Decreased frequency of North Atlantic polar lows associated with future climate warming

Every winter, the high-latitude oceans are struck by severe storms that are considerably smaller than the weather-dominating synoptic depressions1. Accompanied by strong winds and heavy precipitation, these often explosively developing mesoscale cyclones—termed polar lows1—constitute a threat to offshore activities such as shipping or oil and gas exploitation. Yet owing to their small scale, polar lows are poorly represented in the observational and global reanalysis data2 often used for climatological investigations of atmospheric features and cannot be assessed in coarse-resolution global simulations of possible future climates. Here we show that in a future anthropogenically warmed climate, the frequency of polar lows is projected to decline. We used a series of regional climate model simulations to downscale a set of global climate change scenarios3 from the Intergovernmental Panel of Climate Change. In this process, we first simulated the formation of polar low systems in the North Atlantic and then counted the individual cases. A previous study4 using NCEP/NCAR re-analysis data5 revealed that polar low frequency from 1948 to 2005 did not systematically change. Now, in projections for the end of the twenty-first century, we found a significantly lower number of polar lows and a northward shift of their mean genesis region in response to elevated atmospheric greenhouse gas concentration. This change can be related to changes in the North Atlantic sea surface temperature and mid-troposphere temperature; the latter is found to rise faster than the former so that the resulting stability is increased, hindering the formation or intensification of polar lows. Our results provide a rare example of a climate change effect in which a type of extreme weather is likely to decrease, rather than increase.

Simulating the impacts of global warming on wheat in China using a large area crop model

Temperature is one of the most prominent environmental factors that determine plant growth, devel- opment, and yield. Cool and moist conditions are most favorable for wheat. Wheat is likely to be highly vulnerable to further warming because currently the temperature is already close to or above optimum. In this study, the impacts of warming and extreme high temperature stress on wheat yield over China were investigated by using the general large area model (GLAM) for annual crops. The results showed that each 1±C rise in daily mean temperature would reduce the average wheat yield in China by about 4.6%{5.7% mainly due to the shorter growth duration, except for a small increase in yield at some grid cells. When the maximum temperature exceeded 30.5±C, the simulated grain-set fraction declined from 1 at 30.5±C to close to 0 at about 36±C. When the total grain-set was lower than the critical fractional grain-set (0.575{0.6), harvest index and potential grain yield were reduced. In order to reduce the negative impacts of warming, it is crucial to take serious actions to adapt to the climate change, for example, by shifting sowing date, adjusting crop distribution and structure, breeding heat-resistant varieties, and improving the monitoring, forecasting, and early warning of extreme climate events.

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions.

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.

Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convective-scale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.

Asynchronous flowering and within-plant flowering diversity in wheat and the implications for crop resilience to heat

Self-pollination dominates in wheat , with a small level of out-crossing due to flowering asynchrony and male sterility. However, the timing and synchrony of male and female flowering in wheat is a crucial determinant of seed set and may be an important factor affecting gene flow and resilience to climate change. Here, a methodology is presented for assessing the timing and synchrony of flowering in wheat. From the onset of flowering until the end of anthesis, the anther and stigma activity of each floret was assessed on the first five developing ears in potted plants grown under ambient conditions and originating from cv Paragon or cvs Spark-Rialto backgrounds. At harvest maturity, seed presence, size and weight was recorded for each floret scored. The synchrony between pollen dehiscence and stigma collapse within a flower was dependent on its relative position in a spike and within a floret. Determined on the basis of synchrony within each flower, the level of pollination by pollen originating from other flowers reached approximately 30% and did not change throughout the duration of flowering. A modelling exercise parameterised by flowering observations indicated that the temporal and spatial variability of anther activity within and between spikes may influence the relative resilience of wheat to sudden, extreme climatic events which has direct relevance to predicted future climate scenarios in the UK.

Dynamic simulation for closed loops in heating systems with decision-making support

Nowadays utilising the proper HVAC system is essential both in extreme weather conditions and dense buildings design. Hydraulic loops are the most common parts in all air conditioning systems. This article aims to investigate the performance of different hydraulic loop arrangements in variable flow systems. Technical, economic and environmental assessments have been considered in this process. A dynamic system simulation is generated to evaluate the system performance and an economic evaluation is conducted by whole life cost assessment. Moreover, environmental impacts have been studied by considering the whole life energy consumption, CO2 emission, the embodied energy and embodied CO2 of the system components. Finally, decision-making in choosing the most suitable hydraulic system among five well-known alternatives has been proposed.

Cloud bands over southern Africa: seasonality, contribution to rainfall variability, and modulation by the MJO

Tropical-extratropical cloud band systems over southern Africa, known as tropical temperate troughs (TTTs), are known to contribute substantially to South African summer rainfall. This study performs a comprehensive assessment of the seasonal cycle and rainfall contribution of TTTs by using a novel object-based strategy that explicitly tracks these systems for their full life cycle. The methodology incorporates a simple assignment of station rainfall data to each event, thereby creating a database containing detailed rainfall characteristics for each TTT. This is used to explore the importance of TTTs for rain days and climatological rainfall totals in October–March. Average contributions range from 30 to 60 % with substantial spatial heterogeneity observed. TTT rainfall contributions over the Highveld and eastern escarpment are lower than expected. A short analysis of TTT rainfall variability indicates TTTs provide substantial, but not dominant, intraseasonal and interannual variability in station rainfall totals. TTTs are however responsible for a high proportion of heavy rainfall days. Of 52 extreme rainfall events in the 1979–1999 period, 30 are associated with these tropical-extratropical interactions. Cut-off lows were included in the evolution of 6 of these TTTs. The study concludes with an analysis of the question: does the Madden-Julian Oscillation influence the intensity of TTT rainfall over South Africa? Results suggest a weak but significant suppression (enhancement) of intensity during phase 1(6).

Predicting the risks from climate change to forage and crop production for animal feed

Climate change is expected to bring warmer temperatures, changes to rainfall patterns, and increased frequency of extreme weather. Projections of climate impacts on feed crops show that there will likely be opportunities for increased productivity as well as considerable threats to crop productivity in different parts of the world over the next 20 to 50 years. On balance, we anticipate substantial risks to the volume, volatility, and quality of animal feed supply chains from climate change. Adaptation strategies and investment informed by high quality research at the interface of crop and animal science will be needed, both to respond to climate change and to meet the increasing demand for animal products expected over the coming decades.

A climate of control: flooding, displacement and planned resettlement in the Lower Zambezi River valley, Mozambique

In recent years, the potential role of planned, internal resettlement as a climate change adaptation measure has been highlighted by national governments and the international policy community. However, in many developing countries, resettlement is a deeply political process that often results in an unequal distribution of costs and benefits amongst relocated persons. This paper examines these tensions in Mozambique, drawing on a case study of flood-affected communities in the Lower Zambezi River valley. It takes a political ecology approach – focusing on discourses of human-environment interaction, as well as the power relationships that are supported by such discourses – to show how a dominant narrative of climate change-induced hazards for small-scale farmers is contributing to their involuntary resettlement to higher-altitude, less fertile areas of land. These forced relocations are buttressed by a series of wider economic and political interests in the Lower Zambezi River region, such dam construction for hydroelectric power generation and the extension of control over rural populations, from which resettled people derive little direct benefit. Rather than engaging with these challenging issues, most international donors present in the country accept the ‘inevitability’ of extreme weather impacts and view resettlement as an unfortunate and, in some cases, necessary step to increase people’s ‘resilience’, thus rationalising the top-down imposition of unpopular social policies. The findings add weight to the argument that a depoliticised interpretation of climate change can deflect attention away from underlying drivers of vulnerability and poverty, as well as obscure the interests of governments that are intent on reordering poor and vulnerable populations.

Climate change scenarios for precipitation extremes in Portugal

Precipitation indices are commonly used as climate change indicators. Considering four Climate Variability and Predictability-recommended indices, this study assesses possible changes in their spatial patterns over Portugal under future climatic conditions. Precipitation data from the regional climate model Consortium for Small-Scale Modelling–Climate version of the Local Model (CCLM) ensemble simulations with ECHAM5/MPI-OM1 boundary conditions are used for this purpose. For recent–past, medians and probability density functions of the CCLM-based indices are validated against station-based and gridded observational dataset from ENSEMBLES-based (gridded daily precipitation data provided by the European Climate Assessment & Dataset project) indices. It is demonstrated that the model is able to realistically reproduce not only precipitation but also the corresponding extreme indices. Climate change projections for 2071–2100 (A1B and B1 SRES scenarios) reveal significant decreases in total precipitation, particularly in autumn over northwestern and southern Portugal, though changes exhibit distinct local and seasonal patterns and are typically stronger for A1B than for B1. The increase in winter precipitation over northeastern Portugal in A1B is the most important exception to the overall drying trend. Contributions of extreme precipitation events to total precipitation are also expected to increase, mainly in winter and spring over northeastern Portugal. Strong projected increases in the dry spell lengths in autumn and spring are also noteworthy, giving evidence for an extension of the dry season from summer to spring and autumn. Although no coupling analysis is undertaken, these changes are qualitatively related to modifications in the large-scale circulation over the Euro-Atlantic area, more specifically to shifts in the position of the Azores High and associated changes in the large-scale pressure gradient over the area.

Effects of spatial resolution in the simulation of daily and subdaily precipitation in the southwestern US

We evaluate the effects of spatial resolution on the ability of a regional climate model to reproduce observed extreme precipitation for a region in the Southwestern United States. A total of 73 National Climate Data Center observational sites spread throughout Arizona and New Mexico are compared with regional climate simulations at the spatial resolutions of 50 km and 10 km for a 31 year period from 1980 to 2010. We analyze mean, 3-hourly and 24-hourly extreme precipitation events using WRF regional model simulations driven by NCEP-2 reanalysis. The mean climatological spatial structure of precipitation in the Southwest is well represented by the 10 km resolution but missing in the coarse (50 km resolution) simulation. However, the fine grid has a larger positive bias in mean summer precipitation than the coarse-resolution grid. The large overestimation in the simulation is in part due to scale-dependent deficiencies in the Kain-Fritsch convective parameterization scheme that generate excessive precipitation and induce a slow eastward propagation of the moist convective summer systems in the high-resolution simulation. Despite this overestimation in the mean, the 10 km simulation captures individual extreme summer precipitation events better than the 50 km simulation. In winter, however, the two simulations appear to perform equally in simulating extremes.

Recent climatic trends and linkages to river discharge in Central Vietnam

In this study, change in rainfall, temperature and river discharge are analysed over the last three decades in Central Vietnam. Trends and rainfall indices are evaluated using non-parametric tests at different temporal levels. To overcome the sparse locally available network, the high resolution APHRODITE gridded dataset is used in addition to the existing rain gauges. Finally, existing linkages between discharge changes and trends in rainfall and temperature are explored. Results are indicative of an intensification of rainfall (+15%/decade), with more extreme and longer events. A significant increase in winter rainfall and a decrease in consecutive dry days provides strong evidence for a lengthening wet season in Central Vietnam. In addition, trends based on APHRODITE suggest a strong orographic signal in winter and annual trends. These results underline the local variability in the impacts of climatic change at the global scale. Consequently, it is important that change detection investigations are conducted at the local scale. A very weak signal is detected in the trend of minimum temperature (+0.2°C/decade). River discharge trends show an increase in mean discharge (31 to 35%/decade) over the last decades. Between 54 and 74% of this increase is explained by the increase in precipitation. The maximum discharge also responds significantly to precipitation changes leading to a lengthened wet season and an increase in extreme rainfall events. Such trends can be linked with a likely increase in floods in Central Vietnam, which is important for future adaptation planning and management and flood preparedness in the region. Copyright © 2012 John Wiley & Sons, Ltd.

Reducing inconsistencies in point observations of maximum flood inundation level

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

Atmospheric electric fields during the Carrington flare

Karen Aplin and Giles Harrison examine international records of the 1859 Carrington flare and consider what they mean for our understanding of space weather today. Space weather is increasingly recognized as a hazard to modern societies, and one way to assess the extent of its possible impact is through analysis of historic space weather events. One such event was the massive solar storm of late August and early September 1859. This is now widely known as the “Carrington flare” or “Carrington event” after the visual solar emissions on 1 September first reported by the Victorian astronomer Richard Carrington from his observatory in Redhill, Surrey (Carrington 1859). The related aurorae and subsequent effects on telegraph networks are well documented (e.g. Clark 2007, Boteler 2006), but use of modern techniques, such as analysis of nitrates produced by solar protons in ice cores to retrospectively assess the nature of the solar flare, has proved problematic (Wolff et al. 2012). This means that there is still very little quantitative information about the flare beyond magnetic observations (e.g. Viljanen et al. 2014).