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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 157)
Nature Climate Change     Full-text available via subscription   (Followers: 149)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Climatic Change     Open Access   (Followers: 70)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Advances in Climate Change Research     Open Access   (Followers: 60)
Journal of Climate     Hybrid Journal   (Followers: 56)
Climate Policy     Hybrid Journal   (Followers: 53)
Climate Change Economics     Hybrid Journal   (Followers: 50)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
American Journal of Climate Change     Open Access   (Followers: 42)
Atmospheric Science Letters     Open Access   (Followers: 40)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Atmosphere     Open Access   (Followers: 34)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 32)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Journal of Space Weather and Space Climate     Open Access   (Followers: 31)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 30)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Space Weather     Full-text available via subscription   (Followers: 28)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
Advances in Meteorology     Open Access   (Followers: 27)
Climate Change Responses     Open Access   (Followers: 27)
Climate Resilience and Sustainability     Open Access   (Followers: 26)
Energy & Environment     Hybrid Journal   (Followers: 26)
Journal of Climate Change     Full-text available via subscription   (Followers: 25)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
International Journal of Environment and Climate Change     Open Access   (Followers: 24)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 24)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Current Climate Change Reports     Hybrid Journal   (Followers: 22)
Tellus A     Open Access   (Followers: 21)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 21)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 20)
Journal of Economic Literature     Hybrid Journal   (Followers: 20)
Global Meteorology     Open Access   (Followers: 20)
Tellus B     Open Access   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weatherwise     Hybrid Journal   (Followers: 18)
Weather and Climate Extremes     Open Access   (Followers: 18)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 14)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 12)
Climate Risk Management     Open Access   (Followers: 12)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
The Cryosphere (TC)     Open Access   (Followers: 8)
Climate Research     Hybrid Journal   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 8)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Climate of the Past (CP)     Open Access   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 7)
Climate     Open Access   (Followers: 7)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Climate Law     Hybrid Journal   (Followers: 6)
Carbon Balance and Management     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Urban Climate     Hybrid Journal   (Followers: 5)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Meteorological Applications     Open Access   (Followers: 4)
Climate Services     Open Access   (Followers: 4)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Environmental and Climate Technologies     Open Access   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
Atmospheric Environment : X     Open Access   (Followers: 3)
GeoHazards     Open Access   (Followers: 2)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Atmósfera     Open Access   (Followers: 2)
Oxford Open Climate Change     Open Access   (Followers: 2)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 2)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Nīvār     Open Access   (Followers: 1)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Journal of Agricultural Meteorology     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  

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Similar Journals
Journal Cover
Theoretical and Applied Climatology
Journal Prestige (SJR): 0.867
Citation Impact (citeScore): 2
Number of Followers: 14  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1434-4483 - ISSN (Online) 0177-798X
Published by Springer-Verlag Homepage  [2469 journals]
  • Hydrological drought dynamics and its teleconnections with large-scale
           climate indices in the Xijiang River basin, South China

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      Abstract: Abstract Hydrological drought is a highly complex and extreme natural disaster, which has increased in deficit, areal extent, and frequency with the penetration of climate change impact. For better anticipating hydrological droughts, it is crucial to evaluate hydrological drought and its teleconnections with large-scale climate indices (LSCI) effectively. This study estimated the dynamics and patterns of hydrological drought in the near-real river networks by virtue of the standardized runoff index (SRI) based on VIC and large-scale routing model in the Xijiang River basin, and revealed their teleconnections with the climate indices. Results show that model simulation can reasonably reveal the hydrological drought evolutions in near-real river networks and effectively expose the drought downward spread along main channels. The drought spread distances in Hongshuihe and Yujiang Rivers are farther under the comprehensive influence of climate, topography, and watershed shape. Hydrological drought evolutions in the upper reaches are mainly manifested as three patterns, including S12 (simultaneous significant changes in drought intensity, concentration degree, and frequency), S7(simultaneous significant changes in drought intensity and frequency), and S1(single significant change in drought intensity). These drought dynamic patterns are majority affected by climate variation patterns M1 (warm and cold AMO), M3 (cold PDO), and M7 (warm AMO/AO). For decision-makers, this work is beneficial for understanding and anticipating hydrological droughts in the river networks, and further selecting management strategies for water resources.
      PubDate: 2022-08-04
       
  • Future projections of daily maximum and minimum temperatures over East
           Asia for the carbon neutrality period of 2050-2060

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      Abstract: Abstract Future climate projections provide vital information for preventing and reducing disaster risks induced by the global warming. However, little attention has been paid to climate change projections oriented towards carbon neutrality. In this study, we address projected changes in daily maximum (Tmax) and minimum (Tmin) temperatures as well as diurnal temperature range (DTR) over East Asia for the carbon neutrality period of 2050–2060 under the newly available SSP1-1.9 pathway of sustainable development by using CMIP6 model simulations. CMIP6 multi-model ensemble results show that Tmax and Tmin will significantly increase with varying magnitudes during the carbon neutrality period of 2050–2060 under SSP1-1.9 over the whole East Asia while both upward and downward changes will occur for the DTR. Projected Tmax, Tmin, and DTR changes all exhibit new spatial patterns during 2050–2060 under SSP1-1.9 compared with those over the same period under SSP2-4.5 and SSP5-8.5. Compared to 1995–2014, projected Tmax and Tmin averaged over East Asia during 2050–2060 will significantly warm up by 1.43 ℃ and 1.40 ℃ under SSP1-1.9, while the warming magnitudes are 1.93 ℃ and 2.04 ℃ under SSP2-4.5, and 2.67 ℃ and 2.85 ℃ under SSP5-8.5. Research on carbon neutrality-oriented climate change projections needs to be strengthened for jointly achieving a net-zero future.
      PubDate: 2022-08-04
       
  • Extreme rainfall events in southeastern Africa during the summer

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      Abstract: Abstract The Pongola-Mtamvuna (PM) water management area in southeastern Africa is a highly biodiverse and sensitive region whose rainfall variability is not well understood. It is prone to drought and the occasional devastating flood events which are studied here for the early (October–December) and late summer rainy seasons (January–March) from 1984 to 2019 using CHIRPS daily rainfall data. Over 60% of the top 50 extreme rainfall events occurred during late summer (January–March) with tropical lows being by far the main contributor. The remainder are more or less equally distributed between mesoscale convective systems, tropical-extratropical cloud bands and cut-off lows, the latter contribute in October and November. There is considerable interannual variability in the numbers of these events during the record some of which is related to ENSO. Two prominent exceptions are the wet El Niño of OND 2006 and the dry La Niña of OND 2011, SST anomalies in the greater Agulhas Current region seem to have played an important role in both cases. Far fewer extreme events occurred from 2002 onwards than in the first two decades. However, 7 of the top 50 events occurred during the multi-year drought of 2007–2018 when almost all the late summers as well as many of the early summers experienced below average rainfall. The dry conditions during this period would have been much worse had 7 of the top 50 extreme events not occurred then, highlighting the importance of extreme rainfall event analysis for the region.
      PubDate: 2022-08-03
       
  • Correction to: The Arctic sea ice‑cloud radiative negative feedback in
           the Barents and Kara Sea region

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      PubDate: 2022-08-02
       
  • Characteristics of compound low-temperature and limited-light events in
           southern China and their effects on greenhouse grown strawberry

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      Abstract: Abstract The environmental stress, pests and diseases are frequently occurred during production of facility agriculture in China. Among them, adverse meteorological conditions, such as low temperature and limited light, often co-occurred in greenhouses and brought great losses in southern China. Nevertheless, there is little knowledge about agrometeorological disasters in facility, especially for co-occurred climate extremes. Here, we applied machine learning methods to simulate long-term daily minimum temperature in plastic greenhouses, so as to assess the spatio-temporal characteristics of compound low-temperature and limited-light events (LTLL) in southern China. We took strawberry as the representative horticulture plant to quantitatively investigate the potential effects of the LTLL stress based on experimental data. It was found that when the LTLL stress occurred, strawberry was more sensitive to low-temperature than limited-light and duration. The losses of the fruit soluble solids content caused by LTLL stress were relatively lower than that of yield. The LTLL events mainly occurred from November to March of the following year in southern China. The occurrence frequency had a decreasing trend during 1990–2019 at 3.4 d/10 a, which mainly resulted from its reduction in spring. Assuming that all the LTLL events occurred at strawberry flowering stage, ~ 11.71% of them could result strawberry fruit yield losses over 70%, and the most serious LL events mainly occurred in December and January. The northern part of southern China had a higher LTLL risk. The results have the potential to provide guidance for plastic greenhouse layout and strawberry production.
      PubDate: 2022-08-02
       
  • Bias correction, historical evaluations, and future projections of climate
           simulations in the Wei River Basin using CORDEX-EA

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      Abstract: Abstract The utilization of regional climate methods (RCMs) to predict future climate is an important study under the changing environment. The primary objective of the paper is to correct the temperature and precipitation simulations for the period of 1980–2005 and 2026–2098 in the Wei River Basin (WRB), to evaluate the performance of RCMs for the period of 1980–2005, and further, to analyze the future changes of projected temperature and precipitation during 2026–2098. In this paper, the linear scaling method was used to correct the temperature simulations. Quantile mapping, local intensity scaling method, and hybrid method were used to correct the precipitation simulations. The future changes of projected temperature and precipitation for the near term (2026–2050), mid-term (2051–2075), and far term (2076–2098), relative to the period of 1980–2005, were investigated under RCP 2.6 and RCP 8.5. Results indicate that (1) the temperature biases were either warm or cold in the spatial scale, and the precipitation wet biases were detected. After correction, HadGEM2-ES driven by RegCM4-4 had the best temperature reproducibility, and NCC-NorESM1-M driven by RegCM4-4 had the best precipitation reproducibility. (2) Under RCP 2.6, the projected annual, winter, and spring temperature showed decreasing trends. The temperature was higher than that for the period of 1980–2005 except for the spring temperature decreases in the Beiluo River Basin. Under RCP 8.5, the temperature showed significantly increasing trends. The temperature for the near term was similar to that of the period of 1980–2005, while the temperature increased significantly for the mid-term and far term. (3) Under RCP 2.6, the precipitation had decreasing trends. Under RCP 8.5, precipitation trends were also spatially distributed. The relative deviation of winter precipitation was the largest. Relative to the period of 1980–2005, the light- and moderate-rain days showed little change for the period of 2026–2098, while the extreme-rain days showed significantly increasing trends.
      PubDate: 2022-08-02
       
  • Mitigation of climate change impact using green wall and green roof
           strategies: comparison between two different climate regions in Iran

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      Abstract: Abstract An increase in energy demand and consumption is one of the significant challenges of the world community. Global climate change and temperature rise can significantly affect energy demand, especially in the building sector. Green passive design strategies (GPDS) such as green roof and green wall are considered a passive energy-saving technology which can deal with further climate change in near future. This paper compares the energy demand and CO2 emissions of a building with different structural scenarios during the current (2000–2019) and future climatic conditions (the 2050s) in two hot-dry (Kerman) and hot-humid (BandarAbbas) climate samples in Iran. The base case, green roof, and green wall modeling of the selected building have been developed by DesignBuilder software. Results revealed that 61% of the annual energy consumption of Kerman is related to the heating sector, while it will be changed to 47% under the effect of climate change and based on RCP2.6. However, 99% of the annual energy consumption of BandarAbbas belongs to cooling demand and it will not change by 2050s. Also, the maximum heating and cooling energy demand were calculated for the base building. Based on the results, green wall has more efficiency in optimizing total energy consumption compared to green roof in both climate types. On the other hand, GPDS are more efficient to optimize heating energy demand in comparison with cooling energy demand. Furthermore, the green wall strategy has better performance in reducing CO2 emissions as well. Accordingly, CO2 emissions reduce in Kerman by 2.73% and 2.93% by the implementation of the green wall during the observation period and 2050s, respectively. Meanwhile, this strategy can reduce CO2 emissions by only 1% per year in BandarAbbas during all studied periods.
      PubDate: 2022-08-02
       
  • Climatology of Arctic temperature inversions in current and future
           climates

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      Abstract: Abstract Temperature inversions are a common feature of the Arctic climate, affecting the surface energy budget and planetary boundary layer transports. This study investigates the evolution of large-scale temperature inversions (between 925 hPa and 2 m) in the context of a changing climate. To this end, two five-member regional climate model (RCM) ensembles, driven by the Canadian Earth System Model, spanning the 1950–2099 period, corresponding to two greenhouse gas emission scenarios (RCP 4.5 and 8.5), are considered. An ERA-Interim driven simulation for the 1979–2005 period is also considered to assess model performance. A comparison of observed atmospheric soundings with the boundary layer variations in the reanalysis-driven simulation indicates that the model captures the temperature inversion characteristics reasonably well, with some positive biases in the temperature inversion strength and frequency. The transient regional climate change simulations suggest substantial decreases in both temperature inversion strength and frequency in winter in future climate for both emission scenarios. These changes are consistent with the reduced sea ice cover and the associated increase in cloud cover that reduce the surface radiative cooling necessary for the formation of strong temperature inversions. Some increases in the frequency and strength of temperature inversions are projected for summer over the Arctic Ocean, possibly linked with increased poleward moisture transport.
      PubDate: 2022-07-26
       
  • Dependence of spring Eurasian surface air temperature anomalies on the
           amplitude and polarity of the North Atlantic tripole SST anomalies

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      Abstract: Abstract This study compares boreal spring surface air temperature (SAT) anomalies over mid- and high-latitude Eurasia in different categories of the North Atlantic tripole sea surface temperature (SST) anomalies for the period 1951–2018. It is found that Eurasian SAT anomalies depend largely upon the amplitude and polarity of the North Atlantic tripole SST anomalies (positive polarity for positive SST anomalies in the tropics and mid-latitude and negative SST anomalies in the subtropics). The main processes contributing to SAT anomalies vary with the region. In large amplitude positive tripole years, the SAT decreases in Europe and east of the Lake Baikal due to longwave radiation and sensible heat flux and increases in Siberia due to horizontal advection associated with anomalous northerlies. In large amplitude negative tripole years, the SAT increases in Europe and eastern Eurasia due to horizontal advection associated with anomalous southerlies. In small amplitude positive tripole years, the SAT increases in central Eurasia due to horizontal advection associated with mean and anomalous meridional winds. In small amplitude negative tripole years, the SAT decreases in southern central Eurasia, which is contributed by both longwave radiation and horizontal advection associated with anomalous northeasterlies. Atmospheric circulation influences SAT both directly through horizontal advection associated with anomalous winds and indirectly through shortwave radiation and in turn upward longwave radiation and sensible heat flux. The results reveal the necessity of distinguishing the amplitude and polarity of the North Atlantic SST anomalies in their impacts on climate variability.
      PubDate: 2022-07-23
       
  • What is above average air temperature!'

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      Abstract: Abstract In many media, especially in prime-time television shows, we often hear that the temperature is or will be higher than average or above average. It is seldom said which average it is, namely which period this comparison refers to. It is also rare to hear how much this above-average temperature is higher than one average. The question is what the climate average or climate normal is' The World Meteorological Organization (WMO) during the twentieth century defined a period of 30 years as the standard reference for calculating climate normal. The 30-year period, known as the climatological standard normal, serves as a benchmark against which current observations can be compared to the previous one. The last climatological standard normal period 1981–2010 is still in use while a new one is in preparation for a 30-year period that will cover the period from 1991 to 2020. It is expected that this change will be in use from the beginning of 2022. In this paper, based on the temperature change data obtained at the meteorological stations Split Marjan and Zagreb Grič, the differences in the conclusions about the last air temperature changes in the period of the last 10 years (2011–2020) are studied. The following four different 30-year climate normal periods are analysed: (1) 1961–1990; (2) 1971–2000; (3) 1981–2010; (4) 1991–2020. The analyses performed in this paper indicate the necessity of constant changing of the 30-year climate normal period used to estimate variations in recent air temperatures. Given the sudden rise in air temperature over the last 30 years, the period from 1991 to 2020 should be currently used for comparison and assessment of the most recent temperatures and other climatic parameters.
      PubDate: 2022-07-22
       
  • Land–sea thermal contrast associated with summer monsoon onset over the
           Chao Phraya River basin

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      Abstract: Abstract Earlier onset of the Southeast Asian summer monsoon (SAM) was observed over the Chao Phraya River basin in Thailand using Thai Meteorological Department-derived high-resolution merged rainfall data from 1981 to 2016. SAM variability depends on numerous local and global factors, including thermal conditions over the Bay of Bengal (BoB) and Tibetan Plateau (TbT). Despite tremendous past research efforts, the effect of thermal heat contrast on the SAM remains unclear. Using observational and reanalysis datasets, we found that the absolute value of total heat over the BoB was increasing. However, the interannual variability of total heat was greater over the TbT. Changes in surface temperature (± 1.5 °C), air thickness (± 20 m), and geopotential height over the TbT were associated with the timing of SAM onset. The results also suggested that significant changes in air thickness are driven by surface temperature differences over the TbT, while changes in the integrated apparent heat source and integrated apparent moisture sink of ± 100 W m−2 resulted in anomalous convective activities over the BoB and mainland of the Indochina Peninsula in years of early and late SAM onset. At the intraseasonal timescale, Madden–Julian oscillation (MJO) was observed over the Indian Ocean and Western Hemisphere for 4–10 days in years of early SAM onset. The opposite situation was found for years of late SAM onset, with MJO located over the Western Pacific Ocean and Maritime Continent.
      PubDate: 2022-07-21
       
  • Improved complete ensemble empirical mode decompositions with adaptive
           noise of global, hemispherical and tropical temperature anomalies,
           1850–2021

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      Abstract: Abstract ICEEMDAN, a variant of Empirical Mode Decomposition (EMD), is used to extract temperature cycles with periods from half a year to multiple decades from the HadCRUT5 global temperature anomaly data. The residual indicates an overall warming trend. The analysis is repeated for the Southern and Northern Hemispheres as well as the Tropics, defined as areas lying at or below 30 degrees of latitude. Multiannual cycles explain the apparently anomalous pause in global warming starting around 2000. The previously identified multidecadal cycle is found to be the most energetic and to account for recent global warming acceleration, beginning around 1993. This cycle’s amplitude is found to be more variable than by previous work. Moreover, this variability varies by latitude. Sea ice loss acceleration is proposed as an explanation for global warming acceleration.
      PubDate: 2022-07-19
       
  • Evaluation of events of extreme temperature change between neighboring
           days in CMIP6 models over China

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      Abstract: Abstract In the context of global warming, the frequency and intensity of extreme weather and climate events are increasing. However, the impact of these changes that is directly felt by people is the day-to-day temperature change. Extreme temperature changes between neighboring days (ETCNs) carry substantial disease risks and socioeconomic impacts. Evaluation studies of ETCN events with global climate models (GCMs) remain unknown in China. This study quantitatively evaluates the performances of 35 GCMs and the multi-model ensemble (MME) of the Coupled Model Intercomparison Project 6 (CMIP6) in simulating the extreme cooling (EC) and extreme warming (EW) events of two consecutive days as defined by relative thresholds. The results showed that from 1981 to 2013, the annual average EW frequencies showed an increasing trend over China, but a decreasing trend for EC events, and the frequency of EW events was higher than that of EC events. EW events mostly occurred in spring, while EC events occurred in autumn. Additionally, the performances of the CMIP6 models were quite different between EC and EW events. The models could capture the annual cycle of EC and EW events well, and the simulations of EW events were generally more reliable than those of EC events. Furthermore, most CMIP6 models overestimated the frequency of EW events but underestimated the frequency of EC events in China. The CMIP6 models could capture the trends in EC events in China but fail to simulate them in EW events. The interannual variability of EW events exhibited relatively better performance than that of EC events. The CMIP6 MME effectively improved the capabilities of the models to simulate the climatology of ETCN events. Individual CMIP6 models exhibited better performances than the CMIP6 MME in terms of the trend and interannual variability. Finally, according to the overall ranking of the CMIP6 models, MPI-ESM-1–2-HAM and FGOALS-f3-L achieved the best performance in simulating EW and EC events, respectively. This study selected the optimal models in different regions at the seasonal and annual scales, providing theoretical support for the frequency projection and modeling improvement of ETCN events.
      PubDate: 2022-07-19
       
  • A new approach to detecting patterns of ENSO teleconnections with
           temperature and rainfall patterns in the Western Kenya Highlands separates
           seasonal, auto-correlated, and random effects

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      Abstract: Abstract Distinctive annual weather patterns in the Western Kenya Highlands have been attributed to El Niño Southern Oscillation (ENSO) teleconnections. A novel application of a recently developed analytical approach is used to identify statistically significant differences between temperature and rainfall patterns in the Kakamega District during the El Niño and La Niña periods of the ENSO cycle. This approach separates the seasonal trend and 1-day autocorrelation from the statistical noise in an annual data set. The standard deviation of this noise is further analyzed for its own seasonal trend. Thirty-eight years of reanalysis data are analyzed, and statistical comparisons are made on all three aspects of this analysis. El Niño years were characterized by a phase shift in temperature patterns. Larger random variation was detected in El Niño years during the long rains than in La Niña years, leading to a higher probability of anomalously high rainfall. Larger random variation was detected in La Niña years during the short rains, leading to both a higher probability of anomalously high rainfall and a higher probability of no rainfall. The method appears to be a promising tool for analyzing not only the effects of distant teleconnections but also the nature of those effects.
      PubDate: 2022-07-19
       
  • A new approach in evaluation impacts of teleconnection indices on
           temperature and precipitation in Iran

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      Abstract: Abstract In many parts of the world, teleconnection patterns are one of the climate phenomena that significantly change the causative climate anomalies, especially temperature and precipitation. Thus, statistical analysis and modeling of their effects are of great importance in order to understand the fluctuations and climate variability in a region. In this study, 52 teleconnection indices were utilized to perform statistical analysis and conceptual modeling as well as simulation of temperature and precipitation fluctuations in Iran. For this purpose, temperature and precipitation data of 36 synoptic stations in Iran and 52 teleconnection indices for the period 1951–2019 were used. For the analysis, the relevant data were classified into four groups of global (GLB), regional (RGN), El Niño–Southern Oscillation (ENSO), and all indices (ALL). Then, the correlation of the aforementioned indices with temperature and precipitation was calculated using the teleconnectional–statistical model (TSM). Afterward, 5 years with the highest correlation coefficient was selected and considered as the forecasting parameters. The results revealed that the local temperature forecasting using RGN indices and the precipitation forecasting using GLB and ALL indices were more accurate than those using other indices. Our findings highlighted the prominent role of the indices with broader geographical regions that mainly were evolved across the oceans. Moreover, the effect of ENSO teleconnection on Iran climate was explained by the dynamic mechanism of the atmospheric bridge. Comparing TSM outputs and the Climate Forecast System Version 2 (CFSV2), TSM outperformed CFSV2 in the conducting experiment. Overall, the findings of this study emphasized on the existence of coincided synergy in the fluctuation or trend within almost all indices and atmospheric parameters, and most of the fluctuations in the indices occurred simultaneously or right after the ENSO events, including specific super El Niño in 1997–1998 (turning point). Also, the dramatic effect of sunspots on the average temperature of Iran is shown in inverse harmony, which is not easily revealed by correlation analysis. Also, the influence of global warming and especially synchronization with El Niño event on climatic change was briefly discussed in the Middle East. In this work, for the first time in the Middle East, physical mechanisms of how linkages affect Iran’s climate and rainfall were proposed in a synoptic conceptual model.
      PubDate: 2022-07-18
       
  • The Arctic sea ice-cloud radiative negative feedback in the Barents and
           Kara Sea region

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      Abstract: Abstract Shortwave cloud radiative effect (SWCRE), known as the cooling effect triggered by cloud, plays a vital role in adjusting the global radiation budget. As the Arctic gets warmer, it may become a more indispensable factor curbing this warming tendency. Research has pointed out a significant relationship between sea ice cover (SIC) and SWCRE over the Arctic during summer (June–August). Although no evidence has been found on cloud response to SIC during summer on the average of the Arctic, this study regards cloud as an inter-connection which can regulate SIC and SWCRE in a particular place: Barents and Kara Sea region (15°E–85°E, 70°N–80°N). Its SWCRE and SIC vary significantly, with their trends being 5.85 w∙m−2 and − 5.87% per decade compared to those of the Arctic mean (2.93 w∙m−2 and − 4.65% per decade). In this area, we find that the growing number of low-level cloud which is resulted from the loss on SIC may be accountable for the increase in SWCRE, as is shown in the correlation coefficient between low-level cloud and SIC reaches − 0.4. The correlation coefficient between low-level cloud and SWCRE is 0.6. It reflects a SIC-cloud-SWCRE negative feedback. Moreover, a regression fitting model is being established to quantify the contribution of Arctic cloud in the process of slowing down the Arctic warming. It reveals that this specific region would turn into an ice-free region with sea surface temperature (SST) 1.5 °C higher than reality during 2001 if we stop the increase in SWCRE. This result presents how fascinating the contribution cloud has been making in its way slowing down the warming pace.
      PubDate: 2022-07-16
       
  • Characteristics and source analysis of greenhouse gas concentration
           changes at Akedala Station in Central Asia

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      Abstract: Abstract Mole fractions of atmospheric carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and sulfur hexafluoride (SF6) have been continuously measured since September 2009 at the Akedala Station (47°06′N, 87°58′E, 563.3 masl) in China. The station is located in the Central Asia and northwest of China, and it is the only station in that region with background conditions for long-term greenhouse gas observations. Characteristics of the mole fractions, growth rates, and influence of long-distance transport were studied considering data from September 2009 to December 2019. The greenhouse gases concentrations at Akedala Station show a trend of year-on-year growth, with CO2 concentrations ranging from 389.80 × 10−6 to 408.79 × 10−6 (molar fraction of substances, same below), CH4 concentrations ranging from 1890.07 × 10−9 to 1976.32 × 10−9, N2O concentrations ranging from 321.26 × 10−9 to 332.03 × 10−9, and SF6 concentrations ranging from 7.04 × 10−12 to 10.07 × 10−12, the growth rate of which is similar to the decadal average growth rate in the Northern Hemisphere. There exist obvious seasonal variations, with CO2 concentrations showing high in winter and low in summer and CH4 showing a distinct “W”-shaped trend while N2O and SF6 showing little difference between the four seasons. A relatively strong correlation and homology exist among the four greenhouse gases except in summer, and the analysis based on backward trajectories model shows that the Akedala Station is influenced by the airflow from northwest or southwest throughout the year. The Akedala Station is an important atmospheric background station in Central Asia, and its greenhouse gas concentration levels and variation characteristics are significantly different from those of the background stations in the monsoon region. Its degree changes are closely related to local source emissions, monsoon transport, and atmospheric photochemical processes.
      PubDate: 2022-07-16
       
  • Assessment of climate variations in the growing period in Central Europe
           since the end of eighteenth century

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      Abstract: Abstract The paper analyses time series of thermal growing season (GS) start (GSS) and end dates (GSE) and length (GSL) in three cities representing urbanised areas of Central Europe (Kraków, Prague, Vienna) in the period 1792–2020. The classification of dates of growing season start and end, as well as length of the designated growing seasons, was conducted from climate data. An attempt was made to identify the dominant patterns of GS course, considering its start date, length, and end date collectively. In the period 1972–2020 in Central Europe, the growing season was prolonged, although the changes in particular stations selected for analysis occurred unevenly and simultaneously resulted from different causes. Three subperiods can be designated, differing in the intensity of changes in the start and end dates, as well as growing season length. The intensification of the rate of the occurring changes was recorded in all stations at the end of the twentieth and in the twenty-first century. There is a trend of decreasing frequency of short and abnormally short periods and more and more frequent occurrence of long and abnormally long seasons in the analysed multiannual period. Regardless of the differences between the stations in the designated GS types, the shortest of them were observed simultaneously at all three analysed stations in the period 1830–1860 and at the beginning of the twentieth century. The opposite type, representing the longest GS, is most abundant since the 1990s in Central Europe.
      PubDate: 2022-07-15
       
  • A convolution neural network approach to Doppler spectra classification of
           205 MHz radar

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      Abstract: Abstract Wind profiler radars are capable of measuring three-dimensional wind profiles at various altitudes of the atmosphere, at very high temporal and spatial resolution. The Advanced Centre for Atmospheric Radar Research (ACARR), located at Cochin University of Science and Technology (CUSAT), operates the world’s first 205 MHz stratosphere-troposphere wind profiler radar which provides three-dimensional wind profiles for an altitude range of 315 m to 20 km. During non-rainy condition, the radar Doppler power spectrum bears the signature of ambient air motion whereas during rainy conditions, it contains signatures of both ambient air motion and fall velocity of rain droplets. The classification of Doppler power spectra for rainy (Precipitation) and non-rainy (Clear) conditions is necessary as wind profile retrieval from the former needs careful separation of ambient air motion from fall velocity of droplets. A manual classification of the power spectrum is cumbersome, time-consuming, and therefore not practical due to the vast database. This work intends to automate Doppler power spectra classification using the deep learning Convolutional Neural Network (CNN). The proposed Convolutional Neural Network model gives a k-fold validation accuracy of 99.77% and testing accuracy of 99.60% for power spectra classification. The performance of CNN is compared against other popular machine learning classifiers such as Support Vector Machine, Decision Tree, K Nearest Neighbour and Naive Bayes. The performance comparison results show that the proposed CNN outperforms other models in radar Doppler power spectra classification.
      PubDate: 2022-07-15
       
  • Trends and abrupt changes in extreme rainfall events and their influence
           on design quantiles: a case study in São Paulo, Brazil

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      Abstract: Abstract The traditional approach to characterize extreme rainfall events is based on using past observed data to fit a probability distribution, which is used to associate a certain probability of occurrence to a rainfall magnitude, under a stationary assumption. Observed series, however, may exhibit trends and abrupt changes, resulting from the natural hydro climatic variability and the climate change context, which are not usually considered in the stationary modelling procedure and which may affect the characterization of extreme events. In this paper, it was evaluated the presence of these temporal changes in rainfall series and their impact to estimate design quantiles, using rainfall data of 317 stations, located in São Paulo State, Brazil. The results showed that extreme rainfall events are changing in the state. Low-return period events (up to 10 years) are intensifying. Moderate- and high-return period events, on the other hand, did not present a clear spatial pattern. Trends and abrupt changes may significantly influence the estimation of design quantiles. The presence of the former in rainfall series exhibited more influence on low-return period events, showing, however, no clear relationship with high-return period design quantiles. The presence of the latter seems to influence the characterization process, affecting estimated quantiles of all evaluated return periods. Such findings highlight the need to consider the presence of trends and abrupt changes and their influence on design quantiles for a more reliable characterization.
      PubDate: 2022-07-13
       
 
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