Misra, V., & DiNapoli, S. M. (2013). Understanding the wet season variations over Florida.
Clim Dyn, 40(5-6), 1361–1372.
Misra, V., & Li, H. (2014). The seasonal predictability of the Asian summer monsoon in a two-tiered forecast system.
Clim Dyn, 42(9-10), 2491–2507.
Misra, V., & Marx, L. (2009). The coupled seasonal hindcasts of the South American monsoon.
Int. J. Climatol., 29(8), 1101–1115.
Misra, V., Bhardwaj, A., & Mishra, A. (2018). Local onset and demise of the Indian summer monsoon.
Climate Dynamics, 51(5-6), 1609–1622.
Abstract: This paper introduces an objective definition of local onset and demise of the Indian summer monsoon (ISM) at the native grid of the Indian Meteorological Department's rainfall analysis based on more than 100 years of rain gauge observations. The variability of the local onset/demise of the ISM is shown to be closely associated with the All India averaged rainfall onset/demise. This association is consistent with the corresponding evolution of the slow large-scale reversals of upper air and ocean variables that raise the hope of predictability of local onset and demise of the ISM. The local onset/demise of the ISM also show robust internannual variations associated with El Nino and the Southern Oscillation and Indian Ocean dipole mode. It is also shown that the early monsoon rains over northeast India has a predictive potential for the following seasonal anomalies of rainfall and seasonal length of the monsoon over rest of India.
Misra, V., Groenen, D., Bhardwaj, A., & Mishra, A. (2016). The warm pool variability of the tropical northeast Pacific.
Int. J. Climatol., 36(14), 4625–4637.
Misra, V., Mishra, A., & Bhardwaj, A. (2017). High-resolution regional-coupled ocean-atmosphere simulation of the Indian Summer Monsoon.
Int. J. Climatol, 37, 717–740.
Misra, V., Selman, C., Waite, A. J., Bastola, S., & Mishra, A. (2017). Terrestrial and Ocean Climate of the 20th Century. In E. P. Chassignet, J. W. Jones, V. Misra, & J. Obeysekera (Eds.),
Florida's climate: Changes, variations, & impacts (pp. 485–509). Gainesville, FL: Florida Climate Institute.
Misra, V., Stroman, A., & DiNapoli, S. (2013). The rendition of the Atlantic Warm Pool in the reanalyses.
Clim Dyn, 41(2), 517–532.
Palacios-Hernández, E., Carrillo, L., Lavín, M. F., Zamudio, L., & García-Sandoval, A. (2006). Hydrography and circulation in the Northern Gulf of California during winter of 1994-1995.
Continental Shelf Research, 26(1), 82–103.
Petraitis, D. C. (2006).
Long-Term ENSO-Related Winter Rainfall Predictions over the Southeast U.S. Using the FSU Global Spectral Model. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Rainfall patterns over the Southeast U.S. have been found to be connected to the El Niño-Southern Oscillation (ENSO). Warm ENSO events cause positive precipitation anomalies and cold ENSO events cause negative precipitation anomalies. With this level of connection, models can be used to test the predictability of ENSO events. Using the Florida State University Global Spectral Model (FSUGSM), model data over a 50-year period will be evaluated for its similarity to observations. The FSUGSM is a global spectral model with a T63 horizontal resolution (approximately 1.875°) and 17 unevenly spaced vertical levels. Details of this model can be found in Cocke and LaRow (2000). The experiment utilizes two runs using the Naval Research Laboratory (NRL) RAS convection scheme and two runs using the National Centers for Environmental Prediction (NCEP) SAS convection scheme to comprise the ensemble. The simulation was done for 50 years, from 1950 to 1999. Reynolds and Smith monthly mean sea surface temperatures (SSTs) from 1950-1999 provide the lower boundary condition. Atmospheric and land conditions from January 1, 1987 and January 1, 1995 were used as the initial starting conditions. The observational precipitation data being used as the basis for comparison is a gridded global dataset from Willmott and Matsuura (2005). Phase precipitation differences show higher precipitation amounts for El Niño than La Niña in all model runs. Temporal correlations between model runs and the observations show southern and eastern areas with the highest correlation values during an ENSO event. Skill scores validate the findings of the model/observation correlations, with southern and eastern areas showing scores close to zero. Temporal correlations between tropical Pacific SSTs and Southeast precipitation further confirm the model's ability to predict ENSO precipitation patterns over the Southeast U.S. The inconsistency in the SST/precipitation correlations between the models can be attributed to differences in the 200-mb jet stream and 500-mb height anomalies. Slight differences in position and strength for both variables affect the teleconnection between tropical Pacific SSTs and Southeast.