Halogenated Greenhouse Gases Made Global Warming Primarily

Time-series observations of global lower stratospheric temperature (GLST), global land surface air temperature (LSAT), global mean surface temperature (GMST), sea ice extent (SIE) and snow cover extent (SCE), together with observations reported in Paper I, combined with theoretical calculations of GLSTs and GMSTs, have provided strong evidence that ozone depletion and global climate changes are dominantly caused by human-made halogen-containing ozone-depleting substances (ODSs) and greenhouse gases (GHGs) respectively. Both GLST and SCE have become constant since the mid-1990s and GMST/LSAT has reached a peak since the mid-2000s, while regional continued warmings at the Arctic coasts (particularly Russia and Alaska) in winter and spring and at some areas of Antarctica are observed and can be well explained by a sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free warming theory of halogenated GHGs show an excellent agreement with the observed GMSTs after the natural El Niño southern oscillation (ENSO) and volcanic effects are removed. These results provide a convincing mechanism of global climate change and will make profound changes in our understanding of atmospheric processes. This study also emphasizes the critical importance of continued international efforts in phasing out all anthropogenic halogenated ODSs and GHGs.

Relationships between Vertical Temperature Gradients and PM10 Concentrations during Selected Weather Conditions in Upper Silesia (Southern Poland)

This paper studies surface air temperature inversions and their impact on air pollution under the background of meteorological conditions in southern Poland. The relationship of temperature gradients and air quality classes with weather conditions in the most urbanized and polluted part of Poland as represented by the Upper Silesia region (USR) within the administrative boundaries of the Górnośląsko-Zagłębiowska Metropolis (GZM) is presented. Based on probability analysis this study hierarchized the role of the selected weather elements in the development of surface-based temperature inversion (SBI) and air quality (AQ). The thresholds of weather elements for a rapid increase in the probability of oppressive air pollution episodes were distinguished. Although most SBI occurred in summer winter SBIs were of great importance. In that season a bad air quality occurred during >70% of strong inversions and >50% of moderate inversions. Air temperature more strongly triggered AQ than SBI development. Wind speed was critical for SBI and significant for AQ development. A low cloudiness favored SBI occurrence altered air quality in winter and spring during SBI and favored very bad AQ5 (>180 µg/m3) occurrence. The probability of high air pollution enhanced by SBI rapidly increased in winter when the air temperature dropped below −6 °C the wind speed decreased below 1.5 m/s and the sky was cloudless. Changes in the relative humidity did not induce rapid changes in the occurrence of bad AQ events during SBI

Intra-seasonal variation of surface air temperature in Nepal Himalayas

Intra-seasonal variation of surface air temperature observed by the automatic weather station at Syangpoche in Khumbu region, Nepal Himalayas, is analyzed. In the monsoon season, temperature was nearly constant with large decrease in insolation due to monsoon clouds. On the other hand, large intra-seasonal variation existed in the winter with increase in temperature associated with passing synoptic scale high-pressure system which disturb local circulation pattern as well as decrease in temperature due to the nighttime strong radiative cooling under the condition of snow covers. Monsoon clouds and deep valley system caused unique surface temperature variation.

Comparison of Early Twentieth Century Arctic Warming and Contemporary Arctic Warming in the light of daily and sub-daily data

A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the Early Twentieth Century Arctic Warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and sub-daily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from ten individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days; day-to-day temperature variability; and onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the Contemporary Arctic Warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7 °C) and Canadian Arctic (1.9 °C) regions. A shortening of winter and lengthening of summer were registered. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW.

FOCI-MOPS v1 – Integration of Marine Biogeochemistry within the Flexible Ocean and Climate Infrastructure version 1 (FOCI 1) Earth system model

The consideration of marine biogeochemistry is essential for simulating the carbon cycle in an Earth system model. Here we present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, air-sea gas exchange of CO2 and O2, and simulations with prescribed atmospheric CO2 or CO2 emissions. A series of experiments covering the historical period (1850–2014) were performed following the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP6 (Coupled Model Intercomparison Project 6) protocols. Overall, modelled biogeochemical tracer distributions and fluxes, as well as transient evolution in surface air temperature, air-sea CO2 fluxes, and changes of ocean carbon and heat, are in good agreement with observations. Modelled inorganic and organic tracer distributions are quantitatively evaluated by statistically-derived metrics. Results of the FOCI-MOPS model, also including sea surface temperature, surface pH, oxygen (100–600 m), nitrate (0–100 m), and primary production, are within the range of other CMIP6 model results. Overall, the evaluation of FOCI-MOPS indicates its suitability for Earth climate system simulations.

Recent atmospheric changes and future projections along the Saudi Arabian Red Sea Coast

Recent and future climate diagrams (surface air temperature, surface relative humidity, surface wind, and mean sea level pressure) for the Saudi Arabian Red Sea Coast are analysed based on hourly observations (2016–2020) and hourly ERA5 data (1979–2020) with daily GFDL mini-ensemble means (2006–2100). Moreover, GFDL mini-ensemble means are calculated based on the results of three GFDL simulations (GFDL-CM3, GFDL-ESM2M, and GFDL-ESM2G). Observation data are employed to describe the short-term current weather variability. However, ERA5 data are considered to study the long-term current weather variability after bias removal via a comparison to observations. Finally, a bias correction statistical model was developed by matching the cumulative distribution functions (CDFs) of corrected ERA5 and mini-ensemble mean data over 15 years (2006–2020). The obtained local statistic were used to statically downscale GFDL mini-ensemble means to study the future uncertainty in the atmospheric parameters studied. There occurred significant spatial variability across the study area, especially regarding the surface air temperature and relative humidity, based on monthly analysis of both observation and ERA5 data. Moreover, the results indicated that the ERA5 data suitably describe Tabuk, Jeddah and Jizan weather conditions with a marked spatial variability. The best performance of ERA5 surface air temperature and relative humidity (surface wind speed and sea level pressure) data was detected in Tabuk (Jeddah). These data for the Saudi Arabian Red Sea coast, 1979–2020, exhibit significant positive trends of the surface air temperature and surface wind speed and significant negative trends of the relative humidity and sea level pressure. The GFDL mini-ensemble mean projection result, up to 2100, contains a significant bias in the studied weather parameters. This is partly attributed to the coarse GFDL resolution (2° × 2°). After bias removal, the statistically downscaled simulations based on the GFDL mini-ensemble mean indicate that the climate in the study area will experience significant changes with a large range of uncertainty according to the considered scenario and regional variations.

Causes and Mechanisms of Global Warming/Climate Change

Comparison of the average mean surface air temperature around the world during 1951–1978 with that for 2010–2019 shows that the bulk of the warming is around the North Atlantic/Arctic region in contrast to the Antarctic ice sheet. Obviously, the temperature change is not global. Since there is a substantial difference between solar heat absorption between the equator and the poles, heat must be moving to the North Pole by surface ocean currents and tropical cyclones. The cold, dry Arctic air coming from Siberia picks up heat and moisture from the open oceans, making the sea water denser so that the warm water sinks slowly down to c. 2000 m. A deep-water thermohaline flow (THC) transports the excess hot (c. 18°C) water south to Antarctica. It is replaced by a cold (c. 2°C) surface water from that area. The latter quickly cool western Europe and Siberia, and glaciers start to advance in Greenland within about 10 years. The THC flow decreases in Interglacials, causing the increased build-up of heat in the Northern Hemisphere (c. 60% currently stored in the Atlantic Ocean), and the ice cover in the Arctic Ocean thaws. Several such cycles may take place during a single major cold event.

Seasonal Variability in the Mechanisms Behind the 2020 Siberian Heatwaves

Record breaking heatwaves and wildfires immersed Siberia during the boreal spring of 2020 following an anomalously warm winter. Springtime heatwaves are becoming more common in the region, with statistically significant trends in the frequency, magnitude, and duration of heatwave events over the past four decades. Mechanisms by which the heatwaves occur and contributing factors differ by season. Winter heatwave frequency is correlated with the atmospheric circulation, particularly the Arctic Oscillation, while the frequency of heatwaves during the spring months is highly correlated with aspects of the land surface including snow cover, albedo, and latent heat flux. Idealized AMIP-style experiments are used to quantify the contribution of suppressed Arctic sea ice and snow cover over Siberia on the atmospheric circulation, surface energy budget, and surface air temperature in Siberia during the winter and spring of 2020. Sea ice concentration contributed to the strength of the stratospheric polar vortex and Arctic Oscillation during the winter months, thereby influencing the tropospheric circulation and surface air temperature over Siberia. Warm temperatures across the region resulted in an earlier than usual recession of the winter snowpack. The exposed land surface contributed to up to 20% of the temperature anomaly during the spring through the albedo feedback and changes in the ratio of the latent and sensible heat fluxes. This, in combination with favorable atmospheric circulation patterns, resulted in record breaking heatwaves in Siberia in the spring of 2020.

Variability of Indian summer monsoon: Relationship with surface air temperature anomalies over northern hemisphere

Thirty year (1950-79) time series of Monsoon Index (MI) is correlated with the gridded surface air temperature data over northern hemisphere land at various time lags of months (i.e., months preceding concurrent and succeeding to the monsoon season) to identify tele-connections of monsoon with the northern hemisphere surface air temperature anomalies. . Out of three key regions identified which show statistically significant relationship of monsoon rainfall, two regions are in the higher latitudinal belt of 40oN- 70oN over North America and Eurasia which show positive correlations with temperatures during northern winter particularly during January and February. The third region is located over northwest India and adjoining Pakistan, where the maximum positive correlation is observed to occur during the pre-li1onsoon months of April and May. These relationships suggest that cooler northern hemisphere during the preceding seasons of winter/spring over certain key regions are generally associated with below normal summer monsoon rainfall over India and vice-versa which could be useful predictors for long-range forecasting of monsoon. There are two large regions in the northern tropics, namely, Asian and African monsoons whose temperatures reveal strong negative correlations with monsoon rainfall during the seasons concurrent and subsequent to the summer monsoon season. However, persistence of this relationship for longer period of about two seasons after the monsoon, suggests the dominant influence of ENSO (El. Nino-Southern Oscillation) on tropical climate.