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  Subjects -> METEOROLOGY (Total: 112 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: 29)
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: 29)
Atmósfera     Open Access   (Followers: 3)
Atmosphere     Open Access   (Followers: 26)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 15)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 48)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Atmospheric Environment     Hybrid Journal   (Followers: 73)
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: 51)
Carbon Balance and Management     Open Access   (Followers: 4)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 5)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Climate     Open Access   (Followers: 6)
Climate and Energy     Full-text available via subscription   (Followers: 3)
Climate Change Economics     Hybrid Journal   (Followers: 20)
Climate Change Research Letters     Open Access   (Followers: 7)
Climate Change Responses     Open Access   (Followers: 10)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Climate law     Hybrid Journal   (Followers: 8)
Climate of the Past (CP)     Open Access   (Followers: 5)
Climate of the Past Discussions (CPD)     Open Access  
Climate Policy     Hybrid Journal   (Followers: 42)
Climate Research     Hybrid Journal   (Followers: 6)
Climate Resilience and Sustainability     Open Access   (Followers: 9)
Climate Risk Management     Open Access   (Followers: 5)
Climate Services     Open Access   (Followers: 3)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
Climatic Change     Open Access   (Followers: 64)
Current Climate Change Reports     Hybrid Journal   (Followers: 6)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 28)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 3)
Energy & Environment     Hybrid Journal   (Followers: 24)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 7)
Frontiers in Climate     Open Access   (Followers: 3)
GeoHazards     Open Access   (Followers: 2)
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 Climate Change Strategies and Management     Hybrid Journal   (Followers: 20)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
International Journal of Environment and Climate Change     Open Access   (Followers: 4)
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: 34)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 198)
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: 80)
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   (Followers: 2)
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   (Followers: 1)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Monthly Weather Review     Hybrid Journal   (Followers: 34)
Nature Climate Change     Full-text available via subscription   (Followers: 133)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 37)
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: 25)
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: 13)
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: 13  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1434-4483 - ISSN (Online) 0177-798X
Published by Springer-Verlag Homepage  [2653 journals]
  • Trend analysis of precipitation records using an innovative trend
           methodology in a semi-arid Mediterranean environment: Cheliff Watershed
           Case (Northern Algeria)
    • Abstract: The description and analysis of rainfall trends is necessary for effective planning, management, and exploitation of water resources. This study investigates the possible trend of precipitation of 28 stations in a semi-arid Mediterranean environment (Northern Algeria) for the period from 1959 to 2019 (60 years), using a recently proposed innovative partial trend methodology. The main advantage of this new method is that it provides qualitative interpretations of trends in the high, medium, and low precipitation ranges in terms of the structure of the time series’ internal trend. An accurate database has been established thanks to the homogeneity of the data quality leading to rather satisfactory results with a precision of the spatial and temporal tendencies, thus establishing maps of regional trends: “high precipitation,” “average precipitation,” and “low precipitation” for the whole study area.
      PubDate: 2021-03-13
       
  • Ranking of gridded precipitation datasets by merging compromise
           programming and global performance index: a case study of the Amu Darya
           basin
    • Abstract: Accurate representation of precipitation over time and space is vital for hydro-climatic studies. Appropriate selection of gridded precipitation data (GPD) is important for regions where long-term in situ records are unavailable and gauging stations are sparse. This study was an attempt to identify the best GPD for the data-poor Amu Darya River basin, a major source of freshwater in Central Asia. The performance of seven GPDs and 55 precipitation gauge locations was assessed. A novel algorithm, based on the integration of a compromise programming index (CPI) and a global performance index (GPI) as part of a multi-criteria group decision-making (MCGDM) method, was employed to evaluate the performance of the GPDs. The CPI and GPI were estimated using six statistical indices representing the degree of similarity between in situ and GPD properties. The results indicated a great degree of variability and inconsistency in the performance of the different GPDs. The CPI ranked the Climate Prediction Center (CPC) precipitation as the best product for 20 out of 55 stations analysed, followed by the Princeton University Global Meteorological Forcing (PGF) and Climate Hazards Group Infrared Precipitation with Station (CHIRPS). Conversely, GPI ranked the CPC product the best product for 25 of the stations, followed by PGF and CHRIPS. Integration of CPI and GPI ranking through MCGDM revealed that the CPC was the best precipitation product for the Amu River basin. The performance of PGF was also closely aligned with that of CPC.
      PubDate: 2021-03-12
       
  • Observed changes in rainfall amount and extreme events in southeastern
           Ethiopia, 1955–2015
    • Abstract: This study analysed spatio-temporal variability and trends in rainfall amount and extreme events in the southeastern part of Ethiopia for the period 1955–2015. Daily rainfall data from 44 recording stations were used to define total rainfall amounts and 12 extreme event indices for three wet seasons and annual time scale. Mann–Kendall’s trend test and Sen’s slope estimator were used to determine trends and rates of change, respectively. Results showed the emergence of different trend signals across seasons and over space in the study area. Trend tests for total rainfall amount and extreme indices for annual and March–May season show a global significant downward tendency. However, the number of wet and dry days, maximum consecutive wet and dry spells and wet day rainfall intensity for the annual time scale show mixed significant upward and downward tendencies, while trends for the number of dry days and maximum consecutive dry spells showed a global significant increasing trend for the March–May season across the study area. On the other hand, mixed global significant upward and downward tendencies were found in all rainfall indices for the June–September season over the northern part of the study area. Different from the two wet seasons, the trend test for the September–November wet season in the southern part of the study area shows an increasing tendency, although only few of the upward trends were statistically significant. In contrast, the number of dry days and maximum dry spell length for this season reveal decreasing trends at most of the stations. Empirical evidences generated in rainfall trends using dense gauging stations provide useful information to develop spatially relevant climate change adaptation and climate risk management plans.
      PubDate: 2021-03-11
       
  • Estimating monthly air temperature using remote sensing on a region with
           highly variable topography and scarce monitoring in the southern
           Ecuadorian Andes
    • Abstract: Monitoring of air temperature has implications in a wide range of environmental applications. Air temperature commonly measured with meteorological stations provides a high accuracy and temporal resolution for specific monitoring sites. However, in regions with highly variable topography and scare monitoring such as the case of the southern Ecuadorian Andes, these in situ data poorly describe the spatial variability of air temperature. Thus, remote sensing data has a great potential to estimate the spatial distribution of climatological variables due to the spatial continuity of the information. This research aims to estimate the spatial distribution of the monthly air temperature in the Paute river basin for the period 2014–2017, using statistical and geostatistical methods: linear regression (LR), random forest regression (RF), and regression kriging (RK), in addition to evaluate the use of altitude and other auxiliary variables (land surface temperature, latitude, and longitude). Cross-validation showed that RF performed better than LR as well as when using auxiliary variables compared to only the altitude (LR-altitude: RMSE=1.325 °C, P bias= −0.150%, r=0.775; LR-auxiliary variables: RMSE=1.265 °C, P bias=0.000% r=0.795; RF-altitude: RMSE=1.235 °C, P bias =0.200%, r=0.810; RF-auxiliary variables RMSE=1.205 °C, P bias =0.200%, r=0.820). The application of regression kriging was limited since less than 50% of the months had spatial autocorrelation in the regression model residuals. Nevertheless, in these months, regression kriging increased the estimation performance. The outcomes of this research work increase the understanding of the spatial distribution of monthly air temperature in the Paute river basin, which will improve hydrological modeling.
      PubDate: 2021-03-11
       
  • Assessment of APCC models fidelity in simulating the Northeast monsoon
           rainfall variability over Southern Peninsular India
    • Abstract: The fidelity of the eight Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) models in representing the inter-annual variability and decadal shift in the northeast monsoon (NEM; October–December) rainfall over Southern Peninsular India (SPI) is evaluated. The hindcast data is used for the period of 28 years from 1983 to 2010 based on September initial conditions. The observations showed a clear inter-annual and inter-decadal variability of NEM rainfall during the study period. The analysis suggests that most of the models exhibited poor skill in representing the inter-annual variability. Only APCC model rainfall is in phase with observed SPI rainfall variations on the inter-annual time scale. It is noticed from the observed NEM rainfall time series that the period 1990–1999 (first decade) displays an above-normal rainfall and the period 2000–2010 (second decade) displays a below normal rainfall over the SPI region. It is also evident from the observations that NEM rainfall for most of the years displayed negative anomalies in the second decade including El Niño and La Niña years, while in the first decade positive anomalies are noted, suggesting the presence of decadal variability in the NEM. Rainfall variations in most of the coupled models are in phase with the observations during the second decade but are out of phase during the first decade. As evidenced from the observations that the intensified deep convection over the Indo-western Pacific region results in too far southward movement of the intertropical convergence zone (ITCZ) during the second decade. The southward shift in the strong upper-level divergence associated with lower-level convergence over the south Indian Ocean caused negative rainfall anomalies over the SPI in this decade. Further, the difference between the second and first decade demonstrates that an anomalous anticyclonic circulation over the Indian subcontinent is accountable for the vigorous dry northerly flow towards the SPI region and the resultant decadal shift in the rainfall pattern. Though the southward shift in the rainfall and large-scale circulation patterns are mildly captured by some models from decade to decade, most of the models completely misrepresented it. This study suggests that the coupled models displayed a very limited skill not only in capturing the inter-annual variability but also in representing the decadal variability of NEM rainfall.
      PubDate: 2021-03-10
       
  • Value addition to forecasting: towards Kharif rice crop predictability
           through local climate variations associated with Indo-Pacific climate
           drivers
    • Abstract: The Indian Institute of Tropical Meteorology (IITM) has generated seasonal and extended range hindcast products for 1981–2008 and 2003–2016, respectively, using the IITM-Climate Forecast System (IITM-CFS) coupled model at various resolutions and configurations. Notably, our observational analysis suggests that for the 1981–2008 period, the tropical Indo-Pacific drivers, namely, the canonical El Niño-Southern Oscillation (ENSO), ENSO Modoki, and Indian Ocean Dipole (IOD). are significantly associated with the observed Kharif rice production (KRP) of various rice-growing Indian states. In this paper, using the available hindcasts, we evaluate whether these state-of-the-art retrospective forecasts capture the relationship of the KRP of multiple states with the local rainfall as well as the tropical Indo-Pacific drivers, namely, the canonical ENSO, ENSO Modoki, and the IOD. Using techniques of anomaly correlation, partial correlation, and pattern correlation, we surmise that the IITM-CFS successfully simulate the observed association of the tropical Indo-Pacific drivers with the local rainfall of many states during the summer monsoon. Significantly, the observed relationship of the local KRP with various climate drivers is predicted well for several Indian states such as United Andhra Pradesh, Karnataka, Odisha, and Bihar. The basis seems to be the model’s ability to capture the teleconnections from the tropical Indo-Pacific drivers such as the IOD, canonical and Modoki ENSOs to the local climate, and consequently, the Kharif rice production.
      PubDate: 2021-03-08
       
  • Regional circulation patterns inducing coastal upwelling in the Baltic Sea
    • Abstract: Atmospheric feedback involved in the occurrence of coastal upwelling in a small semi-enclosed sea basin, i.e., the Baltic Sea, was analysed, and the regional circulation conditions triggering upwelling in different coastal sections were identified. Upwelling in the summer season (June–August, years 1982–2017) was recognized on the basis of sea surface temperature patterns. Circulation conditions were defined using (1) the established daily indices of zonal and meridional airflow and (2) the synoptic situation at sea level distinguished by applying rotated principal component analysis to sea level pressure data. The 12 daily synoptic patterns differed substantially in the intensity and location of their pressure centres. The mean seasonal frequency of upwelling was generally higher along the western Baltic shores than along the meridionally oriented eastern shores and varied from less than 10 to over 30% along the more predestined coastal sections, i.e., the northwestern coast of the Gulf of Bothnia, the northern Gulf of Finland and the southern Swedish coast. Due to the variable orientations of coastlines, upwelling could occur under almost any prevailing wind direction, and thus, each of the classified synoptic patterns could induce upwelling in some coastal sections. As deduced from the pressure fields for each circulation pattern, mostly alongshore winds triggered upwelling, which is in line with the Ekman rule. With time, upwelling could also be induced by the stress of normal to the coastline seaward winds.
      PubDate: 2021-03-08
       
  • Performance evaluation of NCEP/NCAR reanalysis blended with
           observation-based datasets for estimating reference evapotranspiration
           across Iran
    • Abstract: Computing crop reference evapotranspiration (ETo) with the FAO Penman-Monteith method (PM-ETo) requires maximum and minimum air temperature, shortwave radiation, relative air humidity, and wind speed that are often unavailable in many places. The use of reanalysis data, which is common in climate studies, represents an alternative to observation data for the mentioned weather variables when are not available. This study focuses on the use of the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR)reanalysis blended with gridded data sets for computing monthly PM-ETo at 43 synoptic stations distributed across Iran. First, with a set of statistical indicators, the reanalysis weather variables required for computing ETo were compared with observation data, where a good match was obtained for solar radiation, maximum temperature, and minimum temperature. In contrast, at most of the studied stations, the reanalysis wind speed and relative humidity showed large errors when compared with observations. The PM-ETo computed with the blended reanalysis data were also compared with those obtained using observations. The results show that the PM-ETo computed from blended reanalysis compares relatively well with the ETo computedfrom observation at most of the studied stations. However, the spatial pattern of performance indicators reveal extremely poor results for the coastal locations of the Caspian Sea in the north and the Persian Gulf and Oman Sea in the south of Iran. Results suggest that, except for wind speed and relative humidity, the blended reanalysis products are suitable forestimatingETo in inland areas of Iran despitesome degree of overestimationat most of the studied stations.
      PubDate: 2021-03-07
       
  • Temporal and spatial variations of the air temperature in the Taklamakan
           Desert and surrounding areas
    • Abstract: In recent years, climate change has attracted many researchers’ attention around the world, among which the analysis of long-term surface air temperature (SAT) changes is essential. In this paper, we analyze the spatial and temporal variations of the SAT in Tarim Basin from 1961 to 2015. Our results show that warming of the SAT is evident at most weather stations in the Taklamakan Desert, except for those at Aketao, Kuche, and Tazhong. The overall warming rate is 0.25 °C/decade in the Taklamakan Desert. Mann–Kendall tests are adopted to detect abrupt changes in the SATs. It is demonstrated that nine out of 39 stations experienced a simultaneous abrupt change in 1996, which is consistent with the abrupt changes seen in the local vegetation cover. The relationships between the SAT changes and the underlying landscape and vegetation cover are also discussed in this paper. A moderate negative correlation is discovered between the SAT and the normalized difference vegetation index (NDVI) at oases.
      PubDate: 2021-03-06
       
  • A probabilistic Bayesian framework to deal with the uncertainty in
           hydro-climate projection of Zayandeh-Rud River Basin
    • Abstract: Different sources of uncertainty exist in climate change impacts projection. This study aims to propose a framework to deal with the various sources of uncertainties involved in hydro-climate projections of Zayandeh-Rud River Basin with area of 26,917 km2 in Central Iran. The Bayesian model averaging (BMA) was here used through two distinct approaches for weighting the hydrologic outputs (App. I) as well as the global climate models (GCMs) (App. II) based on their abilities to simulate the baseline period. The results showed that different GCMs have different abilities in estimating the hydro-climatic variables and the application of uncertainty analysis is necessary for climate change studies. Application of the BMA can significantly reduce the errors in historical runoff prediction. Although App. I showed a better performance of generating the stream flow time series during the baseline period, the App. II approach has an acceptable ability in different months. The findings of flow duration curves under both approaches revealed that App. II is more appropriate to deal with uncertainty of hydro-climate projection especially in arid and semi-arid regions.
      PubDate: 2021-03-05
       
  • North Atlantic midwinter storm track suppression and the European weather
           response in ERA5 reanalysis
    • Abstract: In this study, we analyse the influence of North Atlantic midwinter storm track suppressions on European synoptic temperature and precipitation anomalies to determine the large-scale conditions relevant for the so-called Christmas thaw. We diagnose this relation in daily ERA5 reanalysis data in the spatial resolution of 0.25∘ between 1979 and 2018. To access synoptic time scales, a 3–10-day band-pass filter is applied. An index for the suppression is defined by the upper tropospheric Eddy Kinetic Energy (EKE) anomalies in the North Atlantic. We define the strong jet stream years as the year exceeding the 75% of the winter seasonal values at 250 hPa. In winters with strong jet activity, the storm track suppression is found, in agreement with the barotropic governor mechanism. Composites of European surface temperature and precipitation for low index values reveal weakly warmer conditions during winter (DJF) in Central Europe and the British Isles and a distinct cooling in Northern Europe. In the 1-month interval during December 15 to January 15, the warming is more pronounced. The clearest signal is the precipitation increase with a magnitude of 1 mm/day in the Mediterranean region.
      PubDate: 2021-03-05
       
  • Analysis of temperature variability and extremes with respect to crop
           threshold temperature for Maharashtra, India
    • Abstract: Temperature is one of the prime factors affecting crop yield and thereby, in changing climate, it is imperative to investigate the co-variability of crop yield and temperature change. Temperature change can manifest itself in multiple factors such as deviation from long-period average, daily scale variability and frequency/intensity of extreme temperature events. To add to the complexity, each of these factors can affect the crop yield differently which necessitates understanding their effect on crop yield individually as well as collectively. Concerning this, we evaluated their distinct and combined impact with respect to threshold temperature of three major crops, i.e. sorghum, sugarcane and millet sown across the Maharashtra State of India. Further, the temperature parameters were conflated using confirmatory factor analysis to formulate a temperature variability index (TVI) that helped in identifying the collective impact of these multiple factors on each crop. Results show that the TVI and sugarcane yield for Nagpur and Bhandara districts of the Vidarbha region exhibited negative co-variability (− 0.30/year), implying the negative impact of temperature change on sugarcane. For sorghum, Wardha and Bhandara of Vidarbha region, Solapur of Pune region and Ratnagiri of Konkan region exhibited negative co-variability with TVI (~− 0.2 to − 0.4/year). Contrary to sugarcane and sorghum, for millets, Akola, Amravati and Chandarpur districts in Vidarbha region; Hingoli, Parbhani, Nanded and Osmanabad in Marathwada region; Satara and Sangli in Pune region; Jalgaon in Nashik region and Ratnagiri; and Sindhudurg in Konkan region exhibited positive co-variability (0.50/year), signifying the favourable temperature conditions for sowing millet. Overall, due to the high exposure of districts to temperature change in Vidarbha and Pune regions, farmers in these districts are advised to refrain from sowing sorghum and sugarcane; instead, farmers can moderate the adverse effects of climate change by sowing millet due to the existence of conducive temperature for millet in Maharashtra. Further, analysis was used to suggest the region and climate-specific cropping pattern for other districts of Maharashtra that can be used by the policy makers to improve the situation of agriculture, farmers and economy of India.
      PubDate: 2021-03-05
       
  • The influence of cloudiness and atmospheric circulation on radiation
           balance and its components
    • Abstract: The article contains an analysis of the influence of cloudiness and atmospheric circulation on the components of radiation balance (Q*) using the example of measurements taken in an extra-urban area of Koniczynka near Toruń (Central Poland) in the years 2011–2018. The average annual value of Q* was 1,818.5 MJ·m−2 with a maximum of 352.3 MJ·m−2 in June, and negative values from November to January (December: −27.4 MJ·m−2). The shortwave radiation balance (S*) amounted to 3,129.2 MJ·m−2 and the longwave radiation balance (L*) was ˗1,310.7 MJ·m−2. In June the average solar irradiance (S↓) at midday was 600 W·m−2. The natural annual and diurnal course of Q* components, determined by astronomical factors, is disturbed by changes in cloudiness and inflow of various air masses. It has been found that an increase in cloudiness causes the amount of incoming solar radiation (S↓) to fall, thus decreasing the S* balance. Moreover, clouds restrict longwave radiation balance (L*), in particular, downward atmospheric radiation (L↓) increases. The opposite relationships of S* and L* affect Q* in individual months. The components of Q* are influenced by atmospheric circulation; it has been observed that anticyclonic types, characterised by smaller cloud amounts, favour a greater influx of (S↓) and—at the same time—greater emittance (L↑); however, Q* is then greater than in the case of cyclonic circulation. A statistically significant trend of Q* and its components has not been ascertained. A notable great year-on-year variability of Q*, ranging from 1,640.4 MJ·m−2 (in 2011) to 2,081.6 MJ·m−2 (in 2018), affects the environment. The changes are related to the cloudiness and the frequency of occurrence of different atmospheric circulation types. The role of snow cover is also important as snow reflects solar radiation which leads to the decrease of S* and—as a result—to a negative value of Q* in winter.
      PubDate: 2021-03-01
       
  • Innovative and polygonal trend analyses applications for rainfall data in
           Vietnam
    • Abstract: It is a known fact that the size, frequency, and spatial variability of hydrometeorological variables will irregularly increase under the impact of climate change. Among the hydrometeorological variables, rainfall is one of the most important. Trend analysis is one of the most effective methods of observing the effects of climate change on rainfall. Recently, new graphical methods have been proposed as an alternative to classical trend analysis methods. Innovative Polygon Trend Analysis (IPTA), which evolved from Innovative Trend Analysis (ITA), is currently one of the proposed methods and it does not contain any assumptions. The aim of this study is to compare IPTA, ITA with the Significance Test and Mann-Kendall (MK) methods. To achieve this, the monthly total rainfall trends of 15 stations in the Vu Gia-Thu Bon River Basin (VGTBRB) of Vietnam have been examined for the period 1979–2016. The analyses show that rainfall tends to increase (decrease) in March (June) at nearly all stations. IPTA and ITA with the Significance Test are more sensitive than MK in determining the trends. While trends were detected in approximately 90% of all months in IPTA and ITA with the Significance Test, this rate was only 23% in the MK test. Although the arithmetic mean graphs in the 1-year hydrometeorological cycle are considerably regular at almost all stations, their standard deviations are relatively irregular. The most critical month for trend transitions between consecutive months for all the stations is October, which has an average trend slope of −1.35 and a trend slope ranging from −3.98 to −0.21, which shows a decreasing trend.
      PubDate: 2021-03-01
       
  • Spatiotemporal trends in reference evapotranspiration and its driving
           factors in Bangladesh
    • Abstract: This research investigates spatiotemporal variations in ETo and the controlling factor of those variations using the modified Mann-Kendall test, empirical Bayesian kriging model, Morlet wavelet analysis (MWA), and cross-wavelet transform (XWT) model relying on daily climate data sets obtained from 18 meteorological stations for the period 1980–2017. Additionally, the stepwise linear regression analysis and partial correlation coefficient (PCC) were employed to determine the variables driving the changes in ETo. The investigation exhibited a decline in annual for −1.19 mm year−1 and seasonal (−0.40 mm decade−1 during pre-monsoon, −0.47 mm decade−1 during post-monsoon, −0.50 mm decade−1 during winter) ETo, which indicates the existence of “evapotranspiration paradox” in Bangladesh, similar to many regions across the globe. The trend test depicted that despite the increase in mean temperature (MT), a noteworthy decrease in sunshine duration (SD), and wind speed (WS) are the main reasons for the reduction in ETo. Spatial analysis of ETo revealed the highest annual values in the southwest while the lowest in the northwest. Two cycles, 1–3 and 3–5 years were found significant in the annual and seasonal ETo. The outcomes revealed coherence among ETo with meteorological factors at different time-frequency bands, which is noteworthy. Stepwise regression and PCC showed that the impact of meteorological factors on ETo varies on the annual and seasonal scales where MT, RH, and SD are the major factors responsible for the variations of ETo in both annual and seasonal scales. These outcomes of the research can be advantageous for designing irrigation and management of sustainable water resources to mitigate climate change impacts as well as controlling anthropogenic activities.
      PubDate: 2021-02-28
       
  • Evaluation of the performance of bias-corrected CORDEX regional climate
           models in reproducing Baro–Akobo basin climate
    • Abstract: The applicability of the regional climate model (RCMs) for catchment hydroclimate is obscured due to their systematic bias. As a result, bias correction has become an essential precondition for the study of climate change. This study aimed to evaluate the skill of seven rainfall and five maximum and minimum temperature RCM outputs against observed data in simulating the characteristics of climate at several locations over the Baro–Akobo basin in Ethiopia. The evaluation was performed based on raw and bias-corrected RCMs against observed for a long-term basis. Several statistical metrics were used to compare RCMs against observed using a pixel-to-point approach. In this finding, raw RCMs showed pronounced biases such as lower correlation and higher PBIAS in estimating rainfall and minimum temperature than maximum temperature. However, most RCMs after bias correction showed better performance in reproducing the magnitude and distribution of the mean monthly rainfall and temperature and improve all the statistical metrics. The Mann–Kendall trend test for observed and bias-corrected RCMs indicated a decreasing annual rainfall trend while the maximum and minimum temperature showed an increasing trend in most stations. In most statistical metrics, the ensemble mean resulted in better agreement with observation than individual models in most stations. In general, after bias correction, the ensemble adequately simulates the Baro–Akobo basin climate and can be used for evaluation of future climate projections in the region.
      PubDate: 2021-02-26
       
  • Jump point identification in hydro-meteorological time series by crossing
           methodology
    • Abstract: The climate change impact appears as a decreasing or increasing monotonic trend in hydro-meteorology time series records due to greenhouse gas (GHG) emissions causing to global warming and climate change impacts. On the other hand, there may be abrupt changes in the form of jumps in these series due to natural and engineering activities. Although trend identification methods are rather common in the literature, jump determination conventional methodologies are rather rare and their applications present some restrictive asumptions like the serial independence and normal (Gaussian) probability distribution function (PDF). The methodology presented in this paper is away from each of such assumptions and it depicts the minimum number of upcrossing along horizontal truncation levels within the time series variation domain. The applications of the methodology are given for annual Danube River discharge records, Romania; New Jersey rainfall and temperature records, USA; monthly rainfall records and Van Lake level fluctuations, Turkey.
      PubDate: 2021-02-26
       
  • Summertime variability of Mediterranean evaporation: competing impacts
           from the mid latitudes teleconnections and the South Asian monsoon
    • Abstract: Interannual variability of Mediterranean evaporation and its links to regional climate during summer are investigated based on evaporation data from the Woods Hole Oceanographic Institution dataset. An EOF (Empirical Orthogonal Function) analysis performed on the monthly means (i.e., separately for June, July, August, and September time series) revealed two leading modes of evaporation variability, characterized by the monopole (EOF-1) and zonal dipole (EOF-2) patterns. These modes explain altogether more than 60% of the total variability of Mediterranean evaporation for each month. In all summer months, the EOF-1 reflects an interdecadal change signal characterized by below normal evaporation in 1970–2000 and above normal evaporation before and after this period. This mode is associated with the Atlantic Multidecadal Oscillation. The EOF-2 pattern reflects interannual variations of Mediterranean evaporation that differ significantly from month to month. The reason for this difference is the changing roles of regional teleconnections, such as the summer North Atlantic Oscillation (SNAO), the Scandinavian and East Atlantic teleconnections, and the Asian monsoon. The impacts of these teleconnections on Mediterranean evaporation are highly variable both in space and time. The largest impact of the SNAO on Mediterranean evaporation is detected in early summer, but its impact weakens and disappears towards the end of the summer season. An opposite tendency is obtained with the Asian monsoon, having the strongest impact on evaporation in late summer. The study suggests that these teleconnections impact Mediterranean evaporation mostly through atmospheric dynamics (the SNAO) and thermodynamics (the Asian monsoon) in early and late summer respectively.
      PubDate: 2021-02-26
       
  • On the cause-and-effect relations between aerosols, water vapor, and
           clouds over East Asia
    • Abstract: Atmosphere is a complex dynamical system. Here, we investigated the causal links between aerosols, water vapor, and clouds, using the convergent cross mapping (CCM) method, which is based on nonlinear state space reconstruction. We utilized remote sensing data of aerosol optical depth at 550 nm (AOD), water vapor (WV), cloud cover (CC), cloud optical depth (COD), cloud effective radius-ice (CERI), and cloud effective radius-liquid (CERL) from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor over East Asia, for the period 2003–2018. Our analysis shows that there is a bidirectional forcing between AOD, CC, and COD which could be attributed to the invigoration effect of aerosols on clouds. In addition, there is a bidirectional forcing between AOD and WV and AOD and CERL, which could be attributed to the first indirect effect of aerosols on clouds, while there is no causality among AOD and CERI, probably because of strong coupling among aerosols and ice nuclei. Based on our analysis, we conclude that CCM method can effectively be used in all aerosol–cloud interactions’ studies, searching for causality among the parameters.
      PubDate: 2021-02-24
       
  • Evaluation of three approaches to probable maximum precipitation
           estimation: a study on two Indian river basins
    • Abstract: Estimates of probable maximum precipitation (PMP) and corresponding probable maximum flood (PMF) are necessary for planning, design, and risk assessment of flood control structures whose failure could have catastrophic consequences. For PMP estimation, multifractal approach (MA) is deemed to be better than conventional approaches, which are based either on statistical concepts or physical aspects. The MA yields physically meaningful PMP estimates by attempting to capture scale-invariant multiplicative cascade mechanism inherent in rainfall. This paper attempts to gain insights into the performance of MA by comparing PMP estimates obtained using the approach with those resulting from the use of two widely used empirical approaches (storm maximization approach (SMA) and Hershfield method (HM)) on two flood-prone river basins (Mahanadi and Godavari) in India. The results indicate that rainfall data of the two river basins exhibit multifractal properties, and the use of MA has an advantage over HM and SMA in estimating PMP corresponding to longer durations (>3 days). PMP estimates obtained using HM are generally lower (higher) than those obtained using SMA for 1-day (higher) duration. PMP maps are prepared for the two Indian river basins corresponding to 1-day to 5-day durations. Further, PMP estimates obtained based on the PMP maps are provided for 18 catchments in the Mahanadi basin and 53 catchments in the Godavari river basin.
      PubDate: 2021-02-24
       
 
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