Climatology Research Articles

Attending to history in climate change–demography research

Climate change is among the most urgent challenges of our time. While often considered a problem for the natural and physical sciences, the humanities and social sciences have made equally important interventions into research on the reciprocal relationship between humans and our climate. Because demography occupies the intersection of the natural and social sciences, and because it deals specifically with rates of change in social and natural processes, we believe it can make valuable contributions to the pressing imperatives of understanding and addressing climate change and mitigating the harms it is already visiting on the world’s most vulnerable people. We also believe that climate change may afford demographers an opportunity to expand our capacity to think about time and space at finer scales, and to examine the relationships among the core demographic processes – mortality, fertility and migration – which have typically been considered in isolation from one another. Yet responsibly leveraging climate change to advance demography, and leveraging demography to advance climate science and policy, require a cognizance of history that will assist demographers and those who use our analyses in avoiding the replication of past harms and, we hope, the invention of new ones. Understanding the history of demography and of population-environment thought more broadly can help us challenge assumptions that have not served science or policy well in the past – such as the assumption that larger or faster-growing populations necessarily put more pressure on the environment, independent of structural conditions – and consider alternative theoretical framings that might lead to better scientific models and policy solutions.

DeepMIP-Eocene-p1: multi-model dataset and interactive web application for Eocene climate research

Paleoclimate model simulations provide reference data to help interpret the geological record and offer a unique opportunity to evaluate the performance of current models under diverse boundary conditions. Here, we present a dataset of 35 climate model simulations of the warm early Eocene Climatic Optimum (EECO; ~ 50 million years ago) and corresponding preindustrial reference experiments. To streamline the use of the data, we apply standardised naming conventions and quality checks across eight modelling groups that have carried out coordinated simulations as part of the Deep-Time Model Intercomparison Project (DeepMIP). Gridded model fields can be downloaded from an online repository or accessed through a new web application that provides interactive data exploration. Local model data can be extracted in CSV format or visualised online for streamlined model-data comparisons. Additionally, processing and visualisation code templates may serve as a starting point for advanced analysis. The dataset and online platform aim to simplify accessing and handling complex data, prevent common processing issues, and facilitate the sharing of climate model data across disciplines.

Diverging paths, converging goals: Framing crisis to kairos in Bill Gates's and Greta Thunberg's climate discourse

This article introduces a typology of nine communication frames and analyzes how they operate in Bill Gates's How to Avoid a Climate Catastrophe (2021) and Greta Thunberg's The Climate Book (2022). The typology draws special attention to how non-fiction books are vehicles that can appeal for timely action (i.e. kairos), establish authorial ethos, disseminate climate science, and advocate for climate activism and energy transitions. The application of the typology highlights the books' narrative arcs: Gates and Thunberg both begin by acknowledging the reality and severity of the climate crisis and the correspondence between social progress and justice. Then, their arguments diverge: Thunberg critiques ineffective policies, cites climate science, and urges immediate social action; Gates provides economic context to support his appeals for innovation spurred by applied science. Towards their conclusions, the two authors' rhetorical appeals converge again as they each advocate for timely action. The results of this thematic analyses reinforce the value of book-length arguments that engage scientific evidence and envisage urgent individual and collective responses to climate crises.

Integrating night studies into climate science

Integrating night studies into climate science

Climate Research Contributions in Occupational Safety

Objective: This work aimed to identify the additional contributions of the Climate Survey to the Safety area of some companies. Theoretical reference: As a theoretical framework, different questionnaire models were used to research the perceptions of the workforce. Method: A case study was used as a method, whose data collection instrument was a climate questionnaire, constructed from bibliographic research in the ISI Web of Science and Scopus databases, applied to a universe of 455 workers of an offshore organization. Results and Conclusion: Despite being strongly linked to the company culture, the Climate Survey revealed factors underlying risk behaviors, the scope and systemic nature of failures, proving to be an effective diagnostic tool for safety management. Search Implications: This study found that cost reduction policies and focus on financial results tend to reduce organizational investments, leading many companies to adopt reactive management models. And by restricting safety actions to the occurrence of accidents, they ignore unrecorded risks, their scope, latent causes and their systemic nature. Originality/value: This case study is original and assumes an inestimable value due to its scope.

Wave‐Coupled Effects on Oceanic Biogeochemistry: Insights From a Global Ocean Biogeochemical Model in the Southern Ocean

AbstractOceanic biogeochemistry plays a pivotal role in regulating Earth's climate system by governing the cycling of key elements such as carbon, oxygen, and nutrients. Various metocean processes including wind, tides, currents, waves, and eddies significantly influence the dynamics of this system. In particular, ocean surface waves contribute to this intricate interplay by facilitating the exchange of heat, gas, and momentum between the atmosphere and the ocean. Although wave‐coupled effects are substantial, studies on their impacts on oceanic biogeochemistry, particularly on phytoplankton abundance are missing in present‐day research. Additionally, wave‐coupled effects cannot be disregarded in regions like the Southern Ocean (SO), where wind and waves activities are prominent. Addressing this gap, we incorporated a parameterization of surface wave mixing into a global ocean biogeochemical model to investigate its effects on upper ocean and biogeochemical parameters. Our results show that surface wave mixing has significant impacts on sea surface temperature (SST), mixed layer depth (MLD), and nutrient distribution—key factors that influence phytoplankton growth. Additionally, we observed significant improvements in model biases against the observations. During austral summer, additional mixing from surface waves can significantly lower SST by 0.5°C, deepen MLD by 13 m, and enhance Chlorophyll‐a (Chl‐a) concentration, an index of phytoplankton population, by 8% in the SO. This observed increase in Chl‐a concentration is mainly driven by enhanced dissolved iron levels resulting from wave‐induced mixing. Our findings underscore the significance of incorporating surface wave mixing in ocean biogeochemistry studies, an aspect that is currently overlooked.

On the predictability of possible storylines for forced complex systems

Abstract It is well-known that even for fairly simple deterministic nonlinear systems, exact prediction of future state is, on average, impossible beyond some small multiple of the Lyapunov time that quantifies the rate of separation of trajectories within an attractor. Nonetheless, it may be possible to find a physical measure that is the distribution of a trajectory within the attractor. In that sense, there can be a still weaker form of predictability. In this paper, we show that this can also fail but an even weaker form of predictability can appear for non-autonomous (i.e. forced) systems in the presence of tipping points. The {\em predictability of possible storylines} appears when one can interpret the frequencies of runs within an ensemble arriving at one of several possible future attractors (storylines) in a probabilistic manner.
As predictability is a major concern and a challenge in climate science, we illustrate this notion of predictability with two climate-related examples: a chaotic energy balance model and a global ocean model featuring a tipping point of the Atlantic Meridional Overturning Circulation.

Are Our Climate Data Fit for Your Purpose?

Abstract This paper describes the vision and objectives for evaluation and quality control of datasets available on the Climate Data Store (CDS) of the Copernicus Climate Change Service (C3S). The CDS is a cloud service providing reliable, open, and free access to climate datasets from many different sources, including observations and derived climate data records, global and regional reanalysis products, and output from global and regional climate models. CDS data and information are widely used to monitor climate change, for policy development, environmental impact studies, business plans, public awareness, and many other purposes. CDS users include policymakers, technical consultants, and data scientists who are climate literate but not necessarily specialized in climate science. A key objective for C3S is to simplify data discovery and access and to ensure that all information provided is fit for purpose. The role of evaluation and quality control is to generate useful statements about the technical and scientific quality of the datasets available on the CDS, presented in a form that can be mapped directly to user requirements associated with specific application contexts. The ambition is to enable users to select, locate, access, and process climate data that are fit for purpose, simply by expressing their requirements in their own words.

Compound events in the coupled climate and socio-ecological system

The most devastating climate-related impacts are typically a result of multiple compounding drivers among the atmospheric and socio-economic domain. Originally promoted by the climate sciences, compound event research extends to more and more disciplines, thereby turning into a truly interdisciplinary field. This is well reflected in the special issue "compounding effects as drivers of extreme events in socio-ecological systems".

Mapping local climate zones and its applications at the global scale: A systematic review of the last decade of progress and trend

The concept of local climate zone (LCZ) was proposed in 2012 to meet the needs of refinement and standardization of urban climate research. As an important contribution of the World Urban Database and Access Portal Tool (WUDAPT), which is an initiative to collect and share urban data globally to facilitate urban-focused climate researches, LCZ research has shown a booming trend in the past decade. As of the end of October 2023, more than 400 related papers, which involve about 250 cities in the world, have been published. At this juncture (decadal anniversary of the WUDAPT), a review from a global perspective and outlooks of the LCZ framework, from mapping to application and its coordinated development with WUDAPT, are needed to support the popularity and further progress of LCZ and WUDAPT. In this review, statistical and metadata analysis methods were used to summarize and analyze a sample of LCZ-related papers published since 2012, focusing on two aspects: mapping and application. The mapping methods were divided into three categories, namely, remote sensing-based, geographic information system-based, and hybrid methods. The application topics were grouped into two categories, namely, WUDAPT initiative and novel WUDAPT application. Two relevant themes originated from the above summary were further discussed, and then the future was forecasted on the basis of current research limitations. From this review, researchers can benefit from the recent progress in mapping and application of the LCZ system and future research directions, thereby further promoting the development in this field.

Research on the refinement of atmospheric weighted average temperature model in Xi’an based on machine learning

One of the most important parameters for calculating the atmospheric precipitable water vapor (PWV) is the atmospheric weighted mean temperature (Tm). Meteorological parameters that are measured typically constrain the accuracy and regional applicability of commonly used empirical models. When precipitable water is inverted using the Global Navigation Satellite System (GNSS), it results in erroneous Tm being obtained. Thus, in this paper, a small-scale Tm model for Xi’an is proposed by least squares method based on data provided by the European Centre for Mesoscale Weather Forecasts (ECMWF) from 2019 to 2022, while improving the functional model’s capacity to fit nonlinear residuals through the Random Forest method and enabling it to predict peaks more accurately. It is based on a random forest to confirm the weighted average temperature model’s correctness (RF Tm). When comparing the RF Tm model’s projected Tm accuracy to the GPT3, UNB3, and regional Bevis models, using the 2023 ERA5 data as the experimental data, the improvements are 23.6 %, 18.6 %, and 11.4 %, respectively. With the sounding station data as the reference value, the BIAS of RF Tm is only 1.51 K. In determining the atmospheric weighted average temperatures, the two models’ accuracy was comparable to that of the Long Short-Term Memory neural network model (LSTM). However, the LSTM model requires short-term forward data for practical usage, the RF Tm model compensated for the shortfall. The RF Tm model is used to invert the atmospheric precipitable water vapor at the appropriate monitoring stations using data from GNSS monitoring stations in Xi’an. It was demonstrated that the RF Tm model’s PWV inversion accuracy outperformed the PWV inverted by the GPT3 model by at least 30 %. Moreover, Xi’an rainfall data integration shows that the PWV inverted by the RF Tm model reacts to brief rainfall episodes efficiently. To sum up, this study’s RF Tm model provides a dependable and effective approach to meteorological observation and climate research.

An improved method for developing the precipitable water vapor vertical correction global grid model

Precipitable Water Vapor (PWV) is a crucial parameter in climate research. However, obtaining high precision PWV data remains a problem. Discrepancies in water vapor elevation data from diverse observation sources pose challenges, emphasizing the need for precise vertical correction. In this paper, we proposed the precipitable water vapor model with systematic difference correction by using ERA5 (the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis) data and GNSS (Global Navigation Satellite System) data. In this proposed method, two vertical correction models, employing cubic polynomial and exponential functions, were developed. The exponential function demonstrated superior overall performance with the RMS error of 0.96 mm, effectively capturing vertical characteristics across diverse regions, while the cubic polynomial function had the RMS (Root Mean Square) error of 2.77 mm validated by ERA5 PWV. The cubic polynomial function was found more suitable for low-elevation regions, while the exponential function excelled in high-elevation regions. Validated by radiosonde PWV, the cubic polynomial function and the exponential function show a strong correlation with latitude. Both functions exhibit smaller RMS values at higher latitudes and larger RMS values at lower latitudes. Validated by GNSS PWV, the cubic polynomial function exhibits superior accuracy, with the RMS of 2.39 mm, compared to the exponential function, particularly in specific regions. Analyzing six years of data reveals significant systematic differences between ERA5 and GNSS PWV. This discrepancy exhibits a noticeable annual periodic variation. The global GNSS stations were organized into grids, with stations within the same region grouped together for correction. Models considering systematic differences exhibited substantial RMS reductions and better accuracy. These findings can provide reference in atmospheric correction and the study of extreme weather events.

Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model

AbstractSignificant advancements in satellite‐based precipitation retrieval algorithms have led to the development of continuous, quasi‐global precipitation products, offering unique opportunities for hydrometeorological and climate research. In this context, six satellite‐based precipitation products (SPPs), including CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were thoroughly investigated for their application in hydrological simulations over the Wardha River basin in India. The observed gridded precipitation product developed by India Meteorological Department (IMD) has been used as reference data to evaluate the performance of SPPs. Hydrological variables such as runoff, soil moisture (SM) and evapotranspiration (ET) were simulated using the Variable Infiltration Capacity model. The performances of SPPs are critically assessed using various statistical metrics, including Pearson's correlation coefficient (R), Klinga‐Gupta Efficiency (KGE), Percent Bias (PBIAS), root mean square error (RMSE), and the RMSE to standard deviation ratio (RSR). The model‐simulated discharge was compared with streamflow observations at a single gauging site, while a spatially distributed comparison was conducted between simulated SM and ET and satellite‐based SM and ET. The IMD dataset consistently shows superior performance for discharge simulation at both daily and monthly scales, with KGE values of 0.85 and 0.91, respectively. Among SPPs, MSWEP and CHIRPS excel in simulating daily and monthly discharge, respectively. For ET simulation, CHIRPS outperforms IMD and other SPPs, achieving an overall KGE value of 0.37. In contrast, PERSIANN is the most effective for simulating SM compared to other precipitation products.

"Being Simple on Complex Issues" - Accounts on Visual Data Communication About Climate Change.

Data visualizations play a critical role in both communicating scientific evidence about climate change and in stimulating engagement and action. To investigate how visualizations can be better utilized to communicate the complexities of climate change to different audiences, we conducted interviews with 17 experts in the fields of climate change, data visualization, and science communication, as well as with 12 laypersons. Besides questions about climate change communication and various aspects of data visualizations, we also asked participants to share what they think is the main takeaway message for two exemplary climate change data visualizations. Through a thematic analysis, we observe differences regarding the included contents, the length and abstraction of messages, and the sensemaking process between and among the participant groups. On average, experts formulated shorter and more abstract messages, often referring to higher-level conclusions rather than specific details. We use our findings to reflect on design decisions for creating more effective visualizations, particularly in news media sources geared toward lay audiences. We hereby discuss the adaption of contents according to the needs of the audience, the trade-off between simplification and accuracy, as well as techniques to make a visualization attractive.

Designing serious games to advance climate change adaptation

The escalating impact of climate change necessitates innovative strategies to enhance public understanding and action. This research delves into the potential of serious games as transformative tools for climate change education and adaptation. Despite their rising popularity, serious games face challenges in effectively conveying complex climate science concepts and achieving desired learning outcomes. This study builds upon existing frameworks to propose tailored guidelines for designing serious games focused on climate change adaptation. We anchor our guidelines on the Design, Play, Experience (DPE) framework to scaffold strategies to create more effective serious games for climate change adaptation. We propose 11 elements that should be considered between player engagement and design when creating serious games. Through iterative playtesting and community involvement, we underscore the significance of reflecting on language, comprehension, timing, and social dynamics. This work bridges the gap between scientific knowledge and actionable insights in the development of serious games to equip decision-makers and communities with the tools to combat the multifaceted challenges posed by climate change.

Ethnic conflicts and their relationship with temperature change in the eastern Qinghai-Tibet Plateau and its vicinity during the past 2000 years

In the context of global warming, the study of climate change and its impacts has garnered significant attention. The Qinghai-Tibet Plateau, with its unique natural environment and socio-cultural significance, plays a crucial role in climate change and the development of the Chinese nation. Investigating the historical interactions, development, and socio-climatic background of the nomadic groups on the Qinghai-Tibet Plateau and agricultural ethnic groups in eastern China contributes to understanding the intrinsic mechanisms of how climate change affects the social interconnectivity of different ethnic groups. This paper is founded on an analysis of 450 conflict events between these groups, as reflected in ancient Chinese war chronicles and ethnic relations annals, creating a decadal conflict sequence from the Eastern Han to the Qing Dynasty (25AD-1910AD). The study conducts a correlation analysis and phase-wise statistical comparison between the climate research findings and the ethnic conflict sequence, specifically examining their relationship with temperature. The main findings are: (1) From the Eastern Han to the Qing Dynasty, a total of 876 conflicts occurred between the ethnic groups in the eastern Qinghai-Tibet Plateau and its vicinity (averaging 4.6 conflicts per decade), with 62.1% initiated by the Ethnic groups on the Qinghai-Tibet Plateau and 66.6% won by the Ethnic groups in eastern China; (2) The frequency of conflicts is primarily correlated with temperatures in the Eastern region, with a less distinct correlation in the Qinghai-Tibet Plateau. During overall warmer periods, conflict incidents were more frequent, with a higher proportion initiated by the Ethnic groups on the Qinghai-Tibet Plateau. Conversely, in colder periods, there were fewer conflicts, with an increased proportion initiated by the Ethnic groups in eastern China; (3) Unlike conflicts between the Ethnic groups in northwestern and eastern China, the Ethnic groups on the Qinghai-Tibet Plateau's external expansion was not a primary objective, indicating that the conflicts were mainly driven by regional economic strength and land productivity. The temperature can reduce land productivity by limiting the growth potential of crops and livestock or by reducing the advance to restrict their production. As a result, water resources, as a condition of land productivity variation, and climate became significant backgrounds for ethnic interactions.

Spatiotemporal variability of hydro-meteorological droughts over the Arabian Peninsula and associated mechanisms

This study examines the spatiotemporal variability of drought and associated physical processes over the Arabian Peninsula (AP). For this purpose, we computed the standardized precipitation evapotranspiration index (SPEI) for the period 1951–2020 using the Climate Research Unit and fifth generation ECMWF atmospheric reanalysis datasets. By applying rotated empirical orthogonal function analysis on the SPEI data, we identified four homogeneous and coherent drought regions. The droughts in the northern regions follow a relatively similar temporal evolution as compared to those in the southern region. All four sub-regions of the AP exhibit a significant drying trend (p < 0.01) with an abrupt acceleration in drought frequency and intensity over the last two decades. The increase in droughts is associated with the reduction of synoptic activity and an increase in the high pressure over the AP. Seasonally, potential evapotranspiration is the dominant driver of summer droughts in the AP, whereas both precipitation and temperature are important for driving winter droughts. The summer droughts, mainly over the northern AP, are due to the occurrence of an anomalous equivalent barotropic high associated with anomalous dry and hot conditions. However, anomalous dry conditions in winter are a result of an anomalous paucity of winter storms caused by the weakening of the sub-tropical jets.

Organic carbon oxidation and the associated pyrite formation in deep sediments at the Nankai subduction zone

The preservation of organic carbon (OC) in marine sediments is crucial for Earth's climate by sequestering CO2. While OC is mostly remineralized before it reaches the seafloor, a notable fraction is buried in deep-sea sediments, particularly at subduction zones known for their enhanced sedimentation rates that promote OC burial. The mechanisms behind OC recycling and decomposition within subduction zone sediments are governed by biologically mediated redox reactions involving a range of electron acceptors, which facilitate the sequential oxidation of OC. However, direct evidence regarding such effects on OC in deep sediments remains limited. In this study, we examine the contents of pyrite and trace metals of molybdenum (Mo), vanadium (V), and cesium (Cs) in organic-rich deep sediments from the Nankai subduction zone. We find that the pyrite, sulfate, diagenetic illite, and OC contents covary in Unit V, highlighting the important role of organoclastic sulfate reduction and biotic smectite-to-illite reaction at 60–70 °C in OC oxidation and pyrite formation. The profiles of Mo, V, and Cs also align with these processes in the same interval. Our findings contribute to an in-depth understanding of OC dynamics in subduction zones, emphasizing the complex interactions within deep sediments that may influence the global carbon cycle.

The dawn of climate securityThreat Multiplier: Climate, Military Leadership, and the Fight for Global Security Sherri Goodman Island Press, 2024. 272 pp.

A policy pioneer's memoir shows how climate science penetrated the defense sector.

A Dynamically Consistent ENsemble of Temperature at the Earth surface since 1850 from the DCENT dataset

Accurate historical records of Earth’s surface temperatures are central to climate research and policy development. Widely-used estimates based on instrumental measurements from land and sea are, however, not fully consistent at either global or regional scales. To address these challenges, we develop the Dynamically Consistent ENsemble of Temperature (DCENT), a 200-member ensemble of monthly surface temperature anomalies relative to the 1982–2014 climatology. Each DCENT member starts from 1850 and has a 5° × 5° resolution. DCENT leverages several updated or recently-developed approaches of data homogenization and bias adjustments: an optimized pairwise homogenization algorithm for identifying breakpoints in land surface air temperature records, a physics-informed inter-comparison method to adjust systematic offsets in sea-surface temperatures recorded by ships, and a coupled energy balance model to homogenize continental and marine records. Each approach was published individually, and this paper describes a combined approach and its application in developing a gridded analysis. A notable difference of DCENT relative to existing temperature estimates is a cooler baseline for 1850–1900 that implies greater historical warming.