Bhardwaj, A., & Misra, V. (2019). Monitoring the Indian Summer Monsoon Evolution at the Granularity of the Indian Meteorological Sub-divisions using Remotely Sensed Rainfall Products.
Remote Sensing, 11(9), 1080.
Abstract: We make use of satellite-based rainfall products from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to objectively define local onset and demise of the Indian Summer Monsoon (ISM) at the spatial resolution of the meteorological subdivisions defined by the Indian Meteorological Department (IMD). These meteorological sub-divisions are the operational spatial scales for official forecasts issued by the IMD. Therefore, there is a direct practical utility to target these spatial scales for monitoring the evolution of the ISM. We find that the diagnosis of the climatological onset and demise dates and its variations from the TMPA product is quite similar to the rain gauge based analysis of the IMD, despite the differences in the duration of the two datasets. This study shows that the onset date variations of the ISM have a significant impact on the variations of the seasonal length and seasonal rainfall anomalies in many of the meteorological sub-divisions: for example, the early or later onset of the ISM is associated with longer and wetter or shorter and drier ISM seasons, respectively. It is shown that TMPA dataset (and therefore its follow up Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG)) could be usefully adopted for monitoring the onset of the ISM and therefore extend its use to anticipate the potential anomalies of the seasonal length and seasonal rainfall anomalies of the ISM in many of the Indian meteorological sub-divisions. View Full-Text
Cocke, S., Boisserie, M., & Shin, D. - W. (2013). A coupled soil moisture initialization scheme for the FSU/COAPS climate model.
Inverse Problems in Science and Engineering, 21(3), 420–437.
Guimond, S. R. (2007).
A diagnostic study of the effects of trough interactions on tropical cyclone QPF. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A composite study is presented analyzing the influence of upper-tropospheric troughs on the evolution of precipitation in twelve Atlantic tropical cyclones (TCs) between the years 2000 � 2005. The TRMM Multi-Satellite Precipitation Analysis (TMPA) is used to examine the enhancement of precipitation within a 24 h window centered on trough interaction (TI) time in a shear-vector relative coordinate system. Eddy angular momentum flux convergence (EFC) computed from European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses is employed to objectively determine the initiation of a TI while adding insight, along with vertical wind shear, into the intensification of TC vortices. The relative roles of the dynamics (EFC and vertical wind shear) and thermodynamics (moist static energy potential) in TIs are outlined in the context of precipitation enhancement that provides quantitative insight into the “good trough”/“bad trough” paradigm. The largest precipitation rates and enhancements are found in the down-shear left quadrant of the storm, consistent with previous studies of convective asymmetries. Maximum mean enhancement values of 1.4 mm/h are found at the 200 km radius in the down-shear left quadrant. Results indicate that the largest precipitation enhancements occur with “medium” TIs; comprised of EFC values between 17 � 22 (m/s)/day and vertical wind shear Sensitivity tests on the upper vertical wind shear boundary reveal the importance of using the tropopause for wind shear computations when a TC enters mid-latitude regions. Changes in radial mean precipitation ranging from 29 � 40 % across all storm quadrants are found when using the tropopause as the upper boundary on the shear vector. Tests on the lower boundary using QuikSCAT ocean surface wind vectors expose large sensitivities on the precipitation ranging from 42 � 60 % indicating that the standard level of 850 hPa, outside of the boundary layer in most storms, is more physically reliable for computing vertical wind shear. These results should help to improve TC quantitative precipitation forecasting (QPF) as operational forecasters routinely rely on crude statistical methods and rules of thumb for forecasting TC precipitation.
Lim, Y. - K., & Kim, K. - Y. (2006). A New Perspective on the Climate Prediction of Asian Summer Monsoon Precipitation.
J. Climate, 19(19), 4840–4853.
Lim, Y. - K., Cocke, S., Shin, D. W., Schoof, J. T., LaRow, T. E., & O'Brien, J. J. (2010). Downscaling large-scale NCEP CFS to resolve fine-scale seasonal precipitation and extremes for the crop growing seasons over the southeastern United States.
Clim Dyn, 35(2-3), 449–471.
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.
Selman, C., & Misra, V. (2015). Simulating diurnal variations over the southeastern United States.
J. Geophys. Res. Atmos., 120(1), 180–198.
Selman, C., Misra, V., Stefanova, L., Dinapoli, S., & Smith III, T. J. (2013). On the twenty-first-century wet season projections over the Southeastern United States.
Reg Environ Change, 13(S1), 153–164.
Selman, C. M. (2015).
Simulating the Impacts and Sensitivity of the Southeastern United States Climatology to Irrigation. Ph.D. thesis, Florida State University, Tallahassee, FL.
Shin, D. W. (2003). Short- to medium-range superensemble precipitation forecasts using satellite products: 1. Deterministic forecasting.
J. Geophys. Res., 108(D8).