Search

Tropical cyclones (TCs) can cause severe wind and rain hazards. Unusual TC tracks and their extreme precipitation forecasts have become two difficult problems faced by conventional models of primitive equations. The case study in this paper finds that the numerical computation of the climatological component in conventional models restricts the prediction of unusual TC tracks. The climatological component should be a forcing quantity, not a predictor in the numerical integration of all models. Anomaly-based variable models can overcome the bottleneck of forecast time length or the one-week forecasting barrier, which is limited to less than one week for conventional models. The challenge in extreme precipitation forecasting is how to physically get the vertical velocity. The anomalous moisture stress modulus (AMSM), as an indicator of heavy rainfall presented in this paper, considers the two conditions associated with vertical velocity and anomalous specific humidity in the lower troposphere. Vertical velocity is produced by the orthogonal collision of horizontal anomalous airflows. [ABSTRACT FROM AUTHOR]

The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model's precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms. [ABSTRACT FROM AUTHOR]

The Coupled Model Intercomparison Project (CMIP) is one of the biggest international efforts aimed at better understanding the past, present, and future of climate changes in a multi-model context. A total of 21 model intercomparison projects (MIPs) were endorsed in its sixth phase (CMIP6), which included 190 different experiments that were used to simulate 40 000 years and produced around 40 PB of data in total. This paper presents the main findings obtained from the CPMIP (the Computational Performance Model Intercomparison Project), a collection of a common set of metrics, specifically designed for assessing climate model performance. These metrics were exclusively collected from the production runs of experiments used in CMIP6 and primarily from institutions within the IS-ENES3 consortium. The document presents the full set of CPMIP metrics per institution and experiment, including a detailed analysis and discussion of each of the measurements. During the analysis, we found a positive correlation between the core hours needed, the complexity of the models, and the resolution used. Likewise, we show that between 5 %–15 % of the execution cost is spent in the coupling between independent components, and it only gets worse by increasing the number of resources. From the data, it is clear that queue times have a great impact on the actual speed achieved and have a huge variability across different institutions, ranging from none to up to 78 % execution overhead. Furthermore, our evaluation shows that the estimated carbon footprint of running such big simulations within the IS-ENES3 consortium is 1692 t of CO 2 equivalent. As a result of the collection, we contribute to the creation of a comprehensive database for future community reference, establishing a benchmark for evaluation and facilitating the multi-model, multi-platform comparisons crucial for understanding climate modelling performance. Given the diverse range of applications, configurations, and hardware utilised, further work is required for the standardisation and formulation of general rules. The paper concludes with recommendations for future exercises aimed at addressing the encountered challenges which will facilitate more collections of a similar nature. [ABSTRACT FROM AUTHOR]

In the online seminar series "Perspectives on climate sciences: from historical developments to future frontiers", which took place during 2020–2021, well-known and established scientists from several fields – including mathematics, physics, climate science and ecology – presented their perspectives on the evolution of climate science and on relevant scientific concepts. This special issue aims to create a platform for a more detailed elaboration of the topics discussed in the seminars but also to publish new scientific findings. In this paper, we first give an overview of the content of the seminar series, and then we introduce the written contributions to this special issue. In line with the spirit of the seminar series, this paper is structured along thematic areas of the broad field of climate science, conveying different perspectives on the climate system: geophysical fluid dynamics, dynamical systems theory, multiscale processes, statistical physics, paleoclimate and the human dimension. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a spectral surface reflectivity climatology based on observations made by TROPOMI on board the Sentinel-5P satellite. The database contains the directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface for 21 wavelength bands ranging from 328 to 2314 nm and for each calendar month. The spatial resolution of the database grid is 0.125° × 0.125°. A recently developed cloud shadow detection technique is implemented to avoid dark scenes due to cloud shadow. In the database, the anisotropy of the surface reflection is described using a third-order parameterisation of the viewing angle dependence. The viewing angle dependence of the DLER is analysed globally and for a selection of surface type regions. The dependence is found to agree with the viewing angle dependence found in the GOME-2 surface DLER database. Differences exist, related to the actual solar position. On average, the viewing angle dependence in TROPOMI DLER is weaker than for GOME-2 DLER, but still important. Validation of the new database was first performed by comparison of the non-directional TROPOMI surface LER with heritage LER databases based on GOME-1 , OMI, SCIAMACHY, and GOME-2 data. Agreement was found within 0.002–0.02 in the UV-VIS (below 500 nm), up to 0.003 in the NIR (670–772 nm), and below 0.001 in the short-wave infrared (SWIR) (2314 nm). These performance numbers are dominated by the performance over ocean, but they are in most cases also representative for land surfaces. For the validation of the directional TROPOMI surface DLER, we made use of comparison with the MODIS surface bi-directional reflectance distribution function (BRDF) for a selection of surface type regions. In all cases the DLER performed significantly better than the traditional LER, and we found good agreement with the MODIS surface BRDF. The TROPOMI surface DLER database is a clear improvement on previous surface albedo databases and can be used as input not only for satellite retrievals from TROPOMI observations, but also for retrievals from observations from other polar-orbiting satellite instruments provided that their equator crossing time is close to that of TROPOMI. The algorithm that is introduced in this paper can be used for the retrieval of surface reflectivity climatologies from other polar satellite missions as well, including Ocean and Land Colour Instrument (OLCI) on the Sentinel-3 satellites, Sentinel-5, and Multi-viewing Multi-channel Multi-polarisation imager (3MI) on the MetOp-SG-A1 satellite to be launched in 2025, as well as the future CO2M mission. [ABSTRACT FROM AUTHOR]

Article 7 of the Paris Agreement recognizes that adaptation is a 'global challenge faced by all with local, regional and international dimensions.' It further establishes the 'global goal on adaptation focusing on enhancing adaptive capacity, strengthening resilience and reducing vulnerability to climate change, with a view to contributing to sustainable development.' However, the lack of international cooperation between the global north and global south challenge the formulation and implementation of climate change adaptation strategies. This paper brings in the concept of global public goods (GPGs) to the lexicon of climate adaptation and highlights that adverse impacts of climate change such as climate-induced global migration are global public bad. Hence, the measures taken to respond to such impacts, which consequently enhance the resilience of affected countries, make them more adaptive to those adverse impacts, and deliver common values of universal character, should be construed as the global public good. The paper argues that that the idea of GPGs with its universality offers a normative and practical foundation for understanding, addressing, and strengthening the international community's climate adaptation actions and cooperation. [ABSTRACT FROM AUTHOR]

This paper sheds light on an important and under‐researched issue: The sources of information about climate change that teachers use. Utilising a 'scoping review' methodological approach, we analysed over 600 papers to address two main questions: What sources of information about climate change are teachers using? In what ways are teachers using these sources of information? Through our use of inclusive search terms and detailed analysis of papers, we found only 13 studies of relevance, none of which primarily focus on the sources of information teachers use. The 13 studies are all located in the Global North, and within this nearly half are in the USA. Methodologically, all apart from two rely on teachers' reports rather than observation or other methods. Four types of sources of information were frequently mentioned: The Internet; government sources; mass media and professional development courses. The 'superabundance' of information now available to teachers (particularly online), the importance of high‐quality information for students' understandings of climate change, and the limited research on the sources of information about climate change that teachers use makes this is a significant blind spot for research to address. [ABSTRACT FROM AUTHOR]

As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving the model performance. [ABSTRACT FROM AUTHOR]

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested prac titioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks. [ABSTRACT FROM AUTHOR]

A climate system which is transitioning from one state to another is known as an abrupt climate change. Most of the recent studies regarding abrupt climate change have focused on the changes occurring before and after the abrupt change point, while little attention has been given to the "transition process" which occurs when the system breaks away from the original state to a new state. In this study, a novel method for analyzing the process of abrupt climate change was presented. By using the mathematical model based on the Logistic model, the process of the abrupt change could be analyzed and divided into different phases which include start moment, end moment, stable state, and unstable transition state. Meanwhile, the method was confirmed to be effective by testing in a study of Pacific decadal oscillation (PDO) time sequence, and the results of this study specify that this abrupt change process of PDO has a relationship with global warming. [ABSTRACT FROM AUTHOR]

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities. [ABSTRACT FROM AUTHOR]

Copyright of Terr@ Plural is the property of Terr@ Plural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy eficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth. [ABSTRACT FROM AUTHOR]

Among papers stating a position on anthropogenic global warming (AGW), 97 % endorse AGW. What is happening with the 2 % of papers that reject AGW? We examine a selection of papers rejecting AGW. An analytical tool has been developed to replicate and test the results and methods used in these studies; our replication reveals a number of methodological flaws, and a pattern of common mistakes emerges that is not visible when looking at single isolated cases. Thus, real-life scientific disputes in some cases can be resolved, and we can learn from mistakes. A common denominator seems to be missing contextual information or ignoring information that does not fit the conclusions, be it other relevant work or related geophysical data. In many cases, shortcomings are due to insufficient model evaluation, leading to results that are not universally valid but rather are an artifact of a particular experimental setup. Other typical weaknesses include false dichotomies, inappropriate statistical methods, or basing conclusions on misconceived or incomplete physics. We also argue that science is never settled and that both mainstream and contrarian papers must be subject to sustained scrutiny. The merit of replication is highlighted and we discuss how the quality of the scientific literature may benefit from replication. [ABSTRACT FROM AUTHOR]

In unpublished paper, former White House climate adviser calls methane "irrelevant" to climate PHOTO (COLOR): Oil and gas processing, as at this refinery in Russia, are copious sources of methane. Happer crafted a summary of his methane work to support groups that are fighting against methane emissions regulation, said Caleb Rossiter, executive director of the CO2 Coalition. [Extracted from the article]

The chaos caused by the global climate crisis is in the news in many forms and has also entered the consulting room: clients are increasingly naming their fear, despair, rage, and experience of impotence in the face of the unknown. This paper builds on the work of G. Albrecht and J. Bernstein, to investigate how we can face our feelings about climate crisis and live through this time without resorting to unhelpful defenses that block our ability to be present, engaged and effective. It examines the unconscious beliefs, habitual patterns, and defenses of the Western ego, which it presents as the mindset of Economism and the Capitalocene, and investigates its identification with the hero archetype. It pays homage to indigenous analyses of the issue in the work of J. Forbes and I Merculieff, and draws on the work of eco-ethical thinkers such as K. D. Moore, J. Butler, and A. L. Tsing, to suggest that the archetype of the initiate may be a better guide as we move into the uncertain, contingent future. [ABSTRACT FROM AUTHOR]

The concept of a digital twin is intriguing as it presents an innovative approach to solving numerous real-world challenges. Initially emerging from the domains of manufacturing and engineering, digital twin research has transcended its origins and now finds applications across a wide range of disciplines. This multidisciplinary expansion has impressively demonstrated the potential of digital twin research. While the simulation aspect of a digital twin is often emphasized, the role of artificial intelligence (AI) and machine learning (ML) is severely understudied. For this reason, in this paper, we highlight the pivotal role of AI and ML for digital twin research. By recognizing that a digital twin is a component of a broader Digital Twin System (DTS), we can fully grasp the diverse applications of AI and ML. In this paper, we explore six AI techniques—(1) optimization (model creation), (2) optimization (model updating), (3) generative modeling, (4) data analytics, (5) predictive analytics and (6) decision making—and their potential to advance applications in health, climate science, and sustainability. [ABSTRACT FROM AUTHOR]

Promoting climate change discourses may potentially create a useful space for addressing the effects of climate change in Tanzania. During disasters such as floods, everyone obfuscates their agency and blames the other for causing climate change effects. This paper examines the discourse of climate change among scientists, government officials, and the non-scientific Tanzanian stakeholders on climate change and adaptation strategies after the 2019-2020 effects. These actors obfuscate responsibilities and attribute blame on the other for accelerating climate change effects. This paper examines how these attributions contribute to enhancing resilience and adaptation strategies. The paper was theoretically guided by the divided subject and positioning theories. Data for this paper were gathered from YouTube covering the subject. The results suggest that while none of the actors accepts responsibility for accelerating climate change; "what is happening and what should be done" gradually turn into "who is responsible for the mess". Divisive discourse like this is likely to keep Tanzania wobbling to create a resilient society to confront the challenges of climate change. The paper raises the need for the facilitation of a better communication between climate change science and the non-scientific audience. [ABSTRACT FROM AUTHOR]

Natural wetlands are among the most important sources of methane; thus, these areas are important for better understanding long-term temporal variations in atmospheric methane concentration. During the last 60 years, wetlands have experienced extensive conversion and global impacts from climate warming, which makes the estimation of methane emission from wetlands highly uncertain. In this paper, we present a modeling framework, integrating CH4MODwetland, TOPMODEL and TEM models, to analyze the temporal and spatial variations in CH4 emissions from natural wetlands (including inland wetlands, coastal wetlands, lakes and rivers) in China. Our analysis revealed an increase of 25.5%, averaging 0.52 gm-2 per decade, in national CH4 fluxes from 1950 to 2010, which was mainly induced by climate warming. Higher rates of increasing CH4 fluxes occurred in northeastern, northern and northwestern China, associated with large temperature increases. However, decreases in precipitation due to climate warming offset the increase in CH4 fluxes in these regions. The CH4 fluxes from the wetland on the Qinghai Tibetan Plateau exhibited a lower rate of increase, which was approximately 25% of that simulated in northeastern China. Although climate warming has accelerated CH4 fluxes, the total amount of national CH4 emissions decreased by approximately 2.35 Tg (1.91-2.81 Tg), i.e., from 4.50 Tg in the early 1950s to 2.15 Tg in the late 2000s, due to a large wetland loss of 17.0 million ha. Of this reduction, 0.26 Tg (0.24-0.28 Tg) was derived from lakes and rivers, 0.16Tg (0.13-0.20 Tg) from coastal wetlands, and 1.92Tg (1.54-2.33Tg) from inland wetlands. Northeastern China had the largest contribution to this reduction, with a loss of 1.68Tg. The CH4 emissions were reduced by more than half in most regions in China except for the Qinghai Tibetan Plateau, where only a 23.3% decrease in CH4 was observed. [ABSTRACT FROM AUTHOR]

Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model 3). Our study shows that in most parts of the world, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor 10) and, hence, large-scale model-data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere. [ABSTRACT FROM AUTHOR]

End to end modelling is an attractive and rapidly developing approach to solve developing strategies in marine systems science and management. However problems remain in the area of data matching and sub-model compatibility. A mechanism and novel interfacing system (Couplerlib) is presented whereby a physical/biogeochemical model (GOTM-ERSEM) that predicts dynamics of the lower trophic level (LTL) organisms in marine ecosystems is coupled to a dynamic ecosystem model (Ecosim) that predicts food-web interactions among higher trophic level (HTL) organisms. Coupling is achieved by means of a bespoke interface which handles the system incompatibilities between the models and a more generic Couplerlib library which uses metadata descriptions in extensible mark-up language (XML) to marshal data between groups, paying attention to functional group mappings and compatibility of units between models. In addition, within Couplerlib, models can be coupled across networks by means of socket mechanisms. As a demonstration of this approach, a food web model (Ecopath with Ecosim, EwE) and a physical/biogeochemical model (GOTM-ERSEM) representing the North Sea ecosystem were joined with Couplerlib. The output from GOTM-ERSEM varies between years dependent on oceanographic and meteorological conditions. Although inter-annual variability was clearly present, there was always the tendency for an annual cycle consisting of a peak of diatoms in spring, followed by (less nutritious) flagellates and dinoflagellates through the summer resulting in an early summer peak in the mesozooplankton biomass. Pelagic productivity, predicted by the LTL model, was highly seasonal with little winter food for the higher trophic levels. The Ecosim model was originally based on the assumption of constant annual inputs and, consequently, when coupled, pelagic species suffered population loss over the winter months. By contrast, benthic populations were more stable (although the benthic linkage modelled was purely at the detritus level). The coupled model was used to examine long term effects of environmental change, and showed the system to be nutrient limited, relatively unaffected by forecast climate change, especially in the benthos. The stability of an Ecosim formulation for large higher tropic level food webs is discussed and it is concluded that this kind of coupled model formulation is better for examining the effects of long term environmental change than short term perturbations. [ABSTRACT FROM AUTHOR]

Models used to investigate impacts of climatic changes on spatio-temporal vegetation dynamics need to balance required accuracy with computational feasibility. To enhance the computational efficiency of these models, upscaling methods are required that maintain key fine-scale processes influencing vegetation dynamics. In this paper, an adjustable method – the dynamic two-layer classification concept (D2C) – for the upscaling of time- and space-discrete models is presented. D2C aims to separate potentially repetitive calculations from those specific to single grid cells. The underlying idea is to extract processes that do not require information about a grid cell's neighbourhood to a reduced-size non-spatial layer, which is dynamically coupled to the original two-dimensional layer. The size of the non-spatial layer is thereby adaptive and depends on dynamic classifications according to pre-specified similarity criteria. I present how D2C can be used in a model implementation on the example of TreeMig-2L, a new, efficient version of the intermediate-complexity forest-landscape model TreeMig. To discuss the trade-off between computational expenses and accuracy, as well as the applicability of D2C, I compare different model stages of TreeMig-2L via simulations of two different application scenarios. This comparison of different model stages demonstrates that applying D2C can strongly reduce computational expenses of processes calculated on the new non-spatial layer. D2C is thus a valuable upscaling method for models and applications in which processes requiring information about the neighbourhood constitute the minor share of the overall computational expenses. [ABSTRACT FROM AUTHOR]

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was an infra-red (IR) limb emission spectrometer on the Envisat platform. It measured during day and night, pole-to-pole, over an altitude range from 6 to 70 km in nominal mode and up to 170 km in special modes, depending on the measurement mode, producing more than 1000 profiles day-1. We present the results of a validation study of methane version V5R_CH4_222 retrieved with the IMK/IAA MIPAS scientific level 2 processor. The level 1 spectra are provided by ESA, the version 5 was used. The time period covered corresponds to the period when MIPAS measured at reduced spectral resolution, i.e. 2005-2012. The comparison with satellite instruments includes the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the HALogen Occultation Experiment (HALOE), the Solar Occultation For Ice Experiment (SOFIE) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). Furthermore, comparisons with MkIV balloon-borne solar occultation measurements and with air sampling measurements performed by the University of Frankfurt are presented. The validation activities include bias determination, in selected cases, assessment of histograms and comparison of corresponding climatologies. Above 50 km altitude, MIPAS methane mixing ratios agree within 3% with ACE-FTS and SOFIE. Between 30 and 40 km an agreement within 3% with SCIAMACHY has been found. In the middle stratosphere, there is no clear indication of a MIPAS bias since comparisons with various instruments contradict each other. In the lower stratosphere (below about 25-30 km) MIPAS CH4 is biased high with respect to satellite instruments, and the most likely estimate of this bias is 14%. However, in the comparison with CH4 data obtained from cryosampler measurements, there is no evidence of a MIPAS high bias between 20 and 25 km altitude. Precision validation is performed on collocated MIPAS-MIPAS pairs and suggests a slight underestimation of its errors by a factor of 1.2. A parametric model consisting of constant, linear, QBO and several sine and cosine terms with different periods has been fitted to the temporal variation of differences of stratospheric CH4 measurements by MIPAS and ACE-FTS for all 10° latitude/1-2 km altitude bins. Only few significant drifts can be calculated, due to the lack of data. Significant drifts with respect to ACE-FTS tend to have higher absolute values in the Northern Hemisphere, have no pronounced tendency in the sign, and do not exceed 0.2 ppmv per decade in absolute value. [ABSTRACT FROM AUTHOR]

We use an eddy-resolving, regional ocean biogeochemical model to investigate the main variables and processes responsible for the climatological spatio-temporal variability of pCO2 and the air--sea CO2 fluxes in the southwestern Atlantic Ocean. Overall, the region acts as sink of atmospheric CO2 south of 30° S, and is close to equilibrium with the atmospheric CO2 to the north. On the shelves, the ocean acts as a weak source of CO2, except for the mid/outer shelves of Patagonia, which act as sinks. In contrast, the inner shelves and the low latitude open ocean of the southwestern Atlantic represent source regions. Observed nearshore-to-offshore and meridional pCO2 gradients are well represented by our simulation. A sensitivity analysis shows the importance of the counteracting effects of temperature and dissolved inorganic carbon (DIC) in controlling the seasonal variability of pCO2. Biological production and solubility are the main processes regulating pCO2, with biological production being particularly important on the shelf regions. The role of mixing/stratification in modulating DIC, and therefore surface pCO2 is shown in a vertical profile at the location of the Ocean Observatories Initiative (OOI) site in the Argentine Basin (42° S, 42° W). [ABSTRACT FROM AUTHOR]

This study uses the global climate-economy-biosphere (CoCEB) model developed in Part 1 to investigate economic aspects of deforestation control and carbon sequestration in forests, as well as the eficiency of carbon capture and storage (CCS) technologies as policy measures for climate change mitigation. We assume - as in Part 1 - that replacement of one technology with another occurs in terms of a logistic law, so that the same law also governs the dynamics of reduction in carbon dioxide emission using CCS technologies. In order to take into account the effect of deforestation control, a slightly more complex description of the carbon cycle than in Part 1 is needed. Consequently, we add a biomass equation into the CoCEB model and analyze the ensuing feedbacks and their effects on per capita gross domestic product (GDP) growth. Integrating biomass into the CoCEB and applying deforestation control as well as CCS technologies has the following results: (i) low investment in CCS contributes to reducing industrial carbon emissions and to increasing GDP, but further investment leads to a smaller reduction in emissions, as well as in the incremental GDP growth; and (ii) enhanced deforestation control contributes to a reduction in both deforestation emissions and in atmospheric carbon dioxide concentration, thus reducing the impacts of climate change and contributing to a slight appreciation of GDP growth. This effect is however very small compared to that of low-carbon technologies or CCS. We also find that the result in (i) is very sensitive to the formulation of CCS costs, while to the contrary, the results for deforestation control are less sensitive. [ABSTRACT FROM AUTHOR]

Long-range climate forecasts rely upon integrated assessment models that link the global economy to greenhouse gas emissions. This paper evaluates an alternative economic framework, outlined in Part 1, that is based on physical principles rather than explicitly resolved societal dynamics. Relative to a reference model of persistence in trends, model hindcasts that are initialized with data from 1950 to 1960 reproduce trends in global economic production and energy consumption between 2000 and 2010 with a skill score greater than 90%. In part, such high skill appears to be because civilization has responded to an impulse of fossil fuel discovery in the mid-twentieth century. Forecasting the coming century will be more of a challenge because the effect of the impulse appears to have nearly run its course. Nonetheless, the model offers physically constrained futures for the coupled evolution of civilization and climate during the Anthropocene. [ABSTRACT FROM AUTHOR]

GNSS Radio Occultation (RO) refractivity climatologies for the stratosphere can be obtained from the Abel inversion of monthly average bending-angle profiles. The averaging of large numbers of profiles suppresses random noise and this, in combination with simple exponential extrapolation above an altitude of 80 km, circumvents the need for a "statistical optimization" step in the processing. Using data from the US-Taiwanese COSMIC mission, which provides ~ 1500-2000 occultations per day, it has been shown that this Average-Profile Inversion (API) technique provides a robust method for generating stratospheric refractivity climatologies. Prior to the launch of COSMIC in mid-2006, the data records rely on data from the CHAMP mission. In order to exploit the full range of available RO data, the usage of CHAMP data is also required. CHAMP only provided~ 200 profiles per day, and the measurements were noisier than COSMIC. As a consequence, the main research question in this study was to see if the average bending angle approach is also applicable to CHAMP data. Different methods for suppression of random noise - statistical and through data quality pre-screening - were tested. The API retrievals were compared with the more conventional approach of averaging individual refractivity profiles, produced with the implementation of statistical optimization used in the EUMETSAT Radio Occultation Meteorology Satellite Application Facility (ROM SAF) operational processing. In this study it is demonstrated that the API retrieval technique works well for CHAMP data, enabling the generation of long-term stratospheric RO climate data records from August 2001 and onward. The resulting CHAMP refractivity climatologies are found to be practically identical to the standard retrieval at the DMI below altitudes of 35 km. Between 35 km to 50km the differences between the two retrieval methods started to increase, showing largest differences at high latitudes and high altitudes. Furthermore, in the winter hemisphere high latitude region, the biases relative to ECMWF were generally smaller for the new approach than for the standard retrieval. [ABSTRACT FROM AUTHOR]

B I Sustainability and Climate Change i b is a peer-reviewed publication dedicated to furthering the science of sustainability, sustainable development, and climate change. The editorial team of B I Sustainability and Climate Change i b invites you to submit your manuscript for consideration. [Extracted from the article]

Copyright of European Journal of Psychotraumatology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Heritage science is an inherently practice-oriented field that aims to support our understanding, and conservation, of heritage. Research is commonly undertaken using laboratory or field-based methodologies, but given the ethical and scale constraints, over time and space, of these approaches, process-based models should provide a tool for exploring practical solutions. Unlike other fields, such as climate science and ecology, there appears limited engagement with modelling within heritage science. The characteristics and use of processed-based models published in the field is examined to explore tensions in using models to transfer understanding between research and practice. By examining models that investigate interactions between heritage materials and environment, we find that, at best, model outputs may be used by other researchers or occasionally by heritage institutions; or more commonly, the model's existence is used as a justification of research, yet without meaningful engagement within either the academic and heritage practitioner communities. Some models are unlikely to be used in practice as they have been developed at spatial or temporal scales incompatible with being truly applicable to objects or sites, or can seem to advance theory without engaging with practice. The uptake of models by researchers who rerun or change the code is rare. Models that seem to gain substantial use appear to benefit from graphical user interfaces that make them easy to run. Evidence of models in solving real-world conservation problems is hard to find. This may arise because practical applications are rarely reported in academic journal literature and open access publications. There is some evidence they are revealed in conferences and possibly internal heritage organisation reports, but this gray literature doesn't readily feedback into the development and refinement of existing models. It is likely the use of models would increase if mechanisms were available to support the development of user interfaces, training workshops and the ability of practical use cases to be fed back to the modelling community. [ABSTRACT FROM AUTHOR]

In the North West Shelf region of Australia is a surface current (Holloway Current), which flows southwestward along the shelf break. This paper describes a seasonal undercurrent below the Holloway Current. A 5-day climatology is constructed from the output of an eddy-resolving oceanic general circulation model (OGCM). A seasonal northeastward-flowing undercurrent is found on the upper continental slope during the climatological April-May. This undercurrent reverses during February-March. During its annual cycle, the phase of the undercurrent tends to propagate southwestward and upward. The annual frequency dominates, but the positive and negative phases of the undercurrent are not symmetric in the yearly cycle because of the contributions from the semi-annual and 1/3-annual components. We propose a hypothesis that this undercurrent is a beam of coastal trapped wave (CTW). As an initial attempt to assess the plausibility of this hypothesis, we construct an idealized linear coastal-trapped wave (CTW) solution driven by an idealized harmonic meridional winds at the annual frequency. The solution takes the form of a beam originating from the forcing region on the continental shelf and propagating offshore and southward. When it emerges on to the continental slope, it takes the form of an undercurrent. This idealized solution shares several properties with the undercurrent in the OGCM despite several discrepancies. [ABSTRACT FROM AUTHOR]

The optimal control problems of degenerate parabolic equations have many applications in economics, physics, climatology, and so on. Motivated by the applications, we consider the optimal control problems of a class of nonlinear degenerate parabolic equations in this paper. The main result is that we deduce the first order necessary condition for the optimal control problem of nonlinear degenerate parabolic equations by variation method. Moreover, we investigate the uniqueness of the solutions to the optimal control problems. For the linear equations, we obtain the global uniqueness, while for the nonlinear equations, we obtain only the local uniqueness. Finally, we give a numerical example to validate the theoretical results. [ABSTRACT FROM AUTHOR]

Numerous recent tropical cyclones have caused extreme rainfall and flooding events in the CONUS. Climate change is contributing to heavier extreme rainfall around the world. Modeling studies have suggested that tropical cyclones may be particularly efficient engines for transferring the additional water vapor in the atmosphere into extreme rainfall. This paper develops a new indicator for climate change using the enhanced rainfall metric to evaluate how the frequency and/or intensity of extreme rainfall around tropical cyclones has changed. The enhanced rainfall metric relates the amount of rain from a storm over a given location to the 5-yr return period rainfall in that location to determine the severity of the event. The annual area exposed to tropical-cyclone-related 5-yr rainfall events is increasing, which makes it a compelling climate change indicator. Quantile regression illustrates that the distribution of tropical cyclone rainfall is also changing. For tropical storms, all quantiles are increasing. However, major hurricanes show large increases in their most extreme rainfall. This study does not attempt to make any detection claims (vs natural variability) or attribution of the observed trends to anthropogenic forcing. However, the sensitivity of the results to natural variability in tropical cyclone frequency was somewhat constrained by comparing 2 decades from the previous active era (1951–70) with two from the current era (2001–20). This comparison also shows that both the mean rainfall and the maximum rainfall associated with tropical cyclones are increasing over most areas of the eastern CONUS with the most significant increases from northern Alabama to the southern Appalachians. Significance Statement: The purpose of this study is to analyze the changes in frequency and magnitude of extreme precipitation events associated with tropical cyclones with the goal of developing a new indicator for climate change. This is important because heavy rainfall and associated flooding is one of the primary causes of tropical cyclone destruction and fatalities, especially in inland locations away from where storms initially make landfall. Our results show that both the frequency and magnitude of extreme rainfall events from tropical cyclones have increased over the CONUS. The strongest storms (major hurricanes) also show more of an increase in extreme rainfall than storms of weaker intensities. [ABSTRACT FROM AUTHOR]

A convolution based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10 to 30 times compared with a version using a twodimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge. [ABSTRACT FROM AUTHOR]

Copyright of Cientifica is the property of Fundacao de Apoio a Pesquisa e Extensao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Assessing the impacts of anthropogenic ocean acidification requires knowledge of present-day and future environmental conditions. Here, we present a simple model for upwelling margins that projects anthropogenic acidification trajectories by combining high-temporal resolution sensor data, hydrographic surveys for source water characterization, empirical relationships of the CO2 system, and the atmospheric CO22 record. This model characterizes CO2 variability on timescales ranging from hours (e.g. tidal) to months (e.g. seasonal), bridging a critical knowledge gap in ocean acidification research. The amount of anthropogenic carbon in a given water mass is dependent on the age, therefore a density-age relationship was derived for the study region, and was combined with the 2013 Intergovernmental Panel on Climate Change CO2 emission scenarios to add density-dependent anthropogenic carbon to the sensor time series. The model was applied to time series from four autonomous pH sensors, each deployed in the surf zone, kelp forest, submarine canyon edge, and shelf break in the upper 100m of the Southern California Bight. All habitats were within 5 km of one another, and exhibited unique, habitat-specific CO2 variability signatures and acidification trajectories, demonstrating the importance of making projections in the context of habitat-specific CO2 2signatures. In general, both the mean and range of pCO2 increase in the future, with the greatest increases in both magnitude and range occurring in the deeper habitats due to reduced buffering capacity. On the other hand, the saturation state of aragonite (ΩAr) decreased in both magnitude and range. This approach can be applied to the entire California Current System, and upwelling margins in general, where sensor and complementary hydrographic data are available. [ABSTRACT FROM AUTHOR]

Degradation of coastal ecosystems by eutrophication is largely defined by nitrogen loading from land via surface and groundwater flows. However, indicators of water quality are highly variable due to a myriad of other drivers, including temperature and precipitation. To evaluate these drivers, we examined spatial and temporal trends in a 22 year record of summer water quality data from 122 stations in 17 embayments within Buzzards Bay, MA (USA), collected through a citizen science monitoring program managed by Buzzards Bay Coalition. To identify spatial patterns across Buzzards Bay's embayments, we used a principle component and factor analysis and found that rotated factor loadings indicated little correlation between inorganic nutrients and organic matter and chlorophyll a (Chl a) concentration. Factor scores showed that embayment geomorphology in addition to nutrient loading was a strong driver of water quality, where embayments with surface water inputs showed larger biological impacts than embayments dominated by groundwater influx. A linear regression analysis of annual summertime water quality indicators over time revealed that from 1992 to 2013, most embayments (15 of 17) exhibited an increase in temperature (mean rate of 0.082 ± 0.025 (SD) °C yr-1) and Chl a (mean rate of 0.0171 ± 0.0088 log10 (Chl a; mgm-3)yr-1, equivalent to a 4.0% increase per year). However, only 7 embayments exhibited an increase in total nitrogen (TN) concentration (mean rate 0.32 ± 0.47 (SD)μM yr-1). Average summertime log10 (TN) and log10 (Chl a) were correlated with an indication that yield of Chl a per unit total nitrogen increased with time suggesting the estuarine response to TN may have changed because of other stressors such as warming, altered precipitation patterns, or changing light levels. These findings affirm that nitrogen loading and physical aspects of embayments are essential in explaining observed ecosystem response. However, climate-related stressors may also need to be considered by managers because increased temperature and precipitation may worsen water quality and partially offset benefits achieved by reducing nitrogen loading. [ABSTRACT FROM AUTHOR]

Climate change impacts on the marine biogeochemistry and lower trophic level dynamics in the North Sea and Baltic Sea have been assessed using regional downscaling in a number of recent studies. However, most of these where only forced by physical conditions from Global Climate Models (GCMs) and regional downscaling considering the climate change impact on oceanic nutrient conditions from Global Earth System Models (ESMs) are rare and so far solely based on CMIP3-generation climate models. The few studies published show a large range in projected future primary production and hydrodynamic condition. With the addition of CMIP5 models and scenarios, the demand to explore the uncertainty in regional climate change projections increased. Moreover, the question arises how projections based on CMIP5-generation models compare to earlier projections and multi-model ensembles comprising both AR4 and AR5 generation forcing models. Here, we investigated the potential future climate change impacts to the North Sea and the Baltic Sea ecosystem using a coherent regional downscaling strategy based on the regional coupled bio-physical model ECOSMO. ECOSMO was forced by output from different ESMs from both CMIP3 and CMIP5 models. Multi-model ensembles using CMIP3/A1B and CMIP5/RCP4.5 scenarios are examined, where the selected CMIP5 models are the successors of the chosen CMIP3 models. Comparing projected changes with the present day reference condition, all these simulations predicted an increase in Sea Surface Temperature (SST) in both North Sea and Baltic Sea, reduction in sea ice in the Baltic, decrease in primary production in the North Sea and an increase in primary production in the Baltic Sea. Despite these largely consistent results on the direction of the projected changes, our results revealed a broad range in the amplitude of projected climate change impacts. Our study strengthens the claim that the choice of the ESM is a major factor for regional climate projections. The change in oceanic nutrient input appeared to be the major driver for the projected changes in North Sea primary production. Assessing the spread in ensemble groups, we found that there is for the North Sea a significant reduction in the spread of projected changes among CMIP5 forced model simulations compared to those forced by CMIP3 ESMs, except for salinity. The latter was due to an unexpected salinification observed in one of the CMIP5 model while all other models exhibit freshening in the future. However, for the Baltic Sea substantial differences in inter-model variability in projected climate change impact to primary production is lacking. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a bending angle radio occultation climatology (BAROCLIM) based on Formosat-3/COSMIC (F3C) data. This climatology represents the monthlymean atmospheric state from 2006 to 2012. Bending angles from radio occultation (RO) measurements are obtained from the accumulation of the change in the raypath direction of Global Positioning System (GPS) signals. Best quality of these nearvertical profiles is found from the middle troposphere up to the mesosphere. Beside RO bending angles we also use data from the Mass Spectrometer and Incoherent Scatter Radar (MSIS) model to expand BAROCLIM in a spectral model, which (theoretically) reaches from the surface up to infinity. Due to the very high quality of BAROCLIM up to the mesosphere, it can be used to detect deficiencies in current state-of-the-art analysis and reanalysis products from numerical weather prediction (NWP) centers. For bending angles derived from European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields from 2006 to 2012, e.g., we find a positive bias of 0.5% to 1% at 40 km, which increases to more than 2% at 50 km. BAROCLIM can also be used as a priori information in RO profile retrievals. In contrast to other a priori information (i.e., MSIS) we find that the use of BAROCLIM better preserves the mean of raw RO measurements. Global statistics of statistically optimized bending angle and refractivity profiles also confirm that BAROCLIM outperforms MSIS. These results clearly demonstrate the utility of BAROCLIM. [ABSTRACT FROM AUTHOR]

We review the main factors driving the calculation of the tangent height of spaceborne limb measurements: the ray-tracing method, the refractive index model and the assumed atmosphere. We find that commonly used ray-tracing and refraction models are very accurate, at least in the middle-infrared. The factor with largest effect in the tangent height calculation is the assumed atmosphere. Using a climatological model in place of the real atmosphere may cause tangent height errors up to ±200 m. Depending on the adopted retrieval scheme, these errors may have a significant impact on the derived profiles. [ABSTRACT FROM AUTHOR]

An important component of the risks from climate change arises from outcomes that are very unlikely, but whose impacts if they were to occur would be extremely severe. Examples include levels of surface warming, or changes in the water cycle, that are at the extreme of plausible ranges, or crossing of a climate system "tipping point" such as ice sheet or ocean circulation instability. If such changes were to occur their impacts on infrastructure or ecosystems may exceed existing plans for adaptation. The traditional approach of ensemble climate change projections is not well suited to managing these High Impact‐Low Likelihood (HILL) risks, where the objective is to "prepare for the worst" rather than to "plan for what's likely." In this paper we draw together a number of ideas from recent literature, to classify four types of HILL climate outcome and to propose the development of a practical "toolkit" of physical climate information that can be used in future to inform HILL risk management. The toolkit consists of several elements that would need to be developed for each plausible HILL climate outcome, then deployed individually to develop targeted HILL risk management approaches for individual sectors. We argue that development of the HILL toolkit should be an important focus for physical climate research over the coming decade, and that the time is right for a focused assessment of HILL risks by the Intergovernmental Panel on Climate Change in its 7th Assessment Cycle. Plain Language Summary: To prepare for the risks that arise from climate change (and avoid them where possible), it is important to understand how climate is likely to change in future, and what the impacts are likely to be. Over many years, climate science has developed sophisticated climate projections to estimate these likely impacts, and these are widely used to plan how people and societies will need to adapt to climate change. However it is also important to understand possibilities that are unlikely, but would have even more severe impacts if they did occur—for example, global warming levels at the high end of plausible estimates, or crossing a "tipping point" for major changes in ice sheets or ocean currents. A different type of information is needed to plan for these risks. In this paper we propose a new set of climate information "tools" to respond to these high‐impact risks. The tools include plausible scenarios of extreme outcomes, and early warning systems to detect if they are on the horizon. Combining these new tools with existing climate projections will allow society to understand more fully the risks of climate change, and to plan for the likely effects while preparing for the worst. Key Points: Climate outcomes or events that have a high impact are a key component of climate risk, even if their likelihood is lowTraditional climate projections are of limited use to inform management of high impact‐low likelihood risksPhysical climate science needs an increased focus on storylines, early warning and monitoring to inform management of high impact risks [ABSTRACT FROM AUTHOR]

We introduce and document the first version of the Centre National de Recherches Météorologiques Earth system model (CNRM-ESM1). This model is based on the physical core of the CNRM-CM5 model and employs the Interactions between Soil, Bio-sphere and Atmosphere (ISBA) module and the Pelagic Interaction Scheme for Carbon and Ecosystem Studies (PISCES) as terrestrial and oceanic components of the global carbon cycle. We describe a preindustrial and 20th century climate simulation following the CMIP5 protocol. We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers. CNRM-ESM1 reproduces satisfactorily several aspects of the modern carbon cycle. On land, the model reasonably captures the carbon cycling through vegetation and soil, resulting in a net terrestrial carbon sink of 2.2 PgCy-1. In the ocean, the large-scale distribution of hydrodynamical and biogeochemical tracers agrees well with a modern climatology from the World Ocean Atlas. The combination of biological and physical processes induces a net CO2 uptake of 1.7 PgCy-1 that falls within the range of recent estimates. Our analysis shows that the atmospheric climate of CNRM-ESM1 compares well with that of CNRM-CM5. Biases in precipitation and shortwave radiation over the Tropics generate errors in gross primary productivity and ecosystem respiration. Compared to CNRM-CM5, the revised ocean-sea ice coupling has modified the sea-ice cover and ocean ventilation, unrealistically strengthening the flow of North Atlantic deep water (26.1±2 Sv). It results in an accumulation of anthropogenic carbon in the deep ocean. [ABSTRACT FROM AUTHOR]