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This paper described the implementation of a forecasting system of the coupled physical and biogeochemical state of the northern Adriatic Sea and discussed the preliminary results. The forecasting system is composed of two components: the NEMO general circulation model and the BFM biogeochemical model. The BFM component includes an explicit benthic pelagic coupling providing fluxes at the sediment–water interface and the dynamic of the major benthic state variables. The system is forced by atmospheric forcing from a limited-area model and by available land-based (river runoff and nutrient load) data. The preliminary results were validated against available remote and in situ observations. The validation effort indicated a good performance of the system in defining the basin scale characteristics, while locally the forecasting model performance seemed mostly impaired by the uncertainties in the definition of the land-based forcing. [ABSTRACT FROM AUTHOR]

We apply a multiresolution Gaussian process model (Lattice Kriging) to combine satellite observations, ground‐based observations, and an empirical auroral model, to produce the assimilation of auroral energy flux and mean energy over high‐latitude regions. Compared to a simple padding, the assimilation coherently combines various data inputs leading to continuous transitions between different datasets. The multiresolution modeling capability is achieved by allocating multiple layers of basis functions with different resolutions. Higher‐resolution fitting results capture more mesoscale (10–100 s km) structures such as auroral arcs, than the low‐resolution ones and the empirical model. To better reconcile different datasets, two preprocessing steps, temporal interpolation of satellite data and spatial down‐sampling of low‐fidelity data, are implemented. The inherent smoothing effect of the fitting, which causes an unrealistic spreading of the aurora, is mitigated by a post processing step: the K Nearest Neighbor (KNN) algorithm. KNN identifies the probability of a region with significant aurora and thereby eliminates those regions with low values. Thereby, this methodology can be used to maintain realistic and mesoscale auroral structures without boundary issues. We then run the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) driven by the high‐ and low‐resolution auroral assimilations and compare total electron contents (TECs). TIEGCM driven by data assimilation produces enhanced TECs by a factor of ∼2 than the one driven by the empirical aurora, and high‐resolution results show mesoscale structures. Our study shows the value of incorporating realistic auroral inputs via assimilation to drive ionosphere‐thermosphere models for better understanding the consequences of mesoscale phenomena. Plain Language Summary: The energy deposition from the magnetosphere determines the storm‐time Ionosphere‐Thermosphere (I‐T) variations. Among different energy inputs, aurora and electric fields are usually prescribed as external drivers for I‐T models. Historically, these drivers are given by empirical models, which miss mesoscale structures. This poses a long‐lasting challenge to understand and predict mesoscale I‐T variations. This paper adopts a Lattice Kriging model to generate data‐driven auroral maps by combining space‐borne and ground‐based datasets. The approach maintains realistic and mesoscale structures while removing the boundary issues between different datasets compared to a simple padding. The methodology is inherently multiresolution, by laying out different levels of basis functions, to naturally decompose the auroral activities into different scales. The I‐T model simulation driven by the assimilation result well captures the location of enhanced total electron contents during a moderate storm due to auroral precipitation. Our work demonstrates the advantage of using data assimilation to understand mesoscale magnetospheric deposition and its impacts. Nevertheless, this assimilation model still falls into the category of data diagnostics, in which the analysis largely depends on the amount and spatial distribution of the available data. It is not a prediction model and cannot be used to infer the temporal evolution of aurora. Key Points: Multiresolution Gaussian process model (Lattice Kriging) is used to assimilate Special Sensor Ultraviolet Spectrographic Imagers and Time History of Events and Macroscale Interactions during Substorms for auroral energy flux and mean energyAuroral assimilation combines various datasets coherently, alleviates boundary issue, and captures real‐time mesoscale structure as observedThermosphere Ionosphere Electrodynamics General Circulation Model driven by the assimilated auroral maps reproduces strong and structured total electron contents, comparing more favorably with the global navigation satellite system observations [ABSTRACT FROM AUTHOR]

Modern general circulation models continue to require parameterizations of subgrid transport due to planetary boundary layer (PBL) turbulence and convection. Some schemes that unify these processes rely on assumed joint probability distributions of vertical velocity and moist conserved thermodynamic variables to predict the subgrid-scale contribution to the mean state of the atmosphere. The multivariate double-Gaussian mixture has been proposed as an appropriate model for PBL turbulence and shallow convection, but it is unable to reproduce important features of shallow cumulus convection. In this study, a novel unified PBL turbulence–convection–cloud macrophysics scheme is presented based on the eddy-diffusivity/mass-flux framework. The new scheme augments the double-Gaussian representation of subgrid variability with multiple stochastic mass-flux plumes at minimal added computational cost. Improved results for steady-state maritime and transient continental shallow convection from a single-column model implementation of the new scheme are shown with respect to reference large-eddy simulations. Improvements are seen in the cloud layer due to mass-flux plumes occupying the extreme moist, low liquid-water potential temperature tail of the joint temperature–moisture distribution. Significance Statement: Computer models of the atmosphere used to predict future climate are unable to directly represent air motion at small spatial scales because it would take too long to run the model over the entire planet. Instead, models typically use coarse model grid spacing and a simplified statistical representation of the physical processes that cause small-scale motions. This paper improves a particular simplified representation by adding a mechanism to represent statistically rare events of strong small-scale air motion that coherently transport air from near the surface to higher in the atmosphere. This increased transport also improves the representation of clouds, a particularly difficult phenomenon to simulate in models. [ABSTRACT FROM AUTHOR]

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The latest version of the atmospheric general circulation model ARPEGE‐Climat was used to perform 5‐member ensemble simulations for both present and RCP8.5 scenario climates (mid‐21st century). The rotated/stretched configuration enables a local horizontal resolution of less than 15 km over the tropical North Atlantic basin. Moreover, a tracking algorithm was used to extract tropical cyclones (TCs) simulated by the model. Through an Eulerian approach, this paper focuses on the relationships between TCs and rainfall over three French islands in the West Indies. Although the model underestimates the occurrence of TCs over this latitude band, especially in September, precipitation rates during TC days are realistic. Indeed, the model shows a good capacity to reproduce different relationships between island rainfall and TC characteristics such as proximity and intensity. In addition to rainfall distribution, the TC contribution to annual cumulative rainfall is also well captured by the model. We used three different series characterizing precipitation at the island scale to underline that the model overestimates the area that is impacted by TC rainfall. According to the simulations, the number of minor TCs tends to decrease in the future (about −15%) over the study domain (50–70°W × 10–25°N) despite a +1.6°C over ocean warming. In contrast, no trend was detected in the number of major hurricanes. Except for annual precipitation that decreases significantly in the future (about −15%), no significant change was detected in the relationships between TC properties and island rainfall. [ABSTRACT FROM AUTHOR]

Most radiation schemes in weather and climate models use the "correlated k distribution" (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a wider range of gas concentrations can be simulated but at greater computational cost. Unfortunately, the tools to perform this efficiency–accuracy trade-off (e.g. to generate separate CKD models for applications such as short-range weather forecasting to climate modelling) are unavailable to the vast majority of users of radiation schemes. This paper describes the experimental protocol for the Correlated K-Distribution Model Intercomparison Project (CKDMIP), whose purpose is to use benchmark line-by-line calculations: (1) to evaluate the accuracy of existing CKD models, (2) to explore how accuracy varies with N for CKD models submitted by CKDMIP participants, (3) to understand how different choices in the way that CKD models are generated affect their accuracy for the same N , and (4) to generate freely available datasets and software facilitating the development of new gas-optics tools. The datasets consist of the high-resolution longwave and shortwave absorption spectra of nine gases for a range of atmospheric conditions, realistic and idealized. Thirty-four concentration scenarios for the well-mixed greenhouse gases are proposed to test CKD models from palaeo- to future-climate conditions. We demonstrate the strengths of the protocol in this paper by using it to evaluate the widely used Rapid Radiative Transfer Model for General Circulation Models (RRTMG). [ABSTRACT FROM AUTHOR]

The article presents a case study on the GEWEX Cloud System Study (GCSS) cirrus cloud working group's inter-comparison of model simulations. These ranges from microphysical and dynamical models to general circulation models (GCMs). An overview of how it was developed and based on the March 9, 2000 Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) intensive observation period (IOP) is presented.

Concentrated poleward flows near the eastern boundaries between 2- and 4-km depth have been observed repeatedly, particularly in the Southern Hemisphere. These deep eastern boundary currents (DEBCs) play an important role in setting the large-scale tracer distribution and have nonnegligible contribution to global transports of mass, heat, and tracers, but their dynamics are not well understood. In this paper, we first demonstrate the significant role of DEBCs in the southeastern Atlantic, Indian, and Pacific Oceans, using the Southern Ocean State Estimate (SOSE) data assimilating product, and using high-resolution regional general circulation model configurations. The vorticity balances of these DEBCs reveal that, over most of the width of such currents, they are in an interior-like vorticity budget, with the meridional advection of planetary vorticity by and vortex stretching fwz being the largest two terms, and with contributions of nonlinearity and friction that are of smaller spatial scale. The stretching is shown, using a temperature budget, to be largely forced by resolved or parameterized eddy temperature transport. Strongly decaying signals from the eastern boundary in friction and stretching form the dominant balance in a sublayer close to the eastern boundary. The temporal variability of DEBCs is then examined, to help to interpret observations that tend to be sporadic in both time and space. The probability distribution functions of northward velocity inDEBCregions are broad, implying that flow reversals are common. Although the regions of the simulated DEBCs are generally local minima of eddy kinetic energy, they are still constantly releasing westward-propagating Rossby waves. [ABSTRACT FROM AUTHOR]

Abstract: The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Among other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific descriptions of these components are in companion papers) and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present‐day forcing. The suitability of the configuration for predictability on shorter time scales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2‐AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however, there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2‐AO, many aspects of the present‐day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extratropical variability and top‐of‐atmosphere and surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking. [ABSTRACT FROM AUTHOR]

This paper examines the physical controls of extratropical humidity and clouds by isolating the effects of cloud physics factors in an idealized model. The Held–Suarez dynamical core is used with the addition of passive water vapor and cloud tracers, allowing cloud processes to be explored cleanly. Separate saturation adjustment and full cloud scheme controls are used to consider the strength of advection–condensation theory. Three sets of perturbations to the cloud scheme are designed to test the model’s sensitivity to the physics of condensation, sedimentation, and precipitation formation. The condensation and sedimentation perturbations isolate two key differences between the control cases. First, the sub-grid-scale relative humidity distribution assumed for the cloud macrophysics influences the location and magnitude of the extratropical cloud maxima, which interrupt the isentropic transport of moisture to the polar troposphere. Second, within the model’s explicit treatment of cloud microphysics, re-evaporation of hydrometeors moistens and increases clouds in the lower troposphere. In contrast, microphysical processes of precipitation formation (specifically, the ratio of accretion to autoconversion) have negligible effects on humidity, cloudiness, and precipitation apart from the strength of the largescale condensation and formation cycle. In addition, counterintuitive relationships}such as cloud condensate and cloud fraction responding in opposing directions}emphasize the need for careful dissection of physical mechanisms. In keeping with advection–condensation theory, circulation sets the patterns of humidity, clouds, and precipitation to first order, with factors explored herein providing secondary controls. The results substantiate the utility of such idealized modeling and highlight key cloud processes to constrain. [ABSTRACT FROM AUTHOR]

We develop a hierarchy of simplified ocean models for coupled ocean, atmosphere, and sea ice climate simulations using the Community Earth System Model version 1 (CESM1). The hierarchy has four members: a slab ocean model, a mixed‐layer model (MLM) with entrainment and detrainment, an Ekman MLM, and an ocean general circulation model (OGCM). Flux corrections of heat and salt are applied to the simplified models ensuring that all hierarchy members have the same climatology. We diagnose the needed flux corrections from auxiliary simulations in which we restore the temperature and salinity to the daily climatology obtained from a target CESM1 simulation. The resulting three‐dimensional corrections contain the interannual variability fluxes that maintain the correct vertical gradients of temperature and salinity in the tropics. We find that the inclusion of mixed‐layer entrainment and Ekman flow produces sea surface temperature and surface air temperature fields whose means and variances are progressively more similar to those produced by the target CESM1 simulation. We illustrate the application of the hierarchy to the problem of understanding the response of the climate system to the loss of Arctic sea ice. We find that the shifts in the positions of the mid‐latitude westerly jet and of the Inter‐tropical Convergence Zone (ITCZ) in response to sea‐ice loss depend critically on upper ocean processes. Specifically, heat uptake associated with the mixed‐layer entrainment influences the shift in the westerly jet and ITCZ. Moreover, the shift of ITCZ is sensitive to the form of Ekman flow parameterization. Plain Language Summary: Coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the climate system. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this paper, we manage to overcome this problem and develop a globally coupled ocean model hierarchy that can turn on and off the processes of mixed‐layer entrainment and Ekman flow. We use the hierarchy to study the impact of Arctic sea‐ice loss on the climate system. We find that the effect of mixed‐layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid‐latitude westerly jet and the Inter‐tropical Convergence Zone. Key Points: We develop a flux‐corrected globally coupled ocean‐model hierarchy that explicitly includes mixed‐layer entrainment and Ekman flowFlux corrections need to contain components due to interannual variability to reproduce vertical gradient of ocean temperature and salinityThe hierarchy applied to Arctic sea‐ice loss reveals that the Inter‐tropical Convergence Zone is sensitive to the entrainment and Ekman flow parameterization [ABSTRACT FROM AUTHOR]

Extreme temperature events are becoming more frequent due to global warming, and have critical effects on natural ecosystems, social and economic spheres, human production and life. Predicting changes in temperature extremes and trends under future climate scenarios helps to assess the impact of climate change accurately. Based on climate observations from 54 meteorological stations in the North China Plain and the projection data from seven general circulation models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6), this paper researches nine representative extreme temperature indices under four typical climate scenarios. The aim is to reveal the temporal and spatial variations in extreme temperature indices in the North China Plain during the past (1971–2010) and the future (2061–2100). The results show that: using a support vector machine (SVM) to perform regression analysis on the multi-GCMs prediction results, the root mean square error (RMSE) and relative standard deviation (RSD) of the multi-model ensemble simulations obtained by the SVM method are lower than those of the arithmetic mean method and can better match the trend of the historical extreme temperature index; the extreme high temperature index is predicted to show a significant upward trend in the future, while the extreme low temperature index will decrease significantly; and there are significant spatial differences in the extreme temperature index in both historical and future periods, with the extreme temperature index under the high radiation forcing scenario (SSP585) showing the most considerable variation and the most significant spatial differences. [ABSTRACT FROM AUTHOR]

Global climate models, like any in silico numerical experiments, are affected by different types of bias. Uncertainty quantification remains a challenge in any climate detection and attribution analysis. A fundamental methodological question is to determine which statistical summaries, while bringing relevant signals, can be robust with respect to multimodel errors. In this paper, we propose a simple statistical framework that significantly improves signal detection in climate attribution studies. We show that the complex bias correction step can be entirely bypassed for models for which bias between the simulated and unobserved counterfactual worlds is the same as between the simulated and unobserved factual worlds. To illustrate our approach, we infer emergence times in precipitation from the CMIP5 and CMIP6 archives. The detected anthropogenic signal in yearly maxima of daily precipitation clearly emerges at the beginning of the twenty-first century. In addition, no CMIP model seems to outperform the others and a weighted linear combination of all improves the estimation of emergence times. Significance Statement: We show that the bias in multimodel global climate simulations can be efficiently handled when the appropriate metric is chosen. This metric leads to an easy-to-implement statistical procedure based on a checkable assumption. This allows us to demonstrate that optimal convex combinations of CMIP outputs can improve the signal strength in finding emergence times. Our data analysis procedure is applied to yearly maximum of precipitation from CMIP5 and CMIP6 databases. The attribution of the anthropogenic forcing clearly emerges in extreme precipitation at the beginning of the twenty-first century. [ABSTRACT FROM AUTHOR]

Previous studies have shown that solar flares can significantly affect Earth's ionosphere and induce ion upflow with a magnitude of ∼110 m/s in the topside ionosphere (∼570 km) at Millstone Hill (42.61°N, 71.48°W). We use simulations from the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM) and observations from Incoherent Scatter Radar (ISR) at Millstone Hill to reveal the mechanism of ionospheric ion upflow near the X9.3 flare peak (07:16 LT) on 6 September 2017. The ISR observed ionospheric upflow was captured by the TIEGCM in both magnitude and morphology. The term analysis of the F‐region ion continuity equation during the solar flare shows that the ambipolar diffusion enhancement is the main driver for the upflow in the topside ionosphere, while ion drifts caused by electric fields and neutral winds play a secondary role. Further decomposition of the ambipolar diffusive velocity illustrates that flare‐induced changes in the vertical plasma density gradient is responsible for ion upflow. The changes in the vertical plasma density gradient are mainly due to solar extreme ultraviolet (EUV, 15.5–79.8 nm) induced electron density and temperature enhancements at the F2‐region ionosphere with a minor and indirectly contribution from X‐ray (0–15.5 nm) and ultraviolet (UV, 79.8–102.7 nm). Plain Language Summary: Solar flares with a sudden enhancement in solar X‐ray and extreme ultraviolet (EUV) radiation heat the upper atmosphere and increase electron density dramatically, leading to an expansion of Earth's upper atmosphere. Previous observations have shown an upward ion motion of ∼110 m/s at middle latitudes during solar flares; however, the cause of it remains largely speculative. In this paper, we provide a quantitative analysis of the ionospheric ion upflow during the 6 September 2017 X9.3 flare via model‐data comparison. During solar flares, X‐ray and EUV radiation are intensified at different degrees, thus producing different magnitudes of enhancement in ionospheric plasma density and temperature at different altitudes. Enhanced electron density and temperature at ionospheric F‐region due to solar EUV photoionization build up an additional upward pressure gradient force, pushing the plasmas upward. Key Points: Flare‐induced ionospheric ion upflow at midlatitudes was simulated by a 3‐D ionosphere‐thermosphere coupled modelThe midlatitude ion upflow was mainly due to changes in ambipolar diffusion during flaresThe solar extreme ultraviolet (EUV) enhanced electron density and temperature were the primary driver of ambipolar diffusion velocity changes [ABSTRACT FROM AUTHOR]

Although tropical interbasin interactions at interannual time scales are presently receiving much attention, their controlling factors and variations on longer time scales are under debate. Tropical convection plays a crucial role in the occurrence and nonstationarity of them. In this paper, we investigate the dependence of interannual tropical Atlantic–Pacific basin interactions on convection-related features of the tropical oceans' climatology, especially the ITCZ position. We contrast a CGCM control simulation with an experiment in which tropical convection is modified by an artificial perturbation outside the tropics that reduces the incident shortwave radiation in a region of the South Atlantic. Based on previous work, this modification is expected to shift in latitude the climatological position of the simulated ITCZ. The experiment shows altered Walker circulations, stronger interannual variability over the tropical oceans, a westward extension of the Atlantic Niño pattern and of convection, and shallower thermocline in the Pacific, making the basin more sensitive to both local and remote perturbations. As a consequence, the experiment shows enhanced interannual Atlantic–Pacific basin interactions at the equator, and weaker teleconnections between the north tropical Atlantic and the equatorial Pacific. The latter seems to occur because the impact of the warm Atlantic SST anomalies is offset by the presence of warm SST anomalies in El Niño region. Despite the uncertainties raised because the simulations are relatively short, we conclude that this work presents a potential explanation for the long-term changes in the tropical basin interactions and offers a novel and useful methodology for their analysis. [ABSTRACT FROM AUTHOR]

Anticipating risks related to climate extremes often relies on the quantification of large return levels (values exceeded with small probability) from climate projection ensembles. Current approaches based on multi-model ensembles (MMEs) usually estimate return levels separately for each climate simulation of the MME. In contrast, using MME obtained with different combinations of general circulation model (GCM) and regional climate model (RCM), our approach estimates return levels together from the past observations and all GCM–RCM pairs, considering both historical and future periods. The proposed methodology seeks to provide estimates of projected return levels accounting for the variability of individual GCM–RCM trajectories, with a robust quantification of uncertainties. To this aim, we introduce a flexible non-stationary generalized extreme value (GEV) distribution that includes (i) piecewise linear functions to model the changes in the three GEV parameters and (ii) adjustment coefficients for the location and scale parameters to adjust the GEV distributions of the GCM–RCM pairs with respect to the GEV distribution of the past observations. Our application focuses on snow load at 1500 m elevation for the 23 massifs of the French Alps. Annual maxima are available for 20 adjusted GCM–RCM pairs from the EURO-CORDEX experiment under the scenario Representative Concentration Pathway (RCP) 8.5. Our results show with a model-as-truth experiment that at least two linear pieces should be considered for the piecewise linear functions. We also show, with a split-sample experiment, that eight massifs should consider adjustment coefficients. These two experiments help us select the GEV parameterizations for each massif. Finally, using these selected parameterizations, we find that the 50-year return level of snow load is projected to decrease in all massifs by -2.9 kN m -2 (-50 %) on average between 1986–2005 and 2080–2099 at 1500 m elevation and RCP8.5. This paper extends the recent idea to constrain climate projection ensembles using past observations to climate extremes. [ABSTRACT FROM AUTHOR]

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin's development. [ABSTRACT FROM AUTHOR]

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies. [ABSTRACT FROM AUTHOR]

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7–3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks. Plain Language Summary: This paper describes the latest iteration of the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) climate model, which will be used for understanding historical climate change and to make projections for the future. We compare the model output to a wide range of observations over the recent era (1979–2014) and show that there has been a significant increase in how well the model performs compared to the previous version from 2014, particularly in the Southern Ocean, though some persistent biases remain. The model has a temperature response to the increase of carbon dioxide that is slightly higher than previous versions but is well within the range expected from observational and past climate constraints. Key Points: GISS‐E2.1 is an updated climate model version for use within the CMIP6 projectAtmospheric composition is calculated consistently in all model versionsResults demonstrate a significant improvement in skill in a climate model without changes to atmospheric resolution [ABSTRACT FROM AUTHOR]

Water allocation institutions globally must operate within legal and political contexts established by precedent and codified in operating rules, even as they flex and adjust to climate change. California's Central Valley Water System (CVS) is a prime example. Recent global, national, regional, and local climate change assessments have highlighted climate-change-driven impacts on the CVS; however, these previous studies have not discussed the relative likelihood of performance decline, making it difficult to use the information for planning. In response, this paper presents a systematic climate change stress test that utilizes a physically based hydrologic model linked with a water resources system model representing the infrastructure, operations, and policy constraints of the interconnected system of natural river channels and man-made facilities that comprise the CVS. The results provide a summary of the sensitivity of the system to climate change, indicating the specific climate changes that cause performance of the system to decline below historical norms, and an estimation of the General Circulation Model (GCM) informed probability of those changes by 2050. Degraded performance is especially likely for State Water Project (SWP) deliveries (> 85%), and September carryover/drought storage in the Oroville Reservoir (the SWP's largest reservoir, ~ 95% likely to degrade). A decline in Net Delta Outflow is likely in all seasons except summer and early fall (when regulations require supplemental releases to combat salinity from sea level rise). For most of these metrics, the modeled performance drop is more severe in dry years than in wet years. [ABSTRACT FROM AUTHOR]

Here we compare the global‐scale morphology of Earth's the Far‐Ultraviolet (FUV) emissions observed by NASA's Global‐scale Observations of Limb and Disk (GOLD) mission to those modeled using the Global Airglow (GLOW) code with atmospheric parameters provided by Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM). The O 5S oxygen (135.6 nm) and N2 Lyman‐Birge‐Hopfield (LBH) emissions are observed over the Western hemisphere every 30 min by the GOLD instrument. The FUV brightness of the thermosphere‐ionosphere is expected to vary in systemic ways with respect to geophysical parameters, solar energy input from above, and terrestrial weather input from below. In this paper we examine the O 5S oxygen emission and the N2 LBH emission brightnesses with local time, latitude, season, tides, geomagnetic activity, and solar activity based on GOLD observations and GLOW modeling. Early GOLD observations indicate that the model effectively reproduces the brightness variations with local time and latitude but is biased low in magnitude. However, the TIEGCM is unable to accurately represent the extraordinary nighttime equatorial ionization anomaly observed by GOLD. It is also expected from these results that the signal from geomagnetic storms may obscure tidal signals. Plain Language Summary: In January 2018, a FUV instrument, the Global‐scale Observations of Limb and Disk (GOLD), was launched as a NASA mission of opportunity aboard a geostationary satellite and scientific operations began in October of 2018. GOLD views the entire disk of the Earth every 30 min, allowing the separation of geophysical variability in both space and time. This allows an unprecedented test of global models. Here, we model the Earth's upper atmosphere using the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM), which produces temperature and the densities of the major chemical components of the neutral atmosphere, ionized plasma densities, and neutral air temperatures. These atmospheric temperatures and densities are used to calculate the Earth's upper atmosphere emissions in the Far‐Ultraviolet (FUV) with the Global Airglow (GLOW) model. The calculated emission rates are then used to compute the expected FUV signals as observed from geostationary orbit. In this paper, we show how the FUV brightness varies with local time, season, atmospheric activity, and solar activity. Of particular interest is that the GLOW model excels at producing FUV brightnesses that match the local time and latitude trends of the daytime observations; however, the model fails to adequately portray the extraordinary nighttime phenomena observed by GOLD. Key Points: The Global‐scale Observations of Limb and Disk (GOLD) instrument observes the Earth in the Far‐Ultraviolet (FUV) from a geostationary orbitGLOW adequately calculates the FUV brightness for various local times, latitudes, solar forcing, and lower atmospheric forcingGLOW calculations indicate the oxygen brightness varies by ±45 R and the effective temperature varies by more than 80 K due to tides [ABSTRACT FROM AUTHOR]

A critical stage in the development of our ability to model and project climate change occurred in the late 1950s–early 1960s when the first primitive-equation atmospheric general circulation models (AGCMs) were created. A rather idiosyncratic project to develop an AGCM was conducted virtually alone by Cecil E. Leith starting near the end of the 1950s. The Leith atmospheric model (LAM) appears to have been the first primitive-equation AGCM with a hydrological cycle and the first with a vertical resolution extending above the tropopause. It was certainly the first AGCM with a diurnal cycle, the first with prognostic clouds, and the first to be used as the basis for computer animations of the results. The LAM project was abandoned in approximately 1965, and it left almost no trace in the journal literature. Remarkably, the recent internet posting of a half-century-old computer animation of LAM-simulated fields represents the first significant "publication" of results from this model. This paper summarizes what is known about the history of the LAM based on the limited published articles and reports as well as transcripts of interviews with Leith and others conducted in the 1990s and later. [ABSTRACT FROM AUTHOR]

The annual maximum flood records of the Danjiangkou reservoir displayed significant decreasing trends. The upper stream of the reservoir was characterized by minor changes in urbanization in recent decades, while several large reservoirs were built since 1975. To better explain the changes in floods, this paper used the nonstationary generalized extreme value (GEV) distribution by considering the impacts of climate change and human activity. The GEV parameters were expressed as functions of time, climate indices, and climate-reservoir index (CRI). By using CRI as the covariate, the performance of the nonstationary GEV distribution was much better than others. This paper also analyzed the risk of floods using design life level and annual average reliability methods. The reliability obtained from these methods can describe the effects of external indices on floods. Finally, the uncertainty analysis indicated that a nonstationary model might not be practical, and the large confidence intervals of the design flood implied that the results were meaningless. It is essential to build a deterministic relationship between parameters and covariates, and we should be prudent when using general circulation models outputs in extreme statistics. [ABSTRACT FROM AUTHOR]

It is often desirable to simulate a single temperature series or a collection (network) of temperature series. Accurate simulations can enhance our understanding of temperature trends and variabilities. Simulation can also be used to generate data with known specifications, which are useful in assessing climate data processing routines such as quality control and homogenization algorithms. Possessing multiple realistic temperature series is often beneficial as only one natural record of our climate is available. The current popularity of general circulation models (GCMs) demonstrates how important simulation techniques are. However, even with sophisticated downscaling, it is difficult to replicate station temperature data that have realistic seasonal cycles as well as realistic temporal and spatial correlations. This paper reviews and studies statistical time series methods that can replicate a single series or a network of series from data. The methods are purely statistical—no atmospheric dynamics are involved—and attempt to produce replicates of the records under study. The work here develops (a) methods that simulate temperatures from a fixed season (say a particular day or month of the year) that match the distributional characteristics of the observed data; (b) methods for simulating an entire series that matches the series' temporal autocorrelations and seasonal cycle; and (c) methods for simulating a network of series that reproduce the data's observed seasonal cycles and spatial and temporal autocorrelations. Applications are given throughout, including one where a GCM series and local station data are used in tandem to describe long‐term trends and inject realistic station‐level short‐term fluctuations. This paper can be used as a tutorial for the simulation of a single climate observation, an entire climate series, or a network of multiple climate series simultaneously. Extensions of the ideas that involve GCMs are also examined. [ABSTRACT FROM AUTHOR]

The well-posedness of the dynamic framework in earth-system model (ESM for short) is a common issue in earth sciences and mathematics. In this paper, the authors first introduce the research history and fundamental roles of the well-posedness of the dynamic framework in the ESM, emphasizing the three core components of ESM, i.e., the atmospheric general circulation model (AGCM for short), land-surface model (LSM for short) and oceanic general circulation model (OGCM for short) and their couplings. Then, some research advances made by their own research group are outlined. Finally, future research prospects are discussed. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are developed to simulate the past climate and generate future climate predictions. In the context of global warming, their important roles in identifying possible solutions to water resources planning/management are recognized by the world. However, in actual and regional implementation, due to many factors like initial and boundary conditions, parameters and model structures and so forth, there are great variabilities and uncertainties across the future climate projections of GCMs outputs, which has attracted criticism from water resources planners. Thus, the GCMs usually must be evaluated for assessing their performances in simulating the historical observations. Currently, there are many different conclusions and opinions as to whether the optimal individual model is more advantageous or whether the combined consideration of MME works better. The purpose of this paper is to compare the advantages and disadvantages between the selection of the optimal single GCM and multi‐model ensemble (MME) based on one of the more objective selection methods called TOPSIS. The results show that the performances of GCMs in simulating precipitation and temperature in different climate subregions over China are not identical. For CMIP6 GCMs simulations, the optimal precipitation GCM is CMCC‐CM2‐SR5 for EC, MIROC6 for SC, SWC and NWC, CESM2‐WACCM for NC and NEC, and FGOALS‐g3 for QTP. As for temperature, only NESM3 and BCC‐ESM1 are the optimal GCM for QTP and NWC, respectively; in other subregions, MME is better than single GCM. In general, a simple arithmetic averaging approach employed to generate the MME model is not superior to the optimal GCM, although the error metric with the observed data is reduced, at the cost of a severe compression of the interannual variability. [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 https://www.worldocean circulation.org/Products#/metadata/0aa7daac-43e6-42f3-9f95-ef7da46bc702 (Buongiorno Nardelli, 2022). [ABSTRACT FROM AUTHOR]

Among several devastating natural hazards, flooding is a common and serious threat to society causing huge loss of lives, properties, and infrastructure throughout the world. The intensity and frequency of this extreme weather event are expected to increase due to significant changes in the present‐day climate and land use and land cover (LULC) pattern. India has a very systematic and organized structural program and policies but lacks proper implementations, and adverse effect of climate change and the extreme event goes on in society. This paper is an analysis of floods in India and hazards due to climate change and LULC change patterns. Three models, namely "Eco‐biogeography‐based optimization (EBO), Random forest (RF), and Support vector machine (SVM)" were used to obtain the final output to prepare a "Flood susceptibility map". The result was validated through the "Receiver operating characteristics (ROC)" with "Area under curve (AUC)" values. The future rainfall scenario has been estimated by considering the "General circulation models" through different "shared socioeconomic pathways (SSPs)". The values of AUC are 0.915 (EBO), 0.887 (RF), and 0.869 (SVM), respectively. After consideration of different SSPs, the result shows that there is an increasing tendency of flood hazards in the projected period. Among all the employed modelling approaches, the EBO model has notable potential in delineating the possible flood‐prone regions for effective flood planning and management. Decision‐makers can benefit from country‐specific information and regional planner to implement sustainable and long‐term measures to overcome this type of hazardous situation. [ABSTRACT FROM AUTHOR]

The literature offers conflicting findings about which regions contribute most to increases in the global radiative feedback after a forcing increase. This paper explains the disagreement by discriminating between two common definitions of the local feedback, which use either local temperature or global temperature as their basis. Although the two definitions of feedback have been previously compared in aquaplanet models with slab oceans, here the definitions are compared for the first time in an atmosphere-ocean general circulation model (MPI-ESM1.2) integrated over four doublings of atmospheric CO2 concentrations. Large differences between the definitions can be seen in all feedbacks, but especially in the temperature and water vapor feedbacks. Differences of up to 10 W m-2 K-1 over the Southern Ocean can be explained by the pattern of surface warming, which weights the local feedbacks and reduces their contribution to the global mean. This finding is, however, dependent on the resolution of analysis, because the local-temperature definition is mathematically inconsistent across spatial scales. Furthermore, attempts to estimate the effect of "pattern weighting" by separating local feedbacks and warming patterns at the gridcell level fail, because the radiative change in key tropical regions is also determined by tropospheric stability via the global circulation. These findings indicate that studies of regional feedback change are more sensitive to methodological choices than previously thought, and that the tropics most likely dominate regional contributions to global radiative feedback change on decadal to centennial time scales. [ABSTRACT FROM AUTHOR]

Numerical simulations using the National Center for Atmospheric Research (NCAR) thermosphere‐ionosphere‐electrodynamics general circulation model (TIE‐GCM) are performed to elucidate the effects of the interplanetary magnetic field (IMF) on the middle thermosphere composition during a "geomagnetically quiet" period from the day of year (DOY) 110–111 in 2019 (when the Auroral electrojet (AE) index never exceeded 300 nT and the Kp never exceeded 2). In particular, this paper aims to examine how the Global‐scale Observations of the Limb and Disk (GOLD) mission observed daytime thermospheric O and N2 column density ratio (∑O/N2) depletion at mid‐latitudes originated under such a "geomagnetically quiet" condition. A comparison of electric potential, Joule heating rate per unit mass, ion velocity, neutral temperature and winds in the middle thermosphere (∼160 km) between real IMF and without the IMF east‐west component (By) indicates that a By dominant condition can enhance their strengths under this "geomagnetically quiet" condition. Consequently, ∑O/N2 depletion with a stronger magnitude (30% compared with ∼8% without By) and larger disturbed area was introduced in the post‐midnight sector at high‐latitudes due to strong and localized upwelling associated with the enhanced Joule heating rate per unit mass. The ∑O/N2 depletion was transported equatorward and corotated from local post‐midnight to early morning, and was observed by GOLD at middle latitudes during daytime. Plain Language Summary: This study utilizes numerical simulations with a climatological tide in the lower boundary to investigate how thermospheric composition disturbance is produced and transported to mid‐latitudes during a geomagnetically quiet period (DOY110‐112, 2019, maximum Kp = 1.7, AE < 300 nT). Through comparing parameters from simulations under real IMF and By = 0, it is found that the IMF By, which was dominant over this period, can significantly enhance the ionospheric potential, Joule heating rate per unit mass, ion drift and neutral winds compared with Bz only condition. As a result, the geomagnetic activity with AE < 300 nT can trigger stronger depletion (30%) of the column density ratio of thermospheric O and N2 (∑O/N2) in the polar region. Then the accelerated meridional wind transports the ∑O/N2 depletion equatorward to mid‐latitudes. The depletion is also transported from local post‐midnight to local early morning. This study shows the crucial role of dominant By during "quiet time". Additionally, it suggests that the response of ∑O/N2 to geomagnetic activity during the "quiet period" is similar to the one during geomagnetic storms. Key Points: IMF with dominant By enhances ion convection pattern, Joule heating rate and neutral windsStrong thermospheric composition disturbance can be generated and propagate into mid‐latitudes with dominant By during "quiet" timeResponse of thermospheric composition to geomagnetic activity with AE < 300 nT is similar to its response to geomagnetic storms [ABSTRACT FROM AUTHOR]

Previous studies have shown that Kelvin–Rossby instability is a viable mechanism for producing equatorial superrotation in small and/or slowly rotating planets. It is shown in this paper that this mechanism can also produce superrotation with terrestrial parameters when the baroclinic forcing moves to low latitudes, explaining previous results by Williams. The transition between superrotating and subrotating flow occurs abruptly as the baroclinic forcing moves poleward. Although Kelvin–Rossby instability weakens when the baroclinic zone moves away from the equator, the key factor explaining the abrupt transition is the change in the baroclinic eddies. When differential heating is contained within the tropics, baroclinic eddies do not decelerate the subtropical jet and the upper-tropospheric flow approximately conserves angular momentum, providing conditions favorable for Kelvin–Rossby instability. In contrast, when baroclinic eddies are generated in the extratropics, they decelerate the subtropical jet and prevent the Kelvin–Rossby coupling. Due to this sensitivity to baroclinic eddies, the system exhibits hysteresis: near the transition parameter, extratropical eddies can prevent superrotation when they are initially present. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present the results of the Weather Research and Forecasting (WRF) model of solar radiation for moderate climatic zones. This analysis covered the area of northeastern Germany. Due to very unfavorable solar energy conditions in this region for at least 1/3 of the year, we decided to select the dates with the most representative conditions: passing warm fronts, cold fronts, and occluded fronts (two cases each). As the reference, two cloudless conditions during high-pressure situations were chosen. Two different shortwave radiation schemes—Rapid Radiative Transfer Model for general circulation model (RRTMG) and Dudhia—were tested. The obtained results were compared with in situ data measured at Deutscher Wetterdienst (DWD) stations and then with European Medium-Range Weather Forecast reanalysis (ERA5) data. The results showed that for high-pressure situations, the mean correlations with measured data were above 90%. The Dudhia scheme, in addition to the expected good results for the high-pressure situation, showed better results than RRTMG for the warm and cold fronts as well. The forecast using the RRTMG scheme gave the best results for the occluded front, which were also better than those of the ERA5 model. [ABSTRACT FROM AUTHOR]

The global ocean overturning circulation, critically dependent on the global density stratification, plays a central role in regulating climate evolution. While it is well known that the global stratification profile exhibits a strong dependence to Southern Ocean dynamics and in particular to wind and buoyancy forcing, we demonstrate here that the stratification is also acutely sensitive to the mesoscale eddy energy dissipation timescale. Within the context of a global ocean circulation model with an energy constrained mesoscale eddy parameterization, it is shown that modest variations in the eddy energy dissipation timescale lead to significant variations in key metrics relating to ocean circulation, namely the Antarctic Circumpolar Current transport, Atlantic Meridional Overturning Circulation strength, and global ocean heat content, over long timescales. The results highlight a need to constrain uncertainties associated with eddy energy dissipation for climate model projections over centennial timescales and also for paleoclimate simulations over millennial timescales. Plain Language Summary: The ocean is populated by "eddies", analogous to weather systems in the atmosphere, but occurring on much smaller scales of typically 10–100 km. Recent advances in our understanding of the circulation of the Southern Ocean, which connects all of the major ocean basins to the north, have revealed a crucial role for the energy balance of Southern Ocean eddies. In this paper, we show that the timescale over which energy is removed from Southern Ocean eddies has a dramatic impact on the following: (a) the strength of the Antarctic Circumpolar Current, the largest current in the global ocean; (b) the strength of the Atlantic meridional overturning circulation, responsible in part for the relatively mild climatic conditions over northwestern Europe; and (c) global ocean heat content, a key parameter in the global climate system. These results have significant implications for both past and future climates, and highlight the importance of combining observational, theoretical and modeling efforts to better understand and constrain the energy balance of ocean eddies. Key Points: Key metrics of global ocean circulation (Antarctic Circumpolar Current transport, Atlantic Meridional Overturning Circulation strength, and Ocean Heat Content anomaly) acutely sensitive to an eddy energy dissipation timescaleModest variations in the dissipation timescale has a comparable effect to significant variations in the Southern Ocean wind forcingConstraints on the dissipation timescale critical to longtime integrations of ocean climate models such as paleoclimate scenarios [ABSTRACT FROM AUTHOR]

In this paper, we show that the projected global temperature change from CMIP5 models is remarkably similar to that obtained using simple regression models relating the global temperature to the atmospheric concentrations of CO2. This result is strengthened when we consider the projections obtained using the CMIP6 models. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean surface circulation is highly energetic, composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping the general circulation is yet unknown. In the following paper, we use an unsupervised neural network clustering method to analyze the long-term variability of the different mesoscale structures. We decompose 26 years of altimetric data into clusters reflecting different circulation patterns of weak and strong flows with either strain or vortex-dominated velocities. The vortex-dominated cluster is more persistent in the western part of the basin, which is more active than the eastern part due to the strong flow along the coast, interacting with the extended bathymetry and engendering continuous instabilities. The cluster that reflects a weak flow dominated the middle of the basin, including the Mid-Mediterranean Jet (MMJ) pathway. However, the temporal analysis shows a frequent and intermittent occurrence of a strong flow in the middle of the basin, which could explain the previous contradictory assessment of MMJ existence using in-situ observations. Moreover, we prove that the Levantine Sea is becoming more and more energetic as the activity of the main mesoscale features is showing a positive trend. [ABSTRACT FROM AUTHOR]

Climate models project an intensification of the wintertime North Atlantic Ocean storm track, over its downstream region, by the end of this century. Previous studies have suggested that ocean–atmosphere coupling plays a key role in this intensification, but the precise role of the different components of the coupling has not been explored and quantified. In this paper, using a hierarchy of ocean coupling experiments, we isolate and quantify the respective roles of thermodynamic (changes in surface heat fluxes) and dynamic (changes in ocean heat flux convergence) ocean coupling in the projected intensification of North Atlantic transient eddy kinetic energy (TEKE). We show that dynamic coupling accounts for nearly all of the future TEKE strengthening as it overcomes the much smaller effect of surface heat flux changes to weaken the TEKE. We further show that by reducing the Arctic amplification in the North Atlantic, ocean heat flux convergence increases the meridional temperature gradient aloft, causing a larger eddy growth rate and resulting in the strengthening of North Atlantic TEKE. Our results stress the importance of better monitoring and investigating the changes in ocean heat transport, for improving climate change adaptation strategies. Significance Statement: By the end of this century, the North Atlantic Ocean storm track is projected to intensify on its eastward flank. Such intensification will have large societal impacts, mostly over western Europe. Thus, it is critical to better understand the mechanism underlying the intensification of the storm track. Here we investigate the role of ocean coupling in the future intensification of the North Atlantic storm track and find that ocean heat transport processes are responsible for the strengthening of the storm track. Our results suggest that better monitoring the changes in ocean heat transport will hopefully improve climate change adaption strategies. [ABSTRACT FROM AUTHOR]

Assessing the effects of climate change is a key component of the sustainable management of water resources and food security. In this paper, general circulation models (GCM) were evaluated using historical information for Birjand synoptic station, Iran. Modeling was performed using 35 models of the Fifth Climate Change Report for 27 historical periods. The results showed that longer annual periods are the most suitable periods for hydrological simulation when data are available. Therefore, the periods of 1960-1990 may be the most appropriate periods due to the adaptation to the observation data. To estimate rainfall, periods with more years showed a more accurate forecast of the future. Moreover, the results showed more changes in the RCP 8.5 scenario than in the RCP 4.5 scenario. According to the comparison of models, the NorESM1-M model with a root mean square error (RMSE) of 0.091 and the GISS-E2-R model with a low percent bias (PBIAS) can be an appropriate model for estimating rainfall. [ABSTRACT FROM AUTHOR]

Titan’s stratosphere has been observed in a superrotation state, where the atmosphere rotates many times faster than the surface does. Another characteristic of Titan’s atmosphere is the presence of a thick haze layer. In this paper, we performed numerical experiments using a general circulation model to explore the effects of the haze layer on the stratospheric superrotation. We employed a semigray radiation model of Titan’s atmosphere following McKay et al., which takes account of sunlight absorption by the haze particles. The phase change of methane or seasonal changes were not taken into account. Our model with radiation parameters tuned for Titan yielded a global eastward wind around the equator with larger velocities at higher altitudes, except at around 70 km, after 105 Earth days. Although the atmosphere is not in an equilibrium state, the zonal wind profiles are approximately consistent with the observed one. By changing the parameters of the radiation model, we found that the intensity and the location of the maximum zonal wind velocity highly depended on the optical thickness and the altitude of the haze layer, respectively. Analysis of our experiments suggests that the quasi-stationary stratospheric superrotation is maintained by the balance between the meridional circulation decoupled from the surface and the eddies that transport angular momentum equatorward. This is different from, but similar to, the so-called Gierasch mechanism, in which momentum is supplied from the surface. This structure may explain the no-wind region at about 80 km in altitude. [ABSTRACT FROM AUTHOR]

The Earth's magnetosheath and cusps emit soft X‐rays due to the charge exchange between highly charged solar wind ions and exospheric hydrogen atoms. The Lunar Environment Heliospheric X‐ray Imager and Solar wind Magnetosphere Ionosphere Link Explorer missions are scheduled to image the Earth's dayside magnetosphere system in soft X‐rays to investigate global‐scale magnetopause reconnection modes under varying solar wind conditions. The exospheric neutral hydrogen density distribution, especially the value of this density at the subsolar magnetopause is of particular interest for understanding X‐ray emissions near this boundary. This paper estimates the exospheric density during solar minimum using the X‐ray Multimirror Mission (XMM) astrophysics observatory. We selected an event on 12 November 2008 from the XMM data archive, which detects soft X‐rays of magnetosheath origin while solar wind and interplanetary magnetic field conditions are relatively constant. During the event the location of the magnetopause was measured in situ by the THEMIS mission, thus the location of the solar wind ions responsible for the magnetosheath emission is well constrained by observation. We estimated the exospheric density using the Open Geospace Global Circulation Model (OpenGGCM) and a spherically symmetric exosphere model. The ratio of the magnetosheath plasma flux between the OpenGGCM model and the THEMIS, was nearly 1, which means the magnetohydrodynamic model reasonably reproduces the magnetosheath plasma conditions. The OpenGGCM magnetosheath parameters were used to deconvolve soft X‐rays of exospheric origin from the XMM signal. The lower‐limit of the exospheric density of this solar minimum event is 36.8 ± 11.7 cm−3 at 10 RE subsolar location. Key Points: From 11 years of X‐ray Multimirror Mission‐Newton X‐ray observations, we identified 193 intervals that can be used to estimate the exospheric neutral densityWe derived a solar minimum exospheric neutral density from the 12 November 2008 event using a global MagnetoHydroDynamics model and a simplified exosphere modelThe density estimate is 36.8 cm−3 near the subsolar magnetopause and is likely a lower‐limit value [ABSTRACT FROM AUTHOR]

Climate change is expected to exacerbate the extremes in the climate variables. Being prone to harsh climate impacts, it is very crucial to study extreme rainfall-induced flooding for short durations over regions that are rapidly growing. One way to study the extremes is by the application of the Intensity-Duration-Frequency (IDF) curves. The annual maximum rainfall intensity (AMRI) characteristics are often used to construct these IDF curves that are being used in several infrastructure designs for urban areas. Thus, there is a need to obtain high temporal and spatial resolution rainfall information. Many urban areas of developing countries lack long records of short-duration rainfall. The shortest duration obtained is normally at a daily scale/24 h. Thus, it is very crucial to find a methodology to construct IDF curves for short-duration rainfall (sub-daily) for these urban areas. Vietnam is a developing country with rapidly increasing population as well as urbanization. The fast extension of urban area that does not have adequate preparedness to cope with climate change is certainly a big risk to life and economy. The limitation in studying impacts over many regions of Vietnam is the need for robust and sufficient data, both spatial and temporal. To overcome this limitation, this paper describes constructing IDF curves using 6 hourly rainfall AMRI output from a regional climate model (RCM) that downscaled a global climate model (GCM) output at high spatial and temporal resolutions. The study region is Hanoi, the capital city of Vietnam. The sub-daily IDF curves for current and future climate for Hanoi were constructed from 1 to 24 h based on the simple scaling approach. The findings indicate that it is likely that Hanoi might experience more flooding conditions in the future with the AMRI increasing between 34 and 48% for all return periods from 10 to 200 years. The methodology adopted in this paper is suitable for similar ungauged areas elsewhere and will provide useful information in devising adequate planning strategies for drainage designs. [ABSTRACT FROM AUTHOR]

A number of studies have suggested that heat waves will increase in frequency, intensity, and duration under anthropogenic global warming. However, changes to heat extremes and temperature distributions in general are less understood in regions of complex terrain and substantial land-water contrasts. Such surface variations are important in the northwest United States, where synoptic- and mesoscale circulations interact with local topography and land-water interfaces to produce heat waves that have substantial impacts on fire weather, air quality, wind energy, and the population in general. Thus it is crucial to identify how the synoptic- and mesoscale circulations that drive such local extremes will change in a warming world. This paper analyzes changes to the conditions associated with heat extremes over the northwest United States by utilizing global and regional climate models. A maximum in 700-hPa warming is projected over the northwest United States and southwest Canada, with low-level warming attenuated near the coast. Soil moisture declines are projected over the region, which further enhances future extremes. It is found that low-level zonal wind distributions over the northwest United States become narrower, leading to fewer days with strong offshore flow. This is important since extreme warming events are associated with the strongest offshore/downslope flow. Historical and future regional temperature distributions are described and it is shown that although CMIP5 models predict increases in heat extremes for west Oregon and Washington, these increases are less than for inland areas. [ABSTRACT FROM AUTHOR]

In this paper, we report on the mixing structures and transport properties of the Adriatic Sea surface, as a semi-enclosed basin of the Mediterranean Sea, from October 2006 until December 2011. Lagrangian transport models were used to simulate synthetic trajectories from the mean flow fields obtained by the Massachusetts Institute of Technology general circulation model implemented for the Adriatic. We examine the dispersion properties of numerical pair particles, through the calculation of time-averaged finite-size Lyapunov exponents (FSLEs) in the Adriatic Sea during selected months in each year. The results show the significant effects of river runoff and wind forcing, especially the Bora wind field, on the mixing activities of numerical pair particles by the generation of vortices, which appear as a tangle of filaments on the FSLE maps. The stretch/compression lines, which contain high values of the FSLEs, work as robust transport barriers, most having been detected along boundary currents on the eastern and western flanks of the Adriatic, particularly during winter. Numerical experiments have indicated that stable flows, with less mixing activity, occur in the northern part of the Adriatic in June and September of each year, while the Southern Adriatic Pit has flows with larger seasonal fluctuations and high values of eddy kinetic energy because of the influence of wind and energetic currents entering from the Ionian Sea. [ABSTRACT FROM AUTHOR]

Data‐driven parameterizations offer considerable potential for improving the fidelity of General Circulation Models. However, ensuring that these remain consistent with the governing equations while still producing stable simulations remains a challenge. In this paper, we propose a combined Variational‐Multiscale (VMS) Artificial Neural Network (ANN) discretization which makes no a priori assumptions on the model form, and is only restricted in its accuracy by the precision of the ANN. Using a simplified problem, we demonstrate that good predictions of the required closure terms can be obtained with relatively compact ANN architectures. We then turn our attention to the stability of the VMS‐ANN discretization in the context of a single implicit time step. It is demonstrated that the ANN parameterization introduces nonphysical solutions to the governing equations that can significantly affect or prevent convergence. We show that enriching the training data with nonphysical states from intra‐time step iterations is an effective remedy. This indicates that the lack of representative ANN‐induced errors in our original, exact training inputs underpin the observed instabilities. In turn, this suggests that data set enrichment might aid in resolving instabilities that develop over several time steps. Plain Language Summary: Computer models of weather and climate have coarse resolutions, which prevent them from accurately predicting the effect of small atmospheric motions, for instance in low‐lying clouds, on the global climate. Recent studies indicate that improvements might be had by using models for the small motions that are informed purely by data, for example Artificial Neural Network (ANN) models. However, capitalizing on this potential is challenging in practice, since ANNs can introduce instabilities to the numerical model for larger‐scale motions. In this study, we zero in on these instabilities by introducing a model framework in which prediction accuracy is only limited by an ANN's ability to predict the net influence of small atmospheric motions. We contextualize this framework by contrasting it to more commonly used approaches. Using a simple test case based on the motions underpinning the development of low clouds, we illustrate that standard training procedures do not prepare ANN models for their interaction with the rest of the numerical model, and that this can contribute to numerical instability. We demonstrate an effective remedy for a specific type of instability, and suggest how this technique might also be used to treat other types of instabilities prompted by ANN models. Key Points: Artificial Neural Networks (ANNs) can parameterize exact closure terms of a Variational Multiscale method without a priori model form assumptionsThe ANN parameterization outperforms state‐of‐the‐art schemes in offline testsInstabilities in the numerical model comprising the ANN parameterization are amendable through data set enrichment [ABSTRACT FROM AUTHOR]

In the southern winter polar stratosphere, the distribution of gravity wave momentum flux in many state-of-the-art climate simulations is inconsistent with long-time satellite and superpressure balloon observations around 60 ∘ S. Recent studies hint that a lateral shift between prominent gravity wave sources in the tropospheric mid-latitudes and the location where gravity wave activity is present in the stratosphere causes at least part of the discrepancy. This lateral shift cannot be represented by the column-based gravity wave drag parameterisations used in most general circulation models. However, recent high-resolution analysis and re-analysis products of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) show good agreement with the observations and allow for a detailed investigation of resolved gravity waves, their sources, and propagation paths. In this paper, we identify resolved gravity waves in the ECMWF-IFS analyses for a case of high gravity wave activity in the lower stratosphere using small-volume sinusoidal fits to characterise these gravity waves. The 3D wave vector together with perturbation amplitudes, wave frequency, and a fully described background atmosphere are then used to initialise the Gravity Wave Regional or Global Ray Tracer (GROGRAT) gravity wave ray tracer and follow the gravity waves backwards from the stratosphere. Finally, we check for the indication of source processes on the path of each ray and, thus, quantitatively attribute gravity waves to sources that are represented within the model. We find that stratospheric gravity waves are indeed subject to far (>1000 km) lateral displacement from their sources, which already take place at low altitudes (<20 km). Various source processes can be linked to waves within stratospheric gravity wave (GW) patterns, such as the orography equatorward of 50 ∘ S and non-orographic sources above the Southern Ocean. These findings may explain why superpressure balloons observe enhanced gravity wave momentum fluxes in the lower stratosphere over the Southern Ocean despite an apparent lack of sources at this latitude. Our results also support the need to improve gravity wave parameterisations to account for meridional propagation. [ABSTRACT FROM AUTHOR]

There has been a growing interest in model-wise uncertainty decomposition, which quantifies contribution of individual models such as emission scenarios, global circulation models, bias correction techniques and hydrological models, to the total uncertainty of a hydrological projection. However, little research has been conducted for model-wise uncertainty decomposition in spite of its usefulness. In this paper, we propose a novel method for decomposing the total uncertainties into model-wise uncertainties. The proposed model-wise uncertainty decomposition method can be applied with general uncertainty measures, which include mean absolute deviation and variance measures. Moreover, the proposed method provides an intuitive interpretation of the quantified model-wise uncertainties. The results of analyzing real data by the proposed method are presented. [ABSTRACT FROM AUTHOR]

This paper assesses the long-term combined effects of land use (LU) and climate change on river hydrology and water scarcity of two rivers of the Western Ghats of India. The historical LU changes were studied for four decades (1988–2016) using the maximum likelihood algorithm and the long-term LU (2016–2075) was estimated using the Dyna-CLUE prediction model. Five General Circulation Models (GCMs) were utilized to assess the effects of climate change (CC) and the Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the two river catchments. To characterize granular effects of LU and CC on regional hydrology, a scenario approach was adopted and three scenarios depicting near-future (2006–2040), mid-future (2041–2070), and far-future (2071–2100) based on climate were established. The present rate of LU change indicated a reduction in forest cover by 20% and an increase in urbanized areas by 9.5% between 1988 and 2016. It was estimated that forest cover in the catchments may be expected to halve compared to the present-day LU (55% in 2016 to 23% in 2075), along with large-scale conversion to agricultural lands (13.5% in 2016 to 49.5% in 2075). As a result of changes to LU and forecasted climate, it was found that rivers in the Western Ghats of India might face scarcity of fresh water in the next two decades until the year 2040. However, because of large-scale LU conversion toward the year 2050, streamflow in rivers might increase as high as 70.94% at certain times of the year. Although an increase in streamflow is perceived favorable, the streamflow changes during summer and winter may be expected to affect the cropping calendar and crop yield. The changes to streamflow were also linked to a 4.2% increase in ecologically sensitive wetlands of the Aghanashini river catchment. [ABSTRACT FROM AUTHOR]

This paper shows how low-impact development (LID) practices affect the resilience of stormwater drainage system under climate change scenarios. A rainfall-runoff model was calibrated and evaluated a in a tropical watershed located in Midwestern Brazil. An ensemble of 17 general circulation model outputs forced by Representative Concentration Pathways (RCP 4.5 and RCP 8.5) was used to create future climate change scenarios up to 2095. The LID efficiency was evaluated based on the runoff peak reduction and the resilience of stormwater drainage by means of a resilience index. Overall, LID combinations showed a reduction in runoff peak higher than 20%, and the best LID combination had a reduction of as much as 46%. This represents a significant improvement in the resilience against flooding in the study area. Therefore, the findings can contribute to the increase in widespread adoption of LID and can encourage decisionmakers to provide such practices for urban flood management. [ABSTRACT FROM AUTHOR]

This paper describes the main characteristics of CNRM‐CM6‐1, the fully coupled atmosphere‐ocean general circulation model of sixth generation jointly developed by Centre National de Recherches Météorologiques (CNRM) and Cerfacs for the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6). The paper provides a description of each component of CNRM‐CM6‐1, including the coupling method and the new online output software. We emphasize where model's components have been updated with respect to the former model version, CNRM‐CM5.1. In particular, we highlight major improvements in the representation of atmospheric and land processes. A particular attention has also been devoted to mass and energy conservation in the simulated climate system to limit long‐term drifts. The climate simulated by CNRM‐CM6‐1 is then evaluated using CMIP6 historical and Diagnostic, Evaluation and Characterization of Klima (DECK) experiments in comparison with CMIP5 CNRM‐CM5.1 equivalent experiments. Overall, the mean surface biases are of similar magnitude but with different spatial patterns. Deep ocean biases are generally reduced, whereas sea ice is too thin in the Arctic. Although the simulated climate variability remains roughly consistent with CNRM‐CM5.1, its sensitivity to rising CO2 has increased: the equilibrium climate sensitivity is 4.9 K, which is now close to the upper bound of the range estimated from CMIP5 models. Key Points: Description of CNRM‐CM6‐1 model components, their coupling, and tuning procedures are describedHistorical simulations and DECK experiments are assessedPreindustrial simulation is stable and mean climate and variability in historical runs is realistic [ABSTRACT FROM AUTHOR]

This paper studies the Upper Tigris River (UTR) drainage basin in Turkey for climate change impacted runoff estimations. Statistical downscaling method (SDM) is used by taking into consideration spatial dependence function (SDF) for the scenario precipitation projections at a set of available meteorology stations. Temporal adjustment between the climate scenarios and precipitation record time series is achieved by the white Markov (WM) stochastic process. Although various climate research center scenario data are considered, herein, only the general circulation model (GCM) A2 scenario data are adapted from the Hadley Center, England. The precipitation and runoff results are presented in decadal groups starting from 2001 to 2050 as cumulative monthly precipitation (CMP) and cumulative monthly runoff (CMR) graphs. It is observed that after 2021, precipitation decreases at about 12.5% and after 2030, it is 26%. Runoff projections indicate that they may decrease at about 30% especial after 2040. [ABSTRACT FROM AUTHOR]