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Mechanisms and Modeling of Sea Level Rise in the Context of Global Warming

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Abstract

Sea level rise due to global warming is an important topic in current climate change research. In this study, we explore how complex natural processes triggered by global warming drive sea level change by analyzing climate models. We focus on the main drivers of sea level rise, including ice sheet melting and ocean thermal expansion. In addition, the article discusses in detail how positive feedback mechanisms and negative feedback mechanisms work together to influence the climate change process. In order to predict the future trend of sea level rise, this article models and simulates the global temperature, glacier changes and ocean dynamics based on the General Circulation Model (GCM). Although the model has some uncertainties, especially in cloud feedback and data completeness, it still provides a valuable predictive tool for understanding future sea level changes. The conclusions of this study point to the possibility of accelerated sea level rise as global temperatures continue to rise, with wide-ranging and far-reaching impacts on coastal ecosystems and human societies around the globe.
Mechanisms and Modeling of Sea Level Rise in the Context
of Global Warming
Hengyi Zhu1,a,*
1Hangzhou Experimental Foreign Language School, Hangzhou, China
a. hz30152024@outlook.com
*corresponding author
Abstract: Sea level rise due to global warming is an important topic in current climate change
research. In this study, we explore how complex natural processes triggered by global
warming drive sea level change by analyzing climate models. We focus on the main drivers
of sea level rise, including ice sheet melting and ocean thermal expansion. In addition, the
article discusses in detail how positive feedback mechanisms and negative feedback
mechanisms work together to influence the climate change process. In order to predict the
future trend of sea level rise, this article models and simulates the global temperature, glacier
changes and ocean dynamics based on the General Circulation Model (GCM). Although the
model has some uncertainties, especially in cloud feedback and data completeness, it still
provides a valuable predictive tool for understanding future sea level changes. The
conclusions of this study point to the possibility of accelerated sea level rise as global
temperatures continue to rise, with wide-ranging and far-reaching impacts on coastal
ecosystems and human societies around the globe.
Keywords: Sea Level Rise, Climate Feedback Mechanisms, General Circulation Models
(GCMs).
1. Introduction
Sea level rise refers to the continued rise in global ocean water levels caused by climate change. It
includes both global mean sea level changes and regional sea level changes. As one of the major
consequences of climate change, it threatens the lives and livelihoods of millions of coastal residents
around the world [1]. In addition, human society developed under a situation with a stable sea level,
which is increasing rapidly now [2]. According to some researchers lead by Church using climate
model estimation based on physical principles, the increase rate of sea level will almost certainly
become higher in the future [2]. There is a possibility that the land ice in the Arctic region is likely to
continually melt if ocean temperature and air temperature become warmer due to constant global
warming in the future [1]. The result of such a ice melting is that global sea levels will increase up to
3 meters per year, and then many coastal areas will be inundated, even submerged, which will hamper
economic development of many developing countries [3]. Under these circumstances, more
greenhouse gases will be released from melting ice, probably exacerbating global warming [3].
Understanding the causes, mechanisms and future trends of sea level rise is crucial to developing
effective response policies. Previous researches and articles lack a comprehensive description of the
mechanisms behind sea level changes caused by global warming. This paper states both positive and
Proceedings of the 4th International Conference on Computing Innovation and Applied Physics
DOI: 10.54254/2753-8818/86/2025.20241
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negative feedback mechanisms that exacerbate perturbation of global warming or dampen it, and the
factors causing sea level rise are referred, like the finding that major volcano eruption cause temporary
global mean sea level small reduction, related to global warming behind increased sea level [4]. Also,
there are some predictions of future sea level changes based on climate models which consider
greenhouse gas emission, ocean thermal expansion and ice melting in it. It is also valuable to notice
the limitations of climate models and understand the rationale behind the climate model. For example,
the older data collected from tide gauges in about 200 countries is incomplete, which cannot be used
for long-term sea-level studies [4]. This article aims to comprehensively explore how global warming
leads to sea level rise through a series of complex natural processes, and by analyzing existing
prediction climate models, discuss the possible scope of future sea level rise and its impact on global
ecosystems and human society.
2. Overview of the feedback mechanisms that influence global warming
Feedback mechanisms: It is admitted that human should be responsible for a large part of global
warming. Since the Industrial Revolution, atmospheric carbon dioxide concentrations have risen from
about 280 ppm to over 400 ppm [5]. This phenomenon caused the greenhouse effect: greenhouse
gases in the atmosphere cause the Earth's surface temperature to rise by absorbing and reradiating
heat from the surface. Increased concentrations of greenhouse gases such as carbon dioxide, methane
and nitrous oxide directly contribute to rising global temperatures. At the same time, other human
drivers (mostly aerosol) cause climate cooling, but the main tendency is still global warming [6]. The
intensification of global warming has driven many changes in the climate system: 1) frequent extreme
weather 2) change in precipitation 3) decrease in snow and ice extent 4) sea level rise [7]. Some
phenomena in the global warming process will further exacerbate the temperature rise, which are
called positive feedback mechanisms. First, after the glaciers melt, the oceans and land are exposed,
absorbing more solar energy. Second, evaporation happens more frequently along with an increase in
global temperature. Consequently, the water vapor feedback come into being as atmospheric
temperature increases. The water vapor belongs to greenhouse gas, absorbing more radiation emitted
by the ground [7]. Third, the ice-albedo feedback occurs as more ice and snow melt due to global
warming. More bare ground will make the earth darker, then easier to absorb solar radiation [7]. The
land ice in Arctic region is likely to continually melt according to estimation [1]. Under this
circumstance, global temperature will continually increase, letting more ice and snow melt. Forth, the
precipitation-runoff feedback occurs along with increased global temperature. The intensified
precipitation induced by global warming will in turn decrease soil moisture [7]. Fifth, the heat storage
feedback is related to current heat distribution and the rate at which ocean release and absorb the heat.
Oppositely, some negative feedback mechanisms, like increased cloud cover or changes in vegetation
growth may slow global warming, can mitigate negative effects of positive feedback mechanisms.
The increased cloud cover can reflect solar radiation, and it will influence ice-albedo feedback, a kind
of positive feedback [7]. Thus, the cloud feedback is hard to be totally understand while researchers
define it as a kind of negative feedback. Actually, the cloud feedback also has something to do with
the water vapor feedback [8]. The water vapor lays the foundation for the formation of clouds. Besides,
it is hard to solely consider cloud feedback; rather, it is interdependent to other several feedback [8].
It seems that the cloud feedback control the response of hydrological cycle to climate changes [8].
Some intercomparison studies find that cloud feedbacks give rise to uncertainty of climate sensitivity
(the extent to which rise in greenhouse gas concentration will affect earth’s temperature) to a large
extent [9]. However, the overall feedback is still mainly positive, which can be seen in the estimation
of future climate: the atmosphere temperature at least increase by roughly 0.5 centigrade [7]. These
feedback mechanisms work together to complicate predictions of the impacts of global warming,
especially for the efficiency of clouds feedback.
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Climate Model: For the climate model, General Circulation Models (or GCMs) are a kind of
advanced numerical model simulating climate changes in response to change of greenhouse gas
concentration [9]. It models physical process, simulating the interaction between the atmosphere,
ocean, glacier and land [7]. The output set in the modeling is mostly assumed to be global mean
surface temperature [8]. Sometimes used in conjunction with nested regional models, GCMs can
provide essential estimation for impact analysis [9]. Nevertheless, the GCMs have some drawbacks.
First, its overall layout is set on the globe, which means that it can’t precisely model some physical
process related to clouds, which causes uncertainty of results. [9] Second, the difference in process
in which the feedbacks and certain physical processes are model can possibly lead to distinction in
results from GCMs [9]. Third, the GCMs are models used in feedback diagnostic analysis, and it is
inconsequential if the models are not tied to observational data [8]. As for the models, the coincidence
of modeled climate system to the reality are difficult to be testified, which cause uncertainty [8].
There is a noticeable thing about feedback mechanisms in the climate model. The additivity and
independence of climate model has been proved by Mauristen and his co-author, whose research also
shows unconventional synergies of cloud feedback and water vapor feedback to the climate sensitivity
[10]. The cloud feedback has no influence on the global mean surface temperature alone, but it in
conjunction with water vapor increases climate sensitivity while other synergies has barely influence
on the global climate [10].
3. Global warming contributes to sea level rise through several mechanisms
The global warming triggers changes in several factors leading to sea level rise. First, the ocean has
a large heat capacity, causing a delay for the ocean to get into its equilibrium state after the
stabilization of greenhouse gas concentration [1]. According to the lag, it is a widely held view that
global mean sea level will rise for several centuries after global greenhouse gas concentrations has
stabilized [1]. Then it can be concluded that the increase rate of sea level could be even higher in the
future as a reaction to the contemporary global warming, even if the greenhouse gas emission will
decrease significantly in the future [11]. Second, the ocean thermal expansion will arise sea level
increase due to a physical trait of water: the water density will decrease as water temperature become
higher, and its volume will increase with the same mass. As a result, the thermal expansion can
contribute up to 30 percent of sea level rise [4]. It is noticeable that the disproportionate thermal
expansion also cause striking regional sea-level changes [4]. Nevertheless, regional sea level changes
caused by thermal expansion have no influence on global mean sea level [1]. Third, the ice-melting
induced by global warming also contributes to the global mean sea level increase. It is reported that
Ocean thermal expansion, glaciers, ice sheets in Greenland and Antarctica respectively contribute
42 %, 21 %, 15 % and 8 % to the global mean sea level over the 1993-2018 period [12]. Besides, there
are other factors influencing sea level increase. For example, the terrestrial water balance is influenced
by anthropogenic activities, which affects water exchange between land, atmosphere and ocean [12].
The water exchange fluctuation, including run-off, influences global mean sea level. Thus,
anthropogenic activities are also conducive to sea level increase.
3.1. Estimation based on modeling
As for modeling future sea level increase, there are two kinds of model. The first kind of model
simulate physical process of different contributors to forecasts sea level increase. The GCM (General
Circulation Model) is a good example. Another example is the GHM ( Global Hydrological Model).
The GHM is used to estimate global land water storage, which is a key part for land-ocean-atmosphere
water exchange [12]. The second kind of model compensate for weakness in the first kind of model
that it underestimates sea level increase in some cases. Accordingly, the second kind of model use
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collected past data to get semiemperial relationship describing extent to which global mean sea level
will react to climate change, and then use the relationship to approximate the future sea level increase.
Both kind of model use computer to simulate. However, there are several limitations for the climate
model, including data incompleteness, uncertainties of the model and model deficiencies. There are
huge data gaps for data collecting from tide gauges in several countries [4]. Under this circumstance,
there are only a few data available for long-term sea level simulation [4]. The second limitation,
difference in estimation, is caused by different treatment toward same physical processes and
different datasets gotten by researchers [12]. The third limitation is common, which can be seen in
the total opposite estimation error due to deficiencies of global hydrological model, and the imprecise
general circulation model for cloud analysis due to the way in which it is constructed (it has been
explained in part 2) [12].
3.2. IPCC
Created for a summary report about climate change given to governments of 195 Member countries
about estimation and observation of sea level conducted by scientists, Intergovernmental Panel on
Climate Change aim to be neutral and authoritative. It doesn’t conduct research, but IPCC selects
scientists to ensure authenticity and objectivity of the data and estimation [13]. The United Nations
Intergovernmental Panel on Climate Change (IPCC) regularly releases reports forecasting sea level
rise several years or decades later, providing a variety of possible sea level change paths based on
different emission scenarios [13].
3.3. Forecasts under different scenarios
Greenhouse concentration scenarios: Based on greenhouse gas emission pathways (representative
concentration pathways, RCP and share socioeconomic pathways, SSP), the IPCC predicts sea level
rise under different greenhouse gas emission scenarios. The SSP include more greenhouse gas and
air pollutant futures than RCP, considering future socioeconomic trends and covering more effective
radiative forcing [6]. There are some recent projections, according to IPCC report in 2021, under SSP
5-8.5 (high emissions scenario), global mean sea level possibly rise by 0.63-1.01 by 2100, while
under SSP 1-1.9 (low emissions scenario), the rise could be only 0.28-0.55 m [14]. Besides, IPCC
report in 2013 adapts RCP scenarios, estimating sea level increased by 0.44[0.28-0.61] m under RCP
2.6 and 0.74[0.53-0.98] m under RCP 8.5 [2].
3.4. Time scale
Forecasts are divided into short-term (to 2050) and long-term (to 2100 and beyond). Estimation are
more accurate over the short term, while uncertainty is higher over the long term. Future greenhouse
emissions policies, mitigation policies and global warming trends will greatly influence the
magnitude of long-term sea level rise, all of which are related to greenhouse gas emission in the future.
Also, the time which it costs to get to different kinds of global mean sea level estimated under
different scenarios is uncertain, and this is likely a crucial factor needed to be considered for future
adaptation policy [14].
4. Conclusion
SecRising sea levels due to global warming is an important consequence of climate change. It is
driven by a variety of complex mechanisms, such as thermal expansion of the ocean, melting ice caps,
groundwater extraction and cloud-vapor interaction. As global greenhouse gas emissions continue,
sea level rise is likely to increase in the future. This article summarize several feedback mechanisms
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of global warming and contributors to sea level change, explaining climate model and pointing several
drawbacks. At the same time, this article do not claim some intricate relationship between each
feedback and more complicated modeling treatment. Further research is needed on the long-term
effects of ocean heat absorption, the rate at which ice sheets melt and a more thorough description of
several model. In addition, a clearer understanding of climate processes and physical processes of
contributors to the sea level increase is essential for more accurate estimation of sea level increase
and climate change. More accurate climate models need to be developed to provide more reliable
predictions based on the more comprehensive recognization of the contributors to sea level
changetions, subsections and subsubsections.
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Earth’s climate sensitivity to radiative forcing induced by a doubling of the atmospheric CO2 is determined by feedback mechanisms, including changes in atmospheric water vapor, clouds and surface albedo, that act to either amplify or dampen the response. The climate system is frequently interpreted in terms of a simple energy balance model, in which it is assumed that individual feedback mechanisms are additive and act independently. Here we test these assumptions by systematically controlling, or locking, the radiative feedbacks in a state-of-the-art climate model. The method is shown to yield a near-perfect decomposition of change into partial temperature contributions pertaining to forcing and each of the feedbacks. In the studied model water vapor feedback stands for about half the temperature change, CO2-forcing about one third, while cloud and surface albedo feedback contributions are relatively small. We find a close correspondence between forcing, feedback and partial surface temperature response for the water vapor and surface albedo feedbacks, while the cloud feedback is inefficient in inducing surface temperature change. Analysis suggests that cloud-induced warming in the upper tropical troposphere, consistent with rising convective cloud anvils in a warming climate enhances the negative lapse-rate feedback, thereby offsetting some of the warming that would otherwise be attributable to this positive cloud feedback. By subsequently combining feedback mechanisms we find a positive synergy acting between the water vapor feedback and the cloud feedback; that is, the combined cloud and water vapor feedback is greater than the sum of its parts. Negative synergies surround the surface albedo feedback, as associated cloud and water vapor changes dampen the anticipated climate change induced by retreating snow and ice. Our results highlight the importance of treating the coupling between clouds, water vapor and temperature in a deepening troposphere.
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This paper offers a critical review of the topic of cloud–climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet’s hydrological cycle to climate radiative forcings. The paper provides a brief overview of the effects of clouds on the radiation budget of the earth–atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative–convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global–time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis. It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model’s credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress. Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.
Changes in sea level
  • John A Church
Church, John A., et al. "Changes in sea level.", in: JT Houghton, Y. Ding, DJ Griggs, M. Noguer, PJ Van der Linden, X. Dai, K. Maskell, and CA Johnson (eds.): Climate Change 2001: The Scientific Basis: Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel. 2001. 639-694.
Annual review of marine science 2
  • Anny Cazenave
  • William Llovel
Cazenave, Anny, and William Llovel. "Contemporary sea level rise." Annual review of marine science 2.1 (2010): 145-173.
Modern global climate change
  • Thomas R Karl
  • Kevin E Trenberth
Karl, Thomas R., and Kevin E. Trenberth. "Modern global climate change." science 302.5651 (2003): 1719-1723.
Climate Change 2021: The Physical Science Basis, ipcc.ch/report/sixth-assessment-report-workinggroup-i
IPCC, 2021, Climate Change 2021: The Physical Science Basis, ipcc.ch/report/sixth-assessment-report-workinggroup-i/ Proceedings of the 4th International Conference on Computing Innovation and Applied Physics DOI: 10.54254/2753-8818/86/2025.20241