Intraseasonal Characteristics of Rainfall for Eastern Africa Community (EAC) Hotspots: Onset and Cessation dates. In support of;

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1 Intraseasonal Characteristics of Rainfall for Eastern Africa Community (EAC) Hotspots: Onset and Cessation dates In support of; Planning for Resilience in East Africa through Policy, Adaptation, Research and Economic Development (PREPARED) Project November 2014

2 TABLE OF CONTENTS 1. BACKGROUND TERMS OF REFERENCE INTRODUCTION DATA USED METHODOLOGY ADOPTED Identification of the climate change hot spots Determination of the onset and cessation dates RESULTS AND DISCUSSION Identification of the climate change hot spots Determination of the onset and cessation dates SUMMARY ii

3 1. BACKGROUND ICPAC within the framework of the USAID Limited Scope Grant Agreement (LSGA) No LGSA partnered with USAID climate change program called Planning for Resilience in East Africa through Policy, Adaptation, Research, and Economic Development (PREPARED). ICPAC is to work on decision-making tools to help achieve the result Climate change adaptation, technical capacity, policy leadership, and action readiness to regional institutions increased by addressing the following three specific objectives: (a). (b). (c). Support the development of a set of functional and replicable climate science based geospatial decision-making and management tools; Support to ICPAC to strengthen regional climate and information management services; Support improved coordination and coherence among key national and regional institutions on climate information management across the region. 2. TERMS OF REFERENCE The terms of reference (ToR) requires that the following activities be undertaken on part-time basis: Undertake the identification of hot spots in the observed time-space records that contribute to the variability / change in Eastern Africa Develop climate risk maps including the onset, cessation, and dry and wet spells among others. Develop regional maps on climate variability and extremes. This report provides some background as well as the activities that were undertaken to address the first ToR and part of second ToR on identification of hot spots in the observed time-space records that contribute to the variability / change in Eastern Africa and determination of the onset and cessation dates over the identified climate change hot spots respectively. This report covers the activities undertaken during the May October 2014 period. The remaining TORs will be carried out in the coming Financial Year (2014/2015). 3. INTRODUCTION The commencement, performance and stoppage of the rainfall during the rainfall season determines a number of factors such as the sowing time, type of crop to cultivate during the season, the crop management practices and pests and diseases among others. It is therefore of paramount importance to determine the onset and cessation dates of the rainfall as well as the within-the-season distribution of the wet and dry spells. 1

4 Studies have shown that a rainfall season with above average rainfall may not be better than a below average season over an agricultural region if the rainfall are not well distributed in space and time. Crops mostly perform better with evenly distributed light rains than a few isolated heavy rainfall interrupted by prolonged dry periods since consistency of minimum required rainfall as supplied by alternating wet and dry spells is more important than the total rainfall. 4. DATA USED Several data sets were utilized in order to determine the onset and cessation dates over the identified climate change hot spots in Eastern Africa. Blended monthly gauged and satellite rainfall data was used to determine those areas with significant trends (called the climate change hot spots ) over the period 1981 to 2013 over the five countries making up the Eastern Africa community. The data has been incorporated under the GeoCLIM software. Daily Rainfall estimates (RFEs) were also used for the period 1983 to 2013 over the area of study in order to determine the onset and cessation dates over the identified climate change hot spots. The Africa Rainfall Climatology version 2 (ARC2) dataset was utilized for this purpose. This dataset has a horizontal resolution of 0.1 latitude by 0.1 longitude. 5. METHODOLOGY ADOPTED 5.1 Identification of the climate change hot spots The GeoCLIM software allows for the determination of the various rainfall derivatives such as the percentiles, co-efficient of variability, standardized precipitation index among others. It also allows for the determination of the trend over time and further assesses which of these trends are significant. The areas with significant trends were determined during the four standard seasons of January-February (JF), March-April-May (MAM), June-July-August (JJA) and September-October- November-December (SOND) over the Eastern Africa countries of Burundi, Kenya, Rwanda, Tanzania and Uganda. However, the MAM season is emphasized in this report since the onset and cessation dates were mainly determined during this season. 2

5 5.2 Determination of the onset and cessation dates The RFEs were extracted on the grid points over the hotspot areas identified earlier as per section 5.1. The RFEs were extracted during the main rainfall season over hotspot areas with the one preand post-seasonal month included to cater for the early onsets and delayed cessations in each year. The T-Mode Principal component analysis was then undertaken for all the grid point data and the first principal component scores extracted. These scores for the first principal component were then cumulated and plotted as a line graph in order to determine the onset and cessation dates. The onset (cessation) date corresponds with the first consistent upward (downward) turning point in the cumulative scores curve. It was within these two dates (onset and cessation) that the remaining intraseasonal characteristics will be derived. Upon the determination of the onset and cessation dates, the Spearmann rank correlation test was used to determine whether there exist significant trends in these two intraseasonal characteristics. It should however be noted that even the satellite rainfall estimates suffers from the missing records. In order to overcome this problem, the program to determine the onset and cessation dates was allowed to run with upto 15 days missing within the 150 days season. However, two years namely 1985 and 1990 had more than 15 days missing and therefore not analyzed further for the onset and cessation dates. 6. RESULTS AND DISCUSSION 6.1 Identification of the climate change hot spots Figure 1 shows the results for the trend analysis that were obtained from the GeoCLIM software. Figure 1(a) shows that most parts of the Eastern Africa region have decreasing trends during the March-May season during the period 1981 to However, over southern tip and north-western tip of Tanzania; south-western tip, central and north-eastern Uganda; south-western on the Kenya- Tanzania and much of Rift Valley in Kenya, increasing trend were noted. Figure 1(b) shows the areas with significant trends during the MAM season. It is interesting to note that the only the decreasing trends were significant apart from over the south-western Uganda. It was over these areas which are marked with red rectangles (in Figure 1(b)) that the onset and cessation dates were determined 3

6 Figure 1: (a) Trend analysis results during the March-April-May (MAM) season for the period (b) Spatial map showing areas with significant trend during the MAM season of The red rectangle shows the appropriate locations where the onset and cessation dates were determined 6.2 Determination of the onset and cessation dates During the dry period prior to the wet season, there is the depletion of the soil moisture due to the prevailing dry conditions. This is represented by the downward slope in the cumulative principle component score curve. The first consistent point at which this curve turns upwards marks the onset of the rainfall. It simply shows the commencement in the recharge of the soil moisture. The next consistent point at which the curve turns downwards marks the cessation of the rainfall and the beginning of the next dry season and thus the soil moisture depletion again. Figure 2 shows the daily rainfall estimates for every year at each grid point over northern Kenya area (37.7 E 38.9 E; 1.5 N 2.9 N at a horizontal resolution of 0.1 by 0.1 ) for the period 1983 to The thick black line shows the average daily rainfall estimate over this area. It is quite clear that the area receives sporadic rainfall throughout the year but the main rainfall seasons are over the March-May period and October-December period. 4

7 Figure 2: Plots of daily rainfall estimates for all the grid points over northern Kenya (37.7 E 38.9 E; 1.5 N 2.9 N) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. Over this area, the earliest onset and cessation dates of the rainfall were noted as February 15 th and April 7 th respectively. The latest onset and cessation dates were April 16 th and May 26 th respectively. On average, the rainfall commences and ceases on March 24 th and April 30 th. The trend of onset and cessation dates indicated that both tend to occur earlier over time (Figure 3). However, these trends were not significant at 95% confidence levels. 5

8 Figure 3: Interannual variability of the onset and cessation dates over northern Kenya Figure 4 shows the daily rainfall estimates for every year at each grid point over northern coast of Kenya area (40.3 E 40.7 E; 1.8 S 2.6 S) for the period 1983 to Similar to northern Kenya, the area receives sporadic rainfall throughout the year. However the main rainfall seasons are concentrated over April-June period and November-December period. On the northern coast of Kenya, the earliest onset and cessation dates of the rainfall were noted as March 11 th and April 30 th respectively. The latest onset and cessation dates were May 26 th and June 25 th respectively. On average, it starts raining on April 11 th and stops on May 25 th. The trend of onset and cessation dates indicated that both have been delaying over time (Figure 5), with the gradients for the onsets being much steeper. 6

9 Figure 4: Plots of daily rainfall estimates for all the grid points over northern coast of Kenya (40.3 E 40.7 E; 1.8 S 2.6 S) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. Figure 5: Interannual variability of the onset and cessation dates over north coast of Kenya 7

10 Figure 6 shows the daily rainfall estimates for every year at each grid point over central Tanzania area (37.0 E 37.7 E; 7.6 S 8.5 S) for the period 1983 to This area has a distinct unimodal rainfall pattern with the rainfall period starting in November and ending in April. It was therefore only meaningful to determine the cessation dates over this area. The earliest cessation over this area occurred on March 18 th wihile the latest cessation was observed on April 25 th during the 1983 to 2013 period. On the average, the cessation date was April 14 th over this area. The cessation of the rainfall has been delayed over time (Figure 7) although this trend was not significant at 95% confidence level. Figure 6: Plots of daily rainfall estimates for all the grid points over central Tanzania (37.0 E 37.7 E; 7.6 S 8.5 S) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. 8

11 Figure 7: Interannual variability of the cessation dates over Central Tanzania Figure 8 shows the daily rainfall estimates for every year at each grid point over Burundi-Tanzania border area (30.2 E 31.4 E; 3.4 S 4.0 S) for the period 1983 to This area receives rainfall throughout the year with a dry season during the June September period. This therefore means that only the cessation dates can be determined for this area. Over this area, the earliest cessation of the rainfall was noted to be March 27 th while the latest cessation was observed on May 14 th. This gives an interannual range of cessation dates of 48 days. On average, the rainfall ceases on April 18 th over the Burundi-Tanzania border. The trend of cessation dates has remained constant over time in this area (Figure 9). 9

12 Figure 8: Plots of daily rainfall estimates for all the grid points over Burundi-Tanzania border (30.2 E 31.4 E; 3.4 S 4.0 S) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. Figure 9: Interannual variability of the cessation dates over Burundi-Tanzania border 10

13 Figure 10 shows the daily rainfall estimates for every year at each grid point over northern Rwanda area (29.6 E 30.0 E; 1.6 S 1.8 S) for the period 1983 to This area receives rainfall throughout the year with a dry season during the June August period. Although this area was identified from the MAM trend analysis, only the cessation dates could be determined since the earlier part of the MAM season is a continuation of the previous wet season. Over the period 1983 to 2013, the earliest cessation for the rainfall occurred on March 26 th while the latest occurred in May 14 th. On the average the rainfall ceases on April 20 th over this area. Over the years, the trend analysis shows that the rainfall has been ceasing earlier with time, this trend was not significant (Figure 11). Figure 10: Plots of daily rainfall estimates for all the grid points over northern Rwanda (29.6 E 30.0 E; 1.6 S 1.8 S) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. 11

14 Figure 11: Interannual variability of the cessation dates over northern Rwanda Figure 12 shows the daily rainfall estimates for every year at each grid point over northwestern Uganda area (30.9 E 31.1 E; 2.8 N 3.2 N) for the period 1983 to Rainfall commences in February and ends in December over this area. Considering that this area was identified from the MAM trend analysis, it therefore means that only the onset can be determined for this area. During the period 1983 to 2013, the earliest onset was found to occur on February 17 th while the latest onset occurs on April 30 th. This gave an interannual range of onset dates over this area being 72days. The trend analysis of the interannual variability of the onset dates shows a delayed trend (Figure 13) though it was not significant. 12

15 Figure 12: Plots of daily rainfall estimates for all the grid points over northwestern Uganda (30.9 E 31.1 E; 2.8 N 3.2 N) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. Figure 13: Interannual variability of the onset dates over northwestern Uganda 13

16 Figures 14 and 15 shows the daily rainfall estimates for every year at each grid point over central Uganda (30.9 E 31.9 E; 0.1 S 0.6 N) and southern Uganda area (32.1 E 32.7 E; 0.1 S 0.6 S) respectively for the period 1983 to These areas receive rainfall throughout the year despite the fact that they were identified from the MAM seasonal rainfall totals. It was therefore not possible to determine the onset and cessation dates over these areas. Figure 14: Plots of daily rainfall estimates for all the grid points over central Uganda (30.9 E 31.9 E; 0.1 S 0.6 N) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. 14

17 Figure 15: Plots of daily rainfall estimates for all the grid points over central Uganda (32.1 E 32.7 E; 0.1 S 0.6 S) at a horizontal resolution of 0.1 by 0.1 for the period 1983 to The thick black line shows the average value for each day. 7. SUMMARY From the GeoCLIM software, various regions with significant trend in the seasonal rainfall totals for the March to May season over the 33 years (1981 to 2013) period were identified. The identified regions were well spread over the Eastern African countries. All the regions identified have a significant decreasing trend in the MAM seasonal rainfall totals. The satellite daily rainfall estimates (RFEs) over the identified areas were extracted from 1983 to 2013 for the February-June (FMAMJ) period in order to capture the earlier onsets and delayed cessation outside the MAM season. The extracted RFEs were subjected to T-mode PCA and the resulting 1 st principal component scores cumulated to determine the onset and cessation dates. The daily plots of the extracted RFEs showed that while only two areas had the distinct MAM season, the rest of the areas identified with significant decreasing trend did not have a distinct MAM season. For these areas, the MAM season was either the initial/end part of an extended rainfall season. It was therefore not possible to determine both the onset and cessation dates for these areas. 15

18 The onset and/or cessation dates were determined for all the areas identified finally determined. The trends of the interannual variability of these dates were however not significant at 95% confident levels according to the Spearmann rank correlation test. It is highly recommended that the gauged daily rainfall data over those areas with significant decreasing trend be available to supplement the results obtained from the satellite RFEs. 16