Evaluation of performance of seasonal precipitation prediction at regional scale over India

Mohanty, U. C.; Nageswararao, M. M.; Sinha, P. C.; Nair, Archana; Singh, Ankita; K., R.; Kar, S. C.; Ramesh, K. J.; Singh, K. K.; Ghosh, Kripan; Rathore, L. S.; Sharma, Rajat; Kumar, Arun; Dhekale, B. S.; Maurya, Rajendra P; Sahoo, R. K.; Dash, Guru Prasad

doi:10.1007/s00704-018-2421-9

Cited by 14 publications

(4 citation statements)

References 60 publications

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“…Its variability exhibits rich spectrum, ranging from daily to interannual timescales (e.g., Chiang et al., 2017; Jiang et al., 2013; Webster et al., 1998). The ASM precipitation prediction remains a long‐standing challenge (e.g., Li & Robertson, 2015; Liang & Lin, 2018; Mohanty et al., 2019; Wheeler et al., 2017). Li and Robertson (2015) reported that the prediction skill of the submonthly precipitation in the boreal summer season drops rapidly below 0.3 in the second week for most regions in three global ensemble prediction systems.…”

Section: Introductionmentioning

confidence: 99%

Predictable Pattern of Precipitation Over Asian Summer Monsoon Regions

Tang

2021

Geophysical Research Letters

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Section: Introductionmentioning

confidence: 99%

Predictable Pattern of Precipitation Over Asian Summer Monsoon Regions

Tang

2021

Geophysical Research Letters

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“…Numerous studies have assessed the ability of seasonal dynamical models to simulate and predict precipitation associated with the Asian monsoon on different timescales (Webster et al 1998;Rajeevan et al 2004;Kim et al 2012;Pai et al 2017;Ramu et al 2017;Jain et al 2018;Pillai et al 2018;Mohanty et al 2019). While improvements have been made in predicting the Asian monsoon large scale flow patterns, especially with the introduction of coupled atmosphere-ocean models, providing skilful predictions of seasonal precipitation over South Asia remains a challenge and is an active area of research.…”

Section: Introductionmentioning

confidence: 99%

Diverse skill of seasonal dynamical models in forecasting South Asian monsoon precipitation and the influence of ENSO and IOD

et al. 2023

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The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 dynamical models at forecasting seasonal precipitation totals for 1993–2016 for the southwest (June–July–August–September) and northeast (October–November–December) monsoon seasons at regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan, using identical forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally-averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models exhibit highest skill where correlation between observed precipitation and El Niño Southern Oscillation (ENSO) is highest, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of South Asia during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The Indian Ocean Dipole teleconnection is less pronounced in the southwest monsoon season, whereas the spatial pattern for the northeast monsoon closely resembles that of ENSO. Due to high variability in model skill, we recommend basing the SASCOF forecast on a multi-model ensemble of all models but discounting poorly performing models at the national level.

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“…Forecasters use the verification information in their forecast decision process (Ebert and McBride, 2000). Model verification statistics are used in determining whether model equations need to be updated to improve the model performance (Feldmann et al, 2015, Mohanty et al, 2018and Rehman et al, 2018. This decision is highly dependent on the Quantitative Precipitation Forecast (QPF) skills from the model (Hamill, 1999).…”

Section: Introductionmentioning

confidence: 99%

Visualization and Quantitative Assessment to Verify Precipitation Forecasts Associated with Mid-Latitude Cyclones across the Eastern United States

Williams

Hung

2021

IJG

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Analysis was conducted to verify forecast against observation precipitation associated with mid-latitude cyclones over the Eastern US in winter and spring 2013 using Geographic Information Systems (GIS). The forecast data are day two 24-hour Quantitative Precipitation Forecasts (QPF) produced by the Global Forecast System (GFS) model. The analysis methods produced categorical geographic error maps of hits, misses and false alarms in spatial relation to the mid-latitude cyclones and traditional verification scores for each day. A hypothesis test was also performed to determine if the GFS mean forecast precipitation over the study area is significantly different from the mean observed precipitation during mid-latitude cyclones. The spatial verification maps, as an analytical and visualization tool, provided evidences on geographical relationship between correct predictions (hits and correct negatives) and incorrect predictions (misses and false alarms). Working together with quantitative scores and hypothesis test, spatial verification maps reveal that the GFS model has a tendency to over forecast precipitation coverage associated with mid-latitude cyclones over the Eastern US and often moves the mid-latitude cyclones too fast.

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Evaluation of performance of seasonal precipitation prediction at regional scale over India

Cited by 14 publications

References 60 publications

Predictable Pattern of Precipitation Over Asian Summer Monsoon Regions

Predictable Pattern of Precipitation Over Asian Summer Monsoon Regions

Diverse skill of seasonal dynamical models in forecasting South Asian monsoon precipitation and the influence of ENSO and IOD

Visualization and Quantitative Assessment to Verify Precipitation Forecasts Associated with Mid-Latitude Cyclones across the Eastern United States

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