Short- and long-term response of phytoplankton to ENSO in Prydz Bay,Antarctica: Evidences from field measurements,remote sensing data and stratigraphic biomarker records

The study provides one of the first lines of evidence showing linkages between Antarctic phytoplankton abundance and composition in response to ENSO, based on historical reconstruction of sediment biomarkers. In addition to sediment biomarkers, field measured and remote sensing data of phytoplankton abundance were also recorded from Prydz Bay, Eastern Antarctica. Com-munity structure of field measured phytoplankton showed significant El Ni？o/La Ni？a-related succession during 1990 to 2002. In general, the number of algae species decreased during El Ni？o and La Ni？a years compared to normal years. Austral summer monthly variation of remotely sensed chlorophyll-a （Chl-a）, particulate organic carbon （POC）, and sea surface temperature （SST） indicated that ENSO impacted the timing of phytoplankton blooms during 2007 to 2011. Phytoplankton blooms （indicated by Chl-a and POC） preceded the increases in SST during El Ni？o years, and lagged behind the SST increases during La Ni？a years. Stratigraphic record of marine sedimentary lipid （brassicasterol, dinosterol and alkenones） biomarkers inferred that the proportions of different algae （diatoms, dinoflagellates and haptophytes） changed significantly between El Ni？o and La Ni？a events. The relative proportion of diatoms increased, with that of dinoflagellates being decreased during El Ni？o years, while it was reversed during La Ni？a years.     

A georeferenced agent-based model to analyze the climate change impacts on ski tourism at a regional scale

One main argument for modeling socio-ecological systems is to advance the understanding of dynamic correlations between various human and environmental factors, including impacts and responses to environmental change. We explore the shift in skier distribution among ski resorts taking into account the behavioral adaptation of individuals due to the impact of climate change on snow conditions. This analysis is performed at a regional scale by means of a coupled gravity and georeferenced agent-based model. Four different scenarios are considered. Two scenarios assume an increase of winter mean temperature of +2°C and +4°C, respectively, taking into account only natural snow conditions. Two additional scenarios add the effect of snowmaking to enhance the natural snow depth and extend the skiing season in the +2°C and +4°C base scenarios. Results show differing vulnerability levels, allowing the classification of ski resorts into three distinct groups: (1) highly vulnerable ski resorts with a strong reduction in visitors attendance for all climate change scenarios, characterized by unfavorable geographical and attractiveness conditions, making it difficult to ensure snow availability in the future; (2) low vulnerability ski resorts, with moderate reduction in season length during a high climate change scenario but no reduction (or even an increase) in a low one, characterized by ski resorts with a medium capacity and attractiveness to ensure enough snow conditions and capture skiers from other ski resorts; and (3) resilient ski resorts, with good conditions to ensure future snow-reliable seasons and outstanding attractiveness, allowing them to offer longer ski seasons than their competitors and potentially attracting skiers from other closed or marginal resorts. Ski resorts included in this last group increase their skier attendance in all climate change scenarios. Although similar studies in the literature foretell a significant reduction of the ski market in the near future, another probable effect outlined in this study is a redefinition of this market due to a redistribution of skiers, from vulnerable ski resorts to more resilient ones.     

Propagation of vertical and horizontal source data errors into a TIN with linear interpolation

Digital elevation models (DEMs) have been widely used for a range of applications and form the basis of many GIS-related tasks. An essential aspect of a DEM is its accuracy, which depends on a variety of factors, such as source data quality, interpolation methods, data sampling density and the surface topographical characteristics. In recent years, point measurements acquired directly from land surveying such as differential global positioning system and light detection and ranging have become increasingly popular. These topographical data points can be used as the source data for the creation of DEMs at a local or regional scale. The errors in point measurements can be estimated in some cases. The focus of this article is on how the errors in the source data propagate into DEMs. The interpolation method considered is a triangulated irregular network (TIN) with linear interpolation. Both horizontal and vertical errors in source data points are considered in this study. An analytical method is derived for the error propagation into any particular point of interest within a TIN model. The solution is validated using Monte Carlo simulations and survey data obtained from a terrestrial laser scanner.     

REDD+ readiness process in Cameroon: an analysis of multi-stakeholder perspectives

Cameroon has been a keen participant in Reducing Emissions from Deforestation and Forest Degradation plus conservation, sustainable management of forests and enhancement of carbon stocks (REDD+) negotiations since 2005 and has engaged in activities to enhance the implementation of REDD+. This article reviews progress on REDD+ readiness in Cameroon based on a multiple REDD+ functions framework. Results show that some progress has been made in terms of planning and coordination, institutional development, and the development of some REDD+ projects. Absence of a legal framework, inadequate procedures for stakeholder participation, slow progress in the development of a national strategy, monitoring, reporting, and verification (MRV) challenges, and weak financing remain prominent constraints. Despite having one of the slowest REDD Readiness Preparation Proposal (R-PP) processes in the Congo Basin, stakeholders feel strong ownership because the R-PP was done almost entirely by Cameroonian experts. Some opportunities for improving REDD+ can be considered going forward, including the establishment of procedures for a broader participatory process, speeding up the operationalization of the National Observatory on Climate Change, making use of the ongoing forestry law reform, consideration of a carbon concessions concept, tapping from international initiatives to build on MRV, and improving benefit sharing and financing through the development of an appropriate and decentralized mechanism. Enhancing these opportunities is fundamental for successful REDD+ implementation in Cameroon.

Policy relevance

This article offers a new multidimensional approach to assessing the REDD+ readiness process in Cameroon. This critical assessment, which is done using six key functions, provides an opportunity for enhanced understanding of the process by policy makers, decision makers, and professionals with a view to enabling improvements in the readiness process. Furthermore, the article proffers a series of opportunities that the government and other relevant stakeholders can capitalize on to overcome current hurdles affecting the REDD+ readiness process. It is hoped that policy makers driving the REDD+ process in Cameroon will be able to incorporate the findings of this research into their strategic policy, formulated to advance the REDD+ readiness process. More importantly, it is hoped that the multidimensional framework applied in this study could be useful for assessing REDD+ in similar contexts in the Congo Basin.     

Public perceptions of rainfall change in India

People’s perceptions of changes in local weather patterns are an important precursor to proactive adaptation to climate change. In this paper, we consider public perceptions of changes in average rainfall in India, analyzing the relationship between perceptions and the instrumental record. Using data from a national sample survey, we find that local instrumental records of precipitation are a strong predictor of perceived declines in rainfall. Perceptions of decreasing rainfall were also associated with perceptions of changes in extreme weather events, such as decreasing frequency of floods and severe storms, increasing frequency of droughts, and decreasing predictability of the monsoon. Higher social vulnerability—including low perceived adaptive capacity and greater food and livelihood dependence on local weather—was also associated with perceptions of decreasing rainfall. While both urban and rural respondents were likely to perceive local changes in precipitation, we show that rural respondents in general were more sensitive to actual changes in precipitation. Individual perceptions of changes in local climate may play an important role in shaping vulnerability to global climate change, adaptive behavior, and support for adaptation and mitigation policies. Awareness of local climate change is therefore particularly important in regions where much of the population is highly exposed and sensitive to the impacts of climate change.     

A Velocity Dealiasing Scheme for C-band Weather Radar Systems简

A dealiasing algorithm for radar radial velocity observed by C-band Doppler radars is presented as an extension of an existing S-band dealiasing algorithm. This has operational significance in that many portable and many commercial broadcast radars, as well as approximately one half of the Chinese weather radar network （CINRAD）, are C-band radars. With a wavelength of about 5 cm, the Nyquist interval of C-band radars is just about one half that of S-band radars （wavelength of about 10 cm） and thus has more velocity folding. The proposed algorithm includes seven modules to remove noisy data, find the starting radials, dealias velocities, and apply least squares error checking in both the radial and azimuth directions. The proposed velocity dealiasing method was applied to one widespread rain case and three strong convective cases from radars operating in China. It was found that, on average, 92.95% of the aliased radial velocity data could be correctly de-aliased by the algorithm, resulting in 96.65% of the data being valid.     

The meso-scale drivers of temperature extremes in high-latitude Fennoscandia

Extreme temperatures are key drivers controlling both biotic and abiotic processes, and may be strongly modified by topography and land cover. We modelled mean and extreme temperatures in northern Fennoscandia by combining digital elevation and land cover data with climate observations from northern Finland, Norway and Sweden. Multivariate partitioning technique was utilized to investigate the relative importance of environmental variables for the variation of the three temperature parameters: mean annual absolute minima and maxima, and mean annual temperature. Generalized additive modeling showed good performance, explaining 84–95 % of the temperature variation. The inclusion of remotely sensed variables improved significantly the modelling of thermal extremes in this system. The water cover variables and topography were the most important drivers of minimum temperatures, whereas elevation was the most important factor controlling maximum temperatures. The spatial variability of mean temperatures was clearly driven by geographical location and the effects of topography. Partitioning technique gave novel insights into temperature-environment relationship at the meso-scale and thus proved to be useful tool for the study of the extreme temperatures in the high-latitude setting.     

Atmospheric circulation as a factor for air temperatures in Bulgaria

The research period is 1950–2012, and includes data for air temperatures in 21 Bulgarian stations. Two circulation indices, covering the same period and showing west–east or south–north directions of transport of air masses, were calculated. Statistical methods were used in the study. The results show a significant positive trend in average annual air temperatures in almost the entire territory of Bulgaria with the exception of its eastern-northeastern part. The warming occurs mainly in March, June and July, with some stations having significant positive values also in January, May and August. The zonal index reveals an insignificant increase of western transport of air masses in the cold half of the year (October–April) and strengthening of the eastern transport in the rest of the year. The meridional index shows an increase of the northern transport of air masses over the entire year and this is particularly visible in March, June, August and September. Correlation coefficients indicate that atmospheric circulation has leading role in determination of air temperatures during the period from November to April. Western transport of air masses leads to higher temperatures in spring, autumn and winter and to lower temperatures in summer. The influence of ENSO on atmospheric circulation over Bulgaria is weak, with a time lag of 2 months. El Niño is associated with increased western and northern transport of air masses, while La Niña is associated with increased eastern and southern transport of air masses over southeastern Europe.     

What spatial scales are believable for climate model projections of sea surface temperature?

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.     

Diapycnal heat flux and mixed layer heat budget within the Atlantic Cold Tongue

Sea surface temperatures (SSTs) in the eastern tropical Atlantic are crucial for climate variability within the tropical belt. Despite this importance, state-of-the-art climate models show a large SST warm bias in this region. Knowledge about the seasonal mixed layer (ML) heat budget is a prerequisite for understanding SST mean state and its variability. Within this study all contributions to the seasonal ML heat budget are estimated at four locations within the Atlantic cold tongue (ACT) that are representative for the western (0°N, 23°W), central (0°N, 10°W) and eastern (0°N, 0°E) equatorial as well as the southern (10°S, 10°W) ACT. To estimate the contribution of the diapycnal heat flux due to turbulence an extensive data set of microstructure observations collected during ten research cruises between 2005 and 2012 is analyzed. The results for the equatorial ACT indicate that with the inclusion of the diapycnal heat flux the seasonal ML heat budget is balanced. Within the equatorial region, the diapycnal heat flux is essential for the development of the ACT. It dominates over all other cooling terms in the central and eastern equatorial ACT, while it is of similar size as the zonal advection in the western equatorial ACT. In contrast, the SST evolution in the southern ACT region can be explained entirely by air-sea heat fluxes.