The global signature of the ENSO and SST-like fields

Remote Monitoring of Atmospheric and Hydrophysical Characteristics of the Water Surface Based on Microwave Radiometric Measurements

This work summarizes the main characteristics of atmospheric and hydro-physical parameters of the water surface derived from microwave radiometric data. First, current knowledge based on experimental measurements and model calculations of emissivity of the atmosphere and water surface in the microwave spectrum is presented. Emphasis is placed on remote radio-physical methods that have the peculiarity of being related to atmospheric radio-transparency which is one of the main advantages of the microwave radiometric method compared to optical and infrared methods. A detailed presentation is attempted with specific examples of classification of water surface phenomena using software modules included in the system used for the processing of data of radio-physical experiments by the Cosmos-1500 satellite. In addition, the statistical characteristics of the “spotting” of radio-brightness temperatures obtained for the most informative thresholds are analyzed and it is argued that these characteristics for the Pacific areas can also be used to detect abnormal phenomena on the water surface of the Mediterranean Sea. Finally, it is emphasized that the results obtained from this work make it possible to rapidly evaluate various parameters such as temperature, water surface waves, foam formation areas, etc., providing predictions and allocating irregular areas.

Jet Stream Changes over Southeast Australia during the Early Cool Season in Response to Accelerated Global Warming

In recent decades, southeast Australia has experienced both extreme drought and record-breaking rainfall, with devastating societal impacts. Variations in the Australian polar-front jet (PFJ) and the subtropical jet (STJ) determine, for example, the location and frequency of the cool season (April–September) weather systems influencing rainfall events and, consequently, water availability for the southern half of Australia. Changes in jet stream wind speeds also are important for aviation fuel and safety requirements. A split jet occurs when the single jet separates into the STJ and PFJ in the early cool season (April–May). This study focusses on split jet characteristics over Australian/New Zealand longitudes in recent decades. During the accelerated global warming from the mid-1990s, higher mean wind speeds were found in the PJF across the Australian region during June–September, compared to the STJ. In contrast, significant wind speed increases occur in the early cool season (April–May) at STJ latitudes, which straddle the East Coast of Australia and the adjacent Tasman Sea. These changes are linked to major changes in the mean atmospheric circulation, and they include relative vorticity and humidity, both being vital for the development of rain-bearing weather systems that affect the region.

Assessment of Climate Change Impacts on Sea Surface Temperatures and Sea Level Rise—The Arabian Gulf

The Arabian Gulf is one of the regions in the world experiencing major changes due to increased economic growth rates and development practices. As a shallow water body within a hot desert, the Gulf is exposed to obvious warming in the sea surface temperatures (SST). Remotely sensed SST data were utilized to estimate decadal change in SST with a focus on coral reef locations. There is a positive trend in monthly time series SSTs, with a maximum value of about 0.7 °C/decade for the western side of the Gulf. This high trend of SST is associated with significant coral reef bleaching and it coincides with major climate/ocean interactions. Most of the Arabian countries along the Gulf have coastal developments at low-land areas of high vulnerability to sea level rise. Digital elevation models showed that there are more than 3100 km2 of coastal areas that occur at 1 m level along the Arabian countries of the Gulf. Coastal protection and conservation measures are crucial to protect low-lying coasts of urban use.

Future Temperature Extremes Will Be More Harmful: A New Critical Factor for Improved Forecasts

There is increasing evidence that extreme weather events such as frequent and intense cold spells and heat waves cause unprecedented deaths and diseases in both developed and developing countries. Thus, they require extensive and immediate research to limit the risks involved. Average temperatures in Europe in June-July 2019 were the hottest ever measured and attributed to climate change. The problem, however, of a thorough study of natural climate change is the lack of experimental data from the long past, where anthropogenic activity was then very limited. Today, this problem can be successfully resolved using, inter alia, biological indicators that have provided reliable environmental information for thousands of years in the past. The present study used high-resolution quantitative reconstruction data derived from biological records of Lake Silvaplana sediments covering the period 1181-1945. The purpose of this study was to determine whether a slight temperature change in the past could trigger current or future intense temperature change or changes. Modern analytical tools were used for this purpose, which eventually showed that temperature fluctuations were persistent. That is, they exhibit long memory with scaling behavior, which means that an increase (decrease) in temperature in the past was always followed by another increase (decrease) in the future with multiple amplitudes. Therefore, the increase in the frequency, intensity, and duration of extreme temperature events due to climate change will be more pronounced than expected. This will affect human well-being and mortality more than that estimated in today's modeling scenarios. The scaling property detected here can be used for more accurate monthly to decadal forecasting of extreme temperature events. Thus, it is possible to develop improved early warning systems that will reduce the public health risk at local, national, and international levels.

The Earth's Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled "nature-society system (NSS) model", through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts.

On the progress of the 2015–2016 El Niño event

Abstract. It has been recently reported that the current 2015–2016 El Niño could become "one of the strongest on record". To further explore this claim, we performed the new analysis described in detail in Varotsos et al. (2015) that allows the detection of precursory signals of the strong El Niño events by using a recently developed non-linear dynamics tool. In this context, the analysis of the Southern Oscillation Index time series for the period 1876–2015 shows that the running 2015–2016 El Niño would be rather a "moderate to strong" or even a "strong" event and not “one of the strongest on record", as that of 1997–1998.

Scaling regimes and linear/nonlinear responses of last millennium climate to volcanic and solar forcings

Abstract. At scales much longer than the deterministic predictability limits (about 10 days), the statistics of the atmosphere undergoes a drastic transition, the high-frequency weather acts as a random forcing on the lower-frequency macroweather. In addition, up to decadal and centennial scales the equivalent radiative forcings of solar, volcanic and anthropogenic perturbations are small compared to the mean incoming solar flux. This justifies the common practice of reducing forcings to radiative equivalents (which are assumed to combine linearly), as well as the development of linear stochastic models, including for forecasting at monthly to decadal scales. In order to clarify the validity of the linearity assumption and determine its scale range, we use last millennium simulations, with both the simplified Zebiak–Cane (ZC) model and the NASA GISS E2-R fully coupled GCM. We systematically compare the statistical properties of solar-only, volcanic-only and combined solar and volcanic forcings over the range of timescales from 1 to 1000 years. We also compare the statistics to multiproxy temperature reconstructions. The main findings are (a) that the variability in the ZC and GCM models is too weak at centennial and longer scales; (b) for longer than  ≈  50 years, the solar and volcanic forcings combine subadditively (nonlinearly) compounding the weakness of the response; and (c) the models display another nonlinear effect at shorter timescales: their sensitivities are much higher for weak forcing than for strong forcing (their intermittencies are different) and we quantify this with statistical scaling exponents.