Advances in the stochastic modelling of satellite-derived rainfall estimates using a sparse calibration dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration

Complementarity: Towards Robust Human Rights Governance in the New Zealand State Sector

Successive governments have committed New Zealand to implementing international human rights standards domestically. In terms of practical governance, what does this mean and how might effectiveness be measured? A face-value answer can be found in domestic laws and institutions relating to human rights. However, this thesis argues that the effective implementation of ratified international human rights goes well beyond what this thesis terms the law+litigation approach (crucial though that is). By tracing developments historically, analysing the policy and governance issues, and using case studies this research shows that effective implementation is characterised by a new concept: 'complementarity'. This concept is about an increasing coherence between a number of factors affecting the state sector which impact on the fostering and delivery of human rights. These include international and domestic dimensions, law and public policy, public fairness, administrative pragmatism, and proactive and reactive approaches to implementation. Greater complementarity is shown to produce another term suggested in the thesis: robust human rights governance. The opposite - fragile human rights governance - is also explored. As well as the complementarity model, this research also suggests there are six phases in New Zealand's human rights history. It is argued that the sixth most robust stage has been reached, but that there are elements of previous stages that are weak, developing or non-existent. Leading on from this 20 criteria to assess what effectiveness 'looks like' in relation to robust human rights governance are also developed. Although this is primarily a New Zealand study, the widespread adoption of human rights standards by many states inevitably means that the issues are relevant to other countries, even though there are always varying degrees of similarity-difference in constitutional background and developed or emerging human rights systems. This thesis shows the pathways, the mechanisms, the evolving frameworks and the approaches that would help to differentiate robust from fragile human rights governance. The tools in this research should therefore enable a more nuanced assessment of effectiveness in terms of robust human rights governance

Incorporating satellite data into weather index-based insurance

What: Twenty-three people from six countries came together to discuss how drought insurance based on remotely sensed data can reduce the impact of weather shocks on some of the poorest people in the world. Participants were drawn from financial and agricultural sectors, nongovernmental and governmental organizations, and universities. When: 16–17 February 2016. Where: Reading, United Kingdo

Capacity building on agricultural insurance for aggregators in Northern Ghana

Farming is a risky business. Shocks such as drought, flood, pests or disease can make it difficult for farmers to invest in new productive options, such as seeds or fertilizer. These shocks are often regional, reverberating past the level of the individual smallholder. This makes it equally difficult for aggregators such as seed companies, input providers, agri-shops, seed growers and for commercial farmers, all of whom rely on the yields of a large number of smallholders or out-growers. Agricultural insurance is one way to mitigate this risk, unlocking new markets and making existing markets more profitable Most training on insurance is either designed for poor smallholder farmers, or for very large aggregators (e.g. a country-wide fertilizer company). Less attention has been paid to small and medium level aggregators, who might have tens or hundreds of acres, or have a relationship with a smaller number of out growers (tens to thousands). However, connecting with these stakeholders is one method of scaling insurance in a sustainable fashion. The local nature of many of the aggregators allows insurance to reach smallholders without personally visiting every village. The aggregators are also typically from the local communities and can act as champions for new initiatives. These same incentives for connecting with aggregators also hold true for other CCAFS and rural development initiatives. The aim of this workshop was to reach a group of local aggregators in rural Ghana with tailored insurance capacity building material, detailed in this report. A secondary aim was to gather their feedback about their experiences with agricultural insurance, along with jointly designed ideas about how insurance could more easily fit in with their practices

Hierarchical Bayes models for daily rainfall time series at multiple locations from heterogenous data sources

We estimate a Hierarchical Bayesian models for daily rainfall that incorporates two novelties for estimating spatial and temporal correlations. We estimate the within site time series correlations for a particular rainfall site using multiple data sources at a given location, and we estimate the across site covariance in rainfall based on location distance. Previous rainfall models have captured cross site correlations as a functions of site specific distances, but not within site correlations across multiple data sources, and not both aspects simultaneously. Further, we incorporate information on the technology used (satellite versus rain gauge) in our estimations, which is also a novel addition. This methodology has far reaching applications in providing more accurate and complex weather insurance contracts based combining information from multiple data sources from a single site, a crucial improvement in the face of climate change. Secondly, the modeling extends to many other data contexts where multiple datasources exist for a given event or variable where both within and between series covariances can be estimated over time

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII

Weather-index based crop insurance as a social adaptation to climate change and variability in the Upper West Region of Ghana: Developing a participatory approach

Climate change and variability are major challenges to rain-fed crop production in Africa. This paper presents a report on a pilot project to test a concept for operationalizing weatherindex crop insurance as a social adaptation to the climate change and variability problem in the Upper West Region of Ghana. An analysis of long-term weather variables showed rising temperature of 1.7 oC over a period of 53 years as well as major shifts in rainfall patterns. Farmers face a new reality that cannot be addressed with their indigenous knowledge alone. The weather-index based crop insurance concept discussed herein was developed by combined effort of University of Ghana, the German International Cooperation (GIZ) and the Ghana National Insurance Commission (NIC) since 2010. This development was carried out via their filial, the Ghana Agricultural Insurance Pool (GAIP). The proposed concept sought to link various agricultural stakeholders such weather technical persons, farmers, agricultural extension officer, input dealers and other aggregators, and financial institutions as well as the insurance industry and focused on a participatory farmer led approach. The piloting of the concept was supported by the Climate Change and Food Security (CCAFs) project and was tested in the years 2012 and 2013 using a theatrical drama sketch in two districts in the Upper West Region of Ghana: Jirapa and Lawra. It was observed that training of farmers in the basic principles of weather (data collection, interpretation, etc.) facilitated the discussions on drought insurance, adding to the body of evidence supporting participatory design tools. The aim of this paper is to record this process and to put the results into recent context, through discussing them through the lens of insurance operations and research in Ghana. Ensuing discussions showed that although all stakeholders considered the participatory design tools to be meritorious, a number of logistical challenges were identified that need to be addressed for effective scaling. The study also highlighted the high spatial variability of rainfall in the Upper West region of Ghana, showing the necessity of satellite-derived rainfall products. Finally, the framework suggested in this report highlights the complexity and the institutional structures required to implement an effective insurance. In effect, our simple study has exposed the complexities and intricacies that must be overcome in establishing a sustainable insurance scheme in Ghana

The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere