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Lake Kasumigaura, one of Japan’s largest lakes, presents significant challenges for remote sensing due to its eutrophic conditions and complex optical properties. Although the Global Change Observation Mission-Climate (GCOM-C)/Second-generation Global Imager (SGLI)-derived inherent optical properties (IOPs) offer water quality monitoring potential, their performance in such turbid inland waters remains inadequately validated. This study evaluated five established IOP retrieval algorithms, including the quasi-analytical algorithm (QAA_V6), Garver–Siegel–Maritorena (GSM), generalized IOP (GIOP-DC), Plymouth Marine Laboratory (PML), and linear matrix inversion (LMI), using measured remote sensing reflectance (Rrs) and corresponding IOPs between 2017–2018. The results demonstrated that the QAA had the highest performance for retrieving absorption of particles (ap) with a Pearson correlation (r) = 0.98, phytoplankton (aph) with r = 0.97, and non-algal particles (anap) with r = 0.85. In contrast, the GSM algorithm exhibited the best accuracy for estimating absorption by colored dissolved organic matter (aCDOM), with r = 0.87, along with the lowest mean absolute percentage error (MAPE) and root mean square error (RMSE). Additionally, a strong correlation (r = 0.81) was observed between SGLI satellite-derived remote-sensing reflectance (Rrs) and in situ measurements. Notably, a high correlation was observed between the aph (443 nm) and the chlorophyll a (Chl-a) concentration (r = 0.84), as well as between the backscattering coefficient (bbp) at 443 nm and inorganic suspended solids (r = 0.64), confirming that IOPs are reliable water quality assessment indicators. Furthermore, the use of IOPs as variables for estimating water quality parameters such as Chl-a and suspended solids showed better performance compared to empirical methods.

In the context of ongoing discussions about climate change, the focus on beach resilience has gained significant attention in contemporary studies. However, a comprehensive understanding of beach resilience, particularly in the short term, remains limited. This study utilizes a dataset of 104 storm events in Hasaki beach, located on the East coast of Japan, to investigate the 10-day beach recovery. The study considers four types of distinct beach profile patterns based on sandbar formations. Employing XGBoost and the SHAP explanation method, the influence of morphometric indicators on beach resilience were explored. Resilient beach profiles are anticipated to exhibit rapid recovery following erosional storm events. The results reveal that morphometrics play a crucial role in determining the short-term, 10-day, recovery of beaches, with specific morphometric features demonstrating pronounced effects based on profile patterns. The study contributes to the current knowledge of post-storm beach recovery and provides insights that could inform discussions on beach resilience.

In order to estimate the possible parameters of future extreme extratropical cyclones (ETCs), a pseudo-climate modelling study of three historical storms originating from the Atlantic Ocean and one from the Black Sea area was performed using multi-model approach considering IPCC emission scenarios RCP4.5 and RCP8.5 for the twenty-first century. Applying Weather Research and Forecasting atmosphere model (WRF), Finite Volume Community Ocean model (FVCOM-SWAVE) and the Simulating WAves Nearshore (SWAN) model, the changes in initial conditions in atmospheric air temperature, sea surface temperature and relative humidity were considered on the basis of 14 CMIP5 general circulation models ensemble. According to the future scenario results, no notable changes are expected in minimum atmospheric pressure within the ETCs of the future; however, the low pressure area was slightly larger and the strong wind zone was extending further south with greater peak wind speeds in the future (year 2081–2100) simulations. This, in turn, yielded a small surge height increase at Pärnu under RCP4.5 scenario; however, under RCP8.5 scenario the surge increase was up to 22–59 cm. Westerly approaching ETCs will bring more precipitation to the Baltic Sea area in the (warmer) future. In case of a southerly cyclone, the results were more mixed. An insignificant increase in wave heights during extreme storm conditions occurred. Although RCP8.5 future scenario is usually considered as unrealistic, the results of this study still suggest that the extreme ETCs may become more dangerous in the future, although probably not as certainly as tropical cyclones.

The deltaic coast of Myanmar was severely hit by tropical cyclone Nargis in May 2008. In the present study, a top-down numerical simulation approach using the Weather Research and Forecasting (WRF) and Simulating WAves Nearshore (SWAN) models was conducted to study the meteorological and offshore wave characteristics of cyclone Nargis near the coast of Myanmar. The WRF simulation results agree well with the observed data from the India Meteorological Department. SWAN simulation results were compared with the WaveWatch 3 model by National Oceanic and Atmospheric Administration and validated against available measurement data from satellites. The model results show relatively good agreement, and hindcast with satellites data (significant wave height only) shows a correlation coefficient value of 0.89. The SWAN and satellite comparisons also show better fit for high wave conditions. The resulted maximum significant wave height of 7.3 m by SWAN is considerably higher in energy than the seasonal waves normally prevalent at Myanmar’s deltaic coast. The possibility of high energy waves due to cyclones should be considered during the design and operation of coastal and offshore projects in the area, particularly given the risks that climate change can intensify cyclones in the future. Since Myanmar lacks a dense network of in-situ observational stations, the methodology used in the current study presents the potential application of various numerical techniques and satellite data to estimate extreme wave conditions near the Myanmar coast.

A correction to this paper has been published: https://doi.org/10.1007/s11069-021-04687-9

Due to gradual sea level rise and changes in the climate system, coastal vulnerability to storm surge hazards is expected to increase in some areas. Studies regarding the effect of storm surge inundation on buildings and human lives, especially when it comes to relatively low-threat level events, have been few, however. In this research, storm surge load impact around coastal residential areas was quantitatively assessed, through fine-resolution numerical modelling. Meso- and street-scale simulation results for a storm surge event in Nemuro, Japan, were comprehensively validated against observations and field measurements, and the simulation results showed good accuracy for sea level, significant wave height and inundation area. A fine-resolution, street-scale coastal flood simulation was carried out with individual and grouped buildings, created with a building block model, and the results showed the significant role of buildings by realistically capturing inundation dynamics. Hydrodynamic results showed that coastal flood impact on buildings was insignificant (consistent with surveys). Lastly, the potential flood impact on people in the streets was investigated, using five human instability equations, where the most pessimistic results showed average values between 0.0 and 0.2 (max 0.6–0.7), and slightly below 0.4 for children and the elderly, respectively. These values indicated that threat levels during the Nemuro storm event were low, which corresponded with observations (no fatalities). This study framework could be applied wherever an accurate local storm surge threat estimate was required.

Bangladesh, one of the most vulnerable countries to climate change, has been experiencing significant climate change-induced risks. Particularly, the northwest region of the country has been severely affected by climate extremes, including droughts and heat waves. Therefore, proper understanding and assessment of future climate change scenarios is crucial for the adaptive management of water resources. The current study used the statistical downscaling model (SDSM) to downscale and analyze climate change-induced future changes in temperature and precipitation based on multiple global climate models (GCMs), including HadCM3, CanESM2, and CanESM5. A quantitative approach was adopted for both calibration and validation, showing that the SDSM is well-suited for downscaling mean temperature and precipitation. Furthermore, bias correction was applied to enhance the accuracy of the downscaled climate variables. The downscaled projections revealed an upward trend in mean annual temperatures, while precipitation exhibited a declining trend up to the end of the century for all scenarios. The observed data periods for the CanESM5, CanESM2, and HadCM3 GCMs used in SDSM were 1985–2014, 1975–2005, and 1975–2001, respectively. Based on the aforementioned periods, the projections for the next century indicate that under the CanESM5 (SSP5-8.5 scenario), temperature is projected to increase by 0.98 °C, with a 12.4% decrease in precipitation. For CanESM2 (RCP8.5 scenario), temperature is expected to rise by 0.94 °C, and precipitation is projected to decrease by 10.3%. Similarly, under HadCM3 (A2 scenario), temperature is projected to increase by 0.67 °C, with a 7.0% decrease in precipitation. These downscaled pathways provide a strong basis for assessing the potential impacts of future climate change across the northwestern region of Bangladesh.

Weather Research and Forecasting atmosphere model and Finite Volume Community Ocean Model were for the first time used under the pseudo-climate simulation approach, to study the parameters of an extreme storm in the Baltic Sea area. We reconstructed the met-ocean conditions during the historical storm Gudrun (which caused a record-high +275 cm surge in Pärnu Bay on 9 January 2005) and simulated the future equivalent of Gudrun by modifying the background conditions using monthly mean value differences in sea surface temperature (SST), atmospheric air temperature and relative humidity from MIROC5 in accordance with the IPCC scenarios RCP4.5 and RCP8.5 for 2050 and 2100. The simulated storm route and storm surge parameters were in good accordance with the observed ones. Despite expecting the continuation of recently observed intensification of cyclonic activity in winter months, our numerical simulations showed that intensity of the strongest storms and storm surges in the Baltic Sea might not increase by the end of twenty-first century. Unlike tropical cyclones, which derive their energy from the increasing SST, the extratropical cyclones (ETCs) harvest their primary energy from the thermal differences on the sides of the polar front, which may decrease if the Arctic warms up. For climatological generalizations on future ETCs, however, it is necessary to re-calculate a larger number of storms, including those with different tracks and in different thermal conditions.

We analyse a 36-year hydrodynamic and morphological dataset from the Hasaki coast, Japan, comprising 501 wave storm events (405 individual and 96 clustered events) to investigate the impact of storm dynamics and clustering on beach erosion. Focusing on the wave component of storms, events are identified using wave height thresholds. Daily and weekly beach profile measurements from the Hasaki Oceanographic Research Station are used to quantify erosion. The study examines the seasonal influences on Hasaki beach, the characteristics and temporal evolution of storms, and their associated erosional impacts. Moreover, we test two supervised machine learning (ML) algorithms, support vector regression (SVR), and deep neural network (DNN), in predicting shoreline change using 16 wave, storm, and morphological features. SVR showed reasonable accuracy on the training dataset but underperformed on testing, while DNN failed to produce reliable predictions on both. With SVR yielding an R 2 of 0.18 and DNN 0.27 on the testing dataset, we conclude that, given the limited data and available features, such ML models may not generalise well. However, separate analyses using observed data reveal clear seasonal variations in wave storm dynamics and distinct behaviours of clustered events associated with beach erosion, highlighting important insights beyond the ML results.

The extratropical cyclone (ETC) of August 2015 in central Chile was investigated using the WRF model to analyze the sensitivity of meteorological variables to different physical parameterization schemes. This study assesses the performance of different physical schemes in the simulation of track, core pressure, mean sea level pressure, wind direction and wind speed associated with ETC over the South Pacific. The analysis uses a total of 36 sensitivity experiments, consisting of: two microphysics schemes; three surface layer and planetary boundary layer; two cumulus schemes; two longwave and shortwave radiation; and Noah for land surface. Sensitivity experiments indicate that the cumulus, planetary boundary layer and surface layer scheme have a fundamental role in the characterization of ETC track and intensity, while the microphysics scheme plays a secondary role in determining these variables. On the other hand, long‐ and shortwave radiation do not have a significant impact. The sensitivity experiments indicate that exp24 provides the best results overall. The results of this work allow the selection time of the different physical schemes to be optimized according to the ETC characteristics that are to be simulated Key Points Multivariable analysis of the different physical schemes Representation of extratropical cyclone characteristics Effect of the physical parameterization on extratropical cyclone genesis and intensification