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Understanding carbon sources and sinks across the Earth's surface is fundamental in climate science and policy; thus, these topics have been extensively studied but have yet to be fully resolved and are associated with massive debate regarding the sign and magnitude of the carbon budget from global to regional scales. Developing new models and estimates based on state-of-the-art algorithms and data constraints can provide valuable knowledge and contribute to a final ensemble model in which various optimal carbon budget estimates are integrated, such as the annual global carbon budget paper. Here, we develop a new atmospheric inversion system based on the 4D local ensemble transform Kalman filter (4D-LETKF) coupled with the GEOS-Chem global transport model to infer surface-to-atmosphere net carbon fluxes from Orbiting Carbon Observatory-2 (OCO-2) V10r XCO 2 retrievals. The 4D-LETKF algorithm is adapted to an OCO-2-based global carbon inversion system for the first time in this work. On average, the mean annual terrestrial and oceanic fluxes between 2015 and 2020 are estimated as - 2.02 and - 2.34 GtC yr -1 , respectively, compensating for 21 % and 24 %, respectively, of global fossil carbon dioxide (CO 2) emissions (9.80 GtC yr -1). Our inversion results agree with the CO 2 atmospheric growth rates reported by the National Oceanic and Atmospheric Administration (NOAA) and reduce the modeled CO 2 concentration biases relative to the prior fluxes against surface and aircraft measurements. Our inversion-based carbon fluxes are broadly consistent with those provided by other global atmospheric inversion models, although discrepancies still occur in the land–ocean flux partitioning schemes and seasonal flux amplitudes over boreal and tropical regions, possibly due to the sparse observational constraints of the OCO-2 satellite and the divergent prior fluxes used in different inversion models. Four sensitivity experiments are performed herein to vary the prior fluxes and uncertainties in our inversion system, suggesting that regions that lack OCO-2 coverage are sensitive to the priors, especially over the tropics and high latitudes. In the further development of our inversion system, we will optimize the data-assimilation configuration to fully utilize current observations and increase the spatial and seasonal representativeness of the prior fluxes over regions that lack observations. [ABSTRACT FROM AUTHOR]

A comparison of retrieved total column ozone amounts TCO between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado NOAA building. This paper, part of an ongoing study, covers a one-year period starting on 17 December 2013. Both the standard Dobson and Pandora total column ozone TCO retrievals required a correction TCOcorr=TCO (1+C(T )) using the effective climatology derived ozone temperature T to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(T ) are CPandora = 0.00333(T-225) and CDobson = -0.0013(T-226.7) per K. After the applied corrections removed the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1% for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r² = 0.97 and an average offset of 1.1±5.8 DU. In addition, the Pandora data showed 0.3% annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1% annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite). [ABSTRACT FROM AUTHOR]

A compilation of several cruises data from 1998 to 2013 was used to derive polynomial fits that estimate total alkalinity (AT) and total inorganic carbon (CT) from measurements of salinity and temperature in the Mediterranean Sea surface waters. The optimal equations were chosen based on the 10-fold cross validation results and revealed that a second and third order polynomials fit the AT and CT data respectively. The AT surface fit showed an improved root mean square error (RMSE) of ±10.6 μmol kg-1. Furthermore we present the first annual mean CT parameterization for the Mediterranean Sea surface waters with a RMSE of ±14.3 μmol kg-1. Excluding the marginal seas of the Adriatic and the Aegean, these equations can be used to estimate AT and CT in case of the lack of measurements. The seven years averages (2005-2012) mapped using the quarter degree climatologies of the World Ocean Atlas 2013 showed that in surface waters AT and CT have similar patterns with an increasing eastward gradient. The surface variability is influenced by the inflow of cold Atlantic waters through the Strait of Gibraltar and by the oligotrophic and thermohaline gradient that characterize the Mediterranean Sea. The summer-winter seasonality was also mapped and showed different patterns for AT and CT. During the winter, the AT and CT concentrations were higher in the western than in the eastern basin, primarily due to the deepening of the mixed layer and upwelling of dense waters. The opposite was observed in the summer where the eastern basin was marked by higher AT and CT concentrations than in winter. The strong evaporation that takes place in this season along with the ultra-oligotrophy of the eastern basin determines the increase of both AT and CT concentrations. [ABSTRACT FROM AUTHOR]

A 30-year (1980–2010) climatology of the major variables and terms of the transformed Eulerian-mean (TEM) momentum and thermodynamic equations is constructed by using four global atmospheric reanalyses: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2); the Japanese 55-year Reanalysis (JRA-55); the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim); and the Climate Forecast System Reanalysis (CFSR). Both the reanalysis ensemble mean (REM) and the differences in each reanalysis from the REM are investigated in the latitude–pressure domain for December–January–February and for June–July–August. For the REM investigation, two residual vertical velocities (the original one and one evaluated from residual meridional velocity) and two mass streamfunctions (from meridional and vertical velocities) are compared. Longwave (LW) radiative heating and shortwave (SW) radiative heating are also shown and discussed. For the TEM equations, the residual terms are also calculated and investigated for their potential usefulness, as the residual term for the momentum equation should include the effects of parameterized processes such as gravity waves, while that for the thermodynamic equation should indicate the analysis increment. Inter-reanalysis differences are investigated for the mass streamfunction, LW and SW heating, the two major terms of the TEM momentum equation (the Coriolis term and the Eliassen–Palm flux divergence term), and the two major terms of the TEM thermodynamic equation (the vertical temperature advection term and the total diabatic heating term). The spread among reanalysis TEM momentum balance terms is around 10 % in Northern Hemisphere winter and up to 50 % in Southern Hemisphere winter. The largest uncertainties in the thermodynamic equation (about 50 %) are found in the vertical advection, for which the structure is inconsistent with the differences in heating. The results shown in this paper provide basic information on the degree of agreement among recent reanalyses in the stratosphere and upper troposphere in the TEM framework. [ABSTRACT FROM AUTHOR]

Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods is moderate, and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM) for 8 regions in Europe to construct time evolving climate networks and use the network correlation threshold (link strength) as a predictor for heat periods. We show that the skill of the network measure to predict the low frequency dynamics of heat periods is similar to the one of the standard approach, with the potential of being even better in some regions. [ABSTRACT FROM AUTHOR]

Almost all climate time series have some degree of nonstationarity due to external driving forces perturbations of the observed system. Therefore, these external driving forces should be taken into account when reconstructing the climate dynamics. This paper presents a new technique of combining the driving force of a time series obtained using the Slow Feature Analysis (SFA) approach, then introducing the driving force into a predictive model to predict non-stationary time series. In essence, the main idea of the technique is to consider the driving forces as state variables and incorporate them into the prediction model. To test the method, experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted. The results showed improved and effective prediction skill. [ABSTRACT FROM AUTHOR]

In this paper, a new issue that very low relative humidity observations exist in a deeper atmosphere layer in the low- and mid-troposphere is studied on the basis of the global radiosonde observations from December 2008 to November 2009, and the humidity retrieval productions from Formosa Satellite mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC, referred to as COSMIC hereafter) in the same period. Results show that these extremely dry relative humidity observations are considerable universal in the worldwide operational radiosonde data. Globally, the annual average occurrence probability of the extremely dry relative humidity is of 4.2 %. These measurements usually occur between 20° and 40° latitudes in both Northern and Southern Hemispheres, and in the height from 700 to 450 hPa in the low- and mid-troposphere. Winter and spring are the favoured seasons for these extremely dry humidity observations, with the maximum ratio of 9.53% in the Northern Hemisphere and 16.82% in the Southern Hemisphere. The phenomenon is mainly related to the performance of the radiosonde humidity sensor and the cloud types traversed by the radiosonde balloon. These extremely low relative humidity observations are erroneous, which cannot represent the real atmospheric status, and are likely caused by the failure of humidity sensor. However, these observations have been archived as the formal data. It will affect the reliability of numerical weather prediction, the analysis of weather and climate, if the quality control procedure is not applied. [ABSTRACT FROM AUTHOR]

In the current work we present six hindcast Weather Research and Forecasting (WRF) simulations for the EURO-CORDEX domain with different configurations in microphysics, convection and radiation for the time period 1990-2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic biases in both temperature and precipitation linked to different physical mechanisms for the summer and winter season. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly when using Grell-Devenyi convection and the CAM radiation scheme, intensifies the negative summer temperature bias in northern Europe (max -2.5 °C). Conversely, a strong positive downward shortwave summer bias in central (40-60 %) and southern Europe mitigates the systematic cold bias in WRF over these regions, signifying a typical case of error compensation. Maximum winter cold bias is over north-eastern Europe (-2.8 °C); this location is indicative of land-atmosphere rather than cloud-radiation interactions. Precipitation is systematically overestimated in summer by all model configurations, especially the higher quantiles, which are associated with summertime deep cumulus convection. The Kain-Fritsch convection scheme produces the larger summertime precipitation biases over the Mediterranean. Winter precipitation is reproduced with lower biases by all model configurations (15-30 %). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature-precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest methodologies for model improvement. [ABSTRACT FROM AUTHOR]

Data assimilation systems and retrieval systems that are based upon a maximum likelihood estimation, many of which are in operational use, rely on the assumption that all of the errors and variables involved follow a normal distribution. This work develops a series of statistical tests to show that mixing ratio, temperature, wind and surface pressure follow non-normal, or in fact, lognormal distributions thus impacting the design-basis of many operational data assimilation and retrieval systems. For this study one year of Global Forecast System 00:00 UTC 6 h forecast were analyzed using statistical hypothesis tests. The motivation of this work is to identify the need to resolve whether or not the assumption of normality is valid and to give guidance for where and when a data assimilation system or a retrieval system needs to adapt its cost function to the mixed normal-lognormal distribution-based Bayesian model. The statistical methods of detection are based upon Shapiro-Wilk, Jarque-Bera and a χ² test, and a new composite indicator using all three measures. Another method of detection fits distributions to the temporal-based histograms of temperature, mixing ratio, and wind. The conclusion of this work is that there are persistent areas, times, and vertical levels where the normal assumption is not valid, and that the lognormal distribution-based Bayesian model is observationally justified to minimize the error for these conditions. The results herein suggest that comprehensive statistical climatologies may need to be developed to capture the non-normal traits of the 6 h forecast. [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]

An artificial neural network cloud classification scheme is combined with A-Train observations to characterize the physical properties and radiative effects of marine low clouds based on their morphology and type of mesoscale cellular convection (MCC) on a global scale. The cloud morphological categories are (i) organized closed MCC, (ii) organized open MCC and (iii) cellular but disorganized MCC. Global distributions of the frequency of occurrence of MCC types show clear regional signatures. Organized closed and open MCCs are most frequently found in subtropical regions and in mid-latitude storm tracks of both hemispheres. Cellular but disorganized MCC are the predominant type of marine low clouds in regions with warmer sea surface temperature such as in the tropics and trade wind zones. All MCC types exhibit a pronounced seasonal cycle. The physical properties of MCCs such as cloud fraction, radar reflectivity, drizzle rates and cloud top heights as well as the radiative effects of MCCs are found highly variable and a function of the type of MCC. On a global scale, the cloud fraction is largest for closed MCC with mean cloud fractions of about 90%whereas cloud fractions of open and cellular but disorganized MCC are only about 51% and 40 %, respectively. Probability density functions (PDFs) of cloud fractions are heavily skewed and exhibit modest regional variability. PDFs of column maximum radar reflectivities and inferred cloud base drizzle rates indicate fundamental differences in the cloud and precipitation characteristics of different MCC types. Similarly, the radiative effects of MCCs differ substantially from each other in terms of shortwave reflectance and transmissivity. These differences highlight the importance of low cloud morphologies and their associated cloudiness on the shortwave cloud forcing. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the static pressure on a research aircraft in accelerated flight. Geometric altitude data from an integrated inertial measurement unit (IMU) and a Global Navigation Satellite System (GNSS) on the King Air research aircraft of the University of Wyoming is investigated. Differences in pressure measurements during the accelerated flights of research aircrafts are outlined.

This paper details updates to the Met Office's operational coupled hydrodynamicecosystem model from the Medium-Resolution Continental Shelf - POLCOMSERSEM (MRCS-PE) system (Siddorn et al., 2007) to the 7km Atlantic Margin Model NEMO-ERSEM (AMM7-NE) system. We also provide a validation of the ecosystem component of the new operational system. Comparisons have been made between the model variables and available in situ, satellite and climatological data. The AMM7-NE system has also been benchmarked against the MRCS-PE system. The transition to the new AMM7-NE system was successful and it has been running op erationally since March 2011 and has been providing products through MyOcean (http://www.myocean.eu.org) since July 2011. The results presented herein show the AMM7-NE system performs better than the MRCS-PE system with the most improvement in the model nutrient fields. The problem of nutrient accumulation in the MRCSPE system appears to be solved in the new AMM7-NE system with nutrient dynamics improved throughout the domain. Improvements in model chlorophyll are also seen but are more modest. [ABSTRACT FROM AUTHOR]

The article focuses on the metrics used for comparing greenhouse gases with focus on the Integrated Temperature Change Potential (IGTP). It states that the IGTP and global warming potentials (GWP) are asymptotically equal is the time horizon reaches infinity. It says that the IGTP is equal to the Sustained Global Temperature change Potential (SGTP) under standard assumptions when calculating GWPs.

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]

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]

Within the ESA Climate Change Initiative (CCI) project Aerosol cci (2010-2013) algo rithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to under stand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to pro vide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components and their mixing ratios. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data qualitatively by visible analysis of monthly mean AOD maps and quantitatively by comparing global daily gridded satellite data against daily average AERONET sun photometer observations for the different versions of each algorithm. The analysis allowed an assessment of sensitivities of all algorithms which helped define the best algorithm version for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. [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]

In atmospheric modelling applications the aerosol particle size distribution is commonly represented by modal approach, in which particles in different size ranges are described with log-normal modes within predetermined size ranges. Such method in- cludes numerical reallocation of particles from a mode to another for example during particle growth, leading to potentially artificial changes in the aerosol size distribution. In this study we analysed how this reallocation affects climatologically relevant parameters: cloud droplet number concentration, aerosol-cloud interaction coefficient and light extinction coefficient. We compared these parameters between a modal model with and without reallocation routines, and a high resolution sectional model that was considered as a reference model. We analysed the relative differences of the parameters in different experiments that were designed to cover a wide range of dynamic aerosol processes occurring in the atmosphere. According to our results, limiting the allowed size ranges of the modes and the following numerical remapping of the distribution by reallocation, leads on average to underestimation of cloud droplet number concentration (up to 100 %) and overestimation of light extinction (up to 20 %). The analysis of aerosol first indirect effect is more complicated as the ACI parameter can be either over- or underestimated by the reallocating model, depending on the conditions. However, for example in the case of atmospheric new particle formation events followed by rapid particle growth, the reallocation can cause around average 10% overestimation of the ACI parameter. Thus it is shown that the reallocation affects the ability of a model to estimate aerosol climate effects accurately, and this should be taken into account when using and developing aerosol models. [ABSTRACT FROM AUTHOR]

In this paper, we present a description of the tropospheric chemistry component of the UK Chemistry and Aerosols (UKCA) model which has been coupled to the Met Office Hadley Centre's HadGEM family of climate models. We assess the model's transport and scavenging processes, in particular focussing on convective transport, boundary layer mixing, wet scavenging and inter-hemispheric exchange. Simulations with UKCA of the short-lived radon tracer suggest that modelled distributions are comparable to those of other models and the comparison with observations indicate that apart from a few locations, boundary layer mixing and convective transport are effective in the model as a means of vertically re-distributing surface emissions of radon. Comparisons of modelled lead tracer concentrations with observations suggest that UKCA captures surface concentrations in both hemispheres very well although there is a tendency to underestimate the observed geographical and interannual variability in the Northern Hemisphere. In particular, UKCA replicates the shape and absolute concentrations of observed lead profiles, a key test in the evaluation of a model's wet scavenging scheme. The timescale for inter-hemispheric transport, calculated in the model using a simple krypton tracer experiment, does appear to be long relative to other models and could indicate deficiencies in tropical deep convection and/or insufficient boundary layer mixing. We also describe the main components of the tropospheric chemistry and evaluate it against observations and other tropospheric chemistry models. In particular, from a climate forcing perspective, present-day observed surface methane concentrations and tropospheric ozone concentrations are reproduced very well by the model, thereby making it suitable for long centennial integrations as well as studies of biogeochemical feedbacks. Results from both historical and future simulations with UKCA tropospheric chemistry are presented. Future projections of tropospheric ozone vary with the Representative Concentration Pathway (RCP). In RCP2.6, for example, tropospheric ozone increases up to 2010 and then declines by 13% of its year-2000 global mean by the end of the century. In RCP8.5, tropospheric ozone continues to steadily rise throughout the 21st century, with methane being the main driving factor. Finally, we highlight aspects of the UKCA model which are undergoing and/or have undergone recent developments and are suitable for inclusion in a next-generation Earth System Model. [ABSTRACT FROM AUTHOR]

The article presents a study which provides reference publication on the description of the land-surface precipitation data products of the Global Precipitation Climatology Centre (GPCC) with applications such as centennial trend analysis. The study employs interpolation of gauge data, gridding method, and Kriging interpolation. It says that sample applications provide potential users of GPCC data products information regarding the constraints and capabilities of the gridded data sets.

The article presents a study which explored the mid-Pliocene and pre-indusrial atmosphere general circulation models (AGCM) simulations, with Norwegian Earth System Model (NorESM-L). The study evaluated he potential uncertainties in the analysis of climate anomalies in the mid-Pliocene period. Results showed that the uncertainties in mid-Pliocene climate anomaly analyses are large in terms of regional scale, but small on a global scale.

We present a methodology to correct precipitation fluxes from the ECMWF atmospheric reanalysis (ERA-Interim) for oceanographic applications. The correction is performed by means of a spatially varying monthly climatological coefficient, computed within the period 1989-2008 by comparison between ERA-Interim and a satellite-based passive microwave precipitation product. ERA-Interim exhibits a systematic over-estimation of precipitation within the inter-tropical convergence zones (up to 3mmd-1) and underestimation at mid- and high- latitudes (up to -4mmd-1). The correction has been validated within eddy-permitting resolution global ocean hindcasts (1989-2009), demon strating the ability of our strategy in attenuating the 20-yr mean global EMP negative imbalance by 16 %, reducing the near-surface salinity fresh bias in the Tropics up to 1 psu and improving the representation of the sea level interannual variability, with an SSH error decrease of 8%. The ocean circulation is also proved to benefit from the correction, especially in correspondence of the Antarctic Circumpolar Current, where the error in the near-surface current speed decreases by a 9%. Finally, we show that the correction leads to volume and freshwater transports that better agree with independent estimates. [ABSTRACT FROM AUTHOR]

The article discusses the interpretation and definition of quantities relating to climate sensitivity in the discussions paper "Climate sensitivity in the Anthropocene," by M. Previdi and colleagues. It states that the paper brought several errors and inconsistencies in the discussion of climate sensitivity. It says that definition of temperature which denoted surface temperature was inconsistent.

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]

The upper troposphere/lower stratosphere (UTLS) plays a crucial role in the climate system. Changes in the composition and dynamic structure of this atmospheric region result in particularly large changes in the atmospheric radiation balance. Quantifying the physical and chemical processes that control UTLS composition therefore represents an important task. Currently, there is a lack of UTLS observations with sufficient three-dimensional resolution. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) aircraft instrument addresses this observational lack by providing observations of numerous trace constituents as well as temperature and cloud structures with an unprecedented combination of vertical resolution (up to 300 m) and horizontal resolution (up to 20kmx20km). As a result, important scientific questions concerning stratosphere-troposphere-exchange, the occurrence of subvisible cirrus clouds in the lowermost stratosphere (LMS), polar chemistry and gravity wave processes can be addressed, as reviewed in this paper. [ABSTRACT FROM AUTHOR]

The ammonia cycle and nitrate particle formation have been introduced in the LMDz- INCA global model. Both fine nitrate particles formation in the accumulation mode and coarse nitrate forming on existing dust and sea-salt particles are considered. The model simulates distributions of nitrates and related species in agreement with previous studies and observations. The calculated present-day total nitrate direct radiative forcing since the pre-industrial is -0.056Wm-2. This forcing has the same magnitude than the forcing associated with organic carbon particles and represents 18% of the sulfate forcing. Fine particles largely dominate the nitrate forcing representing close to 90% of this value. The model has been used to investigate the future changes in nitrates and direct radiative forcing of climate based on snapshot simulations for the four Representative Concentration Pathway (RCP) scenarios and for the 2030, 2050 and 2100 time horizons. Due to a decrease in fossil fuel emissions in the future, the concentrations of most of the species involved in the nitrate-ammonium-sulfate system drop by 2100 except for ammonia which originates from agricultural practices and for which emissions significantly increase in the future. Despite the decrease of nitrate surface levels in Europe and Northern America, the global burden of accumulation mode nitrates increases by up to a factor of 2.6 in 2100. This increase in nitrate in the future arises despite decreasing NOx emissions due to increased availability of ammonia to form ammonium nitrate. The total aerosol direct forcing decreases from its present-day value of -0.234Wm-2 to a range of -0.070 to -0.130Wm-2 in 2100 based on the considered scenario. The direct forcing decreases for all aerosols except for nitrates for which the direct negative forcing increases to a range of -0.060 to -0.115Wm-2 in 2100. Including nitrates in the radiative forcing calculations increases the total direct forcing of aerosols by a factor of 1.3 in 2000, by a factor of 1.7-2.6 in 2030, by 1.9-4.8 in 2050 and by 6.4-8.6 in 2100. These results show that agricultural emissions of ammonia will play a key role in the future mitigation of climate change with nitrates becoming the dominant contributor to the anthropogenic aerosol optical depth during the second half of the XXIst century and significantly increasing the calculated aerosol direct forcing. This significant increase in the influence that nitrate exert on climate in the future will at the same time affect regional air quality and nitrogen deposition to the ecosystems. [ABSTRACT FROM AUTHOR]

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]

The launch of the US/French mission Topex/Poseidon (T/P) (CNES/NASA) in August 1992 was the start of a revolution in oceanography. For the first time, a very precise altimeter system optimized for large scale sea level and ocean circulation observations was flying. T/P alone could not observe the mesoscale circulation. In the 1990s, the ESA satellites ERS-1/2 were flying simultaneously with T/P. Together with my CLS colleagues, we demonstrated that we could use T/P as a reference mission for ERS-1/2 and bring the ERS-1/2 data to an accuracy level comparable to T/P. Near real time high resolution global sea level anomaly maps were then derived. These maps have been operationally produced as part of the SSALTO/DUACS system for the last 15 yr. They are now widely used by the oceanographic community and have contributed to a much better understanding and recognition of the role and importance of mesoscale dynamics. Altimetry needs to be complemented with global in situ observations. In the end of the 90s, a major international initiative was launched to develop Argo, the global array of profiling floats. This has been an outstanding success. Argo floats now provide the most important in situ observations to monitor and understand the role of the ocean on the earth climate and for operational oceanography. This is a second revolution in oceanography. The unique capability of satellite altimetry to observe the global ocean in near real time at high resolution and the development of Argo were essential to the development of global operational oceanography, the third revolution in oceanography. The Global Ocean Data Assimilation Experiment (GODAE) was instrumental in the development of the required capabilities. This paper provides an historical perspective on the development of these three revolutions in oceanography which are very much interlinked. This is not an exhaustive review and I will mainly focus on the contributions we made together with many colleagues and friends. [ABSTRACT FROM AUTHOR]

The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the European platform ENVISAT was dedicated to the study of the atmosphere of the Earth using the stellar occultation technique. The spectral range of the GOMOS spectrometer extends from the UV to the near infrared, allowing for the retrieval of species such as O3, NO2, NO3, H2O, O2, air density, aerosol extinction and OCIO. Nevertheless, OCIO can not be retrieved using a single GOMOS measurement because of the weak signal-to-noise ratio and the small optical thickness associated with this molecule. We present here the method used to detect this molecule by using several GOMOS measurements. It is based on a two-step approach. First, several co-located measurements are combined in a statistical way to build an averaged measurement with a higher signal-to-noise ratio. Then, a Differential Optical Absorption Spectroscopy (DOAS) method is applied to retrieve OCIO slant column densities. The statistics of the sets of GOMOS measurements used to build the averaged measurement and the spectral window selection are analyzed. The obtained retrievals are compared to results from two balloon-borne instruments. It appears that the inter-comparisons of OCIO are generally satisfying. Then, two nighttime climatologies of OCIO slant column densities based on GOMOS averaged measurements are presented. The first depicts annual global pictures of OCIO from 2003 to 2011. From this climatology, the presence of an OCIO layer in the equatorial region at about 35km is confirmed and strong concentrations of OCIO in both polar regions are observed, a sign of chlorine activation. The second climatology is a monthly time series. It clearly shows the chlorine activation of the lower stratosphere during winter. Moreover the equatorial OCIO layer is observed during all the years without any significant variations. Finally, the anti-correlation between OCIO and NO2 is highlighted. This very promising method, applied on GOMOS measurements, allowed us to build the first nighttime climatology of OCIO [ABSTRACT FROM AUTHOR]

A method for detailed evaluation of a new satellite-derived global 28-yr cloud and radiation climatology (Climate Monitoring SAF Cloud, Albedo and Radiation dataset from AVHRR data, named CLARA-A1) from polar orbiting NOAA and Metop satellites is presented. The method combines 1 km and 5 km resolution cloud datasets from the CALIPSO-CALIOP cloud lidar for estimating cloud detection limitations and the accuracy of cloud top height estimations. Cloud detection is shown to work efficiently for clouds with optical thicknesses above 0.30 except for at twilight conditions when this value increases to 0.45. Some misclassifications generating erroneous clouds over land surfaces in semi-arid regions in the sub-tropical and tropical regions are revealed. In addition, a substantial fraction of all clouds remains undetected in the Polar regions during the polar winter season due to the lack of or an inverted temperature contrast between Earth surfaces and clouds. Subsequent cloud top height evaluation took into account the derived information about the cloud detection limits. It was shown that this has fundamental importance for the achieved results. An overall bias of -274m was achieved compared to a bias of -2762m if no measures were taken to compensate for cloud detection limitations. Despite this improvement it was concluded that high-level clouds still suffer from substantial height underestimations while the opposite is true for low-level (boundary layer) clouds. The validation method and the specifically collected satellite dataset with optimal matching in time and space are suggested for a wider use in the future for evaluation of other cloud retrieval methods based on passive satellite imagery. [ABSTRACT FROM AUTHOR]

The article presents a tagging method, which helps in calculating contribution of individual processes or quantities on state variables for application in climatechemistry models. It also presents 15 differential equations for these contributions or tagged quantities or species. It also discusses possibilities and limitations of this method.

The article presents a study which investigates the comparison of the surface skin temperatures between MODIS and atmospheric infrared sounder (AIRS)/Advanced microwave sounding unit (AMSU) in terms of their trends and climatology. The study uses the bootstrap method to calculate the 95% confidence interval. Results show that the trends of the surface skin temperature from MODIS has revealed a stronger warming values than from AIRS/AMSU over the high latitude oceans.