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Global Climate Change and Its Impacts

species over the past 20 years, the model’s computational power reveals that the region has
lost 10 bird species compared to its baseline. This quantified outcome serves as a resounding
alarm, starkly exposing the long-term cumulative losses inflicted on biodiversity by climate
change. It warns that climate change is silently eroding the foundational diversity of Earth’s
ecosystems, and without prompt implementation of effective countermeasures, this process
will trigger a series of irreversible ecological disasters.
To further enhance the accuracy and reliability of the cumulative sum model in quanti-
fying the long-term cumulative effects of climate change, researchers continue to optimize
and improve the model. On one hand, they incorporate more climate change-related influenc-
ing factors, such as changes in atmospheric circulation patterns, adjustments in ocean heat
transport, and feedback mechanisms from terrestrial ecosystems, integrating these elements
into the model’s computational framework to enable more comprehensive and realistic re-
flection of the complex processes of climate change. On the other hand, by combining with
other advanced scientific technologies such as remote sensing monitoring and Geographic
Information System (GIS) technology, they obtain richer and more accurate spatial data,
thereby achieving detailed simulation and analysis of the long-term cumulative effects of
climate change across spatial dimensions. For instance, remote sensing technology enables
real-time acquisition of vegetation cover changes and land use type alterations across large
areas. Integrating this information with the cumulative sum model allows for in-depth in-
vestigation of the spatial distribution characteristics and evolutionary patterns of climate
change’s long-term cumulative impacts on terrestrial ecosystems.
(3) Integration of Spatial Analysis in Extended Applications
In addition to the two core methodologies of time series analysis and the Cumulative
Sum (CUSUM) model, researchers have innovatively incorporated spatial analysis tech-
niques to achieve organic integration of temporal and spatial dimensions for more compre-
hensive identification and quantification of long-term cumulative climate change effects.
When studying the cumulative effects of regional climate warming, the approach now ex-
tends beyond mere time series data analysis. Leveraging the powerful spatial analysis capa-
bilities of Geographic Information System (GIS) technology, researchers conduct in-depth
examinations of spatial variations in temperature increases across different regions and their
cumulative patterns over extended temporal scales.
First, by collecting and organizing long-term temperature data from different regions,
GIS technology is utilized to visually present these data in the form of maps. On the maps,
different colors, contour lines, or symbols are used to represent temperature changes in dif-
ferent regions, enabling researchers to visually observe the spatial distribution patterns of
temperature rise. Subsequently, by applying time series analysis methods, the temperature
data of each region is individually analyzed to obtain the temperature trends over time for
each region andcumulative increase magnitudes. On this basis, the cumulative sum model is
used to accumulate the annual temperature change values of each region, obtaining the cu-

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