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Chapter II Evidence for Global Climate Change

evidence. For meteorological station observation data, instrument precision is the primary-
considerationMetrics. High-precision instruments such as thermometers, barometers, and
rain gauges can obtain more accurate data on temperature, air pressure, and precipitation.
For instance, when measuring air temperature, instruments with ±0.1°C precision can cap-
ture subtle temperature variations more precisely compared to those with ±0.5°C accuracy,
providing more reliable data support for climate change research. Even a 0.4°C precision
discrepancy may lead to significant deviations in assessing temperature trends during long-
term climate monitoring. Calibration frequency should not be overlooked either, as regular
instrument calibration ensures long-term stability in measurement accuracy. If a meteorolog-
ical station’sanemometers over extended periodsIf left uncalibrated, it may lead to significant
deviations between measured wind speed and actual wind speed, thereby affecting the accu-
racy of wind-related climate change research. Assuming the anemometer’s error reaches 5 m/
s, this could severely misguide climate change studies driven by wind field variations, such
as typhoon track prediction and wind energy resource assessment. Data consistency is equal-
ly crucial. Measurements from different weather stations and across different time periods
at the same station should maintain logical coherence. If two adjacent stations show inexpli-
cably large temperature differences during similar timeframes after excluding geographical
factors, the reliability of such data becomes questionable. For instance, two stations 50 kilo-
meters apart with similar terrainMeteorological stations with similar characteristics, showing
a temperature difference exceeding 10°C at the same moment, highly likely indicate data
issues with one or both stations. For satellite data, radiation calibration accuracy determines
the precision of satellite sensors’ measurement of Earth’s surface radiant energy. Satellites
with high radiation calibration accuracy can more accurately monitor parameters like surface
temperature and vegetation indices. For instance, thermal infrared satellites after high-pre-
cision radiation calibration can precisely measure global surface temperature distribution,
providing reliable data for studying global temperature changes. Atmospheric correction
accuracy serves to eliminate atmospheric interference with satellite observation signals,
ensuring data authenticity in reflecting Earth’s surface conditions. Insufficient atmospheric
correction accuracy may cause deviations in satellite-observed cloud cover and aerosol con-
centration data, compromising studies on atmospheric component changes in climate change.
For example, if atmospheric correction errors cause 20% deviation in aerosol concentration
measurements, this would significantly distort research on atmospheric radiation balance and
climate change feedback mechanisms.
(2) Data Representativeness Indicators
The representativeness of data directly determines whether climate change conclusions
drawn from these data can authentically reflect the overall situation. In terms of spatial rep-
resentativeness, the distribution density of meteorological stations significantly impacts data
representativeness. In densely populated urban areas, the relatively dense distribution of me-
teorological stations can effectively reflect urban climate characteristics; however, in remote

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