Influence Of Sea Surface Temperature Research Articles

Influence of the Amazon/Orinoco Plume on the summertime Atlantic climate

A plume of fresh water forms in the Atlantic due to discharge from the Amazon and Orinoco rivers and creates a stable barrier layer near the surface that is associated with warm sea surface temperature anomalies (SSTAs). The boreal summer atmospheric response to this sea surface temperature (SST) forcing is investigated using a regional atmospheric model. Results from two ensembles, one with the plume SSTA removed, and the other with an idealized plume SSTA imposed, reveal that the scale of the SSTA forcing is large enough to influence the summer climate over the tropical western Atlantic and Central America. Rainfall increases over the SSTAs and downstream over the Caribbean Sea and Central America, as sensible and latent heating associated with the plume SSTAs force a Rossby/Kelvin wave dynamical response. The result is westward shift by 12° of longitude of the North Atlantic subtropical anticyclone, a northward repositioning of the summertime subtropical anticyclone extension over the Gulf of Mexico, and increased moisture convergence into Central America. Warm SSTAs associated with the plume also influence simulated summer tropical Atlantic storms. The presence of the plume increases the number of Atlantic basin storms by 60% (i.e., 4.66 more storms). An increase in storm intensity also occurs, with a 61% increase of the number of storms that reach tropical storm and hurricane strength. However, these storms tend to be shorter lived and are associated with a 12% decrease in the number of tropical storm days. Storm trajectories also shift westward over the western Atlantic associated with the presence of the plume, bringing them closer to the U.S. coast as both the steering winds and vertical wind shear over the Atlantic are modified. These results suggest that the August storm systems may be more likely to track closer to the U.S. coast and/or over the Gulf of Mexico. Since the Amazon and Orinoco rivers are fed primarily by rainfall in the Amazon Basin during austral summer, the influence of the plume SSTs on Atlantic climate is an example of interhemispheric forcing of climate variability across seasons.

Mechanisms of Tropical Atlantic SST Influence on North American Precipitation Variability*

Abstract The dynamical mechanisms associated with the impact of year-to-year variability in tropical North Atlantic (TNA) sea surface temperatures (SSTs) on North American precipitation, during the cold and warm halves of the hydrological year (October–September) are examined. Observations indicate that during both seasons warmer-than-normal TNA SSTs are associated with a reduction of precipitation over North America, mainly west of ∼90°W, and that the effect can be up to 30% of the year-to-year seasonal precipitation RMS variability. This finding confirms earlier studies with observations and models. During the cold season (October–March) the North American precipitation variability associated with TNA fluctuations is considerably weaker than its association with ENSO. During the warm season (April–September), however, the Atlantic influence, per one standard deviation of SST anomalies, is larger than that of ENSO. The observed association between TNA SST anomalies and global and North American precipitation and sea level pressure variability is compared with that found in the output of an atmospheric general circulation model (AGCM) forced with observed SST variability, both globally and in the tropical Atlantic alone. The similarity between model output and observations suggests that TNA SST variability is causal. The mechanisms of the “upstream” influence of the Atlantic on North American precipitation are seasonally dependent. In the warm season, warmer-than-normal TNA SSTs induce a local increase in atmospheric convection. This leads to a weakening of the North Atlantic subtropical anticyclone and a reduction in precipitation over the United States and northern Mexico, associated with the anomalous southward flow there. In the cold season, a response similar to the warm season over the subtropical Atlantic is identified, but there is also a concomitant suppression of convection over the equatorial Pacific, which leads to a weakening of the Aleutian low and subsidence over western North America, similar to the impact of La Niña although weaker in amplitude. The impact of TNA SST on tropical convection and the extratropical circulation is examined by a set of idealized experiments with a linear general circulation model forced with the tropical heating field derived from the full AGCM.

Can ocean acidification affect population dynamics of the barnacle Semibalanus balanoides at its southern range edge?

The global ocean and atmosphere are warming. There is increasing evidence suggesting that, in addition to other environmental factors, climate change is affecting species distributions and local population dynamics. Additionally, as a consequence of the growing levels of atmospheric carbon dioxide (CO2), the oceans are taking up increasing amounts of this CO2, causing ocean pH to decrease (ocean acidification). The relative impacts of ocean acidification on population dynamics have yet to be investigated, despite many studies indicating that there will be at least a sublethal impact on many marine organisms, particularly key calcifying organisms. Using empirical data, we forced a barnacle (Semibalanus balanoides) population model to investigate the relative influence of sea surface temperature (SST) and ocean acidification on a population nearing the southern limit of its geographic distribution. Hindcast models were compared to observational data from Cellar Beach (southwestern United Kingdom). Results indicate that a declining pH trend (-0.0017 unit/yr), indicative of ocean acidification over the past 50 years, does not cause an observable impact on the population abundance relative to changes caused by fluctuations in temperature. Below the critical temperature (here T(crit) = 13.1 degrees C), pH has a more significant affect on population dynamics at this southern range edge. However, above this value, SST has the overriding influence. At lower SST, a decrease in pH (according to the National Bureau of Standards, pHNBs) from 8.2 to 7.8 can significantly decrease the population abundance. The lethal impacts of ocean acidification observed in experiments on early life stages reduce cumulative survival by approximately 25%, which again will significantly alter the population level at this southern limit. Furthermore, forecast predictions from this model suggest that combined acidification and warming cause this local population to die out 10 years earlier than would occur if there was only global warming and no concomitant decrease in pH.

Multimodel Estimates of Atmospheric Response to Modes of SST Variability and Implications for Droughts

Abstract A set of idealized global model experiments was performed by several modeling centers as part of the Drought Working Group of the U.S. Climate Variability and Predictability component of the World Climate Research Programme (CLIVAR). The purpose of the experiments was to assess the role of the leading modes of sea surface temperature (SST) variability on the climate over the continents, with particular emphasis on the influence of SSTs on surface climate variability and droughts over the United States. An analysis based on several models gives more creditability to the results since it relies on the assessment of impacts that are robust across different models. Coordinated atmospheric general circulation model (AGCM) simulations forced with three modes of SST variability were analyzed. The results show that the SST-forced precipitation variability over the central United States is dominated by the SST mode with maximum loading in the central Pacific Ocean. The SST mode with loading in the Atlantic Ocean, and a mode that is dominated by trends in SSTs, lead to a smaller response. Based on the response to the idealized SSTs, the precipitation response for the twentieth century was also reconstructed. A comparison with the Atmospheric Model Intercomparison Project (AMIP) simulations forced with the observed SSTs illustrates that the reconstructed precipitation variability was similar to the one in the AMIP simulations, further supporting the conclusion that the SST modes identified in the present analysis play a dominant role in the precipitation variability over the United States. One notable exception is the Dust Bowl of the 1930s, and further analysis regarding this major climate extreme is discussed.

The relationship between multi-sensor satellite data and Bayesian estimates for skipjack tuna catches in the South Brazil Bight

In this study we tested a Bayesian model based on a conjugate gamma/Poisson pair associated with environmental variables derived from satellite data such as sea surface temperature (SST) and its derived gradient fields from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra, chlorophyll-a concentration from Sea Viewing Wide field of View Sensor (SEAWiFS)/SeaStar and surface winds and Ekman pumping from SeaWinds/Quick Scatterometer (QuikSCAT) to predict weekly catch estimates of the skipjack tuna in the South Brazil Bight. This was achieved by confronting the fishery data with model estimates and regressing the results on the satellite data. The fishery data were expressed by an index of catch per unit effort (CPUE) calculated as the weight of fish caught (in tonnes) by fishing week, and were divided into two series, called historical series (1996–1998; 2001), and validation year (2002). The output of model CPUE estimates is in good agreement with the historical weekly CPUE and generated updated weekly estimates that explained up to 62% of weekly CPUE from 2002. In general, the best proxy for the Bayesian weekly estimates is the gradient zonal SST field. The results refined previous knowledge of the influence of SST on the occurrence of skipjack tuna.

Statistical Analyses of Land–Atmosphere Feedbacks and Their Possible Pitfalls

Abstract In some regions of the world, soil moisture has a typical memory for atmospheric processes and can also feed back to the latter. Thus, a better understanding of feedbacks between soil moisture and the atmosphere could provide promising perspectives for increased seasonal predictability. Besides numerical simulations, statistical analysis of existing GCM simulations or observational data has been used to study such feedbacks. By referring to a recent statistical analysis of soil moisture–precipitation feedbacks in GCM simulations, the authors illustrate potential pitfalls of statistical approaches in this context: (i) most importantly, apparent soil moisture–precipitation feedbacks can often as well or even better be attributed to the influence of sea surface temperatures (SSTs) on precipitation and (ii) the discrepancy between different GCMs is large, which makes the aggregation of individual model results difficult. These aspects need to be carefully evaluated in statistical analyses of land–atmosphere coupling. Results for soil moisture–temperature feedbacks complement the precipitation analysis.

Influence of SST biases on future climate change projections

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977–1999 in the historical period and 2077–2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean–atmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.

North-Atlantic SST amplified recent wintertime European land temperature extremes and trends

Europe has been warming over the past 30 years. In particular all seasonal temperature records have been broken since 2003, which altered socio-economic and environmental systems. Since we expect this trend in both mean and extreme temperatures to continue along the twenty first century under enhanced radiative forcing, it is crucial to understand the underlying mechanisms of such climate variations to help in considering adaptation or mitigation strategies to reduce the impacts of a warmer climate. From a statistical analysis we show that the inter-annual variability of European seasonal temperatures can be reconstructed from North-Atlantic atmospheric circulation only, but not their recent trends and extreme seasons. Adding North-Atlantic sea-surface temperature (SST) as a predictor helps improving the reconstruction, especially in autumn and winter. Sensitivity experiments with the MM5 regional model over 2003–2007 suggest that the anomalous SST enhance European land temperatures through the upper-air advection of heat and water vapor, interacting with radiative fluxes over the continent. This mechanism is pronounced in autumn and winter, where estimates of SST influence as obtained from MM5 are in agreement with those obtained from statistical regressions. We find a lesser SST influence in spring and summer, where local surface and radiative feedbacks are the main amplifiers of recent extremes.

Identification of Pacific Ocean sea surface temperature influences of Upper Colorado River Basin snowpack

Given the importance of Upper Colorado River Basin (UCRB) snowpack as the primary driver of streamflow (water supply) for the southwestern United States, the identification of Pacific Ocean climatic drivers (e.g., sea surface temperature (SST) variability) may prove valuable in long‐lead‐time forecasting of snowpack in this critical region. Previous research efforts have identified El Niño–Southern Oscillation (ENSO) and Pacific Decadel Oscillation (PDO) as the main drivers for western U.S. snowpack, but these drivers have limited influence on regional (Utah and Colorado) UCRB snowpack. The current research applies for the first time the Singular Value Decomposition (SVD) statistical method to Pacific Ocean SSTs and continental U.S. snowpack to identify the primary Pacific Ocean climatic driver of UCRB snowpack. The use of SSTs eliminates any “bias” as to specific climate signals. The second mode of SVD identified a UCRB snowpack region (Colorado and Utah) and a corresponding Pacific Ocean SST region. A “non‐ENSO/non‐PDO” Pacific Ocean SST region between 34°N–24°S and 150°E–160°W was identified as being the primary driver of UCRB snowpack. To confirm the UCRB snowpack results, data from 13 unimpaired (or naturalized) streamflow gages in Colorado and Utah were used to evaluate and support the snowpack findings. Finally, a new and beneficial data set (western U.S. 1 March, 1 April, and 1 May snow water equivalent) was developed, which may be used in future research efforts.

Influence of SST Forcing on Stochastic Characteristics of Simulated Precipitation and Drought

Abstract Recent studies demonstrate that ocean–atmosphere forcing by persistent sea surface temperature (SST) anomalies is a primary driver of seasonal-to-interannual hydroclimatic variability, including drought events. Other studies, however, conclude that although SST anomalies influence the timing of drought events, their duration and magnitude over continental regions is largely governed by land–atmosphere feedbacks. Here the authors evaluate the direct influence of SST anomalies on the stochastic characteristics of precipitation and drought in two ensembles of AGCM simulations forced with observed (interannually varying) monthly SST and their climatological annual cycle, respectively. Results demonstrate that ocean–atmosphere forcing contributes to the magnitude and persistence of simulated seasonal precipitation anomalies throughout the tropics but over few mid- and high-latitude regions. Significant autocorrelation of simulated seasonal anomalies over oceans is directly forced by persistent SST anomalies; over land, SST anomalies are shown to enhance autocorrelation associated with land–atmosphere feedbacks. SST anomalies are shown to have no significant influence on simulated drought frequency, duration, or magnitude over most midlatitude land regions. Results suggest that severe and sustained drought events may occur in the absence of persistent SST forcing and support recent conclusions that ocean–atmosphere forcing primarily influences the timing of drought events, while duration and magnitude are governed by other mechanisms such as land–atmosphere feedbacks. Further analysis is needed to assess the potential model dependence of results and to quantify the relative contribution of land–atmosphere feedbacks to the long-term stochastic characteristics of precipitation and drought.

Influence of sea surface temperature on the European heat wave of 2003 summer. Part I: an observational study

The heat wave affecting Europe during summer of 2003 is analyzed in detail with observational and reanalysis data. Surface, middle and upper troposphere analysis reveal particular circulation patterns related to an atmospheric blocking condition. In general seasonal anomalies, like this intense heat wave, are strongly related to boundary conditions. Composites and empirical orthogonal functions analysis provide evidence for an organized structure in the sea surface temperature (SST) anomaly field: high SSTs in the Mediterranean basin, the North Sea and further north toward the Arctic Circle were observed mainly in the months of June and August. The outcome of this analysis on observational data shows the SST as one of the possible factors in enhancing the heat wave in the European area.

Influence of sea surface temperature on the European heat wave of 2003 summer. Part II: a modeling study

The Center for Ocean–Land–Atmosphere Studies Atmospheric General Circulation Model is used to investigate the role of global boundary conditions of sea surface temperature (SST) in the establishment and maintenance of the European heat wave of 2003 summer. It is found that the global SST anomalies can explain many major features of the European heat wave during the summer of 2003. A further experiment has investigated the role of SST outside the Mediterranean area. This supplements the results of a previous study where the role of warm Mediterranean SST was analyzed. The results suggest that the SST anomalies had an additional effect of reducing the baroclinicity in the European area reinforcing the blocking circulation and helping to create ideal conditions for the establishment of the heat wave.

Structural variation in genesis and landfall locations of North Atlantic tropical cyclones related to SST

The influence of sea surface temperature (SST) on the locations of the genesis and of landfall of tropical cyclones in the North Atlantic is analyzed. For that purpose, these locations are calculated from HURDAT and split into two disjoint subsets according to whether SST in the North Atlantic was above or below average in the year the corresponding storms occurred. Landfalls are investigated separately for the groups of cyclones categorized as tropical storms, minor hurricanes, or major hurricanes at the moment of landfall. The locations are considered realizations of inhomogeneous Poisson point processes, and the corresponding density functions are estimated with kernel estimation methods. In this way, any spatial structure inherent in the data is taken into account. These density functions are then compared with Monte Carlo methods from spatial statistics, which allows the detection of areas of statistically significant differences in the two sets with high and low SST, respectively. Results show many such areas, which is of relevance for the insurance industry and mathematical modelling of cyclones, as well as for decision support during the preparation for natural disasters.

Idealized SST anomaly regional climate model experiments: A note of caution

To date, a number of studies have focused on the influence of sea surface temperature (SST) on global and regional rainfall variability, with the majority of these focusing on certain ocean basins — eg, the Pacific, North Atlantic and Indian Ocean. In contrast, relatively less work has been done on the influence of the central South Atlantic, particularly in relation to rainfall over southern Africa. Previous work by the authors, using reanalysis data and general circulation model (GCM) experiments, has suggested that cold SST anomalies in the central southern Atlantic Ocean are linked to an increase in rainfall extremes across southern Africa. In this paper we present results from idealized regional climate model (RCM) experiments forced with both positive and negative SST anomalies in the southern Atlantic Ocean. These experiments reveal an unexpected response of rainfall over southern Africa. In particular, it was found that SST anomalies of opposite sign can cause similar rainfall responses in the model experiments, with isolated increases in rainfall over central southern Africa as well as a large region of drying over the Mozambique Channel. The purpose of this paper is to highlight this finding and explore explanations for the behaviour of the climate model. It is suggested that the observed changes in rainfall might result from the redistribution of energy (associated with upper-level changes to Rossby waves) or, of more concern, model error, and therefore the paper concludes that the results of idealized regional climate models forced with SST anomalies should be viewed cautiously.

Structural variation in genesis and landfall locations of North Atlantic tropical cyclones related to SST

The influence of sea surface temperature (SST) on the locations of the genesis and of landfall of tropical cyclones in the North Atlantic is analyzed. For that purpose, these locations are calculated from HURDAT and split into two disjoint subsets according to whether SST in the North Atlantic was above or below average in the year the corresponding storms occurred. Landfalls are investigated separately for the groups of cyclones categorized as tropical storms, minor hurricanes, or major hurricanes at the moment of landfall. The locations are considered realizations of inhomogeneous Poisson point processes, and the corresponding density functions are estimated with kernel estimation methods. In this way, any spatial structure inherent in the data is taken into account. These density functions are then compared with Monte Carlo methods from spatial statistics, which allows the detection of areas of statistically significant differences in the two sets with high and low SST, respectively. Results show many such areas, which is of relevance for the insurance industry and mathematical modelling of cyclones, as well as for decision support during the preparation for natural disasters.

Atmospheric Simulations Using OGCM-Assimilation SST: Influence of the Wintertime Japan Sea on Monthly Precipitation

Temperature data for the Japan Sea obtained from ocean data assimilation modeling is applied to atmospheric simulations of monthly precipitation for January 2005. Because the volume of flow of the Tsushima Warm Current was large during the winter season, the sea surface temperature (SST) and coastal precipitation were higher in comparison with those in 2003. In order to evaluate influence of SST on monthly precipitation, we use surface temperatures of the Japan Sea in 2003 and 2005 for comparative simulations of precipitation for January 2005. The precipitation in experiment C (using cool SST data in 2003) is smaller than that in experiment W (using warm SST data in 2005) in a large part of the sea area, since the small evaporation results from the low SST over the upstream area of northwesterly winter monsoon. In the domain of 33.67-45.82°N and 125.89-142.9°E, the averaged evaporation and precipitation in experiment C are 10% and 13% smaller than those in experiment W, respectively. About half of the difference between the precipitations observed for January 2003 and 2005 in a heavy snow area is equal to the difference between the two simulations. Our results show that the mesoscale SST difference between 2003 and 2005 is related to the local difference of monthly precipitation.

Evolution of Mesoscale Convective Systems and its Relationship with the Madden-Julian Oscillation in the Indo-Pacific Region

In this study we investigated the influence of sea surface temperature (SST) and Madden-Julian Oscillation (MJO) on the organization, strength, and distribution of Mesoscale Convective Systems (MCSs) over the Indo-Pacific region for understanding El Nino Southern Oscillation (ENSO). The study is based on the Tropical Rainfall Measuring Mission’s (TRMM) precipitation features dataset during boreal winters of 2001-02 to 2006-07. The results of time series of hot spot analyses show that MCSs are predominantly clustered in the Maritime Continent and West Pacific Regions, and are preferentially observed over ocean compared to land. The largest quantity of MCSs were observed to the south of the equator in January 2002, and the distribution of MCSs as a function of SST for these months peaked between 29-30° Celsius. MJO explains 11% to nearly 30% of the characteristics of MCSs in the Indo-Pacific. The percentage of MCSs over the ocean in January is larger when the MJO is in the active phase than the passive phase from the Indian Ocean to the West Pacific Region. The warm waters under the MCSs may be related to the coupled MJO process that convectively generate and maintain the storms. The effect of the MJO is strongest when it is located within the Maritime Continent region. The MJO analysis indicates that MCSs are more likely accompanied by westerly winds during the eastward propagation of the MJO and the westerly wind bursts have been linked to the onset of El Nino in the Pacific.

Effect of anomalous warming in the central Pacific on the Australian monsoon

The influence of sea surface temperature (SST) anomalies in the central Pacific Ocean on rainfall variability over Australia is investigated using observations and idealized simulations from an atmospheric general circulation model. We show that the SST warming centered at 180°W is associated with increased monsoon precipitation over northern Australia from January to February and a decrease in December and March over the same region, leading to a shorter and more intense monsoon period. In recent years SST anomalies commonly associated with El Niño events have often exhibited a peak signature in the central, not eastern, Pacific. These so‐called El Niño Modoki events are shown here to result in a markedly shorter and more intense Australian monsoon season.

Evidence for tropical SST influence on Antarctic polar atmospheric dynamics

A Singular Value Decomposition analysis is applied to climatological data to determine the modes of variability of monthly mean Sea Surface Temperature (SST) in the tropics coupled with the southern hemisphere stratospheric polar vortex intensity for the 1958 to 2006 period and to identify the tropical region strongly influencing the high latitude stratospheric dynamics. Two subsets of data have been considered by explicitly taking into account the phase of the Pacific Decadal Oscillation (PDO). The study evidences a shift of the tropical region affecting the polar vortex from the Western Pacific to the Indo‐Pacific Ocean, driven by the modulation of the SST pattern, due to the phase of the PDO. The analysis shows in both cases (years with positive/negative PDO phases) a high degree of correlation between an SST related index, calculated from NOAA/ERSST and HadISST datasets, and an index of the polar vortex intensity based on ECMWF data.

Long‐term variability in precipitation and streamflow in Iceland and relations to atmospheric circulation

AbstractHow the variability of the atmospheric circulation affects precipitation in Iceland is not completely understood. Also, the sea surface temperature (SST) has a strong influence on the temperature over the country, and thereby, snow and glacial melt. This study, therefore, aims at explaining how atmospheric circulation and sea surface temperature influence seasonal and annual precipitation, and, consequently, runoff in Iceland.Empirical orthogonal function (EOF) analysis is performed on annual and seasonal time series of precipitation and discharge to identify their key modes of variability during the period 1966–2004. The correlation between the time series of each EOF mode with individual time series of sea level pressure (SLP), air temperature and SST was then evaluated.The analyses evidenced how large‐scale climate variables are connected to the regional precipitation and runoff in Iceland. They showed that the strength of the polar vortex may be, at least, as important for the precipitation in some areas of Iceland as the strength of the Icelandic Low (IL). Moreover, the location of the semi‐permanent IL often defines the predominant wind direction over the country and, as such, the regions of preferred precipitation.Since the watersheds act as large precipitation gauges with response patterns depending on the geology and glaciers, the variability of the annual discharge closely resembles the variability of precipitation, except for the glacial rivers. Glacial melt is highly correlated to air temperature and SST, and the spring discharge is affected by winter and spring temperatures.The results also revealed that Icelandic hydrological conditions in the spring can be forecasted by precipitation and temperature of the autumn and winter seasons, as well as by the general prevalent circulation patterns. Additionally, a potential for seasonal forecast of precipitation, and river discharge in other seasons was identified, particularly if seasonal forecast of SLP is available. Copyright © 2008 Royal Meteorological Society