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The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño-Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of -0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (-0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (-0.66), with precipitation leading by 4-5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 Pg C yr-1 K-1 and -0.46 ± 0.07 Pg C yr-1 100 mm-1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land-atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 Pg C yr-1 K-1 and -0.67 ± 0.04 Pg C yr-1 100 mm-1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than soil respiration. Because NPP is largely driven by precipitation, this suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such "emergent constraint". [ABSTRACT FROM AUTHOR]

Synergistic exploitation of redundant and complementary information from independent observations of the same target remains a major issue in atmospheric remote-sounding and increasing attention is devoted to investigate optimised or innovative methods for the combination of two or more measured data sets. This paper is focusing on the synergy between middle infrared and millimetre-wave limb sounding measurements of atmospheric composition and temperature and reports the results of a study conducted as part of the preparatory activities of the PREMIER (Process Exploration through Measurements of Infrared and millimetre wave Emitted Radiation) mission candidate to the Core Missions of ESA Earth Explorer 7. The activity was based on data acquired by the MIPAS-STR (Michelson Interferometer for Passive Atmospheric Sounding - STRato-spheric aircraft) and MARSCHALS (Millimetre-wave Airborne Receivers for Spectro-scopic CHaracterisation in Atmospheric Limb Sounding) instruments onboard the high altitude research aircraft M-55 Geophysica during the flight of the PremierEx (PREMIER Experiment) campaign on 10 March 2010 from Kiruna, Sweden for observation of the Arctic upper troposphere and lower stratosphere. The cloud coverage observed along the flight provided representative test cases to evaluate the synergy in three different scenarios: low clouds in the first part, no clouds in the central part and high tro-pospheric clouds at the end. The calculation of synergistic profiles of four atmospheric targets (i.e., O2, HNO3, H2O and temperature) was performed using a posteriori combination of individual retrieved profiles, i.e., Level 2 (L2) data rather than simultaneous inverse processing of observed radiances, i.e., Level 1 (L1) data. An innovative method of data fusion, based on the Measurement Space Solution (MSS) was applied along with the standard approach of inverse processing of MARSCHALS spectral radiances using MIPAS-STR retrieval products as a priori information (L1 + L2 method). A quantitative estimate and cross-check of the results of MSS and (L1 + L2) data fusion was achieved based on a specific set of quantifiers including the total retrieval error, the number of degrees of freedom, the relative information distribution and the synergy factor. [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.

This paper proposes a method that allows the detection of trends in the frequency of extreme events and its attribution to changes in atmospheric dynamics characterized through Circulation Types (CTs). The method is applied to summer Extremely Hot Days (EHD) in Spain during the period 1958-2008. For carrying out this exercise, regional series of daily maximum temperature are derived from the regional dataset Spain02. Eight regions with different daily maximum temperature variability are identified. All of them exhibit important trends in the occurrence of EHDs, especially in inner regions. Links between the probability of EHD occurrence in the regions and CTs have been cal10 culated. Furthermore, the consistency of the results to the atmospheric variables used in defining the CTs is analyzed. Sea Level Pressure (SLP), Temperature at 850 hPa Level (T850) and Geopotential Height at 500 hPa Level (Z500) from the ERA40 dataset have been used for the six CT classifications obtained using the variables separately and in different combinations of pairs. The optimum choice of large scale variables depends on the region under consideration, being the combination SLP-T850 the one giving the most suitable characterization for most of them. Finally, an attribution exercise of the regional EHD trends to the dynamics is proposed. Results show that the maximum of attributable EHD trends to changes in dynamics in every region is always below 50%, being even lower than 20% in those regions with the largest EHD trends, mainly located in the center of the Iberian Peninsula (IP). [ABSTRACT FROM AUTHOR]

This paper describes the validation of the SimSphere SVAT model conducted at different ecosystem types in the USA and Australia. Specific focus was given to examining the models' ability in predicting Shortwave Incoming Solar Radiation (Rg), Net Radiation (Rnet), Latent Heat (LE), Sensible Heat (H), Air Temperature at 1.3m (Tair 1.3m) and Air Temperature at 50m (Tair 50m). Model predictions were compared against corresponding in situ measurements acquired for a total of 72 selected days of the year 2011 obtained from 8 sites belonging to the AmeriFlux (USA) and OzFlux (Australia) monitoring networks. Selected sites were representative of a variety of environmental, biome and climatic conditions, to allow for the inclusion of contrasting conditions in the model evaluation. The application of the model confirmed its high capability in representing the multifarious and complex interactions of the Earth system. Comparisons showed a good agreement between modelled and measured fluxes, especially for the days with smoothed daily flux trends. A good to excellent agreement between the model predictions and the in situ measurements was reported, particularly so for the LE, H, Tair 1.3m and Tair 50m parameters (RMSD= 39.47, 55.06 Wm-2, 3.23, 3.77°C respectively). A systematic underestimation of Rg and Rnet (RMSD=67.83, 58.69 Wm-2, MBE= 67.83, 58.69 Wm-2 respectively) was also found. Highest simulation accuracies were obtained for the open woodland savannah and mulga woodland sites for most of the compared parameters. Very high values of the Nash-Sutcliffe efficiency index were also reported for all parameters ranging from 0.720 to 0.998, suggesting a very good model representation of the observations. To our knowledge, this study presents the first comprehensive validation of Sim- Sphere, particularly so in USA and Australian ecosystem types. Findings are important and timely, given the rapidly expanding use of this model worldwide both as an educational and research tool. This includes ongoing research by different Space Agencies examining its synergistic use with Earth Observation data towards the development of global operational products. [ABSTRACT FROM AUTHOR]

Many geophysical quantities, like atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long-range dependence (LRD). LRD means that these quantities experience non-trivial temporal memory, which potentially enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LRD. In this paper we present a modern and systematic approach to the inference of LRD. Rather than Mandelbrot's fractional Gaussian noise, we use the more flexible Autoregressive Fractional Integrated Moving Average (ARFIMA) model which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LRD, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for effcient parameter inference, and show how nuisance parameters (e.g. short memory effects) can be integrated over in order to focus on long memory parameters, and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data, with favorable comparison to the standard estimators. [ABSTRACT FROM AUTHOR]

The collision induced O2 complex, O2O2, is a very important trace gas in remote sensing measurements of aerosol and cloud properties. Some ground based MAX-DOAS measurements of O2O2 slant column density require correction factors of 0.75 ± 0.1 to reproduce radiative transfer modeling (RTM) results for a near pure Rayleigh atmosphere. One of the potential causes of this discrepancy is believed to be uncertainty in laboratory measured O2O2 absorption cross section temperature and pressure dependence, due to difficulties in replicating atmospheric conditions in the laboratory environment. This paper presents direct-sun (DS) and airborne multi-axis (AMAX) DOAS measurements of O2O2 absorption optical depths under actual Earth atmospheric conditions in two wavelength regions (335-390 nm and 435-490 nm). DS irradiance measurements were made by the research grade MFDOAS instrument from 2007-2014 at seven sites with significant pressure (778-1013hPa) and O2O2 profile weighted temperature (247-275 K) differences. Aircraft MAX-DOAS measurements were conducted by the University of Colorado AMAX-DOAS instrument on 29 January 2012 over the Southern Hemisphere subtropical Pacific Ocean. Scattered solar radiance spectra were collected at altitudes between 9 and 13.2 km, with O2O2 profile weighted temperatures of 231-244 K, and near pure Rayleigh scattering conditions. Due to the well defined DS air mass factors and extensively characterized atmospheric conditions during the AMAX-DOAS measurements, O2O2 "pseudo" absorption cross sections, σ, are derived from the observed optical depths and estimated O2O2 column densities. Vertical O2O2 columns are calculated from the atmospheric sounding temperature, pressure and specific humidity profiles. Based on the atmospheric DS observations, there is no pressure dependence of the O2O2 σ, within the measurement errors (3%). The two data sets are combined to derive peak σ temperature dependence of 360 and 477 nm absorption bands from 231-275 K. DS and AMAX derived peak σ(O2O2) as a function of T can be described by a quadratic function at 360 nm and linear at 477 nm with about 9 ± 2.5% per 44 K rate. Recent laboratory measured O2O2 cross sections by Thalman and Volkamer (2013) agree with these "DOAS apparent" peak σ(O2O2) at 233 K, 253 K and 273 K within 3 %. Changes in the O2O2 spectral band-shape at colder temperatures are for the first time also observed in field data. Temperature effects on spectral band shapes can introduce errors in the retrieved O2O2 column abundances if a single room temperature σ(O2O2) is used in the DOAS analysis. Simultaneous fitting of σ(O2O2) at temperatures that bracket the ambient temperature range can reduce such errors. Our results suggest that laboratory measured σ(O2O2) (Hermans et al. (2011) at 296 K and Thalman and Volkamer (2013)) are applicable for observations over a wide range of atmospheric conditions. Column densities derived using Hermans et al. (2011) σ at 296 K require very small correction factors (0.94 ± 0.02 at 231 K and 0.99 ± 0.02 at 275 K) to reproduce theoretically calculated SCDs for DS and AMAX-DOAS measurements. Simultaneous fitting of σ(O2O2) at 203 and 293 K further improved results at UV and visible wavelengths for AMAX-DOAS. [ABSTRACT FROM AUTHOR]

This research incorporates the Monte Carlo Independent Column Approximation (McICA) scheme with the correlated k-distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the impacts on modeled climate through several simulations with variations in cloud structures. Results from experiments with consistent sub-grid cloud structures show that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) calculated by the new scheme are mostly improved relative to those calculated from the original one. The modeled atmospheric temperature and specific humidity are also improved due to changes in the radiative heating rates. The vertical overlap of fractional clouds and horizontal distribution of cloud condensation are important for computing CRFs. The maximum changes in seasonal CRF using the general overlap assumption (GenO) with different decorrelation depths (Lcf) are larger than 10 and 20Wm2 for longwave (LW) CRF and shortwave (SW) CRF, respec15 tively, mostly located in the Tropics and mid-latitude storm tracks. Larger (smaller) Lcf in the Tropics (mid-latitude storm tracks) yield better cloud fraction and CRF compared with observations. The inclusion of an observation-based horizontal inhomogeneity of cloud condensation has a distinct impact on LW CRF and SW CRF, with global means of ∼1.2Wm-2 and ∼3.7Wm-2 at the top of atmosphere, respectively, making these much closer to observations. These results prove the reliability of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed realworld information on cloud structures should be obtained to constrain cloud settings in McICA in the future. [ABSTRACT FROM AUTHOR]

The adsorption isotherm and the mechanism of the buffering effect are important controls on phosphorus behaviors in estuaries and are important for estimating phosphate concentrations in aquatic environments. In this paper, we derive phosphate adsorption isotherms in order to investigate sediment adsorption and buffering capacity for phosphorus discharged from sewage outfalls in the Yangtze Estuary and Hangzhou Bay near Shanghai, China. Experiments were also carried out at different temperatures in order to explore the buffering effects for phosphate. The results show that P sorption in sediments with low fine particle fractions was best described using exponential equations. Some P interactions between water and sediment may be caused by the precipitation of CaHPO4 from Ca2+ and HPO42- when the phosphate concentration in the liquid phase is high. Results from the buffering experiments suggest that the Zero Equilibrium Phosphate Concentrations (EPC0) vary from 0.014 mgl-1 to 0.061 mgl-1, which are consistent with measured phosphate concentrations in water samples collected at the same time as sediment sampling. Values of EPC0 and linear sorption coefficients (K) in sediments with high fine particle and organic matter contents are relatively high, which implies that they have high buffering capacity. Both EPC0 and K increase with increasing temperature, indicating a higher P buffering capacity at high temperatures. [ABSTRACT FROM AUTHOR]

A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. This module is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a very advanced, physics-based atmosphere-to-soil-through-canopy-and-snow modelling chain. Comparisons of modelled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate the improvements of the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modelled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the night-time drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modelled dynamics of the subcanopy snowpack is analysed and yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperatures and biomass heat storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the parameterizations used. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘ C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs). [ABSTRACT FROM AUTHOR]

The mobile ocean weather observation system, named Marine Weather Observer (MWO), developed by the Institute of Atmospheric Physics (IAP), consists of a fully solar-powered, unoccupied vehicle and meteorological and hydrological instruments. One of the MWOs completed a long-term continuous observation, actively approaching the center of Typhoon Sinlaku from 24 July to 2 August 2020, over the South China Sea. The in situ and high-temporal-resolution (1 min) observations obtained from MWO were analyzed and evaluated through comparison with the observations made by two types of buoys during the evolution of Typhoon Sinlaku. First, the air pressure and wind speed measured by MWO are in good agreement with those measured by the buoys before the typhoon, reflecting the equivalent measurement capabilities of the two methods under normal sea conditions. The sea surface temperature (SST) between MWO and the mooring buoys is highly consistent throughout the observation period, indicating the high stability and accuracy of SST measurements from MWO during the typhoon evolution. The air temperature and relative humidity measured by MWO have significant diurnal variations, generally lower than those measured by the buoys, which may be related to the mounting height and sensitivity of sensors. When actively approaching the typhoon center, the air pressure from MWO can reflect some drastic and subtle changes, such as a sudden drop to 980 hPa, which is difficult to obtain by other observation methods. As a mobile meteorological and oceanographic observation station, MWO has shown its unique advantages over traditional observation methods, and the results preliminarily demonstrate the reliable observation capability of MWO in this paper. [ABSTRACT FROM AUTHOR]

The article focuses on a study which aims at assessing Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation retrieval product. In the study, radiosonde data is used to verify radio occultation retrieval product of the COSMIC radio sounding system. It shows similarities in the temperature data from COSMIC with the radiosonde data.

Locust swarms had periodically raged in both North American Plains (NAP) and East Asian Plains (EAP) before 1880 AD. After this period, the locust outbreaks almost never recurred in NAP but have continued to occur in EAP. Since large quantities of pesticides were used in the major agriculture regions of NAP in the late 1870s; this has been suggested as a possible major cause of the disappearing of locust outbreaks. Extensive applications of more effective chemical pesticides were also used in the granary regions of EAP in the 1950s in an effort to kill the pests at a much higher intensity. However, locust swarms came back again in many areas of China in the 1960s. Therefore, NAP locust extinction still remains a puzzle. Frequent locust outbreaks in EAP over the past 130 yr may offer clues to probe key control elements in the disappearing of locust outbreaks in NAP. This paper analyzes the climate extremes and monthly temperature-precipitation combines of NAP and EAP, and found the differences in their frequencies of these climate combines caused different locust fates in the two regions: restrained the locust outbreak in NAP but induced such events in EAP. Validation shows that severer EAP locust outbreak years were coincided with the climate extreme combines years. Thus we suggest that climate changes in frequency, extremes and trends can explain why the fate of the locust plague in EAP was different from that in NAP. The study also points out that, under the present global warming, cautions should be taken to make sure the pest hazard being nipped in the-bud. [ABSTRACT FROM AUTHOR]

The global burden of carbon monoxide, CO, is rather uncertain. In this paper we address the potential of UV-induced CO emission by terrestrial surfaces. Real-time measurements of [CO] were made with a cavity enhanced laser connected in closed loop to either an ecosystem chamber or a leaf scale chamber. Sand and leaves of all examined plant species exhibited emission of CO in response to artificial UV-radiation and the UV-component of natural solar radiation. The UV-induced rate of CO emission exhibited a rather low dependence on temperature, indicating an abiotic process. The emission of CO in response to the UV-component of natural solar radiation was also evident at the ecosystem scale. When scaled to the global level, the UV-induced emission of CO by the major types of terrestrial surfaces, living leaves and soil (here represented by sand), amounts up to 28 Tgyr-1. This source has till now not been accounted for by IPCC, but is equivalent to 14-56% of the 50-200 Tgyr-1 from sources currently accounted for (IPCC 2001). In addition to this are other known sources that ought to be considered. The hitherto unaccounted for terrestrial sources of CO amounts up to 207 Tgyr-1 , almost two-thirds of the latest estimated global CO burden of 360 Tgyr-1 (IPCC, 2001). [ABSTRACT FROM AUTHOR]

The article presents a study on the effect of land use induced land cover change (LULCC) on temperature and rainfall extremes. It states that four climate models within the land use and climate, identification of robust impacts (LUCID) project protocol were used. It concludes that there is a similarity between the changes in temperature extremes and mean temperature caused by LULCC.

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.

We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10-20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system. [ABSTRACT FROM AUTHOR]

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models. [ABSTRACT FROM AUTHOR]

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment. [ABSTRACT FROM AUTHOR]

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration dataset, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5° and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95% confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. Our results, including the modeled spatiotemporal distribution of global soil respiration, are based on a semi-empirical model parameterized with over one thousand data points. We expect that these spatiotemporal estimates will provide a benchmark for future studies and also help to constrain process-oriented models. [ABSTRACT FROM AUTHOR]

Peatlands in discontinuous permafrost regions occur as a mosaic of wetland types, each with variable sensitivity to climate change. Permafrost thaw further increases the spatial heterogeneity in ecosystem structure and function in peatlands. Carbon (C) fluxes are well characterized in end-member thaw stages such as fully intact or fully thawed permafrost but remain unconstrained for transitional stages that cover a significant area of thawing peatlands. Furthermore, changes in the environmental correlates of C fluxes, due to thaw are not well described: a requirement for modeling future changes to C storage of permafrost peatlands. We investigated C fluxes and their correlates in end-member and a number of transitional thaw stages in a sub-arctic peatland. Across peatland lumped CH4 and CO2 flux data had significant correlations with expected correlates such as water table depth, thaw depth, temperature, photosynthetically active radiation and vascular green area. Within individual thaw states, bivariate correlations as well as multiple regressions between C flux and environmental factors changed variably with increasing thaw. The variability in directions and magnitudes of correlates reflects the range of structural conditions that could be present along a thaw gradient. These structural changes correspond to changes in C flux controls, such as temperature and moisture, and their interactions. Temperature sensitivity of CH4 increased with increasing thaw in bivariate analyses, but lack of this trend in multiple regression analyses suggested cofounding effects of substrate or water limitation on the apparent temperature sensitivity. Our results emphasize the importance of incorporating transitional stages of thaw in landscape level C budgets and highlight that end-member or adjacent thaw stages do not adequately describe the variability in structure-function relationships present along a thaw gradient. [ABSTRACT FROM AUTHOR]

Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by e.g. topography and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that leverages the good description of the atmospheric column provided by climate models, together with high resolution DEM's, to derive a consistent topography-based, scaling of coarse grid climate variables to fine-scale. We test the method together with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure-levels: air temperature, relative humidity, wind speed and incoming longwave radiation. It is expected that this method can be used to improve inputs to numerical simulations in complex and/or remote terrain especially when statistical methods are not possible due to lack of observations i.e. remote areas or future periods. [ABSTRACT FROM AUTHOR]

In order to detect shifts in community structure and function associated with global change, the natural background fluctuation in these traits must be known. In a 6-yr study we quantified year to year variability of taxonomic and functional composition of benthic hard bottom communities in the Western Baltic. While taxonomic fluctuations were substantial, functionality of the communities seems preserved in most cases. Environmental conditions potentially driving these fluctuations are winter temperatures and current regimes. We tentatively define a confidence range of natural variability in productivity, composition and diversity a departure from which might help identifying an ongoing regime shift driven by global change. In addition, we propose a statistical procedure distinguishing directional shifts ("signal") from natural fluctuations ("noise"). [ABSTRACT FROM AUTHOR]

The article focuses on a study which aims at analyzing the effect of atmospheric water vapor in detecting turbulence based on the Thorpe method. It describes the Thorpe method in which potential temperature and density are sorted in ascending order. It concludes increase in turbulent faction of the troposphere during saturation of atmospheric water vapor.

Crust formation is a common phenomenon in planktonic foraminifera. Because of their different formation mechanism and hence composition, crusts affect the overall test composition and therefore complicate the use of crust-bearing foraminifera in paleoceanography. Such species are often used to estimate subsurface paleotemperatures and although the influence of the crust on the trace element/Ca ratio is recognised, it has not been systematically explored between and within tests. Here we use laser ablation ICP-MS to assess the variability in trace element composition of the crust of Neogloboquadrina dutertrei within individual chambers, as well as the effect of compositional heterogeneity of the crust on whole test chemistry. Compositionally, the outer crust differs from inner layer by lower Mg/Ca and Mn/Ca, but is indistinguishable in Sr/Ca. Crust thickness decreases towards the younger chambers and it may be entirely absent from the last chamber. In contrast to Mn/Ca and Sr/Ca, crustal Mg/Ca ratios show a tendency towards higher values on the younger chambers. These patterns in crust thickness and in crust Mg/Ca indicates that temperature is not the dominant factor controlling crust composition. Temperature estimates based on N. dutertrei, and presumably other crust-forming species too, are therefore biased towards too low values. Through comparison of modern and glacial tests we show that this bias is not constant and that changes in the crust thickness and/or in the Mg/Ca values can spuriously suggest temperature changes. [ABSTRACT FROM AUTHOR]

Air-sea carbon dioxide (CO2) fluxes have recently been reported for the US South Atlantic Bight (SAB), a low-latitude shallow continental shelf bordered landward by abundant salt marshes and rivers. In this study, influences of terrestrial inputs on sea surface partial pressure of CO2 (pCO2) in the SAB are quantified. After re- moving pCO2 variations due to the annual temperature cycle and air-sea gas ex- change from the in situ pCO2, temperature and gas exchange corrected (TG-corrected) pCO2 is derived. Contributions from the river, marsh, and continental shelf to the TG-corrected pCO2 are then calculated. Findings show that CO2 contributions from the river [ΔpCO2 (river)] are highest close to the coast and decrease with distance off-shore. For example, ΔpCO2 (river) was up to 30 µatm on the inner shelf but averaged only 0--3 µatm on the outer shelf during January and March 2005. CO2 contributions from salt marshes [ΔpCO2 (marsh)] show similar spatial and seasonal distributions as ΔpCO2 (river), with the magnitude of ΔpCO2 (marsh) being about three times as high as that of ΔpCO2 (river). CO2 contributions from within the shelf [ΔpCO2 (shelf)] are highest among the three components. Compared to ΔpCO2 (river) and ΔpCO2 (marsh), ΔpCO2 (shelf) show the smallest onshore-offshore gradients. Despite large uncertainties, this study clearly demonstrates the importance of terrestrial impacts on coastal ocean CO2 distribution. [ABSTRACT FROM AUTHOR]

The article presents a study on the comparison of four Earth system models to climate engineering. The study compared the two couteracting forcings I G1 of the GeoMIP to the preindustrial climate. The result of the study shows that the reduction in evaporation compensated the reduction of the meridional temperature gradient in all models compared to the control simulation.

Deep-sea corals are a potentially valuable archive of the temperature and ocean chemistry of intermediate and deep waters. Living in near constant temperature, salinity and pH, and having amongst the slowest calcification rates observed in carbonate-precipitating biological organisms, deep-sea corals can provide valuable constraints on processes driving mineral equilibrium and disequilibrium isotope signatures. Here we report new data to further develop "clumped" isotopes as a paleothermometer in deep-sea corals as well as to investigate mineral-specific, taxon-specific, and growth-rate related effects. Carbonate clumped isotope thermometry is based on measurements of the abundance of the doubly-substituted isotopologue 13C18O16O2 in carbonate minerals, analyzed in CO2 gas liberated on phosphoric acid digestion of carbonates and reported as Δ47 values. We analyzed Δ47 in live-collected aragonitic scleractinian (Enallopsammia sp.) and calcitic gorgonian (Isididae and Coralliidae) deep-sea corals, and compared results to published data for other aragonitic scleractinian taxa. Measured Δ47 values were compared to in situ temperatures and the relationship between Δ47 and temperature was determined for each group to investigate taxon-specific effects. We find that aragonitic scleractinian deep-sea corals exhibit higher values than calcitic gorgonian corals and the two groups of coral produce statistically different relationship between Δ47-temperature calibrations. These data are significant in the interpretation of all carbonate "clumped" isotope calibration data as they show that distinct Δ47-temperature calibrations can be observed in different materials recovered from the same environment and analyzed using the same instrumentation, phosphoric acid composition, digestion temperature and technique, CO2 gas purification apparatus, and data handling. There are three possible explanations for the origin of these different calibrations. The offset between the corals of different mineralogy is in the same direction as published theoretical predictions for the offset between calcite and aragonite, although the magnitude of the offset is different. One possibility is that the deep-sea coral results reflect that crystals may attain nominal mineral equilibrium clumped isotope signatures only under conditions of extremely slow growth. In that case, a possible explanation for the attainment of disequilibrium bulk isotope signatures and equilibrium clumped isotope signatures by deep-sea corals is that extraordinarily slow growth rates can promote the occurrence of isotopic reordering in the interfacial region of growing crystals. We also cannot rule out a component of a biological "vital-effect" influencing clumped isotope signatures in one or both orders of coral. Based on published experimental data and theoretical calculations, these biological "vital" effects could arise from kinetic isotope effects due to the source of carbon used for calcification, temperature- and pH-dependent rates of CO2 hydration and/or hydroxylation, calcifying fluid pH, the activity of carbonic anhydrase, the residence time of dissolved inorganic carbon in the calcifying fluid, and calcification rate. A third possible explanation is the occurrence of variable acid digestion fractionation factors. Although a recent study has suggested that dolomite, calcite, and aragonite may have similar clumped isotope acid digestion fractionation factors, the influence of acid digestion kinetics on Δ47 is a subject that warrants further investigation. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems of northern Eurasia are greening, yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness and forest fires contribute to the trend in Gross Primary Productivity (GPP) derived from satellite data across northern Eurasia. For the period 1982-2008 we find that GPP, estimated using ensemble satellite NDVI (Normalized Difference Vegetation Index) observations from GIMMS3g and VIP datasets, is most sensitive to temperature, precipitation and cloudiness during summer, the peak of the growing season. For regional median GPP, summer temperature explains 33.3% of the variation in GPP, while the other environmental variables explain from 2.2 to 11.8%. Warming over the period analyzed, even without a sustained increase in precipitation, led to a significant GPP increase over 67.3% of the region. A significant decrease in GPP was found over 6.2% of the region, primarily the dryer grasslands in the south-western. For this area, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. Our results further advance the notion that air temperature is the dominant environmental control for the recent GPP increases across northern Eurasia. [ABSTRACT FROM AUTHOR]

Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions are known to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. In this study, we systematically quantify simultaneities between meteorological extremes and the timing of flowering of four shrub species across Germany by means of event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences. Our systematic investigation supports previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of wildlife plants. In addition, we find statistically significant indications for some long-term relations reaching back to the previous year. [ABSTRACT FROM AUTHOR]

Towards a better understanding of trace element transport in permafrost-affected Earth surface environments, we sampled ~ 60 large and small rivers (< 100 to = 150 000 km² watershed area) of Western Siberia Lowland (WSL) during spring flood and summer and winter base-flow across a 1500 km latitudinal gradient covering continuous, discontinuous, sporadic and permafrost-free zones. Analysis of ~ 40 major and trace elements in dissolved (< 0.45 µm) fraction allowed establishing main environmental factors controlling the transport of metals and trace elements in rivers of this environmentally important region. No statistically significant effect of the basin size on most TE concentration was evidenced. Three category of trace elements were distinguished according to their concentration - latitude pattern: (i) increasing northward in spring and winter (Fe, Al, Ga (only winter), Ti (only winter), REEs, Pb, Zr, Hf, Th (only winter)), linked to leaching from peat and/or redox processes and transport in the form of Fe-rich colloids, (ii) decreasing northward during all seasons (Sr, Mo, U, As, Sb) marking the underground water influence of river feeding and (iii) elements without distinct trend from S to N whose variations within each latitude range were higher than the difference between latitudinal ranges (B, Li, Ti (except summer), Cr, V, Mn, Zn, Cd, Cs, Hf, Th). In addition to these general features, specific, northward increase during spring period was mostly pronounced for Fe, Mn, Co, Zn and Ba and may stem from a combination of enhanced leaching from the topsoil and vegetation and bottom waters of the lakes (spring overturn). A spring time northward decrease was observed for Ni, Cu, Zr, Rb. The southward increase in summer was strongly visible for Fe, Ni, Ba, Rb and V, probably due to peat/moss release (Ni, Ba, Rb) or groundwater feeding (Fe, V). The Principal Component Analysis demonstrated two main factors potentially controlling the ensemble of TE concentration variation. The first factor, responsible for 16-20 % of overall variation, included trivalent and tetravalent hydrolysates, Cr, V, and DOC and presumably reflected the presence of organo-mineral colloids, as also confirmed by previous studies in Siberian rivers. The 2nd factor (8-14 % variation) was linked to the latitude of the watershed and acted on elements affected by the groundwater feeding (DIC, Sr, Mo, As, Sb, U), whose concentration decreased significantly northward during all seasons. Overall, the rank of environmental factors on TE concentration in western Siberian rivers was latitude (3 permafrost zones) > season > watershed size. The effect of the latitude was minimal in spring for most TE but highly visible for Sr, Mo, Sb and U. The main factors controlling the shift of river feeding from surface and subsurface flow to deep underground flow in the permafrost-bearing zone were the depth of the active (unfrozen) seasonal layer and its position in organic or mineral horizons of the soil profile. In the permafrost-free zone, the relative role of carbonate mineral-bearing base rock feeding vs. bog water feeding determined the pattern of trace element concentration and fluxes in rivers of various size as a function of season. Comparison of obtained TE fluxes in WSL rivers with those of other subarctic rivers demonstrated reasonable agreement for most trace elements; the lithology of base rocks was the major factor controlling the magnitude of TE fluxes. The climate change in western Siberia and permafrost boundary migration will affect essentially the elements controlled by underground water feeding (DIC, alkaline-earth elements (Ca, Sr), oxyanions (Mo, Sb, As) and U). The thickening of the active layer may increase the export of trivalent and tetravalent hydrolysates in the form of organo-ferric colloids. Plant litter-originated divalent metals present as organic complexes may be retained via adsorption on mineral horizon. However, due to various counterbalanced processes controlling element source and sinks in plants - peat - mineral soil - river systems, the overall impact of the permafrost thaw on TE export from the land to the ocean may be smaller than that foreseen by merely active layer thickening and permafrost boundary shift. [ABSTRACT FROM AUTHOR]

The article discusses the use of broadband solar occultation to retrieve atmospheric temperature and pressure T(P). It provides an overview of the solar occultation measurement technique and the mechanisms that make the measurement sensitive to temperature. It also discusses the effectiveness of Solar Occultation For Ice Experiment to measure polar mesospheric clouds, mesospheric trace gases and T(P).

Gross primary production (GPP), separated from flux tower measurements of net ecosystem exchange (NEE) of CO2, is used increasingly to validate process-based simulators and remote sensing-derived estimates of simulated GPP at various time steps. Proper validation should include the uncertainty associated with this separation at different time steps. This can be achieved by using a Bayesian framework. In this study, we estimated the uncertainty in GPP at half hourly time steps. We used a nonrectangular hyperbola (NRH) model to separate GPP from flux tower measurements of NEE at the Speulderbos forest site, The Netherlands. The NRH model included the variables that influence GPP, in particular radiation, and temperature. In addition, the NRH model provided a robust empirical relationship between radiation and GPP by including the degree of curvature of the light response curve. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. Adopting a Bayesian approach, we defined the prior distribution of each NRH parameter. Markov chain Monte Carlo (MCMC) simulation was used to update the prior distribution of each NRH parameter. This allowed us to estimate the uncertainty in the separated GPP at half-hourly time steps. This yielded the posterior distribution of GPP at each half hour and allowed the quantification of uncertainty. The time series of posterior distributions thus obtained allowed us to estimate the uncertainty at daily time steps. We compared the informative with non-informative prior distributions of the NRH parameters. The results showed that both choices of prior produced similar posterior distributions GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications. [ABSTRACT FROM AUTHOR]

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in dfferent research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data as similation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized effciently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework. [ABSTRACT FROM AUTHOR]

Information on the relationship between cumulative fossil carbon emissions and multiple climate targets are essential to design emission mitigation and climate adaptation strategies. In this study, the transient responses in different climate variables are quantified for a large set of multi-forcing scenarios extended to year 2300 towards stabilization and in idealized experiments using the Bern3D-LPJ carbon-climate model. The model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte-Carlo type framework. Cumulative fossil emissions of 1000 GtC result in a global mean surface air temperature change of 1.88 °C (68% confidence interval (c.i.): 1.28 to 2.69 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and in steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic Meridional Overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The slopes of the relationships change when CO2 is stabilized. The Transient Climate Response is constrained, primarily by long-term ocean heat observations, to 1.7 _C (68% c.i.: 1.3 to 2.2 °C) and the Equilibrium Climate Sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models, but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability. [ABSTRACT FROM AUTHOR]

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8% for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity. [ABSTRACT FROM AUTHOR]

Microwave remote sensing is important for observing the mass of ice hydrometeors. One of the main error sources of microwave ice mass retrievals is that approximations around the shape of the particles are unavoidable. One common approach to represent particles of irregular shape is the soft particle approximation (SPA). We show that it is possible to define a SPA that mimics mean optical particles of available reference data over narrow frequency ranges, considering a single observation technique at the time, but SPA does not work in a broader context. Most critically, the required air fraction varies with frequency and application, as well as with particle size. In addition, the air fraction matching established density parameterisations results in far too soft particles, at least for frequencies above 90 GHz. That is, alternatives to SPA must be found. One alternative was recently presented by Geer and Baordo (2014). They used a sub-set of the same reference data and simply selected as "shape model" the particle type giving the best overall agreement with observations. We present a way to perform the same selection of a representative particle shape, but without involving assumptions on particle size distribution and actual ice mass contents. Only an assumption on the occurrence frequency of different particle shapes is still required. Our analysis leads to the same selection of representative shape as found by Geer and Baordo (2014). In addition, we show that the selected particle shape has the desired properties also at higher frequencies as well as for radar applications. Finally, we demonstrate that in this context the assumption on particle shape is likely less critical when using mass equivalent diameter to characterise particle size, compared to using maximum dimension, but a better understanding of the variability of size distributions is required to fully characterise the advantage. Further advancements on these subjects are presently difficult to achieve due to a lack of reference data. One main problem is that most available databases of precalculated optical properties assume completely random particle orientation, while for certain conditions a horizontal alignment is expected. In addition, the only database covering frequencies above 340 GHz has a poor representation of absorption as it is based on outdated refractive index data, as well as only covering particles having a maximum dimension below 2mm and a single temperature. [ABSTRACT FROM AUTHOR]

The morphological complexity of urban environments results in a high spatial and temporal variability of the urban microclimate. The consequent demand for high-resolution atmospheric data remains a challenge for atmospheric research and operational application. The recent widespread availability and increasing adoption of low-cost mobile sensing offer the opportunity to integrate observations from conventional monitoring networks with microclimatic and air pollution data at a finer spatial and temporal scale. So far, the relatively low quality of the measurements and outdoor performance compared to conventional instrumentation has discouraged the full deployment of mobile sensors for routine monitoring. The present study addresses the performance of a commercial mobile sensor, the MeteoTracker (IoTopon Srl), recently launched on the market to quantify the microclimatic characteristics of the outdoor environment. The sensor follows the philosophy of the Internet of Things technology, being low cost, having an automatic data flow via personal smartphones and online data sharing, supporting user-friendly software, and having the potential to be deployed in large quantities. In this paper, the outdoor performance is evaluated through tests aimed at quantifying (i) the intra-sensor variability under similar atmospheric conditions and (ii) the outdoor accuracy compared to a reference weather station under sub-optimal (in a fixed location) and optimal (mobile) sensor usage. Data-driven corrections are developed and successfully applied to improve the MeteoTracker data quality. In particular, a recursive method for the simultaneous improvement of relative humidity, dew point, and humidex index proves to be crucial for increasing the data quality. The results mark an intra-sensor variability of approximately ± 0.5 °C for air temperature and ± 1.2 % for the corrected relative humidity, both of which are within the declared sensor accuracy. The sensor captures the same atmospheric variability as the reference sensor during both fixed and mobile tests, showing positive biases (overestimation) for both variables. Through the mobile test, the outdoor accuracy is observed to be between ± 0.3 to ± 0.5 °C for air temperature and between ± 3 % and ± 5 % for the relative humidity, ranking the MeteoTracker in the real accuracy range of similar commercial sensors from the literature and making it a valid solution for atmospheric monitoring. [ABSTRACT FROM AUTHOR]

This paper presents a method for determining the impact of dam reservoirs on the ice cover of rivers downstream of their locations based on a long measurement period (1950–2020) and synthetic-aperture radar (SAR) data. Two rivers and two sets of dam reservoirs located in the Carpathian Mountains (central Europe) were selected for this study. In order to estimate the influence of reservoirs, a logistic regression model was built to describe the relationship between the course of air temperature and the occurrence of ice cover (i.e., total ice cover and border ice) at water gauge cross sections upstream and downstream of the reservoirs. The influence of reservoirs was then defined as the differences between the number of days with ice cover predicted from air temperature and those observed at the water gauge cross sections. Additionally, the extent of the impact of the reservoirs was estimated based on SAR data (Sentinel-1) by identifying river sections downstream of the reservoirs on which total ice cover did not form despite the persistence of very low air temperatures. The study shows that dam reservoirs play an important role in decreasing the incidence of ice cover on rivers. The occurrence of ice cover as a result of reservoir operations could decrease by over 80 % in the sections immediately downstream of the reservoirs. The impact of the reservoir on river ice cover diminishes as the distance from the reservoir increases. Using SAR data, it was estimated that total ice cover did not form in sections 26–60 km downstream of the reservoirs, despite the presence of favorable thermal conditions. Based on the results of the study presented here, it can be assumed that in areas where many dam reservoirs are located, the ice regime of rivers is significantly transformed, which should be taken into account when studying river ice cover. This study also demonstrates that the logistic regression model and SAR data are useful tools for assessing the impact of dam reservoirs on river ice cover. [ABSTRACT FROM AUTHOR]

Ground-based microwave radiometers (MWR) are becoming more and more common for remotely sensing the atmospheric temperature and humidity profile, as well as path integrated cloud liquid water content. The calibration accuracy of the state-of-the-art MWR HATPRO-G2 (Humidity And Temperature Profiler - Generation 2) was investigated during the second phase of the Radiative Heating in Underexplored Bands Campaign (RHUBC-II) in Northern Chile (5320ma.m.s.l. - above mean sea level, 530 hPa) conducted by the the Atmospheric Radiation Measurement (ARM) program conducted between August and October 2009. This study assesses the quality of the two frequently used liquid nitrogen and tipping curve calibrations by performing a detailed error propagation study by exploiting the unique atmospheric conditions of RHUBCII. Both methods are known to have open issues concerning systematic offsets and calibration repeatability. For the tipping curve calibration an uncertainty of 0.2-0.4K (K-band) and 1.0-1.2K (V-band) is found. The uncertainty in the tipping curve calibration is mainly due the atmospheric inhomogeneities. For the liquid nitrogen calibration the estimated uncertainty of 0.5-0.9 K is dominated by the uncertainty of the reflectivity of the liquid nitrogen target. Systematic offsets, which may cause the disagreement of both methods within their estimated uncertainties, are discussed. [ABSTRACT FROM AUTHOR]

This article presents the development of a new numerical system denominated JULESCCATT- BRAMS, which resulted from the coupling of the JULES surface model to the CCATT-BRAMS atmospheric chemistry model. The performance of this system in relation to several meteorological variables (wind speed at 10m, air temperature at 2m, dew point temperature at 2 m, pressure reduced to mean sea level and 6 h accumulated precipitation) and the CO2 concentration above an extensive area of South America is also presented, focusing on the Amazon basin. The evaluations were conducted for two periods, the wet (March) and dry (September) seasons of 2010. The statistics used to perform the evaluation included bias (BIAS) and root mean squared error (RMSE). The errors were calculated in relation to observations at conventional stations in airports and automatic stations. In addition, CO2 concentrations in the first model level were compared with meteorological tower measurements and vertical CO2 profiles were compared with aircraft data. The results of this study show that the JULES model coupled to CCATT-BRAMS provided a significant gain in performance in the evaluated atmospheric fields relative to those simulated by the LEAF (version 3) surface model originally utilized by CCATT-BRAMS. Simulations of CO2 concentrations in Amazonia and a comparison with observations are also discussed and show that the system presents a gain in performance relative to previous studies. Finally, we discuss a wide range of numerical studies integrating coupled atmospheric, land surface and chemistry processes that could be produced with the system described here. Therefore, this work presents to the scientific community a free tool, with good performance in relation to the observed data and re-analyses, able to produce atmospheric simulations/ forecasts at different resolutions, for any period of time and in any region of the globe. [ABSTRACT FROM AUTHOR]

To study the effects of the physical environment on carbon and nutrients cycles dynamics in the north eastern shelf of the Gulf of Cáadiz, changes in currents, tides, salinity, temperature, carbon system parameters (fugacity of CO2 (fCO2), dissolved organic carbon, dissolved inorganic carbon and pH) and others related (dissolved oxygen, total dissolved nitrogen, nutrients and suspended particulate matter) were measured in transects across the Guadalquivir Estuary and Bay of Cáadiz mouths. Thus, the main objective of this study is to investigate the influence of these inner ecosystems on the carbon and nutrient distributions in the adjacent continental shelf. Three cruises have been undertaken in June 2006, November 2006 and February 2007, each one covering one complete tidal cycle during June, both systems were exporting components to the adjacent continental shelf of the Gulf of Cáadiz. In an annual scale, Guadalquivir Estuary exported components while Bay of Cáadiz imported them. Diurnal variability of fCO2 could have a potentially important implication on the estimate of air-sea CO2 fluxes. Monthly studies should be undertaken to completely understand this dynamic system. [ABSTRACT FROM AUTHOR]

Carbon use efficiency (CUE) is a functional parameter that could possibly link the current increasingly accurate global estimates of gross primary production with those of net ecosystem exchange, for which global predictors are still unavailable. Nevertheless, CUE estimates are actually available for only a few ecosystem types, while information regarding agro-ecosystems is scarce, in spite of the simplified spatial structure of these ecosystems that facilitates studies on allocation patterns and temporal growth dynamics. We combined three largely deployed methods, eddy covariance, soil respiration and biometric measurements, to assess monthly values of CUE, net primary production (NPP) and allocation patterns in different plant organs in an apple orchard during a complete year (2010). We applied a measurement protocol optimized for quantifying monthly values of carbon fluxes in this ecosystem type, which allows for a cross-check between estimates obtained from different methods. We also attributed NPP components to standing biomass increments, detritus cycle feeding and lateral exports. We found that in the apple orchard both net ecosystem production and gross primary production on yearly basis, 380±30gCm-2 and 1263±189gCm-2 respectively, were of a magnitude comparable to those of natural forests growing in similar climate conditions. The largest differences with respect to forests are in the allocation pattern and in the fate of produced biomass. The carbon sequestered from the atmosphere was largely allocated to production of fruits: 49% of annual NPP was taken away from the ecosystem through apple production. Organic material (leaves, fine root litter, pruned wood and early fruit falls) contributing to the detritus cycle was 46% of the NPP. Only 5% was attributable to standing biomass increment, while this NPP component is generally the largest in forests. The CUE, with an annual average of 0.71±0.09, was higher than the previously suggested constant values of 0.47-0.50. Low nitrogen investment in fruits, the limited root-apparatus, and the optimal growth temperature and nutritional condition observed at the site are suggested to be explanatory variables for the high CUE observed. [ABSTRACT FROM AUTHOR]

This paper evaluates the relative contribution of light and temperature on net ecosystem CO2 uptake during the 2006 growing season in a polygonal tundra ecosystem in the Lena River Delta in Northern Siberia (72º220 N, 126º300 E). We demonstrate that the timing of warm periods may be an important determinant of the magnitude of the ecosystem's carbon sink function, as they drive temperature-induced changes in respiration. Hot spells during the early portion of the growing season are shown to be more influential in creating mid-day surface-to-atmosphere net ecosystem CO2 exchange fluxes than those occurring later in the season. In this work we also develop and present a bulk flux partition model to better account for tundra plant physiology and the specific light conditions of the arctic region that preclude the successful use of traditional partition methods that derive a respiration-temperature relationship from all night-time data. Night-time, growing season measurements are rare during the arctic summer, however, so the new method allows for temporal variation in the parameters describing both ecosystem respiration and gross uptake by fitting both processes at the same time. Much of the apparent temperature sensitivity of respiration seen in the traditional partition method is revealed in the new method to reflect seasonal changes in basal respiration rates. Understanding and quantifying the flux partition is an essential precursor to describing links between assimilation and respiration at different time scales, as it allows a more confident evaluation of measured net exchange over a broader range of environmental conditions. The growing season CO2 sink estimated by this study is similar to those reported previously for this site, and is substantial enough to withstand the long, low-level respiratory CO2 release during the rest of the year to maintain the site's CO2 sink function on an annual basis. [ABSTRACT FROM AUTHOR]

Numerous reactive volatile organic compounds (VOCs) are emitted into the atmosphere by vegetation. Most biogenic VOCs are highly reactive towards the atmosphere's most important oxidant, the hydroxyl (OH) radical. One way to investigate the chemical interplay between biosphere and atmosphere is through the measurement of total OH reactivity, the total loss rate of OH radicals. This study presents the first determination of total OH reactivity emission rates (measurements via the Comparative Reactivity Method) based on a branch cuvette enclosure system mounted on a Norway spruce (Picea abies) throughout spring, summer and autumn 2011. In parallel separate VOC emission rates were monitored by a Proton Transfer Reaction-Mass Spectrometer (PTR-MS), and total ozone (O3) loss rates were obtained inside the cuvette. Total OH reactivity emission rates were in general temperature and light dependent, showing strong diel cycles with highest values during daytime. Monoterpene emissions contributed most, accounting for 56-69% of the measured total OH reactivity flux in spring and early summer. However, during late summer and autumn the monoterpene contribution decreased to 11-16%. At this time, a large missing fraction of the total OH reactivity emission rate (70-84%) was found when compared to the VOC budget measured by PTR-MS. Total OH reactivity and missing total OH reactivity emission rates reached maximum values in late summer corresponding to the period of highest temperature. Total O3 loss rates within the closed cuvette showed similar diel profiles and comparable seasonality to the total OH reactivity fluxes. Total OH reactivity fluxes were also compared to emissions from needle storage pools predicted by a temperature-only dependent algorithm. Deviations of total OH reactivity fluxes from the temperature-only dependent emission algorithm were observed for occasions of mechanical and heat stress. While for mechanical stress, induced by strong wind, measured VOCs could explain total OH reactivity emissions, during heat stress they could not. The temperature driven algorithm matched the diel course much better in spring than in summer, indicating a different production and emission scheme for summer and early autumn. During these times, unmeasured and possibly unknown primary biogenic emissions contributed significantly to the observed total OH reactivity flux. [ABSTRACT FROM AUTHOR]

The article presents a study which describes the design of rotational-Raman channel for atmospheric temperature and aerosol extinction measurements and its application to the Esrange lidar in Kiruna, Sweden. The study used Newtonian telescopes, emitted laser, and rotational-Raman technique. Results revealed that combining rotational-Raman measurements and the integration technique, Esrange lidar is capable of measuring atmospheric temperature profiles from the troposphere to the mesosphere.

The article presents a study which validated the Optical Spectrograph and InfraRed Imaging System (OSIRIS) mesospheric temperatures with the use of ground-based and satellite measurements. The study obtained continuous temperature profiles between the stratopause and the upper mesosphere from OSIRIS observations on Rayleigh-scattered sunlight. It says that OSIRIS temperatures were in good agreement with the coincident temperature profiles from other ground-based and satellite measurements.

Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (Reco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation, and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input -- air, surface, bole, or soil at a specific depth -- should be used. This choice is a source of uncertainty and potential biases. In this study we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables. [ABSTRACT FROM AUTHOR]

The article discusses a study which evaluates the feasibility and quality of Eddy-Covariance flux measurements from a weight-shift microlight aircraft (WSMA). It examines the precision of the wind measurement, the lynchpin of flux calculations from aircraft. It compares measurements of wind, temperature, humidity and respective fluxes between a tall tower and the WSMA.