1. Overview

The global agro-climatic patterns that emerge at the MRU level (Chapter 1) are reflected with greater spatial detail at the national and sub-national 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 5.2) although extreme events tend to be limited spatially, so that the statistical abnormality is not necessarily reflected in the climate statistics that include larger areas. No attempts are normally made, in this chapter, to identify global patterns that were already covered in Chapter 1. The focus is on 166 individual countries and sometimes their subdivisions for the largest ones. Some of them are relatively minor agricultural producers at the global scale, but their national production is nevertheless crucial for their population, and conditions may be more extreme than among the large producers.

2. Overview of weather conditions in major agricultural exporting countries

The current section provides a short overview of prevailing conditions among the major exporters of maize, rice, wheat and soybeans, conventionally taken as the countries that export at least one million tonnes of the covered commodities. Just 20 countries include the top 10 exporters with the United States and Argentina exporting all four crops and Brazil, Ukraine and Russia exporting three of them each!

Maize: Among the 14 countries that export more than 1 million tonnes of maize, four recorded precipitation exceeding average by 20% or more. They include the USA (+29%), Hungary (+35%) and Serbia (+34%) in the northern hemisphere, where the reporting period covers most of the main maize growing season, and where the harvest is about to start.  Although weather was cool and wet in the USA, the biomass production potential dropped just 1%, with the Cropped Arable Land Fraction indicator (CALF) up 3% and the maximum Vegetation Condition Index VCIx indicator showing values associated with favorable crop condition (0.93). The largest positive increases in the BIOMSS index occur in Ukraine (+6%), India (+7%) and France (+9%) in spite of relatively dry conditions in some of them (e.g. France). In India VCIx is moderate (0.83) with a low CALF (55%) resulting from a 5% drop compared with previous years. 

In the southern hemisphere, Argentina (20% excess precipitation) harvested maize during the first half of the AMJJ period. In the province of Cordoba, the major maize producing area, the excess was just 6%. VCIx indicates below average conditions and the BIOMSS potential indicator is down due to poor sunshine (-9%). In Brazil and Paraguay all indicators show favorable environmental and agronomic conditions.  In South-Africa, where the main maize crop was harvested during the reporting period, cropland increased (CALF up 5%)  but VCIx is just fair and BIOMSS potential fell 10% due to drought (RAIN down 30%).

Rice: The top 3 rice exporters in Asia (India, Thailand and Vietnam) experienced very similar weather conditions at the national scale: mostly dry and warm, reaching heatwave proportions in some areas (India). The RAIN deficit varies from -13% to -23% and TEMP is up 0.4°C to 0.7°C. Mostly driven by favorable sunshine, the biomass production potential is up 8%. CALF is down 8% in India and in Pakistan, where prevailing weather conditions were wet and (+53%) and cool (0.7 °C below average). In the USA, the 5th exporter, conditions were roughly average for rice.

Wheat: Twenty countries in both hemispheres export more than 1 million tonnes of wheat. The top five exporters each market more than 10 million tonnes internationally, including the USA, Canada, Russia, France and Australia. 13 out of twenty exporters had below average rainfall. Few countries had large precipitation excesses, the main exception being the USA where the reporting period witnessed most of the nationwide winter wheat harvest, which mostly ends in July in the northern States. As such, the indicators are very relevant for wheat. The countries with the largest positive BIOMSS departures from average are all located in north-eastern Europe (Latvia and Poland, +11%; Lithuania +16%). All also experienced positive sunshine departures  (5% to 10%), full cropping (CALF at 100%) and favorable VCIx.

In Australia, the JFMA period covers the end of the 2018-19 harvest (up to January) and the early stages of the 2019-20 crop (from April). Very dry conditions have affected the period (RAIN down 17% below average) with a marked drop in CALF (-38%) and unfavorable VCIx (0.42), the lowest value by far among the 20 top exporters. The 2018-19 crop is unlikely to have been satisfactory,  but the impact on the ongoing wheat season is still open.

As already mentioned under maize, Argentina had a marked biomass production potential drop of 9%. Considering, however, that wheat was in early vegetative stages in June and July, the crop is unlikely to have been seriously affected.

Soybean: the soybean harvest extends to the first half of the reporting period and somewhat beyond in south America, and is still to take place in the northern hemisphere. Among the eight countries that export more than one million tonnes of soybean only seven need to be considered as the Netherlands is a Soybean product re-exporter. Above average biomass production potential occurred in Brazil and Ukraine (+4% and +6%). Some damage to soybean due to poor sunshine may have occurred in Argentina (-9%) and in Uruguay (-6%) as both countries also show drops in BIOMSS and extremely low VCIx of 0.45 and 0.39, respectively. The situations seems to be significantly better in Paraguay.

3. Weather anomalies and biomass production potential changes

3.1 A Caveat

Figure 3.1 sometimes shows “very dry” and “very wet” conditions in areas that are currently transitioning from dry season to wet season (e.g. the west African Sahel) or from wet season to dry season  (e.g. the Brazilian Nordeste). Such locations typically have low precipitation values which do not allow to compute meaningful percentages.  In Botswana, for instance, the rainfall deficit reaches 67%, i.e. 11 mm were recorded over the AMJJ period instead of 34 mm, which is about 0.3 mm per day on average (assuming 120 days for the AMJJ period). Clearly, when average amounts are very low, large negative departures are meaningless. Large positive departures are sometimes more relevant, tough, as they may indicate an early start of the season, or late floods. The text below refers only to areas where significant amounts of rainfall are actually expected.

It is also stressed that in many equatorial areas where large amounts of rainfall are actually expected, below average rainfall not necessarily constitutes drought. An example is Myanmar during the current reporting period: average rainfall reaches 1331 mm, so that the amount recorded (1020 mm)  is 23% below average. 1020 mm, however, corresponds to about 8.5 mm per day, which is sufficient to cover the requirements even of water demanding crops. In fact, the biomass production potential is up 2%, because the available water was still sufficient to satisfy crop water demand expressed by RADPAR, which is up 7%. In fact, the deficit in Myanmar probably corresponds to a slightly delayed beginning of the rather long monsoon season (6 months) and does not rise any concern.

3.2 Rainfall

Figure 3.1. Global map of rainfall anomaly (as indicated by the RAIN indicator) by country and sub-national areas, departure from 15YA between April and July 2019

Dry conditions

Among the countries that did expect significant amounts of rainfall during the reporting period (amounts larger than 100 mm over AMJJ),  several areas suffered marked deficits in excess of 25% with the largest national values occurring in the Gambia and in New Caledonia, with deficits reaching 63% in both areas.

Close to Gambia, several other west-Africa countries deserve mentioning because they suffered deficits between 27 and 40% at the time when the rainy season is starting, indicating a delay in the season. Close to Gambia in the western tip of the Sahel, this applies to Senegal and Guinea Bissau. It also applies to Benin and Togo where the north has a Sahelian-type climate, i.e. semi-arid with the rainy season starting around May.

Although technically New Caledonia is not part of Oceania, it shared rather dry conditions with two of its Oceanian neighbors during the current reporting period: New Zealand experienced a 32% precipitation deficit and the nationwide value for Australia reaches 29%.  Values for Queensland were close to the national average but the northern Territory and New South Wales had deficits just under 50%. The island of Timor Leste (-39%) in maritime South-East Asia can be assigned to the same group of countries.

In Asia, drought affected the Korean DPR (-52%), which has repeatedly suffered from water shortage over the recent years. Adjacent areas in China suffered as well, including Anhui (-39%), Henan (-43%), Jiangsu (-53%), Liaoning (-47%) and Hubei (-52%).

In Europe,  northern and Baltic countries are the most concerned (Estonia     -39% with the following countries in the range from -25% to -29%: Lithuania, Latvia, Sweden, Denmark and the Netherlands). The water deficit area extends west and south to France (-11% nationwide, but drier in isolated regions, such as Normandie at -33%) and east into Russia, with several regions in the range from 30% to 40%, including the Republics of Chuvashia and Mari El and the Oblasts of Kemerovo, Orenburg, Tambov and Ulyanov.

In Latin America, the driest areas are concentrated in the Caribbean and Central America and include the Dominican Republic (-49%), Belize (-42%), Dominica (-36%), Honduras (-30%) and Panama (-26%). The drought combined with the Venezuelan crisis are one of the root causes of the displaced persons in the region (refer to Chapter 5.2)

Wet conditions

Wet conditions need to be reported most from the large polygon including Serbia (+34%) and Bosnia-Herzegovina (+35%), the Middle-East including Syria (+99%, from 103 mm instead of the average of 52 mm), Pakistan (+53%) and Kazakhstan, especially the region of Jambyl (+53%) and Yujno kazachstanskaya (+98%). The largest rainfall anomalies occur in this bloc of countries with Afghanistan (+67%), Tajikistan (+72%) and Uzbekistan (+195%, with 208 mm recorded when the average is 101 mm).

The second “wet bloc” covers essentially the United States where the largest excesses pertain to Wyoming  +41%, Louisiana +42%, California +45%, Missouri +45%, Illinois +46%, Oklahoma +48%, Kansas +50%, Nevada +52%, Arkansas +53%, Mississippi +54%, Utah +59%, Nebraska +66% and North Dakota +89%

The third, smaller, wet bloc stretches from Bolivia (+34%) to the Argentinian provinces of Entre Rios (+31%) and Santa Fe (+41%) also including the Chaco (+51%) and Santiago (+60%).

3.3 Temperature anomalies 

There is relatively little spatial coherence between RAIN and TEMP anomaly patters, wit the exceptions of low temperature in north American high rainfall areas and minor rainfall deficits associated with a positive temperature anomaly in southern and south-east Asia. The observation results from the visual examination of Figures 3.1 and 3.2 rather than from a statistical analysis (at the national scale, the correlation between rainfall and temperature anomalies reaches -0.27)

Figure 3.2. Global map of temperature anomaly (as indicated by the TEMP indicator) by country and sub-national areas, departure from 15YA between April and July 2019

Low temperature

Negative temperature anomalies are usually rather moderate at the national and sub-national level and do not reach -1.0°C, with three exceptions: (1) Pavlodar region in Kazkhstan, which is surrounded by less intense anomalies extending in a northeastern direction up to Baltic countries; (2) Indian Kashmir, extending south and west to include Uzbekistan, Pakistan and Afghanistan with smaller departures and (3) four States in the USA: S Dakota (-2.3°C), Nebraska (-2.1°C), Kansas  (-1.7°C) and Oklahoma (-1.6°C).

High temperature

At the national level, positive anomalies are of the same order of magnitude as negative anomalies, and do not exceed 1.0 °C (one occurrence, in Namibia). Considering the whole set of administrative units for which CropWatch computes TEMP departures, only two exceed an anomaly of 2.0°C: the Canton of Obwalden in Central Switzerland and the Dzong of Punakha in Bhutan (+2.2°C and +2.3, respectively). Other areas with very localized temperatures anomalies exceeding +1.5°C occur in Burundi,  Bhutan, near and in central America (Colombia, Dominican Republic, Ecuador, Honduras), south and south-east Asia (Sri Lanka, Myanmar, Thailand and Vietnam) and in the USA (Alaska).

3.4 RADPAR anomalies

RADPAR anomaly patterns are rather close to rainfall patterns (compare Figure 3.1 with Figure 3.3), and the correlation between sunshine departures and rainfall departures (at the national level: -0.44) is stronger than the link between temperature and rainfall.

Figure 3.3. Global map of photosynthetically active radiation anomaly (as indicated by the RADPAR indicator) by country and sub-national areas, departure from 15YA between April and July 2019

Below average sunshine

Negative sunshine departures were generally moderate, with absolute values larger than 5% occurring only in Uruguay (-6%) and in Argentina (-9%). This is just two countries and both are major agricultural exporters; they will be mentioned again below in the section on BIOMSS.

Above average sunshine

33 countries experienced above average sunshine departures of +5% and above. They are located in: (1) Europe and central Asia, with the highest values in Belgium and Lithuania (+10%) and extending as far as Korea DPR; (2) South and South-East Asia including Malaysia, Brunei Darussalaam, Myanmar, Cambodia and Vietnam, with the largest departure in Thailand (+8%); (3) New Zealand (+7%); (4) several patches in Africa: Congo democratic republic and the Congo, Botswana and the highest values (+6%) in Somalia and Zimbabwe; (5) central America, the Caribbean and northern South America: Suriname, French Guiana, Guyana, Panama, Cuba, Haiti and the largest departures (+7%) in Honduras and Belize and in Guatemala (+8%).

3.5 Biomass accumulation potential BIOMSS

The biomass accumulation potential indicator (BIOMSS) largely synthesizes the combined effect of the three previous indicators. It will be discussed below and compared to the agronomic indicators for the spatial units for which they are available. Remember, however, that RAIN, TEMP, RADPAR and BIOMSS are compared against their 2004-2018 average, while CALF departures result from the comparison with 2014-2018.

Regional groups of similar behavior are easily identified in Figure 3.4. They overlap with those described in Chapter 1 (Figure 1.5) and will not be repeated here. Instead, the focus will be on individual national and sub-national units for the largest countries. Additional and separate information by major agro-ecological zones (AEZ) is given later in this chapter for individual countries.

Figure 3.4. Global map of biomass production potential anomaly (as indicated by the BIOMSS indicator) by country and sub-national areas, departure from 15YA between April and July 2019

At the national level, four out of the five largest BIOMSS drop occurred in Africa, starting with Gambia (-17%), Morocco (-13%), Guinea Bissau (-13%) and South Africa (-10%).  All experienced below average precipitation and slightly above average sunshine. All also had low VCIx, which confirm the  negative impact of the weather conditions. In Lebanon, the fifth country, BIOMSS was 12% below average. Both Morocco and Lebanon were at the end of the winter cropping season. While in  Morocco the BIOMSS behavior can be assigned to low rainfall, it is cool weather and reduced sunshine that account for the situation of Lebanon.

Countries where BIOMSS decreases below average range from -7% to -5% include Tajikistan, Sao Tome and Principe,  Kyrgyzstan, Bhutan, Lesotho and Argentina. With the exception of Argentina, their VCIx exceeds nevertheless 0.9, a favorable value, and most of them increased their CALF values, sometimes significantly as Tajikistan (+10%) and Lesotho (+18%). The low VCIx in Argentina was already mentioned above. In fact, the country experienced spatially very diverse conditions which are not easy to interpret as AMJJ covers the harvest of summer crops (mostly maize and soybean during AM) and the planting of winter wheat and barley (during JJ). The main agricultural provinces include Buenos Aires recorded the following BIOMSS departures: +5% in Buenos Aires, the main wheat growing area; average values (+0%) in Cordoba (main producer of maize) and -13%, mostly due to low sunshine and excess precipitation in Santa Fe, which produces about one fifth of the national output of maize and soybeans.

As exemplified above with Argentina, low and high BIOMSS departure values do occur in countries which are doing relatively well on average.  This includes the USA and Russia where the national BIOMSS is down 1% in both countries. Particularly in the USA, this includes some major agricultural states ranging from South Dakota (-17%) to Iowa, Nebraska, Montana and Wyoming (-10%). Biomass losses between 5% and 10% occurred in Colorado (-5%), Kansas, Indiana, Wisconsin, North Dakota, Illinois, Michigan and Minnesota (-10%). As already mentioned, all the listed States are characterized by high rainfall, low sunshine and cool weather.

The situation is more mixed in Russia, where negative BIOMSS anomalies in excess of 5% occurs in 18 areas (out of a total of 96 sub-national units) where precipitation covers the whole spectrum from below average (Republic of Mariy El,  -37%; Oblasts of Kirov and Vologda, -29%), average (Oblast of Perm, +2%) to well above average ( Komi-Permyak Okrug, +28%). In all areas the temperature was low, and so was sunshine (except in the Altai Krai, the Oblast of Novosibirsk and the Republic of Tatarstan, where it was average or slightly above).

While 12 countries, all mentioned above, recorded low BIOMSS compared with average at the national level,  positive departures exceeding +5% occur in 55 countries out of 166.  As shown in Figure  3.4,  high values predominate in South America, AFRICA, Europe, the Middle-East , Southern AND SOUTH-East Asia, as already shown in Chapter 1. The  largest  BIOMSS departures in excess of +10% above average were brought about by several factors:

    • favorable precipitation (Mali, RAIN +33%, BIOMSS +11%; Madagascar +15% and +12%; Iran +63% and +12%; and Pakistan +53% and +18%, the largest national BIOMSS increase for the AMJJ period);

    • favorable sunshine and average temperature, even in the presence of a precipitation deficit in Guatemala (BIOMSS +10%),   Latvia, Poland and Luxembourg (all +11%), Belgium +13%  and Lithuania +16%. In Asia, the only country with a BIOMSS increase above 10% was Laos (+11%).

All countries enjoy VCIx values above 0.9 with the exceptions of Mali (0.69) and Pakistan (0.79). In Mali, the rainy season starts in May (south) or June (north), while Pakistan practices typical northern hemisphere winter and summer crops, most of them irrigated; in Mali, on the other hand, irrigation is limited and confined to the Niger valley, especially the “Inner Delta” region. In both countries, CALF was low (54% and 35%, respectively) and dropped compared to the recent past (-16% and -8%, respectively). Refer to chapter 5.2 (disasters) for likely explanations about the results above.

Very favorable BIOMSS increases (>+10%) at the sub-national are often more relevant for range-land and pastures than for crops, according to local conditions. This applies, for instance, to three provinces in Argentina: Chubut with BIOMSS up 12%, La Pampa +15% and San Luis    +15% as well. In Brazil, high values occur in Rio de Janeiro (+11%), Acre (+11%), Sergipe (+12%) and  Alagoas (+14%) in the presence of low rainfall and high sunshine in mostly Amazonian areas where sunshine of limiting.  In Canada, the largest increases occur at high latitudes in areas of very limited relevance for cropping and livestock.   In India, 8 States had large BIOMSS rises: from Orissa (+11%) through Punjab, Haryana, Rajasthan, Uttar Pradesh, Bihar and Jharkhand (+19%) to Delhi (+22%). The increase was brought about through a variety of mechanisms. In Kazakhstan, a large precipitation excess in the oil-rich Atyrau region led to a BIOMSS increase of 11%.

In Russia, the most favorable BIOMSS situations occur in the Baltic region (Kaliningrad Oblast, +16%, adjacent to the already mentioned Poland and Latvia) and the Caucasus (Republics of Chechnya +11%,  Ingushetiya +13% and Kabardino-Balkaria +14%).

In the United States, only Alaska (+24%) and Arizona (+24%) need mentioning. Rainfall was about average in Arizona and the BIOMSS increase is probably explained by lower than average sunshine and temperature, which have reduced crop water demand.