Is the interdecadal variation of the summer rainfall over eastern China associated with SST?

The present study examined the major features of the interdecadal variation of the summer rainfall over eastern China (IVRC) and the possible association with sea surface temperature (SST). We noted that the first leading mode of IVRC (accounting for nearly half of the total variance and with maximum loading for the summer rainfall anomalies over South China) may be not forced by SST. On the other hand, the second and third leading modes [accounting for 17.1 and 13.6 % of the total variance and mainly associated with the summer rainfall anomalies over the Yangtze River valley (YRV) and North China, respectively] in some extent are forced by SST anomalies. These observational results are confirmed by atmospheric general circulation model (AGCM) simulations forced by observed SST. By eliminating the internal dynamical process driven rainfall though ensemble mean, the simulations further suggest an overall enhancement of the intensity of IVRC in the corresponding ensemble mean, especially in the YRV and North China regions, but not in South China. That implies the different role of SST in driving IVRC over different regions.     

An analysis of prediction skill of monthly mean climate variability

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30?C40?days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability.     

Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2

An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001–2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.     

Multiple statistical approaches for the discrimination of mangrove species of Rhizophoraceae using transformed field and laboratory hyperspectral data

This study aims at discriminating eight mangrove species of Rhizophoraceae family of Indian east coast using field and laboratory spectra in spectral range (350–2500 nm). Parametric and non-parametric statistical analyses were applied on spectral data in four spectral modes: (i) reflectance (ii) continuum removed, (iii) additive inverse and (iv) continuum removed additive inverse. We introduced continuum removal of inverse spectra to utilize the advantage of continuum removal in reflectance region. Non-parametric test gave better separability than parametric test. Principal component analysis and stepwise discriminant analysis were applied for feature reduction and to identify optimal wavelengths for species discrimination. To quantify the separability, Jeffries–Matusita distance measure was derived. Green (550 nm), red edge (680–720 nm) and water absorption region (1470 and 1850 nm) were found to be optimal wavelengths for species discrimination. The continuum removal of additive inverse spectra gave better separability than the continuum removed spectra.     

Holocene tectono-geomorphic evolution of Haryana plains,Western Ganga plain,India

Haryana plain is the drainage divide between the Ganga plain in the east and the Indus plain in the west. Being a part of the Himalayan foreland, its geomorphology, sedimentation processes, and tectonism are broadly controlled by the Himalayan tectonics. Soil and geomorphological mapping in Haryana plain bring out geomorphic features such as paleochannels, various active drainage patterns, and landforms such as old fluvial plains, floodplains, piedmonts, pediments, terminal fans, and eolian plains. Based on the degree of soil development, and Optical stimulated luminescence (OSL) ages, the soil-geomorphic units were grouped into six members (QIMS-I to VI) (Quaternary Indus Morphostratigraphic Sequence) of a morphostratigraphic sequence: QIMS-VI 9.86–5.38 Ka, QIMS-V 5.38–4.45 Ka, QIMS-IV 4.45–3.60 Ka, QIMS-III 3.60–2.91 Ka, QIMS-II <?2.91–1.52 Ka, and QIMS-I <?1.52 Ka. OSL chronology of different geomorphic features suggests six episodes of tectono-geomorphic evolution in the region since 10 Ka. Neotectonic features such as nine faults, two lineaments, and five fault-bounded tectonic blocks have been identified. Independent tilting and sagging of the blocks in response to neotectonics have resulted in modification of landforms, depositional processes, and hydro-geomorphology of the region. Major rivers like the Yamuna, the Ghaggar, and the Sutlej show different episodes of shifting of their courses. Lineament controlled few extinct channels have been recorded between 20 and 25 m depth below the surface in the ground-penetrating radar (GPR) profiles. These buried channels are aligned along the paleo-course of the Lost Saraswati River interpreted from the existing literature and hence are considered as the course of the lost river. Seven terminal fans have been formed on the downthrown blocks of the associated faults. The Markanda Terminal Fan, the first of such features described, is indeed a splay terminal fan and was formed by a splay distributary system of the Markanda River. Association of three terminal fans of different ages with the Karnal fault indicates the segment-wise development of the fault from west to east. Also, comparison with other such studies in the Ganga plain to further east suggests that the terminal fans formed by streams with distributary drainage pattern occur only in semiarid regions as in the present area and thus are indicators of semiarid climate/paleoclimate. Though the whole region is tectonically active, the region between the Rohtak fault and Hisar fault is most active at present signified by the concentration of earthquake epicenters.     

Anisotropic Continuous-in-Scale Universal Multifractal Cascades: Simulation,Analysis and Correction Methods

Continuous-in-scale multifractal cascades has long been an attractive choice for mathematically modeling turbulent and turbulent-like geophysical fields. These fields are usually anisotropic as they are subject to both stratification and rotation, thereby questioning the isotropy assumption often made to model them. The self-affine and generalized scale invariance approaches to scaling are used here to introduce anisotropy in such models. These anisotropic simulations have (1) unresolved large-scale features and (2) statistics that deviate from the desired power-law scaling mainly in the small scales. The former issue is solved via nesting, whereas the latter is attempted to be overcome using singularity correction methods. While earlier studies have proposed isotropic correction methods, here they have been generalized to correct anisotropic simulations. These singularity corrections seem to improve the small-scale statistical properties of mildly anisotropic simulations; nesting, on the other hand, appears to enhance statistics over almost all scales even for strongly anisotropic simulations. Both the correction and nesting techniques lead to a reduction in computational time and memory usage suggesting that nested singularity-corrected cascades offer a better framework for quantitatively modeling the atmosphere, ocean, solid earth, and associated fields.     

A comparative study of soil erosion modelling by MMF,USLE and RUSLE

The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area.