This study investigates the spatial-temporal trends and variability of rainfall within East and South Africa (ESA) region. The newly available Climate Hazards group Infrared Precipitation with Stations (CHIRPS-v2) gridded data spanning 37 years (1981 to 2017) was validated against gauge observations (N = 4243) and utilised to map zones experiencing significant monotonic rainfall trends. Standardised annual rainfall anomalies revealed the spatial-temporal distribution of below and above normal rains that are associated with droughts and floods respectively. Results showed that CHIRPS-v2 data had a satisfactory skill to estimate monthly rainfall with Kling-Gupta efficiency (KGE = 0.68 and a high temporal agreement (r = 0.73) while also preserving total amount (β = 0.99) and variability (γ = 0.8). Two contiguous zones with significant increase in annual rainfall (3–15 mm year⁻¹) occurred in Southwest Zambia and in Northern Lake Victoria Basin between Kenya and Uganda. The most significant decrease in annual rainfall (− 20 mm year⁻¹) was recorded at Mount Kilimanjaro in Tanzania. Other significant decreases in annual rainfall ranging between − 4 and − 10 mm year⁻¹ were observed in Southwest Tanzania, Central-South Kenya, Central Uganda and Western Rwanda. CHIRPS-v2 rainfall product provides reliable high spatial resolution information on amount of rainfall that can complement sparse rain gauge network in rain-fed agricultural systems in ESA region. The observed spatial-temporal trends and variability in rainfall are important basis for guiding targeting of appropriate adaptive measures across multiple sectors.

Monitoring land degradation (LD) to improve the measurement of the sustainable development goal (SDG) 15.3.1 indicator (“proportion of land that is degraded over a total land area”) is key to ensure a more sustainable future. Current frameworks rely on default medium-resolution remote sensing datasets available to assess LD and cannot identify subtle changes at the sub-national scale. This study is the first to adapt local datasets in interplay with high-resolution imagery to monitor the extent of LD in the semiarid Kiteto and Kongwa (KK) districts of Tanzania from 2000–2019. It incorporates freely available datasets such as Landsat time series and customized land cover and uses open-source software and cloud-computing. Further, we compared our results of the LD assessment based on the adopted high-resolution data and methodology (AM) with the default medium-resolution data and methodology (DM) suggested by the United Nations Convention to Combat Desertification. According to AM, 16% of the area in KK districts was degraded during 2000–2015, whereas DM revealed total LD on 70% of the area. Furthermore, based on the AM, overall, 27% of the land was degraded from 2000–2019. To achieve LD neutrality until 2030, spatial planning should focus on hotspot areas and implement sustainable land management practices based on these fine resolution results.

Rainfall onset and cessation date greatly influence cropping calendar decisions in rain-fed agricultural systems. This paper examined trends of onsets, cessation, and the length of growing season over Northern Ghana using CHIRPS-v2, gauge, and farmers’ perceptions data between 1981 and 2019. Results from CHIRPS-v2 revealed that the three seasonal rainfall indices have substantial latitudinal variability. Significant late and early onsets were observed at the West and East of 1.5° W longitude, respectively. Significant late cessations and longer growing periods occurred across Northern Ghana. The ability of farmers’ perceptions and CHIRPS-v2 to capture rainfall onsets are time and location-dependent. A total of 71% of farmers rely on traditional knowledge to forecast rainfall onsets. Adaptation measures applied were not always consistent with the rainfall seasonality. More investment in modern climate information services is required to complement the existing local knowledge of forecasting rainfall seasonality.

This study investigates the magnitude and significance of spatial-temporal trends of 37 years' time series of gridded data for rainfall, maximum (Tmax) and minimum (Tmin) temperature for West Africa. A modified Mann-Kendall test and Theil-Sen's slope estimator were utilized to test the significance and the magnitude of trends, respectively. The magnitude of significant trends for three variables between six agroecological zones (AEZ's) was compared. Gridded climate data represented gauge data with high accuracy and, therefore, can reliably complement the sparse observation network in West Africa. The three variables showed significant positive and negative trends of varying magnitude and spatial extent. June to September rainfall showed a positive increase (0.1 — 5 mm month $^1$ year $^1$ ) that mostly occurred north of 11o latitude. October rainfall showed a positive trend across the region, but the magnitude was higher south of the same latitude. A widespread significant warming trend was observed across all AEZ's and months. However, a localized cooling in August and September over the Sahel and Sudan Savanna was an exception. The cooling trend over the two AEZ's coincided with a positive trend of rainfall. The zonal analysis revealed that the magnitude of the positive direction of June, September, and October rain increased following a North-South gradient from the Sahel to humid forest AEZ's. Results provide spatial evidence of climate change in a limited data environment to guide the targeting of appropriate adaptation measures. The information generated from this study helps the design of early warning systems against droughts and floods.

Sigatoka leaf diseases are a major constraint to banana production. A survey was conducted in Tanzania and Uganda to assess the distribution of Pseudocercospora species and severity of Sigatoka leaf diseases. Pseudocercospora species were identified using species‐specific primers. Sigatoka‐like leaf diseases were observed in all farms and on all cultivars, but disease severity varied significantly ( P < 0.001) between countries, districts/regions within countries, altitudinal ranges and banana cultivars. In all regions except Kilimanjaro, P. fijiensis , the causal agent of black Sigatoka, was the only pathogen associated with Sigatoka disease. Mycosphaerella musae was associated with Sigatoka‐like symptoms in Kilimanjaro region. Black Sigatoka disease was more severe in Uganda, with a mean disease severity index (DSI) of 37.5%, than in Tanzania (DSI = 19.9%). In Uganda, black Sigatoka disease was equally severe in Luwero district (mean DSI = 40.4%) and Mbarara district (mean DSI = 37.9%). In Tanzania, black Sigatoka was most severe in Kagera region (mean DSI = 29.2%) and least in Mbeya region (mean DSI = 11.5%). Pseudocercospora fijiensis , the most devastating sigatoka pathogen, was detected at altitudes of up to 1877 m a.s.l. This range expansion of P. fijiensis , previously confined to altitudes lower than 1350 m a.s.l. in East Africa, is of concern, especially for smallholder banana farmers growing the susceptible East African Highland bananas (EAHB). Among the banana varieties sampled, the EAHB, FHIA hybrids and Mchare were the most susceptible. Here, the loss of resistance in Yangambi KM5, a banana variety previously resistant to P . fijiensis , is reported for the first time.