Mean state and interannual variability of the Indian summer monsoon simulation by NCEP CFSv2

Shukla, Rahul; Huang, Bohua

doi:10.1007/s00382-015-2808-6

Cited by 25 publications

(21 citation statements)

References 58 publications

(77 reference statements)

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“…The FIR also has a positive wind speed bias of up to 4.0 m/s in the southern tropical Pacific Ocean (145°–190°E, 15°–5°S) and central Indian Ocean. Consistent with our previous studies (Shukla and Huang, ), the easterly wind over the central Indian Ocean turns equatorwards farther east than in observations, which generates excessive convergence over the eastern equatorial Indian Ocean (not shown).…”

Section: Sensitivity Of Mean Summer Simulation To Initial Seasonsupporting

confidence: 92%

“…() found that CGCMs better reproduce the SST–rainfall relationship over the warm water in the Indo‐western Pacific than atmospheric models with prescribed SST do. Many previous studies have also demonstrated the importance of atmosphere–ocean interaction in the long‐term simulations and seasonal reforecasts (e.g., El Niño–Southern Oscillation [ENSO]) using the National Centers of Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2; see, e.g., Saha et al ., ; Kim et al ., ; Peng et al ., ; Zuo et al ., ; Shukla and Huang, ; He et al ., ; Shukla et al ., ; Huang et al ., ; Shin et al ., , and references therein).…”

Section: Introductionmentioning

confidence: 99%

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Climatological influence of Eurasian winter surface conditions on the Asian and Indo‐Pacific summer circulation in the NCEP CFSv2 seasonal reforecasts

Shukla

Huang

Dirmeyer

et al. 2019

Intl Journal of Climatology

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This study evaluates the possible influence of the winter surface conditions in Eurasia on the summer circulation over the Asian continent and Indo‐Pacific region. We have analysed multi‐seasonal ensemble reforecasts for 30 years (1979–2008) using the National Centers for Environmental Prediction Climate Forecast System version 2 initialized at the beginning of each month from January to May. It is found that the reforecasts initialized in winter (e.g., February) overestimate the snow cover fraction, depth and water equivalent, as well as surface albedo in the excessively snow‐covered portion of Eurasia from March to June. These biases are generated and perpetuated by a snow‐albedo feedback, leading to excessive upwards shortwave radiation reflected from the overly snow‐covered surface and an intense cold bias from the surface to mid‐troposphere. Originating over land, the cold bias is extended eastwards over the northwestern North Pacific by the advection of prevailing westerly winds. The cold air temperature in the broad mid‐latitude Asian‐Pacific region causes significantly lower geopotential heights at pressure levels in the middle and upper troposphere and thus increases the upper‐level westerly winds on its southern flank over the Asian continent and Indo‐Pacific. A slower than observed snow melting rate helps the winter cold bias persists well into the summer season in these runs. As a result, compared with the reforecasts initialized in spring (e.g., May), winter‐initialized reforecasts feature lower geopotential heights in the upper troposphere over Eurasia and a stronger subtropical jet over the Asian continent and the North Pacific from May to September, especially in early summer. The CFSv2 reforecasts in both sets of cases have too little total cloud fraction over Eurasia during June–August, leading to enhanced downwards shortwave radiation.

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Section: Sensitivity Of Mean Summer Simulation To Initial Seasonsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Climatological influence of Eurasian winter surface conditions on the Asian and Indo‐Pacific summer circulation in the NCEP CFSv2 seasonal reforecasts

Shukla

Huang

Dirmeyer

et al. 2019

Intl Journal of Climatology

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“…This study presents the different characteristics of ensemble spread between drought and flood years of ISM using 20-member ensemble seasonal reforecasts for 58 years . Consistent with previous studies (Shukla & Huang, 2015;Shukla et al, 2017;Sahana & Ghosh, 2018), we have also found that April-initialized CFSv2 reforecasts underestimate summer rainfall over Indian landmass.…”

Section: Summary and Discussionsupporting

confidence: 92%

“…Whereas CFSv2 seems to capture the main GPCP precipitation pattern over India seen in Figure 1a, including enhanced rainfall over western Ghats of India, eastern and central India (not shown), the model quantitatively demonstrates a severe dry bias over northern India with precipitation deficit up to 4.5 mm/day and an excessive rainfall in the central Indian Ocean and in subtropical northern Pacific Ocean (Figure 1b). The cause for the 10.1029/2019GL086586 enhancement and northward shift of intertropical convergence zone near 10°N in CFSv2 model is discussed in Shukla and Huang (2015). The reforecasts depict a large dry bias over Indian landmass with respect to IMD rainfall, but magnitude of rainfall bias over southern eastern India is negligible (Figures 1c and 1d).…”

Section: Resultsmentioning

confidence: 93%

“…There may be several causes for underestimation of summer rainfall over Indian landmass in the reforecasts. It is found that model reforecasts depict a cold bias over the Arabian Sea (Figure 1h) and also produce excessive surface convergence over the equatorial Indian Ocean (not shown), which may reduce the moisture transport toward the Indian subcontinent region (Levine et al, 2013;Shukla & Huang, 2015). Figure 2 shows year-to-year variation of ISMRI for ensemble mean and all members, ESP and NINO3.4 SST index for 1958-2015.…”

Section: Resultsmentioning

confidence: 99%

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Distinguishing Spread Among Ensemble Members Between Drought and Flood Indian Summer Monsoon Years in the Past 58 Years (1958–2015) Reforecasts

Shukla

Shin

2020

Geophysical Research Letters

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This study examines the different characteristics of ensemble spread (ESP) between drought and flood years of Indian summer monsoon (ISM) during June to September mean using the Climate Forecast System version 2 (CFSv2). We have analyzed a set of 20‐member ensemble seasonal reforecasts for 1958–2015 using CFSv2 initialized in April. The ESP of ISM Rainfall (ISMR) is negatively (positively) correlated with ISMR (NINO3.4) index, indicating that ESP in drought ISMR years seems to be larger than that in flood years. The mean value of ESP for drought ISMR years is larger than flood years. The spatial structure of ISMR composite anomalies during drought years shows better agreement with observed rainfall anomalies in comparison to flood years. As a result, smaller ESP in flood years may suggest that ensemble prediction of ISMR in flood years tends to be overconfident and less reliable due to underestimate of forecast uncertainty, compared to drought years.

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Assessment of the simulation of Indian Ocean Dipole in the CESM—Impacts of atmospheric physics and model resolution

Yao

Tang

Chen

et al. 2016

J Adv Model Earth Syst

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This study examines the possible impacts of coupling processes on simulations of the Indian Ocean Dipole (IOD). Emphasis is placed on the atmospheric model resolution and physics. Five experiments were conducted for this purpose, including one control run of the ocean‐only model, four coupled experiments using two different versions of the Community Atmosphere Model (CAM4 and CAM5) and two different resolutions. The results show that the control run could effectively simulate various features of the IOD. The coupled experiments run at the higher resolution yielded more realistic IOD period and intensity than their counterparts at the low resolution. The coupled experiments using CAM5 generally showed a better simulation skill in the tropical Indian SST climatology and phase‐locking than those using CAM4, but the wind anomalies were stronger and the IOD period were longer in the former experiments than in the latter. In all coupled experiments, the IOD intensity was much stronger than the observed intensity, which is attributable to wind‐thermocline depth feedback and thermocline depth‐subsurface temperature feedback. The CAM5 physics seems beneficial for the simulation of summer rainfall over the eastern equatorial Indian Ocean and the CAM4 physics tends to produce less biases over the western equatorial Indian Ocean, whereas the higher resolution tends to generate unrealistically strong meridional winds. The IOD‐ENSO relationship was captured reasonably well in coupled experiments, with improvements in CAM5 relative to CAM4. However, the teleconnection of the IOD‐Indian summer monsoon and ENSO‐Indian summer monsoon was not realistically simulated in all experiments.

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Mean state and interannual variability of the Indian summer monsoon simulation by NCEP CFSv2

Cited by 25 publications

References 58 publications

Climatological influence of Eurasian winter surface conditions on the Asian and Indo‐Pacific summer circulation in the NCEP CFSv2 seasonal reforecasts

Climatological influence of Eurasian winter surface conditions on the Asian and Indo‐Pacific summer circulation in the NCEP CFSv2 seasonal reforecasts

Distinguishing Spread Among Ensemble Members Between Drought and Flood Indian Summer Monsoon Years in the Past 58 Years (1958–2015) Reforecasts

Assessment of the simulation of Indian Ocean Dipole in the CESM—Impacts of atmospheric physics and model resolution

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