Suneet Dwivedi

Prediction Rules for Regime Changes and Length in a New Regime for the Lorenz Model

Abstract Despite the widespread use of the Lorenz model as a conceptual model for predictability studies in meteorology, only Evans et al. seem to have studied the prediction of occurrence of regime changes and their duration. In this paper, simpler rules are presented for forecasting regime changes and their lengths, with near-perfect forecasting accuracy. It is found that when |x(t)| is greater than a critical value xc, the current regime will end after it completes the current orbit. Moreover, the length n of the new regime increases monotonically with the maximum value xm of |x(t)| in the previous regime. A best-fit cubic expression provides a very good estimate of n for the next regime, given xm for the previous regime. Similar forecasting rules are also obtained for regime changes in the forced Lorenz model. This model was introduced by Palmer and used as a conceptual model to explore the effects of sea surface temperature on seasonal mean rainfall. It was found that for the forced Lorenz model, the...

An empirical rule for extended range prediction of duration of Indian summer monsoon breaks

Prediction of the duration of the Indian summer monsoon breaks is highly desirable. It will help in planning water resource management, sowing and harvesting. Applicability of the recently discovered regime transition rules for the Lorenz model in predicting the duration of monsoon breaks, is explored in this paper. Using several indices of the observed summer monsoon intraseasonal oscillation (ISO), it is shown that the peak anomaly in an active regime can be used as a predictor for the duration of the subsequent break spell. It is also found that the average growth rate around the threshold to an active condition can be used as a predictor of the peak anomaly in the active spell. Average growth around the threshold to an active condition can give useful prediction of the duration of the following break, on an average, about 23 days (38 days) in advance of its commencement (end).

THE DOUBLE-CUSP MAP FOR THE FORCED LORENZ SYSTEM

It is found that adding constant forcing terms to the Lorenz equations breaks the (x,y)→(-x,-y) symmetry of the system. As a result of the symmetry breaking the consecutive zmax return map (the cusp map) gets split into a double-cusp map. We investigate the double-cusp map for the forced Lorenz system using approximate invariant manifolds about the fixed points and use the double-cusp map to understand the stability of the attractor.

On Pacific Subtropical Cell Variability over the Second Half of the Twentieth Century

AbstractThe evolution of the Pacific subtropical cells (STC) is presented for the period 1948–2007. Using ocean models of different resolutions forced with interannually varying atmospheric forcing datasets, the mechanisms responsible for the observed STC weakening and late recovery during the period of study are analyzed. As a result of the STC weakening (strengthening), warming (cooling) trends are found in the equatorial Pacific sea surface temperatures (SSTs). Model results agree well with observed estimates of STC transport, STC convergence, and equatorial SST anomalies. It is shown that subtropical atmospheric variability is the primary driver of the STC and equatorial SST low-frequency evolution and is responsible for both the slowdown during the second half of the twentieth century and the rebound at the end of the century. Subtropically forced STC variability is identified as a major player in the generation of equatorial Pacific decadal SST anomalies, pacing tropical Pacific natural climate vari...

Adaptive synchronisation of diffusionless Lorenz systems and secure communication of digital signals by parameter modulation

Diffusionless Lorenz system of equations is a simplified one-parameter version of the Lorenz system of equations. This system is used here as transmitter and receiver for secure communication. An adaptive control procedure is presented, which causes a rapid convergence of the receiver parameter to the transmitter parameter. This convergence can be used for secure communication of digital signals by parameter modulation. Compared with the Lorenz system, the diffusionless Lorenz system leads to faster communication, smoother parameter adaptation and enhanced security. The proposed scheme is robust with respect to relatively large differences in the delay times for the transmission of three chaotic variables from the master to the slave system. The scheme can be scaled up to allow simultaneous transmission of several signals.

Intercomparison of High-Resolution Bay of Bengal Circulation Models Forced with Different Winds

ABSTRACT The high-resolution Bay of Bengal circulation modeling in the region [80E–95E; 5N–22N] is performed with a horizontal resolution of 10 km and the highest vertical resolution of 5 m near the surface. The intercomparison experiments, with ocean model forced with the near-surface (1) National Centers for Environmental Prediction (NCEP) reanalysis winds and (2) blended seawinds data (a combination of remotely sensed scatterometer and in situ observations) are carried out for a period of 17 years during 1998–2014. The seasonal variability of the realistically simulated surface hydrographic (temperature and salinity) and circulation (currents) variables from both the experiments is compared and contrasted with the observational data. The mixed layer depth seasonal variability of the region is also studied. The mesoscale features of currents at 50 and 100 m are also studied. The volume transport across different sections in the Bay of Bengal is computed and its relation with summer monsoon rainfall is investigated. The results suggest that there is no real advantage of using high-resolution blended seawinds over the much coarser NCEP reanalysis winds.

Monitoring the vegetation health over India during contrasting monsoon years using satellite remote sensing indices

The detection and monitoring of drought-related vegetation stress over a large spatial area have become possible with the use of satellite-based remote sensing indices, namely, vegetation condition index (VCI) and temperature condition index (TCI). In particular, the water (precipitation)-related moisture stress during drought may be determined using the VCI, while the temperature-related stress using the TCI. An attempt is made here to investigate and demonstrate the importance of these indices over India during the contrasting monsoon years, 2009, 2010, and 2013, termed as meteorological drought, wet, and normal monsoon years, respectively. The overall health of the vegetation during these years is compared using the vegetation health index (VHI). The advantage of VHI over the VCI and TCI is also shown. An assessment of drought over India is then made using the combined information of VCI, TCI, and VHI. The occurrence of vegetative drought over Rajasthan, Gujrat, and Andhra Pradesh is confirmed using drought assessment index, which shows very low value (well below 40) during 2009 over these regions. The area-averaged time series indices as well as spatial maps over the state of Uttar Pradesh show higher thermal stress and poor vegetation health during 2009 as compared to 2010 and 2013. The standardized precipitation index (SPI) and standardized water-level index (SWI) are used to validate the results obtained using the remote sensing indices.

Effect of averaging timescale on a forced lorenz model

Abstract The effect of temporal averaging on the forced Lorenz model is studied. It is shown that the duration of temporal averaging affects the regime structure. When temporal averaging is increased beyond the fast timescale of the Lorenz model, regime splitting takes place. The increase in the predictability of the system with an increase in moving time average steps is quantified. Our findings from a conceptual forced Lorenz model are consistent with real world observations.

Unraveling the missing link of ENSO control over the Indian monsoon rainfall

Using long daily rainfall (113 years) data, clear evidence of modulation of the statistics of subseasonal active and break spells of the Indian summer monsoon rainfall (ISMR) by the El Nino–Southern Oscillation (ENSO) is unraveled. We show that during the El Nino (La Nina) years, the frequency of longer break (active) spells and shorter active (break) spells increases substantially, while the frequency of shorter breaks (active) and longer active (break) spells decreases compared to ENSO neutral years. It is shown that the large-scale teleconnection through which ENSO weakens (strengthens) the ISMR through shortening (lengthening) of the length of rainy season (LRS) also creates a background for modulation of the statistics of subseasonal spells leading to a further reduction (increase) in the ISMR during El Nino (La Nina) years. Our findings indicate that the “statistics of subseasonal spells” is predictable, brightening the prospect of seasonal prediction of the ISMR.

Short-term predictions by statistical methods in regions of varying dynamical error growth in a chaotic system

In a nonlinear, chaotic dynamical system, there are typically regions in which an infinitesimal error grows and regions in which it decays. If the observer does not know the evolution law, recourse is taken to non-dynamical methods, which use the past values of the observables to fit an approximate evolution law. This fitting can be local, based on past values in the neighborhood of the present value as in the case of Farmer–Sidorowich (FS) technique, or it can be global, based on all past values, as in the case of Artificial Neural Networks (ANN). Short-term predictions are then made using the approximate local or global mapping so obtained. In this study, the dependence of statistical prediction errors on dynamical error growth rates is explored using the Lorenz-63 model. The regions of dynamical error growth and error decay are identified by the bred vector growth rates or by the eigenvalues of the symmetric Jacobian matrix. The prediction errors by the FS and ANN techniques in these two regions are compared. It is found that the prediction errors by statistical methods do not depend on the dynamical error growth rate. This suggests that errors using statistical methods are independent of the dynamical situation and the statistical methods may be potentially advantageous over dynamical methods in regions of low dynamical predictability.