Bellow, J. G., Hudson, R. F., & Nair, P. K. R. (2008). Adoption potential of fruit-tree-based agroforestry on small farms in the subtropical highlands. Agroforest Syst , 73 (1), 23–36.
Morey, S. L., Bourassa, M. A., Dukhovskoy, D. S., & O'Brien, J. J. (2006). Modeling studies of the upper ocean response to a tropical cyclone. Ocean Dynamics , 56 (5-6), 594–606.
Zavala-Hidalgo, J., Gallegos-García, A., Martínez-López, B., Morey, S. L., & O'Brien, J. J. (2006). Seasonal upwelling on the Western and Southern Shelves of the Gulf of Mexico. Ocean Dynamics , 56 (3-4), 333–338.
Solís, D., & Letson, D. (2013). Assessing the value of climate information and forecasts for the agricultural sector in the Southeastern United States: multi-output stochastic frontier approach. Reg Environ Change , 13 (S1), 5–14.
Shin, D. W., & Krishnamurti, T. N. (1999). Improving Precipitation Forecasts over the Global Tropical Belt. Meteorology and Atmospheric Physics , 70 (1-2), 1–14.
Stefanova, L., & Krishnamurti, T. N. (2011). Kinetic energy exchanges between the time scales of ENSO and the Pacific decadal oscillation. Meteorol Atmos Phys , 114 (3-4), 95–105.
Kang, S. - D., Shin, D. W., Cocke, S., Kim, H. - D., & Jung, W. - S. (2011). Comparison of ensemble methods for summer-time numerical weather prediction over East Asia. Meteorol Atmos Phys , 113 (1-2), 27–38.
Peng, M. S., Maue, R. N., Reynolds, C. A., & Langland, R. H. (2007). Hurricanes Ivan, Jeanne, Karl (2004) and mid-latitude trough interactions. Meteorol. Atmos. Phys. , 97 (1-4), 221–237.
Parfitt, R., Ummenhofer, C. C., Buckley, B. M., Hansen, K. G., & D'Arrigo, R. D. (2020). Distinct seasonal climate drivers revealed in a network of tree-ring records from Labrador, Canada. Clim Dyn , 54 (3-4), 1897–1911.
Abstract: Traditionally, high-latitude dendroclimatic studies have focused on measurements of total ring width (RW), with the maximum density of the latewood (MXD) serving as a complementary variable. Whilst MXD has typically improved the strength of the growing season climate connection over that of RW, its measurements are costly and time-consuming. Recently, a less costly and more time-efficient technique to extract density measurements has emerged, based on lignin's propensity to absorb blue light. This Blue Intensity (BI) methodology is based on image analyses of finely-sanded core samples, and the relative ease with which density measurements can be extracted allows for significant increases in spatio-temporal sample depth. While some studies have attempted to combine RW and MXD as predictors for summer temperature reconstructions, here we evaluate a systematic comparison of the climate signal for RW and latewood BI (LWBI) separately, using a recently updated and expanded tree ring database for Labrador, Canada. We demonstrate that while RW responds primarily to climatic drivers earlier in the growing season (January-April), LWBI is more responsive to climate conditions during late spring and summer (May-August). Furthermore, RW appears to be driven primarily by large-scale atmospheric dynamics associated with the Pacific North American pattern, whilst LWBI is more closely associated with local climate conditions, themselves linked to the behaviour of the Atlantic Multidecadal Oscillation. Lastly, we demonstrate that anomalously wide or narrow growth rings consistently respond to the same climate drivers as average growth years, whereas the sensitivity of LWBI to extreme climate conditions appears to be enhanced.
Misra, V., & Bhardwaj, A. (2019). Understanding the seasonal variations of Peninsular Florida. Clim Dyn , 54 (3-4), 1873–1885.
Abstract: This study accounts for varying lengths of the seasons, which turns out to be an important consideration of climate variability over Peninsular Florida (PF). We introduce an objective definition for the onset and demise of the winter season over relatively homogenous regions within PF: North Florida (NF), Central Florida (CF), Southeast Florida (SeF), and Southwest Florida (SwF). We first define the summer season based on precipitation, and follow this by defining the winter season using surface temperature analysis. As a consequence, of these definitions of the summer and the winter seasons, the lengths of the transition seasons of spring and fall also vary from year to year. The onset date variations have a robust relationship with the corresponding seasonal length anomalies across PF for all seasons. Furthermore, with some exceptions, the onset date variations are associated with corresponding seasonal rainfall and surface temperature anomalies, which makes monitoring the onset date of the seasons a potentially useful predictor of the following evolution of the season. In many of these instances the demise date variations of the season also have a bearing on the preceding seasonal length and seasonal rainfall anomalies. However, we find that variations of the onset and the demise dates are independent of each other across PF and in all seasons. We also find that the iconic ENSO teleconnection over PF is exclusive to the seasonal rainfall anomalies and it does not affect the variations in the length of the winter season. Given these findings, we strongly suggest monitoring and predicting the variations in the lengths of the seasons over PF as it is not only an important metric of climate variability but also beneficial to reduce a variety of risks of impact of anomalous seasonal climate variations.
