@article{sims_raman_2019, title={Observed interactions between boundary-layer mesoscale frontal features during summers in the Carolinas coastal region of eastern USA}, volume={131}, ISSN={["1436-5065"]}, DOI={10.1007/s00703-019-0655-4}, number={5}, journal={METEOROLOGY AND ATMOSPHERIC PHYSICS}, author={Sims, Aaron P. and Raman, Sethu}, year={2019}, month={Oct}, pages={1509–1527} }
 @article{neufeld_keinath_gugino_mcgrath_sikora_miller_ivey_langston_dutta_keever_et al._2018, title={Predicting the risk of cucurbit downy mildew in the eastern United States using an integrated aerobiological model}, volume={62}, ISSN={["1432-1254"]}, url={http://europepmc.org/abstract/med/29177798}, DOI={10.1007/s00484-017-1474-2}, abstractNote={Cucurbit downy mildew caused by the obligate oomycete, Pseudoperonospora cubensis, is considered one of the most economically important diseases of cucurbits worldwide. In the continental United States, the pathogen overwinters in southern Florida and along the coast of the Gulf of Mexico. Outbreaks of the disease in northern states occur annually via long-distance aerial transport of sporangia from infected source fields. An integrated aerobiological modeling system has been developed to predict the risk of disease occurrence and to facilitate timely use of fungicides for disease management. The forecasting system, which combines information on known inoculum sources, long-distance atmospheric spore transport and spore deposition modules, was tested to determine its accuracy in predicting risk of disease outbreak. Rainwater samples at disease monitoring sites in Alabama, Georgia, Louisiana, New York, North Carolina, Ohio, Pennsylvania and South Carolina were collected weekly from planting to the first appearance of symptoms at the field sites during the 2013, 2014, and 2015 growing seasons. A conventional PCR assay with primers specific to P. cubensis was used to detect the presence of sporangia in rain water samples. Disease forecasts were monitored and recorded for each site after each rain event until initial disease symptoms appeared. The pathogen was detected in 38 of the 187 rainwater samples collected during the study period. The forecasting system correctly predicted the risk of disease outbreak based on the presence of sporangia or appearance of initial disease symptoms with an overall accuracy rate of 66 and 75%, respectively. In addition, the probability that the forecasting system correctly classified the presence or absence of disease was ≥ 73%. The true skill statistic calculated based on the appearance of disease symptoms in cucurbit field plantings ranged from 0.42 to 0.58, indicating that the disease forecasting system had an acceptable to good performance in predicting the risk of cucurbit downy mildew outbreak in the eastern United States.}, number={4}, journal={INTERNATIONAL JOURNAL OF BIOMETEOROLOGY}, author={Neufeld, K. N. and Keinath, A. P. and Gugino, B. K. and McGrath, M. T. and Sikora, E. J. and Miller, S. A. and Ivey, M. L. and Langston, D. B. and Dutta, B. and Keever, T. and et al.}, year={2018}, month={Apr}, pages={655–668} }
 @article{sims_alapaty_raman_2017, title={Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain-Fritsch Cumulus Parameterization}, volume={145}, ISSN={["1520-0493"]}, DOI={10.1175/mwr-d-16-0047.1}, abstractNote={ Two mesoscale circulations, the Sandhills circulation and the sea breeze, influence the initiation of deep convection over the Sandhills and the coast in the Carolinas during the summer months. The interaction of these two circulations causes additional convection in this coastal region. Accurate representation of mesoscale convection is difficult as numerical models have problems with the prediction of the timing, amount, and location of precipitation. To address this issue, the authors have incorporated modifications to the Kain–Fritsch (KF) convective parameterization scheme and evaluated these mesoscale interactions using a high-resolution numerical model. The modifications include changes to the subgrid-scale cloud formulation, the convective turnover time scale, and the formulation of the updraft entrainment rates. The use of a grid-scaling adjustment parameter modulates the impact of the KF scheme as a function of the horizontal grid spacing used in a simulation. Results indicate that the impact of this modified cumulus parameterization scheme is more effective on domains with coarser grid sizes. Other results include a decrease in surface and near-surface temperatures in areas of deep convection (due to the inclusion of the effects of subgrid-scale clouds on the radiation), improvement in the timing of convection, and an increase in the strength of deep convection. }, number={11}, journal={MONTHLY WEATHER REVIEW}, author={Sims, Aaron P. and Alapaty, Kiran and Raman, Sethu}, year={2017}, month={Nov}, pages={4381–4399} }
 @article{sims_raman_2016, title={Interaction Between Two Distinct Mesoscale Circulations During Summer in the Coastal Region of Eastern USA}, volume={160}, ISSN={["1573-1472"]}, DOI={10.1007/s10546-015-0125-6}, number={1}, journal={BOUNDARY-LAYER METEOROLOGY}, author={Sims, Aaron P. and Raman, Sethu}, year={2016}, month={Jul}, pages={113–132} }