Climate — Open Access Journal

Rising temperature, drought and more-frequent extreme climatic events have been predicted for the next decades in many regions around the globe. In this framework, soil water availability plays a pivotal role in affecting vegetation productivity, especially in arid or semi-arid environments. However, direct measurements of soil moisture are scarce, and modeling estimations are still subject to biases. Further investigation on the effect of soil moisture on plant productivity is required. This study aims at analyzing spatio-temporal variations of a modified temperature vegetation wetness index (mTVWI), a proxy of soil moisture, and evaluating its effect on gross primary production (GPP) in forests. The study was carried out in Europe on 19 representative tree species during the 2000–2010 time period. Results outline a north–south gradient of mTVWI with minimum values (low soil water availability) in Southern Europe and maximum values (high soil water availability) in Northeastern Europe. A low soil water availability negatively affected GPP from 20 to 80%, as a function of site location, tree species, and weather conditions. Such a wetness index improves our understanding of water stress impacts, which is crucial for predicting the response of forest carbon cycling to drought and aridity. Full article

Most weather and climate models simulate circulations by numerically approximating a complex system of partial differential equations that describe fluid flow. These models also typically use one of a few standard methods to parameterize the effects of smaller-scale circulations such as convective plumes. This paper discusses the continued development of a radically different modeling approach. Rather than solving partial differential equations, the author’s Lagrangian models predict the motions of individual fluid parcels using ordinary differential equations. They also use a unique convective parameterization, in which the vertical positions of fluid parcels are rearranged to remove convective instability. Previously, a global atmospheric model and basin-scale ocean models were developed with this approach. In the present study, components of these models are combined to create a new global Lagrangian ocean model (GLOM), which will soon be coupled to a Lagrangian atmospheric model. The first simulations conducted with the GLOM examine the contribution of interior tracer mixing to ocean circulation, stratification, and water mass distributions, and they highlight several special model capabilities: (1) simulating ocean circulations without numerical diffusion of tracers; (2) modeling deep convective transports at low resolution; and (3) identifying the formation location of ocean water masses and water pathways. Full article

Crop yields are strongly dependent on the average climate, extreme temperatures, and carbon dioxide concentrations, all of which are projected to increase in the coming century. In this study, a statistical model was created to predict US yields to 2100 for three crops using low and high-emissions future scenarios (RCP 4.5 and 8.5). The model is based on linear regressions between historical crop yields and daily weather observations since 1970 for every county in the US. Yields were found to be most strongly dependent on heat waves, summer average temperatures, and killing degree days; these relationships were hence used to predict future yields. The model shows that warming temperatures will significantly decrease corn and soybean yields, but will not have as strong of an influence on rice. Before accounting for CO₂ fertilization, crops in the high-emissions scenario are predicted to produce 77%, 85%, and 96% of their expected yield without climate change for corn, soybeans, and rice, respectively. When a simple CO₂ fertilization factor is included, corn, a C4 plant, increases slightly, while the yields of the C3 plants (soybeans and rice) are actually predicted to increase compared to today’s yields. This study exhibits the wide range of possible impacts of climate change on crop yields in the coming century, and emphasizes the need for field research on the combined effects of CO₂ fertilization and heat extremes. Full article

Green infrastructure (GI) has increasingly gained popularity for achieving adaptation and mitigation goals associated with climate change and extreme weather events. To continue implementing GI, financial tools are needed for upfront project capital or development costs and later for maintenance. This study’s purpose is to evaluate financing tools used in a selected GI dataset and to assess how those tools are linked to various GI technologies and other GI project characteristics like cost and size. The dataset includes over 400 GI U.S. projects, comprising a convenience sample, from the American Society of Landscape Architects (ASLA). GI project characteristics were organized to answer a number of research questions using descriptive statistics. Results indicated that the number of projects and overall cost shares were mostly located in a few states. Grants were the most common financial tool with about two-thirds of the projects reporting information on financial tools receiving grant funding. Most projects reported financing from only one tool with a maximum of three tools. Projects primarily included multiple GI technologies averaging three and a maximum of nine. The most common GI technologies were bioswales, retention, rain gardens, and porous pavements. These findings are useful for decision-makers evaluating funding support for GI. Full article

This study is set out to understand the impact of El Niño Modoki and the Tropical Cyclone Potential Intensity (TCPI) in the North Indian Ocean. We also hypothesized and tested if the Indian Ocean Dipole (IOD) reveals a likely connection between the two phenomena. An advanced mathematical tool namely the Empirical Mode Decomposition (EMD) is employed for the analysis. A major advantage of using EMD is its adaptability approach to deal with the non-linear and non-stationary signals which are similar to the signals used in this study and are also common in both atmospheric and oceanic sciences. This study has identified IOD as a likely missing link to explain the connection between El Niño Modoki and TCPI. This lays the groundwork for future research into this connection and its possible applications in meteorology. Full article

Species distribution models have many applications in conservation and ecology, and climate data are frequently a key driver of these models. Often, correlative modeling approaches are developed with readily available climate data; however, the impacts of the choice of climate normals is rarely considered. Here, we produced species distribution models for five disparate species using four different modeling algorithms and compared results between two different, but overlapping, climate normals time periods. Although the correlation structure among climate predictors did not change between the time periods, model results were sensitive to both baseline climate period and model method, even with model parameters specifically tuned to a species. Each species and each model type had at least one difference in variable retention or relative ranking with the change in climate time period. Pairwise comparisons of spatial predictions were also different, ranging from a low of 1.6% for climate period differences to a high of 25% for algorithm differences. While uncertainty from model algorithm selection is recognized as an important source of uncertainty, the impact of climate period is not commonly assessed. These uncertainties may affect conservation decisions, especially when projecting to future climates, and should be evaluated during model development. Full article

An increasing focus of climate change studies is the projection of storm events characterized by heavy, very heavy, extreme, and/or intense precipitation. Projected changes in the spatiotemporal distributions of such intense precipitation events remain uncertain due to large measures of variability in both the definition and evidence of increased intensity in the upper percentile range of observed daily precipitation distributions, particularly on a regional basis. As a result, projecting changes in future precipitation at the upper tail of the distribution (i.e., the heavy to heaviest events), such as through the use of stochastic weather generator programs, remains challenging. One approach to address this challenge is to better define what constitutes intense precipitation events and the degree of location-specific adjustment needed for the weather generator programs to appropriately account for potential increases in precipitation intensity due to climate change. In this study, we synthesized information on categories of intense precipitation events and assessed reported trends in the categories at national and regional scales within the context of applying this information to stochastic weather generation. Investigations of adjusting weather generation models to include long-term regional trends in intense precipitation events are limited, and modeling trends in site-specific future precipitation distributions forecasted by weather generator programs remains challenging. Probability exceedance curves and variations between simulated and observed distributions can help in modeling and assessment of trends in future extreme precipitation events that reflect changes in precipitation intensity due to climate change. Full article

Long-term trend analysis at local scale for rainfall and temperature is critical for detecting climate change patterns. This study analysed historical (1980–2009), near future (2010–2039), mid- (1940–2069) and end-century (2070–2099) rainfall and temperature over Karamoja sub-region. The Modern Era-Retrospective Analysis for Research and Applications (MERRA) daily climate data provided by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) was used. The AgMIP delta method analysis protocol was used for an ensemble of 20 models under two representative concentration pathways (RCPs 4.5 and 8.5). Historical mean rainfall was 920.1 ± 118.9 mm and minimum, maximum and mean temperature were 16.8 ± 0.5 °C, 30.6 ± 0.4 °C and 32.0 ± 0.7 °C, respectively. Minimum temperature over the historical period significantly rose between 2000 and 2008. Near future rainfall varied by scenario with 1012.9 ± 146.3 mm and 997.5 ± 144.7 mm for RCP4.5 and RCP8.5 respectively; with a sharp rise predicted in 2017. In the mid-century, mean annual rainfall will be 1084.7 ± 137.4 mm and 1205.5 ± 164.9 mm under RCP4.5 and RCP8.5 respectively. The districts of Kaabong and Kotido are projected to experience low rainfall total under RCP4.5 (mid-century) and RCP8.5 (end-century). The minimum temperature is projected to increase by 1.8 °C (RCP4.5) and 2.1 °C (RCP8.5) in mid-century, and by 2.2 °C (RCP4.5) and 4.0 °C (RCP8.5) in end-century. Full article

Coastal communities and small-scale fisheries are highly vulnerable to climate change. In this study, we aimed to examine fishers’ decisions to adapt to climate change and their expectations for their children to pursue the same profession. Data were obtained from fisher households covering 8 districts and 22 sub-districts in the coastal area of Chumphon Province, Thailand, using participatory observation, focus group discussion, and in-person field surveys. A binary logistic regression model was used to determine factors influencing the fishers’ decisions and their expectations for their children to inherit their occupation. Results showed that the fishers are aware of the increasing trends in air temperature, sea water temperature, inland precipitation, offshore precipitation, and storms. Increased fishing experience and fishing income increased the likelihood of the fishers applying adaptations to climate change. Looking to the future, fishers with high fishing incomes expect their children to pursue the occupation, whereas increased fishing experience, non-fishing incomes, and perceptions of storms likely discourage them from expecting their children to be fishers. Of the fishers interviewed, 58.06% decided to apply adaptations in response to climate change by incorporating climate-smart agriculture, particularly by cultivating rubber, oil palm, and orchards as a second income source. The adoption of climate-smart fisheries should be considered in relation to the body of local knowledge, as well as the needs and priorities of the fisher community. To cope with the impacts of current and future climate change on coastal communities, the national focal point of adaptation should be climate change, and related governmental agencies should pay more attention to these key factors for adaptation. Full article

The wood rot decay of structures and buildings in Norway represents high costs. This paper reports the observed trends for the potential rot decay of Norwegian wood structures in the cities of Oslo and Bergen over the recent 55 years, calculated as the “wood rot climate index” developed by Scheffer, and compares the reports with previous reported values based on climate change modelling. The observed change in the wood rot climate index was close to the modelling result. Bergen is exposed directly to the westerly Atlantic winds and has among the highest rain amounts in Norway, whereas Oslo is shielded by the Scandinavian mountain chain and has much less rain. The change in the wood rot climate index since 1961 was about 20% in both cities, but the trend in the index (climate index change per year) was about 80% stronger in Bergen. The absolute index changes were largest in the summer; then spring (50 to 60% of the summer increase); and small, zero, or even negative (autumn in Oslo) in the remaining seasons. The relative changes were higher in the spring than summer and very high in Bergen in the winter from a low value. The change to positive index values in the spring and winter indicates temperature and humidity conditions favoring the growth of wood rot and, thus, extended the rot duration through the year. The expected increase in the future wood rot decay potential in Norway shows the need for increased focus on adaption measures to reduce the related damages and costs. Full article

The land surface temperature (LST) in arid regions is a primary controller of many ecological processes. Consequently, we have developed a framework for detection of LST change on a regional scale using data sets covering all deserts of southern California from the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite sensor. The Breaks for Additive Season and Trend (BFAST) methodology was applied to MODIS 1-km monthly LST data from the years 2000 to 2018 to estimate significant time series shifts (breakpoints) and gradual trends. Area-wide results showed five times more positive LST breakpoints (abrupt temperature warming events) than negative (surface cooling) breakpoints. Cross-correlations with high rainfall periods around Mojave dry lake playas, and comparison with timing of wildfire burns for breakpoint patterns, showed that abrupt shifts in LST had the strongest response to these controllers. We detected negative LST (abrupt cooling) breakpoints as consistently associated with the construction of new solar energy facilities. Over the majority of the study area, BFAST results showed warming LST trends between the years 2000 and 2018. The western-most margins of the study area showed consistent widespread warming trends, whereas the eastern portions of the Mojave and Lower Colorado Deserts showed a mix of positive and neutral LST trends. Long-term cooling LST trends were detected only in some of the largest dry lake formations in the Antelope Valley, Death Valley, and Bristol, Cadiz, and Danby playas. Full article

Since 1850, the rise in global mean surface temperatures (GMSTs) from increasing atmospheric concentrations of greenhouse gases (GHGs) has exhibited three ~30-year hiatus (surface cooling) episodes. The current hiatus is often thought to be generated by similar cooling episodes in Pacific or Atlantic ocean basins. However, GMSTs as well as reconstructed Atlantic and Pacific ocean basin surface temperatures show the presence of similar multidecadal components generated from a three-dimensional analysis of differential gravitational (tidal) forcing from the sun and moon. This paper hypothesizes that these episodes are all caused by external tidal forcing that generates alternating ~30-year zonal and meridional circulation regimes, which respectively increase and decrease GMSTs through tidal effects on sequestration (deep ocean heat storage) and energy redistribution. Hiatus episodes consequently coincide with meridional regimes. The current meridional regime affecting GMSTs is predicted to continue to the mid-2030s but have limited tendency to decrease GMSTs from sequestration because of continuing increases in radiative forcing from increasing atmospheric GHGs. The tidal formulation also generates bidecadal oscillations, which may generate shorter ~12-year hiatus periods in global and ocean basin temperatures. The formulation appears to assimilate findings from disciplines as disparate as geophysics and biology. Full article

Strong cold surge events (CSEs) are some of the most distinct winter weather events in East Asia, impacting natural ecosystems and over 100 million individuals. The impact of such extreme CSEs as driven by synoptic systems is direct and immediate. Changes in large-scale synoptic patterns as potentially affected by changes in the Arctic are further expected to influence CSE occurrences in East Asia. Defying a straightforward analysis, semi-permanent atmospheric systems such as the Siberian High (SH), influencing large-scale synoptic patterns, make the atmospheric circulation highly variable and assessment of CSE onset difficult. Rather varied region-specific metrics are currently adopted for predicting CSE occurrence locally but the fundamental understanding of the onset of CSEs continues to be a major challenge. Based on an analysis of monthly synoptic patterns for three unusual CSEs in East Asia and further extended for eight strong to extreme CSEs, we propose a new coupling framework for an improved understanding and interpretation of the atmosphere dynamics driving CSE onset. The coupling framework involves linkages between the Siberian High, Aleutian Low, and Jet Stream. We also present the first meteorological scale for categorizing the intensity of such unusual CSEs. Full article

Climate change incorporation in environmental assessment is a growing research area, particularly following the Paris agreement. Environmental Impact Assessment (EIA) is considered in many quarters to be an important tool in factoring climate-related components in the planning and design of a project. However, many recent researches have shown that EIA has, so far, struggled in the attempt to incorporate climate change into its procedures. This study is an attempt to evaluate the level of consideration of climate change in the EIA process in Nigeria, with particular focus on the Niger Delta region. The result of this quantitative research shows that there is a poor political will to address climate change, as reflected in the absence of climate change requirements in the EIA guidelines of Nigeria. Although, there is a growing trend in the pattern of consideration of climate change in the EIA procedures, the overall level of consideration is still a far cry from the requirements if EIA is to be considered to be an important tool in addressing challenges of climate change in Nigeria. Full article

Heating is responsible for a substantial share of global energy consumption and still relies strongly on fossil fuels. In order to reduce energy consumption for heating, subsidies for building renovations are a common policy measure in Europe. Policy makers often combine them with information and advice measures. Policy mixes of this kind have been acknowledged widely in the literature, but their effectiveness needs further empirical examination. Based on a survey of the recipients of renovation subsidies and on four focus groups, we examine the (cost) effectiveness of subsidies, as follows: The effectiveness of renovation subsidies was measured by the extent to which receiving subsidies contributed either to the decision to renovate at all, or to the decision to enhance the quality or scope of the renovation. Fifty percent of the recipients surveyed reported that the subsidies contributed to a more energy-efficient renovation than was initially intended. The other fifty percent must be considered as free riders. Multivariate analyses further show that homeowners who used advice services and attributed outstandingly positive characteristics to the policy implementer were more likely to spend subsidies to improve energy efficiency. The findings demonstrate the importance of applying a combination of financial and persuasive policy measures. Additionally, they illustrate the importance of non-financial and non-technical factors, such as the communication competencies of the implementer, when designing policy measures. Full article

We qualitatively and quantitatively assessed the factors related to vegetation growth using Earth system models and corroborated the results with historical climate observations. The Earth system models showed a systematic greening by the late 21st century, including increases of up to 100% in Gross Primary Production (GPP) and 60% in Leaf Area Index (LAI). A subset of models revealed that the radiative effects of CO₂ largely control changes in climate, but that the CO₂ fertilization effect dominates the greening. The ensemble of Earth system model experiments revealed that the feedback of surface temperature contributed to 17% of GPP increase in temperature-limited regions, and radiation increase accounted for a 7% increase of GPP in radiation-limited areas. These effects are corroborated by historical observations. For example, observations confirm that cloud cover has decreased over most land areas in the last three decades, consistent with a CO₂-induced reduction in transpiration. Our results suggest that vegetation may thrive in the starkly different climate expected over the coming decades, but only if plants harvest the sort of hypothesized physiological benefits of higher CO₂ depicted by current Earth system models. Full article

Shelters used to protect air temperature sensors from solar radiation induce a measurement error. This work presents a semi-empirical model based on meteorological variables to evaluate this error. The model equation is based on the analytical solution of a simplified energy balance performed on a naturally ventilated shelter. Two main physical error causes are identified from this equation: one is due to the shelter response time and the other is due to its solar radiation sensitivity. A shelter intercomparison measurement campaign performed by the World Meteorological Organization (WMO) is used to perform a non-linear regression of the model coefficients. The regression coefficient values obtained for each shelter are found to be consistent with their expected physical behavior. They are then used to simply classify shelters according to their response time and radiation sensitivity characteristics. Finally, the ability of the model to estimate the temperature error within a given shelter is assessed and compared to the one of two existing models (proposed by Cheng and by Nakamura). For low-response-time shelters, our results reduce the root mean square error by about 15% (0.07 K) on average when compared with other compensation schemes. Full article

Arctic sea ice exhibits rapid reductions and large fluctuations during recent decades in conjunction with a warming climate. Arctic sea ice shows a prominent seasonal cycle with the maximum extent in spring and the minimum extent in fall. In this study a suite of modeling experiments, which were solely forced with observed time-varying sea-ice concentration for spring 1979 to 2008 was conducted using NCAR’s Community Atmosphere Model to identify sea ice impacts on extratropical storms and associated surface climate parameters when they at the peak of their seasonal variability. Storms are the linkage between the large-scale circulation changes, forced by Arctic sea ice and local extreme weather events through strong winds, high precipitation, and high/low air temperature. In this study, a storm identification and tracking algorithm indicates that reduced sea-ice cover enhances Arctic storm activity. As a consequence, surface climate parameters such as surface air temperature (SAT) and precipitation increases in spring over the Arctic. The changes in the Arctic have a direct and indirect effect on the extratropical storm activity over the mid-latitudes. In contrast to the Arctic, storm activity weakens over Eurasia in the years with less sea ice. Further analysis of the surface climate indicates a warmer and dryer Eurasia for years with reduced sea ice. Full article

The invasive species Erigeron karvinskianus or Mexican daisy is considered a significant weed that impacts native forest restoration efforts in New Zealand. Mapping the potential distribution of this species under current and future predicted climatic conditions provides managers with relevant information for developing appropriate management strategies. Using occurrences available from global and local databases, spatial distribution characteristics were analyzed using geostatistical tools in ArcMap to characterize current distribution. Species distribution modeling (SDM) using Maxent was conducted to determine the potential spatial distribution of E. karvinskianus worldwide and in New Zealand with projections into future climate conditions. Potential habitat suitability under future climatic conditions were simulated using greenhouse gas emission trajectories under the Representative Concentration Pathway (RCP) models RCP2.6, RCP4.5, RCP6.0 and RCP8.5 for years 2050 and 2070. Occurrence data were processed to minimize redundancy and spatial autocorrelation; non-correlated environmental variables were determined to minimize bias and ensure robust models. Kernel density, hotspot and cluster analysis of outliers show that populated areas of Auckland, Wellington and Christchurch have significantly greater concentrations of E. karvinskianus. Species distribution modeling results find an increase in the expansion of range with higher RCP values, and plots of centroids show a southward movement of predicted range for the species. Full article