Precipitation, cloud cover and Forbush decreases in galactic cosmic rays

The results of a study to explore variations in cloud cover, over regions that are minimally affected by rainfall and heavy rainfall, and that are coincident with variations in the galactic cosmic ray flux, are presented. Using an extensive record of global satellite derived cloud and rainfall products from the International Satellite Cloud Climatology Project (ISCCP) D1 data series and Xie and Arkin (1996), epoch superposition analysis of a sample of events of short term decreases in the galactic cosmic ray flux, is conducted. Analysis of data that is largely free from the influence of rainfall and heavy rainfall, averaged over 10-degree geomagnetic latitude (ϕ) bands reveals that cloud cover is reduced at high latitudes, and at middle and lower (including equatorial) latitudes over regions of relatively higher cloud cover, over both land and ocean surfaces, while increasing over ocean surfaces at middle and lower latitudes in regions of thinner cloud

On the relationship of cosmic ray flux and precipitation

This paper evaluates whether there is empirical evidence to support the hypothesis that solar variability is linked to the Earth's climate through the modulation of atmospheric precipitation processes. Using global data from 1979–1999, we find evidence of a statistically strong relationship between cosmic ray flux (CRF), precipitation (P) and precipitation efficiency (PE) over ocean surfaces at mid to high latitudes. Both P and PE are shown to vary by 7–9% during the solar cycle of the 1980s over the latitude band 45–90°S. Alternative explanations of the variation in these atmospheric parameters by changes in tropospheric aerosol content and ENSO show poorer statistical relationships with P and PE. Variations in P and PE potentially caused by changes in CRF have implications for the understanding of cloud and water vapour feedbacks

Embracing uncertainty: a discursive approach to understanding pathways for climate adaptation in Senegal

Climate change threatens to increase the frequency and intensity of droughts and floods. There are large uncertainties related to unknowns around the future and society’s responses to these threats. ‘Uncertainty’ as other words with the prefix ‘un’ (unknown, untold, unrest) often has negative connotations. Yet uncertainty is manifested in virtually everything we do. To many in science, uncertainty is akin to error that should be minimized, a lack of knowledge that needs to be rectified. We argue that uncertainty rather should be embraced as a starting point for discussing pathways to climate adaptation. Here we follow a definition of ‘pathways to adaptation’ as representing a set of proactive changes in the present that move people from a climatically unsafe place, to positions of safety (self defined as representing freedom from harm or adverse effect). This article applies an inter-discursive analytical approach where (un)certainty and (un)safety are used to deepen the understanding around the positions of people in Senegal, and their livelihoods, with respect to climate hazards. We examine the discursive socio-cultural values active in the climate adaptive space. Our findings show, that people’s adaptive decisions often were not based on climate information, but on discursive values and emotions that guided them in the direction of responses that felt right. We conclude that acknowledging different understandings and perceptions of uncertainty, and the goal of achieving safety, allows issues of power to be discussed. We contend that this process helps illuminate how to navigate pathways of adaptation to the impacts of climate variability and change

The devil is in the details: an investigation of the relationships between conflict, food price and climate across Africa

This study investigates the relationship between violent conflict, food price, and climate variability at the subnational level. Using disaggregated data on 113 African markets from January 1997 to April 2010, interrelationships between the three variables are analyzed in simultaneous equation models. We find that: (i) a positive feedback exists between food price and violence – higher food prices increase conflict rates within markets and conflict increases food prices; (ii) anomalously dry conditions are associated with increased frequencies of conflict; and (iii) decreased rainfall exerts an indirect effect on conflict through its impact on food prices. These findings suggest that the negative effects of climate variability on conflict can be mitigated by interventions and effective price management in local markets. Creating environments in which food prices are stable and reliable, and markets are accessible and safe, can lower the impacts of both climate change and conflict feedbacks

Who is the climate‐induced trapped figure?

Many will remember the 1990s alarmist narratives of how a human tide of up to a billion climate refugees would flood “our” borders by 2050. By 2011, a new character joined the discourse: the trapped figure. No longer would climatically vulnerable people be forced to move, they could also end up immobile. This review examines the narratives that surround the trapped figure. The article highlights the trapped figure's (i) characterisation, (ii) geography, and (iii) storytellers. The material includes the 2011 Foresight Report, 64 English peer-reviewed journal articles, and seven UNFCCC policy reports. The textual analysis furthers our understanding of the values that shape the meaning of the trapped figure within the wider discursive economy. Out of the 64 articles, 48 located the trapped figure in Asia, while 34 placed the figure in Africa. Meanwhile, the majority of articles—62 in total—were written by scholars based at European research institutes. The study shows that the trapped figure, much as the mythical climate refugee and migrant, is constructed as both a victim in need of rescuing and as an ambiguous security threat. It is ethically problematic that planned relocation was often put forward as an effective tool to “move” the figure out of harm's way. The review also found a range of binary opposites in the discourse on trapped populations, including those of order–disorder, freedom–unfreedom, and victim–savior. This suggests that however well-intentioned the liberal discourse on trapped populations appear, it remains embedded in power relations which demands for critical scrutiny. This article is categorized under: Social Status of Climate Change Knowledge > Sociology/Anthropology of Climate Knowledge Climate and Development > Sustainability and Human Well-Being Perceptions, Behavior, and Communication of Climate Change > Perceptions of Climate Change Climate, Nature, and Ethics > Ethics and Climate Chang

Playing the long game: anticipatory action based on seasonal forecasts

Acting in advance of floods, drought and cyclones often requires decision-makers to work with weather forecasts. The inherently probabilistic nature of these forecasts can be problematic when deciding whether to act or not. Cost-loss analysis has previously been employed to support forecast based decision-making such as Forecast-based Financing (FbF), providing insight to when an FbF system has ‘potential economic value’ relative to a no-forecast alternative. One well-known limitation of cost-loss analysis is the difficulty of estimating losses (which vary with hazard magnitude and extent, and with the dynamics of population vulnerability and exposure). A less-explored limitation is ignorance of the temporal dynamics (sequencing) of costs and losses. That is, even if the potential economic value of a forecast system is high, the stochastic nature of the atmosphere and the probabilistic nature of forecasts could conspire over the first few forecasts to increase the expense of using the system over the no-forecast alternative. Thus, for a forecast-based action system to demonstrate value, it often needs to be used over a prolonged length of time. However, knowing exactly how long it must be used to guarantee value is unquantified. This presents difficulties to institutions mandated to protect those at risk, who must justify the use of limited funds to act in advance of a potential, but not definite disaster, whilst planning multi-year strategies. Here we show how to determine the period over which decision makers must use forecasts in order to be confident of achieving ‘value’ over a no-forecast alternative. Results show that in the context of seasonal forecasting it is plausible that more than a decade may pass before a FbF system will have some certainty of showing value, and that if a particular user requires an almost-certain guarantee that using a forecast will be better than a no-forecast strategy, they must hold out until a near-perfect forecast system is available. The implication: there is potential value in seasonal forecasts, but to exploit it one must be prepared to play the long game

Playing the long game: anticipatory action based on seasonal forecasts

Acting in advance of floods, drought and cyclones often requires decision-makers to work with weather forecasts. The inherently probabilistic nature of these forecasts can be problematic when deciding whether to act or not. Cost-loss analysis has previously been employed to support forecast based decision-making such as Forecast-based Financing (FbF), providing insight to when an FbF system has ‘potential economic value’ relative to a no-forecast alternative. One well-known limitation of cost-loss analysis is the difficulty of estimating losses (which vary with hazard magnitude and extent, and with the dynamics of population vulnerability and exposure). A less-explored limitation is ignorance of the temporal dynamics (sequencing) of costs and losses. That is, even if the potential economic value of a forecast system is high, the stochastic nature of the atmosphere and the probabilistic nature of forecasts could conspire over the first few forecasts to increase the expense of using the system over the no-forecast alternative. Thus, for a forecast-based action system to demonstrate value, it often needs to be used over a prolonged length of time. However, knowing exactly how long it must be used to guarantee value is unquantified. This presents difficulties to institutions mandated to protect those at risk, who must justify the use of limited funds to act in advance of a potential, but not definite disaster, whilst planning multi-year strategies. Here we show how to determine the period over which decision makers must use forecasts in order to be confident of achieving ‘value’ over a no-forecast alternative. Results show that in the context of seasonal forecasting it is plausible that more than a decade may pass before a FbF system will have some certainty of showing value, and that if a particular user requires an almost-certain guarantee that using a forecast will be better than a no-forecast strategy, they must hold out until a near-perfect forecast system is available. The implication: there is potential value in seasonal forecasts, but to exploit it one must be prepared to play the long game

Short-term variability in satellite-derived cloud cover and galactic cosmic rays: an update

Previous work by Todd and Kniveton (2001) (TK2001) has indicated a statistically significant association (at the daily timescale) between short-term reductions in galactic cosmic rays, specifically Forbush decrease (FD) events, and reduced cloud cover, mainly over Antarctica (as recorded in International Satellite Cloud Climatology Project (ISCCP) D1 data). This study presents an extension of the previous work using an extended dataset of FD events and ISCCP cloud data over the period 1983-2000, to establish how stable the observed cloud anomalies are. Composite analysis of ISCCP data based on a sample of 32 FD events (excluding those coincident with solar proton events) indicates cloud anomalies with a very similar space/time structure to that previously reported, although of smaller magnitude. Substantial reductions in high level cloud (up to 12% for zonal mean, compared to 18% reported by TK2001) are observed over the high geomagnetic latitudes, especially of the southern hemisphere immediately following FD event onset. Largest anomalies are centred on the Antarctic plateau region during austral winter. However, the largest cloud anomalies occur where the accuracy of the ISCCP cloud retrievals is likely to be lowest, such that the results must be treated with extreme caution. Moreover, significant positive composite mean surface and tropospheric temperature anomalies centred over the same region are also observed for the FD sample from the National Center for Environmental Prediction (NCEP) reanalysis data. Such increased temperatures are inconsistent with the radiative effect of a reduction in high-level cloud during local winter. Overall, the results do not provide strong evidence of a direct galactic cosmic ray/cloud association at short timescales. The results highlight (a) the potential problems of data quality in the high latitude regions (b) the problems inherent in inferring cause and effect relationships from observational data alone (c) the need for further research to test competing hypotheses

Estimating rainfall and water balance over the Okavango River Basin for hydrological applications

A historical database for use in rainfall-runoff modeling of the Okavango River Basin in Southwest Africa is presented. The work has relevance for similar data-sparse regions. The parameters of main concern are rainfall and catchment water balance which are key variables for subsequent studies of the hydrological impacts of development and climate change. Rainfall estimates are based on a combination of in-situ gauges and satellite sources. Rain gauge measurements are most extensive from 1955 to 1972, after which they are drastically reduced due to the Angolan civil war. The sensitivity of the rainfall fields to spatial interpolation techniques and the density of gauges was evaluated. Satellite based rainfall estimates for the basin are developed for the period from 1991 onwards, based on the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave Imager (SSM/I) data sets. The consistency between the gauges and satellite estimates was considered. A methodology was developed to allow calibration of the rainfall-runoff hydrological model against rain gauge data from 1960-1972, with the prerequisite that the model should be driven by satellite derived rainfall products for the 1990s onwards. With the rain gauge data, addition of a single rainfall station (Longa) in regions where stations earlier were lacking was more important than the chosen interpolation method. Comparison of satellite and gauge rainfall outside the basin indicated that the satellite overestimates rainfall by 20%. A non-linear correction was derived used by fitting the rainfall frequency characteristics to those of the historical rainfall data. This satellite rainfall dataset was found satisfactory when using the Pitman rainfall-runoff model (Hughes et al., this issue). Intensive monitoring in the region is recommended to increase accuracy of the comprehensive satellite rainfall estimate calibration procedur