Diurnal and seasonal cycles of cloud occurrences, types and radiative impact over West Africa

This study focuses on the occurrence and type of clouds observed in West Africa, a subject which has neither been much documented nor quantified. It takes advantage of data collected above Niamey in 2006 with the ARM mobile facility. A survey of cloud characteristics inferred from ground measurements is presented with a focus on their seasonal evolution and diurnal cycle. Four types of clouds are distinguished: high-level clouds, deep convective clouds, shallow convective clouds and mid-level clouds. A frequent occurrence of the latter clouds located at the top of the Saharan Air Layer is highlighted. High-level clouds are ubiquitous throughout the period whereas shallow convective clouds are mainly noticeable during the core of the monsoon. The diurnal cycle of each cloud category and its seasonal evolution is investigated. CloudSat and CALIPSO data are used in order to demonstrate that these four cloud types (in addition to stratocumulus clouds over the ocean) are not a particularity of the Niamey region and that mid-level clouds are present over the Sahara during most of the Monsoon season. Moreover, using complementary data sets, the radiative impact of each type of clouds at the surface level has been quantified in the shortwave and longwave domain. Mid-level clouds and anvil clouds have the largest impact respectively in longwave (about 15 W m−2) and the shortwave (about 150 W m−2). Furthermore, mid-level clouds exert a strong radiative forcing in Spring at a time when the other cloud types are less numerous.

Exploring social barriers to adaptation: insights from Western Nepal

As the challenges and opportunities posed by climate change become increasingly apparent, the need for facilitating successful adaptation and enhancing adaptive capacity within the context of sustainable development is clear. With adaptation high on the agenda, the notion of limits and barriers to adaptation has recently received much attention within both academic and policymaking spheres. While emerging literature has been quick to depict limits and barriers in terms of natural, financial, or technologic processes, there is a clear shortfall in acknowledging social barriers to adaptation. It is against such a backdrop that this paper sets out to expose and explore some of the underlying features of social barriers to adaptation, drawing on insights from two case studies in the Western Nepal. This paper exposes the significant role of cognitive, normative and institutional factors in both influencing and prescribing adaptation. It explores how restrictive social environments can limit adaptation actions and influence adaptive capacity at the local level, particularly for the marginalised and socially excluded. The findings suggest a need for greater recognition of the diversity and complexity of social barriers, strategic planning and incorporation at national and local levels, as well as an emphasis on tackling the underlying drivers of vulnerability and social exclusion.

Mediterranean agriculture under climate change: adaptive capacity, adaptation, and ethics

In the coming decades, the Mediterranean region is expected to experience various climate impacts with negative consequences on agricultural systems and which will cause uneven reductions in agricultural production. By and large, the impacts of climate change on Mediterranean agriculture will be heavier for southern areas of the region. This unbalanced distribution of negative impacts underscores the significance and role of ethics in such a context of analysis. Consequently, the aim of this article is to justify and develop an ethical approach to agricultural adaptation in the Mediterranean and to derive the consequent implications for adaptation policy in the region. In particular, we define an index of adaptive capacity for the agricultural systems of the Mediterranean region on whose basis it is possible to group its different sub-regions, and we provide an overview of the suitable adaptation actions and policies for the sub-regions identified. We then vindicate and put forward an ethical approach to agricultural adaptation, highlighting the implications for the Mediterranean region and the limitations of such an ethical framework. Finally, we emphasize the broader potential of ethics for agricultural adaptation policy.

Role of the atmosphere in the seasonal phase locking of El Nino

The variations with the seasonal cycle of the atmospheric response to constant SST anomalies in the eastern tropical Pacific are investigated with the atmospheric GCM, HadAM3. The equatorial wind response is weakest in January and February when the warmest SSTs are south of the Equator and strongest in April when the warmest SSTs are on the Equator. This may have consequences for the seasonality of the onset and termination of El Niño. Westerly wind anomalies in the tropical Pacific associated with El Niño have previously been observed to shift south of the Equator, weakening on the Equator, during the northern winter. It has been suggested that this may contribute to the termination of El Niño in spring. These experiments demonstrate that such a shift can arise solely in response to the mean seasonal cycle during El Niño and does not require changes in SST anomalies.

Forecasting annual inflation with seasonal monthly data: using levels versus logs of the underlying price index

This paper investigates whether using natural logarithms (logs) of price indices for forecasting inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation rates for a number of European countries and the USA based on monthly seasonal consumer price indices are considered. Stochastic seasonality and deterministic seasonality models are used. In many cases, the forecasts based on the original variables result in substantially smaller root mean squared errors than models based on logs. In turn, if forecasts based on logs are superior, the gains are typically small. This outcome sheds doubt on the common practice in the academic literature to forecast inflation rates based on differences of logs.

Occupants’ behavioural adaptation in workplaces with non-central heating and cooling systems

Occupants’ behaviour when improving the indoor environment plays a significant role in saving energy in buildings. Therefore the key step to reducing energy consumption and carbon emissions from buildings is to understand how occupants interact with the environment they are exposed to in terms of achieving thermal comfort and well-being; though such interaction is complex. This paper presents a dynamic process of occupant behaviours involving technological, personal and psychological adaptations in response to varied thermal conditions based on the data covering four seasons gathered from the field study in Chongqing, China. It demonstrates that occupants are active players in environmental control and their adaptive responses are driven strongly by ambient thermal stimuli and vary from season to season and from time to time, even on the same day. Positive, dynamic, behavioural adaptation will help save energy used in heating and cooling buildings. However, when environmental parameters cannot fully satisfy occupants’ requirements, negative behaviours could conflict with energy saving. The survey revealed that about 23% of windows are partly open for fresh air when air-conditioners are in operation in summer. This paper addresses the issues how the building and environmental systems should be designed, operated and managed in a way that meets the requirements of energy efficiency without compromising wellbeing and productivity.

Seasonal temperature variability of the Neoglacial (3300–2500 BP) and Roman Warm Period (2500–1600 BP) reconstructed from oxygen isotope ratios of limpet shells (Patella vulgata), Northwest Scotland

Seasonal sea-surface temperaturevariability for the Neoglacial (3300–2500 BP) and Roman WarmPeriod (RWP; 2500–1600 BP), which correspond to the Bronze and Iron Ages, respectively, was estimated using oxygen isotope ratios obtained from high-resolution samples micromilled from radiocarbon-dated, archaeological limpet (Patella vulgata) shells. The coldest winter months recorded in Neoglacial shells averaged 6.6 ± 0.3 °C, and the warmest summer months averaged 14.7 ± 0.4 °C. One Neoglacial shell captured a year without a summer, which may have resulted from a dust veil from a volcanic eruption in the Katla volcanic system in Iceland. RWP shells record average winter and summer monthly temperatures of 6.3 ± 0.1 °C and 13.3 ± 0.3 °C, respectively. These results capture a cooling transition from the Neoglacial to RWP, which is further supported by earlier studies of pine history in Scotland, pollen type analyses in northeast Scotland, and European glacial events. The cooling transition observed at the boundary between the Neoglacial and RWP in our study also agrees with the abrupt climate deterioration at 2800–2700 BP (also referred to as the Subboreal/Subatlantic transition) and therefore may have been driven by decreased solar radiation and weakened North Atlantic Oscillation conditions.

Agricultural adaptation to climate change: insights from a farming community in Sri Lanka

The vulnerability of smallholder farmers to climate change and variability is increasingly rising. As agriculture is the only source of income for most of them, agricultural adaptation with respect to climate change is vital for their sustenance and to ensure food security. In order to develop appropriate strategies and institutional responses, it is necessary to have a clear understanding of the farmers’ perception of climate change, actual adaptations at farm-level and what factors drive and constrain their decision to adapt. Thus, this study investigates the farm-level adaptation to climate change based on the case of a farming community in Sri Lanka. The findings revealed that farmers’ perceived the ongoing climate change based on their experiences. Majority of them adopted measures to address climate change and variability. These adaptation measures can be categorised into five groups, such as crop management, land management, irrigation management, income diversification, and rituals. The results showed that management of non-climatic factors was an important strategy to enhance farmers’ adaptation, particularly in a resource-constrained smallholder farming context. The results of regression analysis indicated that human cognition was an important determinant of climate change adaptation. Social networks were also found to significantly influence adaptation. The study also revealed that social barriers, such as cognitive and normative factors, are equally important as other economic barriers to adaptation. While formulating and implementing the adaptation strategies, this study underscored the importance of understanding socio-economic, cognitive and normative aspects of the local communities.

Long-distance dispersal and its influence on adaptation to host resistance in a heterogeneous landscape

Small propagules like pollen or fungal spores may be dispersed by the wind over distances of hundreds or thousands of kilometres,even though the median dispersal may be only a few metres. Such long-distance dispersal is a stochastic event which may be exceptionally important in shaping a population. It has been found repeatedly in field studies that subpopulations of wind-dispersed fungal pathogens virulent on cultivars with newly introduced, effective resistance genes are dominated by one or very few genotypes. The role of propagule dispersal distributions with distinct behaviour at long distances in generating this characteristic population structure was studied by computer simulation of dispersal of clonal organisms in a heterogeneous environment with fields of unselective and selective hosts. Power-law distributions generated founder events in which new, virulent genotypes rapidly colonized fields of resistant crop varieties and subsequently dominated the pathogen population on both selective and unselective varieties, in agreement with data on rust and powdery mildew fungi. An exponential dispersal function, with extremely rare dispersal over long distances, resulted in slower colonization of resistant varieties by virulent pathogens or even no colonization if the distance between susceptible source and resistant target fields was sufficiently large. The founder events resulting from long-distance dispersal were highly stochastic and exact quantitative prediction of genotype frequencies will therefore always be difficult.

Seasonal pattern of regional carbon balance in the central Rocky Mountains from surface and airborne measurements

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling.

High-resolution global climate simulations with the ECMWF model in Project Athena: experimental design, model climate, and seasonal forecast skill

The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena—an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models. In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden–Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena

A framework for agricultural adaptation to climate change in Southern Nigeria

The agricultural sector which contributes between 20-50% of gross domestic product in Africa and employs about 60% of the population is greatly affected by climate change impacts. Agricultural productivity and food prices are expected to rise due to this impact thereby worsening the food insecurity and poor nutritional health conditions in the continent. Incidentally, the capacity in the continent to adapt is very low. Addressing these challenges will therefore require a holistic and integrated adaptation framework hence this study. A total of 360 respondents selected through a multi-stage random sampling technique participated in the study that took place in Southern Nigeria from 2008-2011. Results showed that majority of respondents (84%) were aware that some climate change characteristics such as uncertainties at the onset of farming season, extreme weather events including flooding and droughts, pests, diseases, weed infestation, and land degradation have all been on the increase. The most significant effects of climate change that manifested in the area were declining soil fertility and weed infestation. Some of the adaptation strategies adopted by farmers include increased weeding, changing the timing of farm operations, and processing of crops to reduce post-harvest losses. Although majority of respondents were aware of government policies aimed at protecting the environment, most of them agreed that these policies were not being effectively implemented. A mutually inclusive framework comprising of both indigenous and modern techniques, processes, practices and technologies was then developed from the study in order to guide farmers in adapting to climate change effects/impacts.

Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation

Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.