Sensitivity Experiments Research Articles

Impact of human-induced alterations in bathymetry and geometry on tidal and salt dynamics: Thresholds for morphological dimensions in a convergent estuary

Estuary morphology changes significantly with intensive human intervention, resulting in dynamic structural variations in the estuary. However, little is known about the threshold sizes of estuary morphology that ensure water security. A two-dimensional width-averaged semi-analytical model is applied to explore the impacts of human-induced alterations in bathymetry and geometry on tidal and salt dynamics in Lingdingyang Bay (LDYB). Salt flux (Fs) is positively correlated with tidal flux (Ft) and negatively correlated with tidal energy flux (Fte). Greater geometric convergence reduces Ft and increase Fte. Increased water depth increases Ft and Fte. Thus, both greater geometric convergence and increased bathymetry enhance tidal hydrodynamics. Saltwater transport is weakened by greater geometric convergence and enhanced by increasing water depth. Sensitivity experiments are conducted using maximum water level and salt intrusion length as the criterion. Thresholds for morphological sizes in the LDYB are found to be a convergence ratio (convergence length over mouth width,LcB0) of 0.83–0.88 and a combined depth factor (α) of 1.04–1.07. Moreover, transition of the estuarine morphology from an exponential convergent shape to a prismatic shape had a limited effect on tidal hydrodynamics when the convergent length rate (e-folding convergence length over total convergence length,LeLc) is >0.61. These results notice that human activities, such as reclamation and tidal channel dredging, exacerbate the risk of salt intrusion and should be applied with caution.

Reconstruction of the Temperature Index Series of China in 1368–1911 based on REACHES database

This study reports the methodology for reconstructing anomalous temperature index series of China in 1368–1911 based on the REACHES database which digitizes the Chinese records quoted in the Compendium of Meteorological Records of China in the Last 3000 Years. The reconstruction adopts an ordinal scale index approach ranging from −2 (very cold) to 1 (warm). Based on the grading criteria, a total of 12,871 records were retrieved through a standard coding system established at REACHES. Sensitivity experiments were performed to test robustness of the index system and a reasonability test was conducted to develop an appropriate method for deriving areal mean temperature index. The reconstructed series were validated through comparison with early instrumental data from Global Historical Climatology Network which shows good correlations and reliability of the REACHES reconstructed index data. Annual and semi-annual (winter and summer) temperature index data series were released for the whole domain as well as the 3- and 15-subregion geographical domains in China.

Uncovering the interannual predictability of the 2003 European summer heatwave linked to the Tibetan Plateau

Known as the Third Pole, the Tibetan Plateau (TP) significantly influences global weather and climate, but its potential for improving subseasonal-to-interannual predictions remains underexplored. Through coupled climate simulations and hindcast experiments, we uncovered interannual predictability of the 2003 European summer heatwave that persisted from June to August with devastating impacts. Hindcasts initialized from the atmosphere, land, and ocean states of a coupled simulation that assimilates soil moisture and soil temperature data over the TP show substantial skill in predicting this heatwave two years in advance. Hindcast sensitivity experiments isolated the indispensable role of the spring TP snow cover anomalies and their impact on the Atlantic and Pacific Oceans in exciting the Rossby waves that contributed to the anomalous European summer temperature. These findings highlight the dominant and remote influence of the TP and motivate research on its role in enhancing the predictability of extreme events worldwide.

Arctic climate response to European radiative forcing: a deep learning study on circulation pattern changes

Abstract. Heterogeneous radiative forcing in mid-latitudes, such as that exerted by aerosols, has been found to affect the Arctic climate, though the mechanisms remain debated. In this study, we leverage deep learning (DL) techniques to explore the complex response of the Arctic climate system to local radiative forcing over Europe. We conducted sensitivity experiments using the Max Planck Institute Earth System Model (MPI-ESM1.2) coupled with atmosphere–ocean–land-surface components. Large-scale circulation patterns can mediate the impact of the forcing on Arctic climate dynamics. We employed a DL-based clustering approach to classify large-scale atmospheric circulation patterns. To enhance the analysis of how these patterns impact the Arctic climate, the poleward moist static energy transport (PMSET) associated with the atmospheric circulation patterns was incorporated as an additional similarity metric in the clustering process. Furthermore, we developed a novel method to analyze the circulation patterns' contributions to various climatic parameter anomalies. Our findings indicate that the negative radiative forcing over Europe alters existing circulation patterns and their occurrence frequency without introducing new ones. Specifically, our analysis revealed that while the regional radiative forcing alters the occurrence frequencies of the circulation patterns, these changes are not the primary drivers of the forcing's impact on the Arctic parameters. Instead, it is the shifts in the mean spatial characteristics of the atmospheric circulation patterns, induced by the forcing, that predominantly determine the effects on the Arctic climate. Our methodology facilitates the uncovering of complex, nonlinear interactions within the climate system, capturing nuances that are often obscured in broader seasonal anomaly analyses. This approach enables a deeper understanding of the dynamics driving observed climatic anomalies and their links to specific atmospheric circulation patterns.

The Roles of Moat Width and Outer Eyewall Contraction in Affecting the Timescale of Eyewall Replacement Cycle

AbstractThe timescale of eyewall replacement cycle (ERC) is critical for the prediction of intensity and structure changes of tropical cyclones (TCs) with concentric eyewall (CE) structures. Previous studies have indicated that the moat width can regulate the interaction between the inner and outer eyewalls and has a salient relationship with the ERC timescale. In this study, a series of sensitivity experiments are carried out to investigate the essential mechanisms resulting in the diversity of the duration of CEs using both simple and full‐physics models. Results reveal that a larger moat can induce stronger inflow under the same inner eyewall intensity by providing a longer distance for air parcels to accelerate in the boundary layer. Thus, there is greater inward absolute vorticity flux to sustain the inner eyewall. Besides, the equivalent potential temperature (θe) budget indicates that the vertical advection and surface flux of moist entropy can overbalance the negative contribution from the horizontal advection and lead to an increasing trend of θe in the inner eyewall. This suggests that the thermodynamic process in the boundary layer is not indispensable to the inner eyewall weakening. It is also found that the contraction rate of the secondary eyewall, which directly influences the moat width, is subject to the activity of outer spiral rainbands. By directly introducing positive wind tendency outside the eyewall and indirectly promoting a vertically tilted eyewall structure, active convection in the outer region will impede or even suspend the contraction of the outer eyewall and hence extend the ERC timescale.

Influence of mesoscale sea‐surface temperature structures on the Mediterranean cyclone Ianos in convection‐permitting simulations: Contributions of surface warming and cold wakes

AbstractThis study examined the influence of mesoscale sea‐surface temperature (SST) structures and warming on the tropical‐like cyclone Ianos. The controlling mechanisms were investigated using a set of sensitivity experiments with the non‐hydrostatic weather research and forecasting model. A simulation forced by a high‐resolution SST field from the mesoscale eddy‐resolving HYCOM reanalysis (CTRLH) performed better than a simulation forced by a coarse‐resolution SST field from Optimum Interpolation Sea Surface Temperature (OISST) in terms of precipitation, wind intensity, and landfall location. The suppression of mesoscale SST variability affected the cyclone's intensity, its path, and associated processes. This effect depends on the nature of the anomalies (cold/warm). The suppression of mesoscale SST forcing intensified wind and precipitation in the presence of cold anomalies, leading to a northwestward shift of the storm's path during its mature phase. The magnitude of these changes varied with the scale of smoothing (mesoscale SST). Compared to the CTRLH simulation, a simulation in which a 60‐km smoothing filter was applied to the SST field resulted in a cyclone centered slightly to the west (or delayed by 3–6 hr), which was further shifted to the west (or delayed) when the smoothing filter was increased to 150 km. The intensification of wind and precipitation may be associated with the reduction in the storm's cold wake, which would lead to enhanced turbulent fluxes and increased atmospheric water vapor. These results highlight the role of small‐scale air–sea interaction processes that could have a strong impact on Mediterranean cyclones' path and intensity.

Contrasting the Penultimate Glacial Maximum and the Last Glacial Maximum (140 and 21 ka) using coupled climate–ice sheet modelling

Abstract. The configuration of the Northern Hemisphere ice sheets during the Penultimate Glacial Maximum differed to the Last Glacial Maximum. However, the reasons for this are not yet fully understood. These differences likely contributed to the varied deglaciation pathways experienced following the glacial maxima and may have had consequences for the interglacial sea level rise. To understand the differences between the North American Ice Sheet at the Last and Penultimate glacial maxima (21 and 140 ka), we perform two perturbed-physics ensembles of 62 simulations using a coupled atmosphere–ice sheet model, FAMOUS-ice, with prescribed surface ocean conditions, in which the North American and Greenland ice sheets are dynamically simulated with the Glimmer ice sheet model. We apply an implausibility metric to find ensemble members that match reconstructed ice extent and volumes at the Last and Penultimate glacial maxima. We use a resulting set of “plausible” parameters to perform sensitivity experiments to decompose the role of climate forcings (orbit, greenhouse gases) and initial conditions on the final ice sheet configurations. This confirms that the initial ice sheet conditions used in the model are extremely important in determining the difference in final ice volumes between both periods due to the large effect of the ice–albedo feedback. In contrast to evidence of a smaller Penultimate North American Ice Sheet, our results show that the climate boundary conditions at these glacial maxima, if considered in isolation, imply a larger Penultimate Glacial Maximum North American Ice Sheet than at the Last Glacial Maximum by around 6 m sea level equivalent. This supports the notion that the growth of the ice sheet prior to the glacial maxima is key in explaining the differences in North American ice volume.

Aerosol optical depth retrieval using scaled digital number (DN) values of multi-spectral satellite and a generating adversarial model based on deep learning application

ABSTRACT The current quantitative retrieval of Aerosol Optical Depth (AOD) typically uses Top-of-atmosphere (TOA) reflectance data obtained by the scale and offset terms of radiometric calibration. Errors can be introduced during the conversion of Digital Number (DN) values to TOA reflectance, restraining the accurate retrieval of AOD. Particularly when surface reflectance is high, conversion errors can significantly distort the retrieval of Aerosol Optical Depth (AOD), given the minimal impact of aerosols on the radiation detected by satellite sensors. To counteract this, we introduce an innovative retrieval algorithm that harnesses a Generative Adversarial Network (GANN), a deep learning (DL) model, to accurately derive AOD from the scaled digital number (DN) values of multi-spectral satellite imagery. The DL technology enables the use of scaled DN values for AOD retrieval, bypassing the conversion errors associated with TOA reflectance since it relies on a sample learning approach instead of radiative transfer calculations. To ensure the number and representativeness of training samples, a total of 37,103 samples from different underlying surfaces from 2014 to 2018 were obtained using a space-time matching strategy. Our K-cross validation demonstrates that employing DN values for AOD retrieval promises to yield higher accuracy compared to using TOA reflectance. Independent 2019 data were used to estimate GANN, MCD19A2 and MOD04_3K aerosol products. Our model showed superior performance compared to the other products in terms of a higher correlation (R = 0.8184) with AERONET AOD and obtaining more reliable retrievals (7601). The sensitivity experiment suggests that GANN exhibits limitations in areas characterized by high aerosol loads and heterogeneity. Our study can give a novel insight into AOD retrieval based on multi-spectral satellite and DL models.

Quantify Urbanization-Induced Precipitation and Runoff Anomalies over the Qinhuai River Basin of China: Sensitivity Experiments with WRF-Hydro

Quantify Urbanization-Induced Precipitation and Runoff Anomalies over the Qinhuai River Basin of China: Sensitivity Experiments with WRF-Hydro

Impacts of building modifications on the turbulent flow and heat transfer in urban surface boundary layers

This study examines turbulent airflow and upward heat transport in real urban environments using a building-resolving large-eddy simulation model to understand the characteristics of turbulent airflow and upward heat transport when geometrical distributions of buildings are modified. The target areas were two real urban districts within Osaka City, Japan, having different morphological features. In the numerical experiments, the initial condition was set to a neutral condition in which temperature is uniformly distributed vertically, and buildings emitted heat at a constant rate. The results in the two districts indicated that the features of turbulence and heat transport distinctly differed with different building arrangement. Specifically, taller buildings significantly decelerated airflows and induced warming behind buildings. More high-rise buildings (which resulted in a larger building variability) in a district with a larger building density caused a large heat flux and warming at higher levels. The sensitivity experiments in which a density and height variability of buildings were modified showed that a building density at higher levels and a building height variability significantly influenced warming at upper levels. An increased building height variability weakened wind speed and disturbed horizontal heat advection, whereas a large building density caused numerous heat sources.

Elucidating the impacts of aerosol radiative effects for mitigating surface O3 and PM2.5 in Delhi, India during crop residue burning period

Atmospheric aerosol radiative effects regulate surface air pollution (O3 and PM2.5) via both the aerosol–photolysis effect (APE) and the aerosol–radiation feedback (ARF) on meteorology. Here, we elucidate the roles of APE and ARF on surface O3 and PM2.5 in the heavily polluted megacity, Delhi, India by using a regional model (WRF-Chem) with constraints from limited surface observations. While APE reduces surface O3 (by 6.1%) and PM2.5 concentrations (by 2.4% via impeding the secondary aerosol formations), ARF contributes to a 2.5% and 17.5% increase in surface O3 and PM2.5, respectively. The ARF from smoke enhances PM2.5 (by 8%), black carbon (by 10%), and primary organic aerosol (by 18%) during late autumn when crop residue burning is significant. The synergistic APE and ARF have a negligible impact on the total concentrations of O3 and PM2.5. Hence, the reduction of PM2.5 may lead to O3 escalation due to weakened APE. Sensitivity experiments indicate the need and effectiveness of reducing VOC emission for the co-benefits of mitigating both O3 and PM2.5 concentrations in Delhi.

Impacts of Large-Scale Offshore Wind Farms on Tropical Cyclones: A Case Study of Typhoon Hato

Abstract With the rising global demand for renewable energy sources, a great number of offshore wind farms are being built worldwide, as well as in the northern South China Sea. There is, however, limited research on the impact of offshore wind farms on the atmospheric and marine environment, particularly tropical cyclones, which frequently occur in summertime in the South China Sea. In this paper, we employ the Weather Research and Forecasting (WRF) Model to investigate the impacts of large-scale offshore wind farms on tropical cyclones, using the case of Typhoon Hato, which caused severe damage in 2017. Model results reveal that maximum wind speeds in coastal areas decrease by 3–5 m s−1 and can reach a maximum of 8 m s−1. Furthermore, the wind farms change low-level moisture convergence, causing a shift in the precipitation center toward the wind farm area and causing a significant overall reduction (up to 16%) in precipitation. Model sensitivity experiments on the area and layout of the wind farm have been carried out. The results show that larger wind farm areas and denser turbine layouts cause a more substantial decrease in the wind speed over the coast and accumulated precipitation reduction, further corroborating our findings. Significance Statement This study holds significant implications for developing offshore wind farms in tropical cyclone-prone regions like the South China Sea. By focusing on Typhoon Hato as a case study, the research sheds light on the previously understudied relationship between large-scale offshore wind farms and tropical cyclones. The observed decrease in coastal wind speeds and altered precipitation patterns due to wind farm presence highlights the potential for mitigating cyclone-related risks in these regions. Additionally, the study’s sensitivity experiments underscore the importance of careful planning and design in optimizing wind farm layouts for maximum impact reduction. This research contributes vital insights into sustainable energy infrastructure development while minimizing environmental and meteorological risks in cyclone-prone areas.

Inter-annual changes in transboundary air quality from KORUS-AQ 2016 to SIJAQ 2022 campaign periods and assessment of emission reduction strategies in Northeast Asia

Northeast Asia suffers from high concentrations of particulate matter (PM), prompting nations to actively implement emission reduction policies. This study evaluated the recent inter-annual changes in the chemical transformation and transboundary transport of PM over Northeast Asia, based on both ground and aircraft measurements, as well as WRF-Chem simulations, during two comprehensive campaigns: the Korea–United States Air Quality (KORUS-AQ) campaign in 2016 and the Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) campaign in 2022, both conducted around the Korean Peninsula. Ground measurements in 2022 revealed significant reductions in air pollutants compared to 2016 levels. In the Beijing–Tianjin–Hebei region, PM2.5 and SO2 concentrations decreased by 47.2% and 73.9%, respectively, attributable to successful SOx and NOx emission reduction strategies. Similar trends were observed in downwind areas, including Seoul, where PM2.5 and SO2 levels declined by 30.0% and 41.4%, respectively. WRF-Chem model results indicated substantial decreases in sulfates, nitrates, and their precursors in both surface and upper atmosphere in 2022 compared to 2016. Moreover, model-calculated gas-to-particle conversion ratios, which peaked in the Yellow Sea in 2016, decreased by 15% in 2022 and shifted slightly eastward to the western Korean Peninsula. This shift suggests a potential decline in secondary PM formation processed in the Yellow Sea, coinciding with reduced long-range transport of gaseous pollutants. A comparison of model sensitivity experiments, accounting for both bottom-up emission changes and meteorological variations, revealed that while weather and climate factors such as precipitation and pressure patterns between 2016 and 2022 contributed to the overall decrease in PM concentrations, the primary driver was the reduction in emissions during this period. This study highlighted that the main driver of the substantial improvement in air quality over East Asia was the implementation of emission reduction policies targeting PM and its precursors in the main source regions in China.

The role of diabatic heating/cooling in outer rainbands in the secondary eyewall formation and evolution in a numerically simulated tropical cyclone

In this study, the role of diabatic heating/cooling in outer rainbands (ORBs) in the formation and evolution of the secondary eyewall of a numerically simulated tropical cyclone (TC) is investigated. This is done through a series of sensitivity experiments under idealized conditions using a high-resolution cloud-resolving atmospheric model. The results show that artificially increasing diabatic heating in rainbands enhances convective activities in ORBs and leads to an earlier secondary eyewall formation (SEF), and later the faster weakening and earlier dissipation of the primary eyewall. Reducing diabatic heating in ORBs weakens the rainbands and delays the SEF but prolongs the duration of the double eyewall structure if the SEF occurs. Reducing diabatic cooling in ORBs enhances convective activity in rainbands but has little effect on convection in the primary eyewall prior to the SEF. However, it results in a widened eyewall structure and a stronger TC after the eyewall replacement. Increasing diabatic cooling in ORBs largely suppresses convection in rainbands and prohibits the SEF. These results demonstrate that diabatic heating/cooling in ORBs plays important roles in the SEF and evolution. Since diabatic heating/cooling in rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the critical importance of large-scale environmental moist condition to the formation and evolution of secondary eyewall in TCs. In addition, it is also found that when the area-averaged diabatic heating rate in ORBs becomes similar in magnitude to that in the primary eyewall, the secondary eyewall forms. Plain language summaryPrevious studies have demonstrated the importance of diabatic heating/cooling in outer rainbands to the structure and intensity changes of tropical cyclones (TCs) with a single eyewall. It is unclear whether and how diabatic heating/cooling in outer rainbands may affect the formation and evolution of the secondary eyewall in TCs. These issues have been addressed based on a series of sensitivity experiments under idealized conditions using a high-resolution atmospheric model. Results show that diabatic heating in outer rainbands is favorable for the secondary eyewall formation (SEF). Increasing diabatic heating in outer eyewall can lead to faster weakening and thus earlier dissipation of the primary eyewall. Diabatic cooling in outer rainbands suppresses convection in outer rainbands and prohibits the SEF. Since diabatic heating/cooling in outer rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the importance of the large-scale environmental moist condition to the SEF of TCs. We also found that when the area-averaged diabatic heating rate in outer rainbands becomes similar in magnitude to that in the primary eyewall, the secondary eyewall would form, which can be considered as a measure of the SEF in TCs. Key points1.Increasing diabatic heating in outer rainbands leads to earlier SEF, and faster weakening and earlier dissipation of the primary eyewall.2.Increasing diabatic cooling in outer rainbands suppresses convective activity in outer rainbands and is unfavorable for the SEF.3.When the area-averaged diabatic heating rate in outer rainbands and the eyewall become similar in magnitude, the secondary eyewall forms.

Chinese ink-coated elastic PU/PET fibers as multifunctional flexible wearable sensors

Textiles as conductive substrates are widely used in sensing applications due to their good elasticity, high stretchability and recoverable deformation. Here, the mask rope (polyurethane/polyester blended fibers) was selected as flexible substrate to load of conductive Chinese ink using surface swelling technique in N, N-dimethylformamide. The presence of carbon nanoparticles in the ink imparts electrical conductivity to the elastic fiber while maintaining the mechanical properties and extensibility of the fiber. This simple and low-cost method allows excellent interfacial adhesion between the conductivity ink layer and the elastic fibers, and the carbon particles do not fall off even when the modified fiber was treated by sonication in water. The ink coated elastic fiber as strain sensor shows excellent stability and sensitive responsiveness after 500 stretch-release cycles. The response and recovery times during the sensitivity experiment of the flexible fiber sensor are 133.79 and 134.76 ms. The sensor exhibits physiological motion detection and quality monitoring capabilities, which can accurately monitor human movements such as walking, wrist movement, throat swallowing and articulation. The sensor also has a good Joule heating effect, and the temperature of the conductive fiber can increase 88.9°C in the 60s under 15V voltage. This work develops a simple and efficient, low-cost, mass-producible flexible sensor with potential for physiological activity, temperature, and humidity detection.

Evaluation of the Aggregation Efficiency Modeling at Colder Atmospheric Temperatures in Comparison to Satellite Observations

Abstract Aggregation efficiency in the upper troposphere is highly uncertain because of the lack of laboratory experiments and aircraft measurements, especially at atmospheric temperatures below −30°C. Aggregation is physically broken down into collision and sticking. In this study, theory-based parameterizations for the collision efficiency and sticking efficiency are newly implemented into a double-moment bulk cloud microphysics scheme. Satellite observations of the global ice cloud distribution are used to evaluate the aggregation efficiency modeling. Sensitivity experiments of 9-day global simulations using a high-resolution climate model show that the use of collision efficiency parameterization causes a slight increase in the cloud ice amount above the freezing level over the tropics to midlatitudes and that the use of our new sticking efficiency parameterization causes a significant increase in the cloud ice amount and a slight decrease in the snow amount particularly in the upper troposphere over the tropics. The increase/decrease in the cloud ice/snow amount in the upper troposphere over the tropics is consistent with the vertical profile of radar echoes. Moreover, the ice fraction of the cloud optical thickness is still underestimated worldwide. Finally, the cloud radiative forcing increases over the tropics to reduce the bias in the radiation budget. These results indicate that our new aggregation efficiency modeling reasonably functions even at atmospheric temperatures below −30°C; however, further improvements in the ice cloud modeling are needed. Significance Statement Long-standing biases in the radiative budget in climate models indicate the existence of a missing mechanism to realistically represent the ice cloud growth in the upper troposphere. This study focuses on aggregation efficiency, which has been assumed to be a tuning parameter to optimize the global radiative budget. Therefore, this study employs a theory-based parameterization to calculate the aggregation efficiency. According to the parameterization, aggregation efficiency in high clouds varies by the growth stage of the individual ice particles. As a result, small ice crystals are likely to grow more slowly, and the lifetime of cirrus clouds is prolonged to enhance cloud radiative forcing, particularly over the tropics. These results are promising for reducing the biases observed in climate models.

Long-Term Effects of 90Sr and 239+240Pu Contaminated on the Seafloor Sediment on the Transfer through Marine Food Web: Sensitivity to the Physical Property- and Sediment-Related Parameters

This study, as a follow-up to the <sup>137</sup>Cs study of Kim et al. (2023), performs a set of sensitivity experiments on ocean physical properties and sediment-related parameters based on initial bottom contamination of <sup>90</sup>Sr and <sup>239+240</sup>Pu in the upper sediment layer. Both studies utilizes the Extended BURN model proposed by Bezhenar et al. (2016). The initial contamination levels were set to 3 and 0.4 Bq/kg, respectively, based on observations off the coast of Fukushima. The sensitivity experiments were divided into EXP-WOHAD, which examined the effects of the vertical diffusion coefficient and vertical sediment flux, and EXP-WHAD, which investigated the effects of ocean currents. The results of the EXP-WOHAD experiments showed that both radionuclides are more sensitive to sediment fluxes than to vertical diffusion coefficients. For both <sup>90</sup>Sr and <sup>239+240</sup>Pu, transport was dominated by transport to the intermediate sediment layer rather than to seawater. Specifically, for <sup>239+240</sup>Pu, transport to seawater was insignificant due to its strong sorption properties in sediments. In terms of bioaccumulation, <sup>90</sup>Sr accumulated most in fish and invertebrates, while <sup>239+240</sup>Pu accumulated most in invertebrates, followed by zooplankton. Notably, <sup>239+240</sup>Pu showed high bioaccumulation despite its low initial sediment contamination. The changes in radioactivity concentrations in the EXP-WHAD experiments were similar to those in the EXP-WOHAD experiments, and the bioaccumulation trends in biota were also comparable. This study confirms that the accumulation of radionuclides in seawater, intermediate sediments, and biota is sensitive to the marine physical environment and varies by nuclide. When the sediment flux increased by a factor of 100, the remaining radioactivity levels of <sup>90</sup>Sr and <sup>239+240</sup>Pu in biota after 100 years showed a significant reduction, decreasing by more than 900 and 30,000 times, respectively; it highlighting the importance of parameterization according to the physical environment of the area of interest.

A New Ecosystem Model for Arctic Phytoplankton Phenology From Ice‐Covered to Open‐Water Periods: Implications for Future Sea Ice Retreat Scenarios

AbstractTo predict ecosystem change in the Arctic Ocean, understanding Arctic phytoplankton phenology is essential. We develop a marine ecosystem model focusing on phytoplankton dynamics and the competition for multiple resources based on knowledge from in situ data obtained in the Chukchi Sea. The model is designed to include the unique ecological characteristics of the Arctic Ocean. To the best of our knowledge, this is the first model successfully simulating the current paradigm for Arctic phytoplankton phenology, including both under‐ice blooms and succession of phytoplankton groups. Sensitivity experiments show that the dominance of diatoms can be sustained by lateral transport of a high‐silicate water mass (Pacific Winter Water). Experiments for future scenarios show that sea ice retreat drives a decrease in large diatoms and an increase in the other relatively small non‐diatom groups. These results suggest that dominant phytoplankton groups can be shifted from diatoms to non‐diatoms under ongoing Arctic Ocean sea ice retreat.

Optimization of snow-related processes in Noah-MP land surface model over the mid-latitudes of Asian region

Snow plays a critical role in modulating surface energy, water cycles, and climate prediction. Optimizing snow-related parameterizations can enhance the model behaviors in simulating snow-related physical processes and reduce the cold bias observed in winter climate simulations in the Northern Hemisphere. In this study, the topographic complexity and wind speed were incorporated into the parameterization of the snow cover fraction (SCF) and newly fallen snow density (SFD) respectively within the Noah with multi-parameterization (Noah-MP) LSM to optimize the simulation of snow-related processes in the mid-latitude regions of East Asia. A control simulation and three sensitivity experiments were conducted to investigate and quantify the effects of topographic complexity and wind speed on the simulation of snow-related processes and land surface temperature (LST) against MODIS products. The results showed that modifications to the two schemes effectively mitigated the overestimation of snow cover and albedo, and alleviated cold biases in the most of study area. The influence of SFD scheme considering wind speed was more pronounced in regions with more snowfall and higher wind speed, while the SCF scheme considering topographic complexity showed a more widespread effect. The combination of these two modified schemes yielded the best performance. The mean biases of SCF, albedo, and LST over the entire study region with both modified schemes were reduced by 0.126 (∼63 %), 0.044 (∼41 %), and 0.584 °C (∼18 %), respectively. Their RMSEs were reduced by 0.119 (∼36 %), 0.036 (∼22 %), and 0.489 °C (∼10 %), respectively. This study highlights the importance of wind conditions and topographic complexity in the simulations of snow-related characteristics over the mid-latitudes of Asian region.

Modeling Across Scales of Heavy Precipitation With a Global Variable‐Resolution Model: A Case Study of a Catastrophic Event in China

AbstractAn unprecedented heavy rainfall event in China (“21.7” extreme rainfall event) was simulated using the global variable‐resolution model (MPAS‐Atmosphere) across the scales (4, 8, 16 and 50 km). Although almost all experiments at different resolutions reproduce the spatiotemporal characteristics of precipitation, the simulated precipitation intensity from high to low is 16, 8, 50, and 4 km, with the 16 km simulation being closest to the observations. Precipitation magnitude is prominently influenced by the difference in simulated large‐scale circulation across a range of grid spacings. Further analysis revealed that the differences in latent heating across scales affect the geopotential height and wind field by altering temperature. The latent heating in 4 km simulation is the minimum while the 16 km simulation is maximum. More latent heating release leads to the low‐level pressure depression, amplifies the water vapor flux convergence, produces stronger upward motion and more clouds, and ultimately results in stronger precipitation. The sensitivity experiments for turning off latent heating tendencies during the event showed that the latent heat release has positive feedback on the “21.7” heavy rainfall event. This study highlights the importance of scale‐awareness of latent heat at different resolutions and suggests that the difference in simulated latent heat release during the event is the main reason for simulated different atmospheric circulation and precipitation across scales.