Stand-alone Atmospheric Model Research Articles

Ocean Dynamics Causes the Equatorial Pacific SST Bias in CAS‐ESM2‐0

AbstractCoupled ocean‐atmosphere models still suffer from systematic biases in simulating the sea‐surface temperature (SST) in the equatorial Pacific. Like in many current generations of climate models, the Chinese Academy of Sciences (CAS) Earth System Model (CAS‐ESM2‐0) simulated warmer SST in the eastern Pacific and colder SST in the central to western Pacific at the equator. We analyzed the physical processes causing these biases. We find that model biases in surface heat flux are a consequence, not the cause, of the SST bias. Ocean currents are implicated as the cause. The biases in ocean currents come from both the ocean model itself and the bias in surface winds in the atmospheric model. We show that the bias of ocean currents in the standalone ocean model causes warming in the region of positive precipitation bias in the standalone atmospheric model. When the two models are coupled, the precipitation bias is greatly amplified. Anomalous equatorial winds as atmospheric Rossby‐gravity wave response to precipitation induce additional bias in ocean currents that transport heat in the upper ocean. The cold equatorial SST bias in the central and western Pacific is found to be due to temperature advection by the anomalous zonal currents, while the warm bias in the eastern Pacific is due to advection by the anomalous zonal and meridional currents as well as downwelling. Results from the analysis offer insights into the causes of the SST biases in coupled models in the equatorial Pacific.

Predictability of Coastal Boundary Layer Jets in South China Using Atmosphere–Ocean Coupling

AbstractMost standalone atmospheric models do not perform well in simulations of coastal boundary layer jets (BLJs), important weather processes that can trigger heavy rain in coastal areas by supplying both moisture and dynamic lifting. We compared 33‐year simulations with a coupled atmosphere–ocean model and its standalone atmospheric component, the REgional atmosphere MOdel (REMO), forced by the prescribed sea surface temperature (SST). We validated our results using the Tropical Rainfall Measuring Mission SST and the ERA5 hourly reanalysis data set. We found that the coupled model gave a more realistic SST standard deviation than the REMO on BLJ days and corrected the overestimated air temperature over land during the day. The coupled atmosphere–ocean model showed a lower land–sea thermal contrast in the boundary layer. This increased the effects of inertial oscillation, which caused the ageostrophic flows to veer southwest, which is the direction of the maximum wind speed on BLJ days. This reproduced a more reasonable land–sea thermal contrast in the boundary layer as a result of strong air–sea mixing in coastal weather processes, which led to a more robust inertial oscillation and a larger SST standard deviation over the central South China Sea. These findings deepen our understanding of the influence of a fully mixed air–sea boundary on coastal weather processes. These results show that operational numerical weather prediction models can be improved by applying atmosphere–ocean coupling to advance their ability to forecast the weather (e.g., BLJ events) in coastal areas.

The appraisal of tropical cyclones in the North Indian Ocean: An overview of different approaches and the involvement of Earth’s components

This study aims to provide a comprehensive and balanced assessment of recent scientific studies on the evolution, temporal variability and prediction of tropical cyclones (TCs), focusing on the North Indian Ocean (NIO). The involvement of earth’s components in TC genesis and intensification has been elaborated in a confined way. The advancement of multidisciplinary approaches for comprehending the TCs is highlighted after a brief description of the involvement of oceanic, atmospheric, and land surface processes. Only a few studies illustrate how land surface plays a role in TC intensification; however, the role of latent heat flow, moisture, and convection in cyclogenesis is well documented. Despite two to 3 decades of advancement and significant development in forecasting techniques and satellite products, the prediction of TC’s intensity, dissipation, track, and landfall remains a challenge. The most noticeable improvements in NIO TC’s prediction have been achieved in the last couple of decades when concord techniques are utilized, especially the data assimilation methods and dynamical coupled atmosphere-ocean regional models. Through diverse methodologies, algorithms, parameterization, in-situ observational data, data mining, boundary layer, and surface fluxes, significant research has been done to increase the skills of standalone atmospheric models and air-sea coupled models. However, some crucial issues still exist, and it is suggested that they should be addressed in future studies.

Impact of air–sea coupling on the simulation of Indian summer monsoon using a high-resolution Regional Earth System Model over CORDEX-SA

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.

Impact of ocean waves on offshore wind farm power production

Offshore wind energy has seen a steady increase in the latest years as it serves as an ideal alternative energy source to meet our renewable energy goals. Due to this increase in interest and in installations of offshore wind farms a better understanding of the impact of waves on the power production of wind farms in necessary. This wave-wind farm power production interaction has scarcely been examined, however, some exceptions of small scale large-eddy-simulations exist. Unfortunately, these studies are not able to take multiple wind farms under real weather conditions into account. Here, we show the power production and wake lengths of 1250 offshore wind turbines located in the German Bight simulated by a stand-alone atmospheric (WRF) model and a coupled atmosphere-wave (WRF-SWAN) model. The coupled atmosphere-wave model estimates larger (smaller) power production in case of waves and wind traveling in the same (opposed) direction compared to the stand-alone atmospheric model. The relative difference between the two models can be as much as 20% for the two-week averaged grid power production, while the difference in total power over this two-week period is equal to 9%. Moreover, the wind farm wake lengths of waves and wind traveling in the same (opposed) direction are longer (shorter) for the coupled atmosphere-wave model compared to the stand-alone atmospheric model. Here, the relative difference of the mean wake length between the two models can be up to 25%. This shows the importance of waves as a part of the offshore wind environment and can be an important factor in future wind assessment or power production estimation studies.

Simulation of a flash-flood event over the Adriatic Sea with a high-resolution atmosphere\u2013ocean\u2013wave coupled system

On the morning of September 26, 2007, a heavy precipitation event (HPE) affected the Venice lagoon and the neighbouring coastal zone of the Adriatic Sea, with 6-h accumulated rainfall summing up to about 360 mm in the area between the Venetian mainland, Padua and Chioggia. The event was triggered and maintained by the uplift over a convergence line between northeasterly flow from the Alps and southeasterly winds from the Adriatic Sea. Hindcast modelling experiments, using standalone atmospheric models, failed to capture the spatial distribution, maximum intensity and timing of the HPE. Here we analyze the event by means of an atmosphere-wave-ocean coupled numerical approach. The combined use of convection permitting models with grid spacing of 1 km, high-resolution sea surface temperature (SST) fields, and the consistent treatment of marine boundary layer fluxes in all the numerical model components are crucial to provide a realistic simulation of the event. Inaccurate representations of the SST affect the wind magnitude and, through this, the intensity, location and time evolution of the convergence zone, thus affecting the HPE prediction.

Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model

AbstractThe importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.

Internal Model Variability of Ensemble Simulations With a Regional Coupled Wave-Atmosphere Model GCOAST

Ensemble simulations are performed to quantify the internal variability of both regional atmospheric models and wave-atmosphere coupled model systems. Studies have shown that the internal variability in atmospheric models (e.g., wind or pressure fields) is increased during extreme events, such as storms. Comparing the magnitude of the internal variability of the atmospheric model with the internal variability of the coupled model system reveals that the internal variability can be reduced by coupling a wave model to the atmospheric model. While this effect is most evident during extreme events, it is still present in a general assessment of the mean internal variability during the whole study period. Furthermore, the role of this wave-atmosphere coupling can be distinguished from that of the internal variability of the atmospheric model since the impact of the wave-atmosphere interaction is larger than the internal variability. This is shown to be robust to different boundary conditions. One method to reduce the internal variability of the atmospheric model is to apply spectral nudging, the role of which in both the stand-alone atmospheric model and the coupled wave-atmosphere system is evaluated. Our analyses show that spectral nudging in both coupled and stand-alone ensemble simulations keeps the internal variability low, while the impact of the wave-atmosphere interaction remains approximately the same as in simulations without spectral nudging, especially for the wind speed and significant wave height. This study shows that in operational and climate research systems, the internal variability of the atmospheric model is reduced when the ocean waves and atmosphere are coupled. Clear influences of the wave-atmosphere interaction on both of these earth system components can be detected and differentiated from the internal model variability. Furthermore, the wave-atmosphere coupling has a positive effect on the agreement of the model results with both satellite and in situ observations.

Multidecadal Seesaw in Hadley Circulation Strength Between the Two Hemispheres Caused by the Atlantic Multidecadal Variability

Multidecadal variations in Hadley circulation (HC) strength have been observed during the historical period, which have significant implications for global and regional climate. However, the relationship between HC intensities in the two hemispheres remains unclear. In this study, we identify an interhemispheric seesaw in the annual HC strength at multidecadal timescales. This seesaw pattern physically corresponds to the meridional movement of the ascending branch of annual HC, leading to strengthened HC in one hemisphere and weakened HC in the other. The HC strength seesaw strongly correlates with the tropical land surface precipitation at multidecadal timescales, particularly for the monsoonal land regions. Further analyses link the HC strength seesaw to the Atlantic multidecadal variability (AMV). A suite of Atlantic Pacemaker experiments successfully reproduces the multidecadal HC strength seesaw and its relation to the AMV. The Northern Hemisphere SST warming associated with the positive AMV phase induces a northward shift of the upward branch of HC, and the Southern Hemispheric HC is strengthened in contrast to the weakened Northern Hemispheric HC. Comparisons of the North Atlantic SST forced HC changes between the coupled air-sea model and stand-alone atmospheric model suggest an important and non-negligible role of the SST footprint of AMV over the Indo-Pacific basins. The AMV and its Indo-Pacific SST footprint make a comparable contribution to the SST changes in the Northern Hemisphere, which control the movement of the HC ascending branch and thereby the interhemispheric seesaw in HC strength.

Weakened Impact of the Developing El Niño on Tropical Indian Ocean Climate Variability under Global Warming

Abstract El Niño induces an anomalous easterly wind along the equator and a pair of anomalous anticyclones straddling the equator over the tropical Indian Ocean (TIO) during the autumn of its developing phase. Based on 30 coupled models participating in CMIP5, these atmospheric circulation anomalies over TIO are substantially weakened by about 12%–13% K−1 under global warming scenarios, associated with a weakened zonal gradient of the sea surface temperature (SST) anomaly. The mechanism for the response is investigated based on a hierarchy of model experiments. Based on stand-alone atmospheric model experiments under uniform and patterned mean-state SST warming, the atmospheric circulation anomaly over TIO during the autumn of the developing El Niño is also substantially weakened by about 8% K−1 even if the interannual variability of SST remains exactly unchanged, suggesting that the primary cause resides in the atmosphere rather than the SST anomaly. The tropospheric static stability is robustly enhanced under global warming, and experiments performed by a linear baroclinic model show that a much weaker atmospheric circulation anomaly over TIO is stimulated by an unchanged diabatic heating anomaly under a more stable atmosphere. The weakened atmospheric circulation anomaly due to enhanced static stability weakens the zonal gradient of the SST anomaly within TIO through local air–sea interaction, and it acts to further weaken the atmospheric circulation anomaly. The enhanced static stability of the troposphere is probably the primary cause and the air–sea interaction within TIO is a secondary cause for the weakened impact of the developing El Niño on atmospheric circulation variability over TIO.

A Robustness Analysis of CMIP5 Models over the East Asia-Western North Pacific Domain

Abstract The Coupled Model Intercomparison Project (CMIP) is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Improving the performance of climate models over East Asia and the western North Pacific has been a challenge for the climate-modeling community. In this paper, we provide a synthesis robustness analysis of the climate models participating in CMIP-Phase 5 (CMIP5). The strengths and weaknesses of the CMIP5 models are assessed from the perspective of climate mean state, interannual variability, past climate change during the mid-Pliocene (MP) and the last millennium, and climate projection. The added values of regional climate models relative to the driving global climate models are also assessed. Although an encouraging increase in credibility and an improvement in the simulation of mean states, interannual variability, and past climate changes are visible in the progression from CMIP3 to CMIP5, some previously noticed biases such as the ridge position of the western North Pacific subtropical high and the associated rainfall bias are still evident in CMIP5 models. Weaknesses are also evident in simulations of the interannual amplitude, such as El Nino-Southern Oscillation (ENSO)-monsoon relationships. Coupled models generally show better results than standalone atmospheric models in simulating both mean states and interannual variability. Multi-model intercomparison indicates significant uncertainties in the future projection of climate change, although precipitation increases consistently across models constrained by the Clausius-Clapeyron relation. Regional ocean-atmosphere coupled models are recommended for the dynamical downscaling of climate change projections over the East Asia-western North Pacific domain.

An Overview of CMIP5 and the Experiment Design

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.

An Investigation of the Initial Development of the Double-ITCZ Warm SST Biases in the CCSM

Abstract This paper investigates the initial development of the double ITCZ in the Community Climate System Model version 3 (CCSM3) in the central Pacific. Starting from a resting initial condition of the ocean in January, the model developed a warm bias of sea surface temperature (SST) in the central Pacific from 5°S to 10°S in the first three months. This initial bias is caused by excessive surface shortwave radiation that is also present in the stand-alone atmospheric model. The initial bias is further amplified by biases in both surface latent heat flux and horizontal heat transport in the upper ocean. These biases are caused by the responses of surface winds to SST bias and the thermocline structure to surface wind curls. This study also showed that the warming biases in surface solar radiation and latent heat fluxes are seasonally offset by cooling biases from reduced solar radiation after the austral summer due to cloud responses and in the austral fall due to enhanced evaporation when the maximum SST is closest to the equator. The warming biases from the dynamic heat transport by ocean currents however stay throughout all seasons once they are developed, which are eventually balanced by enhanced energy exchange and penetration of solar radiation below the mixed layer. It was also shown that the equatorial cold tongue develops after the warm biases in the south-central Pacific, and the overestimation of surface shortwave radiation recurs in the austral summer in each year. The results provide a case study on the physical processes leading to the development of the double ITCZ. Applicability of the results in other models is discussed.

Coupling between Northward-Propagating, Intraseasonal Oscillations and Sea Surface Temperature in the Indian Ocean*

Using a hybrid atmosphere–ocean coupled model, it is shown that during the boreal summer northward-propagating, intraseasonal oscillations (NPISOs) are strongly coupled to the underlying sea surface temperature (SST) in the Indian Ocean sector. On the one hand, the intraseasonal atmospheric convection changes the SST through solar radiation, latent heat flux, and mixed-layer entrainment; on the other, the induced SST fluctuations feed back to affect the intraseasonal convection. The preferential northward, rather than southward, propagation of boreal summer ISOs in the Indian Ocean is partially explained by an interaction among the summer-mean climate state, the atmospheric disturbances, and the ocean surface temperature. A solution to an atmosphere-only model forced with daily SST produces much stronger NPISOs than a similar solution forced with monthly mean SST (AMIP-type run). The atmosphere-only model, however, even when it is forced by daily SST from the coupled model (with a small amount of noise in the initial and/or boundary conditions), is unable to reproduce the NPISOs in the coupled case. In the coupled system, intraseasonal SST anomalies are forced by intraseasonal atmospheric convection, and hence are in quadrature with the convection. In the stand-alone atmospheric model, however, SST acts only as a boundary forcing, and the resultant atmospheric convection has almost the same phase with the underlying SST. One consequence is that the intensity of the SST-forced intraseasonal convection in the stand-alone atmospheric model is considerably weaker than in the coupled model. Finally, solutions indicate that the northward movement of the off-equatorial convection in the northern Indian Ocean is more closely related to local intraseasonal SST anomalies than to the equatorial eastward-moving Madden–Julian oscillation: Positive (negative) SST anomalies in the northern Indian Ocean lead the active (break) phases of the intraseasonal convection by about 2 pentads (10 days). Therefore, intraseasonal SST anomalies in the northern Indian Ocean are potentially a useful index to forecast active (break) spells of the south Asian summer monsoon.