A Late April Assessment Indicates Poor Long Rains and Low Gu Harvests for Somalia

Chris Funk, Pete Peterson, Peris Muchiri, Diego Pedreros, Greg Husak, Diriba Korecha, Gideon Galu, Laura Harrison, Will Turner, Marty Landsfeld and Shrad Shukla

This post examines conditions across East Africa at the close of April. As predicted by the  CHG, ICPAC, and a joint assessment by FEWS NET, WFP, FAO and JRC, exceptional warming in the West Pacific appears to have continued to produce subsidence and drying over East Africa.  At present (Figure 1), the FEWS NET food security outlook for Eastern Africa is very concerning, with a June-September outlook calling for IPC phase 3 (crisis) or 4 (emergency) across Kenya, South Sudan, southern Ethiopia and Somalia. The FEWS NET perspective seems largely congruent with the most recent seasonal assessment by the World Food Programme (here).

In Kenya, southern Ethiopia and Somalia June-September food security outcomes will be strongly influenced by rainfall in March and April, since most of the long rains tend to come in these months, and moist soils during this period support the establishment of healthy crops. As we will show below, poor March-April rainfall can be a good predictor of low crop production in Somalia.

FEWS NET Food Security Outlook for June-September 2017. Orange and red shades denote crisis and emergency conditions. Black shading in South Sudan indicates famine.
Figure 1. FEWS NET Food Security Outlook for June-September 2017. Orange and red shades denote crisis and emergency conditions. Black shading in South Sudan indicates famine.

We begin by looking at the observed March to late April rainfall performance using NOAA CPC ARC2 and CHIRPS rainfall fields enhanced with data provided by FAO SWALIM and the National Meteorological Agency of Ethiopia. All evidence indicates poor rainfall performance for much of the Greater Horn of Africa. We then examine the relationship between Somali Gu Sorghum crop production statistics and March-May rainfall. We find that March-April rains are by far the most important – and current March-April totals indicate very poor sorghum production totals for 2017. We conclude with a brief look at the current climate conditions and the performance of the NOAA GEFS weather forecasts.

March-April Rainfall Assessment

March-April 24th ARC2 anomalies (Figure 2) and March-April 20th ‘enhanced’ CHIRPS data, expressed as standardized precipitation index values (Figure 3) are in strong agreement that there has been wide-spread drought across almost all of Kenya, Somalia and Uganda as well as southern Ethiopia, eastern South Sudan, north-central Tanzania and western Yemen. Note that the units in these maps are different. It is useful to consider rainfall anomalies both in terms of absolute magnitude (Figure 2) and as standardized anomalies (Figure 3). In Figure 2 we note very large (100 mm) rainfall deficits across central Kenya, Uganda and in the SNNPR region of Ethiopia; these large deficits could be associated with large disruptions in key crop growing areas. In Figure 3 we see that the seasonal rainfall progress has been exceptionally dry, in a statistical sense (<-1 standard deviations) across most of the Horn.

NOAA CPC ARC2 precipitation totals from March 1st-April 24th 2017.
Figure 2. NOAA CPC ARC2 precipitation totals from March 1st-April 24th 2017.

In Somalia, where even normal rainfall totals are characteristically low, we find that our estimates indicate an exceptionally poor March-May season. While the results in Figure 2 do not indicate performance over the last dekad of April, CPC ARC2 totals for April 21, 22, 23 and 24 show almost no rainfall over Somalia.

 CHIRPS Standardized Precipitation Index values from March 1st-April 20th 2017.
Figure 3. CHIRPS Standardized Precipitation Index values from March 1st-April 20th 2017.

For Somalia, it is important to realize that we have been able to incorporate a fairly dense network of gauge observations provided by FAO SWALIM. Figure 4 shows April 1st to April 20th enhanced CHIRPS rainfall totals. The numbers on this map show rainfall totals from either the SWALIM stations or WMO GTS observations. Across all of East Africa, very few regions appear to have received more than 60 mm of rain so far in April. From a crop perspective, this means that planting has been delayed across Kenya and Somalia, and crop growth is likely to be running substantially behind normal. For example, ARC2 data at Meru, in central Kenya, indicates a seasonal accumulation of ~120 mm, less than half of the normal 270 mm. Results in Baidoa (Bay Region Somalia), Dif in far eastern Kenya, and  Kibre Mengist in south-central Ethiopia are similar.

Enhanced CHIRPS precipitation for April 1 to April 20, 2017.
Figure 4. Enhanced CHIRPS precipitation for April 1 to April 20, 2017.

Seasonal Rainfall Ensembles

To examine likely outcomes for the total March-May season we have combined March 1 to April 20 CHIRPS rainfall totals and then examined the possible combinations of future rainfall by sequentially inserting one of the past 36 years (1981-2016) and then examining the associated distribution of seasonal rainfall totals. We begin by showing these results for the Bay Province of Somalia (Figure 5), which is currently facing food security crisis (i.e. just short of famine) conditions (see Figure 1). We start at a low seasonal total of 42 mm for Bay on April 20th – this low value and large deficit is primarily due to the low April rainfall totals, as shown in the SWALIM station data (Figure 4). To explore the remainder of the season, we sample the CHIRPS data using all prior seasons. Advancing one dekad by this approach gives us a seasonal total for the end of April of 90 mm, only 60% of long term average. As we will see below, this large March-April deficit will very likely be associated with large crop production deficits. Proceeding through the rest of May in this same fashion we arrive at a spread of possible outcomes ranging from near normal to very low, with an average outcome of 174 mm, 74% of the long term average. In the context of the past 20 years, this would be a 1-in-5 year drought (i.e. 20th percentile); 2011, 2001, 2008, and 1999 were a little drier.

Cumulative rainfall ensemble for Bay region of Somalia. Observed CHIRPS dekads are used from February through April 20th.
Figure 5. Cumulative rainfall ensemble for Bay region of Somalia. Observed CHIRPS dekads are used from February through April 20th.

Repeating this process for each pixel, we can assess the probability of March-June rainfall being less than 85% of the long term average (Figure 6) and less than 50% of the long term average (Figure 7). Figure 6 indicates that the regional as a whole is very likely at this point to end with below normal rainfall. The certainty of this outcome is much less in northern East Africa, although some Belg growing regions in the eastern highlands of Ethiopia and the northernmost parts of Somalia and Yemen are shown to have an 80% chance of below normal rains. Across southern Somalia, southern Ethiopia, all of Kenya and much of Tanzania a below normal outcome seems almost certain, given historical rainfall distributions.

Probability of March-May rainfall totals being below normal (less than 85% of average) based on historical rainfall distributions.
Figure 6. Probability of March-May rainfall totals being below normal (less than 85% of average) based on historical rainfall distributions.

Looking at areas likely to see catastrophic (<50% of normal) March-June outcomes, we see that such an outcome is very likely (>50% probability) across much of Kenya and near the Mandera triangle area at the intersection of Somalia, Ethiopia and Kenya. These are regions that have received low March-April 2017 rains (Figure 2 and 3) and have historically had short ‘long’ seasons – such that they now have low chances of anything but poor outcomes. We can see this in more detail by looking at cumulative rainfall totals for the Eastern (Figure 8) and Central (Figure 9) province of Kenya using the USGS Map Viewer. For Eastern province, seasonal rainfall totals have been extremely low (~140 mm), in line with 2010/11, and far below the typical seasonal total of ~310 mm. Historically, rainfall stops in this region at the end of April, hence we find a very high probability of very low rainfall (Figure 7).

Probability of March-May rainfall totals being extremely low (less than 50% of average) based on historical rainfall distributions.
Figure 7. Probability of March-May rainfall totals being extremely low (less than 50% of average) based on historical rainfall distributions.

For the densely populated, well observed Central Province of Kenya, we find that seasonal rainfall accumulations are the lowest in the 2001-2016 RFE2 period of record. The observed 257 mm is far below the average of 518 mm, and substantially lower than values in 2010-2011 at this time (330 mm).

Cumulative RFE2 rainfall totals for the Eastern province of Kenya.
Figure 8. Cumulative RFE2 rainfall totals for the Eastern province of Kenya. Data from https://earlywarning.usgs.gov/fews/mapviewer/index.php?region=af.

In many of these arid land regions current assessments of water hole conditions indicate alert or near-dry conditions – at or near the end of the rainy seasons – it is very likely that conditions will soon get worse in these locations as evaporation takes its toll on surface water stores.

Cumulative RFE2 rainfall totals for the Eastern province of Kenya.
Figure 9. Cumulative RFE2 rainfall totals for the Eastern province of Kenya. Data from https://earlywarning.usgs.gov/fews/mapviewer/index.php?region=af

Assessing likely crop growing outcomes for Somalia’s Gu season

We next turn to Somalia’s Gu sorghum production outlook. This analysis is based on 1999-2016 Gu sorghum production for three key growing regions: Bay, Shabelle Dhexe and Shabelle Hoose. Our objective here is not to produce a precise crop production assessment for Somalia Gu production, but rather to highlight that the poor March-April rainfall totals, alone, are likely to produce serious reductions in crop production. Both the available production data and crop water requirement estimates from a simple crop model indicate that May rainfall will be unable to make up for the poor rainfall distribution in April. Both the crop production and CHIRPS rainfall data in Somalia are likely to be noisy. This analysis is intended to imply that a poor harvest is very likely – but not provide a precise quantitative Somali production forecast.

We began by totaling sorghum production from Bay, Shabelle Dhexe and Shabelle Hoose and related these totals to CHIRPS rainfall from March-May, March-April, and May.  We found an okay level of correspondence between crop production and March-May and March-April rainfall, with corresponding R2 values of 0.22 and 0.34. The correlation between sorghum production and May rainfall was actually weakly negative (-0.25), which helps explain why using March-April totals, rather than March-May totals, improved our predictive skill. The corresponding correlation between April rainfall and Gu sorghum production was fairly high (0.51). April is the key month for crops, according to the empirical data.

To generate a prediction of Gu production in Southern Somalia we regressed (Figure 10) March-April rains in Bay, Shabelle Dhexe and Shabelle Hoose against observed production anomalies (based on a 1999-2016 baseline). We then extracted the average April 1-20 rainfall total from our enhanced CHIRPS data set (27 mm) and assumed 25 mm for the last dekad of April. This latter value was a compromise between the April 21-25 observed ARC2 outcome (~0 mm) and the optimistic weather forecasts (discussed further in the next section). These assumptions and our regression indicate very low March-April rainfall totals and corresponding very poor level of crop performance (-50%), similar to previous recent drought years.

Figure 10. Scatterplot of southern Somalia sorghum production percent anomalies and March-April rainfall [mm].
Figure 10. Scatterplot of southern Somalia sorghum production percent anomalies and March-April rainfall [mm]. The circle marked in red is the production estimate for 2017, based on March-April rainfall.
To further corroborate these results we looked at the relationship between pixel-level Water Requirement Satisfaction Index (WRSI) end-of-season values and onset of rains dates for Bay (Figure 11). The WRSI is an index that shows crop water stress – a value of 100 means no water stress. Note that under normal conditions (with a start in the first or second dekad of April), Bay WRSI values are low (~50). This is a very marginal farming region. In the WRSI model the onset of rains triggers crop growth. It is calculated by identifying areas that receive at least 25 mm of rainfall in a dekad, followed by 20 more mm in the next 20 days. Since our enhanced CHIRPS data indicate average Bay rainfall totals of 12 and 15 mm for the first and second dekad of April, it seems unlikely that the region experienced onset conditions in those dekads. While this outcome was uncommon, we see a large decline in end-of-season WRSI. Our crop simulation results reinforce the critical nature of good early rains.  Crops require weeks of decent rainfall to emerge, put on green vegetation and then divert resources to build up grains. Even if southern Somalia receives torrential rain in the next several weeks it seems unlikely that conditions will be conducive to rainfed agriculture.

 Distribution of end of season WRSI in Bay Somalia, stratified by onset date.
Figure 11. Distribution of end of season WRSI in Bay Somalia, stratified by onset date.

GEFS Forecasts, Current Climate Conditions and What We Know Now

GEFS 7 Day precipitation forecast [mm] April 25-May 2nd.
Figure 12. GEFS 7 Day precipitation forecast [mm] April 25-May 2nd.
We next briefly explore the skill of NOAA’s Global Ensemble Forecast System (GEFS) weather forecasts and discuss their current forecasts for the Horn. The issue we focus on here is the likelihood that current optimistic forecasts (Figure 12) for rainfall over Somalia will verify. These forecasts call for more than 80 mm of rain during the upcoming week. Such relief could definitely improve rangeland conditions and prospects for irrigated agriculture. CHG assessments of GEFS forecast skill (Figure 13) show some promising areas of high correlation, but not for the first half of May or the end of April. Thus while these forecast could prove accurate, the should probably be treated cautiously, since historically they have had fairly low correlations with observations over Somalia, and we have yet to see any rainfall totals approaching this magnitude appear across the region. On the other hand, it is certainly plausible that Somalia could see a few weeks of healthy rain before the season comes to a close. Such rains could improve rangeland conditions and water availability, but may not provide much relief to crop areas in Somalia. Based on the data analyzed here, reliable maps of observed rainfall (Figs. 2-4) provide a solid basis for predicting Gu agricultural outcomes, which look bleak for 2017. Central and Eastern Kenya and the Mandera triangle region also appear very likely to large precipitation deficits.

Correlation between GEFS 2-week forecasts and CHIRPS data for different initialization dates.
Figure 13. Correlation between GEFS 2-week forecasts and CHIRPS data for different initialization dates.

For Kenya, field reports indicate that the area planted with crops is less than 50% of normal in the southeastern lowlands. Central, eastern and coast Kenya has experienced a late onset of rains, only episodic precipitation, and a shortened growing season. At present, maize crops are only just emerging or are very young. Forecasts from the Kenya Met Department are for a normal ending time for the March-May season, suggesting that these crops are unlikely to have time to complete germination and grain filling. The poor March-May trends appear to be part of an ongoing drying trend (Figure 14) associated with warming in the Western Pacific. This trend has helped produce repetitive shocks, reducing household food security and resilience.

March-May rainfall trends based on CHIRPS data enhanced with a dense network of Kenya Met Department observations.
Figure 14. March-May rainfall trends based on CHIRPS data enhanced with a dense network of Kenya Met Department observations.

As an example, consider a time series of NDVI anomalies for the Coastal Province of Kenya (Figure 15). Since 2009, typical vegetation conditions have been below normal, with large drought events in 2009, 2010/11, 2012, and 2016/17. The current 2016/17 appears to be the worst event.

USGS eMODIS NDVI anomalies from the Coastal Province of Kenya.
Figure 15. USGS eMODIS NDVI anomalies from the Coastal Province of Kenya.

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