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A new high-resolution Regional Earth System Model, namely ROM, has been implemented over CORDEX-SA towards examining the impact of air–sea coupling on the Indian summer monsoon characteristics. ROM's simulated mean ISM rainfall and associated dynamical and thermodynamical processes, including the representation of northward and eastward propagating convention bands, are closer to observation than its standalone atmospheric model component (REMO), highlighting the advantage of air–sea coupling. However, the value addition of air–sea coupling varies spatially with more significant improvements over regions with large biases. Bay of Bengal and the eastern equatorial Indian Ocean are the most prominent region where the highest added value is observed with a significant reduction up to 50–500% precipitation bias. Most of the changes in precipitation over the ocean are associated with convective precipitation (CP) due to the suppression of convective activity caused by the negative feedback due to the inclusion of air–sea coupling. However, CP and large-scale precipitation (LP) improvements show east–west asymmetry over the Indian land region. The substantial LP bias reduction is noticed over the wet bias region of western central India due to its suppression, while enhanced CP over eastern central India contributed to the reduction of dry bias. An insignificant change is noticed over Tibetan Plateau, northern India, and Indo Gangetic plains. The weakening of moisture-laden low-level Somalia Jets causes the diminishing of moisture supply from the Arabian Sea (AS) towards Indian land regions resulting in suppressed precipitation, reducing wet bias, especially over western central India. The anomalous high kinetic energy over AS, wind shear, and tropospheric temperature gradient in REMO compared to observation is substantially reduced in the ROM, facilitating the favourable condition for suppressing moisture feeding and hence the wet bias over west-central India in ROM. The warmer midlatitude in ROM than REMO over eastern central India strengthens the convection, enhancing precipitation results in reducing the dry bias. Despite substantially improved ROM'performance, it still exhibits some systematic biases (wet/dry) partially associated with the persistent warm/cold SST bias and land–atmosphere interaction. [ABSTRACT FROM AUTHOR]

In this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean. [ABSTRACT FROM AUTHOR]

Cyclones with tropical characteristics called medicanes ("Mediterranean Hurricanes") eventually develop in the Mediterranean Sea. They have large harmful potential and a correct simulation of their evolution in climate projections is important for an adequate adaptation to climate change. Different studies suggest that ocean–atmosphere coupled models provide a better representation of medicanes, especially in terms of intensity and frequency. In this work, we use the regionally‐coupled model ROM to study how air‐sea interactions affect the evolution of medicanes in future climate projections. We find that under the RCP8.5 scenario our climate simulations show an overall frequency decrease which is more pronounced in the coupled than in the uncoupled configuration, whereas the intensity displays a different behaviour depending on the coupling. In the coupled run, the relative frequency of higher‐intensity medicanes increases, but this is not found in the uncoupled simulation. Also, this study indicates that the coupled model simulates better the summer minimum in the occurrence of medicanes, avoiding the reproduction of unrealistically intense events that can be found in summer in the uncoupled model. [ABSTRACT FROM AUTHOR]

The roles of air–sea coupling and horizontal resolution in the representation of Indian monsoon low pressure systems (LPS) in Met Office Unified Model (MetUM) global climate simulations are investigated. To avoid the generally large sea surface temperature (SST) biases in standard coupled atmosphere–ocean global climate models (GCMs), the analysis is performed on experiments from an atmosphere model coupled to a mixed-layer ocean model (MetUM-GOML2), which allows coupling to be applied regionally as well as globally, while constraining the ocean mean state in coupled regions. Compared to the standard AMIP-style MetUM atmosphere-only simulations, the MetUM-GOML2 simulations produce more monsoon LPS, which is attributed to effects of relatively small remaining (Indian Ocean) SST biases that somewhat strengthen the atmospheric monsoon base state. However, the MetUM-GOML2 simulations, all starting from the same atmospheric and oceanic base state, allow for an idealised approach to evaluate the relative effects of coupling and resolution. When the effects of SST biases are excluded, global coupling has a neutral impact on the number of LPS formed, while the associated rainfall is somewhat reduced due to a local negative air–sea feedback reducing the strength of atmospheric convection and weakening individual LPS. The MetUM-GOML2 simulations show particular sensitivity to localised coupling in the Indian and Pacific Oceans, which appears to enhance the effect of monsoon LPS. Although, in contrast to the global coupling comparison, the comparison of regionally coupled simulations is affected by both differences in interannual SST variability and SST biases, and it is likely that this causes at least part of the positive effects from Indian and Pacific Ocean coupling. More importantly, however, is that the effects of air–sea coupling are substantially smaller than the positive effects of the increase in horizontal resolution from N96 (approx. 200 km) to N216 (approx. 90 km). The resolution effect is also larger than that seen in older MetUM configurations. [ABSTRACT FROM AUTHOR]

Atmosphere‐ocean feedbacks often improve the Madden‐Julian oscillation (MJO) in climate models, but these improvements are balanced by mean state biases that can degrade the MJO through changing the basic state on which the MJO operates. The Super‐Parameterized Community Atmospheric Model (SPCAM3) produces perhaps the best representation of the MJO among contemporary models, which improves further in a coupled configuration (SPCCSM3) despite considerable mean state biases in tropical sea surface temperatures and rainfall. We implement an atmosphere‐ocean‐mixed‐layer configuration of SPCAM3 (SPCAM3‐KPP) and use a flux‐correction technique to isolate the effects of coupling and mean state biases on the MJO. When constrained to the observed ocean mean state, air‐sea coupling does not substantially alter the MJO in SPCAM3, in contrast to previous studies. When constrained to the SPCCSM ocean mean state, SPCAM3‐KPP fails to produce an MJO, in stark contrast to the strong MJO in SPCCSM3. Further KPP simulations demonstrate that the MJO in SPCCSM3 arises from an overly strong sensitivity to El Niño–Southern Oscillation events. Our results show that simulated interannual variability and coupled‐model mean state biases affect the perceived response of the MJO to coupling. This is particularly concerning in the context of internal variability in coupled models, as many previous MJO sensitivity studies in coupled models used relatively short (20‐ to 50‐year) simulations that undersample interannual‐decadal variability. Diagnosing the effects of coupling on the MJO requires simulations that carefully control for mean state biases and interannual variability. Plain Language Summary: Many studies suggest that feedbacks between the atmosphere and ocean are essential for simulating the Madden‐Julian oscillation, which controls weekly to monthly tropical rainfall. However, model experiments that diagnose the effect of these feedbacks are often not performed in a controlled manner, because introducing atmosphere‐ocean feedbacks changes other aspects of the simulation, including the background climate and phenomena such as the El Niño–Southern Oscillation. These changes may affect the Madden‐Julian oscillation as well, separately from direct atmosphere‐ocean feedbacks, but these changes are often erroneously considered part of the sensitivity of the Madden‐Julian oscillation to atmosphere‐ocean feedbacks. We demonstrate that in one model that simulates the Madden‐Julian oscillation well, the Super‐Parameterized Community Atmospheric Model, intraseasonal atmosphere‐ocean feedbacks alone do not substantially alter the Madden‐Julian oscillation. Rather, the previously perceived improvement to the Madden‐Julian oscillation from atmosphere‐ocean feedbacks arises from a too strong response of the Madden‐Julian oscillation to El Niño events. Future studies must carefully control for how introducing atmosphere‐ocean feedbacks affects other aspects of the simulation, to better isolate the effect of those feedbacks on the Madden‐Julian oscillation. Key Points: The response of the Madden‐Julian oscillation (MJO) to coupling is sensitive to the representation of interannual variabilityDiagnosing intraseasonal coupled feedbacks to the MJO requires controling for interannual variability and mean state biasesAir‐sea coupling is not essential to simulate the MJO in the Super‐Parameterized Community Atmospheric Model [ABSTRACT FROM AUTHOR]

This study introduces a new flow‐dependent distribution sampling (FDDS) scheme for air–sea coupling. The FDDS scheme is implemented in a climate model and used to improve the simulated mean and variability of atmospheric and oceanic surface fields and thus air–sea fluxes. Most coupled circulation models use higher resolutions in the sea ice and ocean compared to the atmospheric model component, thereby explicitly simulating the atmospheric subgrid‐scale at the interface. However, the commonly applied averaging of surface fields and air–sea fluxes tends to smooth fine‐scale structures, such as oceanic fronts. The stochastic FDDS scheme samples the resolved spatial ocean (and sea ice) subgrid distribution that is usually not visible to a coarser‐resolution atmospheric model. Randomly drawn nodal ocean values are passed to the corresponding atmospheric boxes for the calculation of surface fluxes, aiming to enhance surface flux variability. The resulting surface field perturbations of the FDDS scheme are based on resolved dynamics, displaying pronounced seasonality with realistic magnitude. The AWI Climate Model is used to test the scheme on interannual time‐scales. Our set‐up features a high ocean‐to‐atmosphere resolution ratio in the Tropics, with grid‐point ratios of about 60:1. Compared to the default deterministic averaging, changes are largest in the Tropics leading to an improved spatial distribution of precipitation with bias reductions of up to 50%. Enhanced sea‐surface temperature variability in boreal winter further improves the seasonal phase locking of temperature anomalies associated with the El Niño–Southern Oscillation. Mean 2m temperature, sea ice thickness and concentration react with a contrasting dipole pattern between hemispheres but a joint increase of monthly and interannual variability. This first approach to implement a flow‐dependent stochastic coupling scheme shows considerable benefits for simulations of global climate, and various extensions and modifications of the scheme are possible. [ABSTRACT FROM AUTHOR]

We examine the merit of atmosphere–ocean coupled models for tropical cyclone (TC) predictions in the western North Pacific (WNP), where accurate TC predictions remain challenging. The UK Met Office operational atmospheric global numerical weather prediction (NWP) model is compared with two trial coupled configurations, in which the operational atmospheric model is coupled to a one‐dimensional mixed‐layer ocean model and a three‐dimensional dynamical ocean model. Reforecasts for the 2016 TC season show that the coupled models outperform the NWP model for TC location predictions, with a systematic improvement of 50–100 km over the seven‐day forecasts, but the coupled models amplify the underestimation of TC intensity in the NWP model. Nearly identical TC predictions (for both location and intensity) are found in the two coupled models, indicating the dominance of thermodynamic processes at the air–sea interface for TC predictions on these timescales. The improved prediction of the TC position in the coupled models is associated with an enhanced Western North Pacific Subtropical High (WNPSH), which introduces an anticyclonic steering flow anomaly that shifts TC tracks further west in the southern part of the region and further east in the northern part. Based on sensitivity experiments, we show that these improvements in the coupled models are due mainly to colder initial sea‐surface temperatures (SSTs). Air–sea feedbacks do not change the WNPSH or TC tracks noticeably. Apart from the effect of the initial SSTs, tropical ocean warming due to air–sea interaction in the coupled forecasts can also reduce the predicted TC intensity, presumably due to a stronger regional Hadley circulation with increased subtropical subsidence. [ABSTRACT FROM AUTHOR]

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM’s intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects. [ABSTRACT FROM AUTHOR]

This study introduces a new approach to investigate the potential effects of air-sea coupling on simulated precipitation inland over Central Europe. We present an inter-comparison of two regional climate models (RCMs), namely, the COSMO-CLM (hereafter CCLM) and RCA4 models, which are configured for the EURO-CORDEX domain in the coupled and atmosphere-only modes. Two versions of the CCLM model, namely, 4.8 and 5.0, join the inter-comparison being almost two different models while providing pronouncedly different summer precipitation simulations because of many changes in the dynamics and physics of CCLM in version 5.0. The coupling effect on the prominent summer dry bias over Central Europe is analysed using seasonal (JJA) mean statistics for the 30-year period from 1979 to 2009, with a focus on extreme precipitation under specific weather regimes. The weather regimes are compared between the coupled and uncoupled simulations to better understand the mechanism of the coupling effects. The comparisons of the coupled systems with the atmosphere-only models show that coupling clearly reduces the dry bias over Central Europe for CCLM 4.8, which has a large dry summer bias, but not for CCLM 5.0 and RCA4, which have smaller dry biases. This result implies that if the atmosphere-only model already yields reasonable summer precipitation over Central Europe, not much room for improvement exists that can be caused by the air-sea coupling over the North Sea and the Baltic Sea. However, if the atmosphere-only model shows a pronounced summer dry bias because of a lack of moisture transport from the seas into the region, the considered coupling may create an improved simulation of summer precipitation over Central Europe, such as for CCLM 4.8. For the latter, the benefit of coupling varies over the considered timescales. The precipitation simulations that are generated by the coupled system COSTRICE 4.8 and the atmosphere-only CCLM 4.8 are mostly identical for the summer mean. However, the COSTRICE simulations are generally more accurate than the atmosphere-only CCLM simulations if extreme precipitation is considered, particularly under Northerly Circulation conditions, in which the airflow from the North Atlantic Ocean passes the North Sea in the coupling domain. The air-sea feedback (e.g., wind, evaporation and sea surface temperature) and land-sea interactions are better reproduced with the COSTRICE model system than the atmosphere-only CCLM and lead to an improved simulation of large-scale moisture convergence from the sea to land and, consequently, increased heavy precipitation over Central Europe. [ABSTRACT FROM AUTHOR]

A successful simulation of the western North Pacific summer monsoon needs a regional ocean-atmosphere coupled model (ROAM). How the performance of ROAM relies on the oceanic component model remains unknown. In this study, the authors investigated the effects of different oceanic components on the simulation of western North Pacific (WNP) summer monsoon in a ROAM. Three cases of simulations were performed, viz. the summer of 1998 (El Niño decaying phase), 2004 (El Niño developing phase), and 1993 (the non-ENSO phase). Results show that the coupled simulations for different ENSO phases exhibit improvements in the simulation of location of Meiyu rainband and spatial distribution of monsoon low-level flow over WNP, whereas the systemic cold biases of sea surface air temperature are further increased. The coupled simulations with different oceanic components show similar performance, which is not ENSO phase dependent. For the case of the summer of 1998, a slightly stronger western Pacific subtropical high and colder sea surface air temperature are found in the simulation with colder sea surface temperature (SST) biases. The colder SST biases are partly contributed by the ocean dynamics processes because the sea surface net flux favors a warmer SST. This study suggests that the dependence of performance of ROAM over WNP on oceanic models is much weaker than that on atmospheric models. [ABSTRACT FROM AUTHOR]

Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September–31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions. [ABSTRACT FROM AUTHOR]