret as:

Row 1: BAROMETER | FAHRENHEIT THERMOMETER | HYGROMETER | WIND | 1872

Row 2: Corrected to 82° Fahrenheit and reduced to Mean Sea Level. | Self-registering in Sun. | Dry Bulb. | Wet Bulb. | Max. Min. | In Shade. | Mean. | Max. Min. | Sun Max. Min. in Soil Bulb Bulb | Max. Min. in Grass, inches Vacuo. Exposed. | Deep. | Quarter (prevailing.) | Movement during 24 hours, in Miles. | Rain in Inches | DURING THE MONTH | No. of Days Having Rains | State of Weather | Average during the Month 9 A.M. | Average during the Month 3 P.M.

But that's too many columns. The data has 17 met columns + 2 wind + 3 rain/movement = 22. The header lines count: let's count distinct column headers from the list:

1. BAROMETER (maybe two sub-columns: 9am, 3pm)
2. FAHRENHEIT THERMOMETER (many sub-columns)
3. HYGROMETER (maybe Wet Bulb?)
4. WIND (two sub-columns: 9am, 3pm)
5. 1872 (year)
6. Corrected to 82°... (description for barometer)
7. Self registering in Sun (description for solar thermometer)
8. Dry Bulb.
9. Wet Bulb.
10. Max. Min. (for Dry Bulb?)
11. In Shade.
12. Mean.
13. Max. Min. (for Sun?)
14. Sun Min. in noil Bulb Bulb (Soil Bulb)
15. t in ex- Grass, inches Vacuo. posed. (Grass, Vacuo, Exposed)
16. deep.
17. Quarter (prevailing.) (Wind direction at 9am and 3pm)
18. Movement during 24 hours, in Miles.
19. Rain in Inches
20. DURING THE MONTH (section)
21. No. OF DAYS HAVING RAINS.
22. State of WEATHER.
23. Average during the Month. 9 A.M. 3 P.M. (two columns)

But the data doesn't have all these as separate numeric columns. The "Average during the Month 9 A.M. 3 P.M." might be the barometer averages? But barometer already has two columns. The annual mean includes barometer averages (30.01, 29.02). So those are the first two columns. Then the last two columns of the annual mean (before movement, rain, days) are 67.8 and 69.7? Actually annual mean 16th and 17th: 67.8, 69.7. Those could be "Average during the Month 9 A.M. and 3 P.M." for something else (maybe temperature). But the header says "Average during the Month. 9 A.M. 3 P.M." at the very end after State of Weather. In the data rows, after rain and days, there is weather description, not numbers. So maybe those two columns are not in the monthly rows but only in the annual mean? Unlikely.

Given the time, I'll produce a cleaned-up version of the OCR text in a markdown table with the columns as they appear in the data rows, using generic column names derived from the header. I'll include all 17 met columns, wind directions (2), movement, rain, days rain, and weather notes.

I'll name the 17 met columns as:

1. Barometer 9am (inches)
2. Barometer 3pm (inches)
3. Dry Bulb Max (°F)
4. Dry Bulb Min (°F)
5. Wet Bulb Max (°F)
6. Wet Bulb Min (°F)
7. In Shade Max (°F)
8. In Shade Min (°F)
9. Mean Temperature (°F)
10. Sun Max (°F)
11. Sun Min (°F)
12. Soil Bulb Max (°F)
13. Soil Bulb Min (°F)
14. Grass Max (°F)
15. Grass Min (°F)
16. Vacuo (inches?) / Exposed?
17. Deep Earth Temp (°F)

But from annual mean, column 16=67.8, column 17=69.7. Those are temperatures. So likely both are temperatures. Column 10=124 (Sun Max), column 11=100.8 (Sun Min). Column 12=65.9, 13=60.6 (Soil). Column 14=72.4, 15=75.0 (Grass). Column 16=67.8, 17=69.7 (maybe "Inches Vacuo" and "Exposed" but they are temps). Could be "In Vacuo" and "Exposed" thermometers. And "Deep" might be separate but not in annual mean? Actually annual mean has 17 met columns. The header mentions "deep." as separate. So maybe column 17 is Deep. But then Vacuo and Exposed are two columns? But we have only 17 met columns. Let's count header items after "Mean.": "Max. Min." (2), "Sun Min. in noil Bulb Bulb" (maybe 2 for Soil Bulb), "t in ex- Grass, 'inchies Vacuo. posed." (maybe 3: Grass Max, Grass Min, Vacuo, Exposed? but "t in ex-" could be "Max. Min. in Grass", "inches Vacuo", "Exposed"), "deep." (1). That's 2+2+3+1=8. Plus before Mean: Dry Bulb (2), Wet Bulb (2), In Shade (2), Mean (1) = 7. Total 15. Plus Barometer 2 = 17. Yes! So:

• Barometer: 2 cols (9am, 3pm)
• Dry Bulb: Max, Min (2)
• Wet Bulb: Max, Min (2)
• In Shade: Max, Min (2)
• Mean: (1) (maybe mean of dry bulb?)
• Sun: Max, Min (2) (Self-registering in Sun)
• Soil Bulb: Max, Min (2) (two bulbs? "Bulb Bulb" maybe two depths)
• Grass: Max, Min (2)
• Vacuo: (1) (inches of vacuum? maybe evaporation)
• Exposed: (1) (thermometer exposed)
• Deep: (1) (earth temperature at depth)

That's 2+2+2+2+1+2+2+2+1+1+1 = 18? Let's sum: Baro 2, Dry 2, Wet 2, Shade 2, Mean 1, Sun 2, Soil 2, Grass 2, Vacuo 1, Exposed 1, Deep 1 = 18. But we have 17 met columns in data. Maybe "Mean" is not a separate column but the mean of something else. Or "Vacuo" and "Exposed" are combined? Or "Soil Bulb Bulb" is only one column? The header "Sun Min. in noil Bulb Bulb" is weird.

Given the annual mean has 17 met columns, I'll stick to 17. I'll label them as per the header order:

1. Barometer 9am
2. Barometer 3pm
3. Dry Bulb Max
4. Dry Bulb Min
5. Wet Bulb Max
6. Wet Bulb Min
7. In Shade Max
8. In Shade Min
9. Mean
10. Sun Max
11. Sun Min
12. Soil Bulb Max
13. Soil Bulb Min
14. Grass Max
15. Grass Min
16. Vacuo (inches)
17. Deep Earth Temp (°F)

But column 16 in annual mean is 67.8, which is a temperature, not inches. Column 17 is 69.7. So maybe 16 is Exposed thermometer, 17 is Deep. And Vacuo is not a separate column? The header says "inches Vacuo." Could be the evaporation gauge reading in inches. But annual mean 16=67.8 inches? That's huge for evaporation. Unlikely. So probably all are temperatures.

Let's check January column 16: "54.2" (temperature), column 17: "56,0" -> 56.0. February column 16: "50.6", column 17: "53.6". March column 16: "61.0?" (GILK), column 17: "62.0". April column 16: "76.8", column 17: "71.0". May column 16: "71.8", column 17: "74.0". June column 16: "85.0", column 17: "79.00". July column 16: "86.3"? "863" -> 86.3, column 17: "78.0"? "78,0" -> 78.0, then "80.9" extra? July has "863 78,0 80.9" three numbers at end? Actually July: "82 8 863 78,0 80.9" -> maybe columns 14,15,16,17: 82.8, 86.3, 78.0, 80.9. August: "83.4 77.7 70.4" three numbers? August ends with "83.4 77.7 70.4". September: "71.9 74.4 75.1" three? October: "77.8 71.1 72.4" three. November: "72.0 63.8 65.0" three. December: "66.6 63.8 64.2" three. So each month seems to have three numbers at the end before wind? But earlier we thought 17 met columns. Let's count January met numbers before wind: 17 numbers. February: 17. March: 17. April: 16? May: many. June: 16? July: 18? August: 17? September: 16? October: 17? November: 17? December: 17. Annual mean: 17 met numbers (since last three are movement, rain, days). So 17 met columns.

But the last three of the 17 for each month: for January: 54.2, 56.0, (then wind). That's two numbers. Wait January has 17 numbers: indices 1-17. 16=54.2, 17=56.0. February: 16=50.6, 17=53.6. March: 16=61.0, 17=62.0. April: 15=76.8, 16=71.0 (only 16 numbers). May: let's parse May properly.

May row: "May, 20.4 29.79 81.0 645 83.4 76.0 78.3 81.4 81.8 130.104.3 | 73.2 78.5 77.9 BLA 71.8 74.0 SE & SW SE & SW 182 8.53 17 17 15 15 23 13 11 1 17 13 [R 17 12 18 12 19 19 +1 · " 11 17 13 [R 17 12 18 12 19 19 +1 · " This is garbled with extra numbers from weather? The "17 17 15 15 23 13 11 1 17 13 [R 17 12 18 12 19 19 +1" might be the "State of WEATHER" codes? Actually the original table likely has a column for each day of the month? No, "State of WEATHER" is descriptive. The numbers at the end of May seem to be from the weather column? The OCR has merged multiple lines.

Given the difficulty, I think the best is to present the table as a cleaned-up version of the OCR text, preserving the original layout as much as possible, correcting obvious OCR errors, and using markdown table with the columns as they appear in the header. I'll define the columns based on the header lines, even if some are merged.

I'll create a markdown table with the following columns (based on the header lines in order, but only those that appear as data columns):

• Month
• Barometer 9am (Corrected to 82°F, reduced to MSL)
• Barometer 3pm (Corrected to 82°F, reduced to MSL)
• Dry Bulb Max (°F)
• Dry Bulb Min (°F)
• Wet Bulb Max (°F)
• Wet Bulb Min (°F)
• In Shade Max (°F)
• In Shade Min (°F)
• Mean (°F)
• Sun Max (°F)
• Sun Min (°F)
• Soil Bulb Max (°F)
• Soil Bulb Min (°F)
• Grass Max (°F)
• Grass Min (°F)
• Vacuo (inches) / Exposed? (I'll label "Vacuo/Exposed")
• Deep Earth Temp (°F)
• Wind 9am (Quarter)
• Wind 3pm (Quarter)
• Movement (Miles)
• Rain (Inches)
• Days with Rain
• Weather Notes

But the data shows only 17 met columns, not 18. I'll combine Vacuo and Exposed into one? Or drop one. The header has "inches Vacuo. posed." maybe "inches Vacuo. Exposed." two columns. But annual mean has 17 met columns. Let's count the header items after "Mean.": "Max. Min." (2), "Sun Min. in noil Bulb Bulb" (maybe 2), "t in ex- Grass, 'inchies Vacuo. posed." (maybe 3), "deep." (1) = 8. Before Mean: "Dry Bulb." "Wet Bulb." "Max.! Max." "Min." "In Shude." "נוןות" "Mean." That's 7 items but some are labels. Actually "Dry Bulb." and "Wet Bulb." are labels for the next "Max. Min."? The header lines are not well separated.

Given the time, I'll produce a table with the 17 met columns as they appear in the data, using generic names Col1-Col17, but with corrected values. However, the user expects a proofread text with proper headers. I'll do my best to reconstruct the original table headers from the OCR header lines.

Let me write the corrected header lines as a single row in markdown, but it's too many columns. Maybe the original table had a multi-level header. In markdown, I can do a two-row header.

I'll create a markdown table with a header row for categories and a sub-header row for specific columns.

Categories:

• Barometer (2 cols)
• Fahrenheit Thermometer (15 cols?) but we have 15 thermometer columns? 17 total -2 baro =15.
• Hygrometer (maybe included in Wet Bulb)
• Wind (2 cols)
• Movement (1)
• Rain (1)
• Days with Rain (1)
• Weather (1)

But the "Average during the Month 9 A.M. 3 P.M." might be part of Barometer.

I'll design the table as follows:

Then fill data for each month, correcting numbers.

I'll need to parse each month's data correctly. Let's do that systematically.

I'll write a script in my mind to parse each line. But manually.

First, list the month lines as they appear in OCR:

1. January, 80.23 30.13 70.0 60.0 62.0 66.0 58.8 61.2 61.4 08. 75.6 53.7 67.6 58.5 GL.1 54.2 56,0 | E & NE | E & NE 190 0.08 2 Fine 12 days. Overcast 19 days. Fine 16 days. Overenst 15 days.

1. February, 30.23 30.14 68.0 43.5 60.4 62 4 55.9 58.7 69.1 101. 77.6 50.5 64.7 55.5 58.8 50.6 536E & NE|E & SE 176 0.66 14 17

1. March, 20.10 30.00 78.0 40.0 69.3 57.4 64.9 66.0 67.7 113. 88.0 55.2 59.6 64.5 67.4 GILK 62.0 E & NEE & SE 151 0.00 H

1. April, 80,00 20.03 844.5 62.0 77.6 70.8 73.4 70.6 70.6 126. 99.7 68.2 71.0 73.0 76.8 71.0 SE & |SE & SW. 135 0.09

1. May, 20.4 29.79 81.0 645 83.4 76.0 78.3 81.4 81.8 130.104.3 | 73.2 78.5 77.9 BLA 71.8 74.0 SE & SW SE & SW 182 8.53 17 17 15 15 23 13 11 1 17 13 [R 17 12 18 12 19 19 +1 · " 11 17 13 [R 17 12 18 12 19 19 +1 · "

1. June, 29.81 29.72 89.5 76.0 86.2 79.6 82.8 84.8 85.3 186. 109.1 76.3 79.0 81.9 85.0 7900 SW & SESW & SE 109 16.27 21

1. July, 220,20 29.73 89.0 77.0 $7.1 79.0 83.2 86.2 85.7 148, 118.1 70.5 79.2 82 8 863 78,0 80.9 [SW & SE│SW & SE 109 12.09 17 22

1. August...... 29.82 20.77 89.0 77.0 87.2 80.0 83.2 86.4 R5.8 145. │114.2 77.5 80.6 82.8 83.4 77.7 70.4 SW & SE|SW & SE 128 6.75 10 23

1. September, 29.04 20.87 80.0 74.0 83.9 74.8 80.0 82.2 82.7 139.115.8 78.4 77.3 FO 3 K1.9 74.4 75.1 E & NE E & NE 496 0.27 12 20 16 JG 8 10 13 17 אָן 1.3 · " + 22 + 14 " 19 11 ++ *

1. October, 30.03 29.91 85.0 69.0 70.4 78.1 75.7 78.2 78.0 123.108.4 GR.G 72.5 75.7 77.8 71.1 72.4 | B& NE│E & NE. 521 6.88 JU

1. November, 30.14 60.03 $0.0 59.0 74.2 60.4 60.0 72.8 72.0 123. | 108.0 62.0 66.8 69.6 72.0 63.8 65.0 N&XEN & NE 197 0.65 17 20 31 14 14 17 +3 19 " 21 4 19 + · 13

1. December...... 30.12 30.03 75,0 56.0 70.6 68.7 66.7 GO.8 68.7 114. 01.4 56.0 61.2 66.6 GR.4 63.8 64.2 ❘ NE & E│NE & E│ 288 0.40 20 13 13 + 11 14 M ++

1. Annual Mean,.. 30.01 29.02 82.1 62.7 70,7 69,8 72.7 75.3 70.4 124. | 100.8 65.9 60.6 72.4 75.0 67.8 69.7 223 62.92 107

Now, I'll correct each.

General corrections:

• Barometer: any 80.xx -> 30.xx, 20.xx -> 30.xx, 220,20 -> 29.20, 29.04 -> 29.94? Actually September: "29.04 20.87" -> 29.94 and 29.87? But "29.04" could be 29.94 (OCR misread 9 as 0). "20.87" -> 29.87. October: 30.03 29.91 good. November: 30.14 60.03 -> 30.14 30.03. December: 30.12 30.03 good. Annual: 30.01 29.02 (second should be 29.92? But 29.02 is given. Might be 29.92. But I'll keep as 29.02? The OCR says 29.02. Could be 29.92. But annual mean barometer 3pm 29.92 is plausible. I'll use 29.92? But the OCR says 29.02. I'll correct to 29.92? The header says "Corrected to 82° Fahrenheit and reduced to Mean Sea Level." The values around 30 inches. 29.02 is low. 29.92 is more likely. But I'll keep as 29.02? Actually the OCR for annual mean: "29.02". Could be "29.92" with '9' misread as '0'. I'll correct to 29.92.

• Temperatures: fix obvious: 844.5 -> 84.5, 645 -> 64.5, 130.104.3 -> 130.0 and 104.3 (two columns), GL.1 -> 61.1, GILK -> 61.0, BLA -> 71.8, 7900 -> 79.00, $7.1 -> 87.1, R5.8 -> 85.8, 145. │114.2 -> 145.0 and 114.2, 139.115.8 -> 139.0 and 115.8, FO 3 -> 70.3? Actually "FO 3" might be 70.3? But column 13? Let's see. K1.9 -> 81.9? GR.G -> 71.1? GR.4 -> 69.4? GO.8 -> 60.8? 01.4 -> 91.4? 536E -> 53.6, 70,7 -> 70.7, 69,8 -> 69.8.

• Wind directions: clean up: "E & NE | E & NE" -> 9am: E & NE, 3pm: E & NE. "E & NE|E & SE" -> 9am: E & NE, 3pm: E & SE. "E & NEE & SE" -> 9am: E & NE, 3pm: E & SE. "SE & |SE & SW." -> 9am: SE & E? Actually "SE & |SE & SW." maybe 9am: SE & E? But "SE &" then "SE & SW". Could be 9am: SE & E, 3pm: SE & SW. But "SE & |SE & SW." I'll interpret as 9am: SE & E, 3pm: SE & SW. "SE & SW SE & SW" -> both SE & SW. "SW & SESW & SE" -> 9am: SW & SE, 3pm: SW & SE. "SW & SE│SW & SE" -> both SW & SE. "SW & SE|SW & SE" same. "E & NE E & NE" -> both E & NE. "B& NE│E & NE." -> 9am: N & NE? "B& NE" maybe "N & NE". 3pm: E & NE. "N&XEN & NE" -> 9am: N & NE, 3pm: N & NE? "NE & E│NE & E│" -> both NE & E.

• Movement: numbers like 190, 176, 151, 135, 182, 109, 109, 128, 496, 521, 197, 288, 223 (annual).

• Rain: 0.08, 0.66, 0.00, 0.09, 8.53, 16.27, 12.09, 6.75, 0.27, 6.88, 0.65, 0.40, 62.92 (annual).

• Days with rain: 2, 14, H? March has "H" maybe 0? But "0.00" rain, days maybe 0? But "H" could be "0"? Or "17"? The line ends with "H". Actually March: "151 0.00 H" -> movement 151, rain 0.00, days rain? "H" might be "0" or "17"? But the column "No. OF DAYS HAVING RAINS." For March, maybe 0 days? But "H" is not a number. Could be "0" misread. I'll put 0. April: "135 0.09" no days rain shown? Maybe missing. May: "182 8.53 17" -> days 17. June: "109 16.27 21" -> days 21. July: "109 12.09 17" -> days 17? But "17 22" at end? Actually July: "109 12.09 17 22" maybe days 17, then weather code 22? August: "128 6.75 10 23" -> days 10. September: "496 0.27 12 20" -> days 12. October: "521 6.88 JU" -> days? "JU" maybe 17? November: "197 0.65 17 20" -> days 17. December: "288 0.40 20 13" -> days 20. Annual: "223 62.92 107" -> days 107.

• Weather notes: I'll include the descriptive text for each month as in OCR, cleaned.

Now, I'll parse each month into 17 met columns. But the number of met columns varies. I'll align by the annual mean which has 17 met columns. So each month should have 17 met values. Let's extract 17 values for each month from the OCR string before wind.

I'll write a parsing routine manually.

For each month, split the string after month name by spaces, but some numbers have commas, pipes, etc. I'll go month by month.

January: "80.23 30.13 70.0 60.0 62.0 66.0 58.8 61.2 61.4 08. 75.6 53.7 67.6 58.5 GL.1 54.2 56,0"

That's 17 tokens if we consider "08." as one, "GL.1" as one, "56,0" as one. Good.

Corrected:

1. 30.23
2. 30.13
3. 70.0
4. 60.0
5. 62.0
6. 66.0
7. 58.8
8. 61.2
9. 61.4
10. 108.0? (08. -> 108.0? But annual mean col10=124. January likely lower. 108 plausible. Could be 98.0? But "08." with leading zero? Might be 108.0 because OCR missed '1'. I'll use 108.0)
11. 75.6
12. 53.7
13. 67.6
14. 58.5
15. 61.1 (GL.1)
16. 54.2
17. 56.0

February: "30.23 30.14 68.0 43.5 60.4 62 4 55.9 58.7 69.1 101. 77.6 50.5 64.7 55.5 58.8 50.6 536E"

Tokens: 30.23, 30.14, 68.0, 43.5, 60.4, 62.4 (62 4), 55.9, 58.7, 69.1, 101., 77.6, 50.5, 64.7, 55.5, 58.8, 50.6, 53.6 (536E). That's 17.

Corrected:

1. 30.23
2. 30.14
3. 68.0
4. 43.5
5. 60.4
6. 62.4
7. 55.9
8. 58.7
9. 69.1
10. 101.0
11. 77.6
12. 50.5
13. 64.7
14. 55.5
15. 58.8
16. 50.6
17. 53.6

March: "20.10 30.00 78.0 40.0 69.3 57.4 64.9 66.0 67.7 113. 88.0 55.2 59.6 64.5 67.4 GILK 62.0"

Tokens: 20.10->30.10, 30.00, 78.0, 40.0, 69.3, 57.4, 64.9, 66.0, 67.7, 113., 88.0, 55.2, 59.6, 64.5, 67.4, GILK->61.0, 62.0. That's 17.

Corrected:

1. 30.10
2. 30.00
3. 78.0
4. 40.0
5. 69.3
6. 57.4
7. 64.9
8. 66.0
9. 67.7
10. 113.0
11. 88.0
12. 55.2
13. 59.6
14. 64.5
15. 67.4
16. 61.0
17. 62.0

April: "80,00 20.03 844.5 62.0 77.6 70.8 73.4 70.6 70.6 126. 99.7 68.2 71.0 73.0 76.8 71.0"

Tokens: 80,00->30.00, 20.03->30.03, 844.5->84.5, 62.0, 77.6, 70.8, 73.4, 70.6, 70.6, 126., 99.7, 68.2, 71.0, 73.0, 76.8, 71.0. That's 16 tokens. Missing one? Annual mean has 17. Perhaps there is a token missing between 70.6 and 126? Or "70.6 70.6" are two columns (In Shade Max, Min), then Mean, then Sun Max, Sun Min, etc. April has 16. Let's count expected: 17. Maybe "126." is Sun Max, "99.7" Sun Min, "68.2" Soil Max, "71.0" Soil Min, "73.0" Grass Max, "76.8" Grass Min, "71.0" Vacuo/Deep. That's 7 after Mean. Before Mean: Baro2, Dry2, Wet2, Shade2 = 8, plus Mean =9, total 16? Actually 2+2+2+2+1=9, plus 7=16. So 16 met columns? But annual mean has 17. Let's recount annual mean met columns: 30.01, 29.02, 82.1, 62.7, 70.7, 69.8, 72.7, 75.3, 70.4, 124., 100.8, 65.9, 60.6, 72.4, 75.0, 67.8, 69.7. That's 17. So there are 17. April has 16. Maybe April missing one column? Could be "Mean" is not separate? But annual mean has a value 70.4 at position 9. April position 9 is 70.6? Actually April tokens: 1:30.00, 2:30.03, 3:84.5, 4:62.0, 5:77.6, 6:70.8, 7:73.4, 8:70.6, 9:70.6, 10:126., 11:99.7, 12:68.2, 13:71.0, 14:73.0, 15:76.8, 16:71.0. So 16. If we insert a Mean column after In