Impact of climate dynamics on cyclical properties of wine production in Douro region using time-frequency approach

Mario CUNHA, Christian RICHTER


Abctract. In this paper we model the impact of climate dynamics on wine production temporal cycles for the period 1933 to 2013 in the Douro wine region. We identify the cyclical properties of wine production and which cycles are determined by spring temperature and soil water levels during summer. We achieve that by applying a time-frequency approach, which is based on Kalman filter regressions in the time domain. The time-varying autoregressive model can explain 79% of the variability of wine production in Douro region. We then transfer the results in the frequency domain and can show that wine production is characterized by two cycles of 5.7 and 2.5 years around the long run trend. The in-season spring temperature as well as the temperatures of two and three years ago could explain about 65% of the variability of wine production. When the soil water level in summer is incorporated, the R2 increases to 83% and the Akaike criterion value is lower. The effects of soil water in wine production are depending on the timing. The in-season effect of an increase in soil water is negative, whilst soil water from two and three years ago have a positive effect on wine production. There is a stable but not constant link between production and the spring temperature. The temperature is responsible for two long-medium cycles of 5.8 year and 4.2 years as well as a short one of 2.4 years that began since the 80s. The soil water level can explained 60%of the 7 years cycles of wine production as well as a short one of 2.3 years cycle which has been happening since the 90s. We can recognise a shift of the relative importance away from temperature to soil water. Despite using a new an extended dataset, our results largely confirm the results of the impact of climate on the wine production in Douro region in our previous research. Modelling the impact of climate on the wine production can be an important instrument contributing for mitigation strategies facing the projected climate conditions in order to remain competitive in the market.

Keywords. Climate variability, Wine production, Time-varying spectra, Kalman filter, Douro region.

JEL. L52, B52, F63.


Climate variability; Wine production; Time-varying spectra; Kalman filter; Douro region.

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Allen, R., (2015). Reference evapotranspiration calculator (Ref-ET). In C.o.A.a.l.S. Kimberly Research and Extension Center. Idaho Agricultural Experiment Station. University of Idaho (Editor), assessed 29 May 2015. [Retrieved from].

Allen, R.G., Pereira, L.S., Raes, D. & Smith, M. (1998). Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56 FAO - Food and Agriculture Organization of the United Nations, Rome, Italy. [Retrieved from].

Bindi, M., Fibbi, L., Gozzini, B., Orlandini, S. & Miglietta, F. (1996). Modelling the impact of future climate scenarios on yield and yield variability of grapevine. Climate Research, 7(3): 213-224. doi. 10.3354/cr007213

Bindi, M., Fibbi, L. & Miglietta, F. (2001). Free Air CO2 Enrichment (FACE) of grapevine (Vitis vinifera L.): II. Growth and quality of grape and wine in response to elevated CO2 concentrations. European Journal of Agronomy, 14(2), 145-155. doi. 10.1016/S1161-0301(00)00093-9

Bisson, L.F., Waterhouse, A.L., Ebeler, S.E., Walker, M.A. & Lapsley, J.T. (2002). The present and future of the international wine industry. Nature, 418(6898), 696. 10.1038/nature01018

Bluestein, L.I. (1968). A linear filtering approach to the computation of the discrete Fourier transform. Northeast Electronics Research and Engineering Meeting Record, 10, 218-219.

Boashash, B. (2003). Time Frequency Signal Analysis and Processing. Elsevier, Oxford.

Boashash, B. & Reilly, A. (1992). Algorithms for time-frequency signal analysis. In: B. Boashash (Editor), Time-Frequency Signal Analysis - Methods and Applications, (pp.163-181), Longman-Cheshire, Melbourne.

Bock, A., Sparks, T.H., Estrella, N. & Menzel, A. (2013). Climate-induced changes in grapevine yield and must sugar content in Franconia (Germany) between 1805 and 2010. PloS one, 8(7), e69015. doi. 10.1371/journal.pone.0069015

Caffarra, A., Rinaldi, M., Eccel, E., Rossi, V. & Pertot, I. (2012). Modelling the impact of climate change on the interaction between grapevine and its pests and pathogens: European grapevine moth and powdery mildew. Agriculture, Ecosystems & Environment, 148, 89-101. doi. 10.1016/j.agee.2011.11.017

Campbell, G.S. & Norman, J.M. (1997). An Introduction to Environmental Biophysics. Springer-Verlag.

Chaves, M. & Rodrigues, L. (1987). Photosynthesis and water relations in grapevines response to environmental factors. In: J.D.e.a. Tenhunen (Editor), Plant Response to Stress-functional analises in Mediterranean Ecosystems. (pp.279-290), Springer Verlag, Berlin.

Clingeleffer, P., Dunn, G., Krstic, M. & Martin, S. (2001). Crop development, crop estimation and crop control to secure quality and production of major wine grape varieties: A national approach, Australian Grape and Wine Authority.

Cola, G. et al., (2014). Description and testing of a weather-based model for predicting phenology, canopy development and source-sink balance in Vitis vinifera L. cv. Barbera. Agricultural and Forest Meteorology, 184, 117-136. doi. 10.1016/j.agrformet.2013.09.008

Cunha, M., Abreu, I., Pinto, P. & Castro, R. (2003). Airborne Pollen Samples for Early-Season Estimates of Wine Production in a Mediterranean Climate of Northern Portugal. American Journal of Enology and Viticulture, 54(3), 189-194.

Cunha, M., Marçal, A. & Silva, L. (2010). Very early prediction of wine yield based on satellite data from VEGETATION. International Journal of Remote Sensing, 31(12), 3125-3142. doi. 10.1080/01431160903154382

Cunha, M., Ribeiro, H. & Abreu, I. (2016). Pollen-based predictive modelling of wine production: application to an arid region. European Journal of Agronomy, 73, 42-54. doi. 10.1016/j.eja.2015.10.008

Cunha, M. & Richter, C. (2012). Measuring the Impact of Temperature Changes on the Wine Production in the Douro Region using the Short Time Fourier Transform. International Journal of Biometeorology, 56(2), 357-370. doi. 10.1007/s00484-011-0439-0

Cunha, M. & Richter, C. (2016). The impact of climate change on the winegrape vineyards of the Portuguese Douro region. Climatic Change, 138(1-2), 239-251. doi. 10.1007/s10584-016-1719-9

Duchêne, E. & Schneider, C. (2005). Grapevine and climatic changes: a glance at the situation in Alsace. Agron. Sustain. Dev., 25(1), 93-99. doi. 10.1051/agro:2004057

Esteves, M.A. & Orgaz, M.D.M. (2001). The influence of climatic variability on the quality of wine. International Journal of Biometeorology, 45(1), 13-21. doi. 10.1007/s004840000075

Everingham, Y.L., Smyth, C.W. & Inman-Bamber, N.G. (2009). Ensemble data mining approaches to forecast regional sugarcane crop production. Agricultural and Forest Meteorology, 149(3), 689-696. doi. 10.1016/j.agrformet.2008.10.018

Fraga, H., Malheiro, A.C., Moutinho-Pereira, J. & Santos, J.A. (2014). Climate factors driving wine production in the Portuguese Minho region. Agricultural and Forest Meteorology, 185, 26-36. doi. 10.1016/j.agrformet.2013.11.003

Fraga, H. et al., (2016). Climatic suitability of Portuguese grapevine varieties and climate change adaptation. International Journal of Climatology, 36(1), 1-12. doi. 10.1002/joc.4325

Gabor, D. (1946). Theory of communication. Journal of the Institute of Electrical Engineering, 93(3), 429-457. doi. 10.1049/ji-3-2.1946.0074

Giorgi, F. & Lionello, P. (2008). Climate change projections for the Mediterranean region. Global and Planetary Change, 63(2-3), 90-104. doi. 10.1016/j.gloplacha.2007.09.005

Gouveia, C., Liberato, M.L.R., DaCamara, C.C., Trigo, R.M. & A.Ramos, M. (2011). Modelling past and future wine production in the Portuguese Douro Valley. Climate Research, 48(2-3), 349-362. doi. 10.3354/cr01006

Guilpart, N., Metay, A. & Gary, C. (2014). Grapevine bud fertility and number of berries per bunch are determined by water and nitrogen stress around flowering in the previous year. European Journal of Agronomy, 54, 9-20. doi. 10.1016/j.eja.2013.11.002

Hughes Hallett, A. & Richter, C., (2003a). Learning and Monetary Policy in a Spectral Analysis Representation. In: P. Wang and S.-H. Chen (Editors), Computational Intelligence in Economics and Finance. (pp.91-103), Springer Verlag, Berlin.

Hughes Hallett, A. & Richter, C. (2006). Measuring the Degree of Convergence among European Business Cycles. Computational Economics, 27, 229-259. doi. 10.1007/s10614-006-9026-6

Hughes Hallett, A. & Richter, C. (2009a). Economics in the Backyard: How much Convergence is there between China and her Special Regions? The World Economy, 32(6), 819-861. doi. 10.1111/j.1467-9701.2009.01171.x

Hughes Hallett, A. & Richter, C. (2009b). Has there been any Structural Convergnence in the Transmission of European Monetary Policies? International Economics and Economic Policy, 6(2), 85-101. doi. 10.1007/s10368-009-0132-5

Hughes Hallett, A. & Richter, C. (2009c). Is the US No Longer the Economy of First Resort? Changing Economic Relationships in the Asia-Pacific Region. International Economics and Economic Policy, 6(2), 207-234. doi. 10.1007/s10368-009-0136-1

IPCC, (2007). Climate Change 2007: The AR4 Synthesis Report. Edited by Rajendra K. Pachauri, IPCC Chairman, Andy Resinger, Head of Technical Support Unit, The Core Writing Team. Published by IPCC, Geneva, Switzerland..

IVDP, (2016). Instituto dos Vinhos do Douro e Porto, dados estatísticos sobre a produção de vinho do Douro e Porto na Região Demarcada do Douro. assessed 29 January 2015. [Retrieved from].

Jenkins, G.M. & Watts, D.G. (1968). Spectral Analysis and its Applications. Holden-Day, San Francisco.

Johnson, L., Pierce, L., Michaelis, A., Scholasch, T. & Nemani, R. (2006). Remote Sensing and Water Balance Modeling in California Drip-Irrigated Vineyards, ASCE World Environmental & Water Resources, Omaha, Nebraska, United Satates.

Jones, G., White, M., Cooper, O. & Storchmann, K. (2005). Climate Change and Global Wine Quality. Climatic Change, 73(3), 319-343. doi. 10.1007/s10584-005-4704-2

Jones, G.V. (2007). Climate Changes and the global wine industry, 13th Australian wine industry technical Conference, Adelaide, Australia.

Jones, G.V. (2012). A climate assessment for the Douro wine region: an examination of the past, present, and future climate conditions for wine production, Associação para o Desenvolvimento da Viticultura Duriense. acessed 19/06/2015. [Retrieved from].

Jones, G.V. & Davis, R.E. (2000). Climate influences on grapevine phenology, grape composition, and wine production and quality for Bordeaux, France. American Journal of Enology and Viticulture, 51(3), 249-261.

LaMotte, L.R. & McWorther, A.J. (1978). An exact test for the presence of random walk coefficients in a linear regression. Journal of the American Statistical Association, 73(364), 816-820.

Lavalle, C. et al., (2009). Climate change in Europe. 3. Impact on agriculture and forestry. A review. Agronomy for Sustainable Development, 29, 433-446. doi. 10.1051/agro/2008068

Laven, G. & Shi, G. (1993). Zur Interpretation von Lagverteilungen, Discussion Paper, Johannes Gutenberg University, Mainz.

Lin, Z. (1997). An Introduction to Time-Frequency Signal Analysis. Sensor Review, 17(1), 46-53. doi. 10.1108/02602289710163364

Lobell, D., Cahill, K. & Field, C. (2007). Historical effects of temperature and precipitation on California crop yields. Climatic Change, 81(2), 187-203. doi. 10.1007/s10584-006-9141-3

Long, S.P., Ainsworth, E.A., Leakey, A.D.B., Nosberger, J. & Ort, D.R. (2006). Food for thought: Lower-than-expected crop yield stimulation with rising CO2 concentrations. Science, 312(5782), 1918-1921. doi. 10.1126/science.1114722

Lorenzo, M.N., Taboada, J.J., Lorenzo, J.F. & Ramos, A.M. (2013). Influence of climate on grape production and wine quality in the Rías Baixas, north-western Spain. Reg Environ Change, 13(4), 887-896. doi. 10.1007/s10113-012-0387-1

Maxwell, J.T., Ficklin, D.L., Harley, G.L. & Jones, G.V. (2016). Projecting future winegrape yields using a combination of Vitis vinifera L. growth rings and soil moisture simulations, northern California, USA. Australian Journal of Grape and Wine Research, 22(1), 73-80. doi. 10.1111/ajgw.12158

May, P. (2004). Flowering and Fruitset in Grapevines. Lythrum Press, Australia.

Moriondo, M. et al., (2015). Modelling olive trees and grapevines in a changing climate. Environmental Modelling & Software, 72: 387-401.

Moriondo, M. et al., (2013). Projected shifts of wine regions in response to climate change. Climatic Change, 119(3-4), 825-839. doi. 10.1016/j.envsoft.2014.12.016

Mosedale, J.R., Abernethy, K.E., Smart, R.E., Wilson, R.J. & Maclean, I.M.D. (2016). Climate change impacts and adaptive strategies: lessons from the grapevine. Global Change Biology, 22(11), 3814-3828. doi. 10.1111/gcb.13406

Nerlove, M., Grether, D.M. & Carvalho, J.L. (1995). Analysis of Economic Time Series. Academic Press, New York.

OIV, (2016). Organization Internationale de la Vigne et du Vin – Statistiques. assessed 30 October 2016. [Retrieved from].

Peterson, T.C. et al., (1998). Homogeneity adjustments of in situ atmospheric climate data: a review. International Journal of Climatology, 18(13), 1493-1517. doi. 10.1002/(SICI)1097-0088(19981115)18:13<1493::AID-JOC329>3.0.CO;2-T

Pierce, L., Nemani, R. & Johnson, L. (2015). VSIM - Vineyard Soil Irrigation Model – release 3/1/06 - User Guide. assessed 29 January 2015. [Retrieved from].

Ploberger, W., Krämer, W. & Kontrus, K. (1989). A New Test For Structural Stability in the Linear Regression Model. Journal of Econometrics, 40(2), 307-318. doi. 10.1016/0304-4076(89)90087-0

Quiroga, S. & Iglesias, A. (2009). A comparison of the climate risks of cereal, citrus, grapevine and olive production in Spain. Agricultural Systems, 101(1-2), 91-100. doi. 10.1016/j.agsy.2009.03.006

Rabiner, L.R., Schafer, R.W. and Rader, C.M., 1969. The chirp z-transform algorithm and its application. Bell System Technical Journal, 48(5), 1249-1292. doi. 10.1002/j.1538-7305.1969.tb04268.x

Reis, R. & Lamelas, H. (1988). Statistical study of decade series of water balance and its components of potencial evapotranspiration calculated by Penman's method. Vol. 36, Instituto Nacional de Meteorologia e Geofisica, Lisbon.

Santos, J., Malheiro, A.C., Karremann, M.K. & Pinto, J.G. (2010). Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions.

Santos, J.A., Grätsch, S.D., Karremann, M.K., Jones, G.V. & Pinto, J.G., (2013). Ensemble projections for wine production in the Douro Valley of Portugal. Climatic Change, 117(1-2), 211-225. doi. 10.1007/s10584-012-0538-x

Saxton, K.E., Rawls, W.J., Romberger, J.S. & Papendick, R.I. (1986). Estimating generalized soil-water characteristics from texture. Soil Sci. Soc. Am. J., 50(4), 1031-1036.

Schultz, H.R. (2003). Differences in hydraulic architecture account for near-isohydric and anisohydric behaviour of two field-grown Vitis vinifera L. cultivars during drought. Plant Cell and Environment, 26(8), 1393-1405. doi. 10.1046/j.1365-3040.2003.01064.x

Thornthwaite, C.W. (1948). An approach toward a rational classification of climat. Geografical Review, 38(1), 55-94. doi. 10.2307/210739

Vasconcelos, M.C., Greven, M., Winefield, C.S., Trought, M.C.T. & Raw, V. (2009). The Flowering Process of Vitis vinifera: A Review. American Journal of Enology and Viticulture, 60(4), 411-434.

Wells, C. (1996). The Kalman Filter in Finance. Advanced Studies in Theoretical and Applied Econometrics, 32. Kluwer Academic Publishers, Dordrecht.

Williams, L.E. & Ayars, J.E. (2005). Grapevine water use and the crop coefficient are linear functions of the shaded area measured beneath the canopy. Agricultural and Forest Meteorology, 132(3), 201-211. doi. 10.1016/j.agrformet.2005.07.010

Wolters, J. (1980). Stochastic Dynamic Properties of Linear Econometric Models. Springer Verlag, Berlin.



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