Global Scale Atmospheric Mixing

Changes in mass contained by mountain glaciers and ice caps can modify the Earth’s hydrological cycle on multiple scales. On a global scale, the mass loss from glaciers contributes to sea-level rise. On regional and local scales, glacier meltwater is an important contributor to and modulator of river flow. In light of strongly accelerated worldwide glacier retreat, the associated glacier mass losses raise concerns over the sustainability of water supplies in many parts of the world. Here, we review recent attempts to quantify glacier mass changes and their effect on river runoff on regional and global scales. We find that glacier runoff is defined ambiguously in the literature, hampering direct comparison of findings on the importance of glacier contribution to runoff. Despite consensus on the hydrological implications to be expected from projected future warming, there is a pressing need for quantifying the associated regional-scale changes in glacier runoff and responses in different climate regimes.

Being one of the major consequences of anthropogenic climate change, sea level rise forms a threat for many coastal areas and their inhabitants. Because all processes that cause sea-level changes have a spatially-varying fingerprint, local sea-level changes deviate substantially from the global mean. As a consequence, there is no single location on the earth that is subject to the global-mean sea-level change. To understand and forecast future changes in both global and regional sea level, a thorough understanding of its major underlying processes and their regional fingerprints is necessary. Nowadays, remote sensing from satellite altimetry provides an accurate estimate of changes in sea level on global and regional scales (Leuliette et al., 2004; Nerem et al., 2010; Ablain et al., 2017). The emergence of satellite gravimetry, in the form of the GRACE mission (Tapley et al., 2004), and the global coverage of in-situ subsurface temperature and salinity observations by the Argo programme (Roemmich et al., 2009; Roemmich and Gilson, 2009) has resulted in an extensive increase of our understanding of sea-level changes over the past decade, and the reliability of the estimates of the individual processes behind sea-level changes has reached the level where we can almost fully explain the observed sea-level changes from these contributors (Rietbroek et al., 2016; Leuliette and Miller, 2009; Dieng et al., 2015; Leuliette, 2015; Kleinherenbrink et al., 2016). However, before this period the spatially-varying signals have been sampled only sparsely by in-situ observations, mainly by means of tide gauges, which limits our current understanding of sea-level changes on global and regional scales. This thesis aims to find an answer to the question whether the sum of the underlying processes that cause sea-level changes can explain the observations, not only on a global scale, which has been assessed a multitude of times (Moore et al., 2011; Church et al., 2011; Gregory et al., 2013; Jevrejeva et al., 2016b), but also on scales of individual ocean basins and coastal regions. The assessment of this so-called sea-level budget has been done for two regional cases, and for the global ocean and individual basins. Furthermore, the effect of ocean bottom deformation on the difference between relative and geocentric observations has been quantified. Finally, we have applied an alternative approach to time-series analysis, in which the various contributors of sealevel variability are co-estimated with a time-varying trend using a Kalman filter and smoother approach, on tide gauge observations.

Changes in daily extreme temperatures have been identified in many studies conducted at local, regional or global scales. For Romanian territory, only little research on this issue was done. In this article, the extra‐Carpathians regions of Romania located southward and eastward from the Carpathians Chain were considered. This study is focused on analyzing daily extreme temperature trends at a regional scale (eastern, southern and southeastern regions of Romania) across 50 years (1961–2010). Data sets of daily minimum and maximum temperature recorded in 14 weather stations were analyzed. The main goal was to find changes in extreme daily temperatures using a set of 20 indices adopted from the core indices developed by ETCCDMI with appropriate modifications to suit to the analyzed territory. The main results suggest that regional temperature trends at the scale of extra‐Carpathians areas of Romania are similar to those calculated for global and European continental scales; the climate has become warmer during the last decades. It has been identified that both extreme daily maximum and minimum temperatures have increased in the analyzed areas. For all the indices related to hot temperature most trends are significantly positive. The strongest increase was detected for hot related extremes such as summer days and tropical nights as well as for maximum values of maximum and minimum daily temperatures. For indices related to cold there are different sign slopes, but negative slopes prevail, especially for number of days under a defined threshold. This is also an evidence of the important warming in the area. Generally, it was found that the daily maximum temperature is getting more extreme, whereas the minimum is getting less extreme. Copyright © 2012 Royal Meteorological Society

<p>The increasing risk of dry extremes and droughts and their further projected exacerbation due to climate change urges the development of reliable risk assessments and mitigation pathways on a regional and global scale. This foremost requires accurate and unambiguous model predictions of dry extremes, as this underpins the effectiveness of the proposed strategies. At present, however, the confidence in regional drought projections is defined as ‘medium to low' by the Intergovernmental Panel on Climate Change (IPCC) sixth assessment report (AR6), and reducing this uncertainty remains one of the main goals in coming years. <br>In this study, the bias in future projected changes in annual meteorological drought duration (hereafter, longest annual drought, LAD) is assessed in the ensemble of CMIP5 and CMIP6 models. The analyses show that it is the present-day inter-model spread in LAD climatology that largely determines the inter-model uncertainty in future predicted LAD changes. Hereby, both CMIP5 and CMIP6 model ensembles indicate a robust “dry-model-gets-drier” relationship in future LAD projections on a global and regional scale. Correcting for this bias using emerging constraint principles and past observational LAD information, we find that nearly half of the world's land area with projected increases in drought duration is underestimating the predicted model ensemble mean change, imposing higher-than-expected risks to the societies and ecosystems. Analysis of physical mechanisms that could underlie this emergent “present-future relationship” points to differences in the responses of “dry models” and “wet models” to CO2 forcing. Dry and wet models show differences in climate states, which support the role of land–atmosphere feedbacks and convective scheme sensitivity to atmospheric moisture in the spread of future LAD change projections. <br>In conclusion, the study reveals world regions where climate change may cause stronger drought duration aggravation than expected, and emphasizes the importance of reducing systematic model errors, which are presently largely owed to rainfall biases. Correcting these biases will increase the confidence of future dry extremes predictions, a prerequisite for the effective drought risk reduction in the near future with direct benefits for human and natural systems.</p>

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

Among the largest uncertainties in quantifying the radiative impacts of clouds are those that arise from the inherent difficulty in precisely specifying the vertical distribution of cloud optical properties using passive satellite measurements. Motivated by the need to address this problem, CloudSat was launched in April 2006 carrying into orbit the first millimeter wavelength cloud radar to be flown in space. Retrieved profiles of liquid and ice cloud microphysical properties from this Cloud Profiling Radar form the basis of the CloudSat's fluxes and heating rates algorithm, 2B‐FLXHR, a standard product that provides high vertical resolution profiles of radiative fluxes and atmospheric heating rates on the global scale. This paper describes the physical basis of the 2B‐FLXHR algorithm and documents the first year of 2B‐FLXHR data in the context of assessing the radiative impact of clouds on global and regional scales. The analysis confirms that cloud contributions to atmospheric radiative heating are small on the global scale because of a cancelation of the much larger regional heating from high clouds in the tropics and cooling from low clouds at higher latitudes. Preliminary efforts to assess the accuracy of the 2B‐FLXHR product using coincident CERES data demonstrate that outgoing longwave fluxes are better represented than those in the shortwave but both exhibit good agreement with CERES on scales longer than 5 days and larger than 5°. Colocated CALIPSO observations of clouds that are undetected by CloudSat further indicate that while thin cirrus can introduce modest uncertainty in the products, low clouds that are obscured by ground clutter represent a far more important source of error in the current 2B‐FLXHR product that must be addressed in subsequent versions of the algorithm.

Natural disasters are creating a major collapse in human existence. Among the many, drought is becoming more frequent and intense. Therefore, mitigation/adaptation measures have to be set to reduce the impact. This can be achieved via the application of Nature-based solutions (NBSs). This concept is now gaining more attention than ever but with fewer applications. The primary goal of this review paper is to analyze the different NBSs targeted for drought impact mitigation. The study constitutes the application of NBS at a global, continental and regional scale. Extensive literature was made to assess; NBS type, location, start and ending period of implementation, status, and level of effectiveness, recommendations set by researchers, and insight for future applications. The comprehensive review revealed that there are only a few scientific publications, hence, grey and non-scientific literature need to be included. Only four papers included a quantitative assessment for evaluating the effectiveness of NBS targeting drought. However, the continental and regional performance of NBS is not mentioned. Therefore, a common effectiveness evaluation framework shall be created to give policymakers a clear view of the different NBS’s. Furthermore, a more collaborative approach, including different stakeholder groups, is recommended, with specific attention to the local communities. In Flanders, most projects are in the pilot project stage. Moreover, the few successfully implemented projects are only very local and have a long realization time which the earlier limits to acquire visible impact at a larger scale. Finally, the loss of wetlands at a global scale and in Flanders (70% are lost), increases the vulnerability of catchments to drought. Therefore, future research should increase the evidence base and implementation of NBS, such as wetlands, in Flanders.

The phylogenetic resolution at which microorganisms display geographic endemism, the rates at which they disperse at global scales, and the role of humans on global microbial dispersal are largely unknown. Answering these questions is necessary for interpreting microbial biogeography, ecology, and macroevolution and for predicting the spread of emerging pathogenic strains. To resolve these questions, I analyzed the geographic and evolutionary relationships between 36,795 bacterial and archaeal ("prokaryotic") genomes from ∼7000 locations around the world. I find clear signs of continental-scale endemism, including strong correlations between phylogenetic divergence and geographic distance. However, the phylogenetic scale at which endemism generally occurs is extremely small, and most "species" (defined by an average nucleotide identity ≥ 95%) and even closely related strains (average nucleotide identity ≥ 99.9%) are globally distributed. Human-associated lineages display faster dispersal rates than other terrestrial lineages; the average net distance between any two human-associated cell lineages diverging 50 years ago is roughly 580 km. These results suggest that many previously reported global-scale microbial biogeographical patterns are likely the result of recent or current environmental filtering rather than geographic endemism. For human-associated lineages, estimated transition rates between Europe and North America are particularly high, and much higher than for non-human associated terrestrial lineages, highlighting the role that human movement plays in global microbial dispersal. Dispersal was slowest for hot spring- and terrestrial subsurface-associated lineages, indicating that these environments may act as "isolated islands" of microbial evolution.

Factors, at different scales, affecting the distribution of species of the genus Chthamalus Ranzani (Cirripedia, Balanomorpha, Chthamaloidea)

Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system

<sec><p indent="0mm">The Paris Agreement has set the goal of limiting the global warming to 2°C above pre-industrial levels and established a process for global carbon stocktaking which will take place every five years starting from 2023. The nationally determined contributions (NDCs) are at the heart of the Paris Agreement, which was adopted at the UN Climate Change Conference (COP21) in 2015. Under the Paris Agreement, each country is required to present its NDCs report using the standard ‘bottom-up’ inventory approach recommended by the Intergovernmental Panel on Climate Change (IPCC). The 49th session of IPCC has suggested a ‘top-down’ inversion approach to assess NDCs using measurements of atmospheric Green House Gases (GHGs). Satellite remote sensing can measure the atmospheric GHG concentration at global scale with fine resolution, high accuracy and high frequency, providing a promising tool to validate each country’s NDCs. The European Union, the United States, Japan, and Canada are vigorously developing their satellite systems for monitoring GHGs’ concentrations and emissions. China is also planning to build a GHGs monitoring satellite system to support the second carbon stocktaking in 2028. Therefore, it is extremely urgent to review and investigate the techniques, methods and cutting-edge applications of remote sensing for GHGs monitoring and stocktaking. </sec><sec> In this paper, we first reviewed the current techniques, networks, and upcoming national or international plans for monitoring atmospheric GHGs based on ground-based, airborne, and satellite platforms. The global carbon stocktaking requires continuous and accurate observations of GHGs’ concentrations and fluxes from ground, tower-based, airborne, and spaceborne platforms. The World Meteorological Congress (WMO) approved an ambitious international project, named the Global Greenhouse Gas Watch (G3W) initiative to address key information gaps in our understanding of anthropic and natural activities on the global carbon cycle, and help parties assess the completion of GST reports. Second, we proposed the key features of the next generation carbon monitoring satellite system, which was characterized by high spatial resolution, high accuracy, high temporal frequency, and multiple gases as well as atmospheric aerosol and co-emitted polluted gases (NO₂, CO). However, it is still challenging to meet the strict accuracy requirements for the atmospheric GHGs’ concentrations, such as <sc>1 ppm</sc> for CO₂, 5 ppb for CH₄, and 1 ppb for N₂O. China’s next-generation carbon satellite is to be launched in 2026, which will greatly enhance observation capabilities, including GHG species, accuracy, time frequency and spatial resolution. Third, taking the Global Carbon Project (GCP) series of assessment reports as the core references, we summarized the current methods, progress and challenges in the scientific assessment of GHGs’ emissions at global or regional scales. We also investigated the roles and current capabilities of satellite remote sensing and assimilation inversion technology in monitoring emissions of the three major greenhouse gases: CO₂, CH₄, and N₂O. At present, there are large uncertainties among the estimated GHGs’ fluxes (both emissions and sinks) due to very limited observations, model accuracy, and coarse resolution of assimilation systems etc. Finally, we investigated China’s demand for GHGs monitoring and emission assessment, and proposed three urgent tasks for global carbon stocktaking using the ‘top-down’ remote sensing method. These tasks include developing a satellite constellation for high-precision GHGs observation, a high-resolution, multi-species global GHG assimilation system, and an operational platform to assess global GHG emissions from terrestrial ecosystems and anthropogenic activities. Therefore, this paper, focusing on the needs of compliance with climate change and the “dual-carbon” targets, provides ideas for the construction of China’s next generation carbon-sensing satellite system. </sec>

A procedure has been proposed by Ciotti and Bricaud (2006) to retrieve spectral absorption coefficients of phytoplankton and colored detrital matter (CDM) from satellite radiance measurements. This was also the first procedure to estimate a size factor for phytoplankton, based on the shape of the retrieved algal absorption spectrum, and the spectral slope of CDM absorption. Applying this method to the global ocean color data set acquired by SeaWiFS over twelve years (1998–2009), allowed for a comparison of the spatial variations of chlorophyll concentration ([Chl]), algal size factor (Sf), CDM absorption coefficient (acdm) at 443 nm, and spectral slope of CDM absorption (Scdm). As expected, correlations between the derived parameters were characterized by a large scatter at the global scale. We compared temporal variability of the spatially averaged parameters over the twelve‐year period for three oceanic areas of biogeochemical importance: the Eastern Equatorial Pacific, the North Atlantic and the Mediterranean Sea. In all areas, both Sf and acdm(443) showed large seasonal and interannual variations, generally correlated to those of algal biomass. The CDM maxima appeared in some occasions to last longer than those of [Chl]. The spectral slope of CDM absorption showed very large seasonal cycles consistent with photobleaching, challenging the assumption of a constant slope commonly used in bio‐optical models. In the Equatorial Pacific, the seasonal cycles of [Chl], Sf, acdm(443) and Scdm, as well as the relationships between these parameters, were strongly affected by the 1997–98 El Niño/La Niña event.

The Integrated Model to Assess the Greenhouse Effect (IMAGE 2) is developed to simulate dynamically the global society-biosphere-climate system. The terrestrial C cycle model is an important component of this model. It is implemented on a grid, runs on a annual time step and simulates the major C fluxes between the atmosphere and the biosphere and controls the storage capacity of C in different compartments. The C fluxes are influenced by the direct and indirect response of ecosystems to changing atmospheric CO2 concentrations and climates. Each ecosystem is characterized by its NPP, which depends on environmental conditions. Incorporation of grid cell specific feedback processes is an innovation in this model. Implemented feedback processes are CO2 fertilization, effects of climate change on photosynthesis, plant respiration and decomposition and shifts in vegetation patterns due to climate change and changes in water use efficiency. This paper presents an evaluation of the importance of feedback processes on global and regional scales. Tempera- ture feedback on plant growth is the most important feedback process at the global scale, while CO2 fertilization is of lesser importance. However, CO2 fertilization is the most significant feedback in low latitudes, while temperature change most strongly influences the C cycle in the high latitudes. The C dynamics of land cover change, including feedbacks, depend on characteristics of the former and actual land cover type. The shifts in land cover are parameterized so that they mimic succession. The course and duration of the transitional phase strongly affect the C fluxes. We applied both an equilibrium approach with instantaneous transitions and dy- namic approaches with gradual type-dependent transitions. Transitions in natural vegetation between 1990 and 2050 involve about one-third of all grid cells, especially in the higher latitudes. The impact of vegetation transitions on C fluxes differs depending on the instantaneous or gradual tran- sition strategy. The latter results in higher and delayed NEP fluxes, resulting in significantly different atmospheric CO2 concentrations. The dynamic approach is more realistic and should be included in integrated assessment models that project future atmospheric CO2 levels.

Drought occurrence is analyzed over global land areas for 1950‐2000 using soil moisture data from a simulation of the terrestrial water cycle with the Variable Infiltration Capacity (VIC) land surface model, which is forced by an observation based meteorological data set. A monthly drought index based on percentile soil moisture values relative to the 50‐year climatology is analyzed in terms of duration, intensity and severity at global and regional scales. Short‐term droughts (&lt;= 6 months) are prevalent in the Tropics and midlatitudes, where inter‐annual climate variability is highest. Medium term droughts (7–12 months) are more frequent in mid‐ to high‐latitudes. Long term (12+ months) droughts are generally restricted to sub‐Saharan Africa and higher northern latitudes. The Sahel region stands out for having experienced long‐term and severe drought conditions. Severe regional drought events are systematically identified in terms of spatial coverage, based on different thresholds of duration and intensity. For example, in northern Europe, 1996 and 1975 were the years of most extensive 3‐ and 12‐month duration drought, respectively. In northern Asia, severe drought events are characterized by persistent soil moisture anomalies over the wintertime. The drought index identifies several well‐known events, including the 1988 US, 1982/83 Australian, 1983/4 Sahel and 1965/66 Indian droughts which are generally ranked as the severest and most spatially extensive in the record. Comparison with the PDSI shows general agreement at global scales and for these major events but they diverge considerably in cooler regions and seasons, and especially in latter years when the PDSI shows a larger drying trend.

Physics-based numerical models are essential for understanding atmosphere–space interactions. These include mechanisms that perturb the upper-atmosphere dynamics and energetics associated with terrestrial weather (impact from below) and solar-geomagnetic input (impact from above). The relevant physical phenomena range from global and synoptic scales down to the kilometer-scale of mesoscale dynamics. This manuscript discusses the impact of fine-scale processes in the ionosphere–thermosphere–mesosphere (ITM) region initiated from above and below, emphasizing the current status and perspectives of their realistic representation in whole-atmosphere and thermosphere–ionosphere models. The possible pathways to address challenges in realistic predictions of the ITM and its fast variability on global and regional scales are examined. They include three powerful modeling and data analysis techniques, namely nesting, nudging, and assimilation, that need to be carefully implemented for the highly dynamical ITM domain. Reasons for potential problems to constrain the high-resolution ITM predictions by data can be attributed to sparse and diverse observations performed in different layers and the increased complexity of the multi-scale ITM processes that need to be taken into account and properly coupled (e.g., dynamics, radiation, chemistry, and electrodynamics). The multi-scale ITM dynamics are dominated by tides, gravity waves, and small-scale eddies. Constraining these with assimilation and/or nudging algorithms requires rapid data analysis to properly adjust the global and regional diurnal and sub-diurnal oscillations to match space-borne and ground-based observations.