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  Subjects -> METEOROLOGY (Total: 110 journals)
Showing 1 - 36 of 36 Journals sorted alphabetically
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 43)
Advances in Climate Change Research     Open Access   (Followers: 28)
Advances in Meteorology     Open Access   (Followers: 24)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 6)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 18)
American Journal of Climate Change     Open Access   (Followers: 27)
Atmósfera     Open Access   (Followers: 3)
Atmosphere     Open Access   (Followers: 25)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 14)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 10)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 47)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 14)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 69)
Atmospheric Science Letters     Open Access   (Followers: 36)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 31)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 1)
Bulletin of the American Meteorological Society     Open Access   (Followers: 49)
Carbon Balance and Management     Open Access   (Followers: 4)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 4)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Climate     Open Access   (Followers: 5)
Climate Change Economics     Hybrid Journal   (Followers: 14)
Climate Change Research Letters     Open Access   (Followers: 7)
Climate Change Responses     Open Access   (Followers: 8)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Climate law     Hybrid Journal   (Followers: 7)
Climate of the Past (CP)     Open Access   (Followers: 5)
Climate of the Past Discussions (CPD)     Open Access  
Climate Policy     Hybrid Journal   (Followers: 36)
Climate Research     Hybrid Journal   (Followers: 6)
Climate Risk Management     Open Access   (Followers: 4)
Climate Services     Open Access   (Followers: 3)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
Climatic Change     Open Access   (Followers: 60)
Current Climate Change Reports     Hybrid Journal   (Followers: 4)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 27)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 18)
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 2)
Energy & Environment     Hybrid Journal   (Followers: 23)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 6)
Frontiers in Climate     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 1)
Global Meteorology     Open Access   (Followers: 17)
International Journal of Atmospheric Sciences     Open Access   (Followers: 21)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
International Journal of Environment and Climate Change     Open Access   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 35)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 199)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 21)
Journal of Climate     Hybrid Journal   (Followers: 54)
Journal of Climate Change     Full-text available via subscription   (Followers: 2)
Journal of Climatology     Open Access   (Followers: 3)
Journal of Hydrology and Meteorology     Open Access   (Followers: 29)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 14)
Journal of Space Weather and Space Climate     Open Access   (Followers: 27)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 79)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Mathematics of Climate and Weather Forecasting     Open Access   (Followers: 6)
Mediterranean Marine Science     Open Access   (Followers: 1)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Meteorological Monographs     Hybrid Journal  
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 26)
Mètode Science Studies Journal : Annual Review     Open Access  
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal  
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 14)
Monthly Weather Review     Hybrid Journal   (Followers: 34)
Nature Climate Change     Full-text available via subscription   (Followers: 125)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 35)
Nīvār     Open Access  
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Open Atmospheric Science Journal     Open Access   (Followers: 2)
Open Journal of Modern Hydrology     Open Access   (Followers: 6)
Revista Brasileira de Meteorologia     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Space Weather     Full-text available via subscription   (Followers: 24)
Studia Geophysica et Geodaetica     Hybrid Journal  
Tellus A     Open Access   (Followers: 22)
Tellus B     Open Access   (Followers: 21)
The Cryosphere (TC)     Open Access   (Followers: 5)
The Cryosphere Discussions (TCD)     Open Access   (Followers: 4)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 27)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 12)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Urban Climate     Hybrid Journal   (Followers: 4)
Weather     Hybrid Journal   (Followers: 19)
Weather and Climate Dynamics     Open Access  
Weather and Climate Extremes     Open Access   (Followers: 16)
Weather and Forecasting     Hybrid Journal   (Followers: 28)
Weatherwise     Hybrid Journal   (Followers: 4)
气候与环境研究     Full-text available via subscription   (Followers: 1)

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Journal Cover
Theoretical and Applied Climatology
Journal Prestige (SJR): 0.867
Citation Impact (citeScore): 2
Number of Followers: 12  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1434-4483 - ISSN (Online) 0177-798X
Published by Springer-Verlag Homepage  [2626 journals]
  • Multiscale spatial variographic analysis of hydroclimatic data
    • Abstract: Abstract The spatial structure of the variance related to hydroclimatic datasets over multi-decadal timescales was studied for Mexico. The changes of variance at different spatial scales were investigated for precipitation and temperature normals by variographic analysis. The objective of the study was to determine the proper spatial scales for studying key climatic elements. Isotropy, anisotropy, 12 different models, and 50 distances from 0.1 to 100% of the study area diameter were tested for raw temperature and precipitation normals, as well as for the residuals resulting from polynomial detrending. Each variogram was tested, and the suitable ones were used to describe and understand the spatial variation of the phenomena. The variance structure in the data of each climatological element varies as a function of the scale, relief, and the application of detrending because the spatial evolution of the phenomena is complex. The active lag distances related to structures that best fit the data belong to meso-β scale and are shorter than the study area radius. Moreover, various mesoscale distances highlight different structures that have physical meanings.
      PubDate: 2021-01-18
  • Trends in the differences between homogenized ground surface temperature
           and surface air temperature in China during 1961–2016 and its possible
    • Abstract: Abstract Based on the latest series of homogenized ground surface temperature (GST) and surface air temperature (SAT) data for China, this study performed a detailed analysis of the trend of the differences between the two homogenized series in 1961–2016. The differences, referred to as surface–air temperature differences (SATDs) in this study, were separately averaged by month, season, and year. The long-term and spatial changes in the trends of SATDs were investigated. Moreover, interdecadal trend breakpoints were identified to understand the characteristics of trends in fluctuation. The possible influences of precipitation, Pacific Decadal Oscillation (PDO), and global warming on SATDs were also analyzed. The results showed that during the 12 months of a year, only three months, March, April, and May, exhibited increasing trends of station-averaged, monthly mean SATDs while the other nine months exhibited decreasing trends. In addition, the station-averaged annual and seasonal mean SATDs of summer, autumn, and winter all showed significant decreasing trends, while the spring mean SATDs showed a significant increasing trend. The spatial distribution pattern of the linear trends of monthly, seasonal, and annual SATDs in meteorological stations indicated that SATDs had more obviously increasing trends in the northern regions than the southern regions of China. The trends of station-averaged monthly mean SATDs (except for April) and station-averaged seasonal and annual mean SATDs experienced interdecadal breakpoints, fully indicative of obvious interdecadal fluctuations with temporal complexity among China’s SATD trends. By the regression analysis of monthly STADs against simultaneous precipitation, as well as the comparative analysis of their linear trends, we found that both amount of precipitation and the change of precipitation type have important influences on SATDs. The results of convergent cross mapping analysis also revealed the causal effect of precipitation on SATDs.
      PubDate: 2021-01-18
  • On the Bayesian network based data mining framework for the choice of
           appropriate time scale for regional analysis of drought Hazard
    • Abstract: Abstract Data mining has a significant role in hyrdrologic research. Among several methods of data mining, Bayesian network theory has great importance and wide applications as well. The drought indices are very useful tools for drought monitoring and forecasting. However, the multi-scaling nature of standardized type drought indices creates several problems in data analysis and reanalysis at regional level. This paper presents a novel framework of data mining for hydrological research—the Bayesian Integrated Regional Drought Time Scale (BIRDts). The mechanism of BIRDts gives effective and sufficient time scales by considering dependency/interdependency probabilities from Bayesian network algorithm. The resultant time scales are proposed for further investigation and research related to the hydrological process. Application of the proposed method consists of 46 meteorological stations of Pakistan. In this research, we have employed Standardized Precipitation Temperature Index (SPTI) drought index for 1-, 3-, 6-, 9-, 12-, 24-, and ()month time scales. Outcomes associated with this research show that the proposed method has rationale to aggregate time scales at regional level by configuring marginal posterior probability as weights in the selection process of effective drought time scales.
      PubDate: 2021-01-16
  • The effect of diurnal temperature range on mortality in Kerman, Iran
    • Abstract: Abstract Diurnal temperature range (DTR) is one of the climate indicators likely to be related to human health. The purpose of this study was to investigate the relation between mortality and DTR in Kerman, Iran. The DLNM (Distributed Lag Non-linear Model)with a quas/i-Poisson regression model was used to evaluate the effect of DTR on mortality in age and sex groups by controlling the confounding variables (long-term trend of daily mortality, effect of day of the week, holidays, mean temperature, humidity, and air pollution). Since DTR effects on mortality may vary in cold and warm seasons, separate analyses were conducted for cold and warm seasons. DTR showed a non-linear relation with mortality. Mortality increased at the 90th percentile of DTR (CRR = 1.16, 95% CI 1.00–1.34), in lag 0–21 and at the 10th percentile of DTR in lag 0–13 (1.27, 95% CI 1.06–1.52), and lag 0–21 1.35 (95% CI 1.06–1.71). Increased mortality was more observed in the > 60 age group and in men. High levels of DTR after long lags (13 days) in the cold season were associated with increasing mortality. High and low diurnal temperature range may be a risk factor for mortality, especially in the men and elderly.
      PubDate: 2021-01-09
  • Responses of yield variability of summer maize in Henan province, north
           China, to large-scale atmospheric circulation anomalies
    • Abstract: Abstract Based on the climate-driven yield index (CDYI) series of summer maize in 17 cities and the monthly series of large-scale atmospheric circulation indices (LACI), the responses of yield fluctuations of summer maize to atmospheric circulation anomalies during 1988–2017 were explored in Henan province, north China. The main findings were as follows: (1) with using principal component analysis, east, north, central, and west Henan were identified as four sub-regions with different CDYI variations; (2) with using ensemble empirical mode decomposition, the CDYI in east and north Henan presented a notable 6-year oscillation, while central and west Henan were dominated by a 3-year oscillation; (3) East Pacific/North Pacific Oscillation in January, Eastern Tropical Pacific SST in May, Tropical Southern Atlantic Index in June, and North Pacific in September were the optimal yield prediction signals in east, north, central, and west Henan, respectively; (4) the regression model with predictors as year and various LACI had the ideal forecasting results on actual regional maize yield, with the average relative error ranged from 4.94 to 9.20%.
      PubDate: 2021-01-09
  • Seasonal trend analysis of minimum air temperature in La Plata river basin
    • Abstract: Abstract Regional economies that depend predominantly on agriculture and livestock are heavily affected by changes in air temperature, one such case are the activities in La Plata river basin (LPB). Some studies suggest that variations in the seasonal cycle and season onset would affect efficiency in the use of radiation by vegetation. This paper evaluates the distribution of minimum temperature seasonality trends over LPB, describes the trends in the seasonal cycle, and detects changes of minimum temperature extremes characterized by the number of frost days and the frequency of warm and cold nights. The analysis includes absolute minimum temperature (TnMin) and minimum average temperature (TnMean) from ERA5 reanalysis for the 1980–2015 period. Significant positive trends in the amplitude of annual average TnMin and TnMean are observed over more than half the area (53.5% and 69.9% of the basin, respectively). Amplitude and phase parameters suggest that average minimum temperature underwent greater variation than absolute minimum temperature over LPB. The shifts in phase indicate that minimum temperatures occurred earlier than usual in the year considering the 35-year series. In general terms, there is a shift toward warmer conditions. This warming is evident in seasonal trends of minimum temperature as well as in the significant increase in the number of warm nights, a significant decrease of cold days and a significant decrease in the number of frost days in the highest Andes mountains in the west of the LPB.
      PubDate: 2021-01-09
  • Determining land suitability for pistachio cultivation development based
           on climate variables to adapt to drought
    • Abstract: Abstract Land evaluation based on its characteristics is a criterion for the proper use of land potential. The high benefit and low water requirement of pistachio has significantly increased its cultivation area in Iran. The objective of this study was to evaluate the suitability of lands for pistachio cultivation based on climatic variables in four provinces, which located in northwestern part of Iran. The climatic requirements of pistachio were specified based on its phenological information. Then, the suitability map of pistachio cultivation zones, spatially modeled in GIS environment based on long term of meteorological data. Subsequently, the results were verified due to field survey and interviews with farmers. The results showed study area classified into three categories from suitable (class S1), moderate suitable (S2), and non-suitable (class N) based on FAO land capability guidelines. So, accuracy of suitability map was validated by overlaying of spatial information of existing pistachio orchards. The results indicated that 33, 33.4, 60, and 12.4% of the East Azerbaijan, West Azerbaijan, Kurdistan, and Ardabil provinces are suitable for pistachio cultivation (class S1), respectively, while the area of unsuitable class (class N) in these provinces was 40, 34.7, 22.7, and 62%, respectively. It was found that the temperature and relative humidity during pollination and growth periods are the main limiting factors for construction of pistachio orchards. The obtained maps can be used as a guide to prevent the planting of pistachios in unsuitable areas and consequently save water consumption in drought conditions.
      PubDate: 2021-01-08
  • Present-day climate and projected future temperature and precipitation
           changes in Ecuador
    • Abstract: Abstract Ecuador is likely to experience significant impacts associated with future changes in climate, but future projections for this region are challenging due to the complex topography and a wide range of climatic conditions. Here we use the Weather Research and Forecasting (WRF) model run at 10 km horizontal resolution over a domain encompassing all of Ecuador to investigate future changes in temperature and precipitation for the middle of the twenty-first century (2041–2070) under a low (RCP4.5) and a high (RCP8.5) emission scenario. The model was validated by running 30-year control runs for the present climate, driven both by the Climate Forecast System Reanalysis (CFSR) and the CCSM4 General Circulation Model. Bias and different correlation coefficient metrics were employed to compare the present-day model results with gridded (CRU TS v 4.03 and CHIRPS v 2.0) and in situ meteorological observations. Detailed hydrometeorological analyses over the Andes in both space and time domains show that WRF accurately simulates temperature variability. The precipitation seasonal cycle and interannual variability are also adequately simulated, but the model shows a general dry bias over the lowlands and a significant wet bias along the eastern Andean slopes. Results from future projections show that Ecuador could warm by an additional 1–2 K by the middle of the century compared with the end of the twentieth century. This warming is highly elevation-dependent, subjecting the highest peaks of the Andes to the strongest future warming. Bias-corrected future precipitation changes document a drying trend along coastal areas in RCP4.5 and increased future precipitation along the eastern Andean slopes in both scenarios.
      PubDate: 2021-01-08
  • Spatial and temporal variabilities in baseflow characteristics across the
           continental USA
    • Abstract: Abstract Trends in baseflows based on observed daily streamflow data are evaluated in this study at several sites in the least anthropogenically affected watersheds in the USA. Trends were determined for annual maximum, annual mean, and annual median baseflow. Baseflow values derived at 574 stations in the USA for the 44 years from 1970 through 2013 are analyzed using two nonparametric trend tests (Spearman’s rho (SR) test and Mann-Kendall (MK)). Results from the trend tests are compiled for 18 major regions to understand the spatial variability of changes in baseflows across the USA. Results from SR tests indicate that almost half of the stations show statistically significant trends in annual maximum baseflows. Trends in annual median baseflows show that 32.06% of the gauging stations have downward trends, and a total of 56.45% of sites show significant trends for annual mean baseflows. The Souris-Red-Rainy, Missouri, and California watershed regions have a larger number of sites with higher upward trends compared with those from other regions in the USA. The results from the SR test indicate that 262 sites have statistically significant trends in annual maximum baseflow compared with the 254 sites with similar trends noted from the MK test. Based on limited data, it can be concluded that baseflow and precipitation values accumulated for the same month are correlated in some regions. In general, the number of sites with decreasing trends for annual maximum, mean, and median baseflows is larger than the number of sites with increasing trends. Decreasing trends in baseflows are cause for concern and have serious implications on future planning for low flow management strategies for several streams in the USA.
      PubDate: 2021-01-08
  • Spatial and temporal changes in vegetation and desertification
           (1982–2018) and their responses to climate change in the Ulan Buh
           Desert, Northwest China
    • Abstract: Abstract To combat desertification, an understanding of its current development is necessary, including that of causative factors associated with climate change and increasing human activity. Whereas, there is an ongoing debate surrounding impact factors for change in vegetation and desertification in arid regions. The present study assesses the spatiotemporal characteristics of vegetation change in the Ulan Buh Desert, northwest China. Driving factors for desertification were discussed using the Global Inventory Monitoring and Modeling System Normalized Difference Vegetation Index (GIMMS NDVI) and SPOT Vegetation NDVI datasets, high-resolution satellite images, and meteorological and socioeconomic data in the period 1982–2018. The results show a trend of overall greening, with increasing trends at rates between 0.0008/year and 0.0013/year indicated by the two NDVI datasets and with a corresponding reduction in dune activity. The spatial variations of two NDVI datasets verified the significantly greening trend in the northern and southern areas of the desert. Human activity was observed to have impacted vegetation dynamics. It is predicted that the implementation of ecological projects will contribute to the restoration of vegetation during a warmer, wetter climate trend. However, the reduction of wind strength played a dominant role in vegetation greenness and dune stability in the Ulan Buh Desert. The present study revealed the spatiotemporal characteristics of vegetation variations and the driving factors for desertification in arid regions.
      PubDate: 2021-01-08
  • Application of machine learning for solar radiation modeling
    • Abstract: Abstract Solar radiation is an important parameter that affects the atmosphere-earth thermal balance and many water and soil processes such as evapotranspiration and plant growth. The modeling of the daily and monthly solar radiation by Gaussian process regression (GPR) with K-fold cross-validation model has been discussed recently. This study evaluated different neural models such as artificial neural network (ANN), support vector machine (SVM), adaptive network-based fuzzy inference system (ANFIS), and multiple linear regression (MLR) for estimating the global solar radiation (daily and monthly) with K-fold cross-validation method. For the appropriate comparison of the models, the randomized complete block (RCB) design applied in the training and test phases. Also, different data sets were evaluated by K-fold cross-validation in each model. The results showed that radial basis function (RBF) model has the lowest error for estimating the monthly and daily solar radiation. In this study, the result of RBF was compared with the GPR models. The conclusion indicated that RBF methodology can predict solar radiation with higher accuracy relative to the GPR model. The results of yearly solar radiation estimation (2009–2014) showed that the RBF model can estimate solar radiation with the MAPE and RMSE of 5.1% and 0.29, respectively. Also, the coefficient of correlation (R2) between actual and estimated values throughout the year is 98% and can be used by the engineers and other researchers for solar and thermal applications.
      PubDate: 2021-01-08
  • Climate and rainfed wheat yield
    • Abstract: Abstract Planning for precision agriculture requires a better understanding of the plant’s response to climate. The economy of Qorveh, in Iran, is severely affected by wheat yield fluctuations. In this study, multivariate statistical methods were used to identify important climatic factors affecting rainfed wheat yield and to simulate yield variations based on these impact factors. A new method was introduced to initiate seed germination. After determining the germination time, the wheat growth period was divided into seven stages based on the growing degree day (GDD). Forty-four climatic variables and indices related to the first six stages were used to perform factor analysis and to develop a model for predicting pre-harvest yield. The results showed that 91.5% of the total variance of 44 variables can be explained by 9 factors. Eighty-five percent of yield variations can be explained and modeled (R = 0.92) using five of these factors. This indicates that rainfed wheat yield is highly correlated with climate conditions, and this relationship is well simulated by statistical methods. According to the results, the significant trend of climatic variables was identified as the main reason for the yield growth trend in Qorveh. The yield showed a direct relationship with precipitation and relative humidity and an inverse relationship with air temperature and sunshine. The impact intensity of variables on yield included precipitation, relative humidity, sunshine, and air temperature, respectively. The results also showed that the yield was more affected by climatic variables of spring and May than other seasons and months, respectively.
      PubDate: 2021-01-07
  • Updating regionalization of precipitation in Ecuador
    • Abstract: Abstract This article identifies homogeneous precipitation regions in Ecuador and their relationship to the El Niño-Southern Oscillation (ENSO), using monthly records from 215 rain stations for the 1968–2014 period. A k-means clustering analysis was used to divide the study area into k regions based on monthly and annual precipitation variables and geographic location (latitude, longitude, and altitude). The robustness of each cluster was evaluated using the “silhouette” coefficient. The groupings were then validated using the regional vector method (RVM). Twenty-two regions of homogeneous precipitation were identified. Seven regions are related to regional climate processes on the Pacific coast (unimodal precipitation). Two regions in the western foothills of the Andes show significant orographic rainfall. Eight regions in the inter-Andean region present a bimodal precipitation regime characterized by a reduction of precipitation from north to south and local variability. Five regions were identified in the Amazon area: three on the outer flanks of the eastern mountain range, one sub-Andean area, and one in the Amazon plain with regular rainfall throughout the year, influenced by the Amazon basin. Although Tropical Pacific sea surface temperature (SST) is strongly related to precipitation in the coastal regions of Ecuador, our findings indicate that SST influence varies among the regions of the country because Ecuador is influenced by the modes of precipitation variability in Colombia and Peru.
      PubDate: 2021-01-07
  • Effects of the Antarctic elevation on the atmospheric circulation
    • Abstract: Abstract The orographic effects of Antarctica on the atmospheric circulation are investigated through idealized orographic reduction numerical experiments performed using the NCAR CAM5 model. The investigation shows that, in the absence of the orography over the continent, the troposphere becomes warmer and wetter, the sea level pressure reduces, and the precipitation is enhanced. Furthermore, over the continent, the height of the tropopause increases, the stationary waves become weaker, and the southern polar jet gets more energetic. The radiative budget also gets altered, with more outgoing longwave radiation over the continent, which drives circulation changes beneath. The mean atmospheric circulation is weakened with weakening and shrinking of the Polar cell and widening of the Ferrel cell in the Southern Hemisphere, which decreases the contribution by mean flow towards poleward energy transport. An increase in transient eddy due to an enhancement of baroclinicity over the region supports poleward energy transport and compensates for a higher outgoing longwave radiation over the Antarctic continent. These significant changes observed in idealized Antarctic orographic reduction demonstrate the importance of the present Antarctic orography and ice cover for the Southern Hemisphere. The impact of these changes provides valuable insights on the future role of Antarctic orography on the earth’s climate system from a fundamental point of view.
      PubDate: 2021-01-07
  • Evaluation of multivariate linear regression for reference
           evapotranspiration modeling in different climates of Iran
    • Abstract: Abstract The study aimed to evaluate the accuracy of empirical equations (Hargreaves-Samani; HS, Irmak; IR and Dalton; DT) and multivariate linear regression models (MLR1–6) for estimating reference evapotranspiration (ETRef) in different climates of Iran based on the Köppen method including arid desert (Bw), semiarid (Bs), humid with mild winters (C), and humid with severe winters (D). For this purpose, climatic data of 33 meteorological stations during 30 statistical years 1990–2019 were used with a monthly time step. Based on various meteorological data (minimum and maximum temperature, relative humidity, wind speed, solar radiation, extraterrestrial radiation, and vapor pressure deficit), in addition to 6 multivariate linear regression models and three empirical equations were used as MLR1, MLR2, and HS (temperature-based), MLR3 and IR (radiation-based), MLR4, MLR5 and DT (mass transfer-based), and MLR6 (combination-based) were also used to estimate the reference evapotranspiration. The results of these models were compared using the root mean square error (RMSE), mean absolute error (MAE), scatter index (SI), determination coefficient (R2), and Nash-Sutcliffe efficiency (NSE) statistical criteria with the evapotranspiration results of the FAO56 Penman-Monteith reference as target data. All MLR models gave better results than empirical equations. The results showed that the simplest regression model (MLR1) based on the minimum and maximum temperature data was more accurate than the empirical equations. The lowest and highest accuracy related to the MLR6 model and HS empirical equation with RMSE was 10.8–15.1 mm month−1 and 22–28.3 mm month−1, respectively. Also, among all the evaluated equations, radiation-based models such as IR in Bw and Bs climates with MAE = 8.01–11.2 mm month−1 had higher accuracy than C and D climates with MAE = 13.44–14.48 mm month−1. In general, the results showed that the ability of regression models was excellent in all climates from Bw to D based on SI < 0.2.
      PubDate: 2021-01-07
  • Analysis of the effects of meteorological parameters on radio
           refractivity, equivalent potential temperature and field strength via
           Mann-Kendall test
    • Abstract: Abstract Trend analysis of meteorological parameters (temperature, pressure, and relative humidity) as well as calculated refractivity, equivalent potential temperature (EPT) for a pseudo-adiabatic process, and field strength in Calabar, Southern Nigeria has been analyzed using Mann-Kendall (M-K) trend test and Sen’s slope estimator (SSE). Data of the meteorological parameters were obtained from the Nigerian Meteorological Agency (NiMet) in Calabar for 14 years (2005–2018). Results show that the maximum and average temperature, atmospheric pressure, refractivity, EPT, and field strength all exhibited a positive Kendall Z value with 2.52, 0.33, 3.83, 0.77, 0.44, and 3.18 respectively which indicated an increase in trend over time, with only maximum temperature, atmospheric pressure and field strength showing a significant increase at 5% (0.05) level of significance, since their calculated p values (0.012, 0.0001, and 0.001) were less than 0.05. The relative humidity and minimum ambient temperature had a decrease in trend over time as they both had negative Kendall Z values (− 0.11 and − 1.09 respectively); however, together with the average ambient temperature and refractivity, their trend was not significant at 5% level of significance since their calculated p values were all more than 0.05. Linear regression, correlation, and partial differentiation showed that relative humidity has the most effect on the changes in seasonal refractivity and an indirect relationship with field strength variability. The novel relationship between EPT and refractivity has been discovered to be very strong and positive. Descriptive statistics has been used to portray the seasonal and annual trend of all parameters.
      PubDate: 2021-01-07
  • Power law characteristics of trend analysis in Turkey
    • Abstract: Abstract Trend identification analyses in any hydrometeorological data are necessary and critical for predictions and planning in many disciplines such as atmospheric, environmental, and oceanographic sciences; water engineering; global warming; and climate change applications. In the literature, many researches have employed trend analyses by Mann-Kendall (MK) and innovative trend analysis (ITA) methods. Especially in recent years, the ITA method is preferred in trend identification methodological applications, because it can present trend graphs with visual inspection, verbal inferences, and objective quantitative calculations. In this paper, the trends of sea surface temperature (SST) data are identified by the MK and ITA methods on double logarithmic graphs, which provide fractal geometrical appearances with power law features. The SST data trends are evaluated at 22 coastal area stations of Turkey with monthly records from 1969 to 2014. According to the MK trend test, only 6 of the 22 stations had a significant upward trend at 5% significant level and 4 of these stations are in the Mediterranean Sea coastal area. At 10% significance level increasing trend numbers become 14 stations. According to the MK test results, the data records have been grouped into two parts as warming and cooling periods considering the physical conditions of the SST data. On the other hand, the results of ITA application provide average behavioral form according to the mathematical power law equations.
      PubDate: 2021-01-07
  • Assessment of surface energy balance algorithm for land and operational
           simplified surface energy balance algorithm over freshwater and saline
           water bodies in Urmia Lake Basin
    • Abstract: Abstract To manage inland water resources, surveying the performance of remote sensing models for estimating the actual evaporation in arid regions is so important. Hence, this study aimed to assess the performance of two energy balance algorithms including surface energy balance algorithm for land (SEBAL) and operational simplified surface energy balance (SSEBop) in freshwater and saline water bodies. Another purpose of the present study was efficiency improvement in hypersaline lakes. In this regard, a practical salinity correction coefficient was used to overcome shortcomings of the selected models over saline Lake. The analysis of yearly lake water budget was used to assess the selected energy balance algorithms’ performance with a novel approach. These algorithms were investigated at Shahid Kazemi Dam Reservoir (as a freshwater body) and Urmia Lake (as a hypersaline water body) in Iran. The results showed that two selected algorithms estimated the evaporation rate at the selected freshwater body with a proper accuracy. The results showed the root mean square error for SEBAL result (RMSESEBAL) as 2.0 mm/day, correlation coefficient for SEBAL result (RSEBAL) as 0.80 mm/day, and RMSESSEBop and RSSEBop as 1.7 and 0.80 mm/day, respectively. However, these models overestimated evaporation over the hypersaline water body (RMSESEBAL = 88.4 mm/month, RSEBAL = 0.90 and RMSESSEBop = 39.9 mm/month, RSSEBop = 0.94). Salinity correction coefficient improved the results as RMSESEBAL = 19.8 mm/month, RSEBAL = 0.90 and RMSESSEBop = 13.4 mm/month, and RSSEBop = 0.94. In general, the algorithm performance was improved using the salinity correction coefficient in the chosen hypersaline water body.
      PubDate: 2021-01-07
  • Factors responsible for consecutive deficit Indian monsoons during 2014
           and 2015
    • Abstract: Abstract Increased frequency of droughts in the recent decade (2002, 2004, 2009, 2014, 2015 being drought years) and the severity of their impact makes drought prediction an inherent component of forecasts for drought mitigation and preparedness. The research and development activities cannot prove their full potential unless they can produce a long lead skillful prediction of extreme conditions like flood or drought. During 2014 and 2015, India experienced deficit monsoon for two successive years. The present study explores the various factors responsible for the droughts during 2014 and 2015 and how well the state-of-the-art coupled model capture the consecutive droughts. The study shows that not only tropical sea surface temperatures (SSTs) but also extratropical SSTs can influence the rainfall over India. Extratropical SSTs impacted the rainfall during 2014 by modulating the strength and location of subtropical jet and tropospheric temperature gradient. On the other hand, tropical SSTs over Pacific Ocean influenced the rainfall during 2015 by modulating the atmospheric teleconnections via Walker circulation. The present-day models considered in this study could not capture consecutively the Indian monsoon droughts and the associated atmosphere and ocean conditions.
      PubDate: 2021-01-07
  • Impact of climate change on groundwater recharge in a Brazilian Savannah
    • Abstract: Abstract There is little information about the availability of water in the Cerrado biome, the main agricultural frontier in Brazil, especially about groundwater, and this has compromised the region’s economic and social development, as well as environmental sustainability. The reduction of rainfall in this region, indicated by numerous climate models, may reduce aquifer recharge and, consequently, groundwater availability and sustainable development of the Cerrado biome. This study aimed to evaluate the impact of global climate change on groundwater recharge in a Brazilian Savannah watershed. Rainfall and water table depth data were recorded between 2007 and 2015. Based on these data, equations were developed relating the average monthly depth of the water table with the accumulated average monthly rainfall. From these equations, monthly average recharges considering the future climate estimates made by climate models (Eta-HadGEM2-ES and Eta-MIROC5) and Representative Concentration Pathway (RCP) scenarios (4.5 and 8.5) were calculated. In a pessimistic scenario (RCP 8.5), the average monthly groundwater recharge is decreasing in the beginning and in the end of the rainy season, indicating that there may be an increase in the dry season and, consequently, a reduction in water availability in the Cerrado biome region.
      PubDate: 2021-01-07
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