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Environmental Research: Climate is a new open-access journal focused on the causes, consequences and solutions of climate variability and change. The field of climate research is at a critical juncture, driven by a broad and heterogeneous community that is seeking to respond to both the rapidly changing climate system and the rapidly evolving needs of society to manage climate-related risks. While there are already many journals publishing research in different areas of this broad field, Environmental Research: Climate aims to fill a unique role by convening the multidisciplinary communities working across the full scope of causes, consequences and solutions, in a fully Open Access publishing venue. The inaugural Editorial Board comprises a broad array of backgrounds, expertise and perspectives that span the physical, biogeochemical and human dimensions that shape climate and its impacts. The Editorial Board is committed to fair, ethical, transparent editorial practices, and the journal offers a suite of modern publishing features that will enhance the journal experience for authors, reviewers and readers. Through these practices and features, Environmental Research: Climate aims to provide the climate research community with a single publishing venue that is sufficiently broad, focused and open to deeply and comprehensively probe the causes, consequences and solutions of climate variability and change—and in doing so coalesce and catalyze the next era of climate research.

Climate simulations often need to be adjusted before carrying out impact studies at a regional scale. Technically, bias adjustment methods are generally calibrated over the last few decades, in order to benefit from a more comprehensive and accurate observational network. At these timescales, however, the climate state may be influenced by the low-frequency internal climate variability. There is therefore a risk of introducing a bias to the climate projections by bias-adjusting simulations with low-frequency variability in a different phase to that of the observations. In this study, we developed a new pseudo-reality framework using an ensemble of simulations from the IPSL-CM6A-LR climate model in order to assess the impact of the low-frequency internal climate variability of the North Atlantic sea surface temperatures on bias-adjusted projections of mean and extreme surface temperature over Europe. We show that using simulations in a similar phase of the Atlantic Multidecadal Variability reduces the pseudo-biases in temperature projections. Therefore, for models and regions where low frequency internal variability matters, it is recommended to sample relevant climate simulations to be bias adjusted in a model ensemble or alternatively to use a very long reference period when possible.

The El Niño-Southern Oscillation (ENSO) is a climate phenomenon that profoundly impacts weather patterns and extreme events worldwide. Here we develop a method based on a recurrent neural network, called echo state network (ESN), which can be trained efficiently to predict different ENSO indices despite their relatively high noise levels. To achieve this, we train the ESN model on the low-frequency variability of ENSO indices and estimate the potential future high-frequency variability from specific samples of its past history. Our method reveals the importance of cross-scale interactions in the mechanisms underlying ENSO and skilfully predicts its variability and especially El Niño events at lead times up to 21 months. This study considers forecasts skillful if the correlation coefficients are above 0.5. Our results show that the low-frequency component of ENSO carries substantial predictive power, which can be exploited by training our model on single scalar time series. The proposed machine learning method for data-driven modeling can be readily applied to other time series, e.g. finance and physiology. However, it should be noted that our approach cannot straightforwardly be turned into a real-time operational forecast because of the decomposition of the original time series into the slow and fast components using low-pass filter techniques.

In the context of ongoing climate change towards a warmer world, it is important to gain insights into the frequency and intensity of weather and climate extreme events over longer periods of time prior to the start of instrumental observations. Reconstructions of their variability are usually hampered by the rareness of natural archives for the pre-instrumental period that document climate variability at a sub-seasonal resolution. A potential archive for extreme events are annually banded reef corals which incorporate isotopic proxies of temperature and hydrology into their carbonate skeletons at sub-seasonal resolution, grow for centuries, and overlap with the observational period. Here, we investigate the relationship between the frequency of heavy precipitation days in southwestern Scandinavia and colder conditions in the northern Red Sea during winter, as documented by a coral oxygen isotope record from the northernmost area of tropical reef growth in the European sector of the Northern Hemisphere. Statistical analysis of observational data reveals that cold conditions in the northern Red Sea are associated with an increased frequency of heavy precipitation in southwestern Scandinavia. From a synoptic-scale perspective, this teleconnection can be explained by winter atmospheric blocking over mid-latitude Europe, which is a large-scale pattern of atmospheric pressure that can be active for several days or weeks. We show that increased winter blocking activity in the European region is related to an increased frequency of extreme moisture transport by atmospheric rivers affecting southwestern Scandinavia, as well as to an increased meridional advection of cold continental air from the north towards the subtropical northern Red Sea. The coral-based Scandinavian heavy precipitation reconstruction shows strong decadal variations during the pre-instrumental period. Our results provide insights into the frequency of winter atmospheric blocking events and related daily precipitation extremes in the European region, as well as into the impact of mid-latitude climate extremes on coral reef ecosystems in the northern Red Sea, during the last centuries.

Extreme event attribution aims to elucidate the link between global climate change, extreme weather events, and the harms experienced on the ground by people, property, and nature. It therefore allows the disentangling of different drivers of extreme weather from human-induced climate change and hence provides valuable information to adapt to climate change and to assess loss and damage. However, providing such assessments systematically is currently out of reach. This is due to limitations in attribution science, including the capacity for studying different types of events, as well as the geographical heterogeneity of both climate and impact data availability. Here, we review current knowledge of the influences of climate change on five different extreme weather hazards (extreme temperatures, heavy rainfall, drought, wildfire, tropical cyclones), the impacts of recent extreme weather events of each type, and thus the degree to which various impacts are attributable to climate change. For instance, heat extremes have increased in likelihood and intensity worldwide due to climate change, with tens of thousands of deaths directly attributable. This is likely a significant underestimate due to the limited availability of impact information in lower- and middle-income countries. Meanwhile, tropical cyclone rainfall and storm surge height have increased for individual events and across all basins. In the North Atlantic basin, climate change amplified the rainfall of events that, combined, caused half a trillion USD in damages. At the same time, severe droughts in many parts of the world are not attributable to climate change. To advance our understanding of present-day extreme weather impacts due to climate change developments on several levels are required. These include improving the recording of extreme weather impacts around the world, improving the coverage of attribution studies across different events and regions, and using attribution studies to explore the contributions of both climate and non-climate drivers of impacts.

This systematic review aims to appraise the quality of evidence on greenness co-benefits of climate change and health. Although there is evidence of the co-benefits of greenness on climate change and health, the research is of poor quality when it comes to addressing the connections and identifying mediators of greenness and climate change mitigation associations. The evaluation sought to identify areas where there was little or no evidence to guide future research. Current published studies mainly cover six health outcome categories (birth outcomes, physical activity, mental wellbeing, obesity, mortality, and cognitive function). For adaptation, greenness and climate change, associated studies included (a) cooling down effects and urban heat island impacts, (b) air quality improvement, and (c) flood mitigation. For each outcome, we performed a systematic search of publications on Web of Science, PubMed, Google Scholar, and Science Direct databases from 2000 to July 2021. After retrieving records in which full papers were assessed and non-English articles were excluded, a total of 173 articles, including research articles and reviews, were chosen. To ascertain the strength of the evidence, all interventions were assessed using the GRADE approach. The quality of evidence ranged from moderate to high for most categories of health outcomes (birth outcomes, mental wellbeing, mortality). GRADE assessment provided low-quality evidence for studies on air quality, flood mitigation, physical activity, and obesity due to poor study design (observational or limited data) and high heterogeneity (some data provided variability), and the review concluded that there is insufficient evidence on firm recommendations for public health interventions. Due to a huge amount of low-quality evidence and several areas of overlapping study, this evaluation recognized the co-benefits of greenness on climate change and health as an understudied field and hence as a research gap. The evidentiary foundation for greenness-climate change mitigation links was generally weak. Future research on climate change greenness co-benefit interventions should pay special attention to flood prevention, air quality interactions, and health effects including physical activity and obesity.

As the clean energy transition gathers momentum, it will face myriad technical, economic, and political challenges. However, one in particular is often underappreciated: the potential disruption to the transition from surging climate extremes. We identify three ways in which extreme events may impede the transition: direct physical impacts to transitional infrastructure, strained resources due to rising recovery costs, and political backlash from disaster-affected populations. If these pitfalls materialize, the transition could stall, leading to continued emissions, additional worsening of climate extremes, and further disruption of the transition. We propose three avenues to avoid this potential positive feedback: integration of adaptation and mitigation as mutually supportive goals, fostering political and cultural commitment to a sustained transition, and an interdisciplinary research and training agenda to improve modeling and preparedness for the cascading impacts of climate extremes

Evapotranspiration is an important cooling mechanism in urban green space (UGS). Irrigating vegetated surfaces with potable water, collected stormwater or recycled sewage water has the potential to increase the cooling effect of UGS by increasing evapotranspiration. Such cooling effect may not always be strong because evapotranspiration is dependent on local and regional factors such as background climate, seasonality and vegetation type. When using irrigation for cooling, city managers also need to consider management issues such as irrigation water supply and amenity use of the UGS. This study aims to develop a theoretical framework that explains the physical and energetic mechanisms of irrigation cooling effect and a framework to assist city managers to make decision about the use of irrigation for urban cooling. This is achieved by reviewing the impacts of irrigation on local climate reported in the literature and identifying the regional and local factors that influence irrigation cooling effect in warm seasons. The literature suggests that irrigation can potentially reduce daily maximum air temperature and ground surface temperature by approximately 2.5 °C and 4.9 °C, respectively, depending on weather conditions and irrigation amount. Background climate is an important factor that influences the cooling potentials of irrigation. Cities with dry and warm climates have the highest cooling potentials from irrigation. The cooling potentials are also influenced by seasonality and weather, vegetation type, irrigation time of day and irrigation amount. Cities with a dry and warm season can consider using irrigation to mitigate urban heat within UGS because such climatic conditions can increase cooling potentials. To maximise irrigation cooling effect, cities with abundant irrigation water supply can use a soil moisture-controlled irrigation regime while those with limited supply can use a temperature-controlled regime. More studies are required to understand the cooling potentials of irrigating small, individual UGS.

Understanding the dynamics of tropical cyclones (TCs) in terms of intensity, and their trajectory is essential for an adequate early warning and mitigation. The present study attempts to understand the synoptic features of the recent TC Ockhi through a simulation-based approach with the Weather Research and Forecasting (WRF, version 3.8.1) model. Ockhi is considered as a unique TC that originated from depression in the Bay of Bengal on 29 November 2017, recurved towards the Arabian Sea, where it intensified into a very severe cyclone storm and weakened on 5 December 2017. WRF model forced with initial condition from (global forecasting system) GFS data and sea surface temperature (SST) from Group for High-Resolution SST (GHRSST) product for different lead times to test the potential sensitivity of the model. One with an extended period from 20 November to 20 December 2017 (WRF1) and another initiated from 27 November to 6 December 2017 (WRF2). Comparison of the simulated track with the best track estimates from the Indian Meteorological Department indicated an overall track deviation greater than 100 km for both the simulations. The analysis with the extended lead time simulation indicates that the WRF simulated sea level pressure and wind intensity are close to that observed by Arabian sea buoys; CB02, AD08, AD10, and AD07. Daily averaged wind estimate comparison of WRF1 with Scatsat-1 and ERA-5 indicates that the model is slightly overestimating, whereas comparison of peak wind intensity with the time instantaneous swath product of Scatsat-1 leads to underestimation. Analysis of various simulated synoptic features of the cyclone, as discussed in this paper, indicates that the model is skillful in capturing the various stages of cyclone Ockhi.

Local climate narratives are influential, shaping climate responses at all scales. They can be unpredictable, however, reflecting local histories, power dynamics, needs, and priorities as much as expert knowledge of climate disruption and possible responses. As new modes of climate governance emerge in response to increasing climate impacts and risks, local climate narratives influence understandings of climate change and what should be done about it, as well as the prospects for implementing fair, effective climate responses. In this study, we examine the case of Miami-Dade County, Florida, USA, an early adopter of climate policies that faces deep inequity and worsening climate impacts. Using historical research, interviews, and policy document analysis, we (a) identify two long-term historic environmental narratives—one dominant narrative focused on economic growth and the other on environmental justice—that shape the local climate debate; (b) create a typology of contemporary climate narratives about emissions, sea level rise, climate gentrification, and resilience; and (c) analyze historic and contemporary narratives' prevalence in emergent local climate policies. While most people in Miami agree that climate change is an immediate problem, various groups talk about and experience climate change very differently. These climate narratives are divided along the geographical and social lines of segregation, leading to conflicting understandings of climate risk and action stemming from socioeconomic and environmental inequities. Histories of growth and the environmental injustices that accompany it have strongly shaped contemporary climate narratives, at times contradicting scientific understandings of climate change and, until recently, leading to climate policies that prioritize economic growth. Community organizations have drawn on histories of environmental injustice to demand greater attention to equity in narratives informing climate discussions, such as debates about climate gentrification, but we find that policy documents still cite equity-related topics and narratives much less frequently. Paying attention to these histories offers an important and often neglected basis for understanding local climate debates, the potential for climate governance to either compound or alleviate existing inequities, and new directions for more equitable climate communication and policy.

The City of Atlanta, Georgia, is a fast-growing urban area with substantial economic and racial inequalities, subject to the impacts of climate change and intensifying heat extremes. Here, we analyze the magnitude, distribution, and predictors of heat exposure across the City of Atlanta, within the boundaries of Fulton County. Additionally, we evaluate the extent to which identified heat exposure is addressed in Atlanta climate resilience governance. First, land surface temperature (LST) was mapped to identify the spatial patterns of heat exposure, and potential socioeconomic and biophysical predictors of heat exposure were assessed. Second, government and city planning documents and policies were analyzed to assess whether the identified heat exposure and risks are addressed in Atlanta climate resilience planning. The average LST of Atlanta's 305 block groups ranges from 23.7 °C (low heat exposure) in vegetated areas to 31.5 °C (high heat exposure) in developed areas across 13 summer days used to evaluate the spatial patterns of heat exposure (June–August, 2013–2019). In contrast to nationwide patterns, census block groups with larger historically marginalized populations (predominantly Black, less education, lower income) outside of Atlanta's urban core display weaker relationships with LST (slopes ≈ 0) and are among the cooler regions of the city. Climate governance analysis revealed that although there are few strategies for heat resilience in Atlanta (n = 12), the majority are focused on the city's warmest region, the urban core, characterized by the city's largest extent of impervious surface. These strategies prioritize protecting and expanding the city's urban tree canopy, which has kept most of Atlanta's marginalized communities under lower levels of outdoor heat exposure. Such a tree canopy can serve as an example of heat resilience for many cities across the United States and the globe.

Studies show anthropogenic aerosols (AAs) can perturb regional precipitation, including the tropical rain belt and monsoons of the Northern Hemisphere (NH). In the NH mid-latitudes, however, the impact of AAs on regional climate and precipitation remains uncertain. This work investigates the influence of AAs on wintertime precipitation along the North American Pacific Coast using models from the Coupled Model Intercomparison Project phase 6 (CMIP6). Over the early to mid-20th century, when U.S. and European AA and precursor gas emissions rapidly increased, a robust wintertime precipitation dipole pattern exists in CMIP6 all-forcing and AA-only forcing simulations, with wetting of the southern Pacific Coast (southward of ∼40^∘ N) and drying to the north. A corresponding dynamical dipole pattern also occurs—including strengthening of the east Pacific jet southward of ∼40^∘ N and weakening to the north—which is related to a Rossby wave teleconnection that emanates out of the tropical Pacific. Over the 21st century, when AAs are projected to decrease, an opposite hydro-dynamic dipole pattern occurs, including drying southward of 40^∘ N (including California) and wetting to the north. Although Pacific Coast precipitation is dominated by natural variability, good multi-model agreement in the forced component of Pacific Coast precipitation change exists, with the AA pattern (north south dipole) dominating the greenhouse gas (uniform) pattern in the historical all-forcing simulations. A high level of agreement in individual model-realization trends also exists, particularly for the early part of the 20th century, suggesting a robustness to the human signature on Pacific Coast precipitation changes. Thus, historical precipitation responses along the Pacific Coast are likely to have been driven by a mixture of natural variability and forced changes. Natural variations appear to drive a large fraction of this change, but human influences (i.e. aerosols) are likely to have preconditioned the variability of the climate in this region.

Parliamentary questions (PQs) are a crucial oversight tool available to parliamentarians in all democracies. In a well-functioning democracy, parliamentary oversight can play an important role in climate change policy, ensuring that climate concerns are represented in national agendas. India is the largest democracy in the world and one of the countries most vulnerable to climate change. Over a 20 year period, from 1999 to 2019, we examine whether parliamentarians used PQs to address climate change issues in India. We asked four questions (a) How often are PQs raised about climate change? (b) Are vulnerable constituency interests being represented in the Parliament? (c) What kinds of questions do parliamentarians ask? and (d) Where do parliamentarians get their information on climate change from? 895 unique PQs related to climate change were raised by 1019 Ministers, forming only a fraction (∼0.3%) of the total PQs asked in parliament during this period, however the number of PQs related to climate change increased over time. PQs were not raised by the states most vulnerable to climate change, nor did they represent the concerns of socially vulnerable groups. The PQs were mostly concerned about the impacts (27.6%) and mitigation (23.4%) of climate change. Impacts on agriculture (38.3%), coastal changes (28.6%), and health (13.4%) were of main interest, along with mitigation issues related to energy (43.6%), agriculture (21.8%), and aviation (9.1%). Despite the significant and growing vulnerability of India to climate change, PQs related to climate change were largely missing. Although they have increased over time, we still find there is substantial room for growth, especially in critical areas of climate justice and adaptation relevant to the Indian context. Raising the level of parliamentary debate on climate change is critical and needs to be foregrounded.

This work investigated the impact of 1.5 °C and 2 °C of global warming levels (GWLs) above pre-industrial levels on annual and seasonal mean changes in temperature extremes over Côte d'Ivoire and its different climatic zones. We used the multi-model Coordinated Regional Climate Downscaling Experiment for Africa of 25 regional climate models under the RCP8.5 scenario. The changes in temperature are quantified relative to the period 1971–2000 based on five Expert Team on Climate Change Detection and Indices indexes namely for warm spells, hot nights, hot days, cold nights and cold days. We show that a global warming of 1.5 °C and 2 °C will lead to an increase in the frequency of warm days and warm nights and a decrease in the occurrence of cold days and cold nights across Côte d'Ivoire in all climatic zones and seasons. More than 80% of the model ensemble members project this change at both GWLs. Moreover, the assessment of differences in GWLs highlights that the difference between the 1.5 °C and 2 °C thresholds may intensify the changes over all the country, climatic zones and seasons. Therefore this 0.5 °C difference in global warming is likely to impact upon energy demand and the agricultural system throughout the country and over all of the seasons. This study provides climate information for decision makers related to sectors such as agriculture, energy in their adaptation strategies.