Publications

Sub judice

Sun, R., S. Sanikommu, A. C. Subramanian, M. R. Mazloff, B. D. Cornuelle, G. Gopalakrishnan, A. J. Miller, I. Hoteit (2024): Enhanced Regional Ocean Ensemble Data Assimilation Through Atmospheric Coupling in the SKRIPS Model. Ocean Modeling.
Yin, Z., A. R. Herrington, R. Tri Datta, A. C. Subramanian, J. T. M. Lenaerts, and A. Gettelman (2024): Improved Understanding of Multicentury Greenland Ice Sheet Response to Strong Warming in the Coupled CESM2‐CISM2 with Regional Grid Refinement. JAMES, sub judice.
Ali S., O. Faruque, Y. Huang, Md. Osman Gani, A. C. Subramanian, N-J Schlegel, J. Wang (2024): Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference, ICMLA.
Cannon, F.; R. Weihs; D. Steinhoff; C. Papadopoulus; B. Kawzenuk; P. Mulrooney; M. Zheng; P. Yao; A. Cobb; A. Wilson; A. Martin; D. Reynolds; A. C. Subramanian; L. Delle Monache; F. M. Ralph (2022): Precipitation Forecast Skill and Uncertainty Over California Watersheds in a High-Resolution Ensemble, Mon. Wea. Rev., sub judice.

Published

[90.] Li, L., Cannon, F., Mazloff, M. R., Subramanian, A. C., Wilson, A. M., & Ralph, F. M. (2024). Impact of atmospheric rivers on Arctic sea ice variations. The Cryosphere, 18(1), 121-137. https://doi.org/10.5194/tc-18-121-2024

[89.] Higgins, T. B., A. C. Subramanian, W. E. Chapman, D. Lavers, and A. C. Winters (2024) : Subseasonal Potential Predictability of Horizontal Water Vapor Transport and Precipitation Extremes in the North Pacific. Weather and Forecasting, In Press.

[88.] Eddebbar, Y., D. Whitt, A. Verdy, M. Mazloff, A. C. Subramanian and M. Long (2024): Eddy-Mediated Mixing of Oxygen in the Equatorial Pacific, JGR-Oceans, In Press.

[87.] Du, D., A. C. Subramanian, W. Han, U. Ninad and J. Runge : Causal Analysis Discovers an Enhanced Impact of Tropical Western Pacific on Indian Summer Monsoon Subseasonal Anomalies, GRL, In Press.

[86.] Du, D., Subramanian, A.C., Han, W., Chapman, W.E., Weiss, J.B. and Bradley, E., 2023. Increase in MJO predictability under global warming. Nature Climate Change, 14, 68–74 (2024). https://doi.org/10.1038/s41558-023-01885-0

[85.] Verdy, A., Mazloff, M., Cornuelle, B. D., Subramanian, A. C. (2023): Balancing volume, temperature, and salinity budgets in the tropical Pacific Ocean state estimate, JGR Oceans, https://doi.org/10.1029/2022JC019576.

[84.] Sun, R., Cobb, A., Villas Bôas, A. B., Langodan, S., Subramanian, A. C., Mazloff, M. R., Cornuelle, B. D., Miller, A. J., Pathak, R., and Hoteit, I. (2023): Waves in SKRIPS: WaveWatch III coupling implementation and a case study of cyclone Mekunu, Geosci. Model Dev., https://doi.org/10.5194/gmd-16-3435-2023.

[83.] H-H. Wei, Subramanian, A. C., K. B. Karnauskas, D. Du, C. A. DeMott, M. R. Mazloff, M. A. Balmaseda, F. Vitart, and B. Sarojini (2023): Tropical Pacific subseasonal forecast: the role of mean state biases, model errors, and ocean data assimilation. QJRMS, In Press.

[82.] Howard, L., A. C. Subramanian, Hoteit, I., (2023) A Machine Learning Augmented Data Assimilation Method for High-Resolution Observation, JAMES, In Press.

[81.] Shulgina, T.; A. Gershunov; B. Hatchett; K. Guirguis; A. C. Subramanian; S. A. Margulis; Y. Fang; D. R. Cayan; D. W. Pierce; M. Dettinger; M. L. Anderson; F. M. Ralph (2022): Observed and projected changes in snowline and snow accumulation in California’s Sierra Nevada and Cascade Ranges, Climate Dynamics, In Press.

[80.] Higgins, T. B., A. C. Subramanian, Andre Graubner, Lukas Kapp-Schwoerer, Peter A. G. Watson, Sarah Sparrow, Karthik Kashinath, Sol Kim, Luca Delle Monache, Will Chapman (2022): Using Deep Learning for a High-Precision Analysis of Atmospheric Rivers in a High-Resolution Large Ensemble Climate Dataset, JAMES, In Press.

[79.] Zhang, Z., DeFlorio, M. J., Monache, L. D., Subramanian, A. C. , Ralph, F. M., Waliser, D. E., Zheng, M., Guan, B., Goodman, A., Molod, A. M., Vitart, F., Kumar, A., Lin, H. (2023): Multi-Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated with Atmospheric Rivers over the Western U.S., JGR-Atmospheres, In Press.

[78.] B. Ait-El-Fquih, A. C. Subramanian, I. Hoteit (2022): An Ensemble Filtering Approach for State-Parameter Estimation of Stochastic Climate Models, QJRMS, In Press.

[77.] Ghosh, S., Miller, A. J., Subramanian, A. C., Bhatla, R., Das, S. (2023): Signals of northward propagating Monsoon Intraseasonal Oscillations (MISO) in the RegCM4.7 CORDEX-CORE simulation over South Asia domain, Climate Dynamics, In Press.

[76.] Castellano, C. M., M. J. DeFlorio, P. B. Gibson, L. Delle Monache, J. F. Kalansky, J. Wang, K. Guirguis, A. Gershunov, F. M. Ralph, A. C. Subramanian, M. L. Anderson (2022): Development of a Statistical Subseasonal Forecast Tool to Predict California Atmospheric Rivers and Precipitation Based on MJO and QBO Activity, JGR Atmos., In Press.

[75.] Reynolds, C.; R. E. Stone; J. D. Doyle; N. L. Baker; A. M. Wilson; F. M. Ralph; D. A. Lavers; A. C. Subramanian; L. Centurioni (2022): Impacts of Northeastern Pacific Buoy Surface Pressure Observations, Mon. Wea.Rev., In Press.

[74.] Cobb, A.; F.M. Ralph; V. Tallapragada; A. M. Wilson; C. A. Davis; L. Delle Monache; J. D. Doyle; F. Pappenberger; C. A. Reynolds; A. C. Subramanian; P. G. Black; F. Cannon; C. Castellano; J. M. Cordeira; J. S. Haase; C. Hecht; B. Kawzenuk; D. A. Lavers; M. Murphy; J. Parrish; R. Rickert; J. J. Rutz; R. Torn; X. Wu; M. Zheng (2021): Atmospheric River Reconnaissance 2021: A Review, Weather and Forecasting, In Press.

[73.] Chandra, V., Sandeep, S., Suhas, E., & Subramanian, A. C. (2022). Weakening of Indian summer monsoon synoptic activity in response to polar sea ice melt induced by albedo reduction in a climate model. Earth and Space Science, 9, e2021EA002185. https://doi.org/10.1029/2021EA002185.

[72.] Simmonds, E.G., Adjei, K.P., Andersen, C.W., Aspheim, J.C.H., Battistin, C., Bulso, N., Christensen, H., Cretois, B., Cubero, R., Davidovich, I.A. and Dickel, L., Subramanian A. C. (2022): Insights into the quantification and reporting of model-related uncertainty across different disciplines. Iscience, p.105512.

[71.] Du, D., A. C. Subramanian, W. Han, H-H Wei, B. B. Sarojini, M. Balmaseda, F. Vitart (2022): Assessing the Impact of Ocean In-situ Observations on MJO Propagation across the Maritime Continent in ECMWF Subseasonal Forecasts, JAMES, In Press.

[70.] Guirguis, K.; A. Gershunov; B. Hatchett; T. Shulgina; M. J. DeFlorio; A. C. Subramanian, J. Guzman-Morales; R. Aguilera; R. Clemesha; T. W. Corringham; L. Delle Monache; D. Reynolds; A. Tardy; I. Small; F. M. Ralph (2021): Weather Patterns Driving Atmospheric Rivers, Santa Ana Winds, Floods, and Wildfires During California Winters Provide Evidence for Increasing Fire Risk. Climate Dynamics, In Press.

[69.] Eddebbar, Y. E., A. C. Subramanian, D. Whitt, M. C. Long, A. Verdy, M. Mazloff, and M. Merrifield (2021) : Seasonal Modulation of Dissolved Oxygen in the Equatorial Pacific by Tropical Instability Vortices. JGR-Oceans, In Press.

[68.] Chapman, W. E., L. Delle Monache, S. Alessandrini, A. C. Subramanian, F. M. Ralph, S-P Xie, S. Lerch, N. Hayatbini (2021) : Machine Learning Methods for Probabilistic Weather Predictions from Deterministic Forecasts. MWR, In Press.

[67.] Sun, R., Villas Bôas, A. B., Subramanian, A. C., Cornuelle, B. D., Mazloff, M. R., Miller, A. J., et al. (2022). Focusing and defocusing of tropical cyclone generated waves by ocean current refraction. Journal of Geophysical Research: Oceans, 127, e2021JC018112. https://doi.org/10.1029/2021JC018112

[66.] Zheng, M., L. Delle Monache, B. D. Cornuelle, F. M. Ralph, V. S. Tallapragada, A. C. Subramanian, J. S. Haase, Z. Zhang, X. Wu, M. J. Murphy, T. B. Higgins, L. DeHaan (2021) : Improved Forecast Skill through the Assimilation of Dropsonde Observations from the Atmospheric River Reconnaissance Program. JGR-Atmosphere, In Press.

[65.] Pathak, R., H. P. Dasari, S. El Mohtar, A. C. Subramanian, S. Sahany, S. K. Mishra, O. Knio and I. Hoteit (2021) : Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6). Frontiers in Climate Predictions and Projections, In Press.

[64.] Shroyer, E., Tandon, A., Sengupta, D., Fernando, H. J., Lucas, A. J., Farrar, J. T., Chattopadhyay, R., de Szoeke, S., Flatau, M., Rydbeck, A., Wijesekera, H., McPhaden, M., Seo, H., Subramanian, A., Venkatesan, R., Joseph, J., Ramsundaram, S., Gordon, A. L., Bohman, S. M., Pérez, J., Simoes-Sousa, I. T., Jayne, S. R., Todd, R. E., Bhat, G.S., Lankhorst, M., Schlosser, T., Adams, K., Jinadasa, S., Mathur, M., Mohapatra, M., Rao, E. P. R., Sahai, A. K., Sharma, R., Lee, C., Rainville, L., Cherian, D., Cullen, K., Centurioni, L. R., Hormann, V., MacKinnon, J., Send, U., Anutaliya, A., Waterhouse, A., Black, G. S., Dehart, J. A., Woods, K. M., Creegan, E., Levy, G., Kantha, L. H., & Subrahmanyam, B. (2021). Bay of Bengal Intraseasonal Oscillations and the 2018 Monsoon Onset, Bulletin of the American Meteorological Society (published online ahead of print 2021).

[63.] Chapman, W., A. C. Subramanian, S-P Xie, F. M. Ralph, M. D. Sierks, Y. Kamae (2020): Intraseasonal Modulation of ENSO teleconnections: Implications for Predictability in North America. J. Clim., In Press.

[62.] Haupt, S. E., W. Chapman, S. V. Adams, C. Kirkwood, J. S. Hosking, N. H. Robinson, S. Lerch, A. C. Subramanian, (2020): Towards Implementing AI Post-processing in Weather and Climate: Proposed Actions from the Oxford 2019 Workshop. Phil. Trans. of the RMS A, In Press.

[61.] Wei, H-H., A. C. Subramanian, K. Karnauskas, C. A. DeMott; M. R. Mazloff; M. A. Balmaseda, (2020): Tropical Pacific Air-sea Interaction Processes and Biases in CESM2 and their Relation to El Nino Development. JGR Oceans., In Press.

[60.] Sun, R., A. C. Subramanian, B. D. Cornuelle, M. Mazloff, A. J. Miller, F. M. Ralph, H. Seo and I. Hoteit (2020): The role of air-sea interactions in atmospheric river events: Case studies using the SKRIPS regional coupled model. JGR-Atmospheres, In Press.

[59.] Zheng, M., L. D. Monache, X. Wu, F. M. Ralph, B. D. Cornuelle, V. Tallapragada, J. S. Haase, A. M. Wilson, M. Mazloff, A. C. Subramanian, F. Cannon (2020): Data Gaps within Atmospheric Rivers over the Northeastern Pacific, BAMS, https://doi.org/10.1175/BAMS-D-19-0287.1.

[58.] Guirguis, K., A. Gershunov, M. DeFlorio, T. Shulgina, L. D. Monache, A. C. Subramanian, T. Corringham, M. Ralph (2020): Four North Pacific circulation regimes and their relationship to California precipitation on daily to seasonal timescales, GRL, 47(16), p.e2020GL087609.

[57.] Fredriksen, H-B., J. Berner, A. C. Subramanian, A. Capotondi (2020): How Does El Niño Southern Oscillation Change Under Global Warming - A First Look at CMIP6, GRL, 47, e2020GL090640. https://doi.org/10.1029/2020GL090640.

[56.] Beal, L., et al., A. C. Subramanian (2020): A roadmap to IndOOS-2: Better observations of the rapidly-warming Indian Ocean, BAMS, doi: https://doi.org/10.1175/BAMS-D-19-0209.1.

[55.] Hoteit, I., et al., A. C. Subramanian (2019): Towards an End-to-End Analysis and Prediction System for Weather, Climate, and Marine Applications in the Red Sea, BAMS, doi: https://doi.org/10.1175/BAMS-D-19-0005.1.

[54.] Meehl, G., et al., A. C. Subramanian (2019): Initialized Earth system prediction from subseasonal to decadal timescales, Nature Reviews, In Press.

[53.] Lavers, D., N. B. Ingleby, A. C. Subramanian, D. Richardson, F. M. Ralph, J. D. Doyle, C. Reynolds, R. D. Torn, M. J. Rodwell, V. Tallapragada, F. Pappenberger, (2019): Forecast Errors and Uncertainties in Atmospheric Rivers, Weather and Forecasting, 35(4), pp.1447-1458.

[52.] Ralph, F.M., Cannon, F., Tallapragada, V., Davis, C.A., Doyle, J.D., Pappenberger, F., Subramanian, A., Wilson, A.M., Lavers, D.A., Reynolds, C.A. and Haase, J.S., 2020. West Coast forecast challenges and development of atmospheric river reconnaissance. Bulletin of the American Meteorological Society, 101(8), pp.E1357-E1377.

[51.] Gagne, D. J., H. Christensen, A. C. Subramanian, A. Monahan (2019): Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model, JAMES, 12, e2019MS001896. https://doi.org/10.1029/2019MS001896.

[50.] Raboudi, N. F., B. Ait-El-Fquih, A. C. Subramanian, and I. Hoteit (2019): Enhancing Ensemble Data Assimilation into One-Way-Coupled Models with One-Step-Ahead-Smoothing, QJRMS, In Press.

[49.] Jacox, M.G., M. A. Alexander, S. Siedlecki, K. Chen, Y.-O. Kwon, S. Brodie, I. Ortiz, D. Tommasi, M. J. Widlansky, D. Barrie, A. Capotondi, W. Cheng, E. Di Lorenzo, C. Edwards, J. Fiechter, P. Fratantoni, E. L. Hazen, A. J. Hermann, A. Kumar, A. J. Miller, D. Pirhalla, M. Pozo Buil, S. Ray, S. C. Sheridan, A. Subramanian, P. Thompson, L. Thorne, H. Annamalai, S. J. Bograd, R. B. Griffis, H. Kim, A. Mariotti, M. Merrifield and R. Rykaczewski, (2019): Seasonal-to-interannual prediction of U.S. coastal marine ecosystems: Forecast methods, mechanisms of predictability, and priority developments. Progress in Oceanography, In Press.

[48.] DeFlorio, M. J., D. E. Waliser, F. M. Ralph, B. Guan, A. Goodman, P. B. Gibson, S. Asharaf, L. Delle Monache, Z. Zhang, A. C. Subramanian, F. Vitart, H. Lin, and A. Kumar (2019): Experimental subseasonal-to-seasonal (S2S) forecasting of atmospheric rivers over the western United States, Journal of Geophysical Research - Atmospheres, 124(21), pp.11242-11265.

[47.] Chapman, W., A. Subramanian, Monache, L.D., and M. Ralph, 2019: Improving atmospheric river forecasts with machine learning. Geophys. Res. Lett., 46, 10,627–10,635, https://doi.org/10.1029/2019GL083662.

[46.] Seo, H., A. C. Subramanian, Song, H., Chowdary, J. S., 2019: Coupled effects of ocean current on wind stress in the Bay of Bengal: Eddy energetics and upper ocean stratification, Deep Sea Research II, 10.1016/j.dsr2.2019.07.005.

[45.] Gopal, G., A. C. Subramanian, A. J. Miller, H. Seo, D. Sengupta, 2019: Estimation and Prediction of the Upper Ocean Circulation in the Bay of Bengal, Deep Sea Research II, https://doi.org/10.1016/j.dsr2.2019.104721.

[44.] Eliashiv, J., A. C. Subramanian, A. J. Miller, 2019: A Reliability Budget analysis of CESM-DART, JAMES, In Press, doi: 10.1029/2019MS001678

[43.] Villas Boas, A. B., Ardhuin, F., et al., A. C. Subramanian, 2018: Integrated observations and modeling of winds, currents, and waves: requirements and challenges for the next decade. Frontiers in Marine Science, 6, p.425, https://doi.org/10.3389/fmars.2019.00425

[42.] Hermes, J. C., et al., A. C. Subramanian, 2018: Sustained Indian Ocean Observing System. Frontiers in Marine Science, https://doi.org/10.3389/fmars.2019.00355.

[41.] Capotondi, A., Sardeshmukh, P.D., Di Lorenzo, E., Subramanian, A.C. and Miller, A.J., 2019. Predictability of US West Coast Ocean Temperatures is not solely due to ENSO. Scientific reports, 9(1), p.10993.

[40.] Subramanian AC, Balmaseda MA, Centurioni L, Chattopadhyay R, Cornuelle BD, DeMott C, Flatau M, Fujii Y, Giglio D, Gille ST, Hamill TM, Hendon H, Hoteit I, Kumar A, Lee J-H, Lucas AJ, Mahadevan A, Matsueda M, Nam S, Paturi S, Penny SG, Rydbeck A, Sun R, Takaya Y, Tandon A, Todd RE, Vitart F, Yuan D and Zhang C (2019) Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability. Front. Mar. Sci. 6:427. doi: 10.3389/fmars.2019.00427.

[39.] Penny SG, Akella S, Balmaseda MA, Browne P, Carton JA, Chevallier M, Counillon F, Domingues C, Frolov S, Heimbach P, Hogan P, Hoteit I, Iovino D, Laloyaux P, Martin MJ, Masina S, Moore AM, de Rosnay P, Schepers D, Sloyan BM, Storto A, Subramanian A, Nam S, Vitart F, Yang C, Fujii Y, Zuo H, O’Kane T, Sandery P, Moore T and Chapman CC (2019) Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction. Front. Mar. Sci. 6:391. doi: 10.3389/fmars.2019.00391

[38.] Sun, R., A. C. Subramanian, A. J. Miller, M. Mazloff, I. Hoteit, and B. D. Cornuelle 2019: A regional coupled ocean–atmosphere modeling framework (MITgcm–WRF) using ESMF/NUOPC: description and preliminary results for the Red Sea, Geo. Mod. Dev. Disc., 12, 4221–4244, 2019

https://doi.org/10.5194/gmd-12-4221-2019.

[37.] Cordero-Quirós, N., A. J. Miller, A. C. Subramanian, J. Y. Luo 2018: A composite physical-biological ENSO in the California Current System, Ocean Modelling, 142, p.101439.

[36.] Eddebbar, Y., K. Rodgers, M. Long, A. C. Subramanian, S-P. Xie, and R. Keeling, 2018: El Niño-like Physical and Biogeochemical Ocean Response to Tropical Eruptions, J. Clim., 32, 2627–2649, https://doi.org/10.1175/JCLI-D-18-0458.1.

[35.] Guirguis, K., A. Gershunov, R. E.S. Clemesha, T. Shulgina, A. C. Subramanian, and F. M. Ralph, 2018: Circulation drivers of Atmospheric Rivers at the North American West Coast, Geo. Res. Let., 45, 12,576–12,584. https://doi.org/10.1029/2018GL079249

[34.] Rodrigues, R., A. C. Subramanian, L. Zanna, J. Berner, 2019: ENSO bimodality and extremes, Geo. Res. Let., 46 (9), 4883-4893.

[33.] Eliashiv, J., A. C. Subramanian, A. J. Miller, 2018: Tropical climate variability in Community Earth System Model and the Data Assimilation Research Testbed, Clim. Dyn., 54(1), 793-806, doi:10.1007/s00382-019-05030-6.

[32.] Subramanian, A. C., S. Juricke, P. Dueben, T. N. Palmer, 2018: A Stochastic Representation of Sub-Grid Uncertainty for Dynamical Core Development. BAMS, 100, 1091–1101, https://doi.org/10.1175/BAMS-D-17-0040.1

[31.] Zhan P., G. Gopalakrishnan, A. C. Subramanian, D. Guo, I. Hoteit, 2018: Adjoint Sensitivity Studies of the Red Sea Eddies. JGR Oceans, 123 (11), 8329-8345.

[30.] Shields, C, et al., A. C. Subramanian, 2018: Atmospheric River Tracking MethodIntercomparison Project (ARTMIP): Project Goals and Experimental Design. Geo. Mod. Dev., 11 (6), 2455-2474.

[29.] Dias, D. F., A. C. Subramanian, L. Zanna, A. J. Miller, 2018: Remote and Local Influences in Forecasting Pacific SST: a Linear Inverse Model and a Multimodel Ensemble Study. Cli. Dyn., 52 (5-6), 3183-3201.

[28.] Haustein, K., V. Venema, K. Cowtan , Z. Hausfather, R.G. Way, F.E.L. Otto, B. White, P. Jacobs, A. C. Subramanian, A.P. Schurer, 2018: A limited role for unforced internal variability in 20th century warming. 32 (16), 4893-4917.

[27.] Subramanian, A. C., F. Vitart, C. Zhang, A. Kumar and M. A. Balmaseda, 2017: Indian Ocean observations for operational subseasonal and seasonal forecasts. (Invited Book Chapter), IndOOS:A roadmap to sustained observations ofthe Indian Ocean for 2020-2030, https://doi.org/10.36071/clivar.rp.4.2019.

[26.] I-S. Kang, M-S. Ahn, H. Miura, and A. C. Subramanian, 2017: GCMs with Full Representation of Cloud Microphysics and Their MJO Simulations, (Book Chapter), "The gap between weather and climate forecasting: sub-seasonal to seasonal prediction", Eds. F. Vitart and A. Robertson, Elsevier.

[25.] Penny, S. G., S. Akella, O. Alves, C. Bishop, M. Buehner, M. Chevallier, F. Counillon, C. Draper, S. Frolov, Y. Fujii, A. Karspeck, A. Kumar, P. Laloyaux, J-F. Mahfouf, M. Martin, M. Pea, P. de Rosnay, A. C. Subramanian, R. Tardif, Y. Wang, X. Wu, 2017: Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations. WMO Whitepaper, In Press.

[24.] Hatfield, S. E., A. C. Subramanian, P. Düben, T. N. Palmer, 2017: Improving weather forecast skill through reduced precision data assimilation. Mon. Wea. Rev., 146 (1), 49-62.

[23.] Ummenhofer, C., A. C. Subramanian, S. Legg 2017: Maintaining Momentum in Climate Model Development. EOS Transactions, 98, https://doi.org/10.1029/2017EO086501.

[22.] Giglio, D., S. Gille, A. C. Subramanian, S. Nguyen, 2017: The role of wind gusts in upper ocean diurnal variability. JGR-Oceans, 122(9):7751-7764.

[21.] Leutbecher, M., et al., A. C. Subramanian, 2017: Stochastic representations of model uncertainties at ECMWF: State of the art and future vision. Quarterly Journal of the Royal Meteorological Society, In Press, doi:10.1002/qj.3094.

[20.] Düben, P., A. C. Subramanian, A. Dawson, T. N. Palmer, 2017: A study of reduced numerical precision to make superparametrisation more competitive. J. of Adv. in Modeling Earth Systems, 9, 566–584, doi:10.1002/2016MS000862.

[19.] Subramanian, A. C., T. N. Palmer, 2017: Ensemble super-parameterization vs stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction. J. of Adv. in Modeling Earth Systems, 9, doi:10.1002/2016MS000857.

[18.] Leung, K., Subramanian, A. C., Shen, S. S. P., 2017: Statistical Characteristics of the Long-term High-Resolution Data of Darwin Precipitable Water Vapor. AADA, In Press.

[17.] Davini, P., J. von Hardenberg, S. Corti, H. H. Christensen, S. Juricke, A. Subramanian, P. A. G. Watson, A. Weisheimer, and T. N. Palmer, 2017: Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in climate simulations. Geosci. Model Dev., 10, 1383-1402, doi:10.5194/gmd-10-1383-2017, 2017.

[16.] Subramanian, A., C. Ummenhofer, A. Giannini, M. Holland, S. Legg, A. Mahadevan, D. Perovich, J. Small, J. Teixeira, and L. Thompson, 2016: Translating process understanding to improve climate models. A US CLIVAR White Paper, Report 2016-3, 48pp., doi:10.5065/D63X851Q.

[15.] Subramanian, A. C., A. Weisheimer, T. N. Palmer, P. Bechtold, F. Vitart, 2016: Impact of stochastic physics on tropical precipitation and climate variability in the ECMWF IFS. Quarterly Journal of the Royal Meteorological Society, 143: 852–865. doi:10.1002/qj.2970.

[14.] Huddart, B. M., A. C. Subramanian, L. Zanna, T. N. Palmer, 2016: Seasonal and Decadal forecasts of Atlantic SST using a Linear Inverse Model. Climate Dynamics,49(5), 1833-1845, doi:10.1007/s00382-016-3375-1.

[13.] Zhan, P., A. C. Subramanian, F. Yao, A. Kartadikaria, D. Guo, I. Hoteit, 2016: The eddy kinetic energy budget in the Red Sea. JGR-Oceans, In press.

[12.] Leung, K., M. Velado, A. C. Subramanian, G. J. Zhang , R. Somerville, S. Shen, 2015: Simulation of high-resolution precipitable water data by a stochastic model with a random trigger. AADA, In press.

[11.] Miller, A. J., H. Song and A. C. Subramanian, 2015: The physical oceanographic environment during the CCE Years: Changes in climate and concepts. Deep-Sea Research II, 112, 6-17.

[10.] Seo, H., A. C. Subramanian, A. J. Miller, and N. R. Cavanaugh, 2014: Coupled impacts of the diurnal cycle of sea surface temperature on the Madden-Julian Oscillation. Journal of Climate, 27, 8422–8443.

[09.] Subramanian, A. C. and G. J. Zhang, 2014: Diagnosing MJO Forecast Biases in NCAR CAM3 Using Nudging During the DYNAMO Field Campaign. JGR-Atmospheres, 119 (12), 7231–7253.

[08.] Zhan, P., A. C. Subramanian, F. Yao, and I. Hoteit, 2013: Eddies in the Red Sea: A statistical and dynamical study. JGR-Oceans, 119 (6), 3909–3925.

[07.] Cavanaugh, N. R., T. Allen, A. C. Subramanian, B. Mapes, H. Seo and A. J. Miller, 2013: The skill of tropical Linear Inverse Models in hindcasting the Madden-Julian Oscillation. Climate Dynamics, 44, 897-906.

[06.] Subramanian, A. C., M. Jochum, A. J. Miller, R. B. Neale, H. Seo, D. E. Waliser and R. Murtugudde, 2012: The MJO and global warming: A study in CCSM4. Climate Dynamics, 42, 2019-2031.

[05.] Subramanian, A. C., A. J. Miller, B. D. Cornuelle, E. Di Lorenzo, R. A. Weller and F. Straneo, 2012: A data assimilative perspective of oceanic mesoscale eddy evolution during VOCALS-REx Atmospheric Chemistry and Physics/Ocean Sciences (VOCALS Special Issue), 13, 3329-3344.

[04.] Song, H., I. Hoteit, B. D. Cornuelle and A. C. Subramanian, 2011: An Adjoint-Based Adaptive Ensemble Kalman Filter, Monthly Weather Review, 141, 3343–3359.

[03.] Subramanian, A. C., I. Hoteit, B. D. Cornuelle, A. J. Miller and H. Song, 2011: Linear vs Nonlinear Filtering with scale selective corrections for balanced dynamics in a simple atmospheric model, Journal of Atmospheric Sciences, 69, 3405–3419.

[02.] Subramanian, A. C., M. Jochum, A. J. Miller, R. Murtugudde, R. B. Neale and D. E. Waliser, 2011: The Madden Julian Oscillation in CCSM4. Journal of Climate, 24, 6261-6282.

[01.] Song, H., I. Hoteit, B. D. Cornuelle and A. C. Subramanian, 2010: An adaptive approach to mitigate background covariance limitations in the ensemble Kalman filter, Monthly Weather Review, 138, 2825-2845.

Fine print: Permission to place copies of works from the Journal of Climate, and the Monthly Weather Review on this server has been provided by the American Meteorological Society. The AMS does not guarantee that the copies provided here are accurate copies of the published work.

Publications from Journal of Geophysical Research, Geophysical Research Letters, and EOS are copyright American Geophysical Union. Further reproduction or electronic distribution is not permitted.

Non-peer-reviewed articles

[03.] Moroni, D. F., Ramapriyan, H., Peng, G., Hobbs, J., Goldstein, J. C., Downs, R. R., Wolfe, R., Shie, C.-L.,Merchant, C. J., Bourassa, M., Matthews, J. L.,Cornillon, P., Bastin, L., Kehoe, K.,Smith, B., Privette,J. L., Subramanian, A. C., Brown, O., &Ivánová,I. (2019) Understanding the Various Perspectives of Earth Science Observational Data Uncertainty. Figshare. https://doi.org/10.6084/m9.figshare.10271450.

[02.] Serra, Y. et al., A. C. Subramanian 2018 The Risks of Contracting the Acquisition and Processing of the Nation's Weather and Climate Data to the Private Sector. BAMS, 99, 869–870.

[01.] Capotondi, A., K. B. Karnauskas, A. Miller, and A. C. Subramanian 2017 ENSO diversity and its implications for U.S. West Coast marine ecosystems. US CLIVAR Variations, In press (not peer reviewed).

Conference Presentations

Subramanian, A. C., 2016: Invited Talk Ensemble super-parameterization for subseasonal-to-seasonal prediction, JpGU-AGU 2017 Meeting, Tokyo, Japan (May. 2017)

Subramanian, A. C., Tim Palmer, Frederic Vitart, Antje Weisheimer, Peter Bechtold, 2016: Ensemble super-parameterization for subseasonal-to-seasonal prediction, AGU Fall Meeting, San Francisco (Dec. 2016)
Subramanian, A. C., Tim Palmer, Frederic Vitart, Antje Weisheimer, Peter Bechtold, 2016: Ensemble super-parameterization for subseasonal-to-seasonal prediction, S2S Extremes Workshop, Columbia University, NY (Dec 2016)
Subramanian, A. C., David Lavers, Mio Matsueda, Tim Palmer 2016: Stochastic Multi-scale Atmospheric Modeling for Weather Forecasting: An Atmospheric River Case Study, International Atmospheric Rivers Conference (August 2016)
Subramanian, A. C., Stephan Juricke, Peter Dueben, Tim Palmer 2016: Invited talk - A Proposal for the Intercomparison of GCM Dynamical Cores with Stochastic Perturbations, Dynamical Core Model Intercomparison Project (June 2016)
Subramanian, A. C., Tim Palmer 2016: Invited talk - Stochastic Multi-scale Modeling for weather and climate prediction, SIAM Conference on Uncertainty Quantification issues in the Geosciences (Apr 2016)
Subramanian, A. C., Tim Palmer, Marat Khairoutdinov, Frederic Vitart, Antje Weisheimer, Peter Bechtold, 2016: Stochastic Multi-scale Modeling for weather and climate prediction, HDCP2 Conference on Convection and Precipitation, Berlin (Feb 2016)
Subramanian, A. C., Tim Palmer, Marat Khairoutdinov, Frederic Vitart, Antje Weisheimer, Peter Bechtold, 2015: Stochastic Multi-scale Modeling for weather and climate prediction, US CLIVAR Climate Process Team workshop, GFDL, Princeton, U.S.A. (Oct 2015)
Subramanian, A. C., Sarah Gille, San Nguyen, 2015: Modeling of diurnal vari- ability in upper ocean processes using satellite and in-situ observations, US CLIVAR Climate Process Team workshop, GFDL, Princeton, U.S.A. (Oct 2015)
Subramanian, A. C. 2015: Invited talk - Stochastic Multi-scale Modeling for weather and climate prediction, University of Washington (October 2015)
Subramanian, A. C., Tim Palmer 2015: Invited talk - Towards the Prototype Probabilistic Earth-System Model for Climate Prediction, SIAM Conference on Mathematical and Computational issues in the Geosciences (June 2015)
Subramanian, A. C., Peter Bechtold, Antje Weisheimer, Frederic Vitart, Marat Khairout- dinov, Tim Palmer 2015: Impact of stochastic- and super-parameterisation of convection on precipitation in the ECMWF model, EGU General Assembly (Apr 2015)
Subramanian, A. C. 2015: Invited Talk - Impact of stochastic- and super- parameterisation of convection on precipitation in the ECMWF model, Stochas- tic Parametrisation Workshop (Mar 2015)
Subramanian, A. C. 2014: Diagnosing MJO hindcast biases in NCAR CAM3 using nudging during the DYNAMO field campaign, Virtual workshop on Bias Corrections in Subseasonal to Interannual Predictions (Sept 2014)

Subramanian, A. C., Ian Eisenman, Simona Bordoni 2013: The influence of sea ice albedo on the global hydrological cycle, AGU Annual Meeting, San Francisco, CA (December 2013)

Subramanian, A. C., Guang Zhang 2013: Diagnosing MJO forecast biases in the NCAR Community Atmosphere Model during the DYNAMO field campaign, AGU Annual Meeting, San Francisco, CA (December 2013)

Subramanian, A. C., Guang Zhang 2013: Modified convection scheme in CAM to improve MJO predictability, 93rd American Meteorological Society Annual Meeting Austin, TX (January 2013)

Subramanian, A. C., M. Jochum, A. J. Miller, R. Neale, H. Seo, D. Waliser, R. Murtugudde 2012: The Madden-Julian Oscillation and Global Warming: A study in CCSM4, AGU Annual Meeting, San Francisco, CA (December 2012)
Subramanian, A. C., Guang Zhang, Mitch Moncrieff, 2012: A study of the sensitivity of the MJO initiation in CAM to moist processes and nonlinear momentum feedback, 1st Pan-GASS Workshop, Boulder, CO (October 2012)
Subramanian, A. C., I. Hoteit, B. D. Cornuelle, A. J. Miller and H. Song, 2011: Linear vs Nonlinear Filtering with scale selective corrections for balanced dynamics in a simple atmospheric model, Ocean Sciences Meeting, Salt Lake City, UT (Feb, 2012)

Subramanian, A. C., M. Jochum, A. J. Miller, R. Murtugudde, R. Neale, D. Waliser, 2011: The Madden-Julian Oscillation in CCSM4, WCRP OSC, Denver, CO (October 2011)

Subramanian, A. C., A. J. Miller, B. D. Cornuelle 2011: Understanding Ocean Processes during VOCALS- A data assimilation framework, VOCALS 3rd Annual Meeting, Miami, FL (March, 2011)

Subramanian, A. C., I. Hoteit, L. Neef and H. Song, 2010: Implementation of the nonlinear filtering problem to study balance in dynamical scales, 28th IUGG Conference on Mathematical Geophysics, Pisa, Italy (June, 2010)

Subramanian, A. C., A. J. Miller, 2009: Eddy Resolving Ocean model of VOCALS domain - A data assimilation framework, VOCALS 2nd Annual Meeting, Seattle, WA (Jul, 2009)

Subramanian, A. C., I. Hoteit, L. Neef and H. Song, 2009: Implementation of the nonlinear filtering problem to study balance in dynamical scales, 5th WMO Symposium on Data Assimilation, Melbourne, Australia (October, 2009)

Subramanian, A. C., A. J. Miller, 2009: Eddy Resolving Ocean model of VOCALS domain - A data assimilation framework, 89th AMS Annual Meeting, Phoenix, AZ (Jan, 2009)

Putrasahan, D, Subramanian, A. C., A. J. Miller, 2009: Coastal Jets and Upwelling Events in the Humboldt Current System, 2009 AGU Fall Meeting, San Francisco, CA (Dec, 2009)

A. J. Miller, Subramanian, A. C., Putrasahan, D 2008: Regional Coupled Modeling and Ocean data assimilation, VOCALS 1st Annual Meeting, Boulder, CO (Mar, 2008)

Subramanian, A. C., A. J. Miller, B. D. Cornuelle 2008: Regional Ocean Modeling of the South East Pacific - A data assimilation framework, 55th Annual Eastern Pacific Ocean Conference, Fallen Leaf Lake, California (Sept., 2008)

Workshops/Summer Colloquiums Attended

2015 Workshop on Subseasonal to Seasonal predictability, Conducted by ECMWF, Reading, UK.

2015 Workshop on Translating Process Understanding to Improve Climate Models, U. S. CLIVAR and GFDL.

2015 Workshop on Stochastic Parametrisation in Climate Models, Conducted by ECMWF, Reading, UK.

2014 Workshop on Tropical Dynamics and the MJO, Conducted by CMMAP, CSU, Fort Collins.

2013 GASS/MJO-TF meeting on diabatic processes of the MJO, Singapore.

2013 First DYNAMO Workshop, Big Island, Hawaii

2012 An Advanced Study Program Summer Colloquium on Weather-Climate Intersection Conducted by National Center for Atmospheric Research, Boulder, Colorado.

2012 Workshop on Physics of Climate Models, Pasadena, CA, Conducted by JPL, NASA.

2010 Workshop on Inverse Ocean Modeling in ROMS, Conducted by Prof. Andrew Moore, University of California, Santa Cruz

2010 International Summer School for Observing, Assimilating and Forecasting the Ocean, Conducted by Global Ocean Data Assimilation Experiment, Perth, Australia

2009 JCSDA Summer Colloquium on Data Assimilation, Conducted by Joint Center for Satellite Data Assimilation, Stevenson, Washington.

2008 An Advanced Study Program Summer Colloquium on Numerical Techniques for Global Atmospheric Models, Conducted by National Center for Atmospheric Research, Boulder, Colorado.

2008 UC-LTER Graduate Student/Postdoc Symposium, La Jolla, CA, Conducted by Scripps Institution of Oceanography.

2007 ROMS User Workshop, Conducted by University of California, Los Angeles

2007 Workshop on Inverse Ocean Modeling in ROMS, Conducted by Prof. Andrew Moore, University of California, Santa Cruz

2007 Post Inverse Ocean Model workshop, Portland, OR, Conducted by Portland State University.

2006 Workshop on Data Assimilation Techniques in Meteorology, Organised by IISc(Indian Institute of Science) and ISRO(Indian Space Research Organisation)

- Subramanian, A. C., Guang Zhang, Mitch Moncrieff, 2012: A study of the sensitivity of the MJO initiation in CAM to moist processes and nonlinear momentum feedback, 1st Pan-GASS Workshop, Boulder, CO (October 2012)

Subramanian, A. C., I. Hoteit, B. D. Cornuelle, A. J. Miller and H. Song, 2011: Linear vs Nonlinear Filtering with scale selective corrections for balanced dynamics in a simple atmospheric model, Ocean Sciences Meeting, Salt Lake City, UT (Feb, 2012)
Subramanian, A. C., M. Jochum, A. J. Miller, R. Murtugudde, R. Neale, D. Waliser, 2011: The Madden-Julian Oscillation in CCSM4, WCRP OSC, Denver, CO (October 2011)
Subramanian, A. C., A. J. Miller, B. D. Cornuelle 2011: Understanding Ocean Processes during VOCALS- A data assimilation framework, VOCALS 3rd Annual Meeting, Miami, FL (March, 2011)
Subramanian, A. C., I. Hoteit, L. Neef and H. Song, 2010: Implementation of the nonlinear filtering problem to study balance in dynamical scales, 28th IUGG Conference on Mathematical Geophysics, Pisa, Italy (June, 2010)
Subramanian, A. C., A. J. Miller, 2009: Eddy Resolving Ocean model of VOCALS domain - A data assimilation framework, VOCALS 2nd Annual Meeting, Seattle, WA (Jul, 2009)
Subramanian, A. C., I. Hoteit, L. Neef and H. Song, 2009: Implementation of the nonlinear filtering problem to study balance in dynamical scales, 5th WMO Symposium on Data Assimilation, Melbourne, Australia (October, 2009)
Subramanian, A. C., A. J. Miller, 2009: Eddy Resolving Ocean model of VOCALS domain - A data assimilation framework, 89th AMS Annual Meeting, Phoenix, AZ (Jan, 2009)
Putrasahan, D, Subramanian, A. C., A. J. Miller, 2009: Coastal Jets and Upwelling Events in the Humboldt Current System, 2009 AGU Fall Meeting, San Francisco, CA (Dec, 2009)
A. J. Miller, Subramanian, A. C., Putrasahan, D 2008: Regional Coupled Modeling and Ocean data assimilation, VOCALS 1st Annual Meeting, Boulder, CO (Mar, 2008)
Subramanian, A. C., A. J. Miller, B. D. Cornuelle 2008: Regional Ocean Modeling of the South East Pacific - A data assimilation framework, 55th Annual Eastern Pacific Ocean Conference, Fallen Leaf Lake, California (Sept., 2008)