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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted alphabetically
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Advances in Climate Change Research     Open Access   (Followers: 53)
Advances in Meteorology     Open Access   (Followers: 27)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 11)
Aeolian Research     Hybrid Journal   (Followers: 7)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
American Journal of Climate Change     Open Access   (Followers: 37)
Atmósfera     Open Access   (Followers: 2)
Atmosphere     Open Access   (Followers: 33)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Science Letters     Open Access   (Followers: 40)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Carbon Balance and Management     Open Access   (Followers: 6)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate     Open Access   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 6)
Climate Change Economics     Hybrid Journal   (Followers: 45)
Climate Change Responses     Open Access   (Followers: 23)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Climate Law     Hybrid Journal   (Followers: 6)
Climate of the Past (CP)     Open Access   (Followers: 6)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Research     Hybrid Journal   (Followers: 9)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Climate Risk Management     Open Access   (Followers: 10)
Climate Services     Open Access   (Followers: 4)
Climatic Change     Open Access   (Followers: 69)
Current Climate Change Reports     Hybrid Journal   (Followers: 18)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 15)
Energy & Environment     Hybrid Journal   (Followers: 25)
Environmental and Climate Technologies     Open Access   (Followers: 3)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 21)
Frontiers in Climate     Open Access   (Followers: 4)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 20)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 30)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
International Journal of Environment and Climate Change     Open Access   (Followers: 22)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 136)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Journal of Climate     Hybrid Journal   (Followers: 56)
Journal of Climate Change and Health     Open Access   (Followers: 5)
Journal of Climatology     Open Access   (Followers: 4)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 21)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Open Access   (Followers: 4)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 29)
Mètode Science Studies Journal : Annual Review     Open Access  
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Nature Climate Change     Full-text available via subscription   (Followers: 147)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Nīvār     Open Access   (Followers: 1)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Space Weather     Full-text available via subscription   (Followers: 27)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Tellus A     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 20)
The Cryosphere (TC)     Open Access   (Followers: 8)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Urban Climate     Hybrid Journal   (Followers: 5)
Weather     Hybrid Journal   (Followers: 20)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Weather and Climate Extremes     Open Access   (Followers: 18)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Weatherwise     Hybrid Journal   (Followers: 18)
气候与环境研究     Full-text available via subscription   (Followers: 2)

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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]
  • Performance evaluation and comparison of observed and reanalysis gridded
           precipitation datasets over Pakistan

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      Abstract: Abstract The present study evaluates five observed gridded precipitation datasets [Global Precipitation Climatology Centre (GPCC), Climate Prediction Centre (CPC), Climatic Research Unit (CRU), Cressman Interpolated High-resolution Gauge-based Gridded Observations (CIHGGO), and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI)] and five reanalysis products [ERA-Interim and ERA5 of European Centre for Medium-Range Weather Forecasts, Twentieth Century Reanalysis (20CR), Japanese 55-year Reanalysis (JRA55), and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2)] against surface precipitation gauge data as reference for the period 1981–2015 over Pakistan. The performance of the above gridded datasets is assessed using six statistical metrics: correlation coefficient, relative bias, root mean square error, mean absolute error, wet/dry years, and precipitation centroid on monthly, seasonal [summer (June–September), and winter (December–March)], and annual timescales. Our results show that GPCC has overall much better performance across an entire country (avg. correlation > 0.95) in terms of all timescales and statistical metrics used. EWEMBI1 displays comparable results to GPCC with higher correlation and lower error values and thus can be ranked as the second-best performing observed gridded precipitation dataset. On the other hand, reanalysis products are found relatively weak in approximating the spatiotemporal distribution of precipitation, especially over complex northern areas of Pakistan. However, ERA5 exhibits a comparatively good positive linear relationship with surface precipitation gauge data at monthly (0.92), seasonal [0.89 (summer) to 0.98 (winter)], and annual (0.87) timescales, which may be attributed to an advanced data assimilation technique and model dynamics employed in the generation of the data.
      PubDate: 2022-05-28
       
  • Encounter risk prediction of rich-poor precipitation using a combined
           copula

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      Abstract: Abstract Encounter risk precipitation of rich-poor precipitation is beneficial for the utilization of flood resources and rational allocation of water resources which often involves a challenging task—estimating the joint probability distribution function (PDF) of multiple hydrologic variables using copulas. This paper introduced a linear combination of three copulas (combined copula) to study probabilistic characteristics of precipitation in two watersheds. To validate the performance of the combined copula, four experiments were employed to identify the joint distribution for the summer monthly precipitation and annual precipitation at two pairs of neighboring stations in Jinghe River, China, which were then compared with three individual copulas, namely, Gumbel copula, Clayton copula, and Frank copula. All the experiments showed that the combined copula performed much better than any of the three individual copulas. The combined copula was further applied to predict the synchronous-asynchronous probabilities of the summer monthly precipitation and annual precipitation at those four stations in Jinghe River. The rich-normal-poor synchronous encounter probabilities of the summer monthly precipitation reach up to 0.7 and 0.63 for Guyuan-Pingliang stations and Huanxian-Xifeng stations, respectively. The rich-normal-poor synchronous encounter probabilities of the annual precipitation reach up to 0.6 and 0.59 for the Guyuan-Pingliang stations and the Huanxian-Xifeng stations, respectively. Moreover, the encounter probability of rich-poor precipitation between receiving areas of Haihe River and upper reaches of Han River was calculated by the combined copula, and the probability that is suitable to transfer water is about 0.35.
      PubDate: 2022-05-27
       
  • Trend assessment of global, UVB, UVA irradiation, and dry bulb temperature
           at the lowest terrestrial site on earth: Dead Sea, Israel

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      Abstract: Abstract The Dead Sea basin is the lowest terrestrial site on the globe. A meteorological station monitoring the global, UVB and UVA irradiation, and the dry bulb temperature was established in 1995 in conjunction with a study of bio-climatological properties of the region with regard to photoclimatherapy treatment of dermatological diseases. The availability of such irradiation and dry bulb temperature databases has been utilized to perform a study to determine if any trends regarding either irradiation or dry bulb temperature exists at this unique site. The global irradiation database included the time interval 1995–2021, whereas the corresponding time interval for the UVB and UVA irradiation databases was 1995–2018. There was no indication of any trends, based upon a p value analysis with regard to the global and UVB and UVA irradiation with the exception of global irradiation during September (− 120.7 Wh/m2/decade; ~ 2%/decade) and UVA irradiation during March (+ 11.1 Wh/m2/decade; ~ 4%/decade) and September (− 9.1 Wh/m2/decade; ~ 0.6%/decade). The dry bulb temperature database consisted of the time interval 1995–2021 and trends were observed during the months of August, September, and October. The dry bulb temperature data were analyzed as a function of time (Israel Standard Time) interval; viz., diurnal from 06:00 to 18:00, nocturnal from 18:00 to 06:00, and daily from 00:00 to 24:00. The trends observed during these three months varied between 0.38 and 0.70 °C/decade.
      PubDate: 2022-05-27
       
  • Long-term soil temperature dynamics of the Kunlun Pass permafrost region
           on the Qinghai-Tibetan Plateau

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      Abstract: Abstract The thermal dynamics was important for permafrost change processes under climate change. However, little studies were focused on the soil thermal dynamics with long-term observed data in the permafrost region on the Qinghai-Tibetan Plateau (QTP). From 2005 to 2017, we have monitored thermal dynamic of active layer overlying permafrost in the Kunlun Pass (CN06 site) region of the QTP. Results demonstrated that the number of thaw days is lower than the number of freeze days, and the start dates of thawing and freezing were delayed over this period. Moreover, air and soil temperature were all fastest warming in summer at different depths, then in autumn, except in spring and winter which has a cooling trend at some depths. Accordingly, the mean annual soil temperatures exhibited an evident warming trend at different depths. In addition, thawing degree-days (TDD) for air and soil temperature (at 10 cm) showed an increasing trend, whereas the respective freezing degree-days (FDD) had a decreasing trend. The mean freezing and thawing n factor were 1.43 and 0.50 from 2005 to 2017, and the surface offset of the study site ranged from 2.65 to 3.42 °C, which was lower than those in the subarctic and Arctic regions. Meanwhile, there was a linear relationship between the TDDs and active layer thickness, and a power function relationship between the TDDa and active layer thickness. The active layer thickness exhibited a significant increase with the rate of 2.4 cm/year from 2005 to 2017. These results can be used to understand the thermal dynamics response to climate change and indicate related changes and differences in permafrost in different permafrost regions.
      PubDate: 2022-05-27
       
  • Projection of droughts in Amu river basin for shared socioeconomic
           pathways CMIP6

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      Abstract: Abstract Droughts significantly affect socioeconomic and the environment primarily by decreasing the water availability of a region. This study assessed the changes in drought characteristics in Central Asia’s transboundary Amu river basin for four shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The precipitation, maximum, and minimum temperature (Pr, Tmx, and Tmn) simulations of 19 global climate models (GCMs) of the coupled model intercomparison project phase 6 (CMIP6) were used to select the best models to prepare the multimodel ensemble (MME) mean. The standard precipitation evapotranspiration index (SPEI) was used to estimate droughts for multiple timescales from Pr and potential evapotranspiration (PET) derived from Tmx and Tmn. The changes in the frequency and spatial distribution of droughts for different severities and timescales were evaluated for the two future periods, 2020–2059 and 2060–2099, compared to the base period of 1975–2014. The study revealed four GCMs, AWI-CM-1–1-MR, CMCC-ESM2, INM-CM4-8, and MPI-ESM1-2-LR, as the most suitable for projections of droughts in the study area. Results revealed a decrease in Pr by 3 to 12% in the near future and by 3 to 9% in the far future in most parts of the basin for different SSPs. However, there is almost no change in PET in the near future while increasing by 10 to 70% in the far future. The changes in Pr and PET would cause a noticeably decrease in drought occurrence in the near future, particularly for moderate droughts by − 50% for SSP5-8.5 and an increase in the far future up to 30% for SSP3-7.0. The increase in all severities of droughts was projected mostly in the center and northwest of the basin. Overall, the results showed a drought shift from the east to the northwest of the basin in the future.
      PubDate: 2022-05-25
       
  • Sensitivity of physical schemes on simulation of severe cyclones over Bay
           of Bengal using WRF-ARW model

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      Abstract: Abstract Gauging appropriate physical parameterization schemes for any numerical weather prediction model is indispensable for obtaining high accuracy in tropical cyclone forecasting. In this study, combinations of five microphysics, three cumulus convection, and two planetary boundary layer (PBL) schemes are investigated with respect to track, intensity, and time of landfall to determine an optimal combination of physical schemes of the weather research and forecasting (WRF) model (version 4.0) with advanced research WRF (ARW) core. All sensitivity experiments are carried out by taking the initial and boundary conditionsfrom the National Centers for Environmental Prediction Global Forecast System (NCEP-GFS). The simulated track, intensity, and landfall time are compared with the Indian Meteorological Department (IMD) observations. The sensitivity experiments reveal that the KF cumulus is performing better with YSU PBL along with WSM6, Ferrier (new eta), and Thompson microphysics for the track (position and time), and intensity with the least errors. Furthermore, we examined the performance of the model with the above combination of schemes on four severe landfalling cyclones (Bulbul, Hudhud, Aila, and Sidr). The root mean square error (RMSE) for central pressure gives the least value in the range of 0.4 to 8 hPa and 0.2 to 3.7 ms−1 for maximum surface wind (MSW) during landfall with YSU-KF- Ferrier combination. The equivalent potential temperature shows strong vertical mixing up to 500 hPa in the case of YSU-KF-Ferrier, which enhances the formation of warm-core, which further explains the intensity of cyclones. Overall, the track, intensity, and rainfall forecasts for the extreme cyclones considered in this study are consistent with IMD observations using YSU PBL, KF cumulus convection, and Ferrier microphysics.
      PubDate: 2022-05-25
       
  • A quality control procedure for long-term series of daily precipitation
           data in a semiarid environment

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      Abstract: The availability of quality precipitation records in the current climate situation is of great importance in the scientific-technical field but also for the public institutions that manage the meteorological networks. This work has implemented a comprehensive spatial quality control procedure in the semiarid region of Andalusia (Southern Spain), using precipitation time series from 1947 stations from three meteorological networks: Spanish Meteorological Agency (AEMET), Agroclimatic Information Network of Andalusia (RIA), and Phytosanitary Information Alert Network (RAIF). The method consists of three consecutive steps: basic, absolute, and relative quality control processes. The latter step compares data from neighboring stations taking into account their proximity, height difference, and correlation, leading to a complete evaluation of each daily value. Finally, the quality of each year at each station can be declared as acceptable, good, or excellent. The automatic weather station networks RIA and RAIF gave absolute quality index \(Q\) above 85% for almost 87% of their stations, while only 57% of AEMET network reached this percentage. However, one of the longest AEMET datasets, San Fernando-Cádiz, obtained, except for 1 year, \(Q\) values over 90% in all available years for more than a century of measurements, since 1870 until 2000. From a total of more than 15 million daily records, almost 82% was flagged as correct. Despite the limitations of Andalusia region (low density of stations and its structural water deficit), the complete quality control procedure has been satisfactorily applied. Finally, related to the number of outliers, no temporal trend was found across the region. Graphical abstract
      PubDate: 2022-05-25
       
  • Monitoring urban carbon emissions from energy consumption over China with
           DMSP/OLS nighttime light observations

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      Abstract: Abstract This paper constructs a model to accurately estimate the urban CO2 emissions in 2000, 2005, and 2013 in China, using the combined data of DMSP/OLS nighttime light data and the provincial energy statistical yearbook data. We calculate and analyze the growth of urban built-up areas and carbon emissions in different time periods both all over the country and the four economic zones in China. It was shown a good fitting relationship between urban growth and carbon emissions, with the R2 at 0.6188 in 2000, 0.7132 in 2005, and 0.7195 in 2013. The growth rate of developed land area was 13.4% from 2000 to 2005 and 15.9% from 2005 to 2013. During the same period, CO2 emissions had been increasing as well, at an average annual growth rate of 12.2% from 2000 to 2005 and 6.5% from 2005 to 2013. From a spatial point of view, carbon emissions are far greater in the eastern region of China than in western China. The carbon emissions are the highest in major metropolitan cities such as Beijing, Shanghai, and Guangzhou. Per capita carbon emissions are also higher in eastern China, which is consistent with the people’s higher living standards. In some cities with large energy and heavy industry concentrations, especially in the northeastern and western regions, the growth rate of carbon emissions has risen faster than in other cities.
      PubDate: 2022-05-25
       
  • Distribution of hazard and risk caused by agricultural drought and flood
           and their correlations in summer monsoon–affected areas of China

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      Abstract: Abstract The summer monsoon–affected area is a suitable area for agricultural production in China. Against the background of climate warming, the activity of the summer monsoon is changing significantly. The drought and flood disasters in this region are becoming more and more frequent and have a greater and more serious impact on agricultural production. Therefore, based on observational data from meteorological stations and yield loss data in agriculture caused by drought and flood disasters in summer monsoon–affected areas, this paper studied the characteristics of the hazard of disaster-causing factors, the risk of losses to agriculture caused by droughts and floods, and their correlation. Moreover, it compared and analyzed the variability of drought and flood hazard and risk to agriculture before and after a temperature rise. The results showed that the precipitation in summer monsoon–affected areas is obviously affected by monsoon activities, and there is an overall though non-significant positive correlation between annual average standardized precipitation evapotranspiration index (SPEI) and the summer monsoon activity index (MI). The drought disaster comprehensive loss rate (DCLR) was generally higher than the flood disaster comprehensive loss rate (FCLR). This shows that the impact of drought on agriculture production is significantly greater than that of floods in this area. The high hazard and risk areas for drought were mainly distributed along the edge of the summer monsoon area and in its vicinity, whereas the high hazard and risk areas for flooding were mainly distributed in the lower reach of the Yangtze, Songhua, and Liaohe Rivers. Among them, Liaoning, Jilin and Heilongjiang are high-risk superposition areas of drought and flood disasters. The hazards of drought and flood dominate the risk of disaster loss. Climate warming has significantly expanded the high-hazard and high-risk ranges in China for drought and flood disasters and has also changed their spatial distribution patterns. The high-hazard area for drought has shifted to the monsoon edge area, the high-risk area for drought has moved northward, and both the high-hazard and the high-risk areas for floods have clearly moved southward. The impact of climate warming on drought was more significant than on floods. This study provides important scientific guidance for formulating drought and flood disaster prevention planning and agricultural production development patterns in China.
      PubDate: 2022-05-24
       
  • Ground validation of GPM Day-1 IMERG and TMPA Version-7 products over
           different rainfall regimes in India

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      Abstract: Abstract This study presents a comprehensive evaluation of multi-satellite precipitation estimates against ground rain gauge data over three different climatic regions of India. In this study, performance evaluation of Integrated Multi-satellitE Retrievals for GPM (IMERG) a next-generation rainfall mission for observing global precipitation characteristics has been carried out. The IMERG was also inter-compared with the TRMM Multi-satellite Precipitation Analysis (TMPA) product for using contingency table and statistical methods. The dependences of the two satellite rainfall products were examined, with special focus on the reliance of product performance at different rainfall intensities over three different rainfall regime area of India (Upper Mahanadi Basin, districts of Himachal Pradesh (NW Himalaya) and regions of Rajasthan (Thar Desert)). The analysis was carried out on daily and monthly scales. Results indicated that both the satellite precipitation products (SPPs) IMERG and TMPA precipitation products overestimate the daily precipitation. Both the SPPs show good correlation at daily and monthly precipitation estimations, and the performance of SPPs is better in Thar desert area, but poor in the mountainous region. The results also revealed that IMERG precipitation shows better detection capability of daily rainfall compared to TMPA precipitation estimates for most of the rainfall events. In general, IMERG and TMPA overestimated rainfall depths for all rainfall events. This study suggests that there is a need for emendation in precipitation estimation algorithm and validation against rain gauge precipitation to capture the rain events more accurately in the study area.
      PubDate: 2022-05-24
       
  • Hybrid deep learning approach for multi-step-ahead prediction for daily
           maximum temperature and heatwaves

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      Abstract: Abstract Availability of increasing information and digital meteorological data leads to an opportunity for better simulations/prediction of complex hydroclimatic phenomena. However, volume and size of such data and underlying complex association pose many challenges to traditional approaches. This study focuses on the potential of a hybrid deep learning (DL) approach, a combination of one-dimensional convolutional neural network (Conv1D) and long short-term memory (LSTM) neural network (hereinafter hybrid Conv1D-LSTM), for multi-step-ahead (1-day to 10-day) daily maximum temperature prediction. The proposed approach is applied to twenty-eight major cities in India, located in different climate regimes, to explore its potential to predict the daily maximum temperature and to foresee the heatwave events. Seven meteorological precursors, closely associated with daily temperature variation along with the month index are used as input and the proposed approach is expected to efficiently learn the complex relationship between the precursors and daily maximum temperature. Apart from its alluring performance in predicting the daily maximum temperature, the results also show some promise to raise an alert for the upcoming heatwaves. The performance of the proposed hybrid model is also compared with other machine learning (ML), DL-based approaches, and three popular weather applications (weather apps) that help to portray the superiority of the proposed hybrid DL–based approach.
      PubDate: 2022-05-24
       
  • Changes in extreme precipitation in the Wei River Basin of China during
           1957–2019 and potential driving factors

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      Abstract: Abstract Extreme precipitation poses a severe threat to the natural ecosystem, socioeconomic development, and human life. Investigating the spatiotemporal variations in extreme precipitation and exploring the potential drivers have implications for disaster risk reduction and water resource management. In this study, we analyzed the changes in nine extreme precipitation indices (EPIs) over the Wei River Basin (WRB) during 1957–2019. Furthermore, we assessed the effect of geographic factors (latitude, longitude, and altitude) on the spatial distribution of EPIs and the potential impact of ocean–atmosphere circulation on the temporal variability of EPIs. The results indicate that six EPIs present a downward trend and three EPIs show an upward trend, but all the trends are not significant. In the seasonal scale, max 1-day precipitation amount (RX1day) increases significantly in summer (P < 0.05), while the trends in max 5-day precipitation amount (RX5day) are not significant in all seasons. The period of about 8 years and less than 3 years were observed in most EPIs. The mean values of EPIs except consecutive dry days (CDD) gradually increase from northwest to southeast of the WRB. Latitude, longitude, and altitude are important factors affecting the spatial distribution of the extreme precipitation. Southern Oscillation Index (SOI) and Atlantic Multidecadal Oscillation (AMO) contribute the most to EPIs variation. Interdecadal and interannual oscillations occur between most EPIs and ocean-atmospheric circulation factors, but their phase relationships are different. Our findings highlight the importance of examining global and local driving factors of trend in regional extreme precipitation by a systematic approach, and help to further understand the precipitation changes in the WRB.
      PubDate: 2022-05-23
       
  • Climate change scenarios and the dragon fruit climatic zoning in Brazil

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      Abstract: Abstract The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth’s land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted.
      PubDate: 2022-05-21
       
  • Comparisons of statistical downscaling methods for air temperature over
           the Qilian Mountains

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      Abstract: Abstract Air temperature is an important indicator of climate change, as well as for understanding changes in hydrology, ecology, and other natural systems. However, meteorological stations that provide reliable temperature observations are usually sparse in areas of complex terrain, thus limiting our ability to quantify high spatial resolution temperature variability in these regions. Here, we apply three statistical downscaling methods to daily air temperature output from the sixth Coupled Model Intercomparison Project (CMIP6), validated with 22 meteorological stations over the Qilian Mountains. Based on different downscaling methods, we find RMSE and MAE are reduced as much as 59–66%, with the ratio of RMSE and MAE to the annual average temperature of stations decreasing from 147.9 to 61.0% and 143.3 to 64.7%, respectively, depending on the method. Compared to the original data, annual temperature based on the best downscaling methods differed by −2.85±3.61°C during the historical 1850–2014 period and, for the 2015–2100 projections, by 2.13±3.30°C for SSP1-2.6, −2.13±3.29°C for SSP2-4.5, −2.11±3.24°C for SSP3-7.0, and −2.12±3.23°C for SSP5-8.5. The downscaled annual air temperatures show a warming trend ranging 0.15–0.22°C/10 years for the historical experiment, 0.08–0.14°C/10 years for SSP1-2.6, 0.24–0.35°C/10 years for SSP2-4.5, 0.43–0.63°C/10 years for SSP3-7.0, and 0.52–0.76°C/10 years for SSP5-8.5 in the Qilian Mountains. These results indicate that the accuracy of the downscaled temperatures is improved compared to the original data. However, we also find that, compared with the downscaled data, the original projections have been overestimated.
      PubDate: 2022-05-20
       
  • Robust bias-correction of precipitation extremes using a novel hybrid
           empirical quantile-mapping method

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      Abstract: Abstract High-resolution, daily precipitation climate products that realistically represent extremes are critical for evaluating local-scale climate impacts. A popular bias-correction method, empirical quantile mapping (EQM), can generally correct distributional discrepancies between simulated climate variables and observed data but can be highly sensitive to the choice of calibration period and is prone to overfitting. In this study, we propose a hybrid bias-correction method for precipitation, EQM-LIN, which combines the efficacy of EQM for correcting lower quantiles, with a robust linear correction for upper quantiles. We apply both EQM and EQM-LIN to historical daily precipitation data simulated by a regional climate model over a region in the northeastern USA. We validate our results using a five-fold cross-validation and quantify performance of EQM and EQM-LIN using skill score metrics and several climatological indices. As part of a high-resolution downscaling and bias-correction workflow, EQM-LIN significantly outperforms EQM in reducing mean, and especially extreme, daily distributional biases present in raw model output. EQM-LIN performed as good or better than EQM in terms of bias-correcting standard climatological indices (e.g., total annual rainfall, frequency of wet days, total annual extreme rainfall). In addition, our study shows that EQM-LIN is particularly resistant to overfitting at extreme tails and is much less sensitive to calibration data, both of which can reduce the uncertainty of bias-correction at extremes.
      PubDate: 2022-05-19
       
  • Spatiotemporal analysis of drought and rainfall in Pakistan via
           Standardized Precipitation Index: homogeneous regions, trend, wavelet, and
           influence of El Niño-southern oscillation

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      Abstract: Abstract The phenomenon of drought is common in the world, especially in Pakistan. El Niño-Southern Oscillation (ENSO) influences the spatial and temporal variability of drought and rainfall in Pakistan. Therefore, the objectives of this study are to identify homogeneous rainfall regions and their trend regions, as well as the impact of ENSO phases. In this study, monthly rainfall data from 44 weather stations are used during 1980–2019. Moreover, descriptive and exploratory statistics tests (e.g., Pettitt and Mann-Kendall—MK), Sen method, and cluster analysis (CA) are evaluated along with the annual Standardized Precipitation Index (SPI) on spatiotemporal scales. ENSO occurrences were classified based on the Oceanic Nino Index (ONI) for region 3.4. Using the cophenetic correlation coefficient (CCC) and a significance level of 5%, seven methods were applied to the rainfall series, with the complete method (CCC > 0.9082) being the best. According to the CA method, Pakistan has four groups of homogeneous rainfall (G1, G2, G3, and G4). Descriptive and exploratory statistics showed that G1 differs from the other groups in size and spatial distribution. Pettitt’s technique identified the most extreme El Niño years in terms of spatial and temporal drought variability, along with the wettest months (March, August, September, June, and December) in Pakistan. Non-significant increases in Pakistan’s annual precipitation were identified via the MK test, with exceptions in the southern and northern regions, respectively. No significant increase in rainfall in Pakistan was found using the Sen method, especially in regions G2, G3, and G4. The severity of the drought in Pakistan is intensified by El Niño events, which demand attention from public managers in the management of water resources, agriculture, and the country’s economy.
      PubDate: 2022-05-18
       
  • Climate change vulnerability in Bangladesh based on trend analysis of some
           extreme temperature indices

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      Abstract: Abstract Extreme temperature is the key indicator of extreme climatic events. The goal of this research was to better understand the long-term trends and shifting behaviors associated with Bangladesh’s record-breaking high temperatures in the country’s atmosphere. Data from 26 Bangladeshi meteorological stations collected between 1981 and 2018 was analyzed with RClimDex. The annual count of warm (cold) spell duration increased, according to the findings (decrease). In the coastal regions, this rising temperature trend is more pronounced. There were longer (shorter) periods of warm (cold) weather in the twentieth century than there were in the previous decade. As a result, the length of warm (cold) spells has become longer since the beginning of the twenty-first century, as compared to the last quarter of the twentieth century. There is little fluctuation in diurnal temperatures, but they are getting smaller and smaller. There is a 13% decrease in the Cold Spell Duration Indicator (CSDI), which indicates that we are in for a long, cold winter. At a rate of 14% per year, the Warm Spell Duration Indicator (WSDI) annual count suggests an extremely hot summer is imminent. Diurnal temperature range (DTR) values decreased by 1.1% year-round, raising the specter of climate extremes like the CSDI and WSD. An increasing (decreasing) trend in indicators of how long hot (cold) weather lasts indicates an increase (decrease) in Bangladesh’s warm atmosphere. As a result, an increase in the number of extreme weather events, particularly along the coasts, should be expected across the country.
      PubDate: 2022-05-17
       
  • Uncertainties in assessing climate change impacts and adaptation options
           with wheat crop models

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      Abstract: Abstract Mechanistic and process-oriented crop models are important tools to quantify the potential impacts of climate change on crop production and yields and to evaluate the efficacy of management strategies, policies, or actions developed by the stakeholders. This review focusses on the epistemic uncertainty associated with the use of crop models. It firstly identifies the main sources of uncertainties from the perspectives of crop model inputs, methods for estimating crop parameters, crop model structure/complexity/process scale, and the underpinning experimental datasets. Pathways for managing those uncertainties are identified and future research directions are discussed. The conclusion is that strengthening experimental studies on the effects of extreme temperatures including their interaction with enhanced atmospheric CO2 concentration on crop production and further improvement, evaluation, and inter-comparison of crop models based on new experimental datasets will contribute to the reduction of uncertainties in projected climate change impacts and evaluated adaptation options. It is envisaged that crop models will continue to serve as an important research tool in addressing climate change in the agricultural sector specifically and in general with respect to global food security. Therefore, this review will provide the agroclimate impact modelling community with information on the sources of uncertainties and the ways forward to tackle this critical issue.
      PubDate: 2022-05-16
       
  • Cooling island effect of urban lakes in hot waves under foehn and climate
           change

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      Abstract: Abstract The central region of Vietnam has a tropical monsoon climate but often undergoes heat waves due to uncontrolled urbanization, foehn winds, and climate change. Water bodies are considered effective candidates for heat mitigation in cities through the water cooling island (WCI) effect. Quantifying the WCI capacity of water areas and related factors is necessary for sites with advantages of surface water. The current attempt used the WCI effect range (Lmax), temperature drop amplitude (ΔTmax), and temperature gradient (Gtemp) to investigate the cooling effect of 20 lakes in the Thanh Noi region, Hue City. Data derived from high-resolution Google Earth, Landsat-8 Satellite Imagery Data, and ground truth. The results show that the average water temperature of the 20 studied lakes was about 36.61 °C, lower than the average temperature in the area with an urban heat island (UHI) of about 2.82 °C. The mean Lmax was 150 m, ΔTmax was 1.52 °C, and Gtemp was 10.16 °C /km or 0.01 °C/m. Climate characteristics and human impacts had reduced the ability of the lakes to create WCI during the period when the lake water level was low. The factors that influenced the WCI significantly were the landscape shape index (LSI), the proportion of green (PG), and the percentage of impervious surfaces (PI). Most lakes with relatively simple LSI, high PG, and low PI obtained high WCI, suggesting that structural and landscape characteristics played a critical role in urban cooling.
      PubDate: 2022-05-16
       
  • Analyzing spatial–temporal change of multivariate drought risk based on
           Bayesian copula: Application to the Balkhash Lake basin

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      Abstract: In the past century, drought events were likely to be frequent and severe in the arid areas under climate change impact. In this study, a Bayesian copula multivariate analysis (BCMA) method is developed for assessing the impact of spatial–temporal variation on drought risk, through coupling Bayesian copula with multivariate analysis. BCMA can reveal the dynamic characteristics of droughts and deal with the uncertainty caused by copula parameters when modeling the dependent structures of variable pairs (duration-severity-affected area). BCMA is applied to the Balkhash Lake basin in Central Asia for assessing multivariate drought risk during 1901–2020. Some major findings can be summarized: (1) in 1901–2020, the basin suffered 53 droughts; the most severe drought occurred from October 1973 to January 1977 (39 months), and 95% of the basin was affected (335,800 km2); (2) droughts usually develop in the direction of “east–west,” and Ili River delta and alluvial plain are the most frequent areas (47.2%) in the basin; (3) droughts show significant seasonality and frequently occur in spring and summer (64.2%), and drought risks of the middle and lower reaches of Ili River are the highest in spring and summer; (4) multivariate characteristics significantly affect drought risk, and drought risk ranges from 1.9 to 18.1% when the guarantee rate is 0.99; (5) the possible causes of drought risk dynamics are meteorological factors (e.g., precipitation and evapotranspiration) and underlying surface factors (e.g., runoff and soil moisture). The findings suggest that droughts in the Balkhash Lake basin are affected by climatic factors, and BCMA can provide methodological support for the studies of drought in other arid regions. Graphical abstract
      PubDate: 2022-05-14
       
 
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