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

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

A discursive review of the textual use of ‘trapped’ in environmental migration studies: The conceptual birth and troubled teenage years of trapped populations

First mooted in 2011, the concept of Trapped Populations referring to people unable to move from environmentally high-risk areas broadened the study of human responses to environmental change. While a seemingly straightforward concept, the underlying discourses around the reasons for being ‘trapped’, and the language describing the concept have profound influences on the way in which policy and practice approaches the needs of populations at risk from environmental stresses and shocks. In this article, we apply a Critical Discourse Analysis to the academic literature on the subject to reveal some of the assumptions implicit within discussing ‘trapped’ populations. The analysis reveals a dominant school of thought that assisted migration, relocation, and resettlement in the face of climate change are potentially effective adaptation strategies along a gradient of migrant agency and governance

Forbush Decreases and Antarctic cloud anomalies in the upper troposphere

We demonstrate evidence that past composite based studies centred around the onset of Forbush decrease (FD) events may have improperly isolated the maximal galactic cosmic ray (GCR) decrease associated with the FD events. After an adjustment of the composite to account for such shortcomings we find indications of anomalous cloud cover decreases (of around 3%) located in the upper levels of the troposphere at high southern latitudes. These cloud changes are detectable after latitudinal averaging, suggesting the possibility of a second order relationship between the rate of GCR flux and cloud cover in this region. The maximal cloud change is observed in advance of the maximal GCR decrease; this implies that if the observed cloud changes bear a causal relationship to the rate of GCR flux, then cloud properties may be sensitive to changes in GCR conditions rather than the maximal deviations themselves

African Climate and Climate Change: Physical, Social and Political Perspectives

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Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa

The net effect of ultraviolet radiation on atmospheric dimethylsulphide over the Southern Indian Ocean

Dimethylsulphide (DMS) in the atmosphere may play an important role in the climate system. This study shows an inverse relationship between ultraviolet extremes and atmospheric DMS, independent of changes in wind speed, sea–surface temperature and photosynthetically active radiation, as measured at Amsterdam Island in the Southern Indian Ocean

The first WetNet precipitation intercomparison project: generation of results

The first WetNet Precipitation Intercomparison Project (PIP‐1) was the first major intercomparative study of global monthly precipitation retrieval techniques based on satellite imagery. As primary products, monthly estimates of rainfall were submitted to the project based on SSM/I satellite passive microwave image data, passive microwave sounding data and infrared data. Rainfall totals were also produced from numerical weather prediction model estimates and surface rain gauges. Instantaneous rain rate retrievals were also analysed in the study along selected latitudes and longitudes. Secondary products were generated from these results in order to more fully display, intercompare and validate various techniques of rainfall retrieval. Examples of both primary and secondary products are presented in this paper. Among the results submitted there was a large variation in coverage. In some data sets, rainfall retrievals were restricted to over ocean surfaces; in others coastal zones, high latitudes, ice and snow surfaces were flagged, and no estimation of precipitation made in some or all of these regions. The large number of products presented in this paper provide examples of the PIP‐1 analyses and allow the comparisons of data sets, withstanding the differences in coverage. This paper describes the process of generating results for this intercomparison project and some of the problems encountered in this exercise