Seasonal prediction of Indian summer monsoon: Sensitivity to persistent SST

Das, Sukanta; Deb, Sanjib; Kishtawal, C. M.; Pal, P. K.

doi:10.1007/s12040-013-0351-6

Cited by 9 publications

(8 citation statements)

References 19 publications

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“…The current study indicates inter-decadal spatial and temporal variability in the precipitation related to the monsoon onset in Pakistan. The results are consistent with the studies carried out around the globe indicating the changes in the summer monsoon rainfall in South Asia including Pakistan (Das et al 2013;Imran et al 2014;Latif and Syed 2015). Seasonal mean rainfall in south Asia shows interdecadal variability, particularly in terms of declining trend with frequently occurring deficiency in summer monsoon rainfall (Intergovernmental Panel on Climate Change 2014).…”

Section: Discussionsupporting

confidence: 89%

Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan

Ali

Khalid

Kiani

et al. 2019

Asia-Pacific J Atmos Sci

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Pakistan receives huge amount of rainfall during summer monsoon season that provides water replenishment for transition periods, helps in maintaining natural and anthropogenic ecosystems, and increased crop productivity. In this changing world, shifts in summer monsoon onset in Pakistan have been observed that seems to affect the society in general. Therefore, it is vital to address these summer monsoon onset shifts to help policy makings and implementation. The study was carried out to analyse the spatio-temporal variability in summer monsoon onset in four objectively defined regions covering all Pakistan. A total of 35 meteorological stations spreading over four regions (i.e., northern, central east, central west, and southern) were taken in to account and shifts in summer monsoon onset have been calculated for the period of 1971-2010. The analysis is based on the observational data of daily precipitation from 20th Jun-20th July for 40 years. The onset for each year and mean onset for each decade has been calculated for all stations. The data was analysed for homogeneity, spatial and temporal variability of monsoon rainfall has been calculated for all four regions, and station wise monsoon onset has been discussed in detail. The temporal analysis shows that the onset of monsoon has shift towards earlier onset from first week of July to last week of June at most of the stations in which the investigation was carried out during the studied period. The spatial analysis shows that the amount of monsoon precipitation during the onset period has decreased after 1970's in almost all regions. This variability in monsoon onset can have major impacts on rain fed agriculture and cultivation of crops like maize, soybean, rice and sugarcane etc. and will have to revisit the cropping calendar. Keywords Monsoon onset. Spatial variability. Temporal variability. Asian summer monsoon. Monsoon shifts Highlights 1-Observations at 35 meteorological stations were processed for summer monsoon onset in Pakistan 2-Temporal analysis of four decades i.e., 1971-2010 3-Mean monsoon onset has observed a shift over 40 years to an earlier time in Pakistan 4-Total amount of precipitation has decreased over the studied period 5-North eastern region of Pakistan received highest amount of precipitation among all others Responsible Editor: Ashok Karumuri.

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Section: Discussionsupporting

confidence: 89%

Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan

Ali

Khalid

Kiani

et al. 2019

Asia-Pacific J Atmos Sci

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“…(SST) and sea-ice concentrations are added with the latest persistent anomaly observed at the time the experiment was conducted. It has been assumed that the SST and sea-ice concentrations are persistent in nature over the forecasted time period; however, a sensitivity study of these persistent SSTs has also been done for a few monsoon years (DAS et al 2013).…”

Section: Seasonal Forecast Of Ism Rainfallmentioning

confidence: 99%

“…Presently, the atmosphere-land component of the CCSM model is used (DAS et al 2011) for experimental seasonal forecast at SAC. Every year upon completion of the summer monsoon season, the experimental seasonal and 30-day forecasts have been assessed with actual observations, and shortcomings in the forecast system have been identified for improvement in the subsequent year's forecasts (DAS et al 2012(DAS et al , 2013. On completion of 5 years since 2009, it is required to quantify the overall validation of the forecast system, and to assess the scope for further improvements of these experimental seasonal forecasts over time, if any.…”

Section: Introductionmentioning

confidence: 99%

Validation of Seasonal Forecast of Indian Summer Monsoon Rainfall

Das

Deb

Kishtawal

et al. 2015

Pure Appl. Geophys.

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The experimental seasonal forecast of Indian summer monsoon (ISM) rainfall during June through September using Community Atmosphere Model (CAM) version 3 has been carried out at the Space Applications Centre Ahmedabad since 2009. The forecasts, based on a number of ensemble members (ten minimum) of CAM, are generated in several phases and updated on regular basis. On completion of 5 years of experimental seasonal forecasts in operational mode, it is required that the overall validation or correctness of the forecast system is quantified and that the scope is assessed for further improvements of the forecast over time, if any. The ensemble model climatology generated by a set of 20 identical CAM simulations is considered as the model control simulation. The performance of the forecast has been evaluated by assuming the control simulation as the model reference. The forecast improvement factor shows positive improvements, with higher values for the recent forecasted years as compared to the control experiment over the Indian landmass. The Taylor diagram representation of the Pearson correlation coefficient (PCC), standard deviation and centered root mean square difference has been used to demonstrate the best PCC, in the order of 0.74-0.79, recorded for the seasonal forecast made during 2013. Further, the bias score of different phases of experiment revealed the fact that the ISM rainfall forecast is affected by overestimation in predicting the low rain-rate (less than 7 mm/day), but by underestimation in the medium and high rain-rate (higher than 11 mm/day). Overall, the analysis shows significant improvement of the ISM forecast over the last 5 years, viz. 2009-2013, due to several important modifications that have been implemented in the forecast system. The validation exercise has also pointed out a number of shortcomings in the forecast system; these will be addressed in the upcoming years of experiments to improve the quality of the ISM prediction.

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“…Recently, Sen Roy et al (2012) independently compared this rainfall product with Kalpana-1 GPI and TRMM Multisatellite Precipitation Analysis (TMPA) estimates and showed that IMSRA is closer to the TMPA estimate in terms of areal spread, geometric shape and location of rainfall areas, as compared to the GPI technique, and is capable of short-period rainfall estimation. This algorithm is also operational at the IMD since 2010 and is used for various agricultural and hydro-meteorological applications and verification of numerical model rainfall outputs Das et al, 2013;Mahesh et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

Gairola¹,

Prakash²,

Pal³

2015

Atmósfera

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RESUMENEn este trabajo se busca calcular la precipitación en la región del monzón de la India mediante el uso sinérgico de datos pluviométricos y del algoritmo multiespectral de precipitación del Sistema Nacional de Satélites de la India (IMSRA, por sus siglas en inglés), obtenido mediante el satélite geostacionario -temporales del satélite Kalpana-1, así como de estimaciones pluviométricas precisas. Se realiza un análisis progresiva se aplica a una resolución de 1º × 1º determinada por el análisis de autocorrelación espacial. Los resultados se comparan con cuatro productos multisatelitales independientes de precipitación global: el mapeo satelital global de precipitación; productos de monitoreo de precipitación en tiempo casi real y para investigación del análisis multisatelital de precipitación de la Misión de Medición de Lluvias Tropicales, y el producto del Proyecto Global sobre la Climatología de las Precipitaciones. El análisis objetivo de las estimaciones de precipitación muestra una notable mejoría respecto de las estimaciones basadas sólo en mediciones satelitales en el sur de la India. La comparación con observaciones pluviométricas independientes también muestra una considerable mejoría en términos de correlación, sesgo y error cuadrático medio, especialmente en regiones con buena densidad de mediciones de precipitación. Los resultados globales demuestran que el uso sinérgico de mediciones satelitales e in situ tiene el potencial de facilitar estimaciones de precipitación más exactas en la región del monzón de la India. ABSTRACTIn this paper, an attempt has been made to estimate rainfall over the Indian monsoon region by the synergistic use of the geostationary Kalpana-1 satellite-derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall -lutions of the Kalpana-1 satellite and accurate rainfall estimates from rain gauges. A preliminary analysis is done for the southwest monsoon season of 2010 at a daily scale. The successive correction method is applied Atmósfera 28(1), 51-61 (2015) doi: 10.20937/ATM.2015.28.01.05 © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias de la Atmósfera. This is an open access article under the CC BY-NC-ND License (http://creativecommons.org/licenses/by-nc-nd/4.0/). 52 R. M. Gairola et al.at a 1º latitude × 1º longitude resolution determined by the spatial autocorrelation analysis. Results are compared with four independent global multisatellite rainfall products, namely the Global Satellite Mapping of Precipitation, the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis near-real time and research version rainfall monitoring products, and the Global Precipitation Climatology Project rainfall product. The objectively analyzed rainfall estimates show noticeable improvement over the satellite-based rainfall estimates alone over southern India. Comparison with independent rain gauge observations shows a considerable improvement in terms of correlation, bias and root-mean-square error after objective analysis, especially over t...

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Seasonal prediction of Indian summer monsoon: Sensitivity to persistent SST

Cited by 9 publications

References 19 publications

Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan

Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan

Validation of Seasonal Forecast of Indian Summer Monsoon Rainfall

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

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