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  Subjects -> METEOROLOGY (Total: 112 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 199)
Nature Climate Change     Full-text available via subscription   (Followers: 134)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 81)
Atmospheric Environment     Hybrid Journal   (Followers: 73)
Atmospheric Research     Hybrid Journal   (Followers: 69)
Climatic Change     Open Access   (Followers: 66)
Journal of Climate     Hybrid Journal   (Followers: 54)
Bulletin of the American Meteorological Society     Open Access   (Followers: 51)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 48)
Climate Policy     Hybrid Journal   (Followers: 45)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 43)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 37)
Atmospheric Science Letters     Open Access   (Followers: 36)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 35)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 34)
Monthly Weather Review     Hybrid Journal   (Followers: 34)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
American Journal of Climate Change     Open Access   (Followers: 31)
Advances in Climate Change Research     Open Access   (Followers: 31)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 31)
Journal of Hydrology and Meteorology     Open Access   (Followers: 29)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 28)
Weather and Forecasting     Hybrid Journal   (Followers: 28)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 27)
Journal of Space Weather and Space Climate     Open Access   (Followers: 27)
Climate Change Economics     Hybrid Journal   (Followers: 26)
Atmosphere     Open Access   (Followers: 26)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 26)
Space Weather     Full-text available via subscription   (Followers: 25)
Advances in Meteorology     Open Access   (Followers: 24)
Energy & Environment     Hybrid Journal   (Followers: 24)
International Journal of Atmospheric Sciences     Open Access   (Followers: 22)
Tellus A     Open Access   (Followers: 22)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 22)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 21)
Tellus B     Open Access   (Followers: 21)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weather     Hybrid Journal   (Followers: 19)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 18)
Global Meteorology     Open Access   (Followers: 17)
Weather and Climate Extremes     Open Access   (Followers: 16)
Climate Resilience and Sustainability     Open Access   (Followers: 15)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 15)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 14)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Climate Change Responses     Open Access   (Followers: 12)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 8)
Current Climate Change Reports     Hybrid Journal   (Followers: 8)
Climate Change Research Letters     Open Access   (Followers: 7)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 7)
Climate     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 6)
Climate Risk Management     Open Access   (Followers: 6)
Mathematics of Climate and Weather Forecasting     Open Access   (Followers: 6)
Aeolian Research     Hybrid Journal   (Followers: 6)
Climate Research     Hybrid Journal   (Followers: 6)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 5)
The Cryosphere (TC)     Open Access   (Followers: 5)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
International Journal of Environment and Climate Change     Open Access   (Followers: 5)
Climate of the Past (CP)     Open Access   (Followers: 5)
Urban Climate     Hybrid Journal   (Followers: 4)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Climate and Energy     Full-text available via subscription   (Followers: 4)
The Cryosphere Discussions (TCD)     Open Access   (Followers: 4)
Carbon Balance and Management     Open Access   (Followers: 4)
Weatherwise     Hybrid Journal   (Followers: 4)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Atmospheric Environment : X     Open Access   (Followers: 3)
Journal of Climate Change     Full-text available via subscription   (Followers: 3)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 3)
Frontiers in Climate     Open Access   (Followers: 3)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Journal of Climatology     Open Access   (Followers: 3)
Atmósfera     Open Access   (Followers: 3)
Climate Services     Open Access   (Followers: 3)
Open Atmospheric Science Journal     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Meteorological Monographs     Hybrid Journal   (Followers: 2)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 1)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Mediterranean Marine Science     Open Access   (Followers: 1)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Weather and Climate Dynamics     Open Access  
Journal of Agricultural Meteorology     Open Access  
Nīvār     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Climate of the Past Discussions (CPD)     Open Access  
Revista Brasileira de Meteorologia     Open Access  
Studia Geophysica et Geodaetica     Hybrid Journal  

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Similar Journals
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  [2657 journals]
  • An investigation of the short-term meteorological drought variability over
           Asir Region of Saudi Arabia
    • Abstract: Changes in precipitation as a result of climate change are becoming a widespread issue all around the world. A lack of rainfall causes a meteorological drought. The short-term Standardized Precipitation Index (SPI-6) index was used to estimate meteorological drought conditions in Saudi Arabia's Asir region from 1970 to 2017. Innovative trend analysis (ITA), the Modified Mann–Kendall test (MMK), the Sequential Mann–Kendall test, and Morlet wavelet transformation were used to detect trend and periodicity in meteorological drought conditions in the Asir region. In addition, the meteorological drought conditions were forecasted by integrating Particle Swarm Optimization (PSO) ensemble machine learning algorithm and an artificial neural network (ANN). Droughts of varying severity have become more frequent in Asir, according to the findings. In most stations, ITA and MMK tests have revealed a significant increase in drought. In all stations, the SQMK test revealed a big sudden year-over-year drought trend. With the exception of one station, all stations experienced extreme drought frequency discovered using Morlet Wavelet Transformation over a long period of time (10 years or more) (station 34). The PSO-ANN hybrid learning algorithm predicted SPI-6 values that had a strong correlation with actual SPI-6 values and also had lower error values, indicating that this model performed well. The PSO-ANN model predicts that the Asir region of Saudi Arabia will experience major moderate to extreme drought events in the coming years (2018–2025). The findings of this analysis will assist planners and policymakers in planning for the acquisition of sustainable agriculture in the study area.
      PubDate: 2021-05-13
       
  • The impact of land use and land cover change on regional climate over East
           Asia during 1980–2010 using a coupled model
    • Abstract: The land use and land cover change (LULCC) presents the large-area features since the 1980s in East Asia, particularly over China, where the largely complicated LULCC has happened for the simultaneous interconversion of croplands, forests, grasslands, and urban lands. In this study, the regional coupled model AVIM-RIEMS2.0 with dynamic vegetation process is employed to examine the impacts of LULCC on regional climate over East Asia. The results show that regional climate and terrestrial surface processes exhibit significantly seasonal and interdecadal signals in East Asia. With the influences of LULCC, forest increased 33.3% and 20.3% from the 1980s to 1990s and from the 1990s to 2000s, respectively. Meanwhile, cropland decreased 17.8% in the 1990s (compared to the 1980s) and 24.8% in the 2000s (compared to the 1990s), respectively. These transitions of land surface processes are roughly coincident with the interdecadal variations in temperature and precipitation, which trigger generally opposite changes in the 1980s as compared to the 1990s, especially over eastern China. The seasonal variability of climatic components is more evident in winter than summer, except for the precipitation. The climate change is also somewhat remarkable under the non-LULCC conditions, combined with the changes in wind fields at the 850 hPa from the simulations during three decades; they together suggest that climate change is also modulated by other controlling factors, such as East Asian monsoon circulations in addition to LULCC conversions. These results highlight the importance of LULCC in regional modeling studies, which would have practical significance in climate mitigation and adaptation over East Asia.
      PubDate: 2021-05-12
       
  • Intercomparison of the impact of INSAT-3D atmospheric motion vectors in
           3DVAR and hybrid ensemble-3DVAR data assimilation systems during Indian
           summer monsoon
    • Abstract: The impact of observations in a data assimilation (DA) may depend on various factors, and one aspect that can affect the impact is the specification of the background error covariance matrix. The present study compares the impact of INSAT-3D atmospheric motion vector (AMV) observations in traditional three-dimensional variational (3DVAR) DA system and hybrid ensemble transform Kalman filter (ETKF)-3DVAR DA system (HYBRID) available in Weather Research and Forecast (WRF) modeling system. The objective of the study is to understand how the impact of INSAT-3D AMV observations differ when assimilated using 3DVAR and HYBRID DA systems. The DA experiments are conducted over a ~4-week period of Indian summer monsoon rainfall of July 2016. Four sets of experiments are performed with and without INSAT-3D AMV in both the DA systems. The domain-wide verification with respect to radiosonde observations reveals that forecasts in HYBRID experiments are more accurate than 3DVAR experiments, in general. Geographical distribution depicts the positive impacts of INSAT-3D AMV observations across the domain in both 3DVAR and HYBRID DA systems. The AMV observations show a larger relative impact in HYBRID than in 3DVAR. The relative improvement in HYBRID with AMV DA compared to 3DVAR is 77% and 71% for wind and tropical temperature. The skill scores for quantitative evaluation of precipitation forecast indicate a modest improvement in rainfall for HYBRID run, and incorporating the AMV observation does not considerably enhance the skill of 24-h and 48-h rainfall forecast.
      PubDate: 2021-05-12
       
  • Projected changes in the climate of Pakistan using IPCC AR5-based climate
           models
    • Abstract: Using an ensemble of 22 climate models from the 5th Annual Report of Intergovernmental Panel on Climate Change (IPCC AR5), the projected robustness and variability of temperature and precipitation for the data-sparse region of Pakistan is studied both on seasonal and annual time scales for the 21st century. The winter season in Pakistan is displaying ensemble-based spatially robust and progressively more relative warming in temperature under representative concentration pathway (RCP) 8.5 scenario as compared to RCP 4.5 scenario, both in the middle (2035−2064) and end (2070−2099) of 21st century projection periods. On the other hand, the ensemble-based relative changes in precipitation during the aforementioned two projected periods are spatially less robust. Most of the atmosphere–ocean general circulation models (AOGCMs) project a relative increase of 5−10% in annual precipitation in all the regions of Pakistan. On a seasonal time scale, most AOGCMs project a relative precipitation decrease (increase) during winter (summer) in central and in southern (central and northern) Pakistan. All the AOGCMs under both RCPs project an increase in temperature in all Pakistan, northern Pakistan, and southern Pakistan on annual, winter, and summer time scales.
      PubDate: 2021-05-12
       
  • An assessment of climate change impact on air masses arriving in Athens,
           Greece
    • Abstract: Climate change is inherently linked to long-term non-stationary changes in the characteristics and frequency of weather patterns. The present study attempts to identify the statistical changes of weather patterns in Athens Greece, from the comparative assessment of 96-h backward trajectories between historic (1980–2009) and future (2020–2049) climatology derived from the IPCC RCP4.5 and RCP8.5 scenarios. Arrival heights at 750 m, 1500 m, and 3000 m above sea level are considered to account for the impact of the planetary boundary layer and the lower free troposphere. The analysis of the historic period yields 7 dominant patterns for all heights determined independently, with similar spatial characteristics but varying frequency of occurrence. The classification of backward trajectories under future climate using the same historic clusters reveals percentage changes from locally short-distance travelling patterns to longer-distance ones with a predominant northbound direction. As a second experiment, backward trajectories are re-clustered independently reaching again the same type of clusters but with observable changes in the cluster origins and trajectory lengths.
      PubDate: 2021-05-11
       
  • A new view on the trend of solar radiation in mainland China — based on
           the optimized empirical model
    • Abstract: As a kind of renewable energy, the development and utilization of solar energy are valued by many countries. To accurately provide a basis for the use of solar energy in mainland China, the optimized empirical model is adopted to analyze the variation trends and spatial patterns in solar radiation (SR) during 1961–2016 based on the data of 31 SR sites and 500 sunshine duration (SD) stations. The results indicate that there are obvious discrepancies in the variation trends of annual SR and SD during 1961–2016, with trend conversion occurring in 1992 (SR) and 1980 (SD), respectively. Overall, annual SR decreases at the rate of −3.68 MJ/m2·a in China. Notably, SR declines at the rate of −16.95 MJ/m2·a during 1961–1989 (“dimming” stage), while it increases at the rate of 5.34 MJ/m2·a for 1990–2016 (“brightening” period). In addition, all seasons show a tendency of dimming first and then brightening except for autumn. Compared with SD, SR is more sensitive to changes in pollution, leading to a marked recovery with the reduction of pollution after the 1990s. This study provides a new perspective for the trend difference between SR and SD after the 1990s.
      PubDate: 2021-05-11
       
  • Climate change impact on the initial development of tropical forest
           species: a multi-model assessment
    • Abstract: Air temperature is a key variable in the development of tropical forest species, and the increasing temperature projected to occur over the twenty-first century can bring additional threats to the development of these species, particularly during the initial development. The aim of this study was to evaluate the impact of air temperature increase in the initial development of three tropical forest species in the seedling stage: Psidium guajava L., Citharexylum myrianthum Cham., and Bixa orellana L. We used the Phyllochron and Wang and Engel development models, both set for current (1980–2005) and projected for future (2021–2050 and 2071–2100) climate conditions, in two scenarios of radiative forcing (RCP 4.5 and 8.5) and considering twelve development simulation planting dates. We used 10 Earth Systems Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The projections indicated that the increases in air temperature (~ 1.4 to ~ 3.9 °C) can be sufficient to change the development rates of the three species. The simulations carried out from March to June may have the early development accelerated and the seedling stage reduced. Differently, the simulations from September to December may slow down the development and increase the seedling stage duration, mainly for Citharexylum myrianthum, the most sensitive to air temperature increase. We conclude that while changing the planting date is a feasible adaptation measure against the threats of climate change, shading and irrigation may reduce the quality of seedlings. Outlining appropriate, timely, and cost-effective adaptation measures is critical for the sustainability of the Brazilian nursery sector.
      PubDate: 2021-05-11
       
  • Role of cloud radiative feedback in the Madden–Julian oscillation
           dynamics: a trio-interaction model analysis
    • Abstract: The authors expand the original wave dynamic-moisture (WM) model by implementing the cloud radiative feedback (CRF) to study the role of the CRF in the Madden–Julian oscillation (MJO) in comparison with the role of the planetary boundary layer (PBL) process. The linear instability analysis is used to elucidate the reactions of the WM mode, WM-CRF mode, WM-PBL mode, and WM-PBL-CRF mode. Compared with the stationary and damped WM mode, the CRF can present an important instability source for all wavenumbers without the planetary-scale selection and tends to slow down the planetary-scale eastward propagation. On the other hand, the PBL process, with the planetary-scale selection, can destabilize the eastward propagation while accelerate the eastward propagation of the planetary-scale oscillation. When the PBL and the CRF processes are both included, the unstable mode is achieved and period is nearly 20–90 days, consistent with the observations. Both the WM and the WM-CRF modes present unrealistic coupled Kelvin–Rossby wave structure, which disagrees with the observations. These caveats can be remitted in the WM-PBL mode and the WM-PBL-CRF mode. The PBL can couple the Kelvin and Rossby waves and present the observed geopotential low in front of the convective center. The CRF, however, can make the phase relation between the precipitation anomalies and pressure anomalies changed in the presence of PBL process.
      PubDate: 2021-05-10
       
  • Assessing the impact of climate change on urban water demand and related
           uncertainties: a case study of Neyshabur, Iran
    • Abstract: This study represents a new strategy for assessing how climate change has impacted urban water demand per capita in Neyshabur, Iran. Future rainfall depths and temperature variations are projected using several general circulation models (GCMs) for two representative concentration pathway (RCP) (i.e., RCP45 and RCP85) scenarios using LARS-WG software. A simulator model is developed using the genetic programming (GP) model to predict future water demand based on projected climate variables of rainfall depth and maximum temperature. The period of 1996–2016 is selected as the base period. Three future periods, namely the near-future (2021–2040), middle future (2041–2060), and far future (2061–2080), are also employed to assess climate change impact on water demand. Results indicate significant increases in annual projected rainfall depth (14~53%), maximum temperature (0.04~4.21 °C), and minimum temperature (1.01~4.71 °C). The projected monthly patterns of rainfall depth and temperature are predicted to cause a 1-month shift in the water demand peak (i.e., it will occur in April instead of May) for all future periods. Furthermore, the annual water demand per capita is projected to increase by 0.5~1.2%, 1.5~3.2%, and (2.2~7.1%), during the near-, middle-, and far-future periods, respectively. The uncertainty associated with water demand is also projected to increase over time for RCP45. The mathematical expression of urban water demand based on climatic variables is vital to managing the water resources of Neyshabur. The methodology proposed in the present study represents a robust approach to assessing how climate change might affect urban water demand in cities other than Neyshabur and provides crucial information for decision-makers.
      PubDate: 2021-05-10
       
  • Influence of the urban spatial layout of central Beijing on the
           atmospheric humidity field
    • Abstract: Based on the meteorological data (2009–2018) acquired by high-density automatic meteorological stations in the central urban area (CUA) of Beijing, this study adopted an urban-rural ratio method to construct a qr to quantify the impact of urbanization on the spatial and temporal distribution of specific humidity (q). And the urban morphological parameters such as building height (BH), building density (BD), floor area ratio (FAR), sky view factor (SVF), and land surface parameters including vegetation coverage (VC) and impervious coverage (IC) with 500-m spatial resolution in CUA were calculated, and furthermore, the relationships between the six spatial layout parameters and another indicator, urban heat island (UHI) intensity, and qr were studied. The results show that q of CUA is 81~114% of that of the suburbs, and the urban dry island (UDI) effect and urban wet island (UWI) effect coexist throughout the year. The maximum UDI occurs during autumn daytime and the maximum UWI appears at night in winter. The UDI effect is prone to occur in areas with VC < 11%, IC >85%, BH > 15 m, and BD > 24%, while the UWI effect is more likely to appear in areas with VC > 35% and FAR < 0.3. The contributions of the six urbanization parameters to the spatial change of qr in different time periods are 6.2 to 33.5%, and VC is the largest (33.5%), followed by BD (31.9%) and SVF (29.9%), and the main factor affecting the annual average qr is BD with the contribution of 18.9%. Compared with the urbanization parameters, the UHI is more important and the contribution to the change of q can be up to 35.7%. The results show that these spatial layout parameters are not sufficient to explain the main change in q, and more other parameters need to be considered.
      PubDate: 2021-05-08
       
  • First and last frost date determinations based on meteorological
           observations in Japan: trend analysis and estimation scheme construction
    • Abstract: We investigated the first and last frost dates using meteorological observation data from Japan. First, we identified long-term trends of retardation (mean: +0.224 day/year) in the first frost date in fall and advancement (−0.228 day/year) in the last frost date in spring using historical frost observation data from 1951 to 2010. Trends determined over 20-year subperiods were distinct from long-term trends and were sensitive to decadal changes in daily minimum air temperature. Second, we proposed a scheme to infer the first and last frost dates from the time series of daily minimum air temperature. After optimization, the first (last) cold date when the daily minimum temperature fell below a temperature criterion of ca. 2 °C yielded the best estimate of the first (last) frost date with an error of 2 days in most cases. However, the overall root mean square errors were 13–16 days because some cases with significant misfits deteriorated the values. Both wind speed and humidity shifted the criterion. Sites with strong winds contributed to a decrease in the temperature criterion. Because this scheme only requires the daily minimum air temperature, it is widely applicable to the quantitative evaluation of the first and last frost dates from given meteorological or climate projection data.
      PubDate: 2021-05-06
       
  • Does increasing the spatial resolution in dynamical downscaling impact
           climate change projection of Indian summer monsoon, population and
           GDP'
    • Abstract: High-resolution regional climate model (RCM) simulations are found to be very useful in deriving realistic climate change projection information. This study uses high-resolution dynamical downscaling framework (CCSM4-WRF) for India. To delineate the advantage of high resolution, we compared the results of 9-km resolution CCSM4-WRF simulations against the 50-km resolution RCM simulations under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) program. Quantitative estimations show that majority of CORDEX-SA models exhibit large dry bias (< − 4 mm/day) and low pattern correlation coefficient (PCC) over the Western Ghats (WG). Mean climatology of Indian summer monsoon (ISM) rainfall simulated by high-resolution CCSM4-WRF outperforms the CORDEX-SA RCMs with low negative biases (~ 1 mm/day) and high PCC (≥ 0.755). This skill of CCSM4-WRF provides better confidence in its future projection at local scale. CCSM4-WRF projects future intensification of monsoon rainfall over most parts of India and reduction over southern WG, which is consistent with recent observed trends, but none of the CORDEX-SA RCMs could simulate this rainfall reduction. For all-India rainfall, ensemble mean of CORDEX-SA models projects an increase by 1.3 ± 0.9 mm/day and CCSM4-WRF projects 0.67 mm/day. Projected changes in socioeconomic variables such as population and gross domestic product (GDP) exhibit future enhancement over most parts of India but with spatial heterogeneity. Shared socioeconomic pathways scenarios show pronounced future population growth over Indian coastal areas and large enhancement in productivity over urban areas. Therefore, climate change projection information of ISM rainfall, together with enhanced future population and GDP, is useful for taking necessary steps for adaptation and mitigation in a sustainable manner.
      PubDate: 2021-05-06
       
  • Vertical structure of Tibetan Plateau Vortex in boreal summer
    • Abstract: The Tibetan Plateau vortex (TPV) is a major rain-producing system over the Tibetan Plateau (TP) in summer. The vertical structure of TPV is critical in understanding the generation and development of TPV. In this paper, the ERA-Interim reanalysis data and an objective TPV detection and vertical tracing method are used to investigate the vertical structure of TPV in boreal summer (June–August). Most TPVs are shallow, with only 1/5 of them can reach 400 hPa. Among the TPVs that move off the TP, more than half are deep vortices. The tilting direction of TPV is related to its baroclinic structure. In general, TPVs tilt to the direction of the cold air from low to high isobaric levels, and the tilting direction depends on the relative positions of the warm pool and the cold air intruding into TPV. Deep TPVs inside the TP and those moving off the TP have different vertical structures. On the plateau, TPVs have convergence at the low levels (400–500 hPa) and divergence at the high levels (above 400 hPa), which can cause updrafts in the vortex and a tropical cyclone-like structure. For the TPVs moving off the TP, the updrafts are significantly weak due to the relatively low low-level convergence and the relatively low high-level divergence. These TPVs almost have positive vertical vorticity and present an extratropical cyclone-like structure. The vertical thickness of TPV is important in determining whether the TPV could move off the TP. The results show that the deep TPVs are more likely to move out than the shallow ones. Therefore, the vertical structure is a better predictor on the movement of TPV than its other properties.
      PubDate: 2021-05-06
       
  • Correction to: Delineation of potential hot spots of aeolian dust using
           normalized difference water index
    • Abstract: A Correction to this paper has been published: https://doi.org/10.1007/s00704-021-03634-9
      PubDate: 2021-05-05
       
  • Evaluation of gridded meteorological datasets and their potential
           hydrological application to a humid area with scarce data for Pirapama
           River basin, northeastern Brazil
    • Abstract: This work evaluated the simulation of streamflow using observed and estimated gridded meteorological datasets and the Soil and Water Assessment Tool (SWAT) model for a humid area with scarce data in northeastern Brazil. The coefficient of determination (R2), Nash-Sutcliffe efficiency (NS), root mean square error (RMSE), normalized root mean square error (NRMSE), and percent bias (PBIAS) were used to assess the SWAT results yielded by estimated and observed rainfall data. The hydrological modeling data from three streamflow stations were used (2000 to 2006 for calibration and 2007 to 2010 for validation). The results show that at daily scale, the estimated rainfall data show a poor agreement (R2 ranging from 0.22 to 0.04) with the observed rainfall but good agreement at monthly (R2 = 0.85) and annual scales (R2 = 0.80). The results showed that estimated accumulated precipitation overestimated the observed data. The results showed that R2 ranged from 0.51 to 0.55 at monthly scale and 0.44-0.52 at annual scale. However, the global data can represent well the variability of rainfall within the region. The results indicated a good correlation in the seasonal variability (R2 ranged from 0.72 to 0.60). The modeling results using monthly TRMM data and observed rainfall data showed good values of NS and R2 during calibration and validation, but PBIAS was unsatisfactory for the three streamflow gauges. The streamflow estimates from the SWAT model using data from the TRMM satellite showed that such data are capable of generating satisfactory results after calibration, although measured rainfall data presented better results; the data could support areas with scarce rainfall data and be applied to other river basins, for example, to analyze the hydrological potential of other basins in the coastal region of northeastern Brazil. Over the past three decades, considerable advances have been made in remote sensing with environmental satellites, increasing the amount of information available, including rainfall estimates. In this context, the use of TRMM data to estimate rainfall has ultimately been shown to be an interesting alternative for areas with scarce rainfall data. Graphical abstract
      PubDate: 2021-05-05
       
  • Evaluating spatial patterns of Asian meteorological drought variations and
           associated SST anomalies in CMIP6 models
    • Abstract: This study evaluates the spatial patterns of the Asian summer drought variations and the associated sea surface temperature (SST) anomalies in 42 Coupled Model Intercomparison Project (CMIP6) models during 1950–2014. The analysis is focused on the meteorological drought measured using the standardized precipitation index (SPI). The evaluation is conducted for short-term, medium-term, and long-term droughts represented by 3-month, 9-month, and 24-month SPI, respectively. Most of the 42 models are able to capture the observed leading spatial pattern of short-term and medium-term drought variations, characterized by a north-south dipole structure. In contrast, most models fail to simulate the observed leading spatial pattern of long-term drought variations, featuring a southwest-northeast oriented tripole distribution. Further analysis shows that most models can represent the spatial pattern of interannual variation of long-term drought with a north-south dipole structure, but cannot produce the spatial pattern of interdecadal variation and trend of long-term drought. In most of the models, the dipole pattern of short-term and medium-term drought variations is associated with an El Niño–type SST anomaly pattern in the tropical Indo-Pacific region, which is similar to the observations, so is the dipole pattern of interannual variation of long-term droughts. This is attributed to the ability of most models to capture the tropica Indo-Pacific SST-related large-scale atmospheric circulation anomaly pattern.
      PubDate: 2021-05-04
       
  • Recent trends in precipitation over the Myanmar Coast during onset and
           withdrawal phases of monsoon season
    • Abstract: Monsoon precipitation is the major driver of agricultural productivity in the Myanmar Coast; it is crucial to quantify and understand recent changes in precipitation during the monsoon season over this region. By using multiple precipitation datasets, we demonstrate that total precipitation during monsoon season over the Myanmar Coast has increased slightly but not significantly, but precipitation during the onset and withdrawal phases of monsoon season exhibit a significant increasing trend during 1979–2015, and the contribution of precipitation during the two phases to total monsoon precipitation has increased significantly. The increased precipitation during the onset phase over the Myanmar Coast directly results from the earlier onset of the South Asian Summer Monsoon in recent decades, which is associated with the phase transition of the Interdecadal Pacific Oscillation in the late 1990s. And the precipitation increase during the withdrawal phase is directly due to the enhances of the ascending motion and convection around this region, which is dynamically correlated to the anomalous cyclone-like circulation around the Bay of Bengal as well as the strengthening of the cross-equatorial flow around the equatorial Indian Ocean.
      PubDate: 2021-05-04
       
  • CMIP5 model performance of significant wave heights over the Indian Ocean
           using COWCLIP datasets
    • Abstract: Wind-generated surface gravity waves forms an integral part in modulating the air-sea exchange processes. Information of wave parameters is also very essential in planning marine- and coastal-related activities. It is now well recognized that wind-wave activity shows changing trends over the global ocean basins. Numerous studies have addressed the projected changes in significant wave height for the Indian Ocean (IO) region, and there is a need to conduct thorough performance evaluation of global climate models (GCMs) over this region for futuristic planning. With this motivation, the present study examined the performance of historical dynamical wave climate simulations generated under the Coordinated Ocean Wave Climate Projections (COWCLIP) experiment. The simulations utilized near-surface wind speed datasets from 8 CMIP5 (Fifth phase of Coupled Model Intercomparison Project) GCMs to force a spectral wave model. The skill level of individual GCM forced wave simulations and multi-model mean (MMM) in reproducing the significant wave height (SWH) over four different sub-domains in the IO was evaluated with reference to the ECMWF Reanalysis 5th Generation (ERA5) datasets. Several performance metrics such as the Taylor Skill, M-Score, Model Climate Performance Index (MCPI), and Model Variability Index (MVI) are employed to establish the skill level of model simulations. The study deciphers that model performance is highly reliant on the region and its characteristics. Representation of the historical wave climate over the Arabian Sea (AS) and the Bay of Bengal (BoB) regions is remarkable in the COWCLIP datasets. However, there are discrepancies noticed in SWH distribution over the South Indian Ocean (SIO) attributed to model limitations in adequately reproducing swell wave fields over that region. The MMM constructed using the best-performing models (MRI-CGCM3, ACCESS1.0, INMCM4, HadGEM2-ES, and BCC-CSM1.1) is found consistent at all the sub-domains. The study signifies that the performance evaluation of GCM forced wave simulations is crucial before employing them for practical applications. Best-performing models listed from this study can be used to establish futuristic scenarios of SWH in a changing climate for the IO region.
      PubDate: 2021-05-04
       
  • On the role of a coupled vegetation-runoff system in simulating the
           tropical African climate: a regional climate model sensitivity study
    • Abstract: The role of vegetation-runoff system—in simulating the tropical African climate—was examined by analysing two 13-year simulations with two runoff schemes of the community land model version 4.5 (CLM45): the default one is TOPMODEL (TOP) and the other one is the Variable Infiltration Capacity (VIC) using a regional climate model (RegCM4-CLM45). In both simulations, the carbon-nitrogen (CN) module was activated. The first simulation was referred to as CN-TOP, while the second one was designated as CN-VIC. Overall, the results showed that the CN-VIC severely decreases the leaf area index (LAI), vegetation transpiration and soil evaporation relative to the CN-TOP. Eventually, it severely underestimates the total evapotranspiration but overestimates the sensible heat flux in comparison with the reanalysis product; meanwhile the CN-TOP opposes this effect. As a result, the CN-TOP shows a strong cold bias, and the CN-VIC shows a slightly warm bias in comparison with the observation. Moreover, enabling the interactive vegetation module leads to intensifying the dry bias of the total surface precipitation in both simulations with respect to the static vegetation case against the reanalysis product; however the CN-VIC still outperforms the CN-TOP in comparison with the observations. In conclusion, the coupled vegetation-runoff system has a strong influence on the tropical African climate relative to the static case, and calibrating the four parameters of the VIC surface dataset ensures a better and more reliable performance of the coupled RegCM4-CLM45-CN-VIC model for simulating the tropical African climate.
      PubDate: 2021-05-03
       
  • Impact of climate change on the staple food crops yield in Ethiopia:
           implications for food security
    • Abstract: Climate change is likely to make matters worse in Ethiopia, where the primary sources of food production depend on agriculture, mainly rain-fed agriculture. This study has two folds: first, we estimate the marginal impact of climate variables on the dominant staple food crops (teff, maize, wheat, and sorghum) grown in Ethiopia using feasible generalized least square (FGLS) and autocorrelation and heteroscedasticity consistent standard error for 31 years’ time series data. Second, based on these estimates, we used regional climate models (UQAM _CRCM5 and SMHI_ RCA4) to identify yield sensitivity change in the future. A significant rise in mean monthly temperature and positive change in rainfall were observed from 1988 to 2018. Though an increase in maximum temperature had a favorable effect on all crop yields, a similar increase in minimum temperature was found to have an adverse impact. Since 2000 there has been a considerable increase in total production, but the increasing trends have been due to increases in area cultivated. Towards the end of the twenty-first century, the projection of climate impacts has suggested that with significant increases in temperature and decreases in rainfall result the decline of sorghum yield by 18.1% and wheat yield by 13.2%. However, the yield of teff and maize will be expected to increase by 20.2 and 17.9% respectively. We recommend adopting and expanding locally fitted climate-smart agricultural practices to minimize the long-run climate change impacts on crop production and address the country’s food security problems sustainably.
      PubDate: 2021-05-03
       
 
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