Historical Grape Harvest:
Background:
CLIMATE AND WRITTEN SOURCES
Taken from: http://cast.uark.edu/research/research_theses/david_holt/climate_and.htm
As early as 3000 BC, historical documents recorded information about climate, either by direct reference or by
inference. By looking directly to the written word, many different aspects of past environments can be extracted from
temperature to sunspot activity. The question is what elements of climate did the authors of these historical documents
find important enough to record?
Various historical records “hide” climate data, not only in agricultural accounts, but in seemingly climateirrelevant accounts as well. Tucked into letters from the Czarina, Catherine the Great, to the peasant, Menetra, are
casual comments concerning food production or snowfall and the like that can be compiled into relatively detailed
climate reconstructions (Catherine et al., 1961, Ménétra and Roche, 1986). An accountant’s record book from a Kentish
Estate contains proxy data concerning crop prices, flood damages, or times of famine, not just a ledger of expenditures
of a large English estate (Toke and Lodge, 1927). Ancient texts yield information in the form of poetry, as with Ovid’s
Metamophoses, or military stratagem may provide insight about drought in Thucydides’ Peloponnesian War.
Agriculture records are valuable for their reflection on production, flora variety, and associated changes over
time. This is evident in the book, Times of Feast, Times of Famine; the various French winery records mirror times of
drought and times of prosperity (Le Roy Ladurie, 1988). These long continuous records of French agricultural
productivity show the direct relationship between vineyard yields and climate variability.
A good example of a broad-based, comprehensive listing of production in England is a document entitled,
Agricultural Records. It was initially compiled by Thomas H. Baker in 1883, updated by John Stratton in 1969, with the
latest version compiled by Ralph Whitlock in 1978 (Stratton and Brown, 1978). The purpose of the book is to provide a
running record of the agricultural and climate changes in England from as many sources as possible. The authors used
everything from meteorological records to ancient legend and anecdotal sources. Agricultural Records is an
amalgamation of many sources from AD 220 to 1977 attempting to form an accurate agricultural and climatic history of
England.
Agricultural Records provides excellent insight into the past climates of England. Granted there is some
climatological correlation between the United Kingdom and central Europe, but the reason this document is evaluated
here is that it is one of the few comprehensive accounts of agriculture in Europe that stretch to the late Iron Age. There
is a relationship between the technological stages of England and central Europe, so this document might yield insight
into the schema of documenting weather before meteorological data in Europe. But do these records document all the
environmental characteristics of the region or just some of them? What did the authors consider worthy of
documenting? How can these documents be analyzed for content so long after they were written? This is directly
related to the validity of historical documents as climate proxy indicators. The only means to approach these types of
quandaries is through a methodology found in rhetorical communication called “Content Analysis”.
Factors Affecting the Grape Harvest
The individual grape variety, the ripeness factor and the weather factor have the greatest influence on “when” to
harvest a cluster of grapes. Primarily it’s the grape’s tannin, acid and sugar content that determines how ripe the grape
actually is and they are key components for influencing a wine’s future finesse and strategic presence. The weather has
a tremendous impact on how the grapes in a given year will behave in a bottle of wine. For starters, the ideal weather
for growing grapes includes a winter that is cool with good moisture. However, once spring hits heavy moisture is
“discouraged” and throughout the summer cool nights with temperate days is the goal. During the actual harvest,
wineries are praying for dry weather to bring the grapes home.
Wine Grape Harvest Time
August, September and October mark prime time for the annual grape harvest for most wineries in Europe and North
America. Australia, New Zealand South America and South Africa, landing decidedly below the equator, enjoy lots of
southern exposure which manipulates the harvest season so that the majority of their grapes are grabbed in the spring,
from February to April.
Data Set:
SUGGESTED DATA CITATION: Chuine, I., et al.. 2005.
Burgundy Grape Harvest Dates and Spring-Summer Temperature Reconstruction
IGBP PAGES/World Data Center for Paleoclimatology
Data Contribution Series #2005-007.
NOAA/NGDC Paleoclimatology Program, Boulder CO, USA.
DESCRIPTION:
Grape harvest dates were collected from up to 18 cities or villages in Burgundy (the actual number depends
on the year) since 1370. To avoid possible biases due to the variability of data availability each year, Dijon - the longest
series overall and the only one available for some periods - was chosen as the reference series. However, the 17 other
series were used to take into account the regional variability. All series were standardized such that they present the
same average date as Dijon over their common recorded period. For each year t the harvest date Ht was computed as
the median date among all available standardized dates including Dijon. The temperature anomalies are with respect to
the April to August mean temperature of Dijon between 1960 and 1989.
Burgundy Grape Harvest Dates and Spring-Summer Temperature Reconstruction
1394
38
-1.11
1420
-1.1
3.26
1446
43
-1.51
1395
20
0.52
1421
25.7
-0.06
1447
43
-1.49
-0.17
1396
26
-0.17
1422
12.5
1.36
1448
50
-1.97
25
-0.01
1397
22
0.32
1423
26.6
-0.12
1449
29
-0.37
1372
28.1
-0.37
1398
25
0.07
1424
12.7
1.23
1450
25
-0.01
1373
20.7
0.41
1399
26
-0.05
1425
16
0.91
1451
39
-1.2
1374
28.2
-0.29
1400
11.6
1.37
1426
14.9
1.12
1452
24
-0.01
1375
20.2
0.45
1401
19.9
0.58
1427
25
0.01
1453
37
-1.02
1376
25.2
-0.12
1402
16.9
0.87
1428
36
-1.02
1454
34
-0.78
1377
21
0.34
1403
19.1
0.56
1429
24
0.11
1455
31
-0.54
1378
25.5
-0.06
1404
29.9
-0.54
1430
15
1.05
1456
33
-0.78
1379
24.7
0.05
1405
28.7
-0.37
1431
19
0.6
1457
14
1.18
1380
22.2
0.17
1406
26.7
-0.12
1432
18
0.65
1458
18
0.71
1381
23.5
0.16
1407
29.2
-0.37
1433
12
1.49
1459
36
-0.96
0.97
1408
-0.54
1434
3.09
1460
21
0.29
1.98
1409
0.57
1435
-0.02
1461
16
0.92
1.98
1410
0.77
1436
-2.3
1462
8
1.88
1.72
1411
-1.02
1437
-0.24
1463
35
-0.89
0.43
1412
0.43
1438
-0.18
1464
14
1.04
0.24
1413
0.99
1439
-0.18
1465
41
-1.33
-0.37
1414
-0.46
1440
-0.37
1466
27
-0.18
-0.06
1415
0.24
1441
0.72
1467
27
-0.19
26.4
-0.17
1442
13
1.32
1468
32
-0.68
Year
Harves
t date
temp
anomal
y
1370
27
1371
1382
1383
1384
1385
1386
1387
1388
1389
15.7
7.5
6.9
9.9
20
23
27.5
25.5
29.7
19.7
17.2
37.2
19.1
15.9
30
22.9
1
25
56
28
27
27
28
18
1390
15.1
0.97
1416
1391
16.2
0.86
1417
22.8
0.24
1443
26
-0.06
1469
20
0.5
1392
39.7
-1.33
1418
11.7
1.52
1444
22
0.18
1470
37
-1.02
1393
3.4
2.48
1419
20.9
0.44
1445
36
-0.96
1471
11
1.56
1472
1473
1474
23
-2
39
0.12
1516
3.63
1517
-1.2
1518
1.29
1560
-0.07
1561
-0.62
1562
40
-1.22
1563
12
26
32
-0.89
1604
22
0.17
-0.02
1605
19
0.58
-0.06
1606
35
-0.89
28
-0.21
1607
24
0.08
34
25
26
1475
31
-0.54
1519
1476
28
-0.37
1520
35
-0.96
1564
48
-1.86
1608
31
-0.62
1477
41
-1.33
1521
4
2.64
1565
32
-0.62
1609
28
-0.21
1478
19
0.59
1522
5
2.48
1566
30
-0.46
1610
20
0.48
1479
16
0.94
1523
-5
4.1
1567
20
0.48
1611
15
1.03
1480
39
-1.22
1524
14
1.03
1568
34
-0.89
1612
31
-0.62
1481
47
-1.76
1525
21
0.38
1569
26
-0.05
1613
26
-0.04
1482
16
0.91
1526
27
-0.17
1570
30
-0.46
1614
36
-0.96
1483
15
1.04
1527
35
-0.89
1571
14
1.13
1615
21
0.35
1484
20
0.34
1528
35
-0.96
1572
22
0.2
1616
12
1.31
1485
43
-1.49
1529
43
-1.49
1573
41
-1.33
1617
33
-0.68
1486
20
0.51
1530
15
1.04
1574
28
-0.22
1618
36
-0.96
1487
22
0.31
1531
26
-0.06
1575
26
-0.06
1619
26
-0.06
-1.5
1532
0.36
1576
-0.54
1620
28
-0.37
-0.54
1533
-0.96
1577
-0.68
1621
46
-1.7
0.03
1534
-0.22
1578
0.29
1622
24
0.11
-1.6
1535
-1.11
1579
-1.2
1623
16
0.93
-0.62
1536
1.82
1580
-0.62
1624
14
1.04
-0.89
1537
-1.11
1581
-0.68
1625
34
-0.78
0.72
1538
0.52
1582
-0.24
1626
31
-0.54
1.44
1539
-0.06
1583
1.29
1627
45
-1.61
-1.49
1540
-0.89
1584
-0.05
1628
44
-1.59
34
-0.78
1585
37
-1.02
1629
27
-0.18
1488
1489
1490
1491
1492
1493
1494
1495
1496
42
31
25
45
31
35
18
12
42
20
36
28
38
8
38
20
26
34
30
33
22
39
31
33
28
13
25
1497
41
-1.33
1541
1498
26
-0.07
1542
50
-1.94
1586
32
-0.62
1630
20
0.48
1499
28
-0.23
1543
31
-0.54
1587
43
-1.49
1631
20
0.55
1500
14
1.02
1544
28
-0.37
1588
24
-0.04
1632
34
-0.89
1501
19
0.61
1545
14
1.17
1589
26
-0.06
1633
37
-1.02
1502
29
-0.37
1546
25
-0.01
1590
10
1.67
1634
33
-0.68
1503
28
-0.2
1547
29
-0.37
1591
32
-0.62
1635
21
0.36
1504
14
1.08
1548
31
-0.62
1592
32
-0.68
1636
4
2.48
1505
43
-1.5
1549
34
-0.78
1593
31
-0.54
1637
3
2.82
1506
28
-0.21
1550
37
-1.02
1594
33
-0.68
1638
9
1.81
1507
21
0.38
1551
28
-0.21
1595
25
-0.01
1639
20
0.51
1508
30
-0.54
1552
13
1.16
1596
34
-0.89
1640
31
-0.62
1509
20
0.51
1553
35
-0.89
1597
43
-1.49
1641
33
-0.68
1510
30
-0.46
1554
22
0.32
1598
23
0.16
1642
33
-0.68
-1.56
1555
-1.43
1599
1.16
1643
31
-0.54
0.03
1556
2.32
1600
-1.58
1644
15
0.89
0
1557
-0.68
1601
-1.11
1645
11
1.55
-1.02
1558
-0.46
1602
-0.26
1646
17
0.84
-0.89
1559
2.64
1603
0.92
1647
18
0.69
1511
1512
1513
1514
1515
44
24
25
37
35
42
5
33
30
4
14
44
38
28
16
1648
1649
1650
31
38
34
-0.62
1692
-1.11
1693
-0.78
1694
-1.22
1736
-0.46
1737
1.01
1738
33
-0.68
1739
39
30
15
0.17
1780
23.6
0.07
0.32
1781
15.1
0.97
-0.78
1782
35.1
-0.89
28.1
-0.28
1783
20.6
0.43
22.1
21.1
34.1
1651
22
0.34
1695
1652
20
0.39
1696
31
-0.62
1740
49.6
-1.94
1784
18.6
0.57
1653
11
1.55
1697
24
0.13
1741
30.1
-0.46
1785
26.1
-0.12
1654
32
-0.62
1698
43
-1.49
1742
36.1
-0.96
1786
30.1
-0.46
1655
23
0.2
1699
28
-0.24
1743
29.1
-0.37
1787
37.1
-1.02
1656
26
-0.19
1700
33.6
-0.78
1744
34.1
-0.89
1788
18.1
0.59
1657
22
0.3
1701
26.1
-0.12
1745
30.6
-0.54
1789
39.6
-1.22
1658
30
-0.46
1702
20.1
0.44
1746
28.6
-0.37
1790
28.6
-0.37
1659
30
-0.46
1703
27.1
-0.21
1747
33.6
-0.68
1791
21.1
0.32
1660
30
-0.54
1704
14.6
0.97
1748
29.1
-0.46
1792
35.1
-0.96
1661
15
1.05
1705
30.1
-0.46
1749
30.6
-0.54
1793
27.6
-0.2
1662
22
0.34
1706
8.1
1.88
1750
27.1
-0.21
1794
17.2
0.77
1663
38
-1.11
1707
25.1
-0.07
1751
39.6
-1.22
1795
31.2
-0.54
0.55
1708
-0.12
1752
-0.62
1796
37.6
-1.11
1.04
1709
-0.46
1753
0.17
1797
38.6
-1.11
1.66
1710
0.29
1754
-0.89
1798
18.1
0.68
-0.23
1711
-0.12
1755
0.31
1799
42.1
-1.43
0.47
1712
-0.46
1756
-1.29
1800
25
-0.08
1.54
1713
-1.02
1757
-0.29
1801
31.2
-0.54
0.31
1714
-0.54
1758
-0.12
1802
20
0.5
0.93
1715
-0.28
1759
-0.06
1803
23.1
0.19
-0.37
1716
-0.89
1760
0.3
1804
31
-0.62
27.1
-0.18
1761
19.1
0.57
1805
47
-1.76
1664
1665
1666
1667
1668
1669
1670
1671
1672
19
15
10
28
19
11
22
16
28
25.1
30.1
21.1
26.6
28.6
37.1
31.1
28.1
34.1
31.6
23.1
35.1
21.6
39.1
28.1
26.6
25.6
20.1
1673
35
-0.89
1717
1674
20
0.54
1718
5.1
2.17
1762
19.1
0.58
1806
24.9
0.05
1675
44
-1.52
1719
6.1
2.09
1763
39.1
-1.22
1807
24
0.11
1676
9
1.69
1720
29.2
-0.46
1764
19.6
0.46
1808
28.8
-0.46
1677
27
-0.18
1721
34.6
-0.78
1765
32.1
-0.62
1809
43.8
-1.48
1678
20
0.5
1722
26.1
-0.12
1766
29.1
-0.37
1810
31.8
-0.62
1679
23
0.19
1723
18.1
0.68
1767
40.1
-1.29
1811
12.3
1.4
1680
9
1.7
1724
19.1
0.43
1768
31.6
-0.62
1812
36.1
-1.02
1681
9
1.79
1725
44.1
-1.6
1769
31.1
-0.54
1813
38.1
-1.11
1682
28
-0.22
1726
11.6
1.51
1770
41.6
-1.43
1814
35
-0.89
1683
13
1.26
1727
13.6
1.23
1771
29.1
-0.37
1815
25.5
-0.07
1684
4
2.48
1728
18.1
0.56
1772
28.6
-0.46
1816
55.2
-2.21
1685
12
1.4
1729
34.1
-0.78
1773
32.1
-0.62
1817
45.6
-1.7
1686
4
2.64
1730
31.1
-0.54
1774
25.6
-0.07
1818
21
0.43
-0.37
1731
0.19
1775
-0.46
1819
25.7
-0.06
-0.22
1732
-0.12
1776
-0.68
1820
37.6
-1.11
-0.19
1733
-0.12
1777
-0.89
1821
45.1
-1.64
0.29
1734
0.68
1778
-0.12
1822
0.3
2.97
0.82
1735
-1.22
1779
-0.06
1823
41.6
-1.43
1687
1688
1689
1690
1691
29
27
27
22
17
23.1
25.6
26.1
18.1
39.6
30.1
32.6
35.6
26.1
25.1
1824
1825
1826
41.6
21.6
30.9
-1.46
1868
0.32
1869
-0.54
1870
1.36
1912
0.07
1913
0.76
1914
35
-0.89
1915
11.9
24.3
17.2
-0.46
1956
42.1
-1.49
-0.62
1957
32.1
-0.62
-0.89
1958
30.1
-0.46
17.2
0.76
1959
16.1
0.86
28.6
32.6
35.1
1827
26
-0.06
1871
1828
28.3
-0.37
1872
31.4
-0.62
1916
37.2
-1.11
1960
20.1
0.31
1829
40.9
-1.33
1873
31.4
-0.54
1917
12.4
1.4
1961
25.1
-0.06
1830
26.7
-0.12
1874
25.3
-0.05
1918
25.1
-0.04
1962
38.1
-1.11
1831
27.8
-0.21
1875
28.5
-0.29
1919
28.1
-0.3
1963
36.1
-0.96
1832
32.8
-0.78
1876
34
-0.89
1920
26.6
-0.19
1964
21.6
0.24
1833
27.4
-0.2
1877
31.3
-0.54
1921
23.1
0.19
1965
42.1
-1.43
1834
18.1
0.69
1878
35.8
-0.96
1922
25.6
-0.06
1966
27.1
-0.17
1835
34.1
-0.78
1879
45
-1.64
1923
27.1
-0.17
1967
30
-0.46
1836
35.5
-0.96
1880
31.6
-0.62
1924
24.6
-0.04
1968
30.1
-0.54
1837
36.1
-0.96
1881
27.1
-0.16
1925
23.6
0.17
1969
35.1
-0.89
1838
37.8
-1.02
1882
33
-0.68
1926
26.1
-0.12
1970
30.1
-0.46
1839
27.9
-0.17
1883
36.6
-0.96
1927
23.6
0.19
1971
18.1
0.68
0.07
1884
-0.54
1928
-0.46
1972
36.1
-1.02
-0.12
1885
-0.12
1929
-0.07
1973
24.1
0.06
1.08
1886
-0.46
1930
-0.28
1974
24.1
0.08
-1.5
1887
-0.46
1931
-0.2
1975
24.6
0.07
0.18
1888
-1.11
1932
-1.22
1976
4.1
2.17
-1.02
1889
-0.04
1933
-0.37
1977
34
-0.78
1.35
1890
-0.68
1934
18.6
0.7
1978
-0.62
1891
-1.43
1935
32.6
-0.62
1979
25
-0.01
-0.37
1892
0.17
1936
-0.59
1980
39
-1.22
-1.4
3.26
1937
20.6
0.42
1981
25
0.02
1840
1841
1842
1843
1844
1845
1846
1847
1848
23.8
26.3
14.6
42.9
23
37.8
12.6
31.7
28.3
30.1
26.1
30.1
29.6
37.2
25.2
33.2
42.2
22.6
28.6
25.1
28.1
27.6
38.6
28.6
30.6
1849
29.8
-0.46
1893
1850
38.8
-1.11
1894
30.1
-0.46
1938
34.1
-0.78
1982
18
0.71
1851
37.6
-1.02
1895
24.1
0.06
1939
44.1
-1.6
1983
24
0.12
1852
31
-0.62
1896
28.1
-0.37
1940
25.1
-0.12
1984
33
-0.78
1853
38.4
-1.11
1897
21.1
0.32
1941
36
-0.96
1985
27
-0.2
1854
31.9
-0.62
1898
31.6
-0.59
1942
22.6
0.24
1986
26
-0.07
1855
35.9
-0.96
1899
27.6
-0.18
1943
22.6
0.24
1987
32
-0.62
1856
36.3
-1.02
1900
28.6
-0.46
1944
33.6
-0.78
1988
23
0.08
1857
20.4
0.45
1901
16.1
0.86
1945
17.1
0.76
1989
16
0.88
1858
22
0.31
1902
32
-0.62
1946
23.1
0.18
1990
19
0.6
1859
20.3
0.42
1903
36.6
-0.96
1947
16.1
0.85
1991
25
0
1860
40.1
-1.33
1904
21.6
0.24
1948
26.1
-0.21
1992
18
0.6
1861
24.8
0.06
1905
24.6
0.06
1949
23.6
0.18
1993
20
0.49
1862
21.9
0.32
1906
22.1
0.24
1950
21.6
0.3
1994
21
0.42
-0.46
1907
-0.78
1951
-1.02
1995
26
-0.06
-0.62
1908
0.19
1952
0.69
1996
20
0.38
1.72
1909
-0.68
1953
0.16
1997
15
1.04
-0.68
1910
-0.89
1954
-1.11
1998
19
0.63
-0.37
1911
1.38
1955
-0.62
1999
19
0.63
1863
1864
1865
1866
1867
29.6
31.6
9.3
32.8
28.8
34.1
22.6
33.1
35.3
12
37.1
17.6
23.6
38.1
32.1
2000
14
1.03
2001
20
0.5
2002
18
0.71
2003
-13
5.86
Questions:
1. You will need to generate two line graphs:
a. Grape Harvest Date after September 1st vs. year (1800-2003)
b. Temperature Anomaly vs. years (1880- 2003)
2. Describe what you see? Decipher the relationship(s) and record observations.
3. What conclusions can be made about the climate through harvest date after September 1st and temperature?
Use 3 pieces of evidences from your research to support your ideas.
4. How can present day data such as this be use by paleoclimatologists to reconstruct past climates?
5. What are the limitations of this source of information?
Resources:

http://www.ncdc.noaa.gov/paleo/historical.html