Coupled General Circulation Model Research Articles

A statistical downscaling scheme to improve global precipitation forecasting

Based on hindcasts obtained from the “Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction” (DEMETER) project, this study proposes a statistical downscaling (SD) scheme suitable for global precipitation forecasting. The key idea of this SD scheme is to select the optimal predictors that are best forecast by coupled general circulation models (CGCMs) and that have the most stable relationships with observed precipitation. Developing the prediction model and further making predictions using these predictors can extract useful information from the CGCMs. Cross-validation and independent sample tests indicate that this SD scheme can significantly improve the prediction capability of CGCMs during the boreal summer (June–August), even over polar regions. The predicted and observed precipitations are significantly correlated, and the root-mean-square-error of the SD scheme-predicted precipitation is largely decreased compared with the raw CGCM predictions. An inter-model comparison shows that the multi-model ensemble provides the best prediction performance. This study suggests that combining a multi-model ensemble with the SD scheme can improve the prediction skill for precipitation globally, which is valuable for current operational precipitation prediction.

The equatorial Pacific cold tongue simulated by IPCC AR4 coupled GCMs: Upper ocean heat budget and feedback analysis

This study examines the contribution of ocean dynamics to sea surface temperature (SST) biases in the eastern Pacific cold tongue region in fifteen coupled general circulation models (CGCMs) participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Twenty years (1980–1999) of the twentieth‐century (20C3m) climate simulations from each model are analyzed. An excessive and narrow SST cold tongue that extends too far west into the western Pacific in comparison to observations is a common bias in CGCMs. This feature is found in CGCMs analyzed here and in many previous studies. The heat budget analysis indicates that errors in both net surface heat flux and total upper ocean heat advection significantly contribute to the excessive cold tongue in the equatorial Pacific. The stronger heat advection in the models is caused by overly strong horizontal heat advection associated with too strong zonal currents, and overly strong vertical heat advection due to excessive upwelling and the vertical gradient of temperature. The Bjerknes feedback in the coupled models is shown to be weaker than in observations, which may be related to the insufficient response of surface zonal winds to SST in the models and an erroneous subsurface temperature structure. A hypothesis that describes how the cold tongue bias is possibly developed in the CGCMs is provided based on the results of our analysis.

Role of the Indo-Pacific Interbasin Coupling in Predicting Asymmetric ENSO Transition and Duration

Warm and cold phases of El Niño–Southern Oscillation (ENSO) exhibit a significant asymmetry in their transition/duration such that El Niño tends to shift rapidly to La Niña after the mature phase, whereas La Niña tends to persist for up to 2 yr. The possible role of sea surface temperature (SST) anomalies in the Indian Ocean (IO) in this ENSO asymmetry is investigated using a coupled general circulation model (CGCM). Decoupled-IO experiments are conducted to assess asymmetric IO feedbacks to the ongoing ENSO evolution in the Pacific. Identical-twin forecast experiments show that a coupling of the IO extends the skillful prediction of the ENSO warm phase by about one year, which was about 8 months in the absence of the IO coupling, in which a significant drop of the prediction skill around the boreal spring (known as the spring prediction barrier) is found. The effect of IO coupling on the predictability of the Pacific SST is significantly weaker in the decay phase of La Niña. Warm IO SST anomalies associated with El Niño enhance surface easterlies over the equatorial western Pacific and hence facilitate the El Niño decay. However, this mechanism cannot be applied to cold IO SST anomalies during La Niña. The result of these CGCM experiments estimates that approximately one-half of the ENSO asymmetry arises from the phase-dependent nature of the Indo-Pacific interbasin coupling.

Improved Simulation of the South Asian Summer Monsoon in a Coupled GCM with a More Realistic Ocean Mixed Layer

Abstract Simulation and prediction of the South Asian summer monsoon in a climate model remain a challenge despite intense efforts by the atmosphere and ocean research community. Because the phenomenon arises from the interaction of the atmosphere with the upper ocean, a deficiency in the simulation of the latter can lead to a poor simulation of the atmospheric meridional circulation. This study demonstrates that a significant improvement can be obtained in the simulation of the summer monsoon by correcting a prevailing deficiency in the mixed layer simulation of the Indian Ocean. A particular physical process of the nonbreaking wave–ocean mixing parameterized as Bυ, which has not been considered in any climate model, is included in this study to enhance the vertical mixing in the upper ocean. Results show that the inclusion of this mixing process in a climate model leads to a better simulation of the ocean mixed layer, especially in the regions where the mixing was previously underestimated. The improved mixed layer simulation further results in stronger meridional differential heating, which drives stronger low-level monsoonal winds and results in stronger moisture transport and convergence, especially in the northern Indian Ocean. Moisture convergence into the Bay of Bengal is significantly enhanced and in general the spatial distribution of moisture is more consistent with observations. The directly driven monsoonal winds by the differential heating are further amplified by the resultant latent heating, which generates not only a wind amplitude comparable to the observations but also a correct vertical structure.

Coupled bred vectors in the tropical Pacific and their application to ENSO prediction

Two independent coupled bred vectors (BVs) were generated to capture growing errors related to a high-frequency mode and typical ENSO mode by applying different rescaling cycles using the SNU Coupled GCM. We showed that zonal advection (vertical advection) is primary mechanism to develop SST perturbation with 1-month (6-month) rescaling cycle, which implies that the physical mechanisms of two coupled BVs are different. In addition, the dominant pattern of a 1-month (6-month) rescaling BV thermocline depth showed a large positive anomaly over the central Pacific (eastern Pacific). Twenty-year ensemble hindcast with BVs showed a significant correlation improvement over the tropical Pacific regions when compared to lagged averaged forecast perturbations. The improvement was greatest after taking ensemble average of two pairs of BVs, providing evidence that BV1 and BV6 exhibit dynamically independent modes.

Predictability of the East Asian winter monsoon interannual variability as indicated by the DEMETER CGCMS

The interannual variability of East Asian winter monsoon (EAWM) circulation from the Development of a European Multi-Model Ensemble (MME) System for Seasonal to Inter-Annual Prediction (DEMETER) hindcasts was evaluated against observation reanalysis data. We evaluated the DEMETER coupled general circulation models (CGCMs)’ retrospective prediction of the typical EAWM and its associated atmospheric circulation. Results show that the EAWM can be reasonably predicted with statistically significant accuracy, yet the major bias of the hindcast models is the underestimation of the related anomalies. The temporal correlation coefficient (TCC) of the MME-produced EAWM index, defined as the first EOF mode of 850-hPa air temperature within the EAWM domain (20°–60°N, 90°–150°E), was 0.595. This coefficient was higher than those of the corresponding individual models (range: 0.39–0.51) for the period 1969–2001; this result indicates the advantage of the super-ensemble approach. This study also showed that the ensemble models can reasonably reproduce the major modes and their interannual variabilities for sea level pressure, geopotential height, surface air temperature, and wind fields in Eurasia. Therefore, the prediction of EAWM interannual variability is feasible using multimodel ensemble systems and that they may also reveal the associated mechanisms of the EAWM interannual variability.

The Role of Sea Ice Thickness Distribution in the Arctic Sea Ice Potential Predictability: A Diagnostic Approach with a Coupled GCM

Abstract The intrinsic seasonal predictability of Arctic sea ice is investigated in a 400-yr-long preindustrial simulation performed with the Centre National de Recherches Météorologiques Coupled Global Climate Model, version 3.3 (CNRM-CM3.3). The skill of several predictors of the pan-Arctic sea ice area was quantified: the sea ice area itself, the pan-Arctic sea ice volume, and some areal predictors built from the subgrid ice thickness distribution (ITD). Sea ice area provides a potential predictability of about 3 months, which is consistent with previous studies using model and observation data. Sea ice volume predictive skill for winter sea ice area prediction is weak. Nevertheless, there is a higher potential to predict the September ice area with the June volume anomaly than with the June area anomaly. Using ITD-based predictors, two “regimes” of predictability were highlighted. The first one, a “persistence regime,” applies to winter/early spring sea ice seasonal predictability. The winter sea ice cover can be predicted in late fall/early winter from the amount of young ice formed since the freeze-up onset in the margins. However, sea ice area itself is potentially the best predictor of winter sea ice area at seasonal time scales. The second regime is a “memory regime.” It applies to the predictability of summer sea ice area. An ice area anomaly in September is potentially predictable up to 6 months in advance, using the area covered by ice thicker than a critical thickness lying between 0.9 and 1.5 m. Results of this study are preliminary; however, they provide information for the design of future prediction systems and highlight the need for observations and a state-of-the-art sea ice model.

기후변화 시나리오에 따른 미래 논벼의 소비수량 및 생산량 변화 분석

Agriculture is dependable to weather condition and its change so that it is necessary to understand the impacts of climatic change. The aim of this study is to analyze the change of consumptive use of water and rice yield due to climate change using CERES-Rice. In this study, the weather data of three emission scenario of A1B, A2 and B1 created from CGCM (Coupled General Circulation Model) were used from 2011 to 2100, and downscaled daily weather data were simulated using LARS-WG (Long Ashton Research Station Weather Generator). The input data for cultivated condition for simulating CERSE (Crop-Environment Resource Synthesis)-Rice were created referring to standard cultivation method of paddy rice in Korea. The results showed that consumptive uses of water for paddy rice were projected decreasing to 4.8 % (2025s), 9.1 % (2055s), 12.6 % (2085s) comparing to the baseline value of 403.5 mm in A2 scenario. The rice yield of baseline was 450.7 kg/10a and projected increasing to -0.4 % (2025s), 3.9 % (2055s), 17.5 % (2085s) in A1B scenario. The results demonstrated relationships between consumptive use of water and rice yields due to climate change and can be used for the agricultural water resources development planning and cultivation method of paddy rice for the future.

Inter-model variability and biases of the global water cycle in CMIP3 coupled climate models

Observed changes such as increasing global temperatures and the intensification of the global water cycle in the 20th century are robust results of coupled general circulation models (CGCMs). In spite of these successes, model-to-model variability and biases that are small in first order climate responses, however, have considerable implications for climate predictability especially when multi-model means are used. We show that most climate simulations of the 20th and 21st century A2 scenario performed with CMIP3 (Coupled Model Inter-comparison Project Phase 3) models have deficiencies in simulating the global atmospheric moisture balance. Large biases of only a few models (some biases reach the simulated global precipitation changes in the 20th and 21st centuries) affect the multi-model mean global moisture budget. An imbalanced flux of −0.14 Sv exists while the multi-model median imbalance is only −0.02 Sv. Moreover, for most models the detected imbalance changes over time. As a consequence, in 13 of the 18 CMIP3 models examined, global annual mean precipitation exceeds global evaporation, indicating that there should be a ‘leaking’ of moisture from the atmosphere whereas for the remaining five models a ‘flooding’ is implied. Nonetheless, in all models, the actual atmospheric moisture content and its variability correctly increases during the course of the 20th and 21st centuries. These discrepancies therefore imply an unphysical and hence ‘ghost’ sink/source of atmospheric moisture in the models whose atmospheres flood/leak. The ghost source/sink of moisture can also be regarded as atmospheric latent heating/cooling and hence as positive/negative perturbation of the atmospheric energy budget or non-radiative forcing in the range of −1 to +6 W m−2 (median +0.1 W m−2). The inter-model variability of the global atmospheric moisture transport from oceans to land areas, which impacts the terrestrial water cycle, is also quite high and ranges from 0.26 to 1.78 Sv. In the 21st century this transport to land increases by about 5% per century with a model-to-model range from 1 to 13%. We suggest that this variability is weakly correlated to the land–sea contrast in air temperature change of these models. Spatially heterogeneous forcings such as aerosols contribute to the variability in moisture transport, at least in one model. The polewards shifts of dry zones in climate simulations of the 21st century are also assessed. It is shown that the multi-model means of the two subsets of models with negative and positive imbalances in the atmospheric moisture budget produce spatial variability in the dry zone positions similar in size to the spatial shifts expected from 21st century global warming. Thus, the selection of models also affects the multi-model mean dry zone extension. In general, we caution the use of multi-model means of E − P fields and suggest self-consistency tests for climate models.

Seasonal Evolutions of Atmospheric Response to Decadal SST Anomalies in the North Pacific Subarctic Frontal Zone: Observations and a Coupled Model Simulation

Abstract Potential impacts of pronounced decadal-scale variations in the North Pacific sea surface temperature (SST) that tend to be confined to the subarctic frontal zone (SAFZ) upon seasonally varying atmospheric states are investigated, by using 48-yr observational data and a 120-yr simulation with an ocean–atmosphere coupled general circulation model (CGCM). SST fields based on in situ observations and the ocean component of the CGCM have horizontal resolutions of 2.0° and 0.5°, respectively, which can reasonably resolve frontal SST gradient across the SAFZ. Both the observations and CGCM simulation provide a consistent picture between SST anomalies in the SAFZ yielded by its decadal-scale meridional displacement and their association with atmospheric anomalies. Correlated with SST anomalies persistent in the SAFZ from fall to winter, a coherent decadal-scale signal in the wintertime atmospheric circulation over the North Pacific starts emerging in November and develops into an equivalent barotropic anomaly pattern similar to the Pacific–North American (PNA) pattern. The PNA-like signal with the weakened (enhanced) surface Aleutian low correlated with positive (negative) SST anomalies in the SAFZ becomes strongest and most robust in January, under the feedback forcing from synoptic-scale disturbances migrating along the Pacific storm track that shifts northward (southward) in accord with the oceanic SAFZ. This PNA-like signal, however, breaks down in February, which is suggestive of a particular sensitivity of that anomaly pattern to subtle differences in the background climatological-mean state. Despite its collapse in February, the PNA-like signal recurs the next January. This subseasonal evolution of the signal suggests that the PNA-like anomaly pattern may develop as a response to the persistent SST anomalies that are maintained mainly through ocean dynamics.

MIROC4h—A New High-Resolution Atmosphere-Ocean Coupled General Circulation Model

MIROC4h—A New High-Resolution Atmosphere-Ocean Coupled General Circulation Model

Forecasting estimates of weather conditions for fire-hazardous season in forests

Possible changes of climatic conditions for fire-hazardous seasons for the XXI century have been considered. Forecasting calculations are based on the results of climatic conditions simulation on the ensemble of atmosphere and ocean coupled general circulation models (CGCM) considering different scenarios of social development and anthropogenic emissions of greenhouse gas.

The role of the intra-daily SST variability in the Indian monsoon variability and monsoon-ENSO–IOD relationships in a global coupled model

The impact of diurnal SST coupling and vertical oceanic resolution on the simulation of the Indian Summer Monsoon (ISM) and its relationships with El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events are studied through the analysis of four integrations of a high resolution Coupled General Circulation Model (CGCM), but with different configurations. The only differences between the four integrations are the frequency of coupling between the ocean and atmosphere for the Sea Surface Temperature (SST) parameter (2 vs. 24 h coupling) and/or the vertical oceanic resolution (31 vs. 301 levels) in the CGCM. Although the summer mean tropical climate is reasonably well captured with all the configurations of the CGCM and is not significantly modified by changing the frequency of SST coupling from once to twelve per day, the ISM–ENSO teleconnections are rather poorly simulated in the two simulations in which SST is exchanged only once per day, independently of the vertical oceanic resolution used in the CGCM. Surprisingly, when 2 h SST coupling is implemented in the CGCM, the ISM–ENSO teleconnection is better simulated, particularly, the complex lead-lag relationships between the two phenomena, in which a weak ISM occurs during the developing phase of an El Niño event in the Pacific, are closely resembling the observed ones. Evidence is presented to show that these improvements are related to changes in the characteristics of the model’s El Niño which has a more realistic evolution in its developing and decaying phases, a stronger amplitude and a shift to lower frequencies when a 2-hourly SST coupling strategy is implemented without any significant changes in the basic state of the CGCM. As a consequence of these improvements in ENSO variability, the lead relationships between Indo-Pacific SSTs and ISM rainfall resemble the observed patterns more closely, the ISM–ENSO teleconnection is strengthened during boreal summer and ISM rainfall power spectrum is in better agreement with observations. On the other hand, the ISM–IOD teleconnection is sensitive to both SST coupling frequency and the vertical oceanic resolution, but increasing the vertical oceanic resolution is degrading the ISM–IOD teleconnection in the CGCM. These results highlight the need of a proper assessment of both temporal scale interactions and coupling strategies in order to improve current CGCMs. These results, which must be confirmed with other CGCMs, have also important implications for dynamical seasonal prediction systems or climate change projections of the monsoon.

Evaluation of IPCC Models’ Performance in Simulating Late-Twentieth-Century Climatologies and Weather Patterns over North America

Abstract The authors analyze the performance of 22 Intergovernmental Panel on Climate Change (IPCC) global climate models (GCMs) over all of North America and its western subregion using several different evaluation metrics. They assess the model skill in simulating climatologies of several climate variables and the skill in simulating the daily synoptic patterns. The evaluation is performed by comparing the model output with the North American Regional Reanalysis (NARR) over the period 1980–99. One set of metrics, based on root-mean-square errors and variance ratios, compares modeled versus the NARR mean annual cycle and interannual variability. Based on these measures the three top performing models are the ECHAM5–Max Planck Institute Ocean Model (MPI-OM), the third climate configuration of the Met Office Unified Model (HadCM3), and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled General Circulation Model, version 3.1 [CGCM3.1(T47)]. Models that perform well over all North America also perform well over its western subregion. However, the model ranking is sensitive to the choice of climate variable. For another evaluation measure the method of self-organizing maps was applied to classify the characteristic daily patterns of sea level pressure over the region. The evaluation consists of correlating the frequencies of these patterns, as generated in GCMs, with the frequencies in the NARR over the baseline period. Most of the models are successful in simulating the frequencies of daily anomaly patterns from the 20-yr-average daily pattern. However, very few GCMs are able to reproduce the occurrences of characteristic daily weather patterns in the NARR on seasonal basis over the baseline period. In terms of relative performance, the three top performing models are the Meteorological Research Institute (MRI) CGCM2.3.2, ECHAM5–MPI-OM, and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]. The model skill in simulating daily synoptic patterns is not strongly linked to the skill in simulating the climatologies of selected variables. Despite the large scatter of model performance across all the metrics, some models consistently rank high [e.g., ECHAM5–MPI-OM and MIROC3.2(medres)]. Likewise, some models consistently rank low [e.g., the Community Climate System Model, version 3 (CCSM3) and the Goddard Institute for Space Studies Model E-R (GISS-ER)] independently of the evaluation measures, domain size, and climate variable of interest.

Changes of climate extremes in a typical arid zone: Observations and multimodel ensemble projections

[1] This article presents an analysis of the spatiotemporal changes (1960–2100) in temperature and precipitation extremes of a typical arid zone (i.e., the Tarim River Basin) in Central Asia. The latest observations in the past five decades (1960–2009) and Coupled General Circulation Model (CGCM) multimodel ensemble projections (2010–2100) using the Bayesian Model Average (BMA) approach are employed for analysis in this study. Results indicate: (1) Most warm (cold) extreme temperature indices have shown significantly positive (negative) trends in the Tarim River Basin in past five decades, while only slight changes in precipitation extremes can be observed. From the spatial perspective, more significantly warm (cold) extremes are found in the desert zones than in upstream mountain zones (i.e., the Tian Shan Mountain and Kunlun Mountain systems which surround the basin). Whereas, there are no identical spatial patterns for the change in extreme precipitation; (2) Ensemble of five CGCM models in Phase 3 of the Coupled Model Intercomparison Project (CMIP3) based on the BMA method suggests that the increasing consecutive dry days (CDD), together with the decreasing frost day (FD) and increasing warm nights frequency (TN90) may lead to more frequent droughts in Tarim in future. Meanwhile, slight increase of annual count of days with precipitation of more than 10 mm (R10), maximum 5-day precipitation total (R5D), simple daily intensity index (SDII), and annual total precipitation with precipitation >95th percentile (R95) in projections indicate a probability of flood occurrence in summer together with frequent occurrence of droughts. The results can provide beneficial reference to water resource and eco-environment management strategies in arid zones for associated policymakers and stakeholders.

Multi-model ensemble projections in temperature and precipitation extremes of the Tibetan Plateau in the 21st century

Projections of changes in climate extreme are important in assessing the potential impacts of climate change on social and natural systems. This article presents future projections of climate extremes in the Tibetan Plateau constructed from ensembles of coupled general circulation models (CGCMs) contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), under a range of emission scenarios. The extremes of temperature and precipitation are described by seven indices, namely, the frost day (FD), percentage of nights when T min > 90th percentile (TN90), consecutive dry days (CDD), annual count of days when precipitation >=10 mm (R10), maximum 5-day precipitation total (R5D), simple daily intensity index (SDII), and annual total precipitation when precipitation > 95th percentile (R95T). Results indicate that frost days decrease over the Tibetan Plateau in the 21st century. More frequent warm nights are also projected in the plateau. The increases of these temperature extremes under A2 and A1B scenarios are more pronounced than under B1. Heavy precipitation events for single days and pentads are projected to increase in their intensity over most parts of Tibetan Plateau. CDD, R10, R5D, R95T and SDII collectively suggest more extreme precipitation in the region (2011–2020). In addition, impacts of climate extremes changes on local water resources and fragile ecosystem are discussed as an extension of this article. The findings will be beneficial to project regional responses in this unique region to global climate change, and then to formulate regional strategies against the potential menaces of climate change.

A multimodel comparison of centennial Atlantic meridional overturning circulation variability

A mechanism contributing to centennial variability of the Atlantic Meridional Overturning Circulation (AMOC) is tested with multi-millennial control simulations of several coupled general circulation models (CGCMs). These are a substantially extended integration of the 3rd Hadley Centre Coupled Climate Model (HadCM3), the Kiel Climate Model (KCM), and the Max Plank Institute Earth System Model (MPI-ESM). Significant AMOC variability on time scales of around 100 years is simulated in these models. The centennial mechanism links changes in the strength of the AMOC with oceanic salinities and surface temperatures, and atmospheric phenomena such as the Intertropical Convergence Zone (ITCZ). 2 of the 3 models reproduce all aspects of the mechanism, with the third (MPI-ESM) reproducing most of them. A comparison with a high resolution paleo-proxy for Sea Surface Temperatures (SSTs) north of Iceland over the last 4,000 years, also linked to the ITCZ, suggests that elements of this mechanism may also be detectable in the real world.

Predictability of western North Pacific typhoon activity and its factors using DEMETER coupled models

Climate prediction using a coupled model with a one-tier scheme is an important research direction. In this study, based on 1974–2001 hindcasts obtained from the “Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction” (DEMETER) project, the capability of coupled general circulation models (CGCMs) to predict six climatic factors that have a close relationship with the western North Pacific typhoon activity is investigated over summer (June–October). Results indicate that all six DEMETER CGCMs well predict the six factors. Using the statistical relationship between these six factors and the typhoon frequency, the ability of the CGCMs to predict typhoon frequency is further explored. It is found that the six CGCMs also well predict the variability in typhoon frequency. Comparison analysis shows that the prediction skill of the statistical downscaling method is much better than that of the raw CGCMs. In addition, the six-model ensemble has the best prediction performance. This study suggests that combining a multi-model ensemble and statistical downscaling greatly improves the CGCM prediction skill, and will be an important research direction for typhoon prediction.

Effects of Tropical Cyclones on Ocean Heat Transport in a High-Resolution Coupled General Circulation Model

Abstract In this paper the interplay between tropical cyclones (TCs) and the Northern Hemispheric ocean heat transport (OHT) is investigated. In particular, results from a numerical simulation of the twentieth-century and twenty-first-century climates, following the Intergovernmental Panel on Climate Change (IPCC) twentieth-century run (20C3M) and A1B scenario protocols, respectively, have been analyzed. The numerical simulations have been performed using a state-of-the-art global atmosphere–ocean–sea ice coupled general circulation model (CGCM) with relatively high-resolution (T159) in the atmosphere. The CGCM skill in reproducing a realistic TC climatology has been assessed by comparing the model results from the simulation of the twentieth century with available observations. The model simulates tropical cyclone–like vortices with many features similar to the observed TCs. Specifically, the simulated TCs exhibit realistic structure, geographical distribution, and interannual variability, indicating that the model is able to capture the basic mechanisms linking the TC activity with the large-scale circulation. The cooling of the surface ocean observed in correspondence of the TCs is well simulated by the model. TC activity is shown to significantly increase the poleward OHT out of the tropics and decrease the poleward OHT from the deep tropics on short time scales. This effect, investigated by looking at the 100 most intense Northern Hemisphere TCs, is strongly correlated with the TC-induced momentum flux at the ocean surface, where the winds associated with the TCs significantly weaken (strengthen) the trade winds in the 5°–18°N (18°–30°N) latitude belt. However, the induced perturbation does not impact the yearly averaged OHT. The frequency and intensity of the TCs appear to be substantially stationary through the entire 1950–2069 simulated period, as does the effect of the TCs on the OHT.

Sea Surface Temperature Biases under the Stratus Cloud Deck in the Southeast Pacific Ocean in 19 IPCC AR4 Coupled General Circulation Models

Abstract This study examines systematic biases in sea surface temperature (SST) under the stratus cloud deck in the southeast Pacific Ocean and upper-ocean processes relevant to the SST biases in 19 coupled general circulation models (CGCMs) participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The 20 years of simulations from each model are analyzed. Pronounced warm SST biases in a large portion of the southeast Pacific stratus region are found in all models. Processes that could contribute to the SST biases are examined in detail based on the computation of major terms in the upper-ocean heat budget. Negative biases in net surface heat fluxes are evident in most of the models, suggesting that the cause of the warm SST biases in models is not explained by errors in net surface heat fluxes. Biases in heat transport by Ekman currents largely contribute to the warm SST biases both near the coast and the open ocean. In the coastal area, southwestward Ekman currents and upwelling in most models are much weaker than observed owing to weaker alongshore winds, resulting in insufficient advection of cold water from the coast. In the open ocean, warm advection due to Ekman currents is overestimated in models because of the larger meridional temperature gradient, the smaller zonal temperature gradient, and overly weaker Ekman currents.