Horizontal Resolution Research Articles

Soil property recovery from incomplete in-situ geotechnical test data using a hybrid deep generative framework

Geotechnical testing serves to assess the strength and stiffness of in-situ soils, for purposes such as informing foundation design. Despite its importance, time constraints, financial considerations, and site-specific limitations often restrict testing to isolated locations with limited horizontal resolution. Therefore, this paper presents a novel hybrid generative deep learning model designed to approximate soil properties across sites based on sparsely sampled geotechnical data. The model uses geological subsurface samples derived from random field theory as ‘a priori’ data for a conditional variational auto-encoder (CVAE) model. By doing so, it attempts to map the relationship between in-situ data and the corresponding spatial coordinates, as well as the inherent link between in-situ data and spatial distribution. Then, in the post-processing phase, a Kriging model interpolates minor discrepancies between the measured and predicted values. To demonstrate its practical application, this paper focuses on cone penetration testing (CPT) as the geotechnical test method. The model's development is thoroughly discussed, followed by the validation using in-situ data and an analysis conducted with synthetic data. It is shown that the uncertainty associated with CVAE-Kriging depends upon both the distance from the sample point and the site's inherent complexity. The proposed methodology not only offers refined subsurface modeling but also expands the understanding of uncertainty in geotechnical testing. Practically, it can assist geotechnical engineers with insights during the survey phase.

Simulation of Track and Landfall Process of Severe Cyclonic Storm Mora over the Bay of Bengal using WRF-ARW Model

The simulations of Severe Cyclonic Storm (SCS) Mora (28-31 May 2017) generated over the Bay of Bengal (BoB) are performed in this study to analyze its features, landfall, and track using the Weather Research and Forecasting (WRF) model. WRF-ARW model has been used on a 10 km Horizontal Resolution (HR) domain for 96, 72, 48, and 24-hour lead time simulations. The model's performance is assessed by examining Mean Sea Level Pressure (MSLP), vertical distribution of velocity components, wind flow pattern, relative vorticity, vertical wind shear, relative humidity, latent heat flux at the surface, and track pattern. The simulated results are compared carefully to the observations from the Bangladesh Meteorological Department (BMD) and the India Meteorological Department (IMD). The findings are reasonably consistent with the observations. The simulated track is also reasonable even up to 72 hours in advance. Finally, the study's results suggest that the WRF model can be used as an effective tool in predicting TCs over the BoB.
 Dhaka Univ. J. Sci. 71(2): 142-152, 2023 (July)

Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba

The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.

Performance evaluation of lightning potential index and flash count using WRF microphysical parameters over Rajasthan and West Bengal, India

Accurate lightning prediction stands as a pressing global challenge, demanding robust solutions for safeguarding lives and valuable assets. In this study, we employ the mesoscale numerical model, Weather Research and Forecasting (WRF-ARW, version 4.0.3), to conduct numerical simulations of lightning occurrences during the 2021 monsoon season in Hooghly (on 07 June) and Jaipur (on 11 July). These events resulted in 31 and 11 casualties, respectively. The WRF model is integrated at horizontal resolutions of 9 km and 3 km for both regions, utilizing six-hourly NCEP-FNL datasets at a 0.25º resolution. The primary objective of this inquiry is to identify the most suitable microphysics scheme among WSM-6, NSSL-2, and MORRISON for a comprehensive assessment of lightning activity. Model performance is meticulously evaluated through skill scores, including Equitable Threat Score (ETS), False Alarm Rate (FAR), Accuracy (ACC), and Probability of Detection (POD), focusing specifically on hourly rainfall. Furthermore, a comprehensive spatial evaluation assesses the Lightning Potential Index and lightning flash count using the McCaul Method. The model-simulated results effectively depict lightning conditions in both regions, showing slight spatial and temporal discrepancies compared to observational datasets. Validation of the simulated lightning flash count is accomplished using data from the Lightning Detection Network (LDN) operated by the Indian Institute of Tropical Meteorology (IITM). The NSSL-2 microphysical scheme demonstrates noteworthy efficacy in identifying lightning occurrences in both regions. Rainfall representations correspond remarkably well with Indian Monsoon Data Assimilation and Analysis (IMDAA) data, indicating precipitation levels of 20–40 mm and 70–80 mm in Jaipur and Hooghly, respectively. The NSSL-2 microphysics scheme exhibits commendable proficiency, with consistently high model skill scores (ACC and POD ∼0.9) for lightning events. This study signifies a significant step toward the development of an operational lightning warning system, offering the potential to substantially reduce the risks associated with lightning occurrences. Consequently, such a system has the capacity to enhance safety and preparedness measures for regions affected by lightning phenomena.

A transient coupled general circulation model (CGCM) simulation of the past 3 million years

Abstract. Driven primarily by variations in the earth's axis wobble, tilt, and orbit eccentricity, our planet experienced massive glacial/interglacial reorganizations of climate and atmospheric CO2 concentrations during the Pleistocene (2.58 million years ago (Ma)–11.7 thousand years ago (ka)). Even after decades of research, the underlying climate response mechanisms to these astronomical forcings have not been fully understood. To further quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model version 1.2 (CESM1.2, ∼3.75∘ horizontal resolution), which covers the climatic history of the past 3 million years (3 Myr). In addition to the astronomical insolation changes, CESM1.2 is forced by estimates of CO2 and ice-sheet topography which were obtained from a simulation previously conducted with the CLIMBER-2 earth system model of intermediate complexity. Our 3 Ma simulation consists of 42 transient interglacial/glacial simulation chunks, which were partly run in parallel to save computing time. The chunks were subsequently merged, accounting for spin-up and overlap effects to yield a quasi-continuous trajectory. The computer model data were compared against a plethora of paleo-proxy data and large-scale climate reconstructions. For the period from the Mid-Pleistocene Transition (MPT, ∼1 Ma) to the late Pleistocene we find good agreement between simulated and reconstructed temperatures in terms of phase and amplitude (−5.7 ∘C temperature difference between Last Glacial Maximum and Holocene). For the earlier part (3–1 Ma), differences in orbital-scale variability occur between model simulation and the reconstructions, indicating potential biases in the applied CO2 forcing. Our model-proxy data comparison also extends to the westerlies, which show unexpectedly large variance on precessional timescales, and hydroclimate variables in major monsoon regions. Eccentricity-modulated precessional variability is also responsible for the simulated changes in the amplitude and flavors of the El Niño–Southern Oscillation. We further identify two major modes of planetary energy transport, which played a crucial role in Pleistocene climate variability: the first obliquity and CO2-driven mode is linked to changes in the Equator-to-pole temperature gradient; the second mode regulates the interhemispheric heat imbalance in unison with the eccentricity-modulated precession cycle. During the MPT, a pronounced qualitative shift occurs in the second mode of planetary energy transport: the post-MPT eccentricity-paced variability synchronizes with the CO2 forced signal. This synchronized feature is coherent with changes in global atmospheric and ocean circulations, which might contribute to an intensification of glacial cycle feedbacks and amplitudes. Comparison of this paleo-simulation with greenhouse warming simulations reveals that for an RCP8.5 greenhouse gas emission scenario, the projected global mean surface temperature changes over the next 7 decades would be comparable to the late Pleistocene glacial-interglacial range; but the anthropogenic warming rate will exceed any previous ones by a factor of ∼100.

GIS-Based RUSLE Reservoir Sedimentation Estimates: Temporally Variable C-Factors, Sediment Delivery Ratio, and Adjustment for Stream Channel and Bank Sediment Sources

The empirical Revised Universal Soil Loss Equation (RUSLE) has been adapted to geographical information system (GIS) frameworks to study the spatial variability of soil erosion across landscapes and has also been used to estimate reservoir sedimentation. The literature presents contradictory results about the efficacy of using RUSLE in a GIS context for quantifying reservoir sedimentation, requiring further evaluation and validation of its estimates relative to measured reservoir sedimentation. Our primary objective was to determine if these contradictory results may be a function of the RUSLE’s inability to account for sediments derived from gullies, stream channels, or stream banks; the temporal variability of some of RUSLE’s empirically based factors such as the land cover/land management (C-) factor; and in some model renditions, the choice of value for the sediment delivery ratio (SDR). The usefulness of adjusting these estimates using a regional representative value of gully/stream bank sediment contributions was also assessed. High-spatial horizontal resolution (2 m) digital elevation models (DEMs) for 12 watersheds were used together with C-factor data for five representative years in a GIS-based RUSLE model that incorporates SDR within a sediment routing routine to study the impacts of choice of C-factor and SDR on reservoir sedimentation estimates. Choice of image date for developing C-factors was found to impact reservoir estimates. We also found that the value of SDR for some of the study watersheds would have to be unrealistically small to produce sedimentation estimates comparable to measured values. Estimates of reservoir sedimentation were comparable to measured data for 5 of the 12 watersheds, when the regionally based adjustment for gully/stream bank contributions was applied. However, differences remained large for the remaining seven watersheds. Statistical analysis revealed that certain combinations of geomorphic, pedologic, or topographic variables could be used to predict the degree of sediment underestimation with a significant and high level of correlation (0.72 < R2 ≤ 0.99; p-value < 0.05). Our findings indicate that the level of agreement between GIS-based RUSLE estimates of reservoir sedimentation and measured values is a function of watershed characteristics; for example, the area-weighted soil erodibility (K-) factor of the soils within the watershed and stream channels, the stream entrenchment ratio and bank full depth, the percentage of the stream corridor having slopes ≥ 21°, and the width of the stream flood way as a percentage of the watershed area. Within the context of GIS, these metrics are easily obtained from digital elevation models and publicly available soils data and may be useful in prioritizing reservoirs’ assessments for function and safety.

Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling

Abstract. Modeling ice sheet instabilities is a numerical challenge of potentially high real-world relevance. Yet, differentiating between the impacts of model physics, numerical implementation choices, and numerical errors is not straightforward. Here, we use an idealized North American geometry and climate representation (similarly to the HEINO (Heinrich Event INtercOmparison) experiments – Calov et al., 2010) to examine the process and numerical sensitivity of ice stream surge cycling in ice flow models. Through sensitivity tests, we identify some numerical requirements for a more robust model configuration for such contexts. To partly address model-specific dependencies, we use both the Glacial Systems Model (GSM) and the Parallel Ice Sheet Model (PISM). We show that modeled surge characteristics are resolution dependent, though they converge (decreased differences between resolutions) at finer horizontal grid resolutions. Discrepancies between fine and coarse horizontal grid resolutions can be reduced by incorporating sliding at sub-freezing temperatures. The inclusion of basal hydrology increases the ice volume lost during surges, whereas the dampening of basal-temperature changes due to a bed thermal model leads to a decrease.

Future projections of extreme precipitation in Tropical America and Panama under global warming based on 150‐year continuous simulations using 20‐km and 60‐km atmospheric general circulation models

AbstractThis study explores future changes in extreme precipitation across tropical America and Panama using 150‐year continuous experiments run on the Meteorological Research Institute atmospheric general circulation model at horizontal resolutions of 20 km (AGCM20) and 60 km (AGCM60). Tropical America is a warming hotspot where the mean seasonal precipitation amounts are decreasing, but annual maximum daily precipitation amounts are following an increasing trend. In Panama, future climates simulated using AGCM20 and AGCM60 show an increase in December–January–February (DJF) precipitation over eastern Panama, and a decrease in June–July–August (JJA) precipitation over western areas near the Pacific coast. Annual maximum daily precipitation increases on the eastern side of the country in both models. The mean annual maximum daily precipitation for tropical America shows decadal oscillations, similar to the global mean but with smaller amplitude variations. The mean annual maximum daily precipitation for Panama shows large oscillations, even for the 10‐year running mean. For tropical America, the mean annual maximum daily precipitation has a linear relationship with surface air temperature that is independent of the Representative Concentration Pathway scenarios, but this is not the case for Panama. Temporal correlations between the tropical America mean annual maximum daily precipitation and annual mean surface air temperature in the historical experiments have a geographical distribution similar to that of the sea surface temperature anomalies during negative El Niño/Southern Oscillation events, but not in the future experiments. The correlation between the Panama mean annual maximum daily precipitation and surface air temperature in both the historical and future experiments has a geographical distribution similar to that of the temporal correlation for the tropical America mean in the historical experiment. The annual maximum daily precipitation in Panama is projected to increase during negative El Niño events in the future, as observed in the historical climate.

Revisiting the effect of increasing horizontal resolution on the evolution of El Niño in a coupled model

The ENSO (El Niño southern oscillation) in the tropical Pacific plays a crucial role in regulating the Indian summer monsoon. Many mechanisms have been proposed to explain the positive and negative feedback associated with the ENSO through air-sea interaction in the tropical Pacific. Historical run data at varying oceanic and atmospheric resolutions from the MPI-ESM model is analyzed and compared with observations to determine the possible reasons for the much earlier onset and delayed withdrawal of ENSO in the coupled model. Increasing the resolution of the oceanic and atmospheric components of the coupled model helps in well-resolving the annual cycle of sea surface temperature in the tropical Pacific. There is a significant improvement in the early onset and late withdrawal of El Niño in the coupled model with increasing horizontal resolution of the model components. The weak subsurface propagation along the 20 °C isotherm in the equatorial Pacific improves on increasing the horizontal resolution of the coupled model. Similar to observations, there is a clear eastward extension of convection, 20° east of the dateline, in the equatorial tropical Pacific in the coupled model during ENSO years. Increasing the resolution of the oceanic and atmospheric components of the coupled model improves the simulation of convective activity over the western Pacific along with the improved magnitude of anomalous zonal wind strength during El Niño years. However, the presentation of convective activity over the equatorial Pacific deteriorated on increasing atmospheric resolution further to T255 due to the enhanced value of the interannual amplitude of intraseasonal zonal wind around the international dateline. Also, the coupled model does not capture the accurate eastward propagation of the Madden Julian Oscillation envelope over the western Pacific. While higher resolutions showed improvement in the representation of El Niño events in terms of their number and duration, challenges persisted in accurately capturing the frequency of these events and their related triggering mechanisms. Understanding the intricate interplay of factors influencing the evolution of El Niño requires further research and progress in modeling strategies.

The Sensitivity of an Idealized Weddell Gyre to Horizontal Resolution

AbstractEstimates of the Weddell Gyre transport vary widely between climate simulations. Here, we investigate if inter‐model variability can originate from differences in the horizontal resolution of the ocean model. We run an idealized model of the Weddell Gyre at eddy‐parameterized, eddy‐permitting, and eddy‐rich resolutions and find that the gyre is strongly sensitive to horizontal resolution. The gyre transport is largest at eddy‐permitting resolutions (45 Sv with a noisy bathymetry) and smallest at eddy‐parameterized resolutions (12 Sv). The eddy‐permitting simulations have the largest horizontal density gradients and the weakest stratification over the gyre basin. The large horizontal density gradients induce a significant thermal wind transport and increase the mean available potential energy for mesoscale eddies. The distribution of eddy kinetic energy indicates that explicit eddies in simulations intensify the bottom circulation of the gyre via non‐linear dynamics. If climate models adopt horizontal resolutions that the Weddell Gyre is most sensitive to, then simulations of the Weddell Gyre could become more disparate.

Recreating the California New Year's Flood Event of 1997 in a Regionally Refined Earth System Model

AbstractThe 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM‐E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California‐focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time‐series and causal analysis frameworks are used to examine runoff sensitivities state‐wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time‐series shape, than forecast lead time, 2‐to‐4 days prior to the 1997 flood onset.

On the Resolution Sensitivity of Equatorial Precipitation in a GFDL Global Atmospheric Model

AbstractWe performed a series of aquaplanet simulations at the horizontal resolution from 50 to 6 km with identical parameterization settings using the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4 implemented with the two‐moment Morrison‐Gettelman cloud microphysics with prognostic precipitation (GFDL AM4‐MG2). At the finer resolution, the global mean resolved‐scale precipitation increases and that from cumulus parameterization decreases. The model also simulates less/thinner clouds over the low latitudes and more/thicker clouds over the high latitudes as the resolution increases. The precipitation over the deep tropics is investigated in detail. We find little resolution sensitivity in the daily mean precipitation extremes. Changes of the equatorial resolved precipitation with resolution cannot be fully explained by the resolution dependence in the vertical velocity amplitude. We report a robust sensitivity in the convective organization over the deep tropics to the model resolution. In simulations of finer resolution, the localized convection is suppressed, and the organized convective system associated with large‐scale circulations becomes more prominent.

The Benefits and Challenges of Downscaling a Global Reanalysis With Doubly‐Periodic Large‐Eddy Simulations

AbstractGlobal reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the “Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics,” or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions.

Spatial and Temporal Resolution Needs for Volcano Topographic Change Data Sets Based on Past Eruptions (1980–2019)

AbstractUp‐to‐date topography data sets are essential for forecasting volcanic hazards and monitoring deformation. Digital elevation models are used to quantify eruption rates, used in flow modeling programs, and are necessary to accurately process interferometric synthetic aperture radar data for surface deformation. We can track topographic change at volcanoes through fieldwork, airborne instruments, and satellite data, with the last providing the greatest potential for global coverage. Despite this global coverage, we do not know the characteristics of topographic change at volcanoes over a given time interval. We define the specific acquisition needs for topography data using topographic change detected from recent eruptions. We review existing literature and compile a data set of eruptive products (121 lava flows, 99 domes and 163 pyroclastic density currents (PDCs)) from eruptions between 1980 and 2019. We find that different sensing capabilities are required for different use cases. A vertical accuracy of 1 m would detect 92% of all eruptive products including 100% of lava domes and lava flows, but only 78% of PDCs. A horizontal resolution of 13 × 13 m pixels is the minimum necessary to detect 90% of all eruptive products. Explosive eruptions (with PDC products) typically lasted less than 1 day and would need a temporal resolution of 1 day while a longer repeat interval is acceptable at effusive eruptions (lava domes and flows), which could last weeks to years. We find a lack of consistent data acquisition, with 45% of the 383 eruptive products reported not having published spatial dimensions.

Performance of land surface schemes on simulation of land falling tropical cyclones over Bay of Bengal using ARW model

The present study encompasses the performance of Land Surface Model (LSM) physics on simulation of Tropical Cyclones (TCs) key characteristics - track, mean sea level pressure (MSLP), maximum sustained wind (MSW) and rainfall. The impact of four LSM schemes - Thermal Diffusion, Noah, RUC and Noah-MP, is evaluated for the simulation of Severe Cyclonic Storm (SCS) ‘Vardah’ that crossed Tamil Nadu coast, near Chennai on 12 December, 2016 and Extremely Severe Cyclonic Storms (ESCS) ‘Fani’ that crossed Odisha coast, close to Puri on 03 May, 2019. For this purpose, the Advanced Weather Research and Forecasting (ARW) model, configured with a single domain of 9 km horizontal resolution covering the Bay of Bengalis considered. The initial and lateral boundary conditions to the model integration are taken from National Centers for Environmental Prediction (NCEP) Final Analysis (FNL). The model simulated track is verified with India Meteorological Department (IMD) observed track for both the cases. The model simulated MSW and MSLP at the landfall location is validated with IMD best estimation along with fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) Re-analysis (ERA5) products. The rainfall associated with both the cyclones are compared with ERA5 and Global Precipitation Measurement (GPM) rainfall for its validation. The track of TCs Vardah and Fani are well simulated with all the four land surface schemes with reasonable accuracy in landfall position and time of landfall of the systems. The Along Track Error (ATE) and Cross Track Error (CTE) are minimal for the unified Noah LSM scheme. The landfall position error (about 2 km only) is significantly improved with the unified Noah scheme. In case of rainfall forecast, LSMs tend to overestimate the rainfall during landfall of both systems. It is also noticed that overestimation is more towards inland than on the coast. Out of all four LSMs, rainfall estimation from the RUC is closest to the GPM and ERA5 rainfall estimates during landfall. In addition to this, RUC scheme intensifies the cyclones in terms of MSLP and MSW during the landfall of the system as compared to the other parameterization schemes.

Understanding the Sensitivity of the North Atlantic Subpolar Overturning in Different Resolution Versions of HadGEM3‐GC3.1

AbstractThe Atlantic Meridional Overturning Circulation (AMOC) is a key component of the global climate but is not simulated consistently across models or model resolutions. Here, we use a hierarchy of the global coupled model HadGEM3‐GC3.1, with ocean resolutions of 1°, ¼°, and 1/12°, to evaluate the subpolar AMOC and its sensitivity to horizontal resolution. In line with observations, the models show that the mean overturning and surface forced water mass transformation (SFWMT) are concentrated in the eastern subpolar gyre rather than in the Labrador Sea. However, the magnitude of the overturning along the OSNAP line at medium and high resolutions is 25% and 40% larger than in the observations, respectively. This disagreement in overturning strength is noted for both OSNAP East and OSNAP West, and is mainly due to anomalously large SFWMT rather than anomalously large interior mixing or overflow transport from the Nordic Seas. Over the Labrador Sea, the intensification of SFWMT with resolution is explained by a combination of two main biases. Anomalously warm surface water enhances heat loss and reduces the extension of marginal sea ice, which increases the surface density flux over the boundary of the basin. A bias in salinity leads to anomalously dense surface water that shifts the outcropping area of the AMOC isopycnal and results in intense dense water formation along the boundary of the basin at medium and high resolutions. Thus, our analysis sheds light on a range of model biases responsible for large overturning over the Labrador Sea in climate models.

Vertical Resolution Impacts Explicit Simulation of Deep Convection

AbstractThe aggregation of tropical convection greatly influences the mean‐state of the atmosphere, altering humidity distributions, total atmospheric radiative cooling, and cloud amounts. Although studies have demonstrated the sensitivity of convective aggregation to horizontal resolution and domain size, few studies have explored the impact of vertical resolution on convective aggregation. Here, we investigate the impact of vertical resolution on simulations of deep convection and convective aggregation using the System for Atmospheric Modeling convection resolving model. We analyze simulations of tropical radiative‐convective equilibrium with varying vertical levels (32, 64, 128, and 256) across small (100 km), medium (700 km) and large (1,500 km) domains. We demonstrate that relative humidity and cloud fraction decrease with increasing vertical resolution as a result of reduced turbulent mixing. Vertical resolution also influences the occurrence of, onset time, and equilibrium intensity of aggregated convection, and also appears to affect the sensitivity of convective aggregation to domain size. Understanding how simulated convection aggregates, as well as its simulated sensitivity to model formulation, is critical for making and interpreting future predictions of global climate change.

Sensitivity of the Lorenz energy cycle of the global ocean

We re-examine the Lorenz energy cycle (LEC) for the global ocean by assessing its sensitivity to model and forcing differences. We do so by comparing LECs derived from two simulations based on different eddy-rich ocean models, ICON-O and MPI-OM, both driven by NCEP/NCAR reanalysis, and by comparing LECs derived from two simulations generated using ICON-O model but driven by two different reanalyses, NCEP/NCAR and ERA5. Regarding model difference, we find weaker eddy kinetic energy, k_e, in the ICON-O simulation than in the MPI-OM simulation. We attribute this to the higher horizontal resolution of MPI-OM in the Southern Ocean. The weaker k_e in ICON-O is not caused by the lack of eddy available potential energy, p_e, but by the strong dissipation of p_e and the resulting weak conversion from p_e to k_e. Regarding forcing difference, we find that considerably more mechanical energy is generated by the ERA5 forcing, which has a higher spatial-temporal resolution compared to the NCEP/NCAR forcing. In particular, the generation of k_e, which also contains the resolved part of the internal wave spectrum, is enhanced by about 1 TW (40%). However, the dominance of the baroclinic and the barotropic pathways forces the enhanced generation of k_e to be balanced by an enhanced dissipation in the surface layer. The gross features of LEC are insensitive to both model and forcing differences, picturing the ocean as an inefficient “windmill” that converts only a small portion of the inputted mechanical energy into the interior mean and transient circulations.

Numerical simulation of upper ocean responses to Typhoon Maria (2018) in the Northwest Pacific: Behavior of sub-mesoscale processes

A deeper understanding of the upper ocean response to typhoons is beneficial to the further improvement of typhoon forecasting. However, because of model horizontal resolution limitations, we still do not understand how sub-mesoscale processes in the ocean may modulate the response of the upper ocean to typhoons. In this study, we set up one-way online nested parent (mesoscale resolving: Exp_9 km) and child (sub-mesoscale permitting: Exp_3 km) models to investigate how the 15–45-km sub-mesoscale processes in the ocean affected the thermal and dynamical response processes of the upper ocean to Super Typhoon Maria (2018). It was found that the sub-mesoscale processes and their induced vertical heat transport (VHT) were mainly concentrated at the eddy, and most of the sub-mesoscale processes and their accompanying VHT disappeared after the typhoon, indicating that typhoons may be destroyers of sub-mesoscale processes. The differences in the sea temperature response between Exp_3 km and Exp_9 km can reached 1.5 °C in the eddy-rich sea surface region and 3 °C at the thermocline. This thermal response difference could be attributed to the difference in vertical diffusion and the difference in total advection processes simulated by the two models. Furthermore, the sub-mesoscale VHT played an important role in causing smaller sea surface cooling (SSC) and larger subsurface warming to the right side of the typhoon, and considering more sub-mesoscale processes improved the simulation accuracy of the SSC on the right side of the typhoon. The difference in near-inertial kinetic energy (NIKE) and the difference in fD1 (a peak frequency approximately equal to the sum of f and D1) kinetic energy between the two experiments were mainly found in the eddy-rich region to the right side of the typhoon, accounting for, at most, 15% of Exp_3 km's NIKE and 50% of Exp_3 km's fD1 kinetic energy, respectively, and resolving more sub-mesoscale processes could limit the lateral propagation of NIKE, especially in warm eddy. The kinetic energy and vertical shear of the near-inertial currents (NICs) and fD1 currents of Exp_3 km were larger than those of Exp_9 km, suggesting that sub-mesoscale processes may enhance ocean vertical mixing. Moreover, sub-mesoscale processes promoted the downward propagation of NIKE, which may be of great significance for promoting NICs-induced ocean mixing into the deep ocean and accelerating the decay of NICs. This work is of great importance for improving the understanding of typhoon-induced thermal and dynamical responses, and thus for improving the typhoon prediction.

Remote detection of upland surface water storage capacity in deglaciated terrain

AbstractA notable characteristic of terrain in non‐urbanized deglaciated areas of northeastern North America is the microtopography created by processes related to surficial geology, deglaciation and mechanical disturbances to surface materials from excavating events, most of which are caused by tree throw in the modern landscape. The features are often on the scale of 1–4 m across and decimetres to a metre in depth, appearing as ‘puddles’ during intense or high‐magnitude precipitation events. Generalized storage capacity values have been summarized in textbooks for varied landscape conditions, but surprisingly little information is available about how microtopography and related surface water storage varies in dominant physiographic settings in deglaciated landscapes defined by slope, surficial geology and land cover conditions. The increasing availability of elevation data at a horizontal resolution of 2 m or higher has made it possible to remotely evaluate differences in terrain elevation and quantify upland surface water storage capacity from relatively small topographic depressions. Here, we describe and quantify these topographic features in several coastal and inland watersheds in the state of Maine (USA) with measurements of depression volume calculated from digital elevation models (DEMs) using a pit filling approach. Results show that microtopographic storage capacity varies with slope and land cover conditions in deglaciated terrain of northeastern North America. Basin‐average surface water depression storage capacity estimates range from ~4 mm to as low as 0.2 mm. Human interventions such as clearing land for agriculture are associated with lower microtopographic surface water storage capacity than forested landscapes in the region.