Most of the research has focused on the enhancement of Typhoon Hagibis due to climate change, examining its impacts on precipitation, flooding in the Chikuma River Basin and Arakawa Basi
T HE NECESSITY OF THE RESEARCH
On October 4, the Japan Meteorological Agency identified a tropical depression at latitude 15.7 and longitude 164.4, leading to the issuance of a Typhoon Hagibis warning due to favorable conditions for cyclone development From October 11 to 13, Typhoon Hagibis impacted central, eastern, and northern Japan, dissipating on October 14 at 18:00 UTC The typhoon exacerbated the destruction caused by Typhoon Faxai in Chiba Prefecture, affecting 15 prefectures and triggering heavy rainfall alerts The disaster resulted in 86 fatalities, three missing persons, nearly 500 injuries, and estimated damages of around $400 billion, marking it as one of the most severe climate disasters in recent history.
Extreme climate events are increasingly frequent and intense, with the Sixth Assessment Report (AR6) confirming that human-induced greenhouse gas emissions have significantly amplified the occurrence and severity of these events, especially those associated with temperature extremes (IPCC, 2023) The Fifth Assessment Report (AR5) also acknowledged the anthropogenic influence on extreme climate occurrences, highlighting a clear connection between observed changes and human activities.
2 human influence and the strengthening of tropical cyclones and extreme precipitation since the findings of AR5 (IPCC, 2023)
Research on Typhoon Hagibis highlights the link between its intensification and climate change, emphasizing the need to understand the consequences such as heavy rainfall, river flooding, and landslides This understanding is vital for creating effective mitigation and adaptation strategies, as well as for developing resilient policies, building codes, and socio-economic measures that enhance resilience against the increasing threats posed by intensified typhoons.
The eastern coast of Japan faces a heightened risk of flooding during heavy rainfall events, particularly from typhoons and storms, due to the prevalence of cities situated on floodplains Accurate forecasting is essential for effective flood mitigation and adaptation strategies, which involve simulating extreme weather events like typhoons Recent research has primarily concentrated on the intensified effects of Typhoon Hagibis linked to climate change, analyzing its influence on precipitation and flooding in the Chikuma River Basin and Arakawa Basin, as well as assessing environmental indicators related to Typhoon Hagibis signals without enhancement.
This research examines how climate change has intensified Typhoon Hagibis and assesses key environmental indicators that may result in significant rainfall effects in both inland and coastal areas of Japan Additionally, it offers a comprehensive analysis of these factors.
L ITERATURE REVIEW
Tropical cyclones in ipcc: anthropogenic effects and future projections
Tropical cyclones (TCs) are primarily influenced by atmospheric and oceanic circulation patterns, including the Hadley, Walker, and monsoon circulations, which complicate forecasting efforts (Christensen et al., 2013; IPCC, 2023) Anthropogenic greenhouse gas emissions further exacerbate this complexity by affecting sea surface temperatures However, advancements in General Circulation Models (GCMs) and the satellite homogenization of historical TC data now allow for more accurate projections of TCs, with an expected increase of 6% per decade (Balaguru et al., 2016) Additionally, the intensification rates of TCs are anticipated to rise, particularly in the Pacific Ocean, where intense TCs are projected to shift northward towards Japan, while the Bay of Bengal region in the Indian Ocean is expected to see an increase in intense TCs Despite these changes, there is an overall predicted decrease in the frequency of tropical cyclones (Balaji et al., 2018).
Figure 1.2 Future projections of shift in TCs in northwestern Pacific Ocean affection
The IPCC AR6 report highlights that human activities have exacerbated extreme climate events, notably increasing the frequency of extreme precipitation and tropical cyclones Projections indicate that precipitation could rise by 11%, 14%, and 28% with temperature increases of +1.5°C, +2.0°C, and +4.0°C, respectively.
2023) Similarly, the frequency of intense cyclones is anticipated to rise by +10%, +13%, and +20% respectively, when compared to data from 1950 (IPCC, 2023) (refer to Figure 1.3 and Figure 1.4)
Figure 1.3 Summary table on observed changes in extremes, their attribution since
Figure 1.4 Future climate experienced at various global warming levels (IPCC,
Environmental indices for heavy precipitation
Tropical cyclones, essential for inducing heavy precipitation, are influenced by various environmental factors Research by Takemi and Unuma (2020) on Typhoon Hagibis revealed that a saturated troposphere and unstable conditions in the lower 2 km led to significant rainfall Similarly, Takemura et al (2019) identified that the Baiu front, driven by strong moisture flux from the North Pacific Subtropical High, caused heavy precipitation in western Japan from July 5 to 7, 2018 Unuma and Takemi (2021) further noted that the high precipitable water levels, exceeding 65 kg/m², were indicative of conditions similar to Quasi-Stationary Convective Clusters (QSCCs), with a K-index over 35 in southern Japan suggesting strong storm development potential Additionally, the Bulk Richardson Number (BRN) in coastal areas ranged from 10 to 40, emphasizing the likelihood of supercell formation.
Relative humidity in the mid-troposphere plays a crucial role in heavy precipitation events, as noted by Yokoyama et al (2017) Kato et al (2007) emphasized that a tropospheric lapse rate of approximately 5.0 to 5.5°C is significant for heavy rainfall during the Baiu front Unuma and Takemi (2021) also found that high mid-level relative humidity is a key factor in generating heavy precipitation Chuda and Niino (2005) examined various environmental factors, including CAPE, CIN, precipitable water, and BRN, across Japan from 1990 to 1999 Their findings revealed that CAPE values were notably higher in the southwest during summer, while low CIN values indicated that weaker air parcel forcing could result in heavy rainfall Conversely, large CIN values were recorded in winter Additionally, precipitable water peaked during the summer months in correlation with CAPE, and the BRN number was strongly influenced by CAPE values, showing the lowest wind shear.
Understanding the environmental factors that contribute to heavy precipitation is crucial This study evaluates key environmental indices, including CAPE, CIN, precipitable water, water vapor flux, and relative humidity, across various RCP scenarios to identify their impact on heavy rainfall events.
Clausius- chaperon application in relation climate change warming
As temperatures rise, the amount of saturated water vapor increases under constant relative humidity, leading to higher precipitation levels, a trend linked to global warming This phenomenon is explained by the Clausius-Clapeyron effect, which demonstrates that atmospheric saturated water vapor pressure grows exponentially with increasing air temperatures Specifically, for every 1°C increase in temperature, the rate of change in saturated water vapor pressure intensifies by approximately 7%, highlighting the significant impact of temperature on moisture in the atmosphere.
According to Clausius-Clapeyron (eq: 1.1) (William H, 2010), the amount of water
8 vapor and precipitation are expected to increase in higher emissions scenarios by 7% for each degree Celsius increase in temperature Consequently, higher rainfall and inundation are anticipated
𝑅 𝑣 𝑇 2 (1-1) es – saturation vapor pressure, Lv – Latent heat of vaporization,
Rv – gas constant for water vapor, T- Temperature
Figure 1.5 The vapor pressure in equilibrium above a liquid water surface, as determined by the Clausius–Clapeyron Equation (William H, 2010).
Pseudo global warming application
Pseudo Global Warming (PGW) employs regional-scale modeling simulations to intentionally introduce significant climate changes at a regional level by modifying boundary conditions (Brogli et al., 2023) This method differs from traditional dynamic downscaling, which relies on the output of Global Climate Models (GCM) to create Regional Climate Models (RCM) and typically requires extensive computational resources.
The brief view of PGW simulations flow chart is represented in the Figure 1.6 In Figure 1.6 the climate change signal (Δ) is derived from the CMIP6 GCM simulations
PGW (perturbed global warming) simulations incorporate climate change signals into historical RCM (regional climate model) simulations of Typhoon Hagibis The differences between the PGW simulations and control simulations (CTRL) illustrate the impacts of climate change.
Figure 1.6 General PGW simulations flow chart (Brogli et al., 2023)
The application of PGW simulations offers a means to mitigate computational requirements and minimize biases in RCM outputs
PGW simulations offer several advantages for climate modeling Firstly, they simplify the simulation process by applying consistent delta "Δ" changes in climate parameters that reflect seasonal cycles rather than interannual variability, allowing for uniform boundary conditions across simulated years Secondly, PGW simulations are cost-effective, requiring only one additional simulation to analyze climate change, which eliminates the need for dynamic downscaling from a GCM and reduces computational and storage costs, making it feasible to run multiple ensembles Additionally, PGW simulations can illustrate how historical events might unfold through the storyline approach Finally, they do not necessitate the entire GCM dataset, as only specific climate variable data is needed for effective simulations.
Research in PGW on typhoon Hagibis
Previous studies on Typhoon Hagibis have utilized PGW simulations to investigate various objectives Kawase et al (2021) examined the PWG storyline approach, conducting both control and non-warming experiments Their research revealed an estimated 10.9% increase in rainfall in the Kanto-Koshin region and a 6.8% increase in precipitation when Japan's topography was not taken into account.
A study by Kita et al (2022) examined the effects of PGW on Typhoon Hagibis in the Arakawa basin, revealing that a 2°C rise in ocean temperature could lead to hourly rainfall rates of 15mm, heightening the risk of flooding Additionally, research by Yoshino et al (2019) indicated that a 4°C increase in global temperatures might result in a 200mm increase in rainfall across Mie and Wakayama prefectures.
The PGW atmospheric ocean coupled model, created by Kanada et al (2021), projected a 23% increase in water vapor mixing ratio in the lower troposphere due to a 3.34 K rise in sea surface temperature (SST) within the PGW climate framework Additionally, Kabasawa et al (2022) utilized PGW simulations to predict a storm surge height of nearly 2 meters in Tokyo Bay under the SSP 585 scenario.
Wakazuki et al (2022) conducted PGW simulations to analyze river inundation in the Kuji and Naka River basins, elevating air temperatures by 1.1°C and 3.4°C Their findings revealed that the Naka River basin is projected to experience greater increases in precipitation at a temperature rise of +4°C, resulting in higher maximum inundation depths.
This study aims to investigate the environmental impacts of climate change on Typhoon Hagibis, as previous research in this area is lacking We will explore various environmental factors under different climate change scenarios, specifically the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 W/m² Through this analysis, we seek to understand the potential changes and impacts on Typhoon Hagibis associated with varying levels of climate change.
R ESEARCH OBJECTIVE AND TASK
We aim to conduct a detailed analysis to rigorously evaluate the correlation between Representative Concentration Pathway (RCP) scenarios and specific environmental factors This investigation focuses on quantifying the numerical associations between prescribed RCP conditions and key environmental parameters.
This research aims to investigate the effects of precipitation enhancement under various Representative Concentration Pathway (RCP) scenarios resulting from global warming It will also analyze the relationship between these RCP scenarios and crucial environmental parameters that influence tropical cyclone precipitation, including relative humidity, precipitable water, water vapor flux density, Convective Available Potential Energy (CAPE), and Convective Inhibition.
The quantitative assessment involves comparison above parameters under different RCP scenarios
The WRF model is employed to analyze Typhoon Hagibis, with a detailed setup outlined in the research methodology section Initial and boundary conditions for control simulations are based on spatial and temporal data from the NCEP-NCR reanalysis, focusing on the period from October 10 to October 13, 2019 Additionally, NCEP-FNL data, which has a spatial resolution of 1-degree by 1-degree grids and is updated every 6 hours, serves as boundary conditions for the Regional Climate Model (RCM) The RCM further interpolates this reanalysis data at each time step during the current climate simulation, enabling accurate results.
The study utilizes reanalysis data to reproduce current climate conditions and employs PGW GCM simulations from the CMIP-6 database, averaging data across five GCMs and covering eight key parameters This dataset shows consistency in mean, maximum, and minimum surface air temperature, precipitation, radiation, humidity, and wind speed, without overestimating global warming projections The GCM data is analyzed for present (2005-2035), near future (2035-2065), and end-of-century (2070-2100) conditions under various RCP scenarios to evaluate the impact of greenhouse gas emissions on climate change The Grid Analysis and Display System (GrADS) is used to visualize and analyze model output, producing plots and graphs to support research findings Additionally, environmental factors such as relative humidity and precipitable water are extracted from both reanalysis and PGW simulations, facilitating a comprehensive comparison to identify trends and implications regarding the relationship between RCP conditions and environmental factors.
R ESEARCH QUESTION AND HYPOTHESIS
This study investigates the impact of environmental factors, including relative humidity, water vapor flux density, convective available potential energy, and convective inhibition, on Typhoon Hagibis under different Representative Concentration Pathway (RCP) scenarios—2.6, 4.5, and 8.5 The research aims to understand how these variables fluctuate due to global warming, providing insights into the potential intensification of typhoons in a changing climate.
We hypothesize that elevated RCP conditions will result in more intense storms, leading to significant alterations in environmental factors In particular, under higher RCP scenarios of 4.5 and 8.5, we anticipate an increase in relative humidity and precipitable water.
Rising air temperatures are expected to increase moisture content and precipitation, while also enhancing atmospheric instability, as indicated by a larger area of Convective Available Potential Energy (CAPE) This may lead to more frequent thunderstorm development, with a decrease in convective inhibitions under higher RCP conditions The CMIP-6 dataset is essential for validating these projections and understanding the complex interactions between Typhoon Hagibis and climate change scenarios.
A TMOSPHERIC MODEL CONFIGURATION
This research utilizes the Weather Research and Forecasting – Advanced Research (WRF-ARW) model to perform simulations through the Pseudo Global Warming (PGW) method WRF-ARW is a prominent numerical weather prediction tool, highly regarded for its effectiveness in scientific applications, particularly in analyzing heavy precipitation and tropical cyclones The model has been extensively employed by the research community to simulate the dynamics of Typhoon Hagibis.
Our research employs three distinct domains with resolutions of 24 km, 6 km, and 2 km, enhancing the accuracy of precipitation forecasts Each dataset consists of 30 vertical levels, ranging from 1000 hPa to 50 hPa at the highest level Figure 2.1 illustrates the selected study domain, while Table 2.1 outlines the specific parameterization used in this analysis To improve the fidelity of the simulations, we implement Spectral Nudging, which aligns the modeled atmospheric fields more closely with observed or analyzed data.
D01: dx = dy = 24 kms D02: dx = dy = 06 kms D03: dx = dy = 02 kms
No of grid points in latitude and longitude
For D01: 99 grids in latitude and 99 grids in longitude
(spacing = 0.108108 deg) For D02: 160 grids in latitude and 160 grids in longitude
(spacing = 0.027027 deg) For D03: 330 grids in latitude and 300 grids in longitude
(50 hPa: highest vertical level) Output time steps
End time: 12.0pm 13-Oct-2019 Geographic center of the domain ref_lat = 33.00, ref_lon = 139.00
Figure 2.1 Weather research and forecast modelling domine used for the study
(24kms, 6kms and 2kms domine)
D ATA , CLIMATE SCENARIO AND GCM
The climate signal data for Typhoon Hagibis is derived from the National Center for Environmental Protection (NCEP) Final Analysis (FNL) 6-hourly data, ensuring accurate initial and boundary conditions To maintain a seamless flow of information, boundary conditions for the finer domain are sourced from the outer domain's output at each time step through nested domains.
In the PGW simulation, the incremental changes were averaged across the simulated
The control simulation incorporates the 16 domain along with the initial and boundary conditions For the PGW simulations, the General Circulation Models (GCMs) utilized are from CMIP6, which consist of the average outputs from five GCMs: MRI-ESM2-0, MIROC6, ACCESS-CM2, and IPSL-CM6A.
The study utilizes data from the LR and MPI-ESM1-2-HR models (Shiogama et al., 2021), focusing on the mean climate variables for September, October, and November across a specified area in Japan, defined by longitudes 135.0 to 145.0 and latitudes 30.0 to 40.0 (see Table 2.2) This dataset encompasses eight critical climate variables essential for assessing the impacts of climate change in Japan Additionally, it incorporates three shared socioeconomic pathways (SSPs): SSP1-2.6, SSP2-4.5, and SSP3-8.5 (O’Neill et al., 2016), providing a comprehensive framework for impact evaluation.
Each RCP scenario is designed with three specific conditions that reflect different time frames and durations: the current climate, the near future, and the projected climate at the end of the 21st century, as detailed in Table 2.3.
Table 2.2 GCM and target period
CM6A-LR, and MPI-ESM1-
Longitude 135.0 to 145.0 and latitude 30.0 to 40.0
RCP conditions Time period Duration Remarks
Present climate 2005-2035 For each condition, the RCP values are calculated for the present, near future, and end of the 21 st century conditions
Far future (End of 21 st Century)
M ETHOD
The climate change signal is determined by averaging future conditions from all General Circulation Models (GCMs) and comparing it to the historical data of Typhoon Hagibis (2019) Future scenarios are projected by combining the existing climate signal with the calculated delta (∆) Detailed methodology for this research is outlined below Figure 2.2.
Future scenario = Typhoon Hagibis (Climate signal) + Delta (for each time-period and RCP conditions)
Figure 2.2 Flow chart of PGW Simulations
In PGW simulations, the vertical air temperature profile is improved, while humidity is adjusted to modified relative humidity to prevent supersaturation in various RCM simulations Future climate boundary conditions for the atmospheric model are established using climate change increments projected by GCMs.
Grid Analysis and Display System (GrADS), Python, and Fortan-90 is used for post processing analysis of the simulation results
CMIP-6 DATA ANALYSIS
The sensitivities of the CMIP-6 dataset were evaluated by analyzing the temporal means of five specific models: MRI-ESM2-0, MIROC6, ACCESS-CM2, IPSL-CM6A-LR, and MPI-ESM1-2-HR This assessment focused on various parameters to determine the sensitivity of the CMIP-6 data across different Representative Concentration Pathways (RCP) scenarios.
Air temperature is projected to rise under all Representative Concentration Pathways (RCPs), with RCP 2.6 indicating an increase of around 0.8°C at 1000 hPa by the end of the century, remaining stable up to 300 hPa In RCP 4.5, temperatures are expected to rise by 1.0°C and 1.8°C for the near future and end-of-century scenarios, respectively, with increases up to 300 hPa reaching approximately 1.35°C and 2.25°C RCP 8.5 forecasts a more significant rise, with air temperatures at 1000 hPa increasing by 1.5°C and 3.6°C, and up to 300 hPa reaching around 1.6°C and 5.2°C for the near future and end-of-century.
The expected rise in air temperature in higher RCP scenarios is driven by multiple factors, including solar radiation and carbon dioxide emissions, which elevate atmospheric temperatures in both RCP 4.5 and 8.5 scenarios This temperature increase leads to enhanced evaporation of water vapor, further intensifying the warming effect (Lacis et al., 2013) Radiative forcing, caused by higher concentrations of greenhouse gases like carbon dioxide and methane, increases heat retention in the atmosphere Consequently, rising surface temperatures accelerate evaporation from oceans, lakes, and other bodies of water, resulting in elevated levels of atmospheric moisture.
Content fuels convective processes by enabling warm, moist air to rise and cool, which releases latent heat into the atmosphere This mechanism of convective heating plays a crucial role in warming the upper troposphere, thereby intensifying the overall rise in air temperature (Cai and Tung, 2012).
Figure 3.1 CMIP-6 temporal means Air temperature data
Surface level air temperature(t as ): The mean temporal surface-level air temperature in
The CMIP-6 projections indicate a rise in temperatures for RCP scenarios 2.6, 4.5, and 8.5 Specifically, RCP 2.6 forecasts minimal change in near surface and end-of-century temperatures, stabilizing around 0.8°C In contrast, RCP 4.5 anticipates increases of 1.0°C in the near future and 1.7°C by century's end RCP 8.5 predicts more significant changes, with near future temperatures rising by 1.5°C and end-of-century temperatures reaching 3.5°C Supporting these findings, the IPCC reports that the global surface air temperature (GSAT) is projected to range from 1.1°C to 2.6°C under RCP 4.5 and 2.6°C to 4.8°C under RCP 8.5 (IPCC, 2023).
The CMIP-6 dataset predicts an increase in mean surface temperature over time for RCP 2.6, RCP 4.5, and RCP 8.5 scenarios Specifically, for RCP 2.6, temperatures are expected to remain stable in both the near future and by the end of the century.
Under the RCP 4.5 scenario, projections indicate a temperature rise of 1.0°C in the near future and 1.7°C by the end of the century In contrast, the RCP 8.5 scenario forecasts a mean surface temperature increase of 1.5°C for the near future and 3.3°C by the century's end, relative to current climatic conditions.
The latest IPCC AR6 report forecasts a significant increase in global surface temperatures for the period 2081–2100 across various greenhouse gas (GHG) emissions scenarios Under the very low GHG emissions scenario (SSP1-1.9), temperatures are expected to rise by 1.0°C to 1.8°C In contrast, the intermediate GHG emissions scenario (SSP2-4.5) predicts an increase of 2.1°C to 3.5°C Alarmingly, under the very high GHG emissions scenario (SSP5-8.5), the projected temperature rise could reach between 3.3°C and 5.7°C (IPCC, 2023).
Figure 3.2 CMIP-6 Surface temperature and Surface level air temperature
Surface level temperatures are significantly affected by various factors, including the ice-albedo feedback, which modifies energy balance and temperature in high emission scenarios Furthermore, water vapor feedback plays a crucial role in regulating both surface and atmospheric temperatures In cases of increased emissions, the interaction known as thermal-radiative coupling also influences these temperature dynamics (Hu et al., 2018).
The heat emitted by the Earth's surface and the heat absorbed and re-emitted by the atmosphere significantly influence temperature variations This interaction of thermal radiation alters longwave radiation, a phenomenon known as thermal feedback (Sejas and Cai, 2016).
Relative humidity is projected to decline significantly under higher emissions scenarios, particularly in the RCP4.5 and RCP8.5 scenarios, with reductions of 1.8% and 2.2% by the end of the century This decrease is closely associated with increased temperatures at higher altitudes and is influenced by the warming contrast, which highlights the drier air over land compared to the ocean As a result, this warming contrast contributes to the overall reduction of relative humidity over land.
P RECIPITATION CHANGES IN RESPONSE TO CLIMATE CHANGE ACROSS
The selected longitude range of 137 to 142 and latitude range of 34 to 38 within Japan aims to evaluate the climate change impacts of Typhoon Hagibis on the Japanese islands This region was specifically chosen due to its significant exposure to the typhoon's effects.
As per the IPCC, the RCP 2.6 scenario represents the low end, limiting the global mean increase in temperature to 2.0°C Figure 3.4 illustrates the total accumulated rainfall in
In the present (P), the regional average accumulated rainfall is 132.52 mm, with projected increases of approximately 5.18% in the near future (NF) and 5.55% by the end of the century (FF) These changes indicate that precipitation will predominantly occur on the western side of Japan under both NF and FF conditions.
The RCP 4.5 scenario represents an intermediate pathway aimed at achieving a radiative forcing stabilization of 4.5 W/m² by 2100 (Thomson et al., 2011) As depicted in Figure 3.5, there is a notable 24-hour maximum accumulated difference in rainfall between the NF and FF conditions The precipitation distributions under various future climatic scenarios show spatial similarities to those of RCP 2.6 Additionally, the regional average precipitation is projected to increase by 6.38% under NF conditions and by 9.38% under FF conditions.
As highlighted, precipitation is expected to increase on the western side of Japan, as well as in mountainous areas
The RCP 8.5 scenario predicts a future marked by significant population growth, high greenhouse gas emissions due to a lack of climate policies, and slow economic development (Riahi et al., 2011) According to Figure 3.6, the maximum 24-hour accumulated rainfall difference under RCP 8.5 shows a net increase in regional average precipitation of 8.69% for NF conditions and 24.77% for FF conditions While the precipitation distribution resembles that of RCP 4.5, it exhibits increased intensity, particularly in land and mountainous regions.
In the PGW scenario, elevated surface temperatures significantly contribute to increased heavy rainfall by enhancing the water vapor mixing ratio Typhoons, influenced by these warmer climate conditions, exhibit a strong potential for intensification The RCP scenarios 2.6, 4.5, and 8.5 show a clear correlation between rising surface temperatures and an increase in the water mixing ratio and saturated vapor pressure, as described by the Clausius-Clapeyron relationship.
The Clapeyron theorem indicates that the regional average water vapor mixing ratio in the lower troposphere (1000 hPa to 700 hPa) is projected to rise by 3.27%, 9.41%, and 22.8% under RCP 2.6, RCP 4.5, and RCP 8.5 FF scenarios, respectively, with corresponding temperature increases of 0.81°C, 1.75°C, and 3.66°C These results imply that the enhanced water vapor mixing ratios, driven by increased surface latent heat release from warmer oceans, may intensify typhoon activity in future climates This trend is further supported by studies on climate change impacts from typhoons Era and Anita.
Higher emissions lead to elevated surface temperatures, which significantly enhance the energy available for typhoons, resulting in increased precipitation This effect is intensified by wind dynamics and is further discussed in the context of changes in water vapor flux In high-emission scenarios, tropical cyclones generate heavy rainfall patterns that correspond with Japan's terrain, particularly in the central region where precipitation can exceed 300 mm This concentration of rainfall highlights the impact of Japan's topography on precipitation distribution (see Figure 3.7 for maximum 24-hour accumulated precipitation along Japan's topography).
Figure 3.4 24-Hour Maximum Accumulated Precipitation for Present and RCP2.6: a) Present, b) Near Future-Present, and c) End of Century–Present
Figure 3.5 24-Hour Maximum Accumulated Precipitation for RCP4.5: a) Near Future-Present, and b) End of Century – Present.
Figure 3.6 24-Hour Maximum Accumulated Precipitation for RCP8.5: a) Near Future-Present, and b) End of Century – Present
Figure 3.7 24-Hour Maximum Accumulated Precipitation Amount with terrain: a) RCP 4.5 (FF), and b) RCP 8.5 FF
Table 3.1 Quantitative assessment of 24 hours accumulated precipitation for various scenarios
Scenario Condition Regional Average 24 hr accumulated rainfall (mm)
W ATER VAPOR FLUX
Our simulations indicate that under higher emissions scenarios, water vapor flux is primarily concentrated in the lower troposphere, specifically below 700 hPa We examined the transport of water vapor flux from the typhoon as it traversed the Japanese islands, noting an increase in flux density associated with higher emissions This rise in water vapor flux density is closely linked to changes in surface temperature, where elevated temperatures enhance the overall flux.
In higher emission scenarios, 26 ideal conditions contribute to the enhancement of cyclones, leading to a significant increase in the pressure gradient between the eye and outer radii, which in turn elevates wind speeds The combination of these higher wind speeds and rising surface temperatures facilitates enhanced moisture transport, further intensifying cyclone activity.
Japan's water vapor flux is heavily affected by its terrain, resulting in orographic precipitation As illustrated in the accompanying figure under the RCP 8.5 scenario, both net flux and accumulated rainfall are depicted The terrain's deflection causes significant rainfall on the windward side of the mountains.
Figure 3.8 Water vapor flux density and 24-Hour Maximum Accumulated
Precipitation Amount with terrain: a) Present; b) RCP 2.6 FF (Near Future – Present); c) RCP 4.5 FF (Near Future –
Present); d) RCP 8.5 FF (Near Future – Present)
C ONVECTIVE AVAILABLE POTENTIAL ENERGY ( CAPE )
Convective available potential energy (CAPE) measures the buoyant energy of a dry air parcel in a saturated environment, making it a crucial metric for assessing the energy available for upward air currents in tropical cyclones Higher CAPE values are associated with enhanced convection, indicating a stronger potential for storm development.
ZLFC : level of free convection;
ZLNB : level of neutral buoyancy;
Tv,p : virtual temperature parcel of the moist adiabat;
Tv,e : virtual environmental; g: acceleration due to gravity
Heavy rainfall on the Japanese islands is mainly attributed to low-level humid air, as noted by Kato (2018) This humid air from the ocean encounters terrain obstacles, resulting in orographic precipitation Kato's research indicates that the water vapor mixing ratio in the lower troposphere exceeds 10 g/kg, significantly higher than that in the middle and upper troposphere To analyze the most unstable Convective Available Potential Energy (CAPE), the study also considers environmental factors such as CAPE and Convective Inhibition (CIN) at approximately 500 meters above the surface, or around 950 hPa.
In scenarios with elevated emissions, the rise in surface temperature leads to an increase in Convective Available Potential Energy (CAPE) due to enhanced enthalpy, which promotes convective activity and allows surface air parcels to ascend As surface temperatures rise—illustrated in Figure 3.2 with increases from 0.787°C, 1.582°C, and 3.29°C for RCP scenarios 2.6, 4.5, and 8.5 by century's end—enthalpy also increases with height, intensifying disorder and further fostering convective activity and CAPE development (M Lee and Frisius, 2018) Moreover, high emissions contribute to greater surface fluxes of heat and moisture, facilitating the exchange of these elements in the atmosphere.
The Earth's surface and atmosphere are essential for maintaining convective instability and supplying energy for convection M Lee and Frisius (2018) note that in high-emission scenarios, friction convection intensifies, leading to stronger winds directed toward the storm's center, which increases CAPE and enhances convection This behavior significantly differs from natural convection.
The RCP 8.5 scenario indicates that Convective Available Potential Energy (CAPE) is primarily concentrated in Japan, with an observed increase in Convective Inhibition (CIN) in flat areas and CAPE in mountainous regions This enhancement is linked to a rise in precipitation levels in mountainous areas under higher emission scenarios.
Elevated emissions are expected to increase moist static energy (MSE), which encompasses the enthalpy per unit mass of air, potential energy, and latent heat This increase is closely associated with Convective Available Potential Energy (CAPE), highlighting a significant dependence on the surplus of MSE across various climatic conditions Analysis at latitudes 35.5° reveals that MSE rises under different future scenarios (RCP 2.6, 4.5, and 8.5) due to increased surface temperatures, leading to higher enthalpy, potential energy, and latent heat The selection of these latitudes illustrates the terrain effect, where MSE is obstructed and enhanced by elevation.
MSE = CpT (Enthalpy) + Φ (potential energy) +Lv q (latent heat) (3-2)
The analysis in Figure 3.11 reveals a significant rise in Mean Sea Level Pressure (MSE) primarily between the 1000 hPa and 700 hPa levels Under different Representative Concentration Pathways (RCP), the regional average hourly MSE has increased by 0.6% for RCP 2.6, 1.5% for RCP 4.5, and 3.3% for RCP 8.5 FF conditions.
Research by Agard and Emanuel (2017) indicates that rising temperatures will lead to increased water vapor, in line with the Clausius-Clapeyron theorem, which is expected to enhance Convective Available Potential Energy (CAPE) under future higher Representative Concentration Pathways (RCP) This connection highlights the interplay between temperature, water vapor levels, and CAPE.
29 underscores the importance of considering climate change impacts on convective process
Figure 3.9 Maximum hourly CAPE for Present and RCP 2.6 scenario (lev 500 mts)
Present, b) Near Future-Present, and c) End of Century – Present
Figure 3.10 Maximum hourly CAPE for RCP 4.5 scenario (lev 1000hpa-100hpa) a) Near Future-Present, and b) End of Century – Present
Figure 3.11 Maximum hourly CAPE for RCP 8.5 scenario (lev 1000hpa-100hpa) a) Near Future-Present, and b) End of Century – Present
Figure 3.12 Maximum hourly MSE at latitude 35.5° a) Present, b) RCP 2.6 Far future, c) RCP 4.5 Far future, and d) RCP 8.5 Far future
C ONVECTIVE INHIBITION ( CIN )
High CAPE values alone do not guarantee strong convection, as an air parcel must first overcome a stable layer between the surface and the level of free convection (LFC) The Convective Inhibition (CIN) indicates the energy required for the air parcel to ascend through this stable layer and access the available energy above the LFC, where convection can occur Essentially, CIN serves as a barrier that hinders convection development, even when high CAPE values are present, by determining the energy needed for the air parcel to breach the stable layer and initiate convective activity.
Z0: Lifting level; rest remains the same as defined in CAPE
In regions with average Convective Available Potential Energy (CAPE), low Convective Inhibition (CIN) values suggest high enthalpy and an unstable atmosphere Significant CIN is noted south of the typhoon track in flat areas However, under the RCP 8.5 scenario, the thermodynamic relationships between CAPE and CIN become more intricate, as illustrated in Figure 3.13, affecting both plain and terrain areas.
The cumulative distribution function (CDF) illustrated in Figure 3.14 reinforces the idea that CIN values vary significantly across different RCP scenarios, specifically RCP 2.6, 4.5, and 8.5 under the FF condition for the latitude range of 34.5 to 36.5 and longitude range of 139.0 to 141.0 Notably, at the 85th percentile, CIN accumulation is substantially higher in the RCP 8.5 scenario, recording 15 J/kg compared to just 4 J/kg in RCP 2.6 This elevated CIN in the plains hinders precipitation, resulting in water vapor being redirected toward the central and western regions of Japan, where the terrain forces it to ascend, ultimately leading to increased precipitation on the eastern side in higher emission scenarios Our findings clarify how rising CIN levels may influence convective patterns.
Recent findings indicate that as typhoons encounter higher Convective Inhibition (CIN) levels, mountainous regions may experience more intense storms and increased heavy precipitation, particularly in warmer temperatures Higher emissions scenarios lead to stronger CIN, creating challenges for weaker storms that struggle to overcome this barrier However, extreme precipitation events capable of penetrating the CIN can significantly impact mountainous areas These observations are consistent with IPCC conclusions that suggest an increase in extreme precipitation in higher emissions scenarios, as elevated CIN levels contribute to higher Convective Available Potential Energy (CAPE) values.
Figure 3.13 Average CIN Build-up (11-Oct-2019 21:00 to 12-Oct-2019 12:00) a) Present, b) RCP 2.6 Far future, c) RCP 4.5 Far future, and d) RCP 8.5 Far future
Figure 3.14 Cumulative distribution of CIN (Lat 34.5 to 36.5, Lon 139.0 to 141.0) a) Present, b) RCP 2.6 Far future, c) RCP 4.5 Far future, and d) RCP 8.5 Far future
Relative humidity significantly influences cloud formation and is crucial for typhoon development Recent CMIP-6 data indicates a decrease in regional average relative humidity due to warming contrast, yet a notable increase in maximum average relative humidity from 800 hPa to 400 hPa in cyclone rainbands has been observed, shifting northward This trend corresponds with the formation of Convective Available Potential Energy (CAPE) in northern areas Additionally, the average relative humidity within rainbands has risen by 12% in both RCP 4.5 and RCP 8.5 far future scenarios In the RCP 8.5 FF scenario, relative humidity levels along the typhoon path have increased over the Japanese islands, significantly influenced by the terrain.
Figure 3.16 illustrates the average humidity levels between 800 hPa and 400 hPa for latitudes 34° to 38° and longitudes 137° to 142°, highlighting the relative humidity across the Japanese islands Under the RCP 8.5 scenario, certain regions exhibit notable variations in humidity.
In area A1, high CIN values prevent saturation, while area A2, located nearer to the terrain, is influenced by terrain-induced relative humidity and convection When moist, high-speed winds meet the terrain, they ascend due to orographic lifting, causing the air to cool and condense, ultimately reaching saturation.
Area A3 shows water vapor transport towards the western side of the Japanese islands at elevated altitudes, where saturation levels remain low This phenomenon is consistent with the observed patterns of water vapor flux transportation.
The maximum average relative humidity (RH) change from 800 hPa to 400 hPa is illustrated in Figure 3.15 across different scenarios: a) RCP 2.6 Near Future, b) RCP 2.6 Far Future, c) RCP 4.5 Near Future, d) RCP 4.5 Far Future, e) RCP 8.5 Near Future, and f) RCP 8.5 Far Future, presented from left to right.
Figure 3.16 Average RH change (lev 800 hPa to 400 hPa) (Lat 34 -38; Long 137-
142) a) RCP 2.6 (Far future-present), b) RCP 4.5 (Far future-present), c) RCP 8.5 (Far future-present)
Measuring precipitable water (PW) is essential for climate analysis, as it offers valuable insights into the water depth in the atmosphere if all moisture were to become rainfall This key parameter plays a vital role in understanding energy budgets and hydrological cycles within the climate system.
The maximum hourly average precipitable water currently stands at 59.41 kg/m² For the near future under RCP 2.6, this value increases to 61.84 kg/m², while it slightly decreases to 61.74 kg/m² for the far future In the case of RCP 4.5, the near future sees an increase to 62.47 kg/m², with a further rise to 65.94 kg/m² in the far future For RCP 8.5, the values escalate to 64.72 kg/m² for the near future and reach 76.10 kg/m² in the far future.
Under the extreme emissions scenario RCP8.5, regional average precipitable water (PW) is projected to nearly double compared to current levels Simulations from the PGW model indicate a direct correlation between precipitable water and surface temperature.
The Clausius-Clapeyron relation in Table 4.1 reveals a direct correlation between regional average precipitable water and surface temperature across various scenarios Notably, in the RCP 8.5 scenario, there is a significant increase in precipitable water, coinciding with a 25.18% rise in saturated vapor pressure, driven by elevated surface temperatures This increase contributes to higher entropy within the climate system, leading to decreased efficiency and greater disorder, as supported by the findings of Lucarini et al (2010) and Rasmussen et al (2020) Furthermore, the distribution of precipitable water reflects the upwind rainfall patterns influenced by the terrain.
The RCP 8.5 scenario highlights a marked rise in precipitable water and saturated vapor pressure, demonstrating how increased surface temperatures significantly affect atmospheric moisture levels and climate dynamics This leads to intensified precipitation on the windward side of the terrain, with precipitable water patterns closely aligning with rainfall distribution in upwind areas.
Figure 3.17 Maximum Increase in hourly Precipitable water for RCP 2.6 scenario a) Present, b) Near Future, and c) End-of-Century Conditions (Left to right)
Our simulations indicate that under higher emissions scenarios, water vapor flux is primarily concentrated in the lower troposphere, specifically below 700 hPa We examined the transportation of this water vapor flux from a typhoon as it traversed the Japanese islands, noting an increase in flux density associated with higher emissions Changes in surface temperature significantly influence water vapor flux density, as elevated temperatures foster conditions that enhance cyclones in these scenarios This phenomenon results in a steeper pressure gradient between the eye of the cyclone and its outer radii, subsequently increasing wind speeds The combination of higher wind speeds and increased surface temperatures ultimately leads to intensified weather events.