Investigation of dominant modes of monsoon ISO in the northwest and eastern Himalayan region

This study investigates the altitudinal variation of dominant modes of summer monsoon intra-seasonal oscillation (ISO) over the Northwest (NWH) and Eastern Himalayan (EH) region using (i) spatially scattered 133 number of station rainfall observations and (ii) latitudinal transect-wise (LT) rainfall variation, obtained from an observed interpolated gridded rainfall data for the period 1995–2004. The altitudinal variation of dominant modes of monsoon ISO were investigated by exploring the strong and weak phases of the principal components of 10–90 days bandpass rainfall data of June to September with respect to location specific station height. Investigation of frequency of days for light and moderate rainfall along with the occurrence of total seasonal rainy days has revealed existence of a rainfall maximum around 2100 m height for the NWH region. Similarly, the total seasonal rainy days of EH region was found to have maxima between 1100 and 1400 m height. Analyses of the spatially scattered station rainfall observation for the NWH region showed that the strong periods of ISO modes exist around 747.9 (±131.7) m and 2227.2 (±100.2) m heights. Over the EH region, the dominant modes of the monsoon ISO were found to be centred around 1200 m. Significant alterations of strong and weak phases of monsoon ISO as a response to altitudinal variation in the mountain surface were observed when latitudinal transect-wise variation of monsoon ISO modes were investigated.     

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.     

Erratum to: Climate change projections over India by a downscaling approach using PRECIS

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.     

Estimation of Above Ground Biomass for Central Indian Deciduous Forests Using ALOS PALSAR L-Band Data

Reliable and accurate estimates of tropical forest above ground biomass (AGB) are important to reduce uncertainties in carbon budgeting. In the present study we estimated AGB of central Indian deciduous forests of Madhya Pradesh (M.P.) state, India, using Advanced Land Observing Satellite – Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR) L-band data of year 2010 in conjunction with field based AGB estimates using empirical models. Digital numbers of gridded 1?×?1° dual polarization (HH & HV) PALSAR mosaics for the study area were converted to normalized radar cross section (sigma naught - σ⁰). A total of 415 sampling plots (0.1 ha) data collected over the study area during 2009–10 was used in the present study. Plot-level AGB estimates using volume equations representative to the study area were computed using field inventory data. The plot-level AGB estimates were empirically modeled with the PALSAR backscatter information in HH, HV and their ratios from different forest types of the study area. The HV backscatter information showed better relation with field based AGB estimates with a coefficient of determination (R²) of 0.509 which was used to estimate spatial AGB of the study area. Results suggested a total AGB of 367.4 Mt for forests of M.P. state. Further, validation of the model was carried out using observed vs. predicted AGB estimates, which suggested a root mean square error (RMSE) of ±19.32 t/ha. The model reported robust and defensible relation for observed vs. predicted AGB values of the study area.