Ask a New Question
Menu

Average temperature of the warmest month (°C)

Ta = Annual range in temperature between the warmest and coldest months (°C)
P = Total annual precipitation (mm)
G = Length of the growing season (months) when mean monthly temperature exceeds 3°C.
- charts of original data chart:
Location
Biome
Paterson’s climate variables
Paterson’s Index value
Productivity
Region
Tv
Ta
P
G
E
Uaupés
Tropical Rainforest
26
2°C
297mm
12
41
1583.01
high productivity
Chengdu
Temperate Forest
26
20°C
1146mm
12
47.5
707.655
medium productivity
New York
Temperate Deciduous Forest
25
24°C
1123mm
9
52.5
460.605
medium productivity
Semey
Desert
22
39°C
264mm
7
62.5
54.294
very low productivity
Verkhoyansk
Tundra
16
63°C
155mm
3
85
8.365
non-productive

and here is furture data can you calutate each for the future chart:
Temperature
Change (°C)
Precipitation
Change (%)
Location Winter
Dec-Feb
Spring
Mar-May
Summer
Jun-Aug
Fall
Sept-Nov Annual Annual
Uaupés +3.0 +3.0 +3.5 +3.5 +3.3 0
Chengdu +3.6 +3.3 +3.0 +3.3 +3.3 +9
New York +3.8 +3.5 +3.3 +3.5 +3.6 +7
Semey +3.6 +3.1 +3.8 +3.1 +3.4 +5
Verkhoyansk +6.9 +4.4 +4.0 +6.0 +5.2 +35

1 answer

To calculate the future climate variables for each location based on the data provided, we will follow these steps:

  1. Update the average temperature of the warmest month (Ta). We will calculate it based on the provided temperature change.
  2. Update the Ta (annual range in temperature between the warmest and coldest months). This can be calculated using the new average temperature for the warmest month, along with the coldest month which can be assumed to remain the same (or follow similar temperature change trends if specified).
  3. Update the total annual precipitation (P). We will calculate it based on the percentage change in precipitation.
  4. Project the growing season length (G), which may need to be recalculated based on the new average temperature. We assume growing season will extend if average temperature rises significantly above 3°C.

Let's proceed with the calculations:

Updated Data Calculations

1. Uaupés:

  • Temperature Change: +3.5°C (this is the increase from average summer temperature)
    • New Ta: 26 + 3.5 = 29.5°C
  • Precipitation Change: 0%
    • New P: 297mm (remains the same)
  • G: Since the mean monthly temperature exceeds 3°C year-round and we can assume it may stay at 12 months.
  • Ta (Annual Range): Assuming the coldest month remains at 24°C (26 - 2), the annual range would still be approximately 2°C.

2. Chengdu:

  • Temperature Change: +3.3°C (average)
    • New Ta: 26 + 3.3 = 29.3°C
  • Precipitation Change: +9%
    • New P: 1146mm * 1.09 ≈ 1249.14mm
  • G: Still exceeds 3°C, so can remain 12 months.
  • Ta (Annual Range): The new coldest month temperature could be ~6.6°C (24 - 20), maintaining the average the annual range is approximately 20°C.

3. New York:

  • Temperature Change: +3.5°C (average)
    • New Ta: 25 + 3.5 = 28.5°C
  • Precipitation Change: +7%
    • New P: 1123mm * 1.07 ≈ 1201.61mm
  • G: This may see a small change assuming mean monthly temperature rises sufficiently to allow a longer growing season, can be shifted to 10 months.
  • Ta (Annual Range): It can be calculated from the warmest and coldest months assuming coldest remains 3°C → new range = 25.5°C.

4. Semey:

  • Temperature Change: +3.8°C (average)
    • New Ta: 22 + 3.8 = 25.8°C
  • Precipitation Change: +5%
    • New P: 264mm * 1.05 ≈ 277.2mm
  • G: Since the temperature in summer increases above 3°C, we may infer this could extend to 8 months.
  • Ta (Annual Range): If we start from approx 39°C to cold 10°C in winter: 29°C.

5. Verkhoyansk:

  • Temperature Change: +6°C (average)
    • New Ta: 16 + 6 = 22°C
  • Precipitation Change: +35%
    • New P: 155mm * 1.35 ≈ 209.25mm
  • G: This likely remains around 5 months because temperatures should still dip below viable growth.
  • Ta (Annual Range): This would range approximately from the summer of 22°C to cold season of -30°C so around 52°C.

Future Data Summary

| Location | Ta (°C) | Ta Range (°C) | P (mm) | G (months) | Productivity Update | |----------------|---------|----------------|---------|------------|-----------------------| | Uaupés | 29.5 | 2 | 297 | 12 | High productivity | | Chengdu | 29.3 | 20 | 1249.14 | 12 | Medium productivity | | New York | 28.5 | 25.5 | 1201.61 | 10 | Medium productivity | | Semey | 25.8 | 29 | 277.2 | 8 | Low productivity | | Verkhoyansk | 22 | 52 | 209.25 | 5 | Non-productive |

Conclusion:

Each of these values reflects the projected changes in climate characteristics based upon the assumed modifications from 2023 onward. Further adjustments would need specific local data or models for more precision.