Bulletin

CropWatch bulletin
OverviewMain producing and exporting countries

Authors: 超级管理员 | Edit: Miao

1. Introduction

The global agro-climatic patterns that emerge at the MRU level (chapter 1) are reflected with greater spatial detail at the national and subnational administrative levels described in this chapter. The “core countries”, including major producing and exporting countries are all the object of a specific and detailed narrative in the later sections of this chapter, while China is covered in Chapter 4. Sub-national units and national agro-ecological zones receive due attention in this chapter as well.

In many cases, the situations listed below are also mentioned in the section on disasters (chapter 5.1) although they tend to be limited spatially so that the statistical abnormality is not necessarily reflected in the climate statistics that include larger areas. Current examples include Kerala floods or the Central American droughts. The latter was followed, during the same reporting period from July to October 2018 by excess precipitation which, in turn, caused floods and landslides. On the other hand,  when extreme conditions affect a large area, even relatively moderate ones, they are bound to have been even more extreme in some locations.    

No attempts are normally made, in this chapter, to identify global patterns that were already covered in Chapter 1. The focus is on 165 individual countries and sometimes their subdivisions for the largest ones.

2. Overview of weather conditions in major agricultural exporting countries

Just 20 countries include the top 10 exporters of maize, rice, wheat, and soybeans, with the United States and Argentina exporting all 4 and Brazil, Ukraine and Russia exporting three of them each!

The United States and Brazil did not suffer major climate anomalies at the national level. In fact, both countries recorded above-average rainfall during the reporting period (+26% and +12%, respectively). In the USA, the JASO period corresponds to the middle and late stages of summer crops and the planting of winter wheat.  Precipitation in the main maize and soybean areas was generally high and possibly excessive in some States such as Iowa. In southern Brazil, winter crops were in their vegetative stage while summer crops (north) were being harvested during the first half of the period. Altogether, conditions were thus conducive to normal crop development.  

Paraguay recorded very abundant precipitation (+43%) that occurred after the harvest of summer crops and during the overwintering of wheat. Altogether, the water supply may have interfered with the preparation of land for summer crop season, which is starting now, but major negative impacts are unlikely.   

Among the major maize exporters in Europe, several suffered a shortage of precipitation at the critical grain filling stage, including Serbia (-35%), Romania (-43%), and especially France (-18%) where, in addition, both temperature (+0.7°C) and sunshine (+10%) where high, increasing crop water consumption. It is likely that the central and eastern parts of France have suffered more than the major western (Atlantic) maize producer regions where irrigation is more common.

In the east, Ukraine had a slight precipitation deficit (-7%) accompanies, as in France, by high temperature and sunshine.

Close to average precipitation occurred in Argentina (-4% nationwide) at a time which corresponds to overwintering of wheat and barley and the very early stages of summer crops. In the major agricultural provinces of Cordoba and Buenos Aires, rather contrasting situations prevail,  with Cordoba suffering a significant deficit of 26 %, accompanied by low sunshine. Buenos Aires recorded a slightly positive anomaly of rainfall at +8%. Compared with the very variable outcome of the previous five years, both Provinces show an increase of the biomass production potential, which points at reasonably good prospects compared with recent years.

Ukraine, Russia, and Kazakhstan are among the major producers of spring wheat (RUS, KAZ) and barley (KAZ, UKR) in addition to growing sizeable amounts of maize (RUS, UKR). The crops were at vegetative to early harvest stages during the reporting period.  They experienced close to average precipitation (+7% in Russia and -7% in Ukraine) but Kazakhstan, like several of her neighbors, recorded well above average values (+46%) over the main summer crop zones.  

Wheat in Australia was overwintering during the reporting period, over which drought conditions prevailed (-30%) just after the harvest of summer crops.  The volume of November and December rainfall will be crucial for the outcome of the season.

For the major Asian rice exporters (India, Thailand, Vietnam, Pakistan, and Cambodia) the current JASO reporting period corresponds to the core growing season, and often includes late planting and early harvest, depending on very variable cycle length. In India, in particular, where Kharif rice is produced mostly in the central-eastern States, the  JASO months cover a variety of stages. As the rice is almost exclusively grown as lowland or irrigated crop, precipitation is less of a limiting factor than for other commodities.  With the exception of dry and cool Cambodia (RAIN down 8%, TEMP -0.8°C) and Pakistan (-12% for RAIN, TEMP 0.6°C), the countries recorded average precipitation and close to average TEMP. Sunshine was average as well, except in INDIA where RADPAR dropped 5%. India is also the country with the largest drop in biomass potential (18%) compared with the recent five years.  For the other listed countries, the drop is just 3% on average.

3. Rainfall anomalies and biomass production potential changes (figures 3.1 and 3.2)

3.1 A Caveat

Rainfall anomalies are expressed against the recent 15-year average (2003-2017) while BIOMSS is compared against the period 2013-2017.

[Figure 3.1. Global map of July to October 2018 rainfall (RAIN) by country and sub‐national areas, departure from 15YA (percentage)]

[Figure 3.2. Global map of July to October 2018 biomass production potential (BIOMSS) by country and sub‐national areas, departure from 15YA (percentage)]

3.2 Low rainfall

The most severe drought conditions prevailed in Oceania and adjacent south-east Asia: Timor Leste had a 71% negative rainfall anomaly, followed by New  Zealand (-68%), New Caledonia and Australia (-30%). Other countries in the region are affected as well, albeit less severely. Both temperature (+1.3°C) and sunshine (+3%) were high, and the resulting BIOMSS fell significantly by 33%.

Among the 26 countries which recorded a rainfall deficit larger than 30%, about half (12) are located in throughout the European continent, from Portugal in the west (-52%) to Moldova in the east (-33%) and from Germany in the north (-40%) to Albania in the south (-38%), confirming the widespread drought. TEMP was generally closer to average (average departure +0.6°C) although heatwave conditions affected Portugal, Germany and the Netherlands, all three at +1.3°C. Sunshine increased 7% above average and BIOMSS fell 14%. The BENELUX countries had the highest sunshine increase (between +14 and +17%). The anomalous area extends as far as the Black Sea and the Caucasus (Azerbaijan, -40%; Georgia -37%)  to western Russian Oblasts.

Several additional locations deserve mentioning in the Horn of Africa (Somalia, Kenya, Uganda, all at -31%) and in southern Africa (Zimbabwe and Botswana, -32% and -69%, respectively).  In the south – the second group - the agricultural season is about to start and, as a result, direct negative impacts on crops are unlikely; not so in the northern countries, where JASO is normally part of the growing season.  However, the large diversity of climatic conditions brought about by the proximity of the equator and elevation make it difficult to make qualitative statements about crop impacts.

Dry conditions also prevailed over North Korea (-37%), extending south-west into China  (Henan province: -30%); over north-west America (Oregon, -47%; Washington -33%) and parts of Latin America, especially eastern Brazil  (e.g. Sergipe, at -61%) and some isolated spots in Argentina.

3.3 High rainfall

Large rainfall anomalies in excess of 50% or even 100% have occurred in 23 countries. Most of them are in semi-arid climate zones and in their crop growing seasons; as a result, rainfall mostly benefited crops and rangelands, especially in West Africa (Niger 621 mm, +50%) and in central Asia. Mongolia, Turkmenistan, and Uzbekistan had excesses close to 90% while the anomaly reached close to 120% in Kyrgyzstan and Tajikistan.

Unseasonally abundant rainfall was also recorded in many Mediterranean and in Southern African countries. In the first group, this includes Morocco (+60%), Algeria and Lebanon (+100%), Tunisia (+110%) and Cyprus (+118%). These countries grow winter crops and the season is about to start, definitely under favorable soil moisture conditions. The second group grows summer crops, and the season is about to start as well, also with favorable soil moisture beneficial to crops and rangelands alike. Countries to be mentioned include Eswatini (+65%), Madagascar (+66%), Mozambique (+74%) and Malawi (+84%).

Many middle-eastern countries can also be mentioned (e.g. Iran, +53%; Iraq, +103%) although irrigation plays a larger part than in the previously mentioned areas. Several countries are just mentioned hereafter because normal rainfall is so low that even a minor volume of precipitation, insufficient to sustain crops, results in a large anomaly when expressed in percent. This includes Libya, Oman, the United Arab Emirates (UAE) and Qatar. For instance, the precipitation anomaly in the UAE reaches 251% but corresponds to just 13mm of rainfall.

The average (unweighted) rainfall anomaly in the listed countries reaches 107%. However, BIOMSS improvement is just 69%. This is largely due to relatively cool conditions (-0.3°C). Sunshine, however, was mostly average, however with some negative departures (-4% in Mongolia and Algeria) and some positive ones in southern Africa (+4% in Madagascar and +6% in Eswatini).

The most relevant BIOMSS departures to mention are those of New Caledonia (-61%) and Dominica (-51%), both resulting from a drop in rainfall in the above-mentioned areas.  High values in excess of 50% all belong to the zones with high rainfall in the Mediterranean, central Asia and the middle-East.   

4. Temperature anomalies (Figure 3.3)

[Figure 3.3. Global map of July to October 2018 temperature (TEMP) by country and sub‐national areas, departure from 15YA (degrees C)]


Temperature anomalies were uncommon during the recent July through October period.

Low values include essentially Eswatini and Paraguay (both at -1.8°C) and Mauritania (-1.5°C). All are associated with higher than average rainfall and large sunshine anomalies in Eswatini (+6%) and Paraguay (-5%). Mauritania had average sunshine.

High temperatures occurred over much of western Eurasia. They reached heatwave proportions in (wet) Cyprus (+2.0°C) and two countries with close to average rainfall: Angola (+2.0°C) and Spain (+2.2°C). Extremely large values are reported for New Caledonia (+6.0°C) and Comoros islands (+8.8°C).   

5. Sunshine anomalies (Figure 3.4)

[Figure 3.4. Global map of July to October 2018 photosynthetically active radiation (RADPAR) by country and sub‐national areas, departure from 15YA (percentage)]

Low sunshine occurred in Latin America and in southern Asia, especially in Argentina (-8%) and Paraguay (-5%), both in their winter season and in Nepal (-7%) and India (-5%) where early stages of Kharif crops may have been affected.

Positive anomalies of 5% were widespread and affected almost one-third of the countries monitored, most of them in western Europe and other areas mentioned above and in chapter 1 as drought affected. Extreme RADPAR departures (10% and more) occurred in West Africa (Sierra Leone     and Côte d’Ivoire, +10%; Liberia +16%), Western Europe (France, +10; Germany, +11%; Luxembourg, +14%; Netherlands, +15% and Belgium +17%). Cuba recorded +11% and two central African countries were at 11%: South Sudan and the Central African Republic.

6. Combinations of anomalies

Only two groups of two neighboring countries appear to have experienced extreme conditions nationwide for RAIN, TEMP, and RADPAR. They are (1) Germany and the Netherlands with a deficit of RAIN close to 40%, high temperature (+1.3°C) and sunshine exceeding reference values by 11% and 15%, respectively; (2) Algeria and Tunisia with about double the average precipitation, cool weather (-0.9 and -1.3°C) and RADPAR down 4% and 3%, respectively.

Considering all the spatial units shown in figures 3.1 to 3.4 leads to exclude Algeria and Tunisia (i.e., the countries are no longer considered extreme compared with the new extremes) but retains Germany and the Netherlands. Three areas are added in north-west Argentina: the provinces of Jujuy, La Rioja and Salta with large excess precipitation, cool weather and reduced sunshine; the State of Sergipe in north-east Brazil (drought, high temperature and abundant sunshine), and Sikkim in India which experienced an unusual combination of dry and cool weather with abundant sunshine.

Table3.0. July - October 2018 agro-climatic and Agronomic indicators by country, currentvalue and departure from average.

 

Code

 

 

Agro-climatic indicators

Agronomic indicators

Country

Departure from 15YA

(2003-2017)

Departure from 5YA

(2013-2017)

Current

 

 

RAIN (%)

TEMP(°C)

PAR (%)

BIOMSS
(%)

CALF (%)

CI (%)

VCIx

AFG

Afghanistan

5

-1.1

0

57

-13

-1

0.26

AGO

Angola

-18

2.0

2

39

33

10

1.02

ARG

Argentina

-4

-0.7

-8

16

0

10

0.73

AUS

Australia

-30

0.1

3

-6

-2

-12

0.74

BGD

Bangladesh

-4

-0.3

1

-7

1

6

0.92

BLR

Belarus

16

0.8

5

-16

0

-4

0.92

BRA

Brazil

12

-0.4

0

26

1

-1

0.71

KHM

Cambodia

-8

-0.8

1

-4

-1

0

0.87

CAN

Canada

-3

-0.7

2

4

0

-3

0.90

CHN

China

4

-0.4

1

-3

0

-2

0.94

EGY

Egypt

-24

-0.1

0

60

1

-4

0.72

ETH

Ethiopia

-10

0.0

3

-24

1

4

0.93

FRA

France

-18

0.7

10

-13

0

-14

0.73

DEU

Germany

-40

1.3

11

-9

0

-4

0.70

HUN

Hungary

-1

0.9

4

-6

0

1

0.84

IND

India

2

-0.2

-5

-18

-3

-3

0.87

IDN

Indonesia

-11

0.0

4

-15

0

0

0.90

IRN

Iran

53

0.4

0

106

7

4

0.66

ITA

Italy

37

0.7

1

7

8

-6

0.90

KAZ

Kazakhstan

42

-0.4

0

13

5

-4

0.83

KEN

Kenya

-31

-0.6

4

-30

25

-4

1.09

MEX

Mexico

-2

-0.3

1

-5

2

-3

0.91

MNG

Mongolia

86

-0.2

-4

12

2

-3

0.93

MAR

Morocco

60

-0.8

-1

54

7

0

1.21

MOZ

Mozambique

74

-0.3

3

30

3

-2

0.89

MMR

Myanmar

3

-0.4

-1

-3

0

-3

0.93

NGA

Nigeria

19

-0.7

7

-5

1

16

0.92

PAK

Pakistan

-12

-0.6

1

2

-8

-6

0.57

PHL

Philippines

-11

0.7

3

-15

0

0

0.93

POL

Poland

0

1.0

8

-6

0

-1

0.79

ROU

Romania

-43

0.3

6

-20

0

-7

0.94

RUS

Russia

7

0.5

4

2

-2

2

0.86

ZAF

South Africa

-14

0.0

4

-3

13

3

0.69

LKA

Sri_Lanka

20

-0.5

-2

7

0

0

0.90

THA

Thailand

1

-0.3

3

-5

0

-1

0.91

TUR

Turkey

5

0.5

0

53

10

-5

0.83

UKR

Ukraine

-7

0.9

5

-4

-3

-4

0.83

GBR

United Kingdom

8

0.4

3

4

0

-1

0.81

USA

United States

26

-0.2

-2

10

2

0

0.89

UZB

Uzbekistan

93

-0.5

1

107

-4

1

0.75

VNM

Vietnam

-1

-0.2

0

-5

0

0

0.93

ZMB

Zambia

4

-0.3

-2

43

35

2

0.87