Present state of knowledge of the upper atmosphere: An assessment report; processes that control ozone and other climatically important trace gases

The state of knowledge of the upper atmosphere was assessed as of January 1986. The physical, chemical, and radiative processes which control the spatial and temporal distribution of ozone in the atmosphere; the predicted magnitude of ozone perturbations and climate changes for a variety of trace gas scenarios; and the ozone and temperature data used to detect the presence or absence of a long term trend were discussed. This assessment report was written by a small group of NASA scientists, was peer reviewed, and is based primarily on the comprehensive international assessment document entitled Atmospheric Ozone 1985: Assessment of Our Understanding of the Processes Controlling Its Present Distribution and Change, to be published as the World Meteorological Organization Global Ozone Research and Monitoring Project Report No. 16

Perceiving the Trend of Terrestrial Climate Change during the Past 40 year (1978-2018)

In past few decades, climate has manifested numerous shifts in its trend. Various natural and anthropogenic factors have influenced the dynamics and the trends of climate change at longer time scale. To understand the long term climate fluctuations, we have analyzed forty years (1978 - 2018) data of ten climatic parameters that are responsible to influence the climate dynamics. The parameters involved in the present study are total solar irradiance (TSI), ultra violet (UV) index, cloud cover, carbon dioxide (CO2) abundances, multivariate (ENSO) index, volcanic explosivity index (VEI), global surface temperature (GST) anomaly, global sea ice extent, global mean sea level and global precipitation anomaly. Using the above mentioned climate entities; we have constructed a proxy index to study the quantitative measure of the climate change. In this process these indicators were aggregated to a single proxy index as global climate index (GCI) that has measured the strength of present climate change in semblance with the past natural variability. To construct GCI, the principal component analysis (PCA) has been used on yearly based data for the period 1978 - 2018. Actually PCA is a statistical tool with which we can reduce the dimensionality of the data and it retains most of the variation in the new data set. Further, we have confined our study to natural climate drivers and anthropogenic climate drivers. Our result has indicated that the strongest climate change has been occurred globally by the end of the year 2018 in comparison to late 1970’s natural variability

Geodynamic monitoring of development of a karst on the basis of georadar sounding

The questions of practical application of georadar sounding for the detailed studying of development of a karst were considered in the article. The importance of the problem being solved for the planning of construction and further operation of industrial facilities in karst limestone areas is emphasized. In the last case, the geodynamic control of karst zones is necessary, as operation of objects in these zones is economi

Impact of ocean warming on sustainable fisheries management informs the Ecosystem Approach to Fisheries

Acknowledgements Serpetti N., Heymans J.J., and Burrows M.T. were funded by the Natural Environment Research Council and Department for Environment, Food and Rural Affairs under the Marine Ecosystems Research Programme (MERP) (grant No. NE/L003279/1). Baudron A. and Fernandes, P.G. were founded by Horizon 2020 European research projects MareFrame (grant No. 613571) and ClimeFish (grant No. 677039). Payne, B.L. was founded by the Natural Environment Research Council and Department for Environment under the ‘Velocity of Climate Change’ (grant No. NE/J024082/1).Peer reviewedPublisher PD

Application of a phase-measuring method in the inclinometric systems of geotechnical monitoring

The article considers the issue of the possibility of applying the phase-measuring method in inclinometric systems of geotechnical monitoring. The main problems with use of the inclinometric systems of geotechnical monitoring. The causes, causing the occurrence of angular measurement error

Trend analysis using non-stationary time series clustering based on the finite element method

In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950–2009 can be explained mostly by AMO and solar activity

Monte Carlo strategies for calibration in climate models

Intensive computational methods have been used by Earth scientists in a wide range of problems in data inversion and uncertainty quantification such as earthquake epicenter location and climate projections. To quantify the uncertainties resulting from a range of plausible model configurations it is necessary to estimate a multidimensional probability distribution. The computational cost of estimating these distributions for geoscience applications is impractical using traditional methods such as Metropolis/Gibbs algorithms as simulation costs limit the number of experiments that can be obtained reasonably. Several alternate sampling strategies have been proposed that could improve on the sampling efficiency including Multiple Very Fast Simulated Annealing (MVFSA) and Adaptive Metropolis algorithms. As a goal of this research, the performance of these proposed sampling strategies are evaluated with a surrogate climate model that is able to approximate the noise and response behavior of a realistic atmospheric general circulation model (AGCM). The surrogate model is fast enough that its evaluation can be embedded in these Monte Carlo algorithms. The goal of this thesis is to show that adaptive methods can be superior to MVFSA to approximate the known posterior distribution with fewer forward evaluations. However, the adaptive methods can also be limited by inadequate sample mixing. The Single Component and Delayed Rejection Adaptive Metropolis algorithms were found to resolve these limitations, although challenges remain to approximating multi-modal distributions. The results show that these advanced methods of statistical inference can provide practical solutions to the climate model calibration problem and challenges in quantifying climate projection uncertainties. The computational methods would also be useful to problems outside climate prediction, particularly those where sampling is limited by availability of computational resources

Long-Term Warming And The Size And Phenology Of Long Island Sound Plankton

In coastal ecosystems with decades of eutrophication and other anthropogenic stressors, the impact of climate change on planktonic communities can be difficult to detect. A time-series of monthly surface water temperatures in the Central Basin of Long Island Sound (LIS) from the late 1940s until 2012 indicates a warming rate of 0.03°C per year, with recent summer temperatures increasing most consistently. During this warming trend, the proportion of chlorophyll produced by smaller phytoplankton and flagellates appears to be higher during warmer summer and fall months, enabling an increase in annual chlorophyll despite static nutrient levels. The phenology of phytoplankton and zooplankton abundance also appears to have shifted. Relative to the 1950s, winter and spring chlorophyll blooms are reduced, summer and fall zooplankton size has decreased, the proportion of small zooplankton has increased, and summer zooplankton abundance is reduced. These changes have occurred despite a lack of evidence for increasing gelatinous zooplankton abundance, which has been suggested as a causal mechanism for reduced summer copepod abundance and enhanced summer/fall phytoplankton abundance in other systems that have experienced long-term warming. These changes confirm general predictions for the direct impacts of climate change on aquatic communities, but also highlight the important of indirect impacts due to altered trophic dynamics

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

Three-dimensional modeling of minor chemical constituents in the mesosphere/lower thermosphere region

Um die Verteilung chemisch aktiver Spurenstoffe im Höhenbereich der Mesosphäre und unteren Thermosphäre (MLT-Region) zu untersuchen, wurde ein bestehendes 3-dimensionales numerisches chemisches Transportmodell (CTM) weiterentwickelt und mit zwei unterschiedlichen Versionen eines dynamischen Modells gekoppelt. Alle wichtigen physikalischen und chemischen Prozesse wurden im Modell berücksichtigt. Zu diesen zählen die in der MLT-Region ablaufenden chemischen Reaktionen, die Photolyse, die molekulare und turbulente Diffusion sowie advektive Transportprozesse. Die wesentlichen Verbesserungen betreffen u. a. die Implementierung eines neuen Transportcodes gekennzeichnet durch extrem geringe numerische Diffusion und die Ableitung der solaren Lyman-α Strahlung aus der Sonnenfleckenrelativzahl als Proxy und deren Berücksichtigung in der Wasserdampfphotolyserate. Das verbesserte CTM wurde mit dynamischen Modellen gekoppelt, welche klimatologische Mittel (COMMA-IAP) bzw. Zustände zum realen Datum (LIMA) berechnen. Diese gekoppelten Modelle wurden insbesondere auf das Studium des Einflusses der solaren Lyman-α Strahlung auf die Aeronomie der MLT-Region, auf die autokatalytische Wasserdampfproduktion als Quelle hoher Mischungsverhältnisse in der Mesosphäre hoher sommerlicher Breiten, auf die Herausbildung des so genannten tertiären Ozonmaximums in winterlichen mittleren und hohen Breiten, auf die Untersuchung nichtlinearer Effekte in der Chemie der MLT-Region, auf den Einfluss stratosphärischer Erwärmungen auf die Spurenstoffverteilung sowie auf Trends der Spurenstoffe in der Mesosphäre auf Grund der Zunahme von Methan, Lachgas und Kohlenstoffdioxyd seit der vorindustriellen Ära angewendet.An existing time-dependent 3-dimensional numerical chemical transport model (CTM) was improved and coupled with two different versions of a dynamical model. All physical processes believed to be important are simulated, including chemical interactions, photochemical dissociation, eddy and molecular diffusion, and advection. The most essential improvements concern the implementation of a new transport scheme marked by almost zero numerical diffusion and the derivation of the solar Lyman-α flux from the sunspot number as proxy and its consideration in the photolysis rate of water vapor. The CTM was coupled with the dynamical models calculating climatologic means (COMMA-IAP) and computing the dynamical state for real dates (LIMA). These coupled models were applied to study some particular phenomena in the mesosphere-lower thermosphere (MLT-region) such as the influence of the variable Lyman-α radiation on the aeronomy, the autocatalytic water vapor production as a source of large mixing ratios within the middle to upper mesosphere in high summery latitudes during, the so-called tertiary ozone maximum formation, the investigation of nonlinear effects of the chemistry, trends of mesospheric minor constituents due to the increase of methane, nitrous oxide and carbon dioxide since the pre-industrial area