Cloud Microphysical Processes Research Articles

Parameterization of Microphysical Processes in Convective Clouds in Global Climate Models

Abstract The microphysical processes inside convective clouds play an important role in climate. They directly control the amount of detrainment of cloud hydrometeor and water vapor from updrafts. The detrained water substance in turn affects the anvil cloud formation, upper-tropospheric water vapor distribution, and thus the atmospheric radiation budget. In global climate models, convective parameterization schemes have not explicitly represented microphysics processes in updrafts until recently. In this paper, the authors provide a review of existing schemes for convective microphysics parameterization. These schemes are broadly divided into three groups: tuning-parameter-based schemes (simplest), single-moment schemes, and two-moment schemes (most comprehensive). Common weaknesses of the tuning-parameter-based and single-moment schemes are outlined. Examples are presented from one of the two-moment schemes to demonstrate the performance of the scheme in simulating the hydrometeor distribution in convection and its representation of the effect of aerosols on convection.

Phase transition observations and discrimination of small cloud particles by light polarization in expansion chamber experiments

Abstract. Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather, and general circulation models. The detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud particle-size range below 50 μm, remains challenging in mixed phase, often unstable environments. The Cloud Aerosol Spectrometer with Polarization (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure the variability in polarization state of their backscattered light. Here we operate the versatile Cosmics Leaving OUtdoor Droplets (CLOUD) chamber facility at the European Organization for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water, and ice particles. In this paper, optical property measurements of mixed-phase clouds and viscous secondary organic aerosol (SOA) are presented. We report observations of significant liquid–viscous SOA particle polarization transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarization ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulfate, and volcanic ash. Finally, we discuss the benefits and limitations of this classification approach for atmospherically relevant concentrations and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to tropical troposphere layer analysis.

Cloud microphysical differences with precipitation intensity in a torrential rainfall event in Sichuan, China

AbstractHigh-resolution data of a torrential rainfall event in Sichuan, China, simulated by the WRF model, were used to analyze the cloud microphysical differences with precipitation intensity. Six-hourly accumulated rainfall was classified into five bins based on rainfall intensity, and the cloud microphysical characteristics and processes in different bins were studied. The results show that: (1) Hydrometeor content differed distinctly among different bins. Mixing ratios of cloud water, rain water, and graupel enhanced significantly and monotonously with increasing rainfall intensity. With increasing precipitation intensity, the monotonous increase in cloud water number concentration was significant. Meanwhile, number concentrations of rain water and graupel increased at first and then decreased or increased slowly in larger rainfall bins. (2) With precipitation intensity increasing, cloud microphysical conversion processes closely related to the production of rainwater, directly (accretion of cloud wat...

A Bayesian Examination of Deep Convective Squall-Line Sensitivity to Changes in Cloud Microphysical Parameters

Abstract Deep convective cloud content, precipitation distribution and rate, dynamics, and radiative fluxes are known to be sensitive to the details of liquid- and ice-phase cloud microphysical processes. Previous studies have explored the multivariate convective response to changes in cloud microphysical parameter values in a framework that isolated the cloud and radiation schemes from the thermodynamic and dynamic environment. This study uses a Bayesian Markov chain Monte Carlo (MCMC) algorithm to generate sets of cloud microphysical parameters consistent with a specific storm environment in a three-dimensional cloud-system-resolving model. These parameter sets, and the corresponding large ensemble of model simulations, contain information about the univariate model sensitivity, as well as parameter–state and parameter–parameter interactions. Examination of the relationships between cloud parameters and in-cloud vertical motion and latent heat release provides information about the influence of microphysical processes on the in-cloud environment. Exploration of the joint dependence of microphysical properties and clear-air relative humidity and temperature allows an assessment of the influence of cloud microphysics on the near-cloud environment. Analysis of the MCMC results indicates the model output is sensitive to a small subset of the parameters. In addition, constraint of cloud microphysics using bulk observations of the hydrologic cycle and TOA radiative fluxes uniquely constrains vertical velocity, latent heat release, and the environmental temperature and relative humidity.

Impact of Long-Range Transported African Dust on Cloud Water Chemistry at a Tropical Montane Cloud Forest in Northeastern Puerto Rico

Bulk and drop size fractionated cloud water was collected at a Caribbean tropical montane cloud forest (TMCF) in northeastern Puerto Rico in the summer months of 2010-2012 and winter months of 2011 as part of the Puerto Rico African Dust and Cloud Study (PRADACS). We studied how cloud water chemistry in a Caribbean TMCF was affected by long-range transported African dust (LRTAD). Using HYSPLIT trajectories and enrichment factor analysis, the air masses influencing clouds at Pico del Este were identified as dust, marine, and dust with anthropogenic influence. Samples were analyzed for pH, conductivity, water-soluble ions, and metals. Na+ and Cl- comprised the main water-soluble ions (60- 80%) suggesting a strong marine influence. A 0.1-10% contribution of anthropogenic (nss-SO_4 ^(2-)) and 0.2-13% contribution of mineral dust (nss-Ca^(2+)) sources to the cloud chemical composition was observed. Primary aerosols (i.e., mineral dust and sea-salt) were enriched in large cloud water droplets (LCWD) and secondary aerosols (i.e., anthropogenic particles) were enriched in small cloud water droplets (SCWD). As a result, pH was found to be higher in LCWD due to the neutralizing capacity of nss-Ca^(2+)) and lower in SCWD due to the presence of acidifying species (nss-SO_4 ^(2-), NO_3 ^-, and organic acids). Fe and Al, indicators for mineral dust were similarly distributed across the cloud droplet size spectrum. Our results show that LRTAD events modulate bulk and size-fractionated cloud water chemistry, potentially influencing cloud microphysical properties and processes.

Genesis of Hurricane Julia (2010) within an African Easterly Wave: Sensitivity to Ice Microphysics

AbstractWhile much attention has been given to investigating the dynamics of tropical cyclogenesis (TCG), little work explores the thermodynamical evolution and related cloud microphysical processes occurring during TCG. This study elaborates on previous research by examining the impact of ice microphysics on the genesis of Hurricane Julia during the 2010 North Atlantic Ocean hurricane season. As compared with a control simulation, two sensitivity experiments are conducted in which the latent heat of fusion owing to depositional growth is removed in one experiment and homogeneous freezing is not allowed to occur in the other. Results show that removing the latent heat of fusion substantially reduces the warming of the upper troposphere during TCG. This results in a lack of meso-α-scale hydrostatic surface pressure falls and no tropical depression (TD)-scale mean sea level pressure (MSLP) disturbance. In contrast, removing homogeneous freezing has little impact on the structure and magnitude of the upper-tropospheric thermodynamic changes and MSLP disturbance. Fundamental changes to the strength and spatial extent of deep convection and related updrafts are found when removing the latent heat of fusion from depositional processes. That is, deep convection and related updrafts are weaker because of the lack of heating in the upper troposphere. These changes to convective development impact the creation of a storm-scale outflow and thus the accumulation of upper-tropospheric warming and the development of the TD-scale MSLP disturbance.

Numerical Experiments to Analyze Cloud Microphysical Processes Depicted in Vertical Profiles of Radar Reflectivity of Warm Clouds

Abstract Information about microphysical processes in warm clouds embedded in satellite measurements must be untangled to be used to improve the parameterization in global models. In this paper, the relationship between vertical profiles of horizontally averaged radar reflectivity Zm and cloud optical depth from cloud top τd was investigated using a hybrid cloud microphysical model and a forward simulator of satellite measurements. The particle size distributions were explicitly simulated using a bin method in a kinematic framework. In contrast to previous interpretations of satellite-observed data, three patterns of the Zm–τd relationship related to microphysical processes were identified. The first is related to the autoconversion process, which causes Zm to increase upward with decreasing τd. Before the initiation of surface precipitation, Zm increases downward with τd in the upper part of the cloud, which is considered to be a second characteristic pattern and is caused by the accretion process. The appearance of this pattern corresponds to the initiation of efficient production of raindrops in the cloud. The third is related to the sedimentation and evaporation of raindrops causing Zm to decrease downward with τd in the lower part of the Zm–τd relationship. It was also found that the bulk collection efficiency has a partially positive correlation with the slope factor of Zm with regard to τd and that the slope factor could be a gross measure of the collection efficiency in partial cases. This study also shows that differences in the aerosol concentration modulate the duration of these three patterns and change the slope factor of Zm.

Putting the clouds back in aerosol–cloud interactions

Abstract. Aerosol–cloud interactions (ACI) are the consequence of perturbed aerosols affecting cloud drop and crystal number, with corresponding microphysical and radiative effects. ACI are sensitive to both cloud microphysical processes (the "C" in ACI) and aerosol emissions and processes (the "A" in ACI). This work highlights the importance of cloud microphysical processes, using idealized and global tests of a cloud microphysics scheme used for global climate prediction. Uncertainties in key cloud microphysical processes examined with sensitivity tests cause uncertainties of nearly −30 to +60 % in ACI, similar to or stronger than uncertainties identified due to natural aerosol emissions (−30 to +30 %). The different dimensions and sensitivities of ACI to microphysical processes identified in previous work are analyzed in detail, showing that precipitation processes are critical for understanding ACI and that uncertain cloud lifetime effects are nearly one-third of simulated ACI. Buffering of different processes is important, as is the mixed phase and coupling of the microphysics to the condensation and turbulence schemes in the model.

Model simulations of heavy precipitation in Kashmir, India, in September 2014

Jammu and Kashmir in north India experienced one of the worst floods during first week of September 2014, due to unprecedented and intense rains. A cyclonic circulation moved northward and intensified between 4 and 7 September, as a result of which unprecedented very heavy rainfall occurred in the region. The main objectives of this study were to simulate this extreme rainfall event using high-resolution regional model and to document role of cloud microphysics on the simulations. A set of experiments have been carried out using Weather Research and Forecasting (WRF) model by configuring it with two nested domains with horizontal resolution of 18 and 6 km. The model was initialized with initial conditions of 00UTC of 2, 3 and 4 September 2014. For each initial condition, two set of numerical experiments were carried out with different cloud microphysics processes. While one set of run used WSM3 scheme, the other set used WSM6 scheme. It is found that the WRF model simulated a stronger cyclonic circulation when WSM scheme with graupels was used. The rainfall amount is also more in these experiments than those with WSM3 scheme. However, the cyclonic system is simulated to the east of the observed location in all the forecasts. The forecast skill is better with lesser lead time, i.e., the WRF model simulations were better when the model runs started from 4 September instead of earlier initial conditions. Examination of MODIS snow cover area suggests that a large mountainous area in catchment of Jhelum and its tributaries was covered with snow on 6 and 7 September 2014. This snow melted very fast, and by 8 September, most of the snow had melted. The WRF model also simulated good amount of snow in the mountains, but the location of maximum snow is to the east of observed location.

Dynamical, convective, and microphysical control on wintertime distributions of water vapor and clouds in the tropical tropopause layer

AbstractProcesses that influence the humidity and cirrus cloud abundance in the Tropical Tropopause Layer (TTL) during boreal winter 2006–2007 are investigated in simulations of clouds along backward trajectories of parcels ending at the 372 K potential temperature (100 hPa) level in the tropics. Trajectories are calculated using offline calculations of seasonal mean tropical radiative heating rates along with reanalysis temperature and wind data with enhanced wave‐driven variability in the TTL. The one‐dimensional (vertical) time‐dependent cloud microphysical model is initialized with water vapor measurements from the Microwave Limb Sounder and the evolution of clouds along each trajectory is simulated using temperature profiles extracted from reanalysis data and convective cloud top heights estimated from 3‐hourly geostationary satellite imagery. Averaged over the tropics, waves dehydrate the 100 hPa level by 0.5 ppmv, while convection and cloud microphysical processes moisten by 0.3 and 0.7 ppmv, respectively. The tropical mean cloud occurrence frequencies in the middle to upper TTL agree well with those based on satellite observations (spatial correlation of 0.8). Waves and convection enhance cloud occurrence at the cold point tropopause by 4% and 2%, respectively. Temporal variability of the heating rates as indicated by the ERA‐Interim 6‐hourly heating rate fields dehydrates the TTL by 0.4 ppmv and decreases the cloud occurrence by 4% because parcels are more likely to encounter the coldest temperatures and dehydrate near the cold point, limiting cloud formation above. The final dehydration locations of parcels, concentrated near the dateline in the tropical Pacific, are insensitive to various model parameters.

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modeling

Abstract. The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather high temperatures of −6 °C. For comparison, a second mixed phase case at about −25 °C is introduced. To further look into the details of cloud microphysical processes, a simple dynamics model of the Asai-Kasahara (AK) type is combined with detailed spectral microphysics (SPECS) forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics, as well as main cloud features, to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity), whereas the ice phase is much more sensitive to the microphysical parameters (ice nucleating particle (INP) number, ice particle shape). The choice of ice particle shape may induce large uncertainties that are on the same order as those for the temperature-dependent INP number distribution.

Analysis of the slope of isentropic surfaces and its tendencies over the North Atlantic

The maintenance of baroclinicity along mid‐ and high‐latitude storm tracks is a matter of ongoing debate. Using an isentropic framework, a novel diagnostic based on the tendency equation for the slope of isentropic surfaces – a measure of the potential for baroclinic development – is presented. The tendency comprises contributions from dynamic processes, latent heat release, radiation and subgrid‐scale turbulence, which incorporates the effect of sensible heat fluxes. A climatology of these tendencies over the North Atlantic is compiled for the winters of 2009 and 2010.It is found that adiabatic tilting flattens the isentropic surfaces, reflecting the action of growing baroclinic cyclones. This tendency is balanced climatologically by the generation of slope by diabatic processes. In the lower troposphere, the most intense diabatic increase of slope is found along the oceanic frontal zone associated with the Gulf Stream and at higher latitudes in the Labrador Sea, the Nordic Seas and the Barents Sea. Latent heat release and sensible heat fluxes both contribute substantially in these regions. A quantitative analysis of cold‐air outbreaks emphasizes their important role in restoring the slope in the lower troposphere over the Gulf Stream region and off the sea‐ice edge at high latitudes. In the upper troposphere, latent heat release due to cloud microphysical processes is the dominant mechanism maintaining the slope.

Scale‐aware parameterization of liquid cloud inhomogeneity and its impact on simulated climate in CESM

AbstractUsing long‐term radar‐based ground measurements from the Atmospheric Radiation Measurement Program, we derive the inhomogeneity of cloud liquid water as represented by the shape parameter of a gamma distribution. The relationship between the inhomogeneity and the model grid size as well as atmospheric condition is presented. A larger grid scale and more unstable atmosphere are associated with larger inhomogeneity that is described by a smaller shape parameter. This relationship is implemented as a scale‐aware parameterization of the liquid cloud inhomogeneity in the Community Earth System Model (CESM) in which the shape parameter impacts the cloud microphysical processes. When used in the default CESM1 with the finite‐volume dynamic core where a constant liquid inhomogeneity parameter was assumed, it reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller (larger) grid size in high (low) latitudes in the longitude‐latitude grid setting of CESM and the more stable (unstable) atmosphere. The single‐column model and general circulation model sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. An advantage of the parameterization is that it can recognize the spatial resolutions of the CESM without special tuning of the cloud water inhomogeneity parameter.

Impacts of cloud microphysics on trade wind cumulus: which cloud microphysics processes contribute to the diversity in a large eddy simulation?

This study investigated the impact of several cloud microphysical schemes on the trade wind cumulus in the large eddy simulation model. To highlight the differences due to the cloud microphysical component, we developed a fully compressible large eddy simulation model, which excluded the implicit scheme and approximations as much as possible. The three microphysical schemes, the one-moment bulk, two-moment bulk, and spectral bin schemes were used for sensitivity experiments in which the other components were fixed. Our new large eddy simulation model using a spectral bin scheme successfully reproduced trade wind cumuli, and reliable model performance was confirmed. Results of the sensitivity experiments indicated that precipitation simulated by the one-moment bulk scheme started earlier, and its total amount was larger than that of the other models. By contrast, precipitation simulated by the two-moment scheme started late, and its total amount was small. These results support those of a previous study. The analyses revealed that the expression of two processes, (1) the generation of cloud particles and (2) the conversion from small droplets to raindrops, were crucial to the results. The fast conversion from cloud to rain and the large amount of newly generated cloud particles at the cloud base led to evaporative cooling and subsequent stabilization in the sub-cloud layer. The latent heat released at higher layers by the condensation of cloud particles resulted in the development of the boundary layer top height.

Incorporating an advanced aerosol activation parameterization into WRF‐CAM5: Model evaluation and parameterization intercomparison

AbstractAerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate‐air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF‐CAM5) to simulate aerosol‐cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near‐surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO2, NO2, HCHO, and O3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NOx at all sites and SO2, O3, PM2.5, and PM10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul‐Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107–113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation, shortwave cloud forcing, and precipitation. The model evaluation identifies several areas of improvements including emissions and their vertical allocation as well as model formulations such as aerosol formation, cloud droplet nucleation, and ice nucleation.

The Wegener-Bergeron-Findeisen process – Its discovery and vital importance for weather and climate

The Wegener-Bergeron-Findeisen process refers to the rapid growth of ice crystals at the expense of surrounding cloud droplets, which frequently occurs in atmospheric mixed-phase clouds. The process is a result of the difference in saturation vapor pressures with respect to liquid and ice, and may in some circumstances lead to abrupt and complete cloud glaciation at temperatures between −40 °C and 0 °C in the Earth’s atmosphere. The process is named after three eminent scientists who were active in the first half of the 20 th century, among them being German meteorologist Walter Findeisen (1909–1945). In his classical paper published in 1938, Findeisen described the contemporary understanding of the Wegener-Bergeron-Findeisen process and other key cloud microphysical processes. Here, we compare the understanding of aforementioned processes at the time with that of the present, and find that they are remarkably similar. We also discuss how the Wegener-Bergeron-Findeisen process is implemented in state-of-the-art numerical models of the atmosphere, and highlight its importance for both weather and climate.

Influence of Mass and Radius of Ice Crystals on Hydrometeors, Internal Energy, and Kinetic Energy: A Numeric Model Study

AbstractTwo cloud-scale experiments with two different ice-phase schemes were carried out for a precipitation event that occurred in eastern China in 2005. The results were analyzed to examine the influences of the change of ice-particle mass and radius on hydrometeors, internal energy, and kinetic energy, as well as the primary factors responsible. It was found that the ice content increases notably and the snow content decreases due to the change. This is the consequence of the modulation of cloud microphysical processes. In particular, the Bergeron process and the accretion of snow and cloud ice are markedly influenced. The differences of internal energy and kinetic energy between the two experiments are caused by adjustments to pressure-flux divergence, the coupling of temperature and divergence, and gravitational work, and the reason is that these three factors result in differences of local changes of internal and kinetic energy.

Quadrature Methods for the Calculation of Subgrid Microphysics Moments

Abstract Many cloud microphysical processes occur on a much smaller scale than a typical numerical grid box can resolve. In such cases, a probability density function (PDF) can act as a proxy for subgrid variability in these microphysical processes. This method is known as the assumed PDF method. By placing a density on the microphysical fields, one can use samples from this density to estimate microphysics averages. In the assumed PDF method, the calculation of such microphysical averages has primarily been done using classical Monte Carlo methods and Latin hypercube sampling. Although these techniques are fairly easy to implement and ubiquitous in the literature, they suffer from slow convergence rates as a function of the number of samples. This paper proposes using deterministic quadrature methods instead of traditional random sampling approaches to compute the microphysics statistical moments for the assumed PDF method. For smooth functions, the quadrature-based methods can achieve much greater accuracy with fewer samples by choosing tailored quadrature points and weights instead of random samples. Moreover, these techniques are fairly easy to implement and conceptually similar to Monte Carlo–type methods. As a prototypical microphysical formula, Khairoutdinov and Kogan’s autoconversion and accretion formulas are used to illustrate the benefit of using quadrature instead of Monte Carlo or Latin hypercube sampling.

The effect of atmospheric radiative heating by clouds on the Madden‐Julian Oscillation

AbstractThis article explores how atmospheric radiative heating, due to the presence of clouds, influences the Madden‐Julian Oscillation (MJO) as simulated by four comprehensive atmosphere general circulation models. Simulations in which clouds are transparent to electromagnetic radiation (“clouds‐off”) are compared with control simulations in which clouds are allowed to interact with radiation (“clouds‐on”). Making clouds transparent to radiation leads to robust changes of the mean state: the westerly winds in the equatorial Indo‐Pacific area weaken and the precipitation reveals a shift from single to double Intertropical Convergence Zones. These changes are accompanied by weaker MJOs. Also, the moisture sensitivity of precipitation changes, however not consistently within our group of models. Further analyses show that within the active phase of intraseasonal variability, cloud‐radiative effects amplify the heating profiles compared to clouds‐off. Heating from nonradiative processes is dominated by the parameterized convection, but large‐scale heating associated with cloud microphysical processes acting on the grid‐scale modifies the shape of the heating profile, leading to a top‐heaviness when cloud‐radiative effects are accounted for. The radiative heating due to clouds slows down the phase speed of the MJO. Averaged over the entire MJO life cycle, the column‐integrated radiative heating due to clouds lags the vertically integrated moist static energy by 40°–60° of longitude (equivalently 7–10 days assuming a period of 60 days). All four models studied reveal more pronounced Kelvin waves when clouds are transparent to radiation, suggesting that cloud‐radiative effects on large‐scale heating profiles damp smaller scale, or faster, Kelvin waves and amplify MJO‐like disturbances.

Climate change effects on the worst-case storm surge: a case study of Typhoon Haiyan

Effects of climate change on the worst case scenario of a storm surge induced by a super typhoon in the present climate are investigated through the case study of Typhoon Haiyan. We present the results of our investigation on super-typhoon Haiyan by using a super high resolution (1 km grid) regional model that explicitly handles cloud microphysical processes. As the parent model, we adopted the operational weekly ensemble experiments (60 km grid) of the Japan Meteorological Agency, and compared experiments using sea surface temperatures and atmospheric environmental parameters from before the beginning of anthropogenic climate change (150 years ago) with those using observed values throughout the typhoon. We were able not only to represent the typhoon’s intensity but also to evaluate the influences of climate change on worst case storm surges in the Gulf of Leyte due to a typhoon with high robustness. In 15 of 16 ensemble experiments, the intensity of the simulated worst case storm in the actual conditions was stronger than that in a hypothetical natural condition without historical anthropogenic forcing during the past 150 years. The intensity of the typhoon is translated to a disaster metric by simulating the storm surge height by using a shallow-water long-wave model. The result indicates that the worst case scenario of a storm surge in the Gulf of Leyte may be worse by 20%, though changes in frequency of such events are not accounted for here.