Climate, Volume 11, Issue 9 (September 2023) – 23 articles

This paper seeks to address Nigeria’s challenges in meeting its climate objectives by investigating feasible pathways that can be implemented to accelerate progress and ensure credibility in meeting these targets. By examining the current policies and practices in place as well as successful strategies employed by other countries, this paper aims to provide strategies and policy implications recommendations for Nigeria to enhance its climate action efforts. The potential scenarios developed in this study ranged from increasing renewable energy capacity to implementing stricter regulations and standards for industries to reduce their carbon footprint, promote sustainable production processes, and strengthen climate governance and policy frameworks. The authors further investigated these measures and discovered that implementing stricter regulations and standards for industries would reduce their carbon footprint, promote sustainable production processes, and strengthen climate governance and policy frameworks. As such, Nigeria will be able to meet its climate goals more quickly as a result of the following factors: preventing environmental degradation, funding environmentally friendly infrastructure, and improving public transportation systems that can reduce vehicle-related greenhouse gas emissions. The authors developed policy measures based on the proposed twelve credible pathways to catching up with climate goals in Nigeria, thereby promoting faster progress by the Nigerian government in achieving climate goals. By adopting these measures, Nigeria’s progress toward the proposed zero net by 2060 will be significantly accelerated. It will position Nigeria as a continental leader in sustainable development and contribute to the overall global efforts to mitigate climate change. This will not only benefit the environment but also lead to financial development and an improved standard of living for its citizens. Full article

The Antarctica and High Arctic regions are extreme environments, with average maximum temperatures below 0 °C for most days of the year. Interestingly, fungi inhabit these regions. This review describes the history of fungal surveys near the Syowa Station and the fungal diversity in this region. In the High Arctic region, I summarize the changes in the fungal communities of the glacial retreat areas of Ny-Ålesund, Norway and Ellesmere Island, Canada, in response to climate change. In addition, the ability of Antarctic and Arctic fungi to secrete enzymes at sub-zero temperatures is presented. Finally, the future directions of Antarctic and Arctic fungal research are provided. Full article

The nitrogen fertilization of boreal forests is investigated in terms of microeconomics as a tool for carbon sequestration. The effects of nitrogen fertilization’s timing on the return rate on capital and the expected value of the timber stock are investigated within a set of semi-fertile, spruce-dominated boreal stands using an inventory-based growth model. Early fertilization tends to shorten rotations, reducing timber stock and carbon storage. The same applies to fertilization after the second thinning. Fertilization applied ten years before stand maturity is profitable and increases the timber stock, but the latter effect is small. The fertilization of mature stands, extending any rotation by ten years, effectively increases the carbon stock. Profitability varies but is increased by fertilization instead of merely extending the rotation. Full article

Early meteorological observations have been found for the period 1788–1813 in a collection of historical documents entitled “Medical and meteorological observation books” (Livros de observações médicas e meteorológicas) that is preserved nowadays in the Municipal Historical Archive of Almada. Almada is a Portuguese city located on the southern bank of the Tagus River, near the mouth of the river, in front of the capital city of Lisbon, which is located on the northern bank. In this work, more than 5000 meteorological readings for the period 1788–1813 have been recovered and analyzed. Daily values have been preserved for the period 1788–1789. However, only monthly values have stood the test of time for the period 1792–1813. The meteorological variables recovered are temperature, pressure, wind direction and the state of the sky. A quality control was carried out to find possible errors, either in the original data or in the digitization process. Unfortunately, there is no information in the metadata about the instruments or the observational methodology. Pressure and temperature data from modern and reanalysis datasets were used as references to study the agreement between these datasets and the Almada dataset. Daily pressure and temperature values from the Almada dataset were used to study, in particular, the meteorological conditions of the winter of 1788/1789 in Almada because this season was one of the coldest in the last 300 years in Central Europe. The complete dataset of early meteorological observations in Almada is freely available to the scientific community. Full article

As nations fail to meet their climate emission mitigation goals, the ambition gap is widening between international climate policy (enacted by the United Nations) and domestic climate policy (what nations propose and enact). A widely held but little verified conventional wisdom exists that nations over-promise internationally and under-deliver domestically. While little data exist to directly test this hypothesis, we documented this gap by constructing heuristic indexes of domestic and international climate policy performance, showing that nations tend to “lead with the international”. We found that nations’ domestic policies are not significant in explaining emissions, although their international policies are significant. We concluded that beyond identifying this gap, analysts must devise metrics to assess domestic climate policy across a range of issue areas, as domestic policies are the foundation of any global effort to manage climate change. Full article

Much attention has been given to the change rule of a single extreme event, and there are few reports on comprehensive characteristics of multiple extreme events in a certain region. Based on the analyzes of annual frequency of extreme high temperature, extreme low temperature, extreme drought, extreme precipitation, and extreme typhoon events in China from 1961 to 2020, a multi extreme events composite risk grade index (MXCI) was constructed and applied to the comprehensive characteristics analyzes of multiple extreme events in China. The results show that the high value areas of MXCI were mainly located in southeast China and southwest China. Over the past 60 years, the MXCI has shown a decreasing trend in western China and most of southeastern China, and an increasing trend in the middle zone from southwest China to northeast China. Through comparative analysis, MXCI can objectively reflect the comprehensive characteristics of multiple extreme climate events in a region, which is helpful to understand regional extreme climate characteristics and effectively cope with extreme climate risks. Full article

Climate change (CC) has a significant impact on human health, resulting in both physical and mental illnesses. Eco-anxiety—the excessive and pervasive fear about the consequences of CC—is the most studied psychoterratic state. This study presents the validation of Italian versions of Hogg’s Eco-Anxiety Scale (HEAS) and the Eco-Paralysis Scale. It also investigates the effects of worry on eco-anxiety and eco-paralysis. The study was conducted on 150 Italian individuals who responded to the two scales and to other questionnaires to make comparisons with the two above. Internal consistency and factorial structure were assessed through Cronbach’s alpha, Confirmatory Factor Analysis and Exploratory Factor Analysis. A median regression was used to assess the association between the EPS and the HEAS and Climate Change Worry Scale (CCWS) and their interaction. HEAS and EPS showed good psychometric properties: HEAS resulted in good internal consistency (Cronbach’s α = 0.986), and the Eco-Paralysis scale had good test-retest reliability (r = 0.988). In both cases, a one-factor structure was suggested to be retained. The interaction terms between HEAS and CCWS (β = −0.02; 95% CI: −0.03, −0.01; p < 0.001) and between HEAS and education (β = −0.05; 95% CI: −0.08, −0.02; p < 0.001) were significant. Therefore, the feeling of worry seems to act as a moderator between climate change anxiety and eco-paralysis since it may appear to influence individuals and their ability to transform anxiety into action. Education plays a role in reducing the risk of Eco-Paralysis in subjects affected by climate change anxiety. Thus, data suggest that working on reinforcing a more cognitive concern might result in more problem-solving-focused strategies to face climate change anxiety and eco-paralysis. Full article

Effects associated with a changing climate could severely threaten potato production in Europe. Hence, farmers need to take up adaptation measures to safeguard agricultural production. Collecting data from 553 farmers from 22 different European countries, our survey evaluates European potato farmers’ perceptions regarding the influence of climate change on local potato production, and their willingness to implement adaptation strategies. An overwhelming majority of survey respondents had already experienced the effects of climatic changes on their potato production. Specifically, drought and heat were identified as the most significant threats. The planting of an adapted variety was the preferred adaptation strategy, while farmers were also willing to take up changes in agricultural management practices. Survey respondents predominantly considered yield stability as the most important characteristic of an adapted variety, closely followed by heat tolerance, disease resistance, drought tolerance, and yield potential. When choosing a variety, the personal experience of the survey respondents as well as the experience of their peers were identified as the most important sources of information. Our survey gives valuable insights into the challenges European potato farmers are facing in times of climate change. Supplying farmers with better-adapted varieties would be a well-targeted and well-accepted measure to advance climate change adaptation. Full article

This paper assessed existing EWS challenges and opportunities in cloud computing through the PSALSAR framework for systematic literature review and meta-analysis. The research used extant literature from Scopus and Web of Science, where a total of 2516 pieces of literature were extracted between 2004 and 2022, and through inclusion and exclusion criteria, the total was reduced to 98 for this systematic review. This review highlights the challenges and opportunities in transferring in-house early warning systems (that is, non-cloud) to the cloud computing infrastructure. The different techniques or approaches used in different kinds of EWSs to facilitate climate-related data processing and analytics were also highlighted. The findings indicate that very few EWSs (for example, flood, drought, etc.) utilize the cloud computing infrastructure. Many EWSs are not leveraging the capability of cloud computing but instead using online application systems that are not cloud-based. Secondly, a few EWSs have harnessed the computational techniques and tools available on a single platform for data processing. Thirdly, EWSs combine more than one fundamental tenet of the EWS framework to provide a holistic warning system. The findings suggest that reaching a global usage of climate-related EWS may be challenged if EWSs are not redesigned to fit the cloud computing service infrastructure. Full article

The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive to human society, inadvertently led to environmental rejuvenation, particularly noticeable in decreased air pollution and improved vegetation health. This study investigates the lockdown’s impact on vegetation health in Jharkhand, India, employing the Google Earth Engine for cloud-based data analysis. MODIS-NDVI data were analyzed using spatio-temporal NDVI analyses and time-series models. These analyses revealed a notable increase in maximum vegetation greenery of 19% from April 2019 to 2020, with subsequent increases of 13% and 3% observed in March and May of the same year, respectively. A longer-term analysis from 2000 to 2020 displayed an overall 16.7% rise in vegetation greenness. While the maximum value remained relatively constant, it demonstrated a slight increment during the dry season. The Landsat data Mann–Kendall trend test reinforced these findings, displaying a significant shift from a negative NDVI trend (1984–2019) to a positive 17.7% trend (1984–2021) in Jharkhand’s north-west region. The precipitation (using NASA power and Merra2 data) and NDVI correlation were also studied during the pre- and lockdown periods. Maximum precipitation (350–400 mm) was observed in June, while July typically experienced around 300 mm precipitation, covering nearly 85% of Jharkhand. Interestingly, August 2020 saw up to 550 mm precipitation, primarily in Jharkhand’s southern region, compared to 400 mm in the same month in 2019. Peak changes in NDVI value during this period ranged between 0.6–0.76 and 0.76–1, observed throughout the state. Although the decrease in air pollution led to improved vegetation health, these benefits began to diminish post-lockdown. This observation underscores the need for immediate attention and intervention from scientists and researchers. Understanding lockdown-induced environmental changes and their impact on vegetation health can facilitate the development of proactive environmental management strategies, paving the way towards a sustainable and resilient future. Full article

The advancements in global climate modeling achieved within the CMIP6 framework have led to notable enhancements in model performance, particularly with regard to spatial resolution. However, the persistent requirement for refined techniques, such as dynamically or statistically downscaled methods, remains evident, particularly in the context of precipitation variability. This study centered on the systematic application of a bias-correction technique (quantile mapping) to four designated CMIP6 models: CNRM-ESM2-6A, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0. The selection of these models was informed by a methodical approach grounded in previous research conducted within the southern–southeastern region of Mexico. Diverse performance evaluation metrics were employed, including root-mean-square difference (rmsd), normalized standard deviation (NSD), bias, and Pearson’s correlation (illustrated by Taylor diagrams). The study area was divided into two distinct domains: southern Mexico and the southeast region covering Tabasco and Chiapas, and the Yucatan Peninsula. The findings underscored the substantial improvement in model performance achieved through bias correction across the entire study area. The outcomes of rmsd and NSD not only exhibited variations among different climate models but also manifested sensitivity to the specific geographical region under examination. In the southern region, CNRM-ESM2-1 emerged as the most adept model following bias correction. In the southeastern domain, including only Tabasco and Chiapas, the optimal model was again CNRM-ESM2-1 after bias-correction. However, for the Yucatan Peninsula, the IPSL-CM6A-LR model yielded the most favorable results. This study emphasizes the significance of tailored bias-correction techniques in refining the performance of climate models and highlights the spatially nuanced responses of different models within the study area’s distinct geographical regions. Full article

The hailstorm of 30 August 2022 in the NE of Catalonia (NE of the Iberian Peninsula) produced the largest hail size, with diameters exceeding 10 cm. Furthermore, hail occurrence exceeded 2 cm in fourteen days and 4 cm in seven days during August 2022. The size and the days number constituted new records in Catalonia for at least the last 30 years. The analysis has compared the thermodynamic values derived from the sounding of Barcelona with the climatic data for 1998–2022 (25 years of data). This fact has allowed the selection and evaluation of different thermodynamic parameters’ behaviour during hail days in Catalonia. In this research, the precipitable water mass provided the best results as a hail forecaster. Second, the study has evaluated if the different parameters have a significant trend during the study period. The answer is yes in all cases, but some parameters presented a stepped rise while others increased smoothly. Finally, the research has analysed if the parameter values during August 2022 were extraordinary compared with the rest of the period. In this case, the thermodynamic parameters nature was well correlated with the hail size and occurrence maximums of August 2022. Full article

The interest in sustainability and energy efficiency is constantly increasing, and the noticeable effects of climate change and rising energy prices are fueling this development. The residential sector is one of the most energy-intensive sectors and plays an important role in shaping future energy consumption. In this context, modeling has been extensively employed to identify relative key drivers, and to evaluate the impact of different strategies to reduce energy consumption and emissions. This article presents a detailed literature review relative to modeling approaches and techniques in residential energy use, including case studies to assess and predict the energy consumption patterns of the sector. The purpose of this article is not only to review the research to date in this field, but to also identify the possible challenges and opportunities. Mobility, electrical devices, cooling and heating systems, and energy storage and energy production technologies will be the subject of the presented research. Furthermore, the energy upgrades of buildings, their energy classification, as well as the energy labels of the electric appliances will be discussed. Previous research provided valuable insights into the application of modeling techniques to address the complexities of residential energy consumption. This paper offers a thorough resource for researchers, stakeholders, and other parties interested in promoting sustainable energy practices. The information gathered can contribute to the development of effective strategies for reducing energy use, facilitating energy-efficient renovations, and helping to promote a greener and more sustainable future in the residential domain. Full article

This study assesses the perceptions and vulnerability of the farming communities to climate change in the southwestern parts of Ethiopia. Climate change vulnerability assessment is a prerequisite to designing climate change adaptation strategies. A multistage cluster sampling technique was used to select four of the six zones from the southwestern parts of Oromia. Close-ended and open-ended questionnaires were used to assess household perceptions of climate change and the degree of vulnerability to climate change by using five household capitals: natural, social, financial, physical, and human capital. Data were collected from 442 households in 4 districts: Jimma Arjo, Bako Tibe, Chewaka, and Sekoru. The vulnerability of the farming communities was assessed using the households’ livelihood vulnerability index. A total of forty indicators from five capitals were applied to calculate household livelihood vulnerability to climate change. Household perceptions of climate change had a statistically significant relationship with changes in rainfall pattern (75.6%, p < 0.001), temperature pattern (69.7%, p < 0.001), drought (41.6%, p = 0.016), flood (44.1%, p = 0.000), and occurrence of early (53.2%, p < 0.001) and late rain (55.9%, p < 0.001). The results show that households in the Sekoru district were the most vulnerable (0.61), while households in the Jimma Arjo district were less vulnerable (0.47) to the effect of climate change. Household vulnerability to climate change is mainly related to the occurrence of drought, lack of much-needed infrastructure facilities, and weak institutional support. Links with financial organizations are also lacking in the household. The findings of this study will help policymakers to address the impact of climate change. To support disaster risk management on the one hand and increase the resilience of vulnerable societies to climate change on the other, we recommend a detailed assessment of the remaining districts of the region. Full article

Rapid urbanization and climate change effects may cause dramatic changes in ecosystem functions in cities, thereby inevitably affecting the growth performance of old trees. Few studies have explored species diversity and spatial differentiation in Benin urban areas. This study aims to explore this dimension of urban ecology in order to build resilience to climate change in the city of Cotonou. Its objective was to determine the predominant level of tree diversity in the city’s land use units. The urban green frame was subdivided into six land use units, namely, establishments, residences, green spaces, commercial areas, administrative areas, and roads. The forest inventories were carried out in 149 plots with surfaces evaluated at 2500 m² each. The IVI, an index that highlights the relative density, relative dominance, and relative frequency of species, has been used to characterize the place occupied by each species in relation to all species in urban ecosystems. This shows ecological importance through the diversity and quality of ecosystems, communities, and species. A total of 62 tree species in 55 genera and 27 families were recorded. The results show that the flora of the city of Cotonou is characterized by a strong preponderance of exotic species with some differences in species presence. The most abundant species with high ecological importance (IVI) in the different types of land use of the city are Terminalia catappa (IVI = 121.47%), Terminalia mantaly (IVI = 90.50%), Mangifera indica (IVI = 64.06%), and Khaya senegalensis (IVI = 151.16%). As the use of ecosystem services is recommended to tackle urban climate hazards, this study shows that direct development of this urban vegetation could improve the resilience of urban life to climate hazards through the provision of urban ecosystem services, potential ecological infrastructure foundations, and urban nature-based solutions. Full article

More than 40 heat indices are being used across the world to quantify outdoor thermal comfort. The selection of an Outdoor Heat Stress Index (OHSI) depends on several parameters, including clothing, age, awareness, local environment, food consumption, human activities, and resources. This study investigates various indicators of heat stress, including (i) OHSIs officially used to quantify heat stress worldwide, (ii) the estimation methods of these indices, and (iii) the sensitivity analysis of indices, namely, Corrected Effective Temperature (CET), Heat Index (HI), Wet Bulb Globe Temperature (WBGT), Universal Thermal Climate Index (UTCI), Discomfort Index (DI), Summer Simmer Index (SSI), and Predicted Mean Vote (PMV). The results indicate the degree of sensitivity of indices, with the HI being the most sensitive for estimating heat stress. Additionally, the WBGT, HI, and CET are recommended indices that can be directly measured using sensors instead of relying on calculated indices that are based on estimation techniques and some ideal physical assumptions. Full article

In areas with a limited or non-existent network of observing stations, it is critical to assess the applicability of gridded datasets. This study examined the agreement of Agri4Cast and E-OBS at two spatial resolutions (10 km (EOBS-0.1) and 25 km (EOBS-0.25)) in 13 Mediterranean stations nearby to wheat crops and how this agreement may influence simulated potential development and production with the crop simulation model (CSM) CERES-Wheat in historical and near-future (2021–2040) (NF) periods. A wide range of sensitivity tests for maximum and minimum air temperatures and impact response surfaces were used for the future projections. EOBS-0.1 showed the lowest discrepancies over observations. It underestimated statistical measures of temperature and precipitation raw data and their corresponding extreme indices and overestimated solar radiation. These discrepancies caused small delays (5–6 days, on average) in crop development and overestimations (8%) in grain production in the reference period. In the NF, the use of EOBS-0.1 reduced by a few (2–3) days the biases in crop development, while yield responses differed among stations. This research demonstrated the ability of EOBS-0.1 for agricultural applications that depend on potential wheat development and productivity in historical and future climate conditions expected in the Mediterranean basin. Full article

A statistical analysis was applied to Northern Hemisphere land surface temperatures (1850–2018) to try to identify the main drivers of the observed warming since the mid-19th century. Two different temperature estimates were considered—a rural and urban blend (that matches almost exactly with most current estimates) and a rural-only estimate. The rural and urban blend indicates a long-term warming of 0.89 °C/century since 1850, while the rural-only indicates 0.55 °C/century. This contradicts a common assumption that current thermometer-based global temperature indices are relatively unaffected by urban warming biases. Three main climatic drivers were considered, following the approaches adopted by the Intergovernmental Panel on Climate Change (IPCC)’s recent 6th Assessment Report (AR6): two natural forcings (solar and volcanic) and the composite “all anthropogenic forcings combined” time series recommended by IPCC AR6. The volcanic time series was that recommended by IPCC AR6. Two alternative solar forcing datasets were contrasted. One was the Total Solar Irradiance (TSI) time series that was recommended by IPCC AR6. The other TSI time series was apparently overlooked by IPCC AR6. It was found that altering the temperature estimate and/or the choice of solar forcing dataset resulted in very different conclusions as to the primary drivers of the observed warming. Our analysis focused on the Northern Hemispheric land component of global surface temperatures since this is the most data-rich component. It reveals that important challenges remain for the broader detection and attribution problem of global warming: (1) urbanization bias remains a substantial problem for the global land temperature data; (2) it is still unclear which (if any) of the many TSI time series in the literature are accurate estimates of past TSI; (3) the scientific community is not yet in a position to confidently establish whether the warming since 1850 is mostly human-caused, mostly natural, or some combination. Suggestions for how these scientific challenges might be resolved are offered. Full article

A distinction is made between data rescue (i.e., copying, digitizing, and archiving) and data recovery that implies deciphering, interpreting, and transforming early instrumental readings and their metadata to obtain high-quality datasets in modern units. This requires a multidisciplinary approach that includes: palaeography and knowledge of Latin and other languages to read the handwritten logs and additional documents; history of science to interpret the original text, data, and metadata within the cultural frame of the 17th, 18th, and early 19th centuries; physics and technology to recognize bias of early instruments or calibrations, or to correct for observational bias; and astronomy to calculate and transform the original time in canonical hours that started from twilight. The liquid-in-glass thermometer was invented in 1641 and the earliest temperature records started in 1654. Since then, different types of thermometers have been invented, based on the thermal expansion of air or selected thermometric liquids with deviation from linearity. Reference points, thermometric scales, and calibration methodologies were not comparable, and not always adequately described. Thermometers had various locations and exposures, e.g., indoor, outdoor, on windows, gardens or roofs, facing different directions. Readings were made only one or a few times a day, not necessarily respecting a precise time schedule: this bias is analysed for the most popular combinations of reading times. The time was based on sundials and local Sun, but the hours were counted starting from twilight. In 1789–1790, Italy changed system and all cities counted hours from their lower culmination (i.e., local midnight), so that every city had its local time; in 1866, all the Italian cities followed the local time of Rome; in 1893, the whole of Italy adopted the present-day system, based on the Coordinated Universal Time and the time zones. In 1873, when the International Meteorological Committee (IMC) was founded, later transformed into the World Meteorological Organization (WMO), a standardization of instruments and observational protocols was established, and all data became fully comparable. In dealing with the early instrumental period, from 1654 to 1873, the comparison, correction, and homogenization of records is quite difficult, mainly because of the scarcity or even absence of metadata. This paper deals with this confused situation, discussing the main problems, but also the methodologies to recognize missing metadata, distinguish indoor from outdoor readings, correct and transform early datasets in unknown or arbitrary units into modern units, and, finally, in which cases it is possible to reach the quality level required by the WMO. The aim is to explain the methodology needed to recover early instrumental records, i.e., the operations that should be performed to decipher, interpret, correct, and transform the original raw data into a high-quality dataset of temperature, usable for climate studies. Full article

This study was motivated by the high reliance on hydropower plants (HPPs) developed and planned along the river Nile and the fact that drought events are the most imminent and drastic threats to Uganda’s power production. The study aimed to assess HPPs’ resilience and the effectiveness of selected adaptation measures. The climate, land, energy, and water system (CLEWs) framework was employed to assess resilience amidst competing water demands and stringent environmental flow requirements. Under extreme dry conditions, power generation could plummet by 91% over the next 40 years, which translates into an annual per capita consumption of 19 kWh, barely sufficient to sustain a decent socioeconomic livelihood. During arid conditions, climate models predicted an increase in streamflow with increasing radiative forcing. Restricting the ecological flow to 150 m³/s could improve generation by 207%. In addition, if planned power plants were to be built 5 years ahead of schedule, the normalized mean annual plant production could increase by 23%. In contrast, increasing reservoir volumes for planned power plants will have no significant impact on generation. The path to HPP resilience could entail a combination of diversifying the generation mix, installing generators with varying capacities, and incorporating adjustable orifices on reservoirs. Full article

This study aims to assess the changes in the atmospheric conditions favorable to storm surges over the Santos Coast in Southeast Brazil. Storm surges can favor high sea level rises and coastal erosion, affecting people and strategic structures in coastal areas. The assessment of the atmospheric conditions was based on the downscaling of climate simulations of the Brazilian Earth System Model by the Eta regional climate model at higher spatial resolution. The detection scheme used by the model was able to reproduce the three observed atmospheric patterns favorable to storm surges found by recent studies: Pattern 1 is characterized by a cyclone on the synoptic scale over the ocean; Pattern 2 presents an intense wind fetch from the southeast; Pattern 3 is characterized by winds parallel to the coast. The simulations underestimated the number of cases in Patterns 1 and 2. However, it overestimated the number of days in Pattern 3. The model presented more intense winds in the three patterns. The storm surges characterized by Pattern 1 will become more intense. However, it will be equal to or less frequent. In Pattern 2, the number of events will decrease. Nevertheless, these episodes will be associated with more precipitation along the coastline. Pattern 3 will have a similar number of storm surges. Full article

Bamboo, a rapidly growing woody grass prevalent in pan-tropical zones, holds promising potential as a nature-based solution (NbS) for climate change mitigation. In this systematic review of 91 research articles, we critically assess the scope and constraints of bamboo’s role in mitigating climate change across three dimensions: as a carbon sink in biomass form, as carbon storage in bamboo products, and as a contributor to carbon project credits. Our analysis reveals that existing studies disproportionately focus on 36 limited species, such as Phyllostachys pubescens and Bambusa vulgaris, with geographic concentration in Asia (91%) and limited studies from Africa (7%) and South America (1%). While many studies emphasize the carbon-saving benefits of bamboo products compared with traditional goods, there is a noticeable gap in comprehensive evaluations of carbon pools from individual bamboo forests encompassing all product varieties. While bamboo forests offer significant carbon trading potential, their global role is restricted by the absence of internationally accepted methodologies and the presence of debates about classifying bamboo as a tree species. This extensive review highlights the multifaceted value of bamboo in climate change mitigation, thereby highlighting its significance as a critical component for informed policymaking and the development of sustainable practices in future climate strategies worldwide. Full article

Cities around the world are facing the implications of a changing climate as an increasingly pressing issue. The negative effects of climate change are already being felt today. Therefore, adaptation to these changes is a mission that every city must master. Leading practices worldwide demonstrate various urban efforts on climate change adaptation (CCA) which are already underway. Above all, the integration of climate data, remote sensing, and in situ data is key to a successful and measurable adaptation strategy. Furthermore, these data can act as a timely decision support tool for municipalities to develop an adaptation strategy, decide which actions to prioritize, and gain the necessary buy-in from local policymakers. The implementation of agile data workflows can facilitate the integration of climate data into climate-resilient urban planning. Due to local specificities, (supra)national, regional, and municipal policies and (by) laws, as well as geographic and related climatic differences worldwide, there is no single path to climate-resilient urban planning. Agile data workflows can support interdepartmental collaboration and, therefore, need to be integrated into existing management processes and government structures. Agile management, which has its origins in software development, can be a way to break down traditional management practices, such as static waterfall models and sluggish stage-gate processes, and enable an increased level of flexibility and agility required when urgent. This paper presents the findings of an empirical case study conducted in cooperation with the City of Constance in southern Germany, which is pursuing a transdisciplinary and trans-sectoral co-development approach to make management processes more agile in the context of climate change adaptation. The aim is to present a possible way of integrating climate data into CCA planning by changing the management approach and implementing a toolbox for low-threshold access to climate data. The city administration, in collaboration with the University of Applied Sciences Constance, the Climate Service Center Germany (GERICS), and the University of Stuttgart, developed a co-creative and participatory project, CoKLIMAx, with the objective of integrating climate data into administrative processes in the form of a toolbox. One key element of CoKLIMAx is the involvement of the population, the city administration, and political decision-makers through targeted communication and regular feedback loops among all involved departments and stakeholder groups. Based on the results of a survey of 72 administrative staff members and a literature review on agile management in municipalities and city administrations, recommendations on a workflow and communication structure for cross-departmental strategies for resilient urban planning in the City of Constance were developed. Full article