Prediction of Surface Temperature and CO2 Emission using a novel grey system model

The increase in surface temperature and CO2 emissions are two of the most important issues in climate studies and global warming. The ‘Global Emissions 2021’ report identifies the six biggest contributors to CO2­ emissions; China, USA, India, Russia, Japan, and Germany. The current study projects the increase in surface temperature and the CO­2 emissions of these six countries by 2028. The EGM (1,1,α,θ) grey model is an even form of the model with a first order differential equation, that has one variable and a weightage background value that contains conformable fractional accumulation. The results show that while the CO2 emissions for Japan, Germany, USA and Russia show a downward projection, they are expected to increase in India and remain nearly constant in China by 2028. The surface temperature has been projected to increase at a significant rate in all these countries. By comparing with the EGM (1,1) grey model, the results show that the EGM (1,1, α, θ) model performs better in both in-sample and out-of-sample forecasting. The paper also puts forward some policy suggestions to mitigate, manage and reduce increases in surface temperature as well as CO2 emissions.

Quantifying Local and Mesoscale Drivers of the Urban Heat Island of Moscow with Reference and Crowdsourced Observations

Urban climate features, such as the urban heat island (UHI), are determined by various factors characterizing the modifications of the surface by the built environment and human activity. These factors are often attributed to the local spatial scale (hundreds of meters up to several kilometers). Nowadays, more and more urban climate studies utilize the concept of the local climate zones (LCZs) as a proxy for urban climate heterogeneity. However, for modern megacities that extend to dozens of kilometers, it is reasonable to suggest a significant contribution of the larger-scale factors to the temperature and UHI climatology. In this study, we investigate the contribution of local-scale and mesoscale driving factors of the nocturnal canopy layer UHI of the Moscow megacity in Russia. The study is based on air temperature observations from a dense network consisting of around 80 reference and more than 1,500 crowdsourced citizen weather stations for a summer and a winter season. For the crowdsourcing data, an advanced quality control algorithm is proposed. Based on both types of data, we show that the spatial patterns of the UHI are shaped both by local-scale and mesoscale driving factors. The local drivers represent the surface features in the vicinity of a few hundred meters and can be described by the LCZ concept. The mesoscale drivers represent the influence of the surrounding urban areas in the vicinity of 2–20 km around a station, transformed by diffusion, and advection in the atmospheric boundary layer. The contribution of the mesoscale drivers is reflected in air temperature differences between similar LCZs in different parts of the megacity and in a dependence between the UHI intensity and the distance from the city center. Using high-resolution city-descriptive parameters and different statistical analysis, we quantified the contributions of the local- and mesoscale driving factors. For selected cases with a pronounced nocturnal UHI, their respective contributions are of similar magnitude. Our findings highlight the importance of taking both local- and mesoscale effects in urban climate studies for megacities into account. Furthermore, they underscore a need for an extension of the LCZ concept to take mesoscale settings of the urban environment into account.

Weather Forecasting in Brazil: A Concise Historical Review

The main objective of this article is to describe the factors and issues responsible for the evolution of the weather forecast in Brazil.This is done based on a historical review of the formation and evolution of the national meteorological services in the last 170 yearsand on the development of weather forecasting methods. Changes in the routines of weather forecasting services in two centenaryBrazilian institutions, the National Institute of Meteorology and the Brazilian Navy, since the creation of the first subjective forecaststo the present day, are highlighted. Information about the 14 undergraduate courses in Meteorology in Brazil is given, which supportthe technological development of this science, through scientific research and training of human resources. The introduction ofmeteorological radar in the 1970s, and its current networks, as well as the elaboration of the first numerical weather predictions (NWP)by the Center for Weather Forecasting and Climate Studies (Centro de Previsão do Tempo e Estudos Climáticos do Instituto Nacionalde Pesquisas Espaciais – CPTEC/INPE), in 1995, are also described. To complement, a survey is presented, showing the currentworking conditions of weather forecasters. The survey results reveal that 45% of the 102 meteorologists interviewed use the CzechRepublic Windy application to prepare their weather forecasts operationally and almost 60% use the Wyoming University website toobtain data from radiosondes launched in Brazil. It is important to highlight that, since the introduction of NWP by CPTEC/INPE, at theend of the 1990s, there has been a great advance in the field of weather forecasting. Moreover, observational networks have undergonea great expansion, with a significant increase in the number of weather stations in recent decades. Despite all the progress achieved,there is still a need for the integration of observational networks and databases of various institutions. Finally, the development ofapplications that meet the demand of young meteorologists in the operational centers is advisable.

Influence of environmental conditions on plants in different climatic zones

Due to global shifts in climate, studies in contrasting conditions of two natural and climatic zones are of particular interest: (1) subzone of mixed and broad-leaved forests, (2) south-steppe subzone. In the period 2019-2020, 308 plant species from 56 families were surveyed. Phytopathogens damage plants, and therefore increase the loss of quality of plant materials. The frequency of occurrence of mycoses in autumn is 2-14 times higher than in spring-summer observations. The activity of phytopathogenic fungi of the genera of Fusarium (the causative agent of fusarium), Puccinia (rust), Phoma (phomosis), Rhizoctonia (scab), Verticillium (tracheomycotic or vascular wilting) increases. Differences in dominant micromycetes from the point of view of geography were determined: zone 1 (forest) - Alternaria spp., Chaetomium spp., Fusarium spp., F. avenaceum (Fr.) Sacc., (Mart.) Sacc., Heterosporium iridis (Fautrey & Roum.) JE Jacques, Phoma spp., Stemphylium spp., Verticillium spp.; zone 2 (steppe) – Alternaria spp., Botrytis spp., Cladosporium spp., Fusarium avenaceum, Fusarium spp., Peronospora spp., Phoma spp., Pullularia spp., Septoria spp. Screening of pesticides (biological fungicides) showed the effectiveness of preparations based on Pseudomonas fluorescens, Bacillus subtilis or Streptomyces griseus in limiting the growth of the mycelium of phytopathogenic fungi.

The effect of using local mean versus constant reference salinity to estimate Arctic Ocean freshwater content changes

Changes of high-latitude freshwater content (FWC) play an important role in shaping the variability of polar oceans. FWC is defined as depth-integrated departure of salinity from a reference salinity Sref divided by this Sref . A constant Sref is often used for high-latitude FWC estimates. Here it is argued that for analyzing FWC spatiotemporal changes the use of local mean Sref is a better choice. Analysis of 2007 FWC anomalies in the 25–75 m layer demonstrated, for example, that the choice of Sref = 34.8 (which is often used in climate studies) leads to FWC spatial anomalies exaggerated, on average, by ~0.6 m, which is a substantial fraction of total spatial FWC changes. The problem is aggravated in areas where the difference between the local Sref and Sref = 34.8 is greater. Thus, it is concluded that using climatological mean salinities as Sref provides superior estimates of spatiotemporal Arctic Ocean FWC changes.