Climate Change Projections for Tanzania Based on High-Resolution Regional Climate Models From the Coordinated Regional Climate Downscaling Experiment (CORDEX)-Africa

Luhunga, Philbert; Kijazi, Agnes Lawrence; Chang’a, Ladislaus Benedict; Kondowe, Afredy Lawrence; Ng’ongolo, Hashim K.; Mtongori, Habiba Ismail

doi:10.3389/fenvs.2018.00122

Cited by 65 publications

(67 citation statements)

References 26 publications

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“…The future climate projections of Tanzania are likely to present several challenges to the agriculture sector. For instance, the projected increase in temperatures in many regions as indicated by Luhunga et al (2018) are likely to influence wilting and drying of plants and multiplication of pest, weeds, and diseases that would result in increased costs of crop production and failure in crop yields. Also, warmer temperatures are likely to cause an eruption of new pests, parasites, and diseases that would affect the agriculture sector severely.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

Luhunga

Songoro

2020

Front. Clim.

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The understanding of climate change impacts and the associated climate extreme events at regional and local scales is of critical importance for planning and development of feasible adaptation strategies. In this paper, we present an analysis of climate change and extreme climate events in the Lake Victoria region of Tanzania, focusing on the Kagera and Geita regions. We use daily simulated climate variables (rainfall and minimum and maximum temperatures) from the Coordinated Regional Climate Downscaling Experiment Program Regional Climate Models (CORDEX_RCMs) for the analysis. Extreme climate event, rainfall, and minimum and maximum temperatures time series during historical (1971–2000) climate condition are compared to future climate projection (2011–2100) under two Representative Concentration Pathway (RCP): RCP 4.5 and RCP 8.5 emission scenarios. The existence, magnitude, and statistical significance of potential trends in climate data time series are estimated using the Mann–Kendall (MK) non-parametric test and Theil-SEN slope estimator methods. Results show that during historical (1971–2000) climate, the Lake Victoria region of Tanzania experienced a statistically significant increasing trend in temperature. The annual minimum and maximum temperatures in the Kagera and Geita regions have increased by 0.54–0.69°C, and 0.51–0.69°C, respectively. The numbers of warm days (TX90p) and warm nights (TN90p) during the historical climate have increased, while the numbers of cold days (TX10p) and cold nights (TN10p) have decreased significantly. However, in future climate condition (2011–2100) under both RCP 4.5 and RCP 8.5 emission scenarios, the Lake Victoria region is likely to experience increased temperatures and rainfall. The frequency of cold events (cold days and cold nights) is likely to decrease, while the frequency of warm events (warm days and warm nights) is likely to increase significantly. The number of consecutive wet days, the intensity of very wet days, and the number of extreme wet days are likely to increase. These results indicate that in future climate condition, socioeconomic livelihoods of people in the Kagera and Geita regions are likely to experience significant challenges from climate-related stresses. It is, therefore, recommended that appropriate planning and effective adaptation policies are in place for disaster risk prevention.

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Section: Introductionmentioning

confidence: 99%

Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

Luhunga

Songoro

2020

Front. Clim.

Self Cite

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“…With limited funding, they tend to prioritise model resolution over model inclusion (e.g. Luhunga et al 2018). Our results indicate the importance of including information from a range of models, rather than the use of just one or an average of many.…”

Section: Discussion and Recommendationsmentioning

confidence: 83%

“…Experience in climate risk assessment has revealed a need to a focus on decision-relevant timescales, and to give greater attention to climate model evaluation (and the decisions therein-see Chaps. 1 and 2) and consideration of climate variability, within climate change analyses to help model projections become more useful in guiding local, practical adaptation (Conway and Schipper 2011;Nissan et al 2019;Ray and Brown 2015).…”

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confidence: 99%

High Stakes Decisions Under Uncertainty: Dams, Development and Climate Change in the Rufiji River Basin

Siderius

Geressu

Todd

et al. 2021

Climate Risk in Africa

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The need to stress test designs and decisions about major infrastructure under climate change conditions is increasingly being recognised. This chapter explores new ways to understand and—if possible—reduce the uncertainty in climate information to enable its use in assessing decisions that have consequences across the water, energy, food and environment sectors. It outlines an approach, applied in the Rufiji River Basin in Tanzania, that addresses uncertainty in climate model projections by weighting them according to different skill metrics; how well the models simulate important climate features. The impact of different weighting approaches on two river basin performance indicators (hydropower generation and environmental flows) is assessed, providing an indication of the reliability of infrastructure investments, including a major proposed dam under different climate model projections. The chapter ends with a reflection on the operational context for applying such approaches and some of the steps taken to address challenges and to engage stakeholders.

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“…1), which are characteristic of the challenges around sustainable and climate-resilient development across the 'water-energy-food' (WEF) nexus (Section 2.3.2). This is especially pertinent given the magnitude of current and proposed major ('high stakes') investments in agriculture and hydropower (Bhave et al 2020;Conway et al 2019;Luhunga et al 2018). For these case studies, we did the following:…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

et al. 2021

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Uncertainty in long-term projections of future climate can be substantial and presents a major challenge to climate change adaptation planning. This is especially so for projections of future precipitation in most tropical regions, at the spatial scale of many adaptation decisions in water-related sectors. Attempts have been made to constrain the uncertainty in climate projections, based on the recognised premise that not all of the climate models openly available perform equally well. However, there is no agreed ‘good practice’ on how to weight climate models. Nor is it clear to what extent model weighting can constrain uncertainty in decision-relevant climate quantities. We address this challenge, for climate projection information relevant to ‘high stakes’ investment decisions across the ‘water-energy-food’ sectors, using two case-study river basins in Tanzania and Malawi. We compare future climate risk profiles of simple decision-relevant indicators for water-related sectors, derived using hydrological and water resources models, which are driven by an ensemble of future climate model projections. In generating these ensembles, we implement a range of climate model weighting approaches, based on context-relevant climate model performance metrics and assessment. Our case-specific results show the various model weighting approaches have limited systematic effect on the spread of risk profiles. Sensitivity to climate model weighting is lower than overall uncertainty and is considerably less than the uncertainty resulting from bias correction methodologies. However, some of the more subtle effects on sectoral risk profiles from the more ‘aggressive’ model weighting approaches could be important to investment decisions depending on the decision context. For application, model weighting is justified in principle, but a credible approach should be very carefully designed and rooted in robust understanding of relevant physical processes to formulate appropriate metrics.

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Climate Change Projections for Tanzania Based on High-Resolution Regional Climate Models From the Coordinated Regional Climate Downscaling Experiment (CORDEX)-Africa

Cited by 65 publications

References 26 publications

Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

High Stakes Decisions Under Uncertainty: Dams, Development and Climate Change in the Rufiji River Basin

Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

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