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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: 31)
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: 31)
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: 4)
Climate Change Economics     Hybrid Journal   (Followers: 25)
Climate Change Research Letters     Open Access   (Followers: 7)
Climate Change Responses     Open Access   (Followers: 12)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Climate of the Past (CP)     Open Access   (Followers: 5)
Climate of the Past Discussions (CPD)     Open Access  
Climate Policy     Hybrid Journal   (Followers: 44)
Climate Research     Hybrid Journal   (Followers: 6)
Climate Resilience and Sustainability     Open Access   (Followers: 13)
Climate Risk Management     Open Access   (Followers: 6)
Climate Services     Open Access   (Followers: 3)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
Climatic Change     Open Access   (Followers: 66)
Current Climate Change Reports     Hybrid Journal   (Followers: 8)
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: 8)
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: 22)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 22)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
International Journal of Environment and Climate Change     Open Access   (Followers: 5)
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: 3)
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: 81)
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: 134)
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  [2656 journals]
  • 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
       
  • Correction to: An optimum initial manifold for improved skill and lead in
           long-range forecasting of monsoon variability
    • Abstract: A Correction to this paper has been published: https://doi.org/10.1007/s00704-021-03608-x
      PubDate: 2021-05-01
       
  • Development of a new ENSO index to assess the effects of ENSO on
           temperature over southern Vietnam
    • Abstract: The aim of this study was to assess the effects of El Niño and the Southern Oscillation (ENSO) on the temperature in southern Vietnam (TSV) and to establish a new ENSO index for the study area (named southern Vietnam Enso Index, VEI). Data used in this study included TSV, sea surface temperature (SST) in Niño regions, sea level pressure (SLP) at Tahiti and Darwin, and ENSO indices. The results showed that, among all ENSO indices, the oceanic Niño Index (ONI) and Japan Meteorological Agency ENSO index (JEI) gave a better correlation with TSV, but their correlation coefficients (R) were relatively low. That may suggest that these indices could be used with low efficiency for climate monitoring and prediction. The VEI was built based on the pair of SST in Niño 3.4 and Niño.West, which gained a higher correlation coefficient with the temperature in southern Vietnam in comparison with other ENSO indices. The lag time between VEI and TSV was about 5 months, which was one month longer than the one between ONI and TSV. Moreover, analyzing the temperature difference between the warm and cold phases also indicated that using VEI led to a higher contrast than using ONI. In brief, the newly established VEI could be more suitable for the study area.
      PubDate: 2021-05-01
       
  • Projection of apparent temperature using statistical downscaling approach
           in the Pearl River Delta
    • Abstract: In this study, a stepwise-clustered statistical downscaling model is established to simulate future apparent temperatures based on NCEP reanalysis data and four global climate models (GCMs). AP is a metric used to quantify thermal comfort or discomfort. The model can express nonlinear relationships between variables at large scale and local scale. The model is employed for projecting future apparent temperature changes over the Pearl River Delta (PRD), on the south coast of China, under three representative concentration pathways (RCP) scenarios. The cluster tree generated for the daily apparent temperature is calibrated for the period 1971–1990 and validated for the period 1991–2000. The R2 values obtained for the validation period at eight selected cities for four GCMs (i.e., CanESM2, CNRM-CM5, CSIRO-Mk3-6-0, and IPSL-CM5A-LR) are 0.88, 0.87, 0.86, and 0.87, respectively. The results reflected that apparent temperature is projected to have a constant increment over the PRD in the future period (2035–2095). Moreover, the monthly apparent temperature in April has the largest expected increment in the future period, while the smallest increment is found in January. The results also indicated that the apparent temperature increases faster than the air temperature under the RCP4.5 and the RCP8.5 scenarios in the PRD. The findings illuminate that the expected increase in apparent temperature over the PRD can be mainly explained by increasing air temperatures and decreasing wind speeds. The results can provide decision makers with useful information for urban health risk assessments.
      PubDate: 2021-05-01
       
  • Selection of the best probability models for daily annual maximum
           rainfalls in Egypt
    • Abstract: Twelve commonly used probability distributions are evaluated to identify the most suitable model that could provide accurate extreme rainfall estimates in Egypt. Three popular parameter estimation methods are applied: the method of moments, L-moments and maximum likelihood. The performance of the models is evaluated based on several numerical and graphical goodness-of-fit criteria. The proposed procedure is applied to annual maximum daily rainfall data from a network of 31 stations located in Egypt. The results indicate that no single distribution performed the best at all stations. Log-Normal, Log-Pearson Type III and Exponential are the top three distributions for the frequency analysis of daily annual extreme rainfalls in Egypt, i.e. they are selected as the “optimum” models for 23%, 19% and 19% of the total stations, respectively. In contrast, the distributions: Normal, Gumbel, Logistic and Generalized Logistic are not suitable for describing the extreme rainfalls in the country. The performances of both L-moments and maximum likelihood methods are almost equal and much better than that of the method of moments. Additionally, Depth-Duration-Frequency curves were established for 18 stations by using the “optimum” model, which can support the design of hydraulic structures. The findings from this study would be helpful for rainfall frequency analysis in similar arid countries.
      PubDate: 2021-05-01
       
  • Spatio-temporal rainfall patterns and trends (1901–2015) across
           Visakhapatnam-Chennai Industrial Corridor, India
    • Abstract: The study of rainfall trends and spatio-temporal evolution (patterns) helps in understanding and planning the utilization of water resources for diverse sectors of the economy, such as agriculture and industries, and also provides indications of climate change. The present study investigates trends and patterns of seasonal, half yearly, and annual rainfall over Visakhapatnam-Chennai Industrial Corridor (VCIC) using non-parametric Mann Kendall and Getis-Ord-Gi* statistics at a district level from 1901 to 2015. The annual rainfall trend for the entire VCIC region shows a significant positive trend at 90%, which is driven by a significant positive trend in monsoons. The intensity of spatial pattern differs across the seasons. However, the annual pattern shows an intensifying hot spot (23% of VCIC), oscillating hot spot (23%), and no pattern (18%). The positive trend in rainfall during monsoon seasons in north-eastern districts and post-monsoon seasons in the southern districts of VCIC has influenced the intensifying hot spot patterns. These trends and patterns are required for carrying out a climate risk assessment for various sectors like urban and industrial areas to plan and propose suitable adaptation measures to cope with extreme rainfall events.
      PubDate: 2021-05-01
       
  • 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
       
  • 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
       
  • 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
       
 
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