General Circulation Model Research Articles

An Empirical Parameterization of the Subgrid‐Scale Distribution of Water Vapor in the UTLS for Atmospheric General Circulation Models

AbstractTemperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from In‐service Aircraft for a Global Observing System (IAGOS) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere. The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundred kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization reproduces the observed distributions with a determination coefficient always greater than 0.917 and with a mean value of 0.997. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 and 300 km.

Effects of the internal temperature on vertical mixing and on cloud structures in ultra-hot Jupiters

The vertical mixing in hot-Jupiter atmospheres plays a critical role in the formation and spacial distribution of cloud particles in their atmospheres. This affects the observed spectra of a planet through cloud opacity, which can be influenced by the degree of cold trapping of refractory species in the deep atmosphere. We aim to isolate the effects of the internal temperature on the mixing efficiency in the atmospheres of ultra-hot Jupiters (UHJs) and the spacial distribution of cloud particles across the planet. We combined a simplified tracer-based cloud model, a picket fence radiative-transfer scheme, and a mixing length theory to the Exo-FMS general circulation model. We ran the model for five different internal temperatures at typical UHJ atmosphere system parameters. Our results show the convective eddy diffusion coefficient remains low throughout the vast majority of the atmosphere, with mixing dominated by advective flows. However, some regions can show convective mixing in the upper atmosphere for colder interior temperatures. The vertical extent of the clouds is reduced as the internal temperature is increased. Additionally, a global cloud layer gets formed below the radiative--convective boundary (RCB) in the cooler cases. Convection is generally strongly inhibited in UHJ atmospheres above the RCB due to their strong irradiation. Convective mixing plays a minor role compared to advective mixing in keeping cloud particles aloft in UHJs with warm interiors. Higher vertical turbulent heat fluxes and the advection of potential temperature inhibit convection in warmer interiors. Our results suggest that isolated upper atmosphere regions above cold interiors may exhibit strong convective mixing in isolated regions around Rossby gyres, allowing aerosols to be better retained in these areas.

Temperature and Precipitation Change Assessment in the North of Iraq Using LARS-WG and CMIP6 Models

Investigating the spatial-temporal evolutionary trends of future temperature and precipitation considering various emission scenarios is crucial for developing effective responses to climate change. However, researchers in Iraq have not treated this issue under CMIP6 in much detail. This research aims to examine the spatiotemporal characteristics of temperature and rainfall in northern Iraq by applying LARS-WG (8) under CMIP6 general circulation models (GCMs). Five GCMs (ACCESS-ESM1-5, CNRM-CM6-1, MPI-ESM1-2-LR, HadGEM3-GC31-LL, and MRI-ESM2-0) and two emissions scenarios (SSP245 and SSP585) were applied to project the upcoming climate variables for the period from 2021 to 2040. The research relied on satellite data from fifteen weather sites spread over northern Iraq from 1985 to 2015 to calibrate and validate the LARS-WG model. Analysis of spatial-temporal evolutionary trends of future temperature and precipitation compared with the baseline period revealed that seasonal mean temperatures will increase throughout the year for both scenarios. However, the SSP585 scenario reveals the highest increase during autumn when the spatial coverage of class (15–20) °C increased from 27.7 to 96.29%. At the same time, the average seasonal rainfall will rise in all seasons for both scenarios except autumn for the SSP585 scenario. The highest rainfall increment percentage is obtained using the SSP585 for class (120–140) mm during winter. The spatial extent of the class increased from 25.49 to 50.19%.

Flows, circulations, and energy transport in the outer and deep atmospheres of synchronous and non-synchronous hot Jupiters

Recent studies have shown that vertical enthalpy transport can explain the inflated radii of highly irradiated gaseous exoplanets. Simultaneously, they have also shown that rotation can influence this transport, leading to highly irradiated, rapidly rotating objects that are uninflated. Here we explore the flows that underpin this transport, including the impact of synchronous or non-synchronous rotation. We used DYNAMICO to run a series of long timescale HD209458b-like atmospheric models at various rotation rates. For models that are tidally locked we considered rotation rates between $1/16^ th $ and $40$ times the rotation rate of HD209458b, whilst for non-synchronous models, we considered the range one-eighth to four times HD209458b. We find that our synchronous models fall into one of three Omega -dependent regimes. At low Omega , we find that the outer atmosphere dynamics are driven by a divergent day-night wind which drives weak vertical transport and can lead to the formation of a night-side hot-spot. At intermediate Omega , we find classical hot Jupiter dynamics, whilst at high Omega we find a strong Coriolis effect that suppresses off-equator dynamics, including the jet-driving standing waves, thus also reducing vertical transport. As for non-synchronicity, when small, we find that it has little effect on the dynamics. However as it grows, we find that temporal variations prevent the formation of the persistent structures that drive large-scale dynamics and transport. We find that rotation can significantly impact the atmospheric dynamics of irradiated exoplanets, including vertical enthalpy advection, which may help explain the scatter in the hot Jupiter radius-irradiation relation. We have also identified a seemingly robust atmospheric feature at slow rotation: a night-side hot-spot. As this may have important implications for both the phase curve and atmospheric chemistry, we suggest that this study be followed up with next-generation global circulation models (GCMs) that robustly model radiation and chemistry.

A Study of the Mixed Layer Warming Induced by the Barrier Layer in the Northern Bay of Bengal in 2013

Strong salinity stratification induced by large freshwater fluxes in the northern Bay of Bengal (BOB) results in the formation of a quasi-permanent barrier layer (BL) that covers almost the entire BOB and leads to a unique temperature inversion within the thick BL in winter. In the presence of temperature inversions, the entrainment process at the bottom of the mixed layer (ML) induces warming effects in the ML, but little is known about this. In this paper, we quantify the contribution of the entrainment process to the ML temperature (MLT) in the northern BOB during the winter of 2013 using monthly and daily data from the Ocean General Circulation Model for the Earth Simulator version 2 (OFES2). It is found that the warming effect of the daily entrainment heat flux (EHF), which resolved the high-frequency variations, is 4 orders of magnitude larger than the monthly EHF for most of the wintertime. This significantly enhanced warming effect in daily data offsets up to 87% of the surface cooling induced by net heat flux during wintertime. A further analysis reveals that the larger daily EHF warming effect compared to its monthly counterpart is closely related to the deepened ML, the larger temperature difference within the ML and vertical velocity at the bottom of the ML.

Manifold increase in the spatial extent of heatwaves in the terrestrial Arctic

It is widely acknowledged that the intensity, frequency and duration of heatwaves are increasing worldwide, including the Arctic. However, less attention has been paid to the land area affected by heatwaves. Here, using atmospheric reanalysis and global climate models, we show that the area covered by heatwaves is substantially expanding in the terrestrial Arctic. Compared to the mid-20th century, the total land area affected by severe heatwaves in the Arctic has doubled, the area of extreme heatwaves has tripled, and the area of very extreme heatwaves has quadrupled. Furthermore, climate model projections suggest that the extent of heatwaves will continue to increase in the 21st century, but with large regional differences in heatwave magnitudes due to summer intraseasonal temperature variability. Our findings underscore the growing vulnerability of the Arctic region to extreme heat, potentially leading to severe impacts on both ecosystems and societies.

Natural sinks and sources of CO<sub>2</sub> and CH<sub>4</sub> in the atmosphere of Russian regions and their contribution to climate change in the 21st century evaluated with CMIP6 model ensemble

The natural fluxes of CO2 and CH4 into the atmosphere from the territory of Russia in the 21st century have been analyzed using the results of calculations with the ensemble of global climate models of the international project CMIP6. Estimates of natural CO2 fluxes in Russian regions differ greatly for different models. Their values for the beginning of the 21st century range from –1 to 1 GtC/yr. In the 21st century the differences in model estimates of fluxes grow and at the end of the 21st century in the scenario with the largest anthropogenic impacts SSP5-8.5 range from –2.5 to 2.5 GtC/year. Estimates of natural methane emissions to the atmosphere from the territory of Russia also differ greatly for different models. Modern methane emissions are estimated in the range from 10 to 35 MtCH4/yr, with an increase in the 21st century of up to 300%. Ensemble model calculations show general trends for changes in natural greenhouse gas fluxes. Most CMIP6 ensemble models are characterized by a maximum of CO2 uptake by terrestrial ecosystems and its further reduction by the end of the 21st century, while natural methane emissions to the atmosphere for all models and scenarios of anthropogenic impacts grow throughout the 21st century. The cumulative temperature potential of natural CO2 fluxes on the territory of Russia in the 21st century is estimated, depending on the scenario of anthropogenic impacts, from –0.3 to 0.1 K, and the warming-accelerating impact of natural CH4 emissions is estimated in the range of 0.03-0.09 K.

Tropical cyclone landfalls in the Northwest Pacific under global warming

AbstractThis study projects the changes in tropical cyclone (TC) landfalls in the western North Pacific under shared socioeconomic pathway (SSPs) scenarios during the TC peak season by using low‐resolution global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). Projections are based on the relationship between mid‐ and lower‐level atmospheric circulation and TC landfall frequency during the historical period from 1985 to 2014 and the future climate period from 2015 to 2100. The landfall areas for TCs are divided into northern East Asia (NEA), middle East Asia (MEA) and southern East Asia (SEA); the TC peak seasons are July–September for NEA and MEA, and July–November for SEA. To evaluate reproducibility, both ensemble and individual model outputs for mid‐ and lower‐level atmospheric circulations associated with TC landfall in each East Asian subregion are compared to the reanalysis. An ensemble of seven models with stable results for all three regions is more reasonable in simulating atmospheric circulation patterns than an ensemble of all CMIP6 models. The findings suggest that TC landfall is projected to increase by about 12% and 32% in NEA and MEA, respectively, in the late 21st century under the SSP5‐8.5 scenario compared to the historical period, while decreasing by 13% in SEA. These changes are consistent under both warming scenarios, and are more pronounced in the SSP5‐8.5 scenario compared to SSP1‐2.6, particularly in the later period of this century. An analysis of future atmospheric circulations suggests that global warming will weaken the western North Pacific subtropical high and cause its boundary to retreat eastward. This will lead to changes in the steering flow, which is closely related to TC tracks, resulting in TC landfalls to increase or decrease depending on the East Asian subregion.

Climate-driven global redistribution of an ocean giant predicts increased threat from shipping

AbstractClimate change is shifting animal distributions. However, the extent to which future global habitats of threatened marine megafauna will overlap existing human threats remains unresolved. Here we use global climate models and habitat suitability estimated from long-term satellite-tracking data of the world’s largest fish, the whale shark, to show that redistributions of present-day habitats are projected to increase the species’ co-occurrence with global shipping. Our model projects core habitat area losses of >50% within some national waters by 2100, with geographic shifts of over 1,000 km (∼12 km yr−1). Greater habitat suitability is predicted in current range-edge areas, increasing the co-occurrence of sharks with large ships. This future increase was ∼15,000 times greater under high emissions compared with a sustainable development scenario. Results demonstrate that climate-induced global species redistributions that increase exposure to direct sources of mortality are possible, emphasizing the need for quantitative climate-threat predictions in conservation assessments of endangered marine megafauna.

The effects of climate change on Pinus tabulaeformis radial growth in the Xiaowutai Mountains, northern China

Clarifying the climate change effects on the radial growth of trees has implications for sustainable forest management, especially under global warming. To investigate tree growth responses to regional climate change of Xiaowutai Mountain, four Chinese pine (Pinus tabulaeformis) ring-width index chronologies were established at different elevations (1290–1600 m). Species growth trends were estimated using climate change projections derived from global climate models. The results show: (1) the four ring-width chronologies exhibited strong statistical characteristics, making them suitable for dendroclimatology studies. Radial growth-climate relationships were highly consistent, showing a negative correlation with previous September temperatures and current May–June temperatures, as well as a positively correlated with precipitation and Palmer Drought Severity Index during the corresponding period; and (2) climate change scenarios revealed that temperature will gradually increase on the Xiaowutai Mountain, and only a slight variation in precipitation is expected. Chinese pine radial growth may show a decline under future climate change.

Assessing the impact of climate change on spring discharge using hydrological modelling in Musanze District, Rwanda

AbstractClimate change has far-reaching impacts on water availability globally, with changing precipitation patterns and global warming contributing to increasing scarcity and unreliability of spring water in many regions. Despite this understanding, the implication of climate change on the hydrological system remains limited in certain areas, including the district of Musanze, Rwanda. This study investigates the effects of climate change on the discharge of 14 springs in Musanze using the hydrological model V2Karst. CORDEX data from two global climate models of CMIP5 are used to simulate the future spring discharges over the period 2021–2100. The results reveal significantly higher annual discharges in the RCP2.6 scenario compared to the RCP8.5 for all springs from 2021 to 2100. Nevertheless, no significant long-term trend in spring discharge is observed between the early (2021–2050) and late (2071–2100) periods. However, the intra-annual temporal discharge patterns are changing with a significant increase in the seasonality index for the RCP8.5 scenario towards the end of the twenty-first century. Additionally, for both RCPs, there is a notable increase in the number of days with discharges below 40% of the mean of annual discharges during the baseline period. The overall findings of this study suggest that climate change significantly impacts the future evolution of spring discharges in Musanze, indicating potential risks to the future availability of water in the region.

Bibliometric Analysis of Global Research on Port Infrastructure Vulnerability to Climate Change (2012–2023): Key Indices, Influential Contributions, and Future Directions

This article analyzes the climate vulnerability of seaports through a bibliometric review of 45 articles published between 2012 and 2023. The research highlights the increase in publications focusing on the vulnerability of port infrastructure to climate impacts, a topic that previously received less attention compared to operational, economic, and logistical factors, which are frequently discussed in the existing literature. The analysis reinforces the relevance of this study, with the United States, Spain, and the United Kingdom emerging as the most influential countries in this research area. This article also reveals the predominance of methods based on the Coastal Vulnerability Index (CVI), which includes ports in its assessments, and emphasizes the need to develop a more robust index for evaluating port vulnerability. Additionally, it discusses current topics, such as sea level rise and the use of global climate models and suggests future research directions to enhance the assessment of port vulnerability in the face of climate change.

The Sensitivity of the Spatial Pattern of Sea Level Changes to the Depth of Antarctic Meltwater Fluxes

AbstractRegional patterns of sea level rise are affected by a range of factors including glacial melting, which has occurred in recent decades and is projected to increase in the future, perhaps dramatically. Previous modeling studies have typically included fluxes from melting glacial ice only as a surface forcing of the ocean or as an offline addition to the sea surface height fields produced by climate models. However, observational estimates suggest that the majority of the meltwater from the Antarctic Ice Sheet actually enters the ocean at depth through ice shelf basal melt. Here we use simulations with an ocean general circulation model in an idealized configuration. The results show that the simulated global sea level change pattern is sensitive to the depth at which Antarctic meltwater enters the ocean. Further analysis suggests that the response is dictated primarily by the steric response to the depth of the meltwater flux.

Transferability and Explainability of Deep Learning Emulators for Regional Climate Model Projections: Perspectives for Future Applications

Abstract Regional climate models (RCMs) are essential tools for simulating and studying regional climate variability and change. However, their high computational cost limits the production of comprehensive ensembles of regional climate projections covering multiple scenarios and driving Global climate models (GCMs) across regions. RCM emulators based on deep learning models have recently been introduced as a cost-effective and promising alternative that requires only short RCM simulations to train the models. Therefore, evaluating their transferability to different periods, scenarios, and GCMs becomes a pivotal and complex task in which the inherent biases of both GCMs and RCMs play a significant role. Here, we focus on this problem by considering the two different emulation approaches introduced in the literature as perfect and imperfect, that we here refer to as perfect prognosis (PP) and model output statistics (MOS), respectively, following the well-established downscaling terminology. In addition to standard evaluation techniques, we expand the analysis with methods from the field of explainable artificial intelligence (XAI), to assess the physical consistency of the empirical links learnt by the models. We find that both approaches are able to emulate certain climatological properties of RCMs for different periods and scenarios (soft transferability), but the consistency of the emulation functions differs between approaches. Whereas PP learns robust and physically meaningful patterns, MOS results are GCM dependent and lack physical consistency in some cases. Both approaches face problems when transferring the emulation function to other GCMs (hard transferability), due to the existence of GCM-dependent biases. This limits their applicability to build RCM ensembles. We conclude by giving prospects for future applications. Significance Statement Regional climate model (RCM) emulators are a cost-effective emerging approach for generating comprehensive ensembles of regional climate projections. Promising results have been recently obtained using deep learning models. However, their potential to capture the regional climate dynamics and to emulate other periods, emission scenarios, or driving global climate models (GCMs) remains an open issue that affects their practical use. This study explores the potential of current emulation approaches incorporating new explainable artificial intelligence (XAI) evaluation techniques to assess the reliability and transferability of the emulators. Our findings show that the different global and regional model biases involved in the different approaches play a key role in transferability. Based on the results obtained, we provide some prospects for potential applications of these models in challenging problems.

A Distinct Role for Aerosol and GHG Forcing in Historical CMIP6 Evapotranspiration Trends

AbstractEvapotranspiration (ET) is crucial for the global water balance, plant growth, and freshwater availability. It connects the surface water balance with surface energy fluxes, making its accurate representation vital for climate projections. However, global climate models (GCMs) struggle with ET representation due to resolution limitations and simplified depictions of soil, plant, and atmosphere interactions. Simulated future changes in ET are uncertain, and the role of driving processes remain unclear. Here, we explore the utility of a simple and interpretable method to disentangle these varying drivers. We investigate the sensitivity of JJA ET to different atmospheric variables through simple linear models predicting ET from atmospheric variables only. The model consistently yields good results across GCMs or forcing scenarios. We find that GCMs have shown strong decreases and subsequent increases in ET over the historical period, related to changes in net surface radiation. For future climate projections, decreases in water availability compete with higher available surface radiation, making future projections uncertain. Single forcing GCM realizations show that historical ET trends in densely populated regions have been more influenced by aerosol emissions than greenhouse gases. Finally, we investigate which atmospheric variables explain most short‐term (year‐to‐year) and long‐term (decadal) changes. While water availability may be the most important driver of short‐term variability, for certain regions, radiation trends dominate long‐term forcing. This paper leverages a simple approach to provide a comprehensive and understandable view into recent and future changes in ET, reconciling the evidence provided by more complex case studies.

GRACE Satellite Observations of Antarctic Bottom Water Transport Variability

AbstractAntarctic Bottom Water (AABW) formation and transport constitute a key component of the global ocean circulation. Direct observations suggest that AABW volumes and transport rates may be decreasing, but these observations are too temporally or spatially sparse to determine the cause. To address this problem, we develop a new method to reconstruct AABW transport variability using data from the GRACE (Gravity Recovery and Climate Experiment) satellite mission. We use an ocean general circulation model to investigate the relationship between ocean bottom pressure and AABW: we calculate both of these quantities in the model, and link them using a regularized linear regression. Our reconstruction from modeled ocean bottom pressure can capture 65%–90% of modeled AABW transport variability, depending on the ocean basin. When realistic observational uncertainty values are added to the modeled ocean bottom pressure, the reconstruction can still capture 30%–80% of AABW transport variability. Using the same regression values, the reconstruction skill is within the same range in a second, independent, general circulation model. We conclude that our reconstruction method is not unique to the model in which it was developed and can be applied to GRACE satellite observations of ocean bottom pressure. These advances allow us to create the first global reconstruction of AABW transport variability over the satellite era. Our reconstruction provides information on the interannual variability of AABW transport, but more accurate observations are needed to discern AABW transport trends.

Designing a Fully‐Tunable and Versatile TKE‐l Turbulence Parameterization for the Simulation of Stable Boundary Layers

AbstractThis study presents the development of a so‐called Turbulent Kinetic Energy (TKE)‐l, or TKE‐l, parameterization of the diffusion coefficients for the representation of turbulent diffusion in neutral and stable conditions in large‐scale atmospheric models. The parameterization has been carefully designed to be completely tunable in the sense that all adjustable parameters have been clearly identified and the number of parameters has been minimized as much as possible to help the calibration and to thoroughly assess the parametric sensitivity. We choose a mixing length formulation that depends on both static stability and wind shear to cover the different regimes of stable boundary layers. We follow a heuristic approach for expressing the stability functions and turbulent Prandlt number in order to guarantee the versatility of the scheme and its applicability for planetary atmospheres composed of an ideal and perfect gas such as that of Earth and Mars. Particular attention has been paid to the numerical stability and convergence of the TKE equation at large time steps, an essential prerequisite for capturing stable boundary layers in General Circulation Models (GCMs). Tests, parametric sensitivity assessments and preliminary tuning are performed on single‐column idealized simulations of the weakly stable boundary layer. The robustness and versatility of the scheme are assessed through its implementation in the Laboratoire de Météorologie Dynamique Zoom GCM and the Mars Planetary Climate Model and by running simulations of the Antarctic and Martian nocturnal boundary layers.

Mutual impact of salinity and climate change on crop production water footprint in a semi-arid agricultural watershed: Application of SWAT-MODFLOW-Salt

Sustainable agriculture in intensively irrigated watersheds, particularly those in arid and semi-arid regions, requires enhanced management practices to maintain crop production, which depends on climate, available water resources, soil conditions, irrigation practices, and crop type. Among these factors, soil salinity and climate change are significant challenges to agricultural productivity. To investigate the long-term influence of salinity and climate change on crop production from 1999 to 2100 in irrigated semi-arid regions, we apply the water footprint (WF) concept using the hydro-chemical watershed model SWAT-MODFLOW-Salt, driven by five General Circulation Models (GCMs) and two climate scenarios (RCP4.5 and RCP8.5), to a 732 km2 irrigated stream-aquifer system within the Lower Arkansas River Valley (LARV), Colorado, USA. The study focused on calculating the green (WFgreen), blue (WFblue), and total (WFtotal) crop production WFs for 29 crops in the region, with and without including salinity effect on crop yield. Results reveal that during the baseline period (1999–2009), the total annual average WFgreen, WFblue, and WFtotal increased by 7.6 %, 4.4 %, and 6.5 %, respectively, under salinity stress, as crops experienced reductions of up to 4.6 %, 1.6 %, and 2.3 % in green, blue, and total crop yield. The mutual impact of salinity and the worst-case climate model (IPSL_CM5A_MR) under the higher emission scenario (RCP8.5) led to a 3.3 %, 1.9 %, and 3 % increase in green, blue, and total crop production WFs. Furthermore, the study highlighted that the proportion of green, blue, and total crop production WFs in the LARV exceeded the world average. This discrepancy was attributed to various factors, including different spatial and temporal crop distribution, irrigation practices, soil types, and climate conditions. Notably, salinity stress affected green crop yield and green WF more significantly than blue crop yield and blue WF across all GCM models. This finding underscores the importance of prioritizing management practices to control salinity-associated challenges within the region.

A Novel Approach for Identifying and Assessing MOR‐Based CMIP6 Model for Hydrological Analysis in an Ungauged Watershed

ABSTRACTThe identification of the onset and retreat dates of the monsoon season is a crucial and intricate phenomenon, given its annual spatiotemporal variability. The monsoon season contributes significantly to rainfall, replenishing water sources and hydrological systems but causes hydrological extremes, especially for the high‐altitude watersheds in Southeast Asia. Global Circulation Model (GCM)‐Coupled Model Intercomparison Project Phase 6 (CMIP6)‐based rainfall and temperature data are helpful for adequately representing present and future climate scenarios. However, the usability of uncorrected GCM‐CMIP6 datasets needs to be assessed regionally. This study focuses on identifying the best‐suited GCM‐CMIP6 based on the monsoon onset (MO) and retreat (MR) dates along with other climatological temporal parameters. A numerical definition for MO and MR has been formulated to find the best‐suited GCM‐CMIP6 (i.e., CMCC‐ESM2). In this context, runoff simulation is carried out using the meteorological inputs of the monsoon onset‐retreat (MOR)‐based best‐suited GCM to evaluate its usability. A multi‐model simulation approach has been carried out for runoff estimation based on observed datasets to find a better‐suited hydrological model. The proposed overall methodology is tested in a hydrological extreme‐prone ungauged watershed (i.e., Ranikhola). CMCC‐ESM2 and SSP2‐4.5 has been identified as best‐suited SSP based on statistical evolution (R2 [0.693], NSE [0.662] and RSR [0.581]) for future daily runoff prediction. Future hydrological analysis shows that the average monsoon peak runoff magnitude will increase from the calibrated period (2015–2020) by 18.01% in the coming years (2021–2049).

The Feasibility of Asynchronous Rotation via Thermal Tides for Diverse Atmospheric Compositions

The equilibrium rotation rate of a planet is determined by the sum of torques acting on its solid body. For planets with atmospheres, the dominant torques are usually the gravitational tide, which acts to slow the planet’s rotation rate, and the atmospheric thermal tide, which acts to spin up the planet. Previous work demonstrated that rocky planets with thick atmospheres may produce strong enough thermal tides to avoid tidal locking, but a study of how the strength of the thermal tide depends on atmospheric properties has not been done. In this work, we use a combination of simulations from a global climate model and analytic theory to explore how the thermal tide depends on the shortwave and longwave optical depth of the atmosphere, the surface pressure, and the absorbed stellar radiation. We find that for planets in the habitable zones of M stars only high-pressure but low-opacity atmospheres permit asynchronous rotation owing to the weakening of the thermal tide at high longwave and shortwave optical depths. We conclude that asynchronous rotation may be very unlikely around low-mass stars, which may limit the potential habitability of planets around M stars.