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Vasubandhu Misra

Abstract

The dominant interannual variation of the austral summer South American monsoon season (SAM) is associated with El Niño–Southern Oscillation (ENSO). Although this teleconnection provides a basis for the seasonal predictability of SAM, it is shown that the conventional tier-2 modeling approach of prescribing observed sea surface temperature (SST) is inappropriate to capture this teleconnection. Furthermore, such a forced atmospheric general circulation model (AGCM) simulation leads to degradation of the SAM precipitation variability.

However, when the same AGCM is coupled to an ocean general circulation model to allow for coupled air–sea interactions, then this ENSO–SAM teleconnection is reasonably well simulated. This is attributed to the role of air–sea coupling in modulating the large-scale east–west circulation, especially associated with Niño-3 SST anomalies. It is also shown that the land–atmosphere feedback in the SAM domain as a result of the inclusion of air–sea coupling is more robust. As a consequence of this stronger land–atmosphere feedback the decorrelation time of the daily rainfall in the SAM region is prolonged to match more closely with the observed behavior.

A subtle difference in the austral summer seasonal precipitation anomalies between that over the Amazon River basin (ARB) and the SAM core region is also drawn from this study in reference to the influence of the air–sea interaction. It is shown that the dominant interannual precipitation variability over the ARB is simulated both by the uncoupled and coupled (to OGCM) AGCM in contrast to that over the SAM core region in southeastern Brazil.

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Vasubandhu Misra

Abstract

The remote influence of the El Niño–Southern Oscillation (ENSO) strongly manifests over the equatorial Amazon (EA)—including parts of southern Venezuela, Guyana, French Guiana, and Suriname—when there is a large-scale anomalous upper-level divergence over continental tropical South America. Modeling studies conducted in this paper suggest that it is because of the modulation of the local diurnal cycle of the moisture flux convergence, which results in the local amplification of the ENSO signal over the EA. Further, it is shown that the local land surface feedback plays a relatively passive but important role of maintaining these interannual precipitation anomalies over the EA region.

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Vasubandhu Misra

Abstract

Shown in this study are a teleconnection pattern relating outgoing longwave radiation (OLR) anomalies over the western Pacific Ocean and sea surface temperature anomalies (SSTAs) over the western Indian Ocean over two seasons [September–October–November (SON) and December–January–February (DJF)] at zero lag from observations and atmospheric general circulation model (AGCM) integrations. This teleconnection pattern suggests that a positive SSTA in the SON and DJF seasons over the western Indian Ocean increases the contemporaneous positive OLR anomalies over the western Pacific Ocean. This teleconnection pattern is also simulated by the Center for Ocean–Land–Atmosphere studies (COLA) AGCM forced with observed SST. From the experimental COLA AGCM runs (wherein the Pacific Ocean SST variability is suppressed except for the climatological annual cycle), it is diagnosed that the interannual variability of OLR over the western Pacific Ocean persists because of this teleconnection. This teleconnection pattern is found to be associated with the modulation of the equatorial zonal wind circulation by the western Indian Ocean SSTAs.

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Vasubandhu Misra

Abstract

In this study predictability of austral summer seasonal precipitation over South America is investigated using a 12-yr set of a 3.5-month range (seasonal) and a 17-yr range (continuous multiannual) five-member ensemble integrations of the Center for Ocean–Land–Atmosphere Studies (COLA) atmospheric general circulation model (AGCM). These integrations were performed with prescribed observed sea surface temperature (SST); therefore, skill attained represents an estimate of the upper bound of the skill achievable by COLA AGCM with predicted SST. The seasonal runs outperform the multiannual model integrations both in deterministic and probabilistic skill. The simulation of the January–February–March (JFM) seasonal climatology of precipitation is vastly superior in the seasonal runs except over the Nordeste region where the multiannual runs show a marginal improvement. The teleconnection of the ensemble mean JFM precipitation over tropical South America with global contemporaneous observed sea surface temperature in the seasonal runs conforms more closely to observations than in the multiannual runs. Both the sets of runs clearly beat persistence in predicting the interannual precipitation anomalies over the Amazon River basin, Nordeste, South Atlantic convergence zone, and subtropical South America. However, both types of runs display poorer simulations over subtropical regions than the tropical areas of South America. The examination of probabilistic skill of precipitation supports the conclusions from deterministic skill analysis that the seasonal runs yield superior simulations than the multiannual-type runs.

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Vasubandhu Misra

Abstract

This study reveals the inadequacy of the Center for Ocean–Land–Atmosphere Studies (COLA) atmospheric general circulation model (AGCM) and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis to resolve the variance of the intraseasonal anomalies of outgoing longwave radiation (OLR) over the South American summer monsoon (SASM) domain and the equatorial eastern Pacific Ocean (EEPO) owing to their coarse horizontal resolution. However, when the NCEP–NCAR reanalysis is downscaled by roughly a factor of 2.5 using the Regional Spectral Model (RSM; control-A experiment), the simulation of the seasonal mean variance of intraseasonal anomalies of OLR improves significantly. But downscaling the results of the COLA AGCM (control-B experiment) by roughly a factor of 4 led to no further improvement.

Using the novel technique of anomaly nesting, which replaces the climatology of the COLA AGCM of the nested variables at the lateral boundaries of the RSM with the NCEP–NCAR reanalysis climatology (AN experiment), the simulation of the intraseasonal variance of OLR improves significantly over control-B runs. This improvement is shown to coincide with a distinct diurnal variation of the intraseasonal scales displayed in the AN integrations, which compare reasonably well with control-A integrations. A disappointing result of this study is that the generated variance of intraseasonal anomalies of OLR in the AN integrations arises from the internal variability of the model. However, it is concluded that the systematic errors of the COLA AGCM imposed on RSM from the lateral boundary conditions suppress the generation of intraseasonal variability.

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Vasubandhu Misra

Abstract

This study is an analysis of AGCM model results to understand the dynamics of the response of precipitation over southern Africa (SA) to anomalies in the sea surface temperature (SST) over the Pacific Ocean. The pattern of interannual precipitation anomaly over SA and its temporal variations are quite similar in both the ensemble mean of the control (where AGCM is forced with observed SSTs in all ocean basins) and experimental runs (where AGCM is forced with seasonally varying climatological SST over the Pacific Ocean). However, the amplitude of the variability is found to be relatively reduced in the experimental runs. This is shown to be a result of the modulation of the Walker circulation by the variability of Pacific Ocean SST. The regional teleconnection pattern between the dominant mode of SA precipitation variability and SST anomalies over the eastern Indian Ocean is also influenced by the variations in Pacific SST. The nature of the teleconnection between SA precipitation and eastern Indian SST is apparent only when the Pacific SST variability is excluded. This is corroborated from observations as well.

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Vasubandhu Misra

Abstract

A methodology is proposed in which a few prognostic variables of a regional climate model (RCM) are strongly constrained at certain wavelengths to what is prescribed from the bias-corrected atmospheric general circulation model (AGCM; driver model) integrations. The goal of this strategy is to reduce the systematic errors in a RCM that mainly arise from two sources: the lateral boundary conditions and the RCM errors. Bias correction (which essentially corrects the climatology) of the forcing from the driving model addresses the former source while constraining the solution of the RCM beyond certain relatively large wavelengths in the regional domain [also termed as scale-selective bias correction (SSBC)] addresses the latter source of systematic errors in RCM. This methodology is applied to experiments over the South American monsoon region. It is found that the combination of bias correction and SSBC on the nested variables of divergence, vorticity, and the log of surface pressure of an RCM yields a major improvement in the simulation of the regional climate variability over South America from interannual to intraseasonal time scales. The basis for such a strategy is derived from a systematic empirical approach that involved over 100 regional seasonal climate integrations.

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Satish Bastola and Vasubandhu Misra

Abstract

This study investigates the sensitivity of the performance of hydrological models to certain temporal variations of precipitation over the southeastern United States (SEUS). Because of observational uncertainty in the estimates of rainfall variability at subdaily scales, the analysis is conducted with two independent rainfall datasets that resolve the diurnal variations. In addition, three hydrological models are used to account for model uncertainty. Results show that the temporal aggregation of subdaily rainfall can translate into a markedly higher volume error in flow simulated by the hydrological models. For the selected watersheds in the SEUS, the volume error is found to be high (~35%) for a 30-day aggregation in some of the selected watersheds. Hydrological models tend to underestimate flow in these watersheds with a decrease in temporal variability in precipitation. Furthermore, diminishing diurnal amplitude by removing subdaily rainfall corresponding to times of climatological daily maximum and minimum has a detrimental effect on the hydrological simulation. This theoretical experiment resulted in the underestimation of flow, with a disproportionate volume error (of as high as 77% in some watersheds). Observations indicate that over the SEUS variations of diurnal variability of rainfall explain a significant fraction of the seasonal variance throughout the year, with especially strong fractional variance explained in the boreal summer season. The results suggest that, should diurnal variations of precipitation get modulated either from anthropogenic or natural causes in the SEUS, there will be a significant impact on the streamflow in the watersheds. These conclusions are quite robust since both observational and model uncertainties have been considered in the analysis.

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Vasubandhu Misra and Amit Bhardwaj

Abstract

This study introduces an objective definition for onset and demise of the northeast Indian monsoon (NEM). The definition is based on the land surface temperature analysis over the Indian subcontinent. It is diagnosed from the inflection points in the daily anomaly cumulative curve of the area-averaged surface temperature over the provinces of Andhra Pradesh, Rayalseema, and Tamil Nadu located in the southeastern part of India. Per this definition, the climatological onset and demise dates of the NEM season are 6 November and 13 March, respectively. The composite evolution of the seasonal cycle of 850-hPa winds, surface wind stress, surface ocean currents, and upper-ocean heat content suggest a seasonal shift around the time of the diagnosed onset and demise dates of the NEM season. The interannual variations indicate onset date variations have a larger impact than demise date variations on the seasonal length, seasonal anomalies of rainfall, and surface temperature of the NEM. Furthermore, it is shown that warm El Niño–Southern Oscillation (ENSO) episodes are associated with excess seasonal rainfall, warm seasonal land surface temperature anomalies, and reduced lengths of the NEM season. Likewise, cold ENSO episodes are likely to be related to seasonal deficit rainfall anomalies, cold land surface temperature anomalies, and increased lengths of the NEM season.

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Vasubandhu Misra and Yuning Zhang

Abstract

The fidelity of the interannual variability of precipitation over Nordeste is examined using the suite of the NCEP Climate Forecast System (CFS) seasonal hindcasts. These are coupled ocean–land–atmosphere multiseasonal integrations. It is shown that the Nordeste rainfall variability in the season of February–April has relatively low skill in the CFS seasonal hindcasts. Although Nordeste is a comparatively small region in the northeast of Brazil, the analysis indicates that the model has a large-scale error in the tropical Atlantic Ocean. The CFS exhibits a widespread El Niño–Southern Oscillation (ENSO) forcing over the tropical Atlantic Ocean. As a consequence of this remote ENSO forcing, the CFS builds an erroneous meridional SST gradient in the tropical Atlantic that is known from observations to be a critical forcing for the rainfall variability over Nordeste.

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