ANALYSIS OF CLIMATE CHANGE INDICES IN

RELATION TO WINE PRODUCTION: A CASE

STUDY IN THE DOURO REGION (PORTUGAL).D. Blanco-Ward1, A. Monteiro1, M. Lopes1, C. Borrego1, C. Silveira1,, C. Viceto2,,

A. Rocha2, A. Ribeiro3, João Andrade3, Manuel Feliciano3, João Castro3, David

Barreales3, Cristina Carlos4, Carlos Peixoto5, A. Miranda1

1 Dept of Environment and Planning, Centre for Environmental and Marine Studies (CESAM), Univ of Aveiro, Portugal

2 Physics Department, CESAM, Univ of Aveiro, Portugal.

3 Mountain Research Centre (CIMO), Polytechnic Institute of Bragança, Portugal.

4 Association for the Development of Viticulture in the Douro region (ADVID), Portugal

5 Casa Ramos Pinto, Portugal

40th World Congress of Vine and Wine, 29 May – 02 June 2017, Sofia, Bulgaria

Introduction Analysis of climate change in relation to wine production

Depending on GHGs emissions scenario, an increase in global mean

surface temperature from 1°C to 3.7°C by the end of the century is

expected (IPPC, 2014).

An increase in temperature would:

Advance phenology

Alter the supply of metabolites to the grape

Advanced phenology in the Portuguese

Douro valley (28-04-2017)

Disastrous consequences in the upper Galician

(Spanish) Minho-Sil valley (29-04-2017)

Introduction Analysis of climate change in relation to wine production

The Douro Demarcated Region (DDR) is located in northern

Portugal. It runs along both margins of the Douro river from its

midcourse in the East to the border of Spain in the West.

It is divided into three sub-regions: Baixo Corgo, Cima Corgo and

Douro superior, which differ in climatic and socio-economic factors.

The Douro DR

Extension: there are about 43,480 ha of vineyards in the region.

Production: as of 2016, about 133.3 millions of litres of wine.

Analysis of climate change in relation to wine production

Sub-regions Baixo Corgo Cima Corgo Douro Superior

Vineyard area 13,368 ha 20,270 ha 9,842 ha

Wine growers 8,855 9,119 3,458

Mean vineyard area 1.5 ha 2.2 ha 2.8 ha

60,4%

32,0%

4,5%

2,5%

0,6%

0,1%

Port Wine

DO wine

Table wine

Muscat

GI Wine

DO Sparkling wine

Climate: Mediterranean, warm temperate Köppen Csb climate.

Distance to sea, height, and slope orientation generate mesoclimates.

Soils: aric anthrosols upon schists, cambisols, fluvisols (FAO 1988).

Varieties: many, ‘Touriga Franca’ (22%), ‘Tinta Roriz’ (12%)...

Step slope viticulture:

‘Pre-Phylloxera socalcos’ (3000-3500 plants/ha)

‘Post-Phylloxera socalcos’ (about 6000 plants/ha)

‘Patamares’ (3000-3500 plants/ha)

‘Vinhas ao alto’ (4500-5000 plants/ha)

Analysis of climate change in relation to wine productionThe Douro DR

HI DI CI MCC system: HI+2/DI+2/CI+1

2740°C day -126 mm 13.6°C Warm/Very dry/Cool nights

Objectives

Objectives:

1) Evaluate the influence of climate parameters, bioclimatic and

climate change indices on vintage yield and quality.

2) Assess the possible impacts of estimated climate changes for mid-

term and long-term future scenarios.

Analysis of climate change in relation to wine production

Data and methods

High-resolution WRF climate simulations:

1. ERA-Interim and MPI-ESM-LR driven WRF climate simulations were

performed for three 20-year periods under RCP 8.5: recent-past (1986-

2005), mid-future (2046-2065) and long-future (2081-2100).

2. These simulations were implemented in three nested domains with

increasing resolution: 81 km, 27 km, and 9 km.

Analysis of climate change in relation to wine production

Analysis of climate change in relation to wine productionData and methods

Phenological modelling:

A mixed ‘Tinta Roriz-Touriga Franca’ model to estimate key stages (e.g. b-

bud burst, f-flowering and v-véraison) based on specific varietal growing

degree days requirements was applied to the four final resulting high-

resolution (9 km) climate datasets (WRF-ERA recent-past, WRF-MPI

recent-past, WRF-MPI mid-future and WRF-MPI long-future).

Source: C. Real et al. (2015)

Data and methods Analysis of climate change in relation to wine production

Climate parameters and indices:

26 climatic parameters, 4 bioclimatic indices and 28 climate change

indices were calculated yearly.

Parameters Bioindices ETCCDI indices

Mean of daily T max Winkler index SU25, summer days per year

Mean of daiy T min Huglin index SU35, hot summer days per year

T avg = (Tmax + Tmin) / 2 Cool night index SU33, hot summer days per year

P, sum of daily precipitation Dryness index CSDI, cold spell duration index

GST, growing season Tavg WSDI, warm spell duration index

GSP, growing season P R10, heavy rain days per year

CWD, maximum spell of wet days

Annual: 2 Annual: 4 Annual: 7

Modelled phenology-based: 12 Modelled phenology-based: 21

Monthly period-based: 12

26 parameters per year 4 indices per year 28 indices per year

Data and methods Analysis of climate change in relation to wine production

Vintage yield and quality data for the recent-past (1986-2005):

Data on average yield (hl/ha) for all types of wines.

Data on Port vintage quality from 9 scoring systems.

Data were selected from available academic literature: A. C. Real (2014, 2016).

Source Acronym

Berry Bros & Rud BBR

Decanter DC

Instituto dos Vinhos do Douro e do Porto IVDP

Michael Broadbent MB

Sotheby’s Wine Encyclopaedia SWE

Vintages VT

Wine Advocate WA

Wine Enthusiast WE

Wine Spectator WS

WRF-ERA data validation:

9 km resolution final climate simulations accurately describe spatial

and temporal patterns and phenological stages across the DDR.

Mean 1986-2005 GST across the DRR

Results Analysis of climate change in relation to wine production

1986-2005 GST medians Véraison date

Region WRF-ERA WorldClim Model Field data 95%

Baixo Corgo 17.1 17.5 234

175-229Cima Corgo 17.0 17.5 234

D. Superior 18.0 18.0 223

Douro superior monthly Tavg - P chart

Results Analysis of climate change in relation to wine production

Vintage yield and quality in relation to climate:

Correlations found are of moderate type.

Elevated heat sums (GDDgs, HI) with elevated T max from véraison

to maturity (T max-v) are related with higher grapevine yields.

Quality ratings relate positively with hot summer days from flowering

to véraison (SU35,33-f) and with elevated T max from bud burst to

flowering (T max-b) but negatively with prolonged heatwaves.

1986-2005 Yield WE MB DC

GDDgs 0.56**

HI 0.52*

T max-b 0.51*

T max-v 0.52*

SU33-f 0.49*

SU35-f 0.64**

WSDI -0.62*

Results Analysis of climate change in relation to wine production

MPIr MPIm MPIl

GST (°C) µ 15.6** 18.0** 20.1**

2 0.8 0.9 0.8

Véraison onset µ 236** 213** 198**

2 159 84 57

SU35 (°C) µ 2** 15** 42**

2 12** 71* 176*

WRF-MPI RCP 8.5 climate simulations:

GST significantly increases, on average, 2.4°C in the mid-future and

2.1°C more in the long-future.

There is a mean advancement on véraison of 23 days in the mid-future

and of another 15 days more in the long-future.

The number of hot summer days also increases very significantly from

2 days to 15 days in the mid-future and 27 days more in the long-future.

Conclusions: Analysis of climate change in relation to wine production

Concluding remarks:

Regional ERA-WRF recent-past climate simulations coupled with

phenological modelling are useful to relate climate, yield and quality.

Regional MPI-WRF future climate simulations reveal advancements in

phenology an higher incidence of hot summer days.

Delay phenology and reduce water stress by suitable plant material

selection and vineyard management to preserve wine typicity.

Acknowledgements Analysis of climate change in relation to wine production

The authors wish to thank the financial support of the DOUROZONE project (PTDC/AAG-

MAA/3335/2014; POCI-01-0145-FEDER-016778) through the Project 3599 – Promoting the

scientific production and the technological development, and thematic networks (3599-PPCDT)

- and through FEDER.

Web page: http://dourozone.web.ua.pt

Contact email: Daniel Blanco-Ward, dblancoward@ua.pt