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: the crop is about to be planted in the southern hemisphere and was harvested in the northern hemisphere. In tropical countries (India), the reporting period corresponds mid-season summer (kharif) maize and early season winter (rabi) crops. Among the 14 countries that export more than 1 million tonnes of maize, only five had positive rainfall anomalies which did not reach 10% in France, Canada and Russia. In the United states, the excess precipitation was more significant (+24%). Among the listed countries, only Russia had a significant biomass production potential (BIOMSS) drop of  8%, which close to average values elsewhere. For more detailed information about maize growing areas in Russia, refer to spring wheat areas below, as they largely coincide.

All other exporters had below average precipitation, which was moderate only in Brazil (-5%) but exceeded 20% elsewhere, including Argentina (-20%) and Paraguay (-44%). Argentina recorded a notable BIOMSS drop of 10% and a poor maximum vegetation condition index (VCIx) of 0.44.

In central-eastern Europe, where temperatures and sunshine were relatively high compared to their averages, precipitation deficits range between 21% (Serbia, Ukraine)  and -35% in Romania, with intermediate values in Hungary and Bulgaria. Agronomic indicators are usually average or close to average, except in Ukraine where the cropped arable land fraction (CALF) drops 4% and VCIx is moderate (0.8)

In India, precipitation excess was huge (40%) but all agronomic indicators remain fair. The rainfall deficit in South-Africa (-52%) regards the very beginning of the maize campaign which, however, will require additional soil moisture soon to compensate for the unfavorable start. BIOMSS and CALF are down (8% and 7%, respectively) and VCIx (0.66) is the second lowest of the group of exporters.

Rice: India and Pakistan, the first and fourth rice exporters had above average precipitation by 40% and 98%, respectively, with moderately below average temperature and sunshine, except for sunshine in India which was down 7%.  Agronomic indicators give contrasting signals, although CALF is up in  both countries (+3% and +14%, respectively).  The second and third exporters, Thailand and Vietnam, recorded  a precipitation deficit  of 17% and 5%, respectively, with slightly above average temperature but more significant rises in sunshine (7% and 6%). All agronomic indicators are fair to good.

In the United states, the main rice producing states (Arkansas, California, Louisiana, Missouri, Texas, Mississippi) had generally above-average precipitation (+11% to +57%), except in California (-67%, 25 mm instead of 61 mm). Other conditions varied between States, which all recorded positive BIOMSS departures in the range from 2% (Missouri) to 7% (Texas), with the exception of California (-4%).

Wheat: Twenty countries in both hemispheres export more than 1 million tonnes of wheat. The top five exporters market more than 10 million tonnes internationally, including the USA, Canada, Russia, France and Australia. During the JASO reporting period, all of them were in at least one of their wheat season, e.g. winter and spring wheat were harvested in the northern hemisphere while harvest has started in Argentina and parts of Australia (Queensland, with other areas about to start). In the southern hemisphere, summer crop season is about to start. As such, current JASO rainfall and other weather variables were relevant for wheat crops everywhere.

Countrywide, the top four wheat exporters (United States, Canada, Russia and France) recorded positive rainfall a anomalies in the range from 3% (France) to 24% (USA). CALF values slightly increased in the United States 9 (+3%) but otherwise agronomic indicators were average (CALF) or favorable (VCIx close to 0.9). Russia and France deserve mentioning for their contrasting values of sunshine (RADPAR down 2% and up 4%, respectively) and BIOMSS (-8% and +8%).

In Russia, the main spring wheat production areas stretch from the Volga region (Baskyria and Orenburg Oblast) to western Siberia (Altai Oblast), along the Kazakh border, while winter wheat concentrates in the Caucasus and north of it. Most winter wheat was planted and has reached or is about to reach dormancy.  Spring wheat areas had generally above-average rainfall  (+9% on average)  with favorable sunshine (+3%) and BIOMSS exceeding average  by 3% as well. Only the Oblast of Chelyanbinsk and the Republic of  Bashkortostan had below average BIOMSS (6% and 24%, respectively), which are directly related to low temperature and low sunshine combined with above average precipitation (+25% and +40%).

Winter wheat areas, which are now past planting, in contrast, had somewhat below average rainfall (nine administrative units out of twelve, 9/12) with generally below average temperature (11/12), close to average sunshine and a marked drop in BIOMSS (-10% in 11 out of twelve units).  The largest BIOMSS drops occurred in he Oblasts of Voronezh (-15%), Penza (-19%), Ulyanovsk and Samarsky (both at -20%).  All the areas had close to average rainfall but cool weather with departures close to or larger than -1.0°C. The most favorable conditions where those in the Kray of Krasnodar.

Large rainfall deficits affected Australia (-38%), Romania and neighboring Hungary and Bulgaria (-35%, -26% and -24%, respectively) , and Argentina (-20%).  In Australia, CALF dropped 15% and VCIx reaches just 0.29,  by far the lowest value among all wheat exporters. In spite of its precipitation deficit, Hungary has the largest positive BIOMSS departure among the top 20 wheat exporters, with favorable CALF and VICx. Just positive departures occurred in the United Kingdom (+17%), Mexico (+16%) and India (+40%). Ukraine, the 6th largest exporter of wheat, and Kazakhstan (9th exporter) still need to be mentioned. Ukraine had a 21% deficit in rainfall which coincided with late maturity and harvest of wheat; the increased sunshine (+6%) has benefited the crop, resulting in average condition. However, the shortage of moisture may negatively impact early stages of the 2020 winter wheat crop. In Kazakhstan, environmental conditions were average, resulting in a +5% change in  BIOMSS. However, CALF fell 8% with VCIx at 0.76, a fair value.

Soybean: Among the eight countries that export more than one million tonnes of soybean only seven need to be considered as the Netherlands is a re-exporter of soybean products. Most countries have already been mentioned above for other summer crops (USA, N. 1 exporter; Argentina, N. 2; Canada N. 4 and Ukraine, N. 7).  In addition to the USA and Canada, Uruguay had above average precipitation (+34%) in the presence of cool weather and a 3% drop in sunshine, resulting in a significant drop in BIOMSS (16%) and low VCIx, indicating a likely delay in soybean planting. The situation is very similar to the one observed in Argentina where the main soybean provinces (Cordoba and Buenos Aires) both experienced low precipitation (-23% and -35%, respectively) and temperature, but nevertheless close to average BIOMSS at the beginning of the planting season. .

In Paraguay, rainfall was rather low (-44%) but BIOMSS and VCIx show more favorable values than in Uruguay. Brazil, with a slight rainfall deficit (-5%) has agronomic and BIOMSS indicator values rather similar those in Paraguay. The  main soybean growing States (Mato Grosso, Parana and Rio Grande do Sul) experienced contrasting conditions with an 8% increase in BIOMSS in Parana in spite of low rainfall (-34%) but in the presence of favorable temperature and sunshine. Arguably, Parana and Mato Grosso do Sul had the most favorable soybean conditions so far.

3. Weather anomalies and biomass production potential changes

3.1 Rainfall (Figure 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 Iraq, for instance, the JASO rainfall deficit reaches 68%, i.e. 8 mm were recorded over the period instead of 25 mm, which is about 0.3 mm per day on average (assuming 120 days for the JASO period). Clearly, when average amounts are very low, large negative departures are meaningless. In Iraqi Kurdistan, near the Turkish and Iranian borders, JAS rainfall is 0 with rainfall picking up only in October (21 mm). Large positive departures are, however, often more relevant, as they may indicate an early start of the season (e.g. before October in Iraqi Kurdistan), or 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 Indonesia during the current reporting period, which corresponds to the beginning of the rainy season in Java, the main agricultural area in Indonesia: average rainfall reaches 1024 mm, so that the amount recorded (728 mm)  is 29% below average. 728 mm, however, corresponds to about 6.1 mm per day, which is sufficient to cover the requirements even of water demanding crops over a period when potential evaporation reaches about 500 mm, 4.2 mm/day. In fact, the biomass production potential is up 2%, because the available water was still sufficient to satisfy crop water demand boosted by RADPAR, which is up 8%. In fact, the deficit in Indonesia probably corresponds to a slightly delayed beginning of the rather long monsoon season (6 months) and does not rise any concern.    

Figure 3.1. National and subnational rainfall anomaly (as indicated by the RAIN indicator) of July to October 2019 total relative to the 2004-2018 average (15YA), in percent.

Dry conditions

The current narrative includes only the countries where average rainfall over the JASO period exceeds 90 mm, a limit chosen to include Mediterranean and southern African countries where the cropping season is just starting.

A large number of countries (more than 30) had precipitation deficits larger than 20%, on all continents.     

The largest group includes central European and Mediterranean to Black Sea countries which are all at the beginning of their winter crop season. The area extends north-east as far as the Moscow Oblast and east across Kazakhstan up to the Altay Republic and the Kray of Krasnoyarsk in Siberia.   With some exceptions (Altay Republic, -31%) the easternmost locations usually experienced somewhat less severe water shortages than the western areas. A large block of countries recorded a deficit of 33% (Portugal, Slovakia, Republic of North Macedonia, Moldova, Montenegro, Greece and Romania). Slightly less severe shortages between 25% and 30% occurred in Turkey, Morocco,

Georgia and Hungary; Bulgaria, Albania, Ukraine, Serbia    and Armenia    has a deficit between 20% and 25%. For the time being, none of the listed countries should have experience crop stresses beyond slightly late planting, except possibly Portugal where CALF at 54% is 18% below average. Most of them show increased BIOMSS due to favorable sunshine.

Deficits between 29% and 33% affect south-east Asia and Oceania, including Indonesia, Timor Leste, New Caledonia and Australia.  Australia is the only country in the group with a drop in CALF and poor VCIx.

In Asia, next to Bhutan (-26%), several Provinces need to be mentioned for China: Anhui -52%, Hubei -48%, Jiangsu -47%, Henan -36% and Ningxia -24%.

Deficits of the same magnitude occur in central and southern America, in Paraguay (-33%), Honduras (-29%), Chile (-26%) and Belize (-24%), as well as several Brazilian States (Mato Grosso Do Sul -48%, Sao Paulo -36%, Parana -34% and Santa Caterina -27%)  and Argentinian Provinces (San Luis and La Pampa, -61%, San Juan -46%, Misiones -36% and Buenos Aires -34%).

In southern Africa, the onset of the main maize season is delayed     as shown by low CALF values, especially in Southern Africa (RAIN down 52%). Other deficit countries include Lesotho (-86%), Eswatini (-24%) and others. Isolated countries with poor rainfall include Burundi (-33%), Mauritius (-24%) and Gambia (-21%)

Wet conditions

In addition to cool and wet northern America, moist conditions need mostly to be reported for the tropical northern hemisphere affected by intense late-monsoon conditions in Pakistan (+98%), Sri Lanka (+48%) and India (+42%) where the following States all recorded precipitation excesses between 50% and 120% (Tamil Nadu, Kerala, Maharashtra, Madhya Pradesh, Andhra Pradesh, Gujarat and Rajasthan).

As mentioned in the section on disasters (5.2), some of the excesses in Asia were related with Indian Ocean cyclone activity, which also affected the Horn of Africa, bringing above average precipitation to Somalia (+42%) and Kenya (+52%) in semi-arid locations where even minor excesses can create havoc.  In the Sahel, Mali (+63%) and Mauritania (+44%), positive rainfall anomalies have benefited crops and range-lands during mid and late season stages. Contrary to its eastern and southern neighbors, Angola (+62%) had favorable precipitation benefiting crops and livestock at the beginning of the season.

3.2 Temperature anomalies (Figure 3.2)

Figure 3.2. National and subnational temperatute rainfall anomaly (as indicated by the RAIN indicator) of July to October 2019 average relative to the 2004-2018 average (15YA), in °C.

For the current reporting period, there is no global spatial coherence between RAIN and TEMP anomaly patterns (r²=0.017, n=167). Continental data, however, show some coherence such as high rainfall and low temperature in north America, Baltic States and north-western Russia.  The observation results from the visual examination of Figures 3.1 and 3.2 rather than from a statistical analysis.

Lowest nationwide temperature anomalies occurred in unrelated locations in Finland (-1.3°C), Timor Leste (-1.0°C) and in Uruguay (-1.0°C), as well as a group of  neighboring central African countries: Sudan -1.2°C, South Sudan (-1.1°C) and Chad (-1.0°C). At the first sub-national level, however, 169 out of 2766 administrative units (6%) underwent negative temperature anomalies of 1.0°C or larger.  In the United States, they include South Dakota (-2.8°C compared with average), Montana (-2.5°C), North Dakota and Idaho, both at -2.0°C. Departures in the range from -1.7°C to -1.2°C include Wyoming, Nebraska, Oregon, Washington, Nevada, Minnesota and Utah. In Russia, the lowest temperatures occur in areas neighboring the Baltic, especially in the Oblasts of Arkhangelsk -2.3°C, Kostroma -2.2°C, Vologda -2.1°C and the Komi Republic (-2.0), as well as in  about 30 places in the agriculturally important areas mentioned above under wheat. The least severe departures (up to -1.0°C) occur, as mentioned, in the winter wheat areas.

Sub-national data also confirm the cool conditions in the Sudan, South-Sudan and Chad areas and encompass the area which reaches from Yemen to north-eastern Nigeria and includes 3 Governorates  in Yemen (e.g. Raymah -1.6°C), 3 Regions Eritrea (e.g. Anseba -1.7°C),  4 districts in Kenya (e.g. Kakamega  -1.5°C), 9 Districts in Uganda (e.g. Kapchorwa -2.9°C and Sironko -1.7°C), 12 States in the Sudan (e.g. Al Jazirah -1.4°C, Sennar -1.6°C), 5 States in South Sudan (e.g. Jungoli -1.5°C), 8 Regions in Chad (e.g. Batha    -1.4°C) and 2 States in  Nigeria (e.g. Gombe, -1.1). Most listed areas also recorded low sunshine.

The largest positive departures were just three at the national level: France with 1.0°C above average, Switzerland with 1.1°C and Kuwait at 1.4°C. 140 spatial units of at the first sub-national level had temperatures that were warmer than average by more than 1.0°C. The largest departures were recorded in Switzerland (Cantons of Lucerne    +2.3°C and Obwalden +2.8°C), Bhutan (Dzong of Punakha +2.7°C) and the United States (    Hawaii, +3.3°C).

3.3 RADPAR anomalies  (Figure 3.3)

Figure 3.3. National and subnational sunshine anomaly (as indicated by the RADPAR indicator) of July to October 2019 total relative to the 2004-2018 average (15YA), in percent.

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) reaches -0.198; it is stronger than the link between temperature and rainfall.

 Significantly below average nationwide sunshine occurred essentially in southern Asia, in India (-7%), Sri Lanka (-5%) and  (Nepal -4%) . At the first administrative level, low values were also recorded in the Baltic countries (Lapland -7%) and  north-western part of European Russia (Oblasts of Perm -24%, Kostroma -20% and Kirov -20% and the Komi-Permyak Okrug -24%), north-western North America (e.g. Alberta Province -7%, Minnesota, N. and S. Dakota -8%) and Eastern Asia (e.g the Chinese provinces of Xizang and Sichuan, both at -6%; Khabarovsk Kray at -4%)  

The largest positive sunshine anomalies at the national scale occurred in Central America and the Caribbean, and are directly related to the “drought corridor” (refer to section 5.2 on Disasters) which forced many people to out-migrate because they had lost their livelihoods: Guatemala +9%, Haiti and Costa Rica +10%, Honduras +12%, Panama +9%, Belize and El Salvador +7%).

Other high sunshine areas include parts of central-eastern Europe (+7% in Serbia, Bulgaria, Norway) and south-eastern Asia: Laos +9%, Malaysia and Indonesia +8%, Thailand and Timor Leste +7%, Vietnam +6%.  

3.4 Biomass accumulation potential BIOMSS (Figure 3.4) and agro-climatic indices

Figure 3.4. National and subnational bionass production potential anomaly (as indicated by the BIOMSS indicator) of July to October 2019 total relative to the 2004-2018 average (15YA), in percent.

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.  As a result, global correlations between the two groups of variables are difficult to interpret, especially because of recent global climate trends.

About ten countries underwent a drop in their biomass production potential larger than 10%. At the high end, they include several countries with significant rainfall deficit in the presence of otherwise average conditions: Syria -30%, Egypt -25%, Jordan -19% and Israel -15%. Most of them practice irrigation and their CALF values were low with generally good VCIx values.   Unfavorable BIOMSS departures with low VCIx occur simultaneously in Argentina (-10%, VCIx 0.44) and Uruguay (-16%, 0.37); both were already mentioned at the beginning of this chapter under the headings of major exporters. In Ethiopia (-13%), the main factor behind the BIOMSS reduction may be a relatively minor drop in temperature of 0.3°C.

BIOMSS departures from average exceeding 10% occurred in ten countries, including three  “climatically Sahelian” ones as the result of above normal precipitation during the middle and final parts of the cropping season, which usually peaks in July or August: Niger +11%, Eritrea +12% and Mauritania +13%. VCIx values are exceptional in Eritrea, but this is most probably the result of the tail of cyclone Kyarr (see section 5.2 on Disasters) which caused a temporary – but nevertheless beneficial – greening of vegetation. In Europe and north Africa, increases resulted from various combinations of factors including improved water supply and favorable sunshine or temperature. The BIOMSS increases reached 11% in Hungary, 12% in Spain and in Croatia, 17% in Albania and 22% in Tunisia .  The largest BIOMSS increases occurred in Yemen (+27%) and Pakistan (+29%) where RAIN was above average, TEMP was average and RADPAR just below average.  Both had significant increases in CALF (+46% and +14%, respectively) and their VCIx are comparable with the best historical values.

3.6 Combinations of extremes

Several countries were characterized by unusual combinations of factors (climatic, agronomic or both) and deserve closer monitoring over coming reporting periods.  In Portugal and South Africa, both agro-climatic and  agronomic indicators show very unfavorable values. The countries with unfavorable CALF and VCIx, but generally acceptable climatic variables include several southern African countries (Botswana, Eswatini, Namibia and Zambia) and Spain. Although the listed countries belong to rather different agro-ecological settings, they are similar in that their main agricultural season is just starting; they can recover if precipitation improves.   

Uruguay and Argentina also share some issues, including low temperature and low agronomic indices. They are at the beginning of their summer crop season and can recover.

Other potential problem countries include Afghanistan (low sunshine and poor VCIx), Montenegro and Romania (low precipitation with mixed CALF/VCIx).