3.1 Overview

Table 3.1 presents the agroclimatic and agronomic indicators for the period from October 2017-January 2018, showing their departure from the five and fifteen-year averages as applicable. Figures 3.2 through 3.5 show the underlying CWAI indicators. While chapter 1 focuses on global climate patterns that characterize the current reporting period (“ONDJ”) using large spatial units, the present introduction to chapter 3 focuses on countries, i.e. it aims at identifying countries that suffered abnormal climatic conditions and resulting abnormal agronomic conditions. 165 countries and territories are included, omitting only those which are too small to yield meaningful results at the spatial resolution (approximately 25 km x 25 km at the equator) adopted for the CropWatch agroclimatic indices (CWAIs). They include mostly the smallest island states. 

Only for the 30 major producers and China (30+1 countries), Table 3.1 also lists departures from important agronomic variables including the biomass production potential (BIOMSS), Cropped Arable Land Fraction (CALF) and the maximum Vegetation Condition Index (VCIx). BIOMSS provides the rainfall and temperature limited contribution of the reporting period to annual biomass accumulation. CALF indicates which fraction of arable land was actually cropped. Positive departures mean that cultivated area increased over the average of the previous five years (5YA). VCIx is a measure of yield compared with historical yield for the same locations. High values identify areas where crops performed as well as during the best recent years. Below 0 and above 1 values stand for “worst ever” and “best ever”, respectively.  

The major climatic characteristics and anomalies of the reporting period are listed in Chapter 1 and are not repeated in this section which, as mentioned, focuses on countries. Figures 3.1 to 3.4 (RAIN, TEMP, RADPAR and BIOMSS departures, respectively) bear a marked resemblance to the corresponding figures in Chapter 1, although the spatial detail is greater as in this chapter, figures include not only countries but also first-level administrative units for the 8 largest countries of the world, of which Kazakhstan is the smallest. 

Readers are also invited to consult section 5.2 (Chapter 5) on disasters where additional information is provided for major disasters that occurred during the reporting period, and table 3.1 - mentioned above - which summarises the indicators for the 30 major agricultural countries

Agronomic indicators

The available agronomic indicators do not carry the same statistical weight as the agroclimatic indicators because only selected countries are covered. It is, nevertheless, interesting to compare the countries and to highlight “good” and “bad” performers. 

Average VCIx is 0.86 (unweighted), but the statistical distribution is negatively skewed (skew:  -0,997), i.e. 35% of values are below 0.86 and 65% are above. The large number of positive values results from the technological trend of yields. The lowest values are the following:  Iran (0.51), Pakistan (0.67), Australia (0.67), Kazakhstan (0.67), South Africa (0.68) and China (0.70). High values occur in Indonesia (0.97), Philippines (0.97), Brazil (0.97), Myanmar (0.98), Poland (1.00) and Ukraine (1.04). It is relatively easy to understand the numbers in terms of environmental conditions, as will be illustrated in the country narratives in Chapter 3.2. 

The (unweighted) average CALF variation reaches +3% and here too, the distribution is skewed, but this time the skew is positive (1.202) with 68% of values below the average and 32% above. The worst performers for the current reporting period include Kazakhstan (-45%), Canada (-11%) and Australia (-7%), thus including two of the main global wheat exporters. At the high end we find Ukraine (+13%), Iran (+14%), Pakistan (+16%) and Uzbekistan (+63%).

Interestingly, very few countries “compensate” CALF by VCIx, i.e. low calf by high VCIx or the reverse. On the contrary, CALF and VCIx appear to be (weakly) positively correlated, which results from the same environmental factors affecting both areas cultivated and yield. Among the countries that do “compensate” it is in order to mention Iran (CALF +14%, VCIx 0.51), Pakistan(+16%, 0.67) and Argentina (+8%, 0.71). It is not known at this stage, however, to what extent the “compensation” will ensure satisfactory production.

The extremes include Kazakhstan (-45% CALF, 0.67 VCIx), Australia (-7%, 0.67), Canada (-11%, 0.74), South Africa (-4%, 0.68) and China (-3%, 0.7). At the high end we find Romania (9%, 0.94), Brazil (2%, 0.97), Uzbekistan (63%, 0.95) and Ukraine (13%, 1.04), where the main surprise is Uzbekistan.

Abnormal rainfall 

Drought

The main country-wide rainfall deficit occur in the Mediterranean basin, where winter is the main period of agricultural production and the dominant field crops include wheat in Europe, wheat and barley in Africa as well as in Asia. If rainfall does not improve during spring, serious agricultural impacts are to be expected, all the more so because the same area has suffered drought in the recent past, which resulted in low soil and groundwater moisture storage. Significantly above average precipitation amounts are required to replenish water reserves which are needed as well for irrigated  crops cultivated in winter and in summer, not to mention other water uses. Irrigation using river water dominates in Italy, Spain and Egypt. Countries where groundwater plays a major role in irrigation are particularly at risk, including Portugal1, Spain, Greece and Morocco, as well as the remaining countries bordering the Mediterranean.

Portugal (-65%) and Algeria (-63%) were the driest countries of the area followed by Cyprus (-52%) and several countries in the -50% to -40% range (Italy, Lebanon, Spain,Tunisia and Libya). Among the dry countries we have as well several  Middle-Eastern countries  but their expected rainfall is much lower. For instance Saudi Arabia recorded 13 mm against an average of 34mm, Although the deficit reaches -62%, it is clearly irrelevant for current crop production, although it matters for recharging groundwater reserves. 

Nepal (-60%) and Pakistan (-48%) are among the top drought affected countries in Asia. They are part of a much larger post-monsoon ensemble of where irrigation plays a dominant part for winter (rabi) crops to be harvested next spring. Winter rainfall is not unimportant in those areas as it provides extra and free water, but it is usually not vital for crops. The following areas can be listed in this context, listed by decreasing deficit (-92% to -50%): Delhi, Uttar Pradesh, Himachal Pradesh*, Uttarkhand*, Haryana, Bihar, Madhya Pradesh and Rajasthan. Only the two States marked by an asterisk normally expect more than 100 mm during the ONDJ period.

Severe deficits also occurred in Chile (-51%) where crops are now mostly in the vegetative stage or nearing harvest (wheat). The impact of the drought is potentially severe, particularity for wheat, but the large agro-ecological diversity of the country is a favorable factor. It remains that most of the “southern cone” south of and including the Gran Chaco had moisture supply below expectations, including Uruguay (-26%) and most provinces of Argentina where the deficits are in the order of -40% to -30%, exceptionally drier in parts of Patagonia where crops play a limited part compared with livestock. Rangeland productivity is likely to have been reduced by drought. Drops in BIOMSS indices are, however, about 10% smaller than the corresponding rainfall deficits.

At the national level, two more areas deserve mentioning: New-Zealand (rainfall is down to 145 mm from 279 mm, a 48% drop) and southern Africa with – by decreasing deficit -  Zimbabwe (-36%), Malawi (-36%), Lesotho (-25%) and Botswana (-21%). South Africa (-14%), the major agricultural country in the region is described in detail in the later sections of this chapter. Readers will find that yields of the current maize crop, the main staple in the country, are currently faring poorly (VCIx at 0.68) with a reduction in area (CALF) of 4%. It is stressed that all countries in the region suffered from drought at the time when they receive their summer rains, which correspond to the growth of their dominant cereal staple, i.e. maize. Maize flowering and most water demanding growth stage typically occur in February. February rainfall will thus largely condition the output of crops in the region.

Excess precipitation

At the national level five groups of countries clearly emerge. They are presented here according to their growing season type and timing. 

The first includes eight countries grouped around the Baltic sea and which constitute the “wet counterpart” to the “dry Mediterranean” in Europe. By increasing water excesses, the group includes Estonia (+30%), Finland, Germany, Lithuania, Sweden (+37%) , Belarus, Poland and Norway (+46%). All the countries grow winter crops, although their relative importance compared with summer crops decreases in the northernmost countries. The core of this “Baltic” group is surrounded, especially to the east by a fringe of areas with decreasing excess water. Still among winter crop areas, we mention two Black Sea countries: Georgia (+30%) and Armenia (+76%) and, in central Asia, Kyrgyzstan (+51%) and Azerbaijan (+60%). It is unlikely that the listed countries have suffered from excess water, even if planting may have been initially delayed because of water logged soils. On the contrary, the stored soil moisture will be beneficial to both winter crops and the summer crops to be planted in 2018.

A second group of two countries that belongs to similar climate conditions occurs in Latin America (Paraguay +35%, Bolivia +34%) ;   however they are currently in the summer-crop season which are mostly at a vegetative stage or very the very beginning of harvest. In Bolivia, due to altitude, crops are currently at the planting stage. In both countries excess precipitation is potentially harmful if soils remain water-logged too long.

The subsequent groups of countries are all tropical or equatorial. The reporting period covers the harvest of their main crop and early stages or planting of secondary crops. Two Caribbean countries 

(Jamaica +36%, Cuba +56%) and their central American neighbors were affected by two cyclones  (Hurricanes Maria and Irma, November 2017) and therefore recorded damage to their crops due excess water, ocean spray and strong winds. Several typhoons that hit maritime south-east Asia also brought abundant moisture to Vietnam (+38%), Cambodia (+39%) and the Philippines (+46%). The three countries are listed in the section on disasters and they are the subject of a detailed narrative later in the chapter. All of them behave well in terms of their agronomic indicators with CALF departures close to 0 and VCIx above 0.93 (the lowest of the three values which occurs in Vietnam)

Abnormal temperature

How extreme a temperature is can be defined in statistical terms based on a time series analyses. In this case, temperatures in the upper or lower deciles could be termed extreme. This is the approach adopted by the Standardized Precipitation Index (SPI) for rainfall. It is, however, more useful, and more difficult, to define the extreme temperatures in terms of their impacts. 

How extreme any climatic parameter is, interestingly also depends on the spatial scale. The CropWatch agroclimatic indicators are spatial averages over agricultural areas (polygons, such as countries or the large CropWatch MRUs used in Chapter 1). At that scale, random spatial variations of temperature will result in low, probably zero departures compared with average values. In order for departures to reach larger absolute values of departures (for instance two or three degree) it is necessary that the abnormal temperatures be present over large areas inside the polygon.  This is why a departure of two or three degrees at the scale of a country is a meaningful departure. It means that, inside the polygon, there are pixels where the departure was probably much larger, with accordingly larger impacts. Finally, it is noted that positive and negative departures are not symmetric in their effects, as negative departures may reach freezing. 

For the current discussion, we adopt a 1.5°C threshold as “significant” for both negative and positive departures. This is sufficient to define “cooler (warmer) than average” weather, but is does not qualify as cold (heat) wave, for which larger departures in the range or 4 or 5 degrees are required. 

The largest negative departures occurred in Yemen (-2.2°C) and neighboring Eritrea (-1.8°C) as well as Ethiopia and North Sudan.  They are followed by an area in southern Africa which includes  Swaziland (-2.1°C) and Lesotho (-1.5°C) as well as Mozambique, Malawi and Madagascar with departures close to 1.0°C. In Europe, the area affected by low temperature includes the United Kingdom and Ireland (both at -1.9°C), France and Norway (both at -1.6°C). North Africa, Tunisia recorded 14°C average temperature, 1.6°C below average. Ethiopia is doing fine in terms of agronomic indices for the reporting period, which covers the late harvest of the main “meher” season. The same applies to the United Kingdom and France, where winter crops are currently overwintering (CALF +1% and -1%; VCIx 0.89 and 0.84).   

Positive departures, but nowhere of heat-wave intensity occurred in Bhutan and Belarus (+1.5°C for both), Jammu & Kashmir (+1.6°C), as  well as Iraq and Syria (resp. +1.8°C and +1.9°C). The largest increases occur, as noted repeatedly in the Recent CropWatch bulletins, at Boreal latitudes in areas of minor agricultural relevance, such as the Arkhangelsk Oblast and the Komi Republic in the European part of Russia and the Yukon & Northwest Territory, which constitute the northernmost parts of Canada. In Canada, the corresponding  average temperatures are close to -20.0°C, so that temperature remains well within the freezing range and significant ecological changes are unlikely. In Russia, however, the averages are just -5.0°C or -6.0°C, and local thawing or ice and snow is likely, with possible agricultural and ecological consequences such as overwintering of pests, alterations to the water balance and increased winter methane emissions from peat-lands. 

Abnormal   radiation

Sunshine deficits in excess of 15% all occurred in Europe in an area centered on the Baltic Sea and including Finland (-24%), Belarus (-19%), Estonia (-18%), Luxembourg (-17%), Ireland (-16%), Germany and neighboring Poland, both at -15%. For sunshine, a factor much less variable spatially than temperature and rainfall, the listed values would be the equivalent of a “dark wave.” During summer, it would reduce photosynthesis by an approximately equivalent percentage and yields would be affected. For the current season, when crops are dormant and days are short, it is unlikely that a lasting effect on crops will result.  Indeed, agronomic indices for Germany and Poland are very favourable, with VCIx showing yields close to historical records.

Values below average by more than 10% include, in Europe, Lithuania (-14%), Belgium (-13%), Latvia (-13%), Ukraine (-13%), Norway (-12%), Czechia (-12%), Netherlands (-11%) and Sweden (-10%). In Asia, with the main exception of China (-12%), which also cultivates winter crops, several tropical countries are currently in their irrigated dry season or at the early stages of their second crop after harvesting the main crops at the end of the year, which includes Vietnam (-14%), Japan (-12%),  Bangladesh (-11%), Lao PDR (-10%) and Timor Leste (-10%).  Some crop impact of the low sunshine is likely, especially on rice for which sunshine is the major limiting factor, although both Bangladesh and Vietnam show rather good VCIx of 0.95 and 0.93, respectively. Among the listed countries, China is the only one where a crop impact s likely based on agronomic indicators, including a reduction in planted area (CALF, -3%) and just about fair yield (VCIx at 0.70).   

Finally,  one African country has to be listed: Sao Tome and Principe (-12%). 

Countries in the range of -6% to -9% number 26. They cannot be listed although the sunshine departures are still significant. Most of them belong to the general areas mentioned above, e.g. Nigeria (-6%) and Liberia (-8%). Some do occur in other parts of the world, such as Honduras (-9%), Cuba (-9%) and Jamaica (-8%) and, in the south of the continent, Chile at -6%. Russia, because of it’s size, deserves mentioning as well (-6%). Actually, RADPAR is the most “extreme” CWAI for Russia. Some very low values between -21% and -26% departures are recorded in the west, between the Baltic and Ukraine and including the Oblasts of Arkhangelsk (-21%),  Orlovsky, 

Kursk , Vologodsky, Lipetsk and Murmansk (-26%). According to VCIx Russian yields are not spectacular, but they are largely compensated by a cropped arable land fraction increase of 7% over the 5YA. 

 Positive RADPAR departures are much less frequent than poor sunshine conditions. They are all associated with reduced rainfall or drought and include Italy (+5%), Botswana (+6%), Greece (+6%) and Portugal (+9%). 

Combinations of abnormal weather conditions

The above-mentioned Portugal combines two extremes: the largest positive sunshine anomaly (+9% RADPAR) with the largest rainfall departure (RAIN -65%). Other countries combine three extremes.

To establish the list below, the deciles are considered as the thresholds for extremes, i.e. for each variable (RAIN, TEMP, RADPAR) the departures (among 164 countries) that fall in the upper or lower 10% are considered as extremes. Five European countries are ranked as extreme for all their climatic variables:  Belarus  (+40%, 1.5°C, -19%), Poland  (+41%, 1.4°C, -15%), Norway  (+46%, -1.6°C, -12%), Lithuania  (+33%, 1.4°C, -14%) and Germany  (33%, 1.2°C, -15%), where the brackets contain ΔRAIN, ΔTEMP and ΔRADPAR. Four  of them fall into the category of very wet and warm winter conditions with very low sunshine; all of them are “Baltic” countries. Interestingly, number 5, a geographically very close country (Norway) is in the category of very wet and cold winter conditions with very low sunshine. 

If a less stringent threshold is adopted, e.g. 0.75, which considers the upper and lower quartiles as extreme, the category of countries extreme for all three RAIN, TEMP and RADPAR would number 22. 

Six countries stand out for unusual values of TEMP and RADPAR, including Ireland  (-1.9°C, -16%), Estonia  (1.3°C, -18%),  Latvia  (1.3°C, -13%), Czechia  (1.3°C, -12%), Ukraine  (1.4°C, -13%) and … Somalia  (-1.3°C, 3%). All of them also had above average rainfall in the range of +20% to +30%. CropWatch agronomic indicators are available for Ukraine where the combination of a record yield (VCIx value of 1.04) and a significant increase in cultivated areas (+13%, one of the largest of all countries monitored by CropWatch). 

Countries which, for the current reporting period, were abnormal in terms of RAIN and RADPAR number three: Portugal  (-65%, 9%), Spain  (-46%, 4%) and Vietnam  (38%, -14%). Four stand out because of unusual RAIN and TEMP: dry and cool Horn of Africa and south Arabian Peninsula with Yemen  (-58%, -2.2°C), Eritrea  (-51%, -1.8°C) and North Sudan (-46%, -1.2°C), wet and cool Paraguay  (35%, -1.4°C) and dry and warm New Zealand  (-48%, 1.2°C).