Explore the vast range of titles available.

Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, \"sound science.\" In A Vast Machine Paul Edwards has news for these doubters: without models, there are no data. Today, no collection of signals or observations--even from satellites, which can \"see\" the whole planet with a single instrument--becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere--to measure it, trace its past, and model its future. Edwards argues that all our knowledge about climate change comes from three kinds of computer models: simulation models of weather and climate; reanalysis models, which recreate climate history from historical weather data; and data models, used to combine and adjust measurements from many different sources. Meteorology creates knowledge through an infrastructure (weather stations and other data platforms) that covers the whole world, making global data. This infrastructure generates information so vast in quantity and so diverse in quality and form that it can be understood only by computer analysis--making data global. Edwards describes the science behind the scientific consensus on climate change, arguing that over the years data and models have converged to create a stable, reliable, and trustworthy basis for the reality of global warming.

Relocation of earthquakes recorded by the agency for meteorology, climatology and geophysics (BMKG) in Indonesia and inversions of global positioning system (GPS) data reveal clear seismic gaps to the south of the island of Java. These gaps may be related to potential sources of future megathrust earthquakes in the region. To assess the expected inundation hazard, tsunami modeling was conducted based on several scenarios involving large tsunamigenic earthquakes generated by ruptures along segments of the megathrust south of Java. The worst-case scenario, in which the two megathrust segments spanning Java rupture simultaneously, shows that tsunami heights can reach ~ 20 m and ~ 12 m on the south coast of West and East Java, respectively, with an average maximum height of 4.5 m along the entire south coast of Java. These results support recent calls for a strengthening of the existing Indonesian Tsunami Early Warning System (InaTEWS), especially in Java, the most densely populated island in Indonesia.

Flash droughts can be distinguished by rapid intensification from near-normal soil moisture to drought conditions in a matter of weeks. Here, we provide the first characterisation of a climatology of flash drought across Australia using a suite of indices. The experiment is designed to capture a range of conditions related to drought: evaporative demand describes the atmospheric demand for moisture from the surface; precipitation, the supply of moisture from the atmosphere to the surface; and evaporative stress, the supply of moisture from the surface relative to the demand from the atmosphere. We show that regardless of the definition, flash droughts occur in all seasons. They can terminate as rapidly as they start, but in some cases can last many months, resulting in a seasonal-scale drought. We show that flash-drought variability and its prevalence can be related to phases of the El Niño–Southern Oscillation, highlighting scope for seasonal-scale prediction. Using a case study in southeast Australia, we show that monitoring precipitation is less useful for capturing the onset of flash drought as it occurs. Instead, indices like the Evaporative Demand Drought Index and Evaporative Stress Index are more useful for monitoring flash-drought development.

Amines at typical atmospheric concentrations of a only few molecules per trillion air molecules combine with sulphuric acid to form highly stable aerosol particles at rates similar to those observed in the lower atmosphere. Atmospheric chemistry of anthropogenic amines Amines emitted into the atmosphere from anthropogenic sources are thought to enhance nucleation from trace atmospheric vapours, stimulate particle formation and influence the development and properties of clouds. Direct evidence for this under atmospheric conditions has been lacking; however, this study, using the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN, demonstrates that amines at atmospherically relevant concentrations can sufficiently increase nucleation rates to be able to account for the particle formation rates observed in the atmospheric environment. Nucleation of aerosol particles from trace atmospheric vapours is thought to provide up to half of global cloud condensation nuclei 1 . Aerosols can cause a net cooling of climate by scattering sunlight and by leading to smaller but more numerous cloud droplets, which makes clouds brighter and extends their lifetimes 2 . Atmospheric aerosols derived from human activities are thought to have compensated for a large fraction of the warming caused by greenhouse gases 2 . However, despite its importance for climate, atmospheric nucleation is poorly understood. Recently, it has been shown that sulphuric acid and ammonia cannot explain particle formation rates observed in the lower atmosphere 3 . It is thought that amines may enhance nucleation 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , but until now there has been no direct evidence for amine ternary nucleation under atmospheric conditions. Here we use the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN and find that dimethylamine above three parts per trillion by volume can enhance particle formation rates more than 1,000-fold compared with ammonia, sufficient to account for the particle formation rates observed in the atmosphere. Molecular analysis of the clusters reveals that the faster nucleation is explained by a base-stabilization mechanism involving acid–amine pairs, which strongly decrease evaporation. The ion-induced contribution is generally small, reflecting the high stability of sulphuric acid–dimethylamine clusters and indicating that galactic cosmic rays exert only a small influence on their formation, except at low overall formation rates. Our experimental measurements are well reproduced by a dynamical model based on quantum chemical calculations of binding energies of molecular clusters, without any fitted parameters. These results show that, in regions of the atmosphere near amine sources, both amines and sulphur dioxide should be considered when assessing the impact of anthropogenic activities on particle formation.

The process of forming a settlement is inseparable from the influence of ecology (the natural environment) and the influence of socio-cultural (human). Natural elements, namely the sun, climate, soil topography, and human way of life are synergized mutually so that a settlement could exist and developed. Such things also apply to waterfront settlements (habitation located on the water's edge), even though that settlements located at the waterfront could face a rather distinguish climatology issues. This study aims to learn about the development of waterfront settlements and the influence of ecology, social and cultural elements in shaping waterfront settlements in Pangururan sub-district. The research method used by researchers is a qualitative method, using observation and interviews. The benefits of this research are to find the concept of waterfront settlements based on ecology, sociology, and culture that can support the lives of people living in these settlements so that the government can apply the concept in various regions that have the same environmental conditions.

The 2019 positive Indian Ocean Dipole (IOD) event in the boreal autumn was the most serious IOD event of the century with reports of significant sea surface temperature (SST) changes in the east and west equatorial Indian Ocean. Observations of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) between 2012 and 2020 are used to study the significant biological dipole response that occurred in the equatorial Indian Ocean following the 2019 positive IOD event. For the first time, we propose, identify, characterize, and quantify the biological IOD. The 2019 positive IOD event led to anomalous biological activity in both the east IOD zone and west IOD zone. The average chlorophyll-a (Chl-a) concentration reached over ~ 0.5 mg m −3 in 2019 in comparison to the climatology Chl-a of ~ 0.3 mg m −3 in the east IOD zone. In the west IOD zone, the biological activity was significantly depressed. The depressed Chl-a lasted until May 2020. The anomalous ocean biological activity in the east IOD zone was attributed to the advection of the higher-nutrient surface water due to enhanced upwelling. On the other hand, the dampened ocean biological activity in the west IOD zone was attributed to the stronger convergence of the surface waters than that in a normal year.

Extreme precipitation is one of the most devastating forms of atmospheric phenomenon, causing severe damage worldwide, and is likely to intensify in strength and occurrence in a warming climate. This contribution gives an overview of the potential and challenges associated with using weather radar data to investigate extreme precipitation. We illustrate this by presenting radar data sets for Germany, the U.S. and the UK that resolve small-scale heavy rainfall events of just a few km2 with return periods of 5 years or more. Current challenges such as relatively short radar records and radar-based QPE uncertainty are discussed. An example from a precipitation climatology derived from the German weather radar network with spatial resolution of 1 km reveals the necessity of radars for observing short-term (1-6 h) extreme precipitation. Only 17.3% of hourly heavy precipitation events that occurred in Germany from 2001 to 2018 were captured by the rain gauge station network, while 81.8% of daily events were observed. This is underlined by a similar study using data from the UK radar network for 2014. Only 36.6% (52%) of heavy hourly (daily) rain events detected by the radar network were also captured by precipitation gauging stations. Implications for the monitoring of hydrologic extremes are demonstrated over the U.S. with a continental-scale radar-based reanalysis. Hydrologic extremes are documented over ∼1000 times more locations than stream gauges, including in the majority of ungauged basins. This underlines the importance of high-resolution weather radar observations for resolving small-scale rainfall events, and the necessity of radar-based climatological data sets for understanding the small-scale and high-temporal resolution characteristics of extreme precipitation.

Satellite precipitation products have been largely improved in the recent years particularly with the launch of the global precipitation measurement (GPM) core satellite. Moreover, the development of techniques for exploiting the information provided by satellite soil moisture to complement/enhance precipitation products have improved the accuracy of accumulated rainfall estimates over land. Such satellite enhanced precipitation products, available with a short latency (< 1 day), represent an important and new source of information for river flow prediction and water resources management, particularly in developing countries in which ground observations are scarcely available and the access to such data is not always ensured. In this study, three recently developed rainfall products obtained from the integration of GPM rainfall and satellite soil moisture products have been used; namely GPM+SM2RAIN, PRISM-SMOS, and PRISM-SMAP. The prediction of observed daily river discharge at 10 basins located in Europe (4), West Africa (3) and South Africa (3) is carried out. For comparison, we have also considered three rainfall products based on: (1) GPM only, i.e., the Early Run version of the Integrated Multi-Satellite Retrievals for GPM (GPM-ER), (2) rain gauges, i.e., the Global Precipitation Climatology Centre, and (3) the latest European Centre for Medium-Range Weather Forecasts reanalysis, ERA5. Three different conceptual and lumped rainfall-runoff models are employed to obtain robust and reliable results over the 3-year data period 2015–2017. Results indicate that, particularly over scarcely gauged areas (West Africa), the integrated products outperform both ground- and reanalysis-based rainfall estimates. For all basins, the GPM+SM2RAIN product is performing the best among the short latency products with mean Kling–Gupta Efficiency (KGE) equal to 0.87, and significantly better than GPM-ER (mean KGE = 0.77). The integrated products are found to reproduce particularly well the high flows. These results highlight the strong need to disseminate such integrated satellite rainfall products for hydrological (and agricultural) applications in poorly gauged areas such as Africa and South America.

The energy balance of the Earth is controlled by the shortwave and longwave radiation emitted to space. Changes in the thermodynamic state of the system over time affect climate and are noticeable when viewing the system as a whole. In this paper, we study the changes in the complexity of climate in the last four decades using data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). First, we study the complexity of the shortwave and longwave radiation fields independently using Approximate Entropy and Sample Entropy, observing that the rate of complexity change is faster for shortwave radiation. Then, we study the causality of those changes using Transfer Entropy to capture the non-linear dynamics of climate, showing that the changes are mainly driven by the variations in shortwave radiation. The observed behavior of climatic complexity could be explained by the changes in cloud amount, and we research that possibility by investigating its evolution from a complexity perspective using data from the International Satellite Cloud Climatology Project (ISCCP).