Simulated Sea Surface Temperature Research Articles

Response of the equatorial basin‐wide SST to non‐breaking surface wave‐induced mixing in a climate model: An amendment to tropical bias

One of the common problems of the coupled atmosphere‐ocean general circulation models (AOGCMs) without flux correction is that the simulated sea surface temperature (SST) deviates noticeably from the observation especially in the tropics, such as the too cold tongue in the eastern Pacific and a reversed SST zonal gradient in the equatorial Atlantic. The coupled atmosphere‐wave‐ocean general circulation model, which incorporates the non‐breaking surface wave‐induced mixing into the CCSM3 through a coupler, can improve the simulation of the tropical SST. On the ocean‐basin scale, the wave‐induced vertical mixing can generate “West‐Positive and East‐Negative” pattern for the equatorial SST that much alleviates the tropical bias. The formation mechanism for this basin‐wide response to the wave‐induced mixing is analyzed through sensitive experiments of AOGCMs and stand‐alone ocean general circulation models (OGCMs). First, in each basin, the SST becomes colder under the direct effect of the wave‐induced mixing, and the SST in the eastern part of each basin is colder due to the shallower ocean mixed layer than that of the western part. The SST in the western basin (or central basin in the Pacific Ocean) increases due to the weakened eastward zonal current. Then, the pattern of warm SST in the west and cold SST in the east is amplified due to the Bjernkes feedback in a climate system. The net heat flux feedback plays a negative role in this kind of SST response.

Assessment of 1 month forecasts of weak Indian monsoons based on the NCEP Climate Forecast System (CFS)

AbstractThis study focuses on analyses and validation of 1 month forecasts (OMFs) of weak Indian monsoons based on 10 member ensemble hindcasts (retrospective forecasts) of the NCEP Climate Forecast System (CFS) model for the period 1981–2008. The weak monsoon episodes chosen for the analysis correspond to summer monsoon months which were characterized by significant deficits in the All‐India monthly rainfall of − 20% of the climatological normal. Examination of the CFS‐OMFs shows poor skill of the model in capturing the observed rainfall and circulation anomalies during weak monsoons. The present analysis suggests that deficiencies in realistically capturing the ocean‐atmosphere coupling in the tropical Indian Ocean (IO) introduces biases in simulating sea surface temperature and rainfall anomalies in the equatorial region, which in turn affects the monsoon precipitation forecasts over the sub‐continent. In particular, the mean thermocline in the near‐equatorial IO is found to be practically flat in the CFS model, so that the near‐equatorial anomalies in the model are not strong enough to weaken the summer monsoon circulation and reduce the monsoon precipitation over India. By examining a 100 year free run of the CFS model, it is seen that moderate monsoon‐droughts simulated by the model have weak teleconnections with the equatorial IO dynamics. On the other hand, intense monsoon‐droughts in the CFS‐model are found be remarkably linked with the equatorial IO anomalies. It is suggested that improving the slope of the equatorial IO thermocline and allowing for more realistic IO‐monsoon coupling in the CFS‐model would be an important step for improving the skill of extended‐range monsoon forecasts. Copyright © 2012 Royal Meteorological Society

How good are the simulations of tropical SST–rainfall relationship by IPCC AR4 atmospheric and coupled models?

The failure of atmospheric general circulation models (AGCMs) forced by prescribed SST to simulate and predict the interannual variability of Indian/Asian monsoon has been widely attributed to their inability to reproduce the actual sea surface temperature (SST)-rainfall relationship in the warm Indo-Pacific oceans. This assessment is based on a comparison of the observed and simulated correlation between the rainfall and local SST. However, the observed SSTconvection/rainfall relationship is nonlinear and for this a linear measure such as the correlation is not an appropriate measure. We show that the SST-rainfall relationship simulated by atmospheric and coupled general circulation models in IPCC AR4 is nonlinear, as observed, and realistic over the tropical West Pacific (WPO) and the Indian Ocean (IO). The SST-rainfall pattern simulated by the coupled versions of these models is rather similar to that from the corresponding atmospheric one, except for a shift of the entire pattern to colder/warmer SSTs when there is a cold/warm bias in the coupled version.

Pre-industrial and mid-Pliocene simulations with NorESM-L

Abstract. The mid-Pliocene period (3.3 to 3.0 Ma) is known as a warm climate with atmospheric greenhouse gas levels similar to the present. As the climate at this time was in equilibrium with the greenhouse forcing, it is a valuable test case to better understand the long-term response to high levels of atmospheric greenhouse gases. In this study, we use the low resolution version of the Norwegian Earth System Model (NorESM-L) to simulate the pre-industrial and the mid-Pliocene climate. Comparison of the simulation with observations demonstrates that NorESM-L simulates a realistic pre-industrial climate. The simulated mid-Pliocene global mean surface air temperature is 16.7 °C, which is 3.2 °C warmer than the pre-industrial. The simulated mid-Pliocene global mean sea surface temperature is 19.1 °C, which is 2.0 °C warmer than the pre-industrial. The warming is relatively uniform globally, except for a strong amplification at high latitudes.

Towards seasonal prediction of the distribution and extent of cold bottom waters on the Bering Sea shelf

A coupled sea ice–ocean model, combined with observational and reanalysis data, is used to explore the seasonal predictability of the distribution and extent of cold bottom waters on the Bering Sea shelf through numerical simulations or statistical analyses. The model captures the spatiotemporal variability of trawl survey observations of bottom water temperature over the period 1970–2009. Of the various winter air–ice–ocean parameters considered, the interannual variability of the winter on-shelf heat transport across the Bering Sea shelf break, dominated by changes in ocean flow, is most highly correlated with the interannual variability of the bottom layer properties (bottom temperature, and the distribution and extent of cold bottom waters) in spring–summer. This suggests that the winter heat transport may be the best seasonal predictor of the bottom layer properties. To varying degrees, the winter mean simulated sea surface temperature (SST), National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis surface air temperature (SAT), simulated and observed sea ice extent, the Bering Strait outflow, and the Pacific Decadal Oscillation are also significantly correlated with the spring–summer bottom layer properties. This suggests that, with varying skill, they may also be useful for statistical seasonal predictions. Good agreement between observations and results of the coupled ice–ocean model suggests also the possibility of numerical seasonal predictions of the bottom layer properties. The simulated field of bottom layer temperature on the Bering Sea shelf on 31 May is a good predictor of the distribution and extent of cold bottom waters throughout late spring and summer. These variables, both in the model and in reality, do not change significantly from June to October, primarily owing to increased upper ocean stratification in late spring due to ice melt and surface warming, which tends to isolate and preserve the cold bottom waters on the shelf. However, the ocean stratification, and hence the isolation effect, is stronger in cold years than in warm years because more ice is available for melting in spring–summer.

Altimeter data assimilation in the tropical Indian Ocean using water property conserving scheme

Altimeter data have been assimilated in an ocean general circulation model using the water property conserving scheme. Two runs of the model have been conducted for the year 2004. In one of the runs, altimeter data have been assimilated sequentially, while in another run, assimilation has been suppressed. Assimilation has been restricted to the tropical Indian Ocean. An assessment of the strength of the scheme has been carried out by comparing the sea surface temperature (SST), simulated in the two runs, with in situ derived as well as remotely sensed observations of the same quantity. It has been found that the assimilation exhibits a significant positive impact on the simulation of SST. The subsurface effect of the assimilation could be judged by comparing the model simulated depth of the 20°C isotherm (hereafter referred to as D20), as a proxy of the thermocline depth, with the same quantity estimated from ARGO observations. In this case also, the impact is noteworthy. Effect on the dynamics has been judged by comparison of simulated surface current with observed current at a moored buoy location, and finally the impact on model sea level forecast in a free run after assimilation has been quantified in a representative example.

Analysis of Local Air–Sea Interaction in East Asia Using a Regional Air–Sea Coupled Model

Abstract A regional air–sea coupled climate model based on the third regional climate model (RegCM3) and the regional oceanic model [the Princeton Ocean Model (POM)] is used to analyze the local air–sea interaction over East Asia in this study. The results indicate that the simulated sea surface temperature (SST) of the coupled model RegCM3–POM is reasonably accurate, and that the spatial pattern and temporal variation are consistent with that of the Global Sea Ice and Sea Surface Temperature dataset (GISST). The correlation between the SST and the atmospheric variables shows that the uncoupled model RegCM3 forced by the given SST cannot reproduce the real-time and SST lag correlation between SST and precipitation, and between SST and surface wind speed, whereas the relationship in the coupled model RegCM3–POM is reasonably accurate. RegCM3–POM reflects the air–sea interaction in the South China Sea and western Pacific Ocean, where the SST lead correlation is the inverse of the SST lag correlation between SST and precipitation, and strong winds bring warm water to the midlatitudes, so the correlation between wind speed and SST is negative in low latitudes and positive in the Kuroshio area. The uncoupled model fails to reproduce the effect of the atmosphere on the ocean. The further study on air–sea interaction in the South China Sea indicates that the earlier warm seawater corresponds to strong sensible heat flux, evaporation, precipitation, and weak net solar radiation, and the early strong sensible heat flux, evaporation, wind at the 10-m level, and weak net solar radiation cause the cold SST.

A New Ocean Mixed-Layer Model Coupled into WRF

A new mesoscale air-sea coupled model (WRFOMLM-Noh) was constructed based on the Weather Research and Forecasting (WRF) model and an improved Mellor-Yamada ocean mixed-layer model from Noh and Kim (OMLM-Noh). Through off-line tests and a simulation of a real typhoon, the authors compared the performance of the WRF-OMLM-Noh with another existing ocean mixed-layer coupled model (WRF-OMLM-Pollard). In the off-line tests with Tropical Ocean Global Atmosphere Program’s Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) observational data, the results show that OMLM-Noh is better able to simulate sea surface temperature (SST) variational trends than OMLM-Pollard. Moreover, OMLM-Noh can sufficiently reproduce the diurnal cycle of SST. Regarding the typhoon case study, SST cooling due to wind-driven ocean mixing is underestimated in WRF-OMLM-Pollard, which artificially increases the intensity of the typhoon due to more simulated air-sea heat fluxes. Compared to the WRFOMLM-Pollard, the performance of WRF-OMLM-Noh is superior in terms of both the spatial distribution and temporal variation of SST and air-sea heat fluxes.

A New Global Climate Model of the Meteorological Research Institute: MRI-CGCM3 —Model Description and Basic Performance—

A new global climate model, MRI-CGCM3, has been developed at the Meteorological Research Institute (MRI). This model is an overall upgrade of MRI’s former climate model MRI-CGCM2 series. MRI-CGCM3 is composed of atmosphere-land, aerosol, and ocean-ice models, and is a subset of the MRI’s earth system model MRI-ESM1. Atmospheric component MRI-AGCM3 is interactively coupled with aerosol model to represent direct and indirect effects of aerosols with a new cloud microphysics scheme. Basic experiments for pre-industrial control, historical and climate sensitivity are performed with MRI-CGCM3. In the pre-industrial control experiment, the model exhibits very stable behavior without climatic drifts, at least in the radiation budget, the temperature near the surface and the major indices of ocean circulations. The sea surface temperature (SST) drift is sufficiently small, while there is a 1 W m-2 heating imbalance at the surface. The model’s climate sensitivity is estimated to be 2.11 K with Gregory’s method. The transient climate response (TCR) to 1 % yr-1 increase of carbon dioxide (CO2) concentration is 1.6 K with doubling of CO2 concentration and 4.1 K with quadrupling of CO2 concentration. The simulated present-day mean climate in the historical experiment is evaluated by comparison with observations, including reanalysis. The model reproduces the overall mean climate, including seasonal variation in various aspects in the atmosphere and the oceans. Variability in the simulated climate is also evaluated and is found to be realistic, including El Niño and Southern Oscillation and the Arctic and Antarctic oscillations. However, some important issues are identified. The simulated SST indicates generally cold bias in the Northern Hemisphere (NH) and warm bias in the Southern Hemisphere (SH), and the simulated sea ice expands excessively in the North Atlantic in winter. A double ITCZ also appears in the tropical Pacific, particularly in the austral summer.

Effects of Initial and Boundary Conditions of Mesoscale Models on Simulated Atmospheric Refractivity

AbstractRadar ducting is caused by sharp vertical changes in temperature and, especially, water vapor at the top of the atmospheric boundary layer, both of which are sensitive to variations in the underlying surface conditions, local mesoscale weather, and synoptic weather patterns. High-resolution numerical weather prediction (NWP) models offer an alternative to observation to determine boundary layer (BL) structure and to assess the spatial variability of radar ducts. The benefit of using NWP models for simulating ducting conditions very much depends on the initial state of sea surface temperature (SST) and the model spinup time, both of which have a great impact on BL structure. This study investigates the effects of variation of NWP-model initial conditions and simulation length on the accuracy of simulating the atmosphere’s refractive index over the Wallops Island, Virginia, region, which has pronounced SST variability and complex BL structure. The Met Office Unified Model (MetUM) with horizontal resolution of 4 km (4-km model) was used to simulate the atmospheric environment when observations were made during the Wallops-2000 experiment. Sensitivity tests were conducted in terms of the variability of SST and model spinup time. The evaluation of the model results was focused on low-level moisture, temperature, and surface ducting characteristics including the frequency, strength, and the height of the ducting layer. When provided with more accurate SST and adequate simulation length, the MetUM 4-km model demonstrated an improved ability to predict the observed ducting.

Temporal and Spatial Variability in the Distribution of Vibrio vulnificus in the Chesapeake Bay: A Hindcast Study

Vibrio vulnificus, an estuarine bacterium, is the causative agent of seafood-related gastroenteritis, primary septicemia, and wound infections worldwide. It occurs as part of the normal microflora of coastal marine environments and can be isolated from water, sediment, and oysters. Hindcast prediction was undertaken to determine spatial and temporal variability in the likelihood of occurrence of V. vulnificus in surface waters of the Chesapeake Bay. Hindcast predictions were achieved by forcing a multivariate habitat suitability model with simulated sea surface temperature and salinity in the Bay for the period between 1991 and 2005 and the potential hotspots of occurrence of V. vulnificus in the Chesapeake Bay were identified. The likelihood of occurrence of V. vulnificus during high and low rainfall years was analyzed. From results of the study, it is concluded that hindcast prediction yields an improved understanding of environmental conditions associated with occurrence of V. vulnificus in the Chesapeake Bay.

Sensitivity of a regional ocean-atmosphere coupled model to convection parameterization over western North Pacific

[1] With the motivation to improve the simulation of western North Pacific (WNP) summer monsoon, the regional climate model RegCM3 is coupled with the Princeton ocean model (POM2000) through the coupler OASIS3.0 (Ocean Atmosphere Sea Ice Soil 3.0). The performance of the regional ocean-atmosphere coupled model (hereafter ROAM) is assessed by doing case simulation of the 1998 summer monsoon. The cold bias of simulated sea surface temperature (SST) is evident as previous ROAM simulations over the Asian-Australian summer monsoon region. Five sets of sensitivity experiments with convection suppression criterion based on the averaged relative humidity from cloud base to cloud top are designed to improve the performance of ROAM. The results show that the column-averaged cloud fraction is reduced in convection suppression experiments. A reduction of column-averaged cloud cover, which is dominated by the decrease of convective cloud cover, increases the solar shortwave radiation reaching in sea surface, then warms the SST. A reduction of convective rainfall is followed by an increase of large-scale rainfall which results from increasing cloud water. When the critical value is set to 0.70, the rainfall is partly improved in terms of the spatial distribution and root-mean-square error. The percentage of convective rainfall over WNP is also improved. The authors show evidence that the SST cold biases, which are evident in many regional ocean-atmosphere coupled models in the Asian-Australian summer monsoon region, may partly stem from the overestimation of convection frequency by the atmospheric model.

A coupled climate model simulation of Marine Isotope Stage 3 stadial climate

Abstract. We present a coupled global climate model (CGCM) simulation, integrated for 1500 yr to quasi-equilibrium, of a stadial (cold period) within Marine Isotope Stage 3 (MIS 3). The simulated Greenland stadial 12 (GS12; ~44 ka BP) annual global mean surface temperature (Ts) is 5.5 °C lower than in the simulated recent past (RP) climate and 1.3 °C higher than in the simulated Last Glacial Maximum (LGM; 21 ka BP) climate. The simulated GS12 is evaluated against proxy data and previous modelling studies of MIS3 stadial climate. We show that the simulated MIS 3 climate, and hence conclusions drawn regarding the dynamics of this climate, is highly model-dependent. The main findings are: (i) Proxy sea surface temperatures (SSTs) are higher than simulated SSTs in the central North Atlantic, in contrast to earlier simulations of MIS 3 stadial climate in which proxy SSTs were found to be lower than simulated SST. (ii) The Atlantic Meridional Overturning Circulation (AMOC) slows down by 50 % in the GS12 climate as compared to the RP climate. This slowdown is attained without freshwater forcing in the North Atlantic region, a method used in other studies to force an AMOC shutdown. (iii) El-Niño-Southern Oscillation (ENSO) teleconnections in mean sea level pressure (MSLP) are significantly modified by GS12 and LGM forcing and boundary conditions. (iv) Both the mean state and variability of the simulated GS12 is dependent on the equilibration. The annual global mean Ts only changes by 0.10 °C from model years 500–599 to the last century of the simulation, indicating that the climate system may be close to equilibrium already after 500 yr of integration. However, significant regional differences between the last century of the simulation and model years 500–599 exist. Further, the difference between simulated and proxy SST is reduced from model years 500–599 to the last century of the simulation. The results of the ENSO variability analysis is also shown to depend on the equilibration.

Key factors in simulating the equatorial Atlantic zonal sea surface temperature gradient in a coupled general circulation model

Causes of the coupled model bias in simulating the zonal sea surface temperature (SST) gradient in the equatorial Atlantic are examined in three versions of the same coupled general circulation model (CGCM) differing only in the cumulus convection scheme. One version of the CGCM successfully simulates the mean zonal SST gradient of the equatorial Atlantic, in contrast to the failure of the Coupled Model Intercomparison Project phase 3 models. The present analysis shows that key factors to be successful are high skills in simulating the meridional location of the Intertropical Convergence Zone, the precipitation over northern South America, and the southerly winds along the west coast of Africa associated with the West African monsoon in boreal spring. Model biases in the Pacific contribute to the weaker precipitation over northern South America. Uncoupled experiments with the atmospheric component further confirm the importance of remote influences on the development of the equatorial Atlantic bias. Key Points: The zonal SST gradient of the equatorial Atlantic is well simulated in a CGCM; Key factors for the realistic simulation of the Atlantic SST are presented; Remote forcing from the Pacific may contribute to the Atlantic SST bias

Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases

The Arabian Sea is an important moisture source for Indian monsoon rainfall. The skill of climate models in simulating the monsoon and its variability varies widely, while Arabian Sea cold sea surface temperature (SST) biases are common in coupled models and may therefore influence the monsoon and its sensitivity to climate change. We examine the relationship between monsoon rainfall, moisture fluxes and Arabian Sea SST in observations and climate model simulations. Observational analysis shows strong monsoons depend on moisture fluxes across the Arabian Sea, however detecting consistent signals with contemporaneous summer SST anomalies is complicated in the observed system by air/sea coupling and large-scale induced variability such as the El Nino-Southern Oscillation feeding back onto the monsoon through development of the Somali Jet. Comparison of HadGEM3 coupled and atmosphere-only configurations suggests coupled model cold SST biases significantly reduce monsoon rainfall. Idealised atmosphere-only experiments show that the weakened monsoon can be mainly attributed to systematic Arabian Sea cold SST biases during summer and their impact on the monsoon-moisture relationship. The impact of large cold SST biases on atmospheric moisture content over the Arabian Sea, and also the subsequent reduced latent heat release over India, dominates over any enhancement in the land-sea temperature gradient and results in changes to the mean state. We hypothesize that a cold base state will result in underestimation of the impact of larger projected Arabian Sea SST changes in future climate, suggesting that Arabian Sea biases should be a clear target for model development.

Simulation of sea surface temperature changes in the Middle Pliocene warm period and comparison with reconstructions

The Middle Pliocene (ca 3.12–2.97 Ma) is a recent warm period in the Earth’s history. In many respects, the warmth of the Middle Pliocene is similar to the probable warm situation of the late 21st century predicted by climate models. Understanding the Middle Pliocene climate is important in predicting the future climate with global warming. Here, we used the latest reconstructions for the Middle Pliocene—Pliocene Research Interpretation and Synoptic Mapping (PRISM) version 3—to simulate the Middle Pliocene climate with a fully coupled model Fast Ocean Atmosphere Model. From comparison of the results of simulations with reconstructions, we considered two important scientific topics of Middle Pliocene climate modeling: extreme warming in the subpolar North Atlantic and a permanent El Niño in the tropical Pacific. Our simulations illustrate that the global annual mean sea surface temperature (SST) in the Middle Pliocene was about 2.3°C higher than that in the pre-industrial era. The warming was stronger at mid- and high latitudes than at low latitudes. The simulated SST changes agree with SST reconstructions in PRISM3 data, especially for the North Atlantic, North Pacific and west coast of South America. However, there were still discrepancies between the simulation of the SST and reconstructions for the subpolar North Atlantic and tropical Pacific. In the case of the Atlantic, the weakened meridional overturning circulation in the simulation did not support the reconstruction of the extremely warm condition in the subpolar North Atlantic. In the case of the tropical Pacific, the whole ocean warmed, especially the eastern tropical Pacific, which did not support the permanent El Niño suggested by the reconstruction. From evaluation of the modeling and reconstruction, we suggest that the above discrepancies were due to uncertainties in reconstructions, difficulties in paleoclimate modeling and deficiencies of climate models. The discrepancies should be reduced through consideration of both the modeling and data.

Effects of Relative and Absolute Sea Surface Temperature on Tropical Cyclone Potential Intensity Using a Single-Column Model

Abstract The effects of relative and absolute sea surface temperature (SST) on tropical cyclone potential intensity are investigated using the Massachusetts Institute of Technology (MIT) single-column model. The model is run in two modes: (i) radiative–convective equilibrium (RCE) to represent the convective response to uniform warming of the ocean as in a homogeneous aqua planet, and (ii) weak temperature gradient (WTG) to represent the convective response to warming over a limited area of ocean while the SST outside that area remains unchanged. The WTG calculations are taken to represent the sensitivity of the atmospheric state to relative SST changes, while the RCE calculations are taken to represent the sensitivity to absolute SST changes occurring in the absence of relative SST changes. The potential intensity is computed using temperature and moisture profiles from the two sets of experiments for various values of SST. The computed potential intensity is more sensitive to relative SST than to absolute SST, with slopes of between about 7 and 8 m s−1 °C−1 (depending on choice of input parameters in the model’s convection scheme and other details of the model configuration) in the WTG calculations and about 1 m s−1 °C−1 in RCE. The sensitivity to relative SST obtained from these calculations is quantitatively similar to that obtained previously by G. Vecchi and B. J. Soden from global climate model output. The greater sensitivity of potential intensity to SST in the WTG simulations (relative to RCE) can be attributed primarily to larger changes in the air–sea thermodynamic disequilibrium in those calculations as SST changes, which results from the inability of the free troposphere to adjust to the SST in WTG as it does in RCE.

Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

Accelerated warming of the Southern Ocean and its impacts on the hydrological cycle and sea ice

The observed sea surface temperature in the Southern Ocean shows a substantial warming trend for the second half of the 20th century. Associated with the warming, there has been an enhanced atmospheric hydrological cycle in the Southern Ocean that results in an increase of the Antarctic sea ice for the past three decades through the reduced upward ocean heat transport and increased snowfall. The simulated sea surface temperature variability from two global coupled climate models for the second half of the 20th century is dominated by natural internal variability associated with the Antarctic Oscillation, suggesting that the models' internal variability is too strong, leading to a response to anthropogenic forcing that is too weak. With increased loading of greenhouse gases in the atmosphere through the 21st century, the models show an accelerated warming in the Southern Ocean, and indicate that anthropogenic forcing exceeds natural internal variability. The increased heating from below (ocean) and above (atmosphere) and increased liquid precipitation associated with the enhanced hydrological cycle results in a projected decline of the Antarctic sea ice.

Response of the eastern subtropical Atlantic SST to Saharan dust: A modeling and observational study

Retrievals of aerosol optical depth (AOD) from MODIS, and of sea surface temperature (SST) from TMI are analyzed jointly with the output of a numerical model for the period 2000–2006 to determine the impact of Saharan dust on the eastern subtropical North Atlantic SST. Simultaneously with, or shortly after strong dust outbreaks, a decrease in SST of 0.2° to 0.4°C can be observed in the microwave SST data set, which is consistent with an independent estimate of SST decrease simulated here by a local mixed layer model. However, low wind conditions and a shallow mixed layer are required to reach this response, and it is therefore unlikely that a clear response of SST to dust lasting more than a few days can be seen in the microwave SST observations. An inspection of microwave SST observations suggests that about 30% of SST variance could be explained by dust‐induced cooling in our study region that is not represented in existing AVHRR SST fields nor represented in reanalysis centers‐provided surface heat fluxes. On longer time scales, a comparison between observed SST fields and simulated SST, using an eddy‐permitting model of the North Atlantic, suggests a cooling of about 0.5°C on the local SST on sub‐seasonal to interannual time scales which is significantly correlated and consistent with a dust‐induced cooling. However, while supportive of the hypothesis that Saharan dust lead to a reduction in SST, the eddy‐resolving model results are not by themselves conclusive. Moreover, the effects of dust‐induced cooling on simulations of the ocean circulation, on atmospheric forecasts and on climate simulations remains to be investigated in future studies.