Advances in Meteorology
 Journal metrics
Acceptance rate37%
Submission to final decision118 days
Acceptance to publication49 days
CiteScore2.900
Journal Citation Indicator0.390
Impact Factor1.962

Article of the Year 2020

Evaluating the Dependence between Temperature and Precipitation to Better Estimate the Risks of Concurrent Extreme Weather Events

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 Journal profile

Advances in Meteorology publishes research in all areas of meteorology and climatology. Topics include forecasting techniques and applications, meteorological modelling, data analysis, atmospheric chemistry and physics, and climate change.

 Editor spotlight

Dr Jamie Cleverly, the journal’s Chief Editor, is based at James Cook University in Cairns, Australia. Their research interests include carbon, water and energy fluxes of arid-land Acacia swales; physics of the atmospheric surface layer and interactions with terrestrial ecosystems.

 Special Issues

We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

Latest Articles

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Research Article

Seasonal Changes in Climate Variables in Rainfed Crop Areas in the Lerma-Chapala-Santiago Basin, Mexico

This paper shows the effects of changes in the spatial-temporal behavior and phase shift of climate variables on rainfed agriculture in the Lerma-Chapala-Santiago Basin in central Mexico. Specifically, changes in rainfall (R), maximum temperature (Tmax), and minimum temperature (Tmin) were analyzed over two 25-year periods (1960 to 1985 and 1986 to 2010). Climate surfaces were generated by interpolation using the thin-plate smoothing spline algorithm in the software ANUSPLIN. Climate data were Fourier-transformed and fitted to a sinusoidal curve model, and changes in amplitude (increase) and phase were analyzed. The temporal behavior (1960–2010) indicated that rainfall was the most stable variable at the monthly level and presented no significant changes. However, Tmax increased by 2°C in the final period, and Tmin increased by 0.7°C at the end of the final period. The basin was discretized into ten rainfed crop areas (RCAs) according to the extent of changes in the amplitude and phase of the climate variables. The central and southern portions (55% of the area) presented more significant changes in amplitude, mainly in Tmin and Tmax. The remaining RCAs were smaller (14.6%) but presented greater variation: the amplitude of the Tmin decreased in addition to showing a phase shift, whereas Tmax increased in addition to showing a phase shift. These results translate into a delay in the characteristic temperatures of the spring and summer seasons, which can impact the rainfed crop cycle. Additionally, rainfall showed an annual decrease of approximately 50 mm in all RCAs, which can affect the phenological development of crops during critical stages (emergence through flowering). These changes represent a significant threat to the regional economy and food security of Mexico.

Research Article

Drought and Wetness Variability and the Respective Contribution of Temperature and Precipitation in the Qinghai-Tibetan Plateau

Quantifying drought and wetness fluctuations is of great significance to the regional ecological environment and water resource security, especially in the fragile Qinghai-Tibetan Plateau (QTP). In this paper, the standardized precipitation evapotranspiration index (SPEI) was calculated based on the observed data and China Meteorological Forcing Dataset (CMFD) in the QTP for the period of 1979–2015, and the drought and wetness evolution based on the SPEI series and respective contribution of temperature and precipitation were also analyzed. Results indicated that meteorological stations are mainly concentrated in the eastern part of the plateau, which cannot reflect the drought and wetness trend of the whole QTP. The linear trend and Mann–Kendall test revealed that SPEI series calculated based on CMFD data at 1-, 3-, 6-, 9-, 12-, and 24-month time scales all showed significant upward trend , indicating that the QTP as a whole tended to be wetter. Spatially, the regions with significant drying and increased drought probability were mainly concentrated in the Qaidam Basin and the southern part of the QTP, and the mean contribution rates of temperature and precipitation variability to SPEI trend in these regions were 60% and −11%, respectively. The regions with significant wetting and decreased drought probability were mainly concentrated in the northeast, central, and western parts of the plateau, and the mean contribution rates of temperature and precipitation variability to SPEI trend were −9% and 61% in these regions. From the statistics in different climatic regions, most of the arid and humid regions in the QTP tended to be drier, while the semiarid regions tended to be wetter.

Research Article

Convective Cold Pool Associated with Offshore Propagation of Convection System over the East Coast of Southern Sumatra, Indonesia

The cold pool outflow has been previously shown to be generated by decaying Mesoscale Convective Complexes (MCCs) in the Maritime Continent. The cold pool also has a main role in the development processes of oceanic convective systems inducing heavy rainfall. This study investigated a cold pool event (January 1-2, 2021) related to a heavy rainfall system over the coastal region of Lampung, Southern Sumatra, within a high-resolution model simulation using a regional numerical weather prediction of the Weather Research and Forecasting (WRF) with convection permitting of 1 km spatial resolution, which was validated by satellite and radar data observations. It is important to note that the intensity, duration, timing, and structure of heavy rainfall simulated were in good agreement with satellite-observed rainfall. The results also showed that a cold pool (CP) plays an important role in inducing Mesoscale Convective Complex (MCC) and was responsible for the development of an offshore propagation of land-based convective systems due to the late afternoon rainfall over inland. This study also suggests that the propagation speed of the CP 8.8 m·s−1 occurring over the seaside of the coastal region, the so-called CP-coastal, is a plausible mechanism for the speed of the offshore-propagating convection, which is dependent on both the background prevailing wind and outflow. These conditions help to maintain the near-surface low temperatures and inhibit cold pool dissipation, which has implications for the development of consecutive convection.

Research Article

Accuracy Evaluation and Parameter Analysis of Land Surface Temperature Inversion Algorithm for Landsat-8 Data

Many researchers have developed a variety of land surface temperature (LST) inversion algorithms based on satellite data. The main LST inversion algorithms include Radiative Transfer Equation (RTE), Single Channel (SC) algorithm, Mono Window (MW) algorithm, and Split Window (SW) algorithm. In this study, nine LST inversion algorithms were designed using Landsat-8 data and meteorological station data to test the inversion efficiency of different algorithms in different seasons and different locations. The results show that the error of various LST inversion algorithms will increase with the rise of LST. R2 of the inversion results of each LST algorithm and the measured data are all greater than 0.73°C in winter and about 0.5°C in the other seasons. By analyzing the stability of various algorithms inside and outside the city, it is found that the stability of each LST inversion algorithm inside the city is better than that outside the city. For the same surface features, the inversion temperature inside the city is 3–5°C higher than that outside the city. In addition, the sensitivity of various inversion algorithms to parameters was also analyzed. The influence of atmospheric transmittance on RTE, SC, and MW inversion algorithms is in logarithmic form. The effect of emissivity on each algorithm is linear. The influence of NDVI on the algorithms is mainly through the estimation of surface emissivity parameters to affect the inversion results. The effect of ascending radiation on SC (LST4 and LST5) is linear and on RTE (LST1 and LST2) is logarithmic. The effect of downslope radiation on SC and RTE is linear. The influence of atmospheric water vapor content on SW (LST7) is nonlinear.

Research Article

Comparison of Multiple Surface Ocean Wind Products with Buoy Data over Blue Amazon (Brazilian Continental Margin)

Remote sensing data for space-time characterization of wind fields in extensive oceanic areas have been shown to be increasingly useful. Orbital sensors, such as radar scatterometers, provide data on ocean surface wind speed and direction with spatial and temporal resolutions suitable for multiple applications and air-sea studies. Even considering the relevant role of orbital scatterometers to estimate ocean surface wind vectors on a regional and global scale, the products must be validated regionally. Six different ocean surface wind datasets, including advanced scatterometer (ASCAT-A and ASCAT-B products) estimates, numerical modelling simulations (BRAMS), reanalysis (ERA5), and a blended product (CCMP), were compared statistically with in situ measurements obtained by anemometers installed in fifteen moored buoys in the Brazilian margin (8 buoys in oceanic and 7 in shelf waters) to analyze which dataset best represents the wind field in this region. The operational ASCAT wind products presented the lowest differences in wind speed and direction from the in situ data (0.77 ms−1 < RMSEspd < 1.59 ms−1, 0.75 < Rspd < 0.96, −0.68 ms−1 < biasspd < 0.38 ms−1, and 12.7° < RMSEdir < 46.8°). CCMP and ERA5 products also performed well in the statistical comparison with the in situ data (0.81 ms−1 < RMSEspd < 1.87 ms−1, 0.76 < Rspd < 0.91, −1.21 ms−1 < biasspd < 0.19 ms−1, and 13.7° < RMSEdir < 46.3°). The BRAMS model was the one with the worst performance (RMSEspd > 1.04 m·s−1, Rspd < 0.87). For regions with a higher wind variability, as in the southern Brazilian continental margin, wind direction estimation by the wind products is more susceptible to errors (RMSEdir > 42.4°). The results here presented can be used for climatological studies and for the estimation of the potential wind power generation in the Brazilian margin, especially considering the lack of availability or representativeness of regional data for this type of application.

Research Article

Carbon Dioxide Emission Measurement and Its Spatiotemporal Evolution of Tourism Industry in Heilongjiang Province, China

This study analyses the composition and evolution of carbon dioxide emissions from the tourism industry in Heilongjiang Province and its 12 regions by the tourism consumption stripping coefficient method and calculates the decoupling relationship between the carbon dioxide emissions and economic growth of tourism from 2010 to 2019. The empirical results are as follows. (1) From 2010 to 2019, carbon dioxide emissions from Heilongjiang Province’s tourism industry and its subsector increased steadily, of which the tourism industry accounted for a relatively large amount of carbon dioxide emissions in “Transport, Storage, and Post.” (2) Time series analysis reveals that the carbon dioxide emissions of tourism basically show an increasing trend and there are still multiple decoupling relationships with economic growth. Expansive decoupling and weak decoupling have occurred more frequently. (3) Spatial analysis reveals that the carbon dioxide emissions of the regional tourism industry show a fluctuating upward trend. The tourism industry in Harbin has significantly higher carbon dioxide emissions than in other regions. In addition, this study provides feasible suggestions and countermeasures for low-carbon tourism development in Heilongjiang Province. The findings are considered useful in future planning of energy conservation and emission reduction in Heilongjiang Province and the regional tourism industry.

Advances in Meteorology
 Journal metrics
Acceptance rate37%
Submission to final decision118 days
Acceptance to publication49 days
CiteScore2.900
Journal Citation Indicator0.390
Impact Factor1.962
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.