Role Of Sea Surface Temperature Research Articles

Simulation of the role of Caspian Sea surface temperature and air temperature on precipitation intensity in lake-effect snow

Heavy snowfall is one of the perilous atmospheric phenomena which occurs occasionally in south-west coasts of the Caspian Sea. In this paper, we have simulated the role of sea surface temperature (SST) and lake-air temperature difference on the lake-effect snow in south-west coasts of the Caspian Sea using Weather Research and Forecasting (WRF) model. SST was increased by 2 °C–4 °C and air temperature decrease by 2 °C–4 °C in model simulations and the resulting precipitation was compared to observed values. The results show that the precipitation is significantly sensitive to the SST and lake-air temperature difference. The results indicated that the regions with heavy precipitation correspond with 4 °C increase in SST and 2 °C decrease in air temperature, add about 60 mm to the total precipitation. Furthermore, the increase in SST enhances snowfall along the coastlines. In overall, an increase between 2 °C and 4 °C in SST over 5 days, increases the precipitation between 8.43% and 19.41%, respectively, and decrease air temperature by 2 °C and 4 °C increase precipitation about 24.78% and 0.72%, respectively. Overall, the highest increase in precipitation in the whole region is related to the 2 °C decrease in air temperature and the 4 °C increase in SST. Since other atmospheric parameters such as pressure, wind field, and humidity flux are affected by temperature change, so excessive decrease in air temperature tends to weaken the low pressure and vertical motion and less precipitation occurs. Therefore, the amount of the lake-air temperature difference is a key factor in strengthening the lake-effect precipitation.Additionally, SST increases the latent heat flux and injects additional humidity to the region which further strengthens orographic uplifts and intensifies unstable condition. In the meantime, stronger wind speed caused by unstable boundary layer over the lake and sufficient fetch, accumulate additional humidity in the convergence zone along the south-west coastlines.

Temporal evolution of surface humidity in Turkey: recent trends and the role of sea surface temperatures

Temporal evolution of surface humidity in Turkey: recent trends and the role of sea surface temperatures

Asian meteorological droughts on three time scales and different roles of sea surface temperature and soil moisture

AbstractThe present study utilizes the standard precipitation index (SPI) to differentiate Asian summer droughts that are associated with variations of precipitation over periods of 3, 9 and 24 months (termed as short‐term, medium‐term and long‐term droughts, respectively). Then, the relationships between these droughts and atmospheric circulation, sea surface temperature (SST), and soil moisture are investigated. While the spatial and temporal characteristics of short‐term and medium‐term droughts are fairly similar, long‐term droughts display different spatial and temporal features. The leading spatial mode of short‐term and medium‐term droughts exhibits a dipole pattern with opposite loading north and south of approximately 30°N. The second spatial mode displays a tripole pattern with the same sign of loading over India and north‐northeast China–Mongolia and opposite loading in between. Temporal variations of short‐term and medium‐term droughts are dominated by interannual variabilities. For long‐term droughts, the first two spatial modes switch their order, and the long‐term trends are as important as the interannual and interdecadal variabilities. The droughts of the dipole mode are associated with SST anomalies featuring an El Niño‐like pattern in the tropical Indo‐Pacific Ocean that affect the drought variations through inducing large‐scale divergence and convergence. The interannual variability of the droughts with the dipole mode is also associated with the SST anomalies in the North Atlantic Ocean that affect the North Atlantic‐Eurasian atmospheric circulation. Local soil moisture conditions are more important for the formation of long‐term droughts than short‐term and medium‐term droughts.

Did a skillful prediction of near-surface temperatures help or hinder forecasting of the 2012 US drought?

This study aims to understand the role of near-surface temperatures in predicting US climatic extremes using the North American Multi-Model Ensemble (NMME) system. Here, the forecasting skill was measured by anomaly correlation coefficient (ACC) between the observed and forecasted precipitation (PREC)/2-meter air temperature (T2m) anomalies over the contiguous United States (CONUS) during 1982–2012. The strength of the T2m–PREC coupling was measured by ACC between observed PREC and T2m or forecasted PREC and T2m over the CONUS. We also assessed the NMME forecasting skill for the summers of 2004 (spatial anomaly correlation between PREC and T2m: 0.05), 2011 (−0.65), and 2012 (−0.60) when the T2m–PREC coupling was weaker or stronger than the 1982–2012 climatology (ACC: −0.34). We found that most of the NMME models show the bias of stronger T2m–PREC coupling than the observed coupling over 1982–2012, indicating that they failed to reproduce the interannual variability of T2m–PREC coupling. Some NMME models with skillful prediction for T2m show the skillful prediction of the precipitation anomalies and US droughts in 2011 and 2012 via strong T2m–PREC coupling despite the fact that the forecasting skill is year-dependent and model-dependent. Most of the NMME models show the limited seasonal forecasting skill of the PREC surplus from active Atlantic tropical cyclones in the summer of 2004 and thus fail to reproduce weak T2m–PREC coupling. Lastly, we explored how the role of sea surface temperatures in predicting T2m and PREC. The findings of this study suggest a need for the selective use of the current NMME seasonal forecasts for US droughts and pluvials.

Influence of the mightiest rivers worldwide on coastal sea surface temperature warming

Ocean warming as a consequence of climate change occurred during the last decades is not homogeneous. This is especially patent for coastal areas, where the warming is influenced by local processes that occur at different time and spatial scales. In this sense, plumes formed by rivers discharge can play a key role in sea surface temperature (SST) warming. SST trends for the coastal points affected by the plumes of the 19 world's mightiest rivers (south 60°N) and their oceanic counterparts were analyzed by means of NOAA's AVHRR OISST data over the period 1982–2019. Coastal areas affected by river plumes showed an annual less intense warming trend than observed at the adjacent ocean in all cases. In average, warming trend was 0.088 °C dec−1 lower for coastal areas, ranging from 0.027 °C dec−1 for Mekong and Irrawaddy/Salween River plume systems to 0.208 °C dec−1 and 0.278 °C dec−1 for Mississippi and Paraná River plumes. The differences in coastal-ocean warming obtained for rivers debouching into inland seas (Danube and Volga Rivers) are similar to the ones observed for the rest of the rivers, even if inland seas are prone to higher warming rates than open seas. As the main conclusion, river plumes seem to have the ability to modulate SST warming near coast within the current context of global warming.

Potential Predictability of the Silk Road Pattern and the Role of SST as Inferred from Seasonal Hindcast Experiments of a Coupled Climate Model

AbstractThe Silk Road pattern (SR) is a leading mode of atmospheric circulation over midlatitude Eurasia in boreal summer. Its temporal phase is known to be unpredictable in many models. Previous studies have not reached a clear consensus on the role of sea surface temperature (SST) associated with SR. By comparing seasonal hindcasts from the Pusan National University (PNU) coupled general circulation model with reanalysis, we investigate if there are any sources of predictability originating from the SST. It was found that the PNU model cannot predict SR temporally. In fact, SR is associated with El Niño–Southern Oscillation (ENSO) in the model hindcasts, in contrast to reanalysis results in which SR is more associated with North Atlantic SST anomalies. The PNU system, however, shows potential predictability in SR associated with tropical Pacific SST. Bias in stationary Rossby waveguides is proposed as an explanation for the SR–ENSO relationship in hindcast runs. Model upper-level wind bias in the North Atlantic results in a less continuous waveguide connecting the North Atlantic to Asia, and may hinder wave propagations induced by North Atlantic SST to trigger SR. On the other hand, model upper-level wind bias in the subtropical western Pacific may favor westward propagation of zonally elongated waves from the ENSO region to trigger SR. This study implies that the role of SST with regard to SR can be substantially changed depending on the fidelity of model upper-level background winds.

Sea surface temperature in coral reef restoration outcomes

Successful restoration of coral reefs depends on the survival of outplanted species. Research shows that outplanting survival is mixed, with outplants often experiencing rapid mortality in response to various stressors. We used published results on outplant monitoring to investigate the role of sea surface temperature in the survival rates of corals. We find that the maximum temperature experienced at an outplanting site is very important in determining outplant survival, with ∼50% mortality occurring if temperatures reach 30.5 °C. Some genera, however, are more tolerant than others. Outplant survival increases when sites experience greater variability in temperature, where outplants are exposed to temperatures both warmer and cooler than the long-term mean. Similar results were found when considering temperature conditions of the site in the year prior to outplanting. Thus, sea surface temperature data can be used as a tool to assess whether a restoration site is appropriate, with sites chosen to increase outplant survival.

Role of sea surface temperature on the equatorial waves and intraseasonal oscillations

Ocean interactions are known to play a major role in the modulation of intraseasonal variability. The role of sea surface temperature (SST) and major oceanic processes like ENSO (El Nino-Southern Oscillation) and IOD (Indian Ocean Dipole) on intraseasonal oscillations like Madden-Julian Oscillation (MJO) and convectively coupled equatorial waves (Kelvin wave, equatorial Rossby (ER), mixed-Rossby gravity and tropical depressions (together MT)) is explored using 32 years of satellite observations and reanalysis data. It is shown that the relationship between wave activity and SST is highly seasonal and region dependent. The study also shows that the global wave activity is more related to major oceanic phenomena like ENSO and IOD, while regionally, local intensification of the waves is observed to be directly associated with corresponding regional SST. But this relation is mostly limited to the western hemisphere. Globally, while Kelvin and Rossby waves intensify during El Nino, MT waves are shown to intensify during La Nina. MJO and ER are suppressed and MT is intensified during positive IOD. It is shown that the zonal and meridional distribution of moist static energy (MSE) during different phases of ENSO and IOD is the major factor in modulating the observed changes in the intensity of waves along with the distribution of vertical shear. Seasonal variations in these relationships are also explored.

The Decadal Reduction of Southeastern Australian Autumn Rainfall since the Early 1990s: A Response to Sea Surface Temperature Warming in the Subtropical South Pacific

AbstractRainfall in southeastern Australia (SEA) decreased substantially in the austral autumn (March–May) of the 1990s and 2000s. The observed autumn rainfall reduction has been linked to the climate change–induced poleward shift of the subtropical dry zone across SEA and natural multidecadal variations. However, the underlying physical processes responsible for the SEA drought are still not fully understood. This study highlights the role of sea surface temperature (SST) warming in the subtropical South Pacific (SSP) in the autumn rainfall reduction in SEA since the early 1990s. The warmer SSP SST enhances rainfall to the northwest in the southern South Pacific convergence zone (SPCZ); the latter triggers a divergent overturning circulation with the subsidence branch over the eastern coast of Australia. As such, the subsidence increases the surface pressure over Australia, intensifies the subtropical ridge, and reduces the rainfall in SEA. This mechanism is further confirmed by the result of a sensitivity experiment using an atmospheric general circulation model. Moreover, this study further indicates that global warming and natural multidecadal variability contribute approximately 44% and 56%, respectively, of the SST warming in the SSP since the early 1990s.

Modeling the variability of the atmospheric gas composition at RSHU

A set of numerical models of the lower and middle atmosphere gas composition has been created at the Russian State Hydrometeorological University (RSHU). The set of RSHU numerical models consists of a global chemistry-climate model (CCM) of the troposphere, stratosphere and mesosphere (0-90 km), a chemistry-transport model (CTM) of the troposphere and stratosphere gas composition with meteorological parameters specified from reanalysis data (0-60 km), and a model of Eurasia air quality (0-32 km). All models use a single block of chemical transformations in the atmosphere and different ways of using meteorological parameters that determine the effect of atmospheric transport on atmospheric gases. The CCM allows us to study the interaction of physical and chemical processes in the lower and middle atmosphere, the CTM is suitable for studying the influence of chemical processes on the gas composition of the atmosphere under a given influence of dynamic factors, and the air quality model can be used to analyze the impact of surface emissions of pollutants and meteorological conditions on the observed variability of air quality in different parts of Eurasia. Numerical experiments with RSHU CCM described in this article allowed us to identify the relative role of natural and anthropogenic factors in the interannual variability of atmospheric ozone in tropical, middle and polar latitudes. Quantitative estimates of ozone trends revealed a greater rate of ozone decrease in Northern mid-latitude compared to its variability in the tropical latitudes. During periods of sharp ozone decrease and then recovery in the 90th years of the twentieth century, in the tropics and mid-latitudes, the additive role played by the combination of several factors: the fall in ozone as a result of increased content of chlorine and bromine gases and reduction in solar activity and the role of sea surface temperature on the background of increasing chlorine and bromine gases and the increase in the ozone content in the result of the purification of stratospheric aerosol and the influence of the variability of sea surface temperature and growth of solar activity. The results of numerical calculations with CTM demonstrated the predominant role of dynamic processes in the formation of winter-spring ozone anomalies in the Arctic and Subarctic. Rapid use of the air quality model has shown the important impact of meteorological conditions on air quality in Eurasia

How much of monthly mean precipitation variability over global land is associated with SST anomalies?

The role of sea surface temperature (SST) in determining the predictability of monthly mean precipitation over the global land is assessed by analyzing the Atmospheric Model Intercomparison Project (AMIP)-like simulations forced by observed SST, which provides a benchmark for the impact of SST on the precipitation. The correlations of monthly mean precipitation anomalies between the ensemble mean of the AMIP simulations and observations are dominated by positive values with maxima around 0.3–0.4 in the tropical North Africa along 15° N and northeastern Brazil. The SST forcing for the precipitation variability is mainly associated with the El Nino-Southern Oscillation (ENSO) and in the tropical Indian Ocean. Statistically, positive and negative SST anomalies associated with an ENSO cycle have a comparable influence on precipitation variability over the land. In addition to the spatial variations, the precipitation responses to SST also vary with season and decade. Pattern correlations are larger in boreal winter than in boreal summer in the Northern Hemisphere, and relatively larger in April-June and September–November in the Southern Hemisphere. The global average of correlation is lower during 1957–1980 and 2000–2018, and higher in between. The interdecadal fluctuation of the pattern correlations is coherent with the interdecadal variation of the amplitude of ENSO.

Role of Sea Surface Temperatures in Forcing Circulation Anomalies Driving U.S. Great Plains Pluvial Years

Abstract In the U.S. Great Plains (GP), diagnosing precipitation variability is key in developing an understanding of the present and future availability of water in the region. Building on previous work investigating U.S. GP pluvial years, this study uses ERA twentieth century (ERA-20C) reanalysis data to investigate key circulation anomalies driving GP precipitation anomalies during a subset of GP pluvial years (called in this paper Pattern pluvial years). With previous research showing links between tropical Pacific sea surface temperature (SST) anomalies and GP climate variability, this study diagnoses the key circulation anomalies through an analysis of SSTs and their influence on the atmosphere. Results show that during Pattern southern Great Plains (SGP) pluvial years, central tropical Pacific SST anomalies are coincident with key atmospheric anomalies across the Pacific basin and North America. During northern Great Plains (NGP) Pattern pluvial years, no specific pattern of oceanic anomalies emerges that forces the circulation anomaly feature inherent in specific NGP pluvial years. Utilizing the results for SGP pluvial years, a conceptual model is developed detailing the identified pathway for the occurrence of circulation patterns that are favorable for pluvial years over the SGP. Overall, results from this study show the importance of the identified SGP atmospheric anomaly signal and the potential for predictability of such events.

THE ROLE OF SEA SURFACE TEMPERATURE IN THE RAINFALL REGIME IN SUB-SAHARAN AFRICA

This study sought to understand the role of the surface temperatures of the ocean and continent in the variability of rains in sub-Saharan Africa, contributing to the improvement of weather forecasting and prevention of extreme events in the region. Through perturbation experiments using a climate model of intermediate complexity, we seek to understand the roles of sea surface temperature (SST) of ocean basins around the sub-Saharan Africa and the surface temperature in Southern Africa, in defining the spatial distribution of Spatial distribution of rainfall in the region of action of Intertropical Convergence Zone (ITCZ) which assumes an approximate shape of an inverted S during the quarter December-January-February in this continent, due to connections with other systems of the same scale. By comparing the regional perturbation experiments of SST and the continental surface temperature with respect to the climatology we came to the conclusion that the SST in the Atlantic and Indian Oceans have major contribution in the formation of inverted S of precipitation than the continent's surface temperature. Comparing these two ocean basins, the Indian SST has predominant role in the climate variability in sub-Saharan Africa, modulating the position and intensity of the ITCZ and therefore the formation of their spatial distribution across the continent.

Role of Sea Surface Temperature in Modulating Life Cycle of Tropical Cyclones over Bay of Bengal

Sea surface temperature (SST) varies significantly in the presence of tropical cyclones (TCs). Using fixed SST throughout the integration of high resolution TC models is general practice in research and operational endeavor over the North Indian Ocean. The present study is to assess the impact of updating realistic SST in TC lifetime on track, intensity and rainfall of TCs. The Hurricane Weather Research Forecast (HWRF) model of single domain with 9km resolution is used. A total of 31 forecast cases are considered from 6 TCs during 2007- 16 with unique track and intensity characteristics. A set of two numerical experiments are done without (CNTL) and with 6-hourly SST update (SST) in TC lifetime.Mean track and intensity errors show that there is an improvement of 3–41% in track during 12–120h forecast length for SST run. The SST runs improve landfall position and time prediction by 20% and 33% respectively. The cross track error of SST run is comparable (44km) with average errors available for this basin (34km); and along track errors are improved by 60% as compared to CNTL as well as average errors of the basin. The model is biased to overestimate a weaker TC and underestimate a stronger TC, however, the bias is reduced in SST run by 5–51%. The analyses of wind, enthalpy flux and warm core structures provide insight for realistic intensity prediction of SST run unlike CNTL. Rainfall intensity and radial distribution is also improved in SST run. Thus, this study highlights the significance of ocean coupling with TC models to advance forecast guidance.

Predicting wintertime windy days in Beijing with the preceding autumn sea surface temperature and large-scale circulation patterns

In this study, we investigate the role of sea surface temperature and large-scale circulation patterns in the preceding autumn for the prediction of wintertime windy days in Beijing during the period of 1979–2016, based on a time-scale decomposition approach. A windy day is defined according to the threshold of 2 m·s−1, which can effectively remove or reduce air pollution of Beijing. Wintertime windy days in Beijing, preceding autumn sea surface temperature and large-scale climate indices are separated into the interannual and interdecadal components. For the interannual component, the preceding autumn sea surface temperature in central western Pacific Ocean, Polar/Eurasia pattern, and Scandinavia pattern are identified as predictors of wintertime windy days in Beijing. For the interdecadal component, the identified predictors include the preceding autumn sea surface temperature in northeastern part of North Atlantic Ocean, Arctic Oscillation, and North Atlantic Oscillation. We develop statistical models for the interannual and interdecadal components based on these preceding autumn predictors, and take them together to predict wintertime windy days in Beijing. The leave-one-out cross-validation for 1979–2016 time series shows that 76% of the total variance of observed wintertime windy days in Beijing can be predicted. Hindcast experiments for the period of 1999–2016 also yield the high prediction skills. The physical mechanisms responsible for links between these predictors and wintertime windy days in Beijing are also discussed. The statistical models proposed herein are expected to be applied to and aid to improve seasonal forecasting of wintertime windy days in Beijing.

The role of sea surface temperature in the atmospheric seasonal cycle of the equatorial Atlantic

We investigate the role of sea surface temperature (SST) and land surface temperature (LST) in driving the seasonal cycle of the atmosphere (surface winds and precipitation) in the tropical Atlantic. For this we compare three atmospheric general circulation model (AGCM) experiments for the historical period 1982–2013 forced by different SST: (1) observed daily-climatological SST, (2) globally annual-mean SST, and (3) annual-mean SST in the equatorial Atlantic and daily-climatological SST elsewhere. Seasonal variations in SST strongly influence the seasonal evolution of the West African Monsoon (WAM) and ITCZ over the equatorial Atlantic Ocean. Forcing the model with annual mean SST (globally and in the equatorial Atlantic) considerably reduces the seasonal variance in the atmosphere, except for the zonal winds in the eastern equatorial Atlantic. Equatorial Atlantic SST contributes to the seasonal cycle in precipitation and meridional winds over the entire equatorial Atlantic, but only strongly influences zonal winds in the western equatorial Atlantic and has little influence on the northward penetration of the WAM. The leading modes of coupled SST–LST-atmosphere co-variability are identified by multivariate analysis. The analysis shows that both LST and SST drive seasonal variations in precipitation over equatorial Atlantic, with the LST being a larger contributor to the continental rainfall in West Africa. The coupling between ocean and atmosphere is stronger in the western than in the eastern equatorial Atlantic. The pressure adjustment mechanism is the main driver of the surface meridional wind convergence in the eastern tropical Atlantic.

Role of Sea Surface Temperature over the Kuroshio Extension Region on Heavy Rainfall Events over the Korean Peninsula

This study examines the active role of sea surface temperature (SST) over the Kuroshio Extension region during heavy rainfall events over the Korean Peninsula within Changma period (June–July). While the overall synoptic patterns during the heavy rainfall events over Korea are similar to those during moderate rainfall events (i.e. between 0.5 and 1 standard deviation), the synoptic signals preceding heavy rainfall events are distinct from those of moderate rainfall events. A distinguishing feature is the maintenance of a high-pressure anomaly over the Kuroshio Extension region, which lead to persistent southerly winds and resultant heavy rainfall events over the Korean Peninsula, from roughly 1 week before the start of heavy rainfall events. On the other hand, the high-pressure anomaly associated with the moderate rainfall events is propagated from the west along the climatological westerly winds. It was found that positive SST anomalies over the Kuroshio Extension region (140–156°E, 28–35°N) play an important role in maintaining the high-pressure anomaly over the Kuroshio Extension region. None of heavy rainfall events was found when the positive geopotential height anomaly over the Kuroshio Extension region was co-located with a local negative SST anomaly. This probability increased to 62% when the positive geopotential height anomaly was co-located with a local positive SST anomaly. This shows that a positive SST anomaly over the Kuroshio Extension region can be a useful precursor to heavy rainfall events over the Korean Peninsula.

Roles of SST versus Internal Atmospheric Variability in Winter Extreme Precipitation Variability along the U.S. West Coast

The U.S. West Coast exhibits large variability of extreme precipitation during the boreal winter season (December–February). Understanding the large-scale forcing of such variability is important for improving prediction. This motivates analyses of the roles of sea surface temperature (SST) forcing and internal atmospheric variability on extreme precipitation on the U.S. West Coast. Observations, reanalysis products, and an ensemble of Atmospheric Model Intercomparison Project (AMIP) experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are analyzed. It is found that SST forcing only accounts for about 20% of the variance of both extreme and nonextreme precipitation in winter. Under SST forcing, extreme precipitation is associated with the Pacific–North American teleconnection, while nonextreme precipitation is associated with the North Pacific Oscillation. The remaining 80% of extreme precipitation variations can be explained by internal atmospheric dynamics featuring a circumglobal wave train with a cyclonic circulation located over the U.S. West Coast. The circumglobal teleconnection manifests from the mid- to high-latitude intrinsic variability, but it can also emanate from anomalous convection over the tropical western Pacific, with stronger tropical convection over the Maritime Continent setting the stage for more extreme precipitation in winter. Whether forced by SST or internal atmospheric dynamics, atmospheric rivers are a common and indispensable feature of the large-scale environment that produces concomitant extreme precipitation along the U.S. West Coast.

Understanding the role of sea surface temperature-forcing for variability in global temperature and precipitation extremes

The oceans are a well-known source of natural variability in the climate system, although their ability to account for inter-annual variations of temperature and precipitation extremes over land remains unclear. In this study, the role of sea-surface temperature (SST)-forcing is investigated for variability and trends in a range of commonly used temperature and precipitation extreme indices over the period 1959 to 2013. Using atmospheric simulations forced by observed SST and sea-ice concentrations (SIC) from three models participating in the Climate of the Twentieth Century Plus (C20C+) Project, results show that oceanic boundary conditions drive a substantial fraction of inter-annual variability in global average temperature extreme indices, as well as, to a lower extent, for precipitation extremes. The observed trends in temperature extremes are generally well captured by the SST-forced simulations although some regional features such as the lack of warming in daytime warm temperature extremes over South America are not reproduced in the model simulations. Furthermore, the models simulate too strong increases in warm day frequency compared to observations over North America. For extreme precipitation trends, the accuracy of the simulated trend pattern is regionally variable, and a thorough assessment is difficult due to the lack of locally significant trends in the observations. This study shows that prescribing SST and SIC holds potential predictability for extremes in some (mainly tropical) regions at the inter-annual time-scale.

Relative role of sea surface temperature and snow on Indian summer monsoon seasonal simulation using a GCM

Indian summer monsoon is a global scale phenomenon controlled by different land, ocean, and atmospheric parameters. Sea surface temperature (SST) and snow are two of the major parameters, which may alter the spatial and temporal patterns of circulation and rainfall during Indian summer monsoon. In the current paper, we study the monsoon variability using long integrations (20 years) of the Indian Institute of Technology Delhi (IITD) Spectral model at T80L18 resolution with observed and climatological SST and snow. Study shows response of IITD GCM in simulating the Indian summer monsoon rainfall and circulation relative to the snow and SST as boundary conditions. The model’s response to SST and snow is examined by conducting four types of experiments by varying observed and climatological values of snow and SST. This paper discusses the seasonal total rainfall for country as a whole and 850 and 200 hPa wind for the period of 20 years starting from 1985 to 2004. The model has been integrated in the ensemble mode with five different initial conditions from the last week of April and first week of May. The model is able to capture the climatological patterns of seasonal total rainfall and averaged wind at lower and upper levels. Observed snow in the presence of climatological SST as a boundary condition shows much impact on rainfall and circulation than observed SST in the presence of climatological snow. Model performance is good in simulating the normal and excess monsoon conditions; it shows poor skill in capturing deficit monsoon years.