Time-dependent response of a zonally averaged ocean–atmosphere–sea ice model to Milankovitch forcing

An ocean–atmosphere–sea ice model is developed to explore the time-dependent response of climate to Milankovitch forcing for the time interval 5–3 Myr BP. The ocean component is a zonally averaged model of the circulation in five basins (Arctic, Atlantic, Indian, Pacific, and Southern Oceans). The atmospheric component is a one-dimensional (latitudinal) energy balance model, and the sea-ice component is a thermodynamic model. Two numerical experiments are conducted. The first experiment does not include sea ice and the Arctic Ocean; the second experiment does. Results from the two experiments are used to investigate (1) the response of annual mean surface air and ocean temperatures to Milankovitch forcing, and (2) the role of sea ice in this response. In both experiments, the response of air temperature is dominated by obliquity cycles at most latitudes. On the other hand, the response of ocean temperature varies with latitude and depth. Deep water formed between 45°N and 65°N in the Atlantic Ocean mainly responds to precession. In contrast, deep water formed south of 60°S responds to obliquity when sea ice is not included. Sea ice acts as a time-integrator of summer insolation changes such that annual mean sea-ice conditions mainly respond to obliquity. Thus, in the presence of sea ice, air temperature changes over the sea ice are amplified, and temperature changes in deep water of southern origin are suppressed since water below sea ice is kept near the freezing point.     

Seasonal climate hindcasts with Eta model nested in CPTEC coupled ocean–atmosphere general circulation model

This work evaluates the added value of the downscaling technique employed with the Eta model nested in the CPTEC atmospheric general circulation model and in the CPTEC coupled ocean?Catmosphere general circulation model (CGCM). The focus is on the austral summer season, December?CJanuary?CFebruary, with three members each year. Precipitation, latent heat flux, and shortwave radiation flux at the surface hindcast by the models are compared with observational data and model analyses. The global models generally overestimate the precipitation over South America and tropical Atlantic. The CGCM and the nested Eta (Eta + C) both produce a split in the ITCZ precipitation band. The Eta + C produces better precipitation pattern for the studied season. The Eta model reduces the excessive latent heat flux generated by these global models, in particular the Eta + C. Comparison against PIRATA buoys data shows that the Eta + C results in the smallest precipitation and shortwave radiation forecast errors. The Eta + C comparatively best results are though as a consequence of both: the regional model resolution/physics and smaller errors on the lateral boundary conditions provided by the CGCM.     

Isolating mesoscale coupled ocean–atmosphere interactions in the Kuroshio Extension region

The Kuroshio Extension region is characterized by energetic oceanic mesoscale and frontal variability that alters the air–sea fluxes that can influence large-scale climate variability in the North Pacific. We investigate this mesoscale air-sea coupling using a regional eddy-resolving coupled ocean–atmosphere (OA) model that downscales the observed large-scale climate variability from 2001 to 2007. The model simulates many aspects of the observed seasonal cycle of OA coupling strength for both momentum and turbulent heat fluxes. We introduce a new modeling approach to study the scale-dependence of two well-known mechanisms for the surface wind response to mesoscale sea surface temperatures (SSTs), namely, the ‘vertical mixing mechanism’ (VMM) and the ‘pressure adjustment mechanism’ (PAM). We compare the fully coupled model to the same model with an online, 2-D spatial smoother applied to remove the mesoscale SST field felt by the atmosphere. Both VMM and PAM are found to be active during the strong wintertime peak seen in the coupling strength in both the model and observations. For VMM, large-scale SST gradients surprisingly generate coupling between downwind SST gradient and wind stress divergence that is often stronger than the coupling on the mesoscale, indicating their joint importance in OA interaction in this region. In contrast, VMM coupling between crosswind SST gradient and wind stress curl occurs only on the mesoscale, and not over large-scale SST gradients, indicating the essential role of the ocean mesocale. For PAM, the model results indicate that coupling between the Laplacian of sea level pressure and surface wind convergence occurs for both mesoscale and large-scale processes, but inclusion of the mesoscale roughly doubles the coupling strength. Coupling between latent heat flux and SST is found to be significant throughout the entire seasonal cycle in both fully coupled mode and large-scale coupled mode, with peak coupling during winter months. The atmospheric response to the oceanic mesoscale SST is also studied by comparing the fully coupled run to an uncoupled atmospheric model forced with smoothed SST prescribed from the coupled run. Precipitation anomalies are found to be forced by surface wind convergence patterns that are driven by mesoscale SST gradients, indicating the importance of the ocean forcing the atmosphere at this scale.     

A study on air–sea interaction on the simulated seasonal climate in an ocean–atmosphere coupled model

This study investigates the effects of air–sea interaction upon simulated tropical climatology, focusing on the boreal summer mean precipitation and the embedded intra-seasonal oscillation (ISO) signal. Both the daily coupling of ocean–atmosphere and the diurnal variation of sea surface temperature (SST) at every time step by accounting for the ocean mixed layer and surface-energy budget at the ocean surface are considered. The ocean–atmosphere coupled model component of the global/regional integrated model system has been utilized. Results from the coupled model show better precipitation climatology than those from the atmosphere-only model, through the inclusion of SST–cloudiness–precipitation feedback in the coupled system. Cooling the ocean surface in the coupled model is mainly responsible for the improved precipitation climatology, whereas neither the coupling itself nor the diurnal variation in the SST influences the simulated climatology. However, the inclusion of the diurnal cycle in the SST shows a distinct improvement of the simulated ISO signal, by either decreasing or increasing the magnitude of spectral powers, as compared to the simulation results that exclude the diurnal variation of the SST in coupled models.     

Role of sea surface temperature,Arctic sea ice and Siberian snow in forcing the atmospheric circulation in winter of 2012–2013

Climate Dynamics - During the 2012–2013 winter, the negative phase of the North Atlantic Oscillation (NAO) predominated, resulting in a cold winter over Europe and northern Asia punctuated by...     

A multi-model study of atmosphere predictability in coupled ocean–atmosphere systems

Of great importance for guiding numerical weather and climate predictions, understanding predictability of the atmosphere in the ocean − atmosphere coupled system is the first and critical step to understand predictability of the Earth system. However, previous predictability studies based on prefect model assumption usually depend on a certain model. Here we apply the predictability study with the Nonlinear Local Lyapunov Exponent and Attractor Radius to the products of multiple re-analyses and forecast models in several operational centers to realize general predictability of the atmosphere in the Earth system. We first investigated the predictability characteristics of the atmosphere in NCEP, ECMWF and UKMO coupled systems and some of their uncoupled counterparts and other uncoupled systems. Although the ECMWF Integrated Forecast System shows higher skills in geopotential height over the tropics, there is no certain model providing the most precise forecast for all variables on all levels and the multi-model ensemble not always outperforms a single model. Improved low-frequency signals from the air − sea and stratosphere − troposphere interactions that extend predictability of the atmosphere in coupled system suggests the significance of air − sea coupling and stratosphere simulation in practical forecast development, although uncertainties exist in the model representation for physical processes in air − sea interactions and upper troposphere. These inspire further exploration on predictability of ocean and stratosphere as well as sea − ice and land processes to advance our understanding of interactions of Earth system components, thus enhancing weather − climate prediction skills.

     

Predictability of the subtropical dipole modes in a coupled ocean–atmosphere model

Predictability of the subtropical dipole modes is assessed using the SINTEX-F coupled model. Despite the known difficulty in predicting subtropical climate due to large internal variability of the atmosphere and weak ocean–atmosphere coupling, it is shown for the first time that the coupled model can successfully predict the South Atlantic Subtropical Dipole (SASD) 1 season ahead, and the prediction skill is better than the persistence in all the 1–12 month lead hindcast experiments. There is a prediction barrier in austral winter due to the seasonal phase locking of the SASD to austral summer. The prediction skill is lower for the Indian Ocean Subtropical Dipole (IOSD) than for the SASD, and only slightly better than the persistence till 6-month lead because of the low predictability of the sea surface temperature anomaly in its southwestern pole. However, for some strong IOSD events in the last three decades, the model can predict them 1 season ahead. The co-occurrence of the negative SASD and IOSD in 1997/1998 austral summer can be predicted from July 1st of 1997. This is because the negative sea level pressure anomalies over the South Atlantic and the southern Indian Ocean in September–October (November–December) that trigger the occurrence of the negative SASD and IOSD are related to the well predicted tropical Indian Ocean Dipole (El Niño/Southern Oscillation). Owing to the overall good performances of the SINTEX-F model in predicting the SASD, some strong IOSD, and El Niño/Southern Oscillation, the prediction skill of the southern African summer precipitation is high in the SINTEX-F model.     

Application of a coupled ice‐ocean model to the Labrador Sea

Abstract

The steady, coupled ice‐ocean circulation model of Willmott and Mysak (1989) for a meridional channel is applied to the Labrador Sea for the winter season. The model consists of a thermodynamic reduced‐gravity ocean combined with a variable thickness ice cover that is in thermal equilibrium. Upon specifying the forcing fields of surface air temperature, wind stress and water temperature along the open southern boundary, the winter climatological ice‐edge position, ice thickness, ocean circulation and temperature fields are determined in the channel domain. The sensitivity of the results to the various model parameters is examined. In particular, the optimum heat exchange coefficients for the interfaces of air‐water, ice‐water and air‐ice are found.

The model ice‐edge position compares favourably with the 50% winter climatological ice concentration isoline obtained from an analysis of 32 years (1953–84) of sea‐ice concentration data. The simulations of the ocean temperature and ice thickness are also quite realistic according to the observed records available. The model is also applied to two specific winters (1981 and 1983) during which anomalous sea‐ice and weather conditions prevailed in the Labrador Sea.     

Arctic sea ice and the Madden–Julian Oscillation (MJO)

Arctic sea ice responds to atmospheric forcing in primarily a top-down manner, whereby near-surface air circulation and temperature govern motion, formation, melting, and accretion. As a result, concentrations of sea ice vary with phases of many of the major modes of atmospheric variability, including the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño-Southern Oscillation. However, until this present study, variability of sea ice by phase of the leading mode of atmospheric intraseasonal variability, the Madden–Julian Oscillation (MJO), which has been found to modify Arctic circulation and temperature, remained largely unstudied. Anomalies in daily change in sea ice concentration were isolated for all phases of the real-time multivariate MJO index during both summer (May–July) and winter (November–January) months. The three principal findings of the current study were as follows. (1) The MJO projects onto the Arctic atmosphere, as evidenced by statistically significant wavy patterns and consistent anomaly sign changes in composites of surface and mid-tropospheric atmospheric fields. (2) The MJO modulates Arctic sea ice in both summer and winter seasons, with the region of greatest variability shifting with the migration of the ice margin poleward (equatorward) during the summer (winter) period. Active regions of coherent ice concentration variability were identified in the Atlantic sector on days when the MJO was in phases 4 and 7 and the Pacific sector on days when the MJO was in phases 2 and 6, all supported by corresponding anomalies in surface wind and temperature. During July, similar variability in sea ice concentration was found in the North Atlantic sector during MJO phases 2 and 6 and Siberian sector during MJO phases 1 and 5, also supported by corresponding anomalies in surface wind. (3) The MJO modulates Arctic sea ice regionally, often resulting in dipole-shaped patterns of variability between anomaly centers. These results provide an important first look at intraseasonal variability of sea ice in the Arctic.     

Will the summer sea ice in the Arctic reach a tipping point?

The Arctic sea-ice cover has decreased in extent, area, and thickness over the last six decades. Most global climate models project that the summer sea-ice extent (SIE) will decline to less than 1 million (mill.) km² in this century, ranging from 2030 to the end of the century, indicating large uncertainty. However, some models, using the same emission scenarios as required by the Paris Agreement to keep the global temperature below 2°C, indicate that the SIE could be about 2 mill. km² in 2100 but with a large uncertainty of ±1.5 mill. km². Here, the authors take another approach by exploring the direct relationship between the SIE and atmospheric CO₂ concentration for the summer–fall months. The authors correlate the SIE and ln(CO₂/CO₂r) during the period 1979–2022, where CO₂r is the reference value in 1979. Using these transient regression equations with an R² between 0.78 and 0.87, the authors calculate the value that the CO₂ concentration needs to reach for zero SIE. The results are that, for July, the CO₂ concentration needs to reach 691 ± 16.5 ppm, for August 604 ± 16.5 ppm, for September 563 ± 17.5 ppm, and for October 620 ± 21 ppm. These values of CO₂ for an ice-free Arctic are much higher than the targets of the Paris Agreement, which are 450 ppm in 2060 and 425 ppm in 2100, under the IPCC SSP1-2.6 scenario. If these targets can be reached or even almost reached, the “no tipping point” hypothesis for the summer SIE may be valid.     

Bi-decadal variability excited in the coupled ocean–atmosphere system by strong tropical volcanic eruptions

Decadal and bi-decadal climate responses to tropical strong volcanic eruptions (SVEs) are inspected in an ensemble simulation covering the last millennium based on the Max Planck Institute—Earth system model. An unprecedentedly large collection of pre-industrial SVEs (up to 45) producing a peak annual-average top-of-atmosphere radiative perturbation larger than ?1.5 Wm^?2 is investigated by composite analysis. Post-eruption oceanic and atmospheric anomalies coherently describe a fluctuation in the coupled ocean–atmosphere system with an average length of 20–25 years. The study provides a new physically consistent theoretical framework to interpret decadal Northern Hemisphere (NH) regional winter climates variability during the last millennium. The fluctuation particularly involves interactions between the Atlantic meridional overturning circulation and the North Atlantic gyre circulation closely linked to the state of the winter North Atlantic Oscillation. It is characterized by major distinctive details. Among them, the most prominent are: (a) a strong signal amplification in the Arctic region which allows for a sustained strengthened teleconnection between the North Pacific and the North Atlantic during the first post-eruption decade and which entails important implications from oceanic heat transport and from post-eruption sea ice dynamics, and (b) an anomalous surface winter warming emerging over the Scandinavian/Western Russian region around 10–12 years after a major eruption. The simulated long-term climate response to SVEs depends, to some extent, on background conditions. Consequently, ensemble simulations spanning different phases of background multidecadal and longer climate variability are necessary to constrain the range of possible post-eruption decadal evolution of NH regional winter climates.     

Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.     

Thirty-two-year ocean–atmosphere coupled downscaling of global reanalysis over the Intra-American Seas

This study examines the oceanic and atmospheric variability over the Intra-American Seas (IAS) from a 32-year integration of a 15-km coupled regional climate model consisting of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System (ROMS) for the ocean. It is forced at the lateral boundaries by National Centers for Environmental Prediction-Department of Energy (NCEP-DOE R-2) atmospheric global reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis. This coupled downscaling integration is a free run without any heat flux correction and is referred as the Regional Ocean–Atmosphere coupled downscaling of global Reanalysis over the Intra-American Seas (ROARS). The paper examines the fidelity of ROARS with respect to independent observations that are both satellite based and in situ. In order to provide a perspective on the fidelity of the ROARS simulation, we also compare it with the Climate Forecast System Reanalysis (CFSR), a modern global ocean–atmosphere reanalysis product. Our analysis reveals that ROARS exhibits reasonable climatology and interannual variability over the IAS region, with climatological SST errors less than 1 °C except along the coastlines. The anomaly correlation of the monthly SST and precipitation anomalies in ROARS are well over 0.5 over the Gulf of Mexico, Caribbean Sea, Western Atlantic and Eastern Pacific Oceans. A highlight of the ROARS simulation is its resolution of the loop current and the episodic eddy events off of it. This is rather poorly simulated in the CFSR. This is also reflected in the simulated, albeit, higher variance of the sea surface height in ROARS and the lack of any variability in the sea surface height of the CFSR over the IAS. However the anomaly correlations of the monthly heat content anomalies of ROARS are comparatively lower, especially over the Gulf of Mexico and the Caribbean Sea. This is a result of ROARS exhibiting a bias of underestimation (overestimation) of high (low) clouds. ROARS like CFSR is also able to capture the Caribbean Low Level Jet and its seasonal variability reasonably well.     

Climate tendencies of changes in multiyear sea ice thickness in the Arctic Basin (1970–2005)

The area integral of the sea ice thickness in the Arctic Basin is estimated from the measurements of sea ice surface fluctuations at drift-ice stations. The 1970–1990 linear trend is indicative of an approximately 10-cm reduction in the average sea ice thickness over the entire Arctic Basin, which makes 3% of the average ice thickness (about 3 m). Seasonal changes made 40 cm. The amplitude of variations of the average ice thickness in that period is 20 cm with a period of changes of approximately 6–8 years. The observations were interrupted during 1991–2003 and then resumed in 2004. During 1990–2005, the old ice thickness over the entire Arctic Basin decreased, on average, by 110 cm.     

Coupling ocean–atmosphere intensity determines ocean chlorophyll-induced SST change in the tropical Pacific

Phytoplankton pigments (e.g., chlorophyll-a) absorb solar radiation in the upper ocean and induce a pronounced radiant heating effect (chlorophyll effect) on the climate. However, the ocean chlorophyll-induced heating effect on the mean climate state in the tropical Pacific has not been understood well. Here, a hybrid coupled model (HCM) of the atmosphere, ocean physics and biogeochemistry is used to investigate the chlorophyll effect on sea surface temperature (SST) in the eastern equatorial Pacific; a tunable coefficient, α, is introduced to represent the coupling intensity between the atmosphere and ocean in the HCM. The modeling results show that the chlorophyll effect on the mean-state SST is sensitively dependent on α (the coupling intensity). At weakly represented coupling intensity (0 ≤ α < 1.01), the chlorophyll effect tends to induce an SST cooling in the eastern equatorial Pacific, whereas an SST warming emerges at the strongly represented coupling intensity (α ≥ 1.01). Thus, a threshold exists for the coupling intensity (about α = 1.01) at which the sign of SST responses can change. Mechanisms and processes are illustrated to understand the different SST responses. In the weak coupling cases, indirect dynamical cooling processes (the adjustment of ocean circulation, enhanced vertical mixing, and upwelling) tend to dominate the SST cooling. In the strong coupling cases, the persistent warming induced by chlorophyll in the southern subtropical Pacific tends to induce cross-equatorial northerly winds, which shifts to anomalous westerly winds in the eastern equatorial Pacific, consequently reducing the evaporative cooling and weakening indirect dynamical cooling; eventually, SST warming maintains in the eastern equatorial Pacific. These results provide new insights into the biogeochemical feedback on the climate and bio-physical interactions in the tropical Pacific.