420
Liang, X. Z., Xu, M., Gao, W., Reddy, K. R., Kunkel, K., Schmoldt, D. L., & Samel, A. N. (2012b).
A distributed cotton growth model developed from GOSSYM and its parameter determination.
Agronomy Journal, 104(3), 661–674.
Liang, X.-Z., Xu, M., Yuan, X., Ling, T., Choi, H. I., Zhang, F., Chen, L., Liu, S., Su, S., & Qiao,
F. (2012c). Regional climate-weather research and forecasting model. Bulletin of the American
Meteorological Society, 93(9), 1363–1387.
Liang, X.-Z., & Zhang, F. (2013). The cloud–aerosol–radiation (CAR) ensemble modeling system.
Atmospheric Chemistry and Physics, 13(16), 8335–8364.
Liu, S., Wang, J. X. L., Liang, X.-Z., Morris, V., & Fine, S. S. (2015). A hybrid approach to
improving the skills of seasonal climate outlook at the regional scale. Climate Dynamics, 46(1–
2), 483–494. https://doi.org/10.1007/s00382-015-2594-1.
McKinion, J., Baker, D., Whisler, F., & Lambert, J. (1989). Application of the GOSSYM/COMAX
system to cotton crop management. Agricultural Systems, 31(1), 55–65.
Miguez, F. E., Zhu, X. G., Humphries, S., Bollero, G. A., & Long, S. P. (2009). A semimechanistic
model predicting the growth and production of the bioenergy crop Miscanthus × giganteus:
Description, parameterization and validation. Global Change Biology Bioenergy, 1, 282–296.
Miguez, F. E., Maughan, M., Bollero, G. A., & Long, S. P. (2012). Modeling spatial and dynamic
variation in growth, yield, and yield stability of the bioenergy crops Miscanthus × giganteus and Panicum virgatum across the conterminous United States. Global Change Biology
Bioenergy, 4, 509–520.
Pang, X., Letey, J., & Wu, L. (1997). Yield and nitrogen uptake prediction by CERES-Maize model
under semiarid conditions. Soil Science Society of America Journal, 61(1), 254–256.
Reddy, K. R., Hodges, H. F., & McKinion, J. M. (1997). Modeling temperature effects on cotton
internode and leaf growth. Crop Science, 37(2), 503–509.
Reddy, K. R., Kakani, V. G., McKinion, J. M., & Baker, D. N. (2002). Applications of a cotton
simulation model, GOSSYM, for crop management, economic and policy decisions. In L. R.
Ahuja, L. Ma, & T. A. Howell (Eds.), Agricultural system models in field research and technology transfer. Boston, MA: CRC Press.
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, M. G., Huang, X.-Y., Wang,
W., & Powers, J.G. (2008). A description of the advanced research WRF Version 3. NCAR
Technical Note. NCAR/TN–475+ STR (113p).
Tsvetsinskaya, E. A., Mearns, L. O., & Easterling, W. E. (2001). Investigating the effect of seasonal plant growth and development in three-dimensional atmospheric simulations. Part I:
Simulation of surface fluxes over the growing season. Journal of Climate, 14(5), 692–709.
Wang, D., Jaiswal, D., Lebauer, D. S., Wertin, T. M., Bollero, G. A., Leakey, A. D. B., & Long,
S. P. (2015). A physiological and biophysical model of coppice willow (Salix spp.) production yields for the contiguous USA in current and future climate scenarios. Plant, Cell and
Environment, 38(9), 1850–1865. https://doi.org/10.1111/pce.12556.
Yuan, X., & Liang, X. Z. (2011). Improving cold season precipitation prediction by the nested
CWRF-CFS system. Geophysical Research Letters, 38(2). https://doi.org/10.1029/201
0GL046104.
Energy-Centric Approaches to FEWS Modeling
Dale, L., Karali, N., Millstein, D., Carnall, M., Vicuña, S., Borchers, N., Bustos, E., O’Hagan, J.,
Purkey, D., Heaps, C., Sieber, J., Collins, W., & Sohn, M. (2015). An integrated assessment of
water-energy and climate change in Sacramento, California: How strong is the nexus? Climatic
Change, 132, 223–235.
Hunt, P., Miller, J., Ducey, T., Lang, M., Szogi, A., & McCarty, G. (2014). Denitrification in soils
of hydrologically restored wetlands relative to natural and converted wetlands in the MidAtlantic coastal plain of the USA. Ecological Engineering, 71, 438–447.
F. R. Miralles-Wilhelm
Liang, X. Z., Xu, M., Gao, W., Reddy, K. R., Kunkel, K., Schmoldt, D. L., & Samel, A. N. (2012b).
A distributed cotton growth model developed from GOSSYM and its parameter determination.
Agronomy Journal, 104(3), 661–674.
Liang, X.-Z., Xu, M., Yuan, X., Ling, T., Choi, H. I., Zhang, F., Chen, L., Liu, S., Su, S., & Qiao,
F. (2012c). Regional climate-weather research and forecasting model. Bulletin of the American
Meteorological Society, 93(9), 1363–1387.
Liang, X.-Z., & Zhang, F. (2013). The cloud–aerosol–radiation (CAR) ensemble modeling system.
Atmospheric Chemistry and Physics, 13(16), 8335–8364.
Liu, S., Wang, J. X. L., Liang, X.-Z., Morris, V., & Fine, S. S. (2015). A hybrid approach to
improving the skills of seasonal climate outlook at the regional scale. Climate Dynamics, 46(1–
2), 483–494. https://doi.org/10.1007/s00382-015-2594-1.
McKinion, J., Baker, D., Whisler, F., & Lambert, J. (1989). Application of the GOSSYM/COMAX
system to cotton crop management. Agricultural Systems, 31(1), 55–65.
Miguez, F. E., Zhu, X. G., Humphries, S., Bollero, G. A., & Long, S. P. (2009). A semimechanistic
model predicting the growth and production of the bioenergy crop Miscanthus × giganteus:
Description, parameterization and validation. Global Change Biology Bioenergy, 1, 282–296.
Miguez, F. E., Maughan, M., Bollero, G. A., & Long, S. P. (2012). Modeling spatial and dynamic
variation in growth, yield, and yield stability of the bioenergy crops Miscanthus × giganteus and Panicum virgatum across the conterminous United States. Global Change Biology
Bioenergy, 4, 509–520.
Pang, X., Letey, J., & Wu, L. (1997). Yield and nitrogen uptake prediction by CERES-Maize model
under semiarid conditions. Soil Science Society of America Journal, 61(1), 254–256.
Reddy, K. R., Hodges, H. F., & McKinion, J. M. (1997). Modeling temperature effects on cotton
internode and leaf growth. Crop Science, 37(2), 503–509.
Reddy, K. R., Kakani, V. G., McKinion, J. M., & Baker, D. N. (2002). Applications of a cotton
simulation model, GOSSYM, for crop management, economic and policy decisions. In L. R.
Ahuja, L. Ma, & T. A. Howell (Eds.), Agricultural system models in field research and technology transfer. Boston, MA: CRC Press.
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, M. G., Huang, X.-Y., Wang,
W., & Powers, J.G. (2008). A description of the advanced research WRF Version 3. NCAR
Technical Note. NCAR/TN–475+ STR (113p).
Tsvetsinskaya, E. A., Mearns, L. O., & Easterling, W. E. (2001). Investigating the effect of seasonal plant growth and development in three-dimensional atmospheric simulations. Part I:
Simulation of surface fluxes over the growing season. Journal of Climate, 14(5), 692–709.
Wang, D., Jaiswal, D., Lebauer, D. S., Wertin, T. M., Bollero, G. A., Leakey, A. D. B., & Long,
S. P. (2015). A physiological and biophysical model of coppice willow (Salix spp.) production yields for the contiguous USA in current and future climate scenarios. Plant, Cell and
Environment, 38(9), 1850–1865. https://doi.org/10.1111/pce.12556.
Yuan, X., & Liang, X. Z. (2011). Improving cold season precipitation prediction by the nested
CWRF-CFS system. Geophysical Research Letters, 38(2). https://doi.org/10.1029/201
0GL046104.
Energy-Centric Approaches to FEWS Modeling
Dale, L., Karali, N., Millstein, D., Carnall, M., Vicuña, S., Borchers, N., Bustos, E., O’Hagan, J.,
Purkey, D., Heaps, C., Sieber, J., Collins, W., & Sohn, M. (2015). An integrated assessment of
water-energy and climate change in Sacramento, California: How strong is the nexus? Climatic
Change, 132, 223–235.
Hunt, P., Miller, J., Ducey, T., Lang, M., Szogi, A., & McCarty, G. (2014). Denitrification in soils
of hydrologically restored wetlands relative to natural and converted wetlands in the MidAtlantic coastal plain of the USA. Ecological Engineering, 71, 438–447.
F. R. Miralles-Wilhelm