Search

In this paper we describe the implementation of the carbon isotopes 13 C and 14 C (radiocarbon) into the marine biogeochemistry model REcoM3. The implementation is tested in long-term equilibrium simulations where REcoM3 is coupled with the ocean general circulation model FESOM2.1, applying a low-resolution configuration and idealized climate forcing. Focusing on the carbon-isotopic composition of dissolved inorganic carbon (δ13 C DIC and Δ14 C DIC), our model results are largely consistent with reconstructions for the pre-anthropogenic period. Our simulations also exhibit discrepancies, e.g. in upwelling regions and the interior of the North Pacific. Some of these differences are due to the limitations of our ocean circulation model setup, which results in a rather shallow meridional overturning circulation. We additionally study the accuracy of two simplified modelling approaches for dissolved inorganic 14 C, which are faster (15 % and about a factor of five, respectively) than the complete consideration of the marine radiocarbon cycle. The accuracy of both simplified approaches is better than 5 %, which should be sufficient for most studies of Δ14 C DIC. [ABSTRACT FROM AUTHOR]

Xinjiang, located in the arid region of the northwest, is one of the areas most sensitive to global changes. The Kaidu River Basin, situated in the heart of Xinjiang, is one of the sources of China's largest inland river—the Tarim River. The Kaidu River not only bears the responsibility for supplying water for industrial use and agricultural production and people's daily life in the basin, but also plays a crucial role in ecological water supply to the Tarim River. Studying and analyzing the characteristics and trends of meteorological condition in the future under climate change can provide important references and a basis for a deeper understanding of changes in the hydrological process and water resources in the basin. Therefore, this paper selects seven precipitation bias correction methods and four temperature bias correction methods to adjust the precipitation and temperature output data of eight general circulation models of the Sixth Coupled Model Intercomparison Project (CMIP6) within the Kaidu River Basin. The applicability of different bias correction methods in the study area is evaluated, and based on the corrected future meteorological data and calculated extreme meteorological index, the trends of meteorological data (precipitation, temperature) in the future period (2025–2050) under four SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) in the Kaidu River Basin are analyzed. The results show that: (1) Different types of bias correction methods have different correction focus and effects; their reflections on evaluation indicators are also different. (2) In the future period (2025–2050), the annual precipitation and average temperature in the Kaidu River Basin are higher than those in the historical period (1975–2014). The average annual temperature shows an upward trend in the future, but the annual precipitation shows a downward trend in the future except for the SSP2-4.5 scenario. (3) Compared with the historical period, the extreme precipitation in the future period under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios is higher than that in the historical period, and the number of rainless days decreases. In the future, under the SSP1-2.6 and SSP5-8.5 scenarios, the probability of meteorological drought events occurring due to high temperatures in the basin may further increase, while under the SSP2-4.5 scenario, the situation of high temperatures and heavy rain in the basin may continue to increase. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new high-resolution (1/10 °) data-driven dataset of 3D ocean currents developed by the National Research Council of Italy in the framework of the European Space Agency World Ocean Circulation project: the WOC-NATL3D dataset. The product domain extends over a wide portion of the North Atlantic Ocean from the surface down to 1500 m depth, and the dataset covers the period between 2010 and 2019. To generate this product, a diabatic quasi-geostrophic diagnostic model is applied to data-driven 3D temperature and salinity fields obtained through a deep learning technique, along with ERA5 fluxes and empirical estimates of the horizontal Ekman currents based on input provided by the European Copernicus Marine Service. The assessment of WOC-NATL3D currents is performed by direct validation of the total horizontal velocities with independent drifter estimates at various depths (0, 15 and 1000 m) and by comparing them with existing reanalyses that are obtained through the assimilation of observations into ocean general circulation numerical models. Our estimates of the ageostrophic components of the flow improve the total horizontal velocity reconstruction, being more accurate and closer to observations than model reanalyses in the upper layers, also providing an indirect proof of the reliability of the resulting vertical velocities. The reconstructed WOC-NATL3D currents are freely available at 10.12770/0aa7daac-43e6-42f3-9f95-ef7da46bc702. [ABSTRACT FROM AUTHOR]

Key message: Drought severely worsened till 2100 and eventually outplayed growth-enhancing CO2 fertilization turning productivity gains into losses for beech and fir. Most scenarios generated notable losses in profitability but economic tipping points were later than for productivity due to lag effects related to discounting. Time mixture of fir and shortening rotation can counteract economic risks under climate change, but requires early admixture and moderate establishment costs. Context: Adaptation strategies to climate change (CC) such as establishing mixed forests are often based on ecological understanding while economic rationale is often disregarded. Aims: This paper studies CC uncertainty on productivity and profitability of European beech (Fagus sylvatica L.) and Silver fir (Abies alba Mill.). Besides, the economic consequences to actively adapt beech forests by admixing Silver fir are investigated. Methods: We used the process-based forest growth model GOTILWA + to simulate RCP2.6, RCP4.5 and RCP8.5 climatic projection by the MPI-ESM-LR global circulation model (MPI-ESM-LR) with the CO2 fertilization effect (eCO2) switched on and off. We analysed the sensitivity of the land expectation value (LEV) on CC and economic parameters. Results: CC initially increased productivity, but declined after a tipping point (2040–2070) and later also profitability (2045–2100). RCP8.5 had positive, RCP2.6 negative and RCP4.5 neutral effects on LEV. Switching off eCO2 turned RCP8.5 from the most profitable to the least profitable scenario and the opposite for RCP2.6. CC generally reduced optimal rotation (Ropt) being scenario dependant, but comparatively more for fir than beech. Admixing fir created an economic benefit when implemented before stand age 50 of beech. This benefit was nullified with protection costs for browsing control (fencing or tree shelters). Conclusions: Economic parameters (not CC) were the major source of uncertainty stemming from discounting factors and establishment costs. Admixture of fir and shortening rotation can provide a solution to tackle economic and climate uncertainties, but requires early admixture and browsing control. [ABSTRACT FROM AUTHOR]

When the negatively buoyant air in the cloud downdrafts reaches the surface, it spreads out horizontally, producing cold pools. A cold pool can trigger new convective cells. However, when combined with the ambient vertical wind shear, it can also connect and upscale them into large mesoscale convective systems (MCS). Given the broad spectrum of scales of the atmospheric phenomenon involving the interaction between cold pools and the MCS, a parameterization was designed here. Then, it is coupled with a classical convection parameterization to be applied in an atmospheric model with an insufficient spatial resolution to explicitly resolve convection and the sub‐cloud layer. A new scalar quantity related to the deficit of moist static energy detrained by the downdrafts mass flux is proposed. This quantity is subject to grid‐scale advection, mixing, and a sink term representing dissipation processes. The model is then applied to simulate moist convection development over a large portion of tropical land in the Amazon Basin in a wet and dry‐to‐wet 10‐days period. Our results show that the cold pool edge parameterization improves the organization, longevity, propagation, and severity of simulated MCS over the Amazon and other different continental areas. Plain Language Summary: In nature, cold pools are formed by cold air masses descending from the low to mid‐troposphere in thunderstorms. When these drafts reach the surface, they spread out horizontally. A manifestation of cold pools is the relatively high speed at the gust front, which can lift environmental air producing new convective cells. Moreover, depending on ambient conditions, the cold pools may help organize the new convective cells, increasing their aggregation and forming the so‐called mesoscale convective systems (MCSs). MCSs, which cover hundreds to thousands of km2, significantly impact the global scale circulation, energy budget, hydrological cycle, and population safety. Forecasting MCSs is challenging for global circulation models (GCM) due to the broad spectrum of scales of the involved atmospheric phenomenon. The computational limitations, at present and for some time to come, do not allow running in real‐time GCMs, which explicitly solves all relevant scales of motion. This paper describes a methodology to account for essential interplays between cold pools edges and moist convection to be applied in the GCMs of weather and climate forecasting. We show that the method improves the model simulation of the main types of MCSs over the Amazon Basin and other continental areas. Key Points: A model scheme for including effect of cold pools edges in triggering new convective cells and storm propagation is presentedThe scheme is coupled with a convection parameterization and applied in the modeling of moist convective systemsThe method improves the organization, longevity, propagation, and severity of the simulated mesoscale convective systems [ABSTRACT FROM AUTHOR]

In this paper, we constructed the Exospheric Temperature Models (ETM) on the basis of CHAMP and GRACE data using different empirical orthogonal functions (EOFs). The EOFs of the exospheric temperature can be derived either from satellite data directly or from the outputs of the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) and MSIS models by applying the Principal Component Analysis method. Then, the thermospheric mass densities calculated from ETM are used to compare with the observed data in order to evaluate the performance of different ETM models. It was found that all these three models can provide good specification of thermospheric density including day‐night, seasonal, and latitudinal variations. However, the ETM based on CHAMP and GRACE data gives a better performance in modeling the Equatorial Thermospheric Anomaly and the Midnight Density Maximum features than the MSIS‐ETM and TIEGCM‐ETM. Specifically, independent SWARM‐C data comparison showed that the Relative Deviations and corresponding Root‐Mean‐Square‐Errors of our Texo models are less than 8.9% and 22.8%, much better than the MSIS‐00 model. Plain Language Summary: Exospheric temperature, the atmospheric temperature at an altitude above 300 km, is a critical parameter used in most thermospheric density models. In this study, we use different mathematical functions to construct the exospheric temperature models (ETM) named ETM, MSIS‐ETM, and Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM)‐ETM, respectively based on the CHAMP and GRACE density observations. The mathematical functions can be derived either using the data‐driven method or using the model‐driven method. Our purpose is to evaluate the performance of these constructed models in reflecting the thermosphere, and we found that all these models can provide good specification of the thermosphere such as the typical day‐night, seasonal, and latitudinal variation characteristics. Overall, the ETM constructed by using the data‐driven method gives a better performance than the MSIS‐ETM and TIEGCM‐ETM, and it can effectively simulate the physical features that are observed in the thermosphere. Our results indicate that compared with the model‐driven method utilizing the sufficient data‐driven PCA method to bend the exospheric temperature model is also an effective way. Key Points: Exospheric Temperature Models (ETM) are constructed on the basis of CHAMP and GRACE data using different empirical orthogonal functions (EOFs)The three ETM models can provide good specification of thermospheric density after they are embedded in the MSISThe ETM with EOFs directly from the observations gives a better performance than those with EOFs obtained from the MSIS and Thermosphere Ionosphere Electrodynamics General Circulation Model models [ABSTRACT FROM AUTHOR]

It is shown that a recently developed hybrid modeling approach that combines machine learning (ML) with an atmospheric global circulation model (AGCM) can serve as a basis for capturing atmospheric processes not captured by the AGCM. This power of the approach is illustrated by three examples from a decades‐long climate simulation experiment. The first example demonstrates that the hybrid model can produce sudden stratospheric warming, a dynamical process of nature not resolved by the low resolution AGCM component of the hybrid model. The second and third example show that introducing 6‐hr cumulative precipitation and sea surface temperature (SST) as ML‐based prognostic variables improves the precipitation climatology and leads to a realistic ENSO signal in the SST and atmospheric surface pressure. Plain Language Summary: This paper introduces and tests schemes for efficiently enabling significant expansion of the utility and scope of a recently introduced hybrid modeling technique that combines machine learning with an atmospheric global circulation model (AGCM). Simulation experiments are carried out with an implementation of the approach on a low resolution simplified AGCM. An examination of the simulated atmospheric circulation suggests that the hybrid model can capture dynamical process not captured by the AGCM. Moreover, the addition of precipitation and sea surface temperature (SST) as machine learning predicted physical quantities to the model improves the precipitation climatology and leads to a realistic El Niño‐La Niña signal in the SST and atmospheric surface pressure. Key Points: A hybrid system combining an atmospheric global circulation model (AGCM) with a machine‐learning component can capture processes not captured by the AGCMMachine learning provides a flexible framework to introduce additional prognostic variables into the hybrid modelThe prototype hybrid model tested in the paper is stable and has a realistic climate in decades‐long simulation experiments [ABSTRACT FROM AUTHOR]

Air-sea CO2 fluxes over the Pacific Ocean are known to be characterized by coherent large-scale structures that reflect not only ocean subduction and upwelling patterns, but also the combined effects of wind-driven gas exchange and biology. On the largest scales, a large net CO2 influx into the extra-tropics is associated with a robust seasonal cycle, and a large net CO2 efflux from the tropics is associated with substantial inter-annual variability. In this work, we have synthesized estimates of the net air-sea CO2 flux from a variety of products drawing upon a variety of approaches in three sub-basins of the Pacific Ocean, i.e., the North Pacific extra-tropics (18° N-66° N), the tropical Pacific (18° S-18° N), and the South Pacific extra-tropics (44.5° S-18° S). These approaches include those based on the measurements of CO2 partial pressure in surface seawater (pCO2sw), inversions of ocean interior CO2 data, forward ocean biogeochemistry models embedded in the ocean general circulation models (OBGCMs), a model with assimilation of pCO2sw data, and inversions of atmospheric CO2 measurements. Long-term means, inter-annual variations and mean seasonal variations of the regionally-integrated fluxes were compared in each of the sub-basins over the last two decades, spanning the period from 1990 through 2009. A simple average of the long-term mean fluxes obtained with surface water pCO2 diagnostics and those obtained with ocean interior CO2 inversions are -0.47 ± 0.13PgCyr-1 in the North Pacific extra-tropics, +0.44 ± 0 .14PgCyr-1 in the tropical Pacific, and -0.37 ± 0.08PgCyr-1 in the South Pacific extra-tropics, where positive fluxes are into the atmosphere. This suggests that approximately half of the CO2 taken up over the North and South Pacific extra-tropics is released back to the atmosphere from the tropical Pacific. These estimates of the regional fluxes are also supported by the estimates from OBGCMs after adding the riverine CO2 flux, i.e., -0.49 ± 0.02PgCyr-1 in the North Pacific extratropics, +0.41 ± 0.05PgCyr-1 in the tropical Pacific, and -0.39 ± 0.11 PgCyr-1 in the South Pacific extra-tropics. The estimates from the atmospheric CO2 inversions show large variations amongst different inversion systems, but their median fluxes are consistent with the estimates from climatological pCO2sw data and pCO2sw diagnostics. In the South Pacific extra-tropics, where CO2 variations in the surface and ocean interior are severely under-sampled, the difference in the air-sea CO2 flux estimates between the diagnostic models and ocean interior CO2 inversions is larger (0.18 PgCyr-1). The range of estimates from forward OBGCMs is also large (-0.19 to -0.72 PgCyr-1). Regarding inter-annual variability of air-sea CO2 fluxes, positive and negative anomalies are evident in the tropical Pacific during the cold and warm events of the El Nino Southern Oscillation in the estimates from pCO2sw diagnostic models and from OBGCMs. They are consistent in phase with the Southern Oscillation Index, but the peak-to-peak amplitudes tend to be higher in OBGCMs (0.40 ± 0.09 PgCyr-1) than in the diagnostic models (0.27 ± 0.07PgCyr-1). [ABSTRACT FROM AUTHOR]

Using the general circulation model ECHAM5-JSBACH forced by observed sea surface temperatures (SSTs) for the 20th century, we investigate the role of vegetation and land surface albedo dynamics in shaping rainfall variability in the Sahel.We use two different land surface albedo schemes, one in which the albedo of the canopy is varying and one in which additionally the albedo changes of the surface below the canopy are taken into account. The SST-forcing provides the background for simulating the observed decadal signal in Sahelian rainfall, though the respone to SST-forcing only is not strong enough to fully capture the observed signal. The introduction of dynamic vegetation leads to an increase in inter-annual variability of the rainfall, and gives rise to an increased number of high amplitude rainfall anomaly events. The dynamic background albedo leads to an increased persistence of the rainfall anomalies. The increase in persistence means that the difference between the dry and the wet decades is increased compared to the other simulations, and thus more closely matching the observed absolute change between these two periods. These results highlight the need for a consistent representation of land surface albedo dynamics for capturing the full extent of rainfall anomalies in the Sahel. [ABSTRACT FROM AUTHOR]

One of the largest sources of uncertainties in modelling of the future global climate is the response of the terrestrial carbon cycle. Studies have shown that it is likely that the extant land sink of carbon will weaken in a warming climate. Should this happen, a larger portion of the annual carbon dioxide emissions will remain in the atmosphere, and further increase the global warming, which in turn may further weaken the land sink. We investigate the potential sensitivity of global terrestrial ecosystem carbon balance to differences in future climate simulated by four general circulation models (GCMs) under three different CO2 concentration scenarios. We find that the response in simulated carbon balance is more influenced by GCMs than CO2 concentration scenarios. Singular Value Decomposition (SVD) analysis of sea surface temperatures (SSTs) reveals differences in the GCMs SST variability leading to decreased tropical ecosystem productivity in two out of four GCMs. We extract parameters describing GCM characteristics by parameterizing a statistical replacement model mimicking the simulated carbon balance results. By sampling two GCM-specific parameters and global temperatures we create 60 new "artificial" GCMs and investigate the extent to which the GCM characteristics may explain the uncertainty in global carbon balance under future radiative forcing. Our analysis suggests that differences among GCMs in the representation of SST variability and ENSO and its effect on precipitation and temperature patterns explains the majority of the uncertainty in the future evolution of global terrestrial ecosystem carbon. [ABSTRACT FROM AUTHOR]

There is great uncertainty about the future effects of climate change on the global economic, social, environmental, and water sectors. This paper focuses on watershed vulnerabilities to climate change by coupling a distributed hydrological model with artificial neural networks and spatially distributed indicators for the use of a predictive model of such vulnerability. The analyses are complemented by a Monte Carlo evaluation of the uncertainty associated with the projections of the global circulation models, including how such uncertainty impacts the vulnerability forecast. To test the proposal, the paper uses current and future vulnerabilities of the Turbio River watershed, located in the semi-arid zone of Guanajuato (Mexico). The results show that nearly 50% of the watershed currently has medium and high vulnerabilities, and only the natural areas in the watershed show low vulnerabilities. In the future, an increase from medium to high vulnerability is expected to occur in urban and agricultural areas of the basin, with an associated uncertainty of ±15 mm in the projected precipitation. [ABSTRACT FROM AUTHOR]

Although the surface energy budget is essential to determine Earth's climate, site measurements of various radiative components are still too scarce to properly characterize their spatial and temporal variations. This has led to the development of a growing number of surface radiation products, mainly including remotely sensed data, model reanalysis data, and simulations using General Circulation Models (GCMs). This collection of papers introduces new techniques, including the use of machine learning methods for radiation estimation, and evaluates and compares various radiation products, as well as their spatio-temporal variations. These studies show large discrepancies among various products across nearly all radiative parameters in either accuracy or spatio-temporal variations. However, remotely sensed radiation products perform relatively better than others. Despite this, there is an urgent need for further efforts to address these discrepancies and improve the accuracy of these estimates. Even though the major radiative parameters including downward shortwave radiation, net longwave radiation, and albedo, from most products show insignificant long-term variation trends on a global scale, only specific regions, such as the Yunnan-Kweichow Plateau (YKP) and regions with permafrost (i.e. Qinghai-Tibet Plateau and Arctic) and glaciers (i.e. Altai Mountains) exhibit remarkable trends. [ABSTRACT FROM AUTHOR]

In this paper we develop a novel framework aimed to significantly reduce biases related to marine stratocumulus clouds in general circulation models (GCMs) while circumventing excessive computational cost requirements. Our strategy is to increase the horizontal resolution using a regionally refined mesh (RRM) over our region of interest in addition to using the Framework for Improvement by Vertical Enhancement (FIVE) to increase the vertical resolution only for specific physical processes that are important for stratocumulus. We apply the RRM off the coast of Peru in the southeastern Pacific, a region that climatologically contains the most marine stratocumulus in the subtropics. We find that our new modeling framework is able to replicate the results of our high-resolution benchmark simulation with much fidelity, while reducing the computational cost by several orders of magnitude. In addition, this framework is able to greatly reduce the long-standing biases associated with marine stratocumulus in GCMs when compared to the standard-resolution control simulation. [ABSTRACT FROM AUTHOR]

The article presents a study which compares the changes in global mean temperature obtained from emission driven Global Climate Model (GCM) in response to various future scenarios. It states GCM simulations models uncertainties in atmospheric feedbacks, ocean physics, and land carbon cycle and aerosol sulphur cycles. It suggests that uncertainty sampling from the emission leads to a wide range of atmospheric concentrations and results of changes in temperature.

The article reports on the implementation of the HadGEM2-ES Coupled Model Intercomparison Project (CMIP5), a standard experimental protocol for studying the output of general circulation models (GCMs). It covers the greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the experiments. It also details how the HadGEM2-ES ensemble members were initialised from the control run.

Reliable projection of evapotranspiration (ET) is important for planning sustainable water management for the agriculture field in the context of climate change. A global dataset of monthly climate variables was generated to estimate potential ET (PET) using 14 General Circulation Models (GCMs) for four main shared socioeconomic pathways (SSPs). The generated dataset has a spatial resolution of 0.5° × 0.5° and a period ranging from 1950 to 2100 and can estimate historical and future PET using the Penman-Monteith method. Furthermore, this dataset can be applied to various PET estimation methods based on climate variables. This paper presents that the dataset generated to estimate future PET could reflect the greenhouse gas concentration level of the SSP scenarios in latitude bands. Therefore, this dataset can provide vital information for users to select appropriate GCMs for estimating reasonable PETs and help determine bias correction methods to reduce between observation and model based on the scale of climate variables in each GCM. [ABSTRACT FROM AUTHOR]

The ratio of O to N2 number densities (O/N2) at different altitudes is an important parameter in describing thermospheric neutral composition changes and their effects on the ionosphere during geomagnetic storms. However, storm‐induced vertical variations in O/N2 and its dependence on the O and N2 perturbations are still not fully understood. Here, the Thermosphere/Ionosphere Electrodynamics General Circulation Model simulations were used to investigate the responses of thermospheric composition at different pressure levels to the super geomagnetic storm occurred on November 20 and 21 in 2003. Our analysis shows that the behaviors of O/N2 perturbations on different pressure levels are similar above ∼180 km altitude. In the middle and low thermosphere of below ∼300 km, the storm‐time O/N2 decrease is mainly caused by a large reduction of O number density. However, N2 enhancement plays a vital role in O/N2 decreases in the upper thermosphere. The O/N2 enhancement is mainly attributed to the N2 decreases at all pressure levels. The changes of O and N2 number densities at a constant pressure level can be explained by the perturbations of their mass mixing ratio (mmr) and total mass density (ρ). The regions of the O/N2 decrease are characterized by the O mmr decrease and N2 mmr enhancement, whereas the regions of the O/N2 increase are characterized by the O mmr increase and N2 mmr decrease. The ρ value that shows the decrease globally at most pressure levels during the storm either enhance or reduce the O and N2 perturbations. Plain Language Summary: The column O/column N2 density ratio (∑O/N2) was usually used to describe thermospheric neutral composition responses to geomagnetic storms and the storm effects on ionospheric plasma density. However, thermospheric circulation changed considerably during the storm, resulting in discrepancies in composition at different altitudes. Additionally, the daytime electron density changes during geomagnetic storms are more related to those of local O/N2 at a given altitude, not the ∑O/N2. Therefore, it is important to fully understand the storm‐induced vertical variations in O, N2 and O/N2 perturbations. In this paper, the vertical variations in O/N2 and its dependence on the O and N2 perturbations during the 20–21 November 2003 storm are investigated by the numerical simulations. Our results shows that the behaviors of O and N2 perturbations depend much on the altitude, but those of O/N2 on different pressure levels are similar, especially above ∼180 km. This study helps us better understand the physical process of storm‐time ∑O/N2 variations based on the observations. Key Points: In middle and low thermosphere of below ∼300 km, storm‐time decreases of the ratio of O/N2 volume density are mainly caused by O reductionIn the upper thermosphere, N2 enhancement plays a vital role in the decreases of the ratio of O/N2 volume density during the stormAt all pressure levels, storm‐time increases of the ratio of O/N2 volume density depend more on the N2 decreases [ABSTRACT FROM AUTHOR]

We address the question of how to use a machine learned (ML) parameterization in a general circulation model (GCM), and assess its performance both computationally and physically. We take one particular ML parameterization (Guillaumin & Zanna, 2021, https://doi.org/10.1002/essoar.10506419.1) and evaluate the online performance in a different model from which it was previously tested. This parameterization is a deep convolutional network that predicts parameters for a stochastic model of subgrid momentum forcing by mesoscale eddies. We treat the parameterization as we would a conventional parameterization once implemented in the numerical model. This includes trying the parameterization in a different flow regime from that in which it was trained, at different spatial resolutions, and with other differences, all to test generalization. We assess whether tuning is possible, which is a common practice in GCM development. We find the parameterization, without modification or special treatment, to be stable and that the action of the parameterization to be diminishing as spatial resolution is refined. We also find some limitations of the machine learning model in implementation: (a) tuning of the outputs from the parameterization at various depths is necessary; (b) the forcing near boundaries is not predicted as well as in the open ocean; (c) the cost of the parameterization is prohibitively high on central processing units. We discuss these limitations, present some solutions to problems, and conclude that this particular ML parameterization does inject energy, and improve backscatter, as intended but it might need further refinement before we can use it in production mode in contemporary climate models. Plain Language Summary: This paper discusses how machine learning can be used to make climate models more accurate. Specifically, we import an existing machine learning model that predicts how small eddies (in the order of 10–100 km) in the ocean affect larger currents. We test this machine learning model in a different ocean circulation model than the one it was originally designed for, and found that it worked well. However, we also found some limitations: the model works differently at different depths in the ocean, and it does not work as well near the coasts of the ocean. We also found that the model takes a long time to run on normal computers. Overall, we concluded that the model is promising, but more work is needed to make it work well in realistic situations. Key Points: A stochastic‐deep learning model is implemented in an ocean circulation model, MOM6We evaluate the online performance of the stochastic‐deep learning model as a subgrid parameterizationWe identify certain limitations of the machine learned parameterization which otherwise has the potential to improve specific metrics [ABSTRACT FROM AUTHOR]

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper evaluated and compared the performance of a statistical downscaling method and a dynamical downscaling method to simulate the spatial–temporal rainfall distribution. Outputs from RegCM4 Regional Climate Model (RCM) and the CanESM2 Atmosphere–Ocean General Circulation Model (AOGCM) were selected for the data scarce Gwadar‐Ormara basin, Pakistan. The evaluation was based on the climatological average and standard deviation for historic (1971–2000) and future (2041–2070) time periods under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. The performance evaluation showed that statistical downscaling is preferred to simulate and project rainfall patterns in the study area. Additionally, the Statistical DownScaling Model (SDSM) showed low R2 values in calibration and validation of the simulations with respect to observed data for the historic period. Overall, SDSM generated satisfactory results in simulating the monthly rainfall cycle of the entire basin. In this study, RegCM4 showed large rainfall errors and missed one rainfall season in the historic period. This study also explored whether the grid‐based rainfall time series of the Asian Precipitation—Highly Resolved Observational Daily Integration Towards Evaluation (APHRODITE) dataset could be used to enlarge and complement the sample of in situ observed rainfall time series. A spatial correlogram was used for observed and APHRODITE rainfall data to assess the consistency between the two data sources, which resulted in rejecting APHRODITE data. For the future time period (2041–2070) under RCPs 4.5 and 8.5 scenarios, rainfall projections did not show significant difference for both downscaling approaches. This may relate to the driving model (CanESM2 AOGCM) and not necessarily suggests poor performance of downscaling; either statistical or dynamical. Hence, the study recommends evaluating a multi‐model ensemble including other GCMs and RCMs for the same area of study. [ABSTRACT FROM AUTHOR]

The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to simulate the observed rainfall using the latest state-of-the-art model is essential for reliable forecasting. Based on this background, this paper objectively aims at assessing and ranking the capabilities of the recent Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the observed rainfall over the Philippines. The Global Precipitation Climatology Project (GPCP) v2.3 was used as a proxy to gauge the performance of 11 CMIP6 models in simulating the annual and rainy-season rainfall during 1980–2014. Several statistical metrics (mean, standard deviation, normalized root means square error, percentage bias, Pearson correlation coefficient, Mann–Kendall test, Theil–Sen slope estimator, and skill score) and geospatial measures were assessed. The results show that that CMIP6 historical simulations exhibit satisfactory effectiveness in simulating the annual cycle, though some models display wet/dry biases. The CMIP6 models generally underestimate rainfall on the land but overestimate it over the ocean. The trend analysis shows that rainfall over the country is insignificantly increasing both annually and during the rainy seasons. Notably, most of the models could correctly simulate the trend sign but over/underestimate the magnitude. The CMIP6 historical rainfall simulating models significantly agree on simulating the mean annual cycle but diverge in temporal ability simulation. The performance of the models remarkably differs from one metric to another and among different time scales. Nevertheless, the models may be ranked from the best to the least best at simulating the Philippines' rainfall in the order GFDL, NOR, ACCESS, ENS, MRI, CMCC, NESM, FIO, MIROC, CESM, TAI, and CAN. The findings of this study form a good basis for the selection of models to be used in robust future climate projection and impact studies regarding the Philippines. The climate model developers may use the documented shortcoming of these models and improve their physical parametrization for better performance in the future. [ABSTRACT FROM AUTHOR]

Precipitation is highly variable on spatial scales smaller than a typical general circulation model (GCM) grid box. Neglecting this subgrid‐scale variability can impact the simulation of the underlying land surface and its coupling with the atmosphere. In this study we present a scheme to stochastically disaggregate precipitation from an atmospheric grid to an underlying mosaic of surface tiles, using an assumed probability distribution of subgrid precipitation derived from observations. Unlike previous GCM‐based schemes, our approach includes a treatment of memory to allow persistence of subgrid features. In single column model experiments, we demonstrate the ability of the scheme to reproduce observed precipitation statistics at the spatial scale of the surface tiles. The root mean square error of hourly spatial standard deviation of precipitation is reduced from 1.90 to 0.96 mm hr−1 when disaggregation is applied. The scheme increases the spatial standard deviations of surface heat fluxes, soil moisture and temperature, and we show that incorporating memory amplifies these increases by a factor of 2–4. We also document increases in mean precipitation runoff and the Bowen ratio. Plain Language Summary: Global climate and weather models (GCMs), used for global warming projections and near‐term weather prediction, represent the atmosphere on a grid, while the underlying land surface is often composed of smaller elements. In most models, all surface elements under a given atmospheric grid point receive the same precipitation rate. However, real‐world precipitation rates vary significantly over the scale of a GCM grid cell. This paper presents an approach to represent subgrid precipitation variability in a GCM. Grid mean precipitation is randomly distributed across surface elements, such that surface precipitation reproduces observed statistics. The approach is found to increase grid cell‐averaged surface runoff as well as the spatial variances of surface temperature, soil moisture, and surface sensible heat and moisture fluxes. Key Points: A parameterization is developed to stochastically distribute precipitation across subgrid surface tiles within a general circulation model (GCM)In single column experiments, the scheme reproduces observed precipitation statistics at the scale of land surface tilesThe scheme increases surface runoff, Bowen ratio, and the spatial variance of surface properties at the ARM Southern Great Plains site [ABSTRACT FROM AUTHOR]

This paper evaluates barotropic tides simulated by a newly developed multi-layer ocean general circulation, ICON-O, and assesses processes and model configurations that can impact the quality of the simulated tides. Such an investigation is crucial for applications addressing internal tides that are much more difficult to evaluate than the barotropic tides. Although not specially tuned for tides and not constrained by any observations, ICON-O is capable of producing the main features of the open-ocean barotropic tides as described by the geographical distributions of amplitude, phase, and amphidromic points. An error analysis shows, however, that the open-ocean tides simulated by ICON-O are less accurate than those simulated by two other ocean general circulation models (OGCMs), especially when not properly adjusting the time step and the parameters used in the time-stepping scheme. Based on a suite of tidal experiments, we show that an increase in horizontal resolution only improves tides in shallow waters. Relevant for using ICON-O with its telescoping grid capacity, we show that spatial inhomogeneity does not deteriorate the quality of the simulated tides. We further show that implementing a parameterization of topographic wave drag improves the quality of the simulated tides in deep ocean independent of the model configuration used, whereas the implementation of a self-attraction and loading (SAL) parameterization in a low-resolution (40 km) version of ICON-O degrades the quality of tides in shallow ocean. Finally, we show that the quality of tides simulated by ICON-O with low resolution (40 km) can be significantly improved by adjusting the time step or the parameters in the time-stepping scheme used for obtaining the model solution. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is expected to cause an increase in fire danger over south-eastern Australia during the 21st century, primarily driven by increased surface temperature. Studies of future fire weather in Victoria, Australia, have so far mostly utilised direct output from general circulation models, which have inadequate resolution for resolving the dynamics of local fire danger and are prone to substantial biases that may affect the seasonality of dry fuels. In this paper, we assess the ability of the Multivariate Adaptive Constructed Analogs (MACA) method to downscale output from general circulation models over Victoria, and replicate statistical attributes of fire danger indices. We find that climatological descriptors of meteorological variables of wind, temperature and humidity are captured extremely well, and fields on extreme fire days are well captured. We find that the method works very well for statistically downscaling fire weather elements over Victoria and provides a vehicle to assess the regional variation of fire weather projections over Victoria. This paper evaluates the computationally efficient Multivariate Adaptive Constructed Analogs (MACA) method for downscaling a single general circulation model to a fine scale over the state of Victoria, Australia. Comparison with a 4-km fire weather climatology dataset shows the method well reproduces observed statistics of mean and extreme fire weather. Photo showing planned burn in Victoria, Australia, by Tim Brown. [ABSTRACT FROM AUTHOR]

Atmospheric radiation is one of the most important atmospheric physics, and its expensive computation cost severely restricts the numerical simulation of atmospheric general circulation models. Therefore, it is necessary to study an efficient radiation parameterization scheme. Due to the powerful computing power of GPU, more and more numerical models are being transplanted to GPU. The CUDA C version (CC-RRTMG_SW) of the rapid radiative transfer model for general circulation models (RRTMG) shortwave radiation scheme (RRTMG_SW) has successfully run on GPU, but its computing efficiency is not yet very high, and the performance potential of GPU computing needs to be realized further. This paper is dedicated to optimizing CC-RRTMG_SW and exploring its maximum computing performance on GPU. First, a three-dimensional acceleration algorithm for CC-RRTMG_SW is proposed. Then, some optimization methods, such as decoupling data dependency, optimizing memory access, and I/O optimization, are studied. Finally, the optimized version of CC-RRTMG_SW is developed, namely CC-RRTMG_SW++. The experimental results demonstrate that the proposed acceleration algorithm and performance optimization methods are effective. CC-RRTMG_SW++ achieved good acceleration effects on different GPU architectures, such as NVIDIA Tesla K20, K40, and V100. Compared to RRTMG_SW running on a single Intel Xeon E5-2680 v2 CPU core, CC-RRTMG_SW++ obtained a speedup of 99.09 × on a single V100 GPU without I/O transfer. Compared to CC-RRTMG_SW, the computing efficiency of CC-RRTMG_SW++ increased by 174.46%. [ABSTRACT FROM AUTHOR]

In this study, we used observations from multiple instruments (all‐sky imager [ASI], digisonde, and Beidou geostationary satellite global positioning system receivers) to show the occurrence and evolution of two plasma density enhancement structures (PDESs) during the night of 8 February and 4 November 2018. The PDESs were elongated from northwest to southeast. Their zonal scales were about 200–400 km and longitudinal ranges were about 800–1,400 km. Within the PDES, the plasma density can be enhanced by about two times over the background density. The PDESs appeared before midnight and gradually dissipated after midnight. Plasma density depletion structures appeared within the PDES at the later stage of PDES. Each PDES event lasted for over 4 hours. The morphology and evolution of the PDESs presented in this paper are different from those reported in previous studies. In addition, based on the thermosphere‐ionosphere‐electrodynamics general circulation model simulations and digisonde observations, we proposed a possible cause for the PDESs in the events, in which the occurrence and evolution of PDES are related to the variations of thermospheric meridional winds in the equatorial region. Plain Language Summary: Ionospheric plasma irregularities or disturbances are frequently observed in the equatorial region and have been the focus of ionospheric research. These irregularities include plasma bubbles, traveling ionospheric disturbances, and plasma density enhancements. They have a great impact on the trans‐ionospheric radio wave signals. Most of the previous studies show that the plasma density enhancements occur over large scales and the occurrence of plasma density enhancements is usually accompanied by plasma density depletions in the adjacent areas, and hence, the formation of the density enhancement is suggested to be related to the plasma density depletion. In this study, two unique plasma density enhancement structures (PDESs) were observed using multiple instruments. The observed plasma density enhancements were elongated from northwest to southeast, which is different from previous studies. This paper presents the full evolution of the plasma density enhancement from its appearance to disappearance. In addition, we proposed a possible formation process for the equatorial plasma density enhancement in which the occurrence and evolution of PDES are related to the variations of thermospheric meridional winds in the equatorial region. Our results provide new insight into the dynamics and variability of the coupled thermosphere and ionosphere system in the equatorial region. Key Points: Evolution of equatorial ionospheric plasma density enhancements from occurrence to disappearance was illustrated with multiple data setsThe plasma density enhancement structures (PDESs) were elongated from northwest to southeast, with their sizes changing with time, and they produced Spread F in ionogramsVariations in neutral winds may contribute to the occurrence of the observed PDES [ABSTRACT FROM AUTHOR]

General circulation models are a useful tool in understanding the three dimensional structure of hot Jupiter and sub-Neptune atmospheres; however, understanding the validity of the results from these simulations requires an understanding of the artificial dissipation required for numerical stability. In this paper, we investigate the impact of the longitudinal filter and vertical 'sponge' used in the Met Office's unified model when simulating gaseous exoplanets. We demonstrate that excessive dissipation can result in counter-rotating jets and a catastrophic failure to conserve angular momentum. Once the dissipation is reduced to a level where a super-rotating jet forms, however, the jet and thermal structure are relatively insensitive to the dissipation, except in the nightside gyres where temperatures can vary by |$\sim 100\, \mathrm{K}$|⁠. We do find, however, that flattening the latitudinal profile of the longitudinal filtering alters the results more than a reduction in the strength of the filtering itself. We also show that even in situations where the temperatures are relatively insensitive to the dissipation, the vertical velocities can still vary with the dissipation, potentially impacting physical processes that depend on the local vertical transport. [ABSTRACT FROM AUTHOR]

This document is a corrigendum for an article titled "A seasonal undercurrent along the northwest coast of Australia." The author acknowledges an error in the analytic solutions and figures presented in the original article. The corrected solutions and figures have been provided, and the author states that this error does not affect the scientific conclusions of the article. The corrigendum was published in the journal Frontiers in Marine Science. [Extracted from the article]

Philosophers have yet to provide a systematic analysis of the relationship between historical science and model-based science. In this paper I argue that prototypical model-based sciences exhibit features understood to be central to historical science. Philosophers of science have argued that historical scientists are distinctly concerned with inference to the best explanation, that explanations in historical science tend to increase in complexity over time, and that the explanations take the form of narratives. Using general circulation models in climate science as a reference, I illustrate how simulation models in model-based science share these features exhibited by historical science. That model based sciences share these features raises important philosophical questions about how we should understand prototypical types of scientific enquiry, including the relationship between experimental science, historical science, and model-based science. I conclude by exploring several options for how to accommodate the noted similarities within a more general taxonomy of the sciences. [ABSTRACT FROM AUTHOR]

This paper introduces the new Venus global ionosphere‐thermosphere model (V‐GITM) which incorporates the terrestrial GITM framework with Venus‐specific parameters, ion‐neutral chemistry, and radiative processes in order to simulate some of the observable features regarding the temperatures, composition, and dynamical structure of the Venus atmosphere from 70 to 170 km. Atmospheric processes are included based upon formulations used in previous Venus GCMs, several augmentations exist, such as improved horizontal and vertical momentum equations and tracking exothermic chemistry. Explicitly solving the momentum equations allows for the exploration of its dynamical effects on the day‐night structure. In addition, V‐GITM's use of exothermic chemistry instead of a strong heating efficiency accounts for the heating due to the solar EUV while producing comparable temperatures to empirical models. V‐GITM neutral temperatures and neutral‐ion densities are compared to upper atmosphere measurements obtained from Pioneer Venus and Venus Express. V‐GITM demonstrates asymmetric horizontal wind velocities through the cloud tops to the middle thermosphere and explains the mechanisms for sustaining the wind structure. In addition, V‐GITM produces reasonable dayside ion densities and shows that the neutral winds can carry the ions to the nightside via an experiment advecting O2+ ${\mathrm{O}}_{2}^{+}$. Plain Language Summary: We present a new, state‐of‐the‐art Venus global circulation model, the Venus global ionosphere thermosphere model. The new model will be useful for answering unknown questions about Venus' atmosphere, the physics of CO2 rich planets, and Venus missions utilizing the aerobraking maneuver. We performed many model simulations and compared the results to some of the existing Venus data sets to assess the accuracy of the model. The results showed that the dayside extreme ultraviolet heating can be captured using the dominant ion‐neutral chemistry rather than relying on simplified legacy methods. Furthermore, the cloud layer below the thermosphere has a unique wind pattern and its impact on the thermospheric temperatures and winds were explored. This work also revealed that the thin nightside ionosphere forms as a result of the transport of a single ion species. Key Points: A new, non‐hydrostatic Venus ionosphere‐thermosphere model is introduced with new physics not previously included in Venus GCMsSimulations during solar minimum conditions are used for data‐model comparisons of the temperatures, plasma, and neutral densitiesThe influence of the retrograde superrotating zonal flow is explored in relation to how it affects the neutral temperature and velocities [ABSTRACT FROM AUTHOR]

When solar wind and interplanetary magnetic field (IMF) disturb, thermospheric winds change accordingly. Among the momentum forces driving high‐latitude thermospheric winds, ion drag is supposed to greatly affect wind variations through ion‐neutral coupling when abrupt and strong changes in ion drifts occur. However, due to the great inertia of thermospheric winds it needs a certain period of time for the wind changes to be prominent both in speed and direction. How long the neutral winds take to change from one steady state to another through the ion‐neutral coupling process is currently still a controversial issue. In this paper, we examine the high latitudinal ion‐neutral coupling time scale based on the Thermosphere Ionosphere Electrodynamics General Circulation Model simulations, which can determine whether wind variations are dominantly driven by ion drag by analyzing the relative contribution of each momentum force. It is found that the spatial variation of ion‐neutral coupling time scale is primarily determined by local electron density, but also varies with neutral density and ion‐neutral collision frequency. Simulations during periods of medium solar activity at ∼250 km altitude show that the ion drag‐dominated region is generally located at the dayside convection inverse boundary and the coupling time scale (e‐folding time) is ∼1 hr when IMF By is the dominant component of the IMF and changes direction. Meanwhile, the southward component of IMF Bz enlarges the ion drag‐dominated region. When IMF Bz is southward with a large magnitude, ion drag‐dominated region is primarily located in the nightside auroral oval with ∼2 hr coupling time scale. Key Points: The spatial variation of ion‐neutral coupling time scale depends primarily on local electron densityThe ion drag dominant region is located at the dayside convection cell boundary (nightside auroral oval) when interplanetary magnetic field (IMF) By (negative Bz) disturbsWhen wind variation is greatly affected by IMF By, the concurrent negative shift of IMF Bz obviously enlarges the ion drag dominant region [ABSTRACT FROM AUTHOR]

This paper examines spectra of horizontal kinetic energy (HKE) in the surface and sub‐surface ocean, with an emphasis on internal gravity wave (IGW) motions, in global high‐resolution ocean simulations. Horizontal wavenumber‐frequency spectra of surface HKE are computed over seven oceanic regions from two global simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three global simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). In regions with high IGW activity, high surface HKE variance in the horizontal wavenumber‐frequency spectra is aligned along IGW linear dispersion curves. For both HYCOM and MITgcm, and in almost all regions, finer horizontal resolution yields more energetic supertidal IGW continuum spectra. The ratio of high‐horizontal‐wavenumber variance in semi‐diurnal and supertidal motions relative to lower‐frequency motions, a quantity of great interest for swath altimetry, depends on the model employed and the horizontal resolution within the model, implying that quantitative predictions of the partition between low‐ and high‐frequency motions taken from particular simulations should be treated with care. The frequency‐vertical wavenumber spectra, frequency spectra, and vertical wavenumber spectra from the models are compared to spectra computed from McLane profilers at nine locations. In general, MITgcm spectra match the McLane profiler spectra more closely at high frequencies (|ω| > 4.5 cpd). In both models, vertical wavenumber spectra roll off more steeply than observations at high vertical wavenumbers (m > 10−2 cpm). The vertical wavenumber spectra in such models is an important target for improvement, due to turbulence production and dissipation that takes place at high vertical wavenumbers. Plain Language Summary: Recently, a small but growing number of global ocean models have begun to employ simultaneous tidal and atmospheric forcing. At the same time, increasing supercomputer power has allowed for simulations of oceanic motions with increasing accuracy, increasing feature (spatial) resolution, and more frequent time slices. Global ocean models with fine grid spacing, and simultaneous tidal and atmospheric forcing, host a vigorous spectrum of high‐frequency waves that control mixing over most of the ocean water column, and are important for many operational oceanography challenges. As an example of the latter, high‐resolution global internal wave models have been used to study the relative partition of high‐frequency versus low‐frequency motions at the small horizontal scales that will be measured by the new Surface Water Ocean Topography mission. The partition described above depends on the model employed and the grid spacing employed within that model, meaning that conclusions about the partition are dependent on the model used to estimate it. Comparisons between the models and vertically profiling instruments indicate that resolving fine scale motions in the vertical direction, where ocean mixing takes place, is not yet handled well by the models. Modeling of fine‐vertical scale motions is therefore an important future research direction. Key Points: Vertical wavenumber spectra of internal gravity wave kinetic energy in two high‐resolution global models are compared to observed spectraModels under‐estimate motions at high vertical wavenumbers (small vertical scales), flagging this as a target for model improvementThe ratio of high‐ versus low‐frequency surface kinetic energy at small horizontal scales is dependent on the model and grid spacings employed [ABSTRACT FROM AUTHOR]

The SOLA Award in 2022 was given to two outstanding papers. The first paper, by Dr. Yasumitsu Maejima et al., focused on the potential impact of a rich phased array weather radar (PAWR) network on the numerical weather prediction (NWP) of a heavy rainfall event in Kyushu, Japan. The study showed that assimilating PAWR data improved heavy rainfall prediction up to a 1-hour lead time, suggesting that a network of fast-scanning radars combined with advanced data assimilation can lead to improved forecasts of local heavy rainfall systems. The second paper, by Dr. Tomoe Nasuno et al., examined the impact of mid-latitude sea surface temperature (SST) anomaly on tropical cyclone (TC) activity. The study demonstrated that the mid-latitude SST anomaly in the western North Pacific during the boreal summer of 2018 systematically affected TC activity and contributed to an increase in TC track density in the eastern North Pacific. This study provides new insights into the interaction between large-scale atmospheric circulation and TC activity. [Extracted from the article]

HDO and the D/H ratio are essential to understand Mars past and present climate, in particular with regard to the evolution through ages of the Martian water cycle. We present here new modeling developments of the HDO cycle with the Laboratoire de Météorologie Dynamique Mars Global Climate Model (GCM). The present study aims at exploring the behavior of the D/H ratio cycle and its sensitivity to the modeling of water ice clouds and the formulation of the fractionation by condensation. Our GCM simulations are compared with observations provided by the Atmospheric Chemistry Suite (ACS) on board the ESA/Roscosmos Trace Gas Orbiter (TGO), and reveal that the model quite well reproduces the temperature and water vapor fields, which offers a good basis for representing the D/H ratio cycle. The comparison also emphasizes the importance of modeling the state of supersaturation, resulting from the microphysical processes of water ice clouds, to correctly account for the water vapor and the D/H ratio of the middle‐to‐upper atmosphere. This work comes jointly with a detailed comparison of the measured D/H profiles by TGO/ACS and the model outputs, conducted in the companion paper of Rossi et al. (2022, https://doi.org/10.1029/2022JE007201) (this issue). Plain Language Summary: The D/H ratio observed in a planetary atmosphere is traditionally used as a proxy to estimate the initial water reservoir of the planet. We present here an improved global circulation model including HDO, the main isotope of water on Mars. The updated model takes into account the details of the formation of clouds and their radiative effect. It also includes the effect of photochemistry on HDO and deuterated species. We find that supersaturation is key to the representation of the D/H cycle by making the hygropause more porous, allowing more HDO in the upper atmosphere. It also reduces the efficiency of the isotopic fractionation occurring at condensation. We present here comparisons between observations by the Atmospheric Chemistry Suite spectrometer onboard the orbiter TGO. While the model is globally in agreement with the observations, the inability of the model to reproduce the observed vertical distribution of dust, especially during the Global Dust Storm, causes discrepancies in the representation of water vapor. The model reveals the importance of representing the state of supersaturation to correctly account for the water vapor amount reaching the top of the atmosphere and estimate the D/H ratio at escape. Key Points: The HDO cycle has been implemented in the last version of the Laboratoire de Météorologie Dynamique Mars Global Climate Model including microphysics and radiative effect of water ice cloudsKinetics effect is now included in HDO fractionation during condensation and proves to be significantSupersaturation, the presence of which is regulated by cloud processes, alters significantly the relative abundances of HDO and H2O [ABSTRACT FROM AUTHOR]

This paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century). Plain Language Summary: The projections of future climate change are uncertain because they are dependent on different possible scenarios of human‐caused emissions and their interaction with natural forcings, internal climate variability, and inter‐model differences. This paper presents the results of the climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, for the anthropogenically forced climate response for the twenty first century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The sensitivity of the model response to different magnitudes of anthropogenic forcings in the twenty‐first‐century scenarios were performed using two different versions for the atmospheric composition and two different ocean general circulation models. Compared to CMIP5 GISS‐E2 versions, the CMIP6 GISS‐E2.1 climate model shows a stronger warming by 2100 in comparable scenarios due to larger effective climate sensitivity and transient climate response. Both climate models with two different ocean components project decreases in the Atlantic overturning stream function by 2100. Key Points: GISS E2.1 model with different configurations is used to carry out 134 Shared Socioeconomic Pathway (SSP) experimentsGISS‐E2.1 climate model shows a stronger warming by 2,100 in comparable Representative Concentration Pathway scenarios in CMIP5 due to larger effective climate sensitivity and stronger transient climate responseBoth coupled models, E2.1‐G and E2.1‐H, project decreases in the Atlantic overturning stream function by 2100 with the largest decrease in the warmest scenario SSP5‐8.5 in the E2.1‐G model [ABSTRACT FROM AUTHOR]

In the aftermath of an earthquake and tsunami on 11 March 2011 considerable amounts of radioactive materials were accidentally released into the sea off Fukushima-Daiichi, Japan. This study uses a three-dimensional eddy-resolving oceanic general circulation model to explore potential pathways of a tracer, similar to 137Cs, from the coast to the open ocean. Results indicate that enhanced concentrations meet a receding spring bloom offshore and that the area of enhanced concentrations offshore is strongly determined by surface mixed layer dynamics. However, huge uncertainties remain. Among them are the realism of the simulated cross-shelf transport and apparently inconsistent estimates of the particle reactivity of 137Cs which are discussed in a brief literature review. We argue that a comprehensive set of 137Cs measurements, including sites offshore, could be a unique opportunity to both evaluate and advance the evaluation of oceanic general circulation models. [ABSTRACT FROM AUTHOR]

The article describes the energy and water components of the Joint UK Land Environment Simulator (JULES). It reveals that JULES can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. In addition, JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

The simulation of current and projected wildfires is crucial for predicting vegetation as well as pyrogenic emissions in the African continent. This study uses a data-driven approach to parameterize burned area models applicable to dynamic vegetation models (DVMs) and global circulation models (GCMs). Therefore we restricted our analysis to variables for which either projections based on climate scenarios are available, or which are calculated by DVMs and the spatial scale to one degree spatial resolution, a common scale for DVMs as well as GCMs. We used 9 years of data (2000-2008) for the variables tree and herb cover, precipitation over the last dry season, wet season and averaged over the last 2 years, a fire-danger index (the Nesterov index), population density and an annual proportion of area burned derived from the MODIS MCD45A1 product. Since the effect of fires on vegetation depends strongly on burning conditions, the timing of wildfires is of high interest too. We related the seasonal occurrence of wildfires to the Nesterov index and found a lognormal relationship with a maximum at a value of 104. We parameterized two generalized linear models, one with the full variable set (model I) and one (model II) considering only climate variables. All introduced variables resulted in an increase in model performance. Model I correctly predicts the spatial distribution and extent of fire prone areas though the total variability is under represented. Model II has a much lower performance in both aspects (correlation coefficient of predicted and observed ratio of burned area: 0.71 model I and 0.58 model II). An application of the models with simulated climate data ranging from 1980 to 2060 resulted in a strong decrease of burned area of ca. 20-25%. Since wildfires are an integral part of land use practices in Africa, this indicates a high loss in areas favourable for food production. [ABSTRACT FROM AUTHOR]

The article focuses on the use of multivariate probability density function (PDF) to solve scale gap problems on climate models and to analyze cloud fraction, condensate and droplet. It mentions the use of grid flow description language (GFDL) single column model (SCM) simulations and general circulation models to determine aerosol concentration and cloud droplet number concentration in low-level clouds. It suggests assessing the effect of aerosols in droplet number and on cloud properties.

In this paper we describe the implementation of the carbon isotopes 13C and 14C (radiocarbon) into the marine biogeochemistry model REcoM3. The implementation is tested in long-term equilibrium simulations where REcoM3 is coupled with the ocean general circulation model FESOM2.1, applying a low-resolution configuration and idealized climate forcing. Focusing on the carbon-isotopic composition of dissolved inorganic carbon (δ13CDIC and Δ14CDIC), our model results are largely consistent with reconstructions for the pre-anthropogenic period. Our simulations also exhibit discrepancies, e.g., in upwelling regions and the interior of the North Pacific. Some of these differences are due to the limitations of our ocean circulation model setup which results in a rather shallow meridional overturning circulation. We additionally study the accuracy of two simplified modelling approaches for dissolved inorganic 14C, which are faster (15 % and about a factor of five, respectively) than the complete consideration of the marine radiocarbon cycle. The accuracy of both simplified approaches is better than 5 % which should be sufficient for most studies of Δ14CDIC. [ABSTRACT FROM AUTHOR]

We introduce ModE-Sim (Modern Era SIMulations), a medium-sized ensemble of simulations with the atmospheric general circulation model ECHAM6 in its LR (low-resolution) version (T63; approx. 1.8 ∘ horizontal grid width with 47 vertical levels). At the lower boundary we use prescribed sea surface temperatures and sea ice that reflect observed values while accounting for uncertainties in these. Furthermore we use radiative forcings that also reflect observed values while accounting for uncertainties in the timing and strength of volcanic eruptions. The simulations cover the period from 1420 to 2009. With 60 ensemble members between 1420 and 1850 and 36 ensemble members from 1850 to 2009, ModE-Sim consists of 31 620 simulated years in total. ModE-Sim is suitable for many applications as its various subsets can be used as initial-condition and boundary-condition ensembles to study climate variability. The main intention of this paper is to give a comprehensive description of the experimental setup of ModE-Sim and to provide an evaluation, mainly focusing on the two key variables, 2 m temperature and precipitation. We demonstrate ModE-Sim's ability to represent their mean state, to produce a reasonable response to external forcings, and to sample internal variability. Through the example of heat waves, we show that the ensemble is even capable of capturing certain types of extreme events. [ABSTRACT FROM AUTHOR]

Tidal signatures in sporadic E (Es) layer have been confirmed by observations and simulations. However, the effect of gravity waves (GWs) on the Es layer formation process has not yet been fully understood. In this paper, the modulation of Es layers by GWs is examined through numerical simulations, in which a physics‐based model of Es layer is forced by neutral winds from the High Altitude Mechanistic General Circulation Model that can resolve GWs with horizontal wavelengths longer than 156 km (λh > 156 km). Comparison of the simulation results with and without the GWs (1,350 km > λh > 156 km) forcing reveals that the inclusion of GWs leads to short‐period (1.2–3 hr) density perturbations in Es layers, which are also seen in ground‐based ionosonde observations. At a given time, the metallic ion density at altitudes between 120 and 150 km can either increase (by up to ∼+600%) or reduce (by up to −90%) in response to GW forcing. The relative density perturbations are smaller (by up to 60%) between 90 and 120 km altitude. It is also found that the GW effect on the metallic ion density relates to the longitude, which is mostly explained by the geographical distribution of GWs activity in the mesosphere and lower thermosphere region. The longitudinal variation of the background geomagnetic field plays only a secondary role. Key Points: The modulation of Es layers by gravity waves (GWs) (1,350 km > λh > 156 km) is simulatedGWs cause short‐period (1.2–3 hr) Fe+ density perturbations, leading to production of fine structure in mid‐latitude Es layersLongitudinal dependence in Fe+ density perturbations is mainly explained by the longitudinal distribution of GWs activity in the mesosphere and lower thermosphere region [ABSTRACT FROM AUTHOR]

Climate is closely related to human life, food security and ecosystems. Forecasting future climate provides important information for agricultural production, water resources management and so on. In this paper, historical climate data from 1962–2001 was used at three sites in Tianjin Baodi, Tianjin and Tanggu districts as baseline and the model parameters were calibrated by the Long Ashton Research Station Weather Generator (LARS-WG). 2m-temperatures in 2011–2020 were verified under two scenarios, representative concentration pathway (RCP) 4.5 and RCP8.5 in different atmospheric circulation models with optimal minimum 2m-temperatures at the three sites. From 2031–2050, Tianjin will be using more moderate minimum 2m-temperatures in future simulations. Support vector machines (SVM) were used to optimize the simulated data to obtain more accurate future maximum and minimum 2m-temperatures for the three sites. The results showed that the determinant coefficient of LARS-WG simulation was 0.8 and SVM optimized determinant coefficient was 0.9 which greatly improved the prediction accuracy. The minimum and maximum future 2m-temperatures optimized under European Community Earth System Model (EC-EARTH) were relatively low and the same future 2m-temperatures optimized under Hadley Centre Global Environment Model Earth System (Had-GEM2-ES4) were high especially in the RCP8.5 scenario which simulated 2051–2070 climate. The SVM optimization showed that the maximum and minimum 2m-temperatures were in general agreement with the original simulation values. [ABSTRACT FROM AUTHOR]

In geoscience and other fields, researchers use models as a simplified representation of reality. The models include processes that often rely on uncertain parameters that reduce model performance in reflecting real‐world processes. The problem is commonly addressed by adapting parameter values to reach a good match between model simulations and corresponding observations. Different optimization tools have been successfully applied to address this task of model calibration. However, seeking one best value for every single model parameter might not always be optimal. For example, if model equations integrate over multiple real‐world processes which cannot be fully resolved, it might be preferable to consider associated model parameters as random parameters. In this paper, a random parameter is drawn from a wide probability distribution for every singe model simulation. We developed an optimization approach that allows us to declare certain parameters random while optimizing those that are assumed to take fixed values. We designed a corresponding variant of the well known Covariance Matrix Adaption Evolution Strategy (CMA‐ES). The new algorithm was applied to a global biogeochemical circulation model to quantify the impact of zooplankton mortality on the underlying biogeochemistry. Compared to the deterministic CMA‐ES, our new method converges to a solution that better suits the credible range of the corresponding random parameter with less computational effort. Plain Language Summary: In geoscience and other fields, researchers use models as a simplified representation of reality. The models include processes that often rely on uncertain parameters that reduce model performance in reflecting real‐world processes. The problem is commonly addressed by adapting parameter values to reach a good match between model simulations and corresponding observations. However, seeking one best value for every single model parameter might not always be optimal. For example, if model equations integrate over multiple real‐world processes it might be preferable to consider associated model parameters as random parameters that are drawn from a wide probability distribution for every single model simulation. To explore this further, we modified a popular variant of the Covariance Matrix Adaption Evolution Strategy (CMA‐ES) in order to tune the other parameters. The new algorithm was applied to a global biogeochemical circulation model to quantify the impact of zooplankton mortality on the underlying biogeochemistry. Compared to the deterministic CMA‐ES our new method converges to a solution that better suits the credible range of the corresponding random parameter. Key Points: Model calibration is an important task in the view of parametric uncertaintiesWe allow specific uncertain model parameters to be random while optimizing other model parameters, providing an efficient tool for the taskWe apply it to a global biogeochemical circulation model to quantify the impact of zooplankton mortality on the underlying biogeochemistry [ABSTRACT FROM AUTHOR]

The potential role of the New England seamount chain (NESC) on the Gulf Stream pathway and variability has been long recognized, and the series of numerical experiments presented in this paper further emphasize the importance of properly resolving the NESC when modeling the Gulf Stream. The NESC has a strong impact on the Gulf Stream pathway and variability, as demonstrated by comparison experiments with and without the NESC. With the NESC removed from the model bathymetry, the Gulf Stream remains a stable coherent jet much farther east than in the experiment with the NESC. The NESC is the leading factor destabilizing the Gulf Stream and, when it is not properly resolved by the model's grid, its impact on the Gulf Stream's pathway and variability is surprisingly large. A high-resolution bathymetry, which better resolves the New England seamounts (i.e., narrower and rising higher in the water column), leads to a tighter Gulf Stream mean path that better agrees with the observed path and a sea surface height variability distribution that is in excellent agreement with the observations. [ABSTRACT FROM AUTHOR]

We develop a doubly periodic version of the Simple Convection‐Permitting E3SM Atmosphere Model (SCREAM) to provide an efficient configuration for this global convection permitting model (GCPM), akin to a single column model often found in conventional general circulation models. The design details are explained, in addition to the extensive case library associated with the doubly periodic SCREAM (DP‐SCREAM) configuration. We demonstrate that doubly periodic cloud resolving models are useful tools to explore the horizontal resolution sensitivity of GCPMs, in addition to replicating biases seen in the global models. Using DP‐SCREAM, we show that SCREAM exhibits behaviors of a scale aware model as it is able to naturally partition between sub‐grid scale (SGS) and resolved vertical transport across the gray zone of turbulence. We show that SCREAM is reasonably scale insensitive when run at resolutions from 1 to 5 km, but can exhibit sensitivity, particularly for the shallow convective regime, when run at resolutions approaching that of large eddy simulations. We conclude that SGS parameterization improvements are likely needed to reduce this scale sensitivity. Plain Language Summary: Advances in computational resources have allowed climate simulations to be performed with very high resolution, which provides higher quality results. However, these simulations require a lot of time and computer resources to perform, which makes these models difficult to use for the common scientist. In this paper we develop a high‐resolution configuration which focuses on a specific point on the globe, enabling it to run fast and to use minimal computational resources. This allows users and developers to gauge how the model may perform before doing a computationally intensive global simulation. We show that this faster configuration is a useful tool to replicate problems that are found in the global model and is a valuable way to assess sensitivities of the model, particularly pertaining to choices made in its resolution. Key Points: Doubly periodic configurations represent an efficient framework to supplement global cloud resolving modelsShallow convection is sensitive to horizontal resolution in Simple Convection‐Permitting E3SM Atmosphere Model (SCREAM) but stratiform clouds are more robustSCREAM exhibits the behaviors of a scale aware model and can represent a range of cloud regimes [ABSTRACT FROM AUTHOR]

The Indo-Pacific Ocean appears exponentially stratified between 1- and 3-km depth with a decay scale on the order of 1 km. In his celebrated paper "Abyssal recipes," W. Munk proposed a theoretical explanation of these observations by suggesting a pointwise buoyancy balance between the upwelling of cold water and the downward diffusion of heat. Assuming a constant upwelling velocity w and turbulent diffusivity κ, the model yields an exponential stratification whose decay scale is consistent with observations if κ ∼ 10−4 m2 s−1. Over time, much effort has been made to reconcile Munk's ideas with evidence of vertical variability in κ, but comparably little emphasis has been placed on the even stronger evidence that w decays toward the surface. In particular, the basin-averaged w nearly vanishes at 1-km depth in the Indo-Pacific. In light of this evidence, we consider a variable-coefficient, basin-averaged analog of Munk's budget, which we verify against a hierarchy of numerical models ranging from an idealized basin-and-channel configuration to a coarse global ocean simulation. Study of the budget reveals that the decay of basin-averaged w requires a concurrent decay in basin-averaged κ to produce an exponential-like stratification. As such, the frequently cited value of 10−4 m2 s−1 is representative only of the bottom of the middepths, whereas κ must be much smaller above. The decay of mixing in the vertical is as important to the stratification as its magnitude. Significance Statement: Using a combination of theory and numerical simulations, it is argued that the observed magnitude and shape of the global ocean stratification and overturning circulation appear to demand that turbulent mixing increases quasi-exponentially toward the ocean bottom. Climate models must therefore prescribe such a vertical profile of turbulent mixing in order to properly represent the heat and carbon uptake accomplished by the global overturning circulation on centennial and longer time scales. [ABSTRACT FROM AUTHOR]

The thermospheric neutral density response to the 7–9 September 2017 storms is investigated based on the Swarm satellite observations and the thermosphere‐ionosphere‐electrodynamic general circulation model (TIEGCM) simulation. The Swarm data depicted a prominent interhemispheric asymmetry (IHA) in the afternoon sector during the second storm, a feature that was yet explained. Driven by realistic high‐latitude electric potential and electron precipitation patterns, the TIEGCM is able to reproduce the observed storm‐time neutral density response. The TIEGCM simulation reveals that the differences in the traveling atmospheric disturbances (TADs) is largely responsible for the observed IHA in the neutral mass density response at low and middle latitudes, whereas the difference in mean molecular mass between the two hemispheres may contribute to the IHA in neutral density at higher latitudes. The IHAs in TADs and mean molecular mass are attributed to the IHA in Joule heating dissipation on the night and dawn sides. Plain Language Summary: During geomagnetic storms, thermospheric neutral density can increase drastically due to intense heat inputs. Enhanced neutral density increases the air drag on satellites which could lower their orbits and lead to faster atmosphere reentering of satellites. In addition, enhanced neutral mass density may cause larger uncertainties in orbit prediction which increases the risk of collisions with other space objects. Therefore, it is essential to improve the understanding of storm‐time neutral density variations to improve satellite operations. Recent satellite observations have revealed that thermospheric neutral mass density response can be interhemispherically asymmetric even under equinox conditions when the background density in the two hemispheres is comparable. This paper presents a case study of such an event based on data analysis and numerical simulations to investigate the physical mechanisms behind this intriguing phenomenon. The event took place on 7–9 September 2017 and the most prominent interhemispheric asymmetry of neutral density occurred in the afternoon sector. Our study found that the interhemispheric asymmetry during this event results from the differences in the generation, propagation and interaction of globally propagating atmospheric waves, namely traveling atmospheric disturbances, as well as the difference in mean molecular mass between the northern and southern hemispheres. Key Points: Thermosphere‐ionosphere‐electrodynamic general circulation model captures the observed interhemispheric asymmetry (IHA) in the neutral density response to the 7–9 September 2017 geomagnetic stormsThe IHA in the neutral density response results from the IHA in traveling atmospheric disturbances and mean molecular massThe observed IHA in the neutral density response is not caused by direct Joule heating dissipated at the same local time [ABSTRACT FROM AUTHOR]