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Journal articles on the topic 'Precipitation (meteorology)'
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1
Akgül, Mehmet Ali, and Hakan Aksu. "Areal Precipitation Estimation Using Satellite Derived Rainfall Data over an Irrigation Area." Turkish Journal of Agriculture - Food Science and Technology 9, no. 2 (February 23, 2021): 386–94. http://dx.doi.org/10.24925/turjaf.v9i2.386-394.4061.
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The average precipitation on the irrigation field can be estimated from the Meteorology Observation Stations by using spatial interpolation methods such as Thiessen polygon and isohyetal curves. However, the fact that precipitation doesn't occur homogenous in spatial scales, spatial interpolation methodologies need a large number of meteorology stations for more accurate results. In recent years, remote sensing methods have diversified to estimate precipitation. In this study, performance of the satellite-based precipitation data was assessed to determine areal precipitation over an irrigation area. This study was conducted over left bank irrigation area located in the Çukurova Plain of Turkey. Relationship between CHIRPS satellite based on monthly precipitation data and 4 meteorology stations’ data were analyzed. Determination coefficients (R2) of the stations were found between 0.64 and 0.77, for point based comparison, R2 was calculated as 0.84 with Thiessen polygon method. It is concluded that the precipitation amount in the irrigated area can be estimated as accurately as classical methods such as Thiessen polygon with satellite-based precipitation data.
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Ahrens, B., K. Jasper, and J. Gurtz. "On ALADIN precipitation modeling and validation in an Alpine watershed." Annales Geophysicae 21, no. 3 (March 31, 2003): 627–37. http://dx.doi.org/10.5194/angeo-21-627-2003.
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Abstract. Highly resolved precipitation forecasts are necessary in many applications, especially in mountain meteorology and flash flood forecasts for small- to medium-sized alpine watersheds. Here we present precipitation forecasts simulated by the limited area model ALADIN applying different grid resolutions (Dx = 10 km and 4 km). Target area of the investigations is the Alpine Ticino-Verzasca-Maggia watershed (total area: 2627 km2). We discuss problems of validation of high-resolution precipitation forecasts by comparison with observed precipitation fields and apply an indirect validation approach by using ALADIN forecasts as input to hydrologic simulations. These simulations are carried out with the distributed hydrologic model WaSiM-ETH (Dx = 500 m, Dt = 1 h). The time step of meteorological input to WaSiM-ETH is fixed at 1 h but spatial resolution varies. The main result of the validation experiments for three heavy precipitation events is, that coarser-scale ALADIN forecasts (in model version 11.2) provide better precipitation predictors for hydrologic modeling than higher-resolution forecasts. The experiments demonstrate that hydrologic modeling is a promising tool for the evaluation of high-resolution precipitation fields.Key words. Hydrology (floods) – Meteorology and atmospheric dynamics (mesoscale meteorology; precipitation)
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Liu, Yan Ping, Yong Wang, and Zhen Wang. "RBF Prediction Model Based on EMD for Forecasting GPS Precipitable Water Vapor and Annual Precipitation." Advanced Materials Research 765-767 (September 2013): 2830–34. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2830.
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The forecast of precipitations is important in meteorology and atmospheric sciences. A new model is proposed based on empirical mode decomposition and the RBF neural network. Firstly, GPS PWV time series is broken down into series of different scales intrinsic mode function. Secondly, the phase space reconstruction is done. Thirdly, each component is predicted by RBF. Finally, the final prediction value is reconstructed. Next, the model is tested on annual precipitation sequence from 2001 to 2010 in northeast China. The result shows that predictive value is close to the actual precipitation, which can better reflect the actual precipitation change. From 2001 to 2010, the maximum deviation of the predicted values never exceeds 4%. The testing results show that the proposed model can increase precipitation forecasting accuracies not only in GPS PWV but also in annual precipitation.
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Demaria, E. M. C., E. P. Maurer, J. Sheffield, E. Bustos, D. Poblete, S. Vicuña, and F. Meza. "Using a Gridded Global Dataset to Characterize Regional Hydroclimate in Central Chile." Journal of Hydrometeorology 14, no. 1 (February 1, 2013): 251–65. http://dx.doi.org/10.1175/jhm-d-12-047.1.
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Abstract Central Chile is facing dramatic projections of climate change, with a consensus for declining precipitation, negatively affecting hydropower generation and irrigated agriculture. Rising from sea level to 6000 m within a distance of 200 km, precipitation characterization is difficult because of a lack of long-term observations, especially at higher elevations. For understanding current mean and extreme conditions and recent hydroclimatological change, as well as to provide a baseline for downscaling climate model projections, a temporally and spatially complete dataset of daily meteorology is essential. The authors use a gridded global daily meteorological dataset at 0.25° resolution for the period 1948–2008, adjusted by monthly precipitation observations interpolated to the same grid using a cokriging method with elevation as a covariate. For validation, daily statistics of the adjusted gridded precipitation are compared to station observations. For further validation, a hydrology model is driven with the gridded 0.25° meteorology and streamflow statistics are compared with observed flow. The high elevation precipitation is validated by comparing the simulated snow extent to Moderate Resolution Imaging Spectroradiometer (MODIS) images. Results show that the daily meteorology with the adjusted precipitation can accurately capture the statistical properties of extreme events as well as the sequence of wet and dry events, with hydrological model results displaying reasonable agreement with observed streamflow and snow extent. This demonstrates the successful use of a global gridded data product in a relatively data-sparse region to capture hydroclimatological characteristics and extremes.
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Chubb, Thomas H., Michael J. Manton, Steven T. Siems, and Andrew D. Peace. "Evaluation of the AWAP daily precipitation spatial analysis with an independent gauge network in the Snowy Mountains." Journal of Southern Hemisphere Earth Systems Science 66, no. 1 (2016): 55. http://dx.doi.org/10.1071/es16006.
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The Bureau of Meteorology's Australian Water Availability Project (AWAP) daily precipitation analysis provides high resolution rainfall data by interpolating rainfall gauge data, but when evaluated against a spatially dense independent gauge network in the Snowy Mountains large systematic biases are identified. Direct comparisons with the gauge data in May–September between 2007 and 2014 reveal average root mean square errors of about 4.5 mm, which is slightly greater than the average daily precipitation amount, and the errors are larger for higher elevation gauges. A standard Barnes objective analysis is per-formed on the combined set of independent gauges and Bureau of Meteorology gauges in the region to examine the spatial characteristics of the differences. The largest differences are found on the western (windward) slopes, where the Barnes analysis is up to double the value of the AWAP analysis. These differences are attributed to a) the lack of Bureau of Meteorology gauges in the area to empirically represent the precipitation climatology, and b) the inability of the AWAP analysis to account for the steep topography exposed to the prevailing winds. At high elevation (>1400 m) the Barnes analysis suggests that the precipitation amount is about fifteen percent greater than that of the AWAP analysis, where the difficulties of measuring frozen precipitation likely have a large impact.
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Keup-Thiel, E., C. Ph Klepp, E. Raschke, and B. Rockel. "Regional model simulation of the North Atlantic cyclone "Caroline" and comparisons with satellite data." Annales Geophysicae 21, no. 3 (March 31, 2003): 655–59. http://dx.doi.org/10.5194/angeo-21-655-2003.
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Abstract. An individual regional model simulation of cyclone "Caroline" has been carried out to study water cycle components over the North Atlantic Ocean. The uncertainties associated with quantitative estimates of the water cycle components are highlighted by a comparison of the model results with SSM/I (Special Sensor Microwave Imager) satellite data. The vertically integrated water vapor of the REgional MOdel REMO is in good agreement with the SSM/I satellite data. The simulation results for other water budget components like the vertically integrated liquid water content and precipitation compare also reasonably well within the frontal system. However, the high precipitation rate in the cold air outbreak on the backside of the cold front derived from SSM/I satellite data is generally underestimated by REMO. This results in a considerable deficit of the total precipitation amount accumulated for the cyclone "Caroline". While REMO simulates 24.3 108 m3 h-1 for 09:00 UTC, the total areal precipitation from SSM/I satellite data amounts to 54.7 08 m3 h-1.Key words. Meteorology and atmospheric dynamics (precipitation; mesoscale meteorology) – Radio science (remote sensing)
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Xu, Fengyang, Guanbin Li, Yunfei Du, Zhiguang Chen, and Yutong Lu. "Multi-Layer Networks for Ensemble Precipitation Forecasts Postprocessing." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 14966–73. http://dx.doi.org/10.1609/aaai.v35i17.17756.
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The postprocessing method of ensemble forecasts is usually used to find a more precise estimate of future precipitation, because dynamic meteorology models have limitations in fitting fine-grained atmospheric processes and precipitation is driven more often by smaller-scale processes, while ensemble forecasts can hit this precipitation at times. However, the pattern of these hits cannot be easily summarized. The existing objective postprocessing methods tend to extend the rain area or false alarm the precipitation intensity categories. In this work, we introduce a multi-layer structure to simultaneously reduce the bias in forecast ensembles output by meteorology models and merge them to a quality deterministic (single-valued) forecast using cross-grid information, which differs quite dramatically from the previous statistical postprocessing method. The multi-layer network is designed to model the spatial distribution of future precipitation of different intensity categories(IC-MLNet). We provide a comparison of IC-MLNet to simple average as well as another two state-of-the-art ensemble quantitative precipitation forecasts (QPFs) postprocessing approaches over both single-model and multi-model ensemble forecasts datasets from TIGGE. The experimental results indicate that our model achieves superior performance over the compared baselines in precipitation amount prediction as well as precipitation intensities categories prediction.
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Korolev, Victor, Andrey Gorshenin, and Konstatin Belyaev. "Statistical Tests for Extreme Precipitation Volumes." Mathematics 7, no. 7 (July 19, 2019): 648. http://dx.doi.org/10.3390/math7070648.
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The analysis of the real observations of precipitation based on the novel statistical approach using the negative binomial distribution as a model for describing the random duration of a wet period is considered and discussed. The study shows that this distribution fits very well to the real observations and generalized standard methods used in meteorology to detect an extreme volume of precipitation. It also provides a theoretical base for the determination of asymptotic approximations to the distributions of the maximum daily precipitation volume within a wet period, as well as the total precipitation volume over a wet period. The paper demonstrates that the relation of the unique precipitation volume, having the gamma distribution, divided by the total precipitation volume taken over the wet period is given by the Snedecor–Fisher or beta distributions. It allows us to construct statistical tests to determine the extreme precipitations. Within this approach, it is possible to introduce the notions of relatively and absolutely extreme precipitation volumes. An alternative method to determine an extreme daily precipitation volume based on a certain quantile of the tempered Snedecor–Fisher distribution is also suggested. The results of the application of these methods to real data are presented.
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Oswald, Sandro M., Helga Pietsch, Dietmar J. Baumgartner, Philipp Weihs, and Harald E. Rieder. "Pyranometer offsets triggered by ambient meteorology: insights from laboratory and field experiments." Atmospheric Measurement Techniques 10, no. 3 (March 21, 2017): 1169–79. http://dx.doi.org/10.5194/amt-10-1169-2017.
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Abstract. This study investigates the effects of ambient meteorology on the accuracy of radiation (R) measurements performed with pyranometers contained in various heating and ventilation systems (HV-systems). It focuses particularly on instrument offsets observed following precipitation events. To quantify pyranometer responses to precipitation, a series of controlled laboratory experiments as well as two targeted field campaigns were performed in 2016. The results indicate that precipitation (as simulated by spray tests or observed under ambient conditions) significantly affects the thermal environment of the instruments and thus their stability. Statistical analyses of laboratory experiments showed that precipitation triggers zero offsets of −4 W m−2 or more, independent of the HV-system. Similar offsets were observed in field experiments under ambient environmental conditions, indicating a clear exceedance of BSRN (Baseline Surface Radiation Network) targets following precipitation events. All pyranometers required substantial time to return to their initial signal states after the simulated precipitation events. Therefore, for BSRN-class measurements, the recommendation would be to flag the radiation measurements during a natural precipitation event and 90 min after it in nighttime conditions. Further daytime experiments show pyranometer offsets of 50 W m−2 or more in comparison to the reference system. As they show a substantially faster recovery, the recommendation would be to flag the radiation measurements within a natural precipitation event and 10 min after it in daytime conditions.
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Renggono, F., H. Hashiguchi, S. Fukao, M. D. Yamanaka, S. Y. Ogino, N. Okamoto, F. Murata, et al. "Precipitating clouds observed by 1.3-GHz boundary layer radars in equatorial Indonesia." Annales Geophysicae 19, no. 8 (August 31, 2001): 889–97. http://dx.doi.org/10.5194/angeo-19-889-2001.
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Abstract. Temporal variations of precipitating clouds in equatorial Indonesia have been studied based on observations with 1357.5 MHz boundary layer radars at Serpong (6.4° S, 106.7° E) near Jakarta and Bukittinggi (0.2° S, 100.3° E) in West Sumatera. We have classified precipitating clouds into four types: stratiform, mixed stratiform-convective, deep convective, and shallow convective clouds, using the Williams et al. (1995) method. Diurnal variations of the occurrence of precipitating clouds at Serpong and Bukittinggi have showed the same characteristics, namely, that the precipitating clouds primarily occur in the afternoon and the peak of the stratiform cloud comes after the peak of the deep convective cloud. The time delay between the peaks of stratiform and deep convective clouds corresponds to the life cycle of the mesoscale convective system. The precipitating clouds which occur in the early morning at Serpong are dominated by stratiform cloud. Concerning seasonal variations of the precipitating clouds, we have found that the occurrence of the stratiform cloud is most frequent in the rainy season, while the occurrence of the deep convective cloud is predominant in the dry season.Key words. Meteorology and atmospheric dynamics (convective processes; precipitation; tropical meteorology)
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Hossein, Syed Zakir, Han Man Shin, and Choi Gyewoon. "Evaluation of regional droughts using monthly gridded precipitation for Korea." Journal of Hydroinformatics 14, no. 4 (March 9, 2012): 1036–50. http://dx.doi.org/10.2166/hydro.2012.070.
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This paper attempts to characterize regional drought using 0.5 degree reanalyzed GPCC (Global Precipitation Climatology Center) gauge-based gridded monthly precipitation data sets in Korea. Drought is a function of precipitation and long-term observed precipitation was performed to enhance this characterization. There are limited long-term records from each station, therefore, a global gridded data set has been employed. Before using this data, 10 corresponding grids with KMA (Korea Meteorology Administration) stations were validated through cross-correlations (0.93–0.99). The impacts of drought are dependent on its duration, severity and spatial extent. Drought occurs when a below average water availability persists and becomes regionally extensive. In this study, 66 GPCC gridded precipitations were employed to estimate the effective drought index along with the available water resource index. The results of the 10 KMA corresponding stations were as accurate as those of the global data. Consequently, gridded data are suitable for a monthly drought severity investigation. In addition, spatial distribution of drought and available water resources were exposed by kriging interpolation technique over Korea. Through this study, drought risk city Taebaek in Kangwon province was classified by its 2009 intensity of monthly precipitations, droughts and available water resources.
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Adams, David K., Rui M. S. Fernandes, Kirk L. Holub, Seth I. Gutman, Henrique M. J. Barbosa, Luiz A. T. Machado, Alan J. P. Calheiros, et al. "The Amazon Dense GNSS Meteorological Network: A New Approach for Examining Water Vapor and Deep Convection Interactions in the Tropics." Bulletin of the American Meteorological Society 96, no. 12 (December 1, 2015): 2151–65. http://dx.doi.org/10.1175/bams-d-13-00171.1.
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Abstract The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial–temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km × 100 km) networks: 1) a 1-yr (April 2011–April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized.
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Lazri, M., S. Hameg, S. Ameur, J. M. Brucker, F. Ouallouche, and Y. Mohia. "Behavior analysis of convective and stratiform rain using Markovian approach over Mediterranean region from meteorological radar data." Hydrology and Earth System Sciences Discussions 9, no. 5 (May 16, 2012): 6225–50. http://dx.doi.org/10.5194/hessd-9-6225-2012.
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Abstract. The aim of this study is to analyze the chronological behavior of precipitation in the north of Algeria using a Markovian approach. The probabilistic approach presented here proposes to study the evolution of the rainfall phenomenon in two distinct study areas, one located in sea and other located in ground. The data that we have used are provided by the National Office of Meteorology in Algiers (ONM). They are a series of images collected by the meterological radar of Setif during the rainy season 2001/2002. A decision criterion is established and based on radar reflectivity in order to classify the precipitation events located in both areas. At each radar observation, a state of precipitations is classified, either convective (heavy precipitation) or stratiform (average precipitation) both for the "sea" and for the "ground". On the whole, a time series of precipitations composed of three states; S0 (no raining), S1 (stratiform precipitation) and S2 (convective precipitation), is obtained for each of the two areas. Thereby, we studied and characterized the behavior of precipitation in time by a Markov chain of order one with three states. Transition probabilities Pij of state Si to state Sj are calculated. The results show that rainfall is well described by a Markov chain of order one with three states. Indeed, the stationary probabilities, which are calculated by using the Markovian model, and the actual probabilities are almost identical.
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Srinivasan, J. "Diagnostic study of errors in the simulation of tropical continental precipitation in general circulation models." Annales Geophysicae 21, no. 5 (May 31, 2003): 1197–207. http://dx.doi.org/10.5194/angeo-21-1197-2003.
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Abstract. A simple diagnostic model has been used to identify the parameters that induce large errors in the simulation of tropical precipitation in atmospheric General Circulation models (GCM). The GCM that have been considered are those developed by the National Center for Environmental Prediction (NCEP), the National Center for Atmospheric Research (NCAR) and the Japanese Meteorological Agency (JMA). These models participated in the phase II of the Atmospheric Model Inter-comparison Project (AMIP II) and simulated the climate for the period 1979 to 1995. The root mean-square error in the simulation of precipitation in tropical continents was larger in NCEP and NCAR simulations than in the JMA simulation. The large error in the simulation of precipitation in NCEP was due to errors in the vertical profile of water vapour. The large error in precipitation in NCAR in North Africa was due to an error in net radiation (at the top of the atmosphere). The simple diagnostic model predicts that the moisture converge is a nonlinear function of integrated water vapour. The large error in the interannual variance of rainfall in NCEP over India has been shown to be due to this nonlinearity.Key words. Meteorology and atmospheric dynamics (precipitation; tropical meteorology; convective processes)
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Chen, Tianyu. "U-Net-based Precipitation Predict by Cloud Map." Highlights in Science, Engineering and Technology 39 (April 1, 2023): 633–38. http://dx.doi.org/10.54097/hset.v39i.6615.
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Many traditional precipitation prediction methods in meteorology nowadays require many types of data to be input as parameters. This research is to investigate ways to use deep learning techniques for precipitation prediction using only input cloud maps. This paper establishes a technical route for predicting rainfall through cloud map data using U-Net, and experiments. Rainfall models were successfully trained using U-Net and predicted.
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França, G. B., M. V. de Almeida, and A. C. Rosette. "Self-Nowcast Model of extreme precipitation events for operational meteorology." Atmospheric Measurement Techniques Discussions 8, no. 10 (October 16, 2015): 10635–61. http://dx.doi.org/10.5194/amtd-8-10635-2015.
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Abstract. Nowadays many social activities require short-term (one to two hours) and local area forecasts of extreme weather. In particular, air traffic systems have been studying how to minimize the impact of meteorological events, such as turbulence, wind shear, ice, and heavy rain, which are related to the presence of convective systems during all flight phases. This paper presents an alternative self-nowcast model, based on neural network techniques, to produce short-term and local-specific forecasts of extreme meteorological events in the area of the landing and take-off region of Galeão, the principal airport in Rio de Janeiro, Brazil. Twelve years of data were used for neural network training and validation. Data are originally from four sources: (1) hourly meteorological observations from surface meteorological stations at five airports distributed around the study area, (2) atmospheric profiles collected twice a day at the meteorological station at Galeão Airport, (3) rain rate data collected from a network of twenty-nine rain gauges in the study area; and (4) lightning data regularly collected by national detection networks. An investigation was done about the capability of a neural network to produce early warning signs – or as a nowcasting tool – for extreme meteorological events. The self-nowcast model was validated using results from six categorical statistics, indicated in parentheses for forecasts of the first, second, and third hours, respectively, namely: proportion correct (0.98, 0.96, and 0.94), bias (1.37, 1.48, and 1.83), probability of detection (0.84, 0.80, and 0.76), false-alarm ratio (0.38, 0.46, and 0.58), and threat score (0.54, 0.47, and 0.37). Possible sources of error related to the validation procedure are discussed. Two key points have been identified in which there is a possibility of error: i.e., subjectivity on the part of the meteorologist making the observation, and a rain gauge measurement error of about 20 % depending on wind speed. The latter was better demonstrated when lightning data were included in the validation. The validation showed that the proposed model's performance was quite encouraging for the first and second hours.
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Barabash, V., S. Kirkwood, and P. B. Chilson. "Are variations in PMSE intensity affected by energetic particle precipitation?" Annales Geophysicae 20, no. 4 (April 30, 2002): 539–45. http://dx.doi.org/10.5194/angeo-20-539-2002.
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Abstract. The correlation between variations in Polar Mesosphere Summer Echoes (PMSE) and variations in energetic particle precipitation is examined. PMSE were observed by the Esrange VHF MST Radar (ESRAD) at 67°53' N, 21°06' E. The 30 MHz riometer in Abisko (68°24' N, 18°54' E) registered radio wave absorption caused by ionization changes in response to energetic particle precipitation. The relationship between the linear PMSE intensity and the square of absorption has been estimated using the Pearson linear correlation and the Spearman rank correlation. The mean diurnal variation of the square of absorption and the linear PMSE intensity are highly correlated. However, their day-to-day variations show significant correlation only during the late evening hours. The correlation in late evening does not exceed 0.6. This indicates that varying ionization cannot be considered as a primary source of varying PMSE, and the high correlation found when mean diurnal variations are compared is likely a by-product of daily variations caused by other factors.Key words. Ionosphere (particle precipitation) Magnetospheric physics (energetic particles, precipitating) Meteorology and atmospheric dynamics (precipitation)
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Karlický, Jan, Peter Huszár, Tereza Nováková, Michal Belda, Filip Švábik, Jana Ďoubalová, and Tomáš Halenka. "The “urban meteorology island”: a multi-model ensemble analysis." Atmospheric Chemistry and Physics 20, no. 23 (December 4, 2020): 15061–77. http://dx.doi.org/10.5194/acp-20-15061-2020.
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Abstract. Cities and urban areas are well-known for their impact on meteorological variables and thereby modification of the local climate. Our study aims to generalize the urban-induced changes in specific meteorological variables by introducing a single phenomenon – the urban meteorology island (UMI). A wide ensemble of 24 model simulations with the Weather Research and Forecasting (WRF) regional climate model and the Regional Climate Model (RegCM) on a European domain with 9 km horizontal resolution were performed to investigate various urban-induced modifications as individual components of the UMI. The results show that such an approach is meaningful, because in nearly all meteorological variables considered, statistically significant changes occur in cities. Besides previously documented urban-induced changes in temperature, wind speed and boundary-layer height, the study is also focused on changes in cloud cover, precipitation and humidity. An increase in cloud cover in cities, together with a higher amount of sub-grid-scale precipitation, is detected on summer afternoons. Specific humidity is significantly lower in cities. Further, the study shows that different models and parameterizations can have a strong impact on discussed components of the UMI. Multi-layer urban schemes with anthropogenic heat considered increase winter temperatures by more than 2 ∘C and reduce wind speed more strongly than other urban models. The selection of the planetary-boundary-layer scheme also influences the urban wind speed reduction, as well as the boundary-layer height, to the greatest extent. Finally, urban changes in cloud cover and precipitation are mostly sensitive to the parameterization of convection.
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Hansson, Hans-Christen, Peter Tunved, Radovan Krejci, Eyal Freud, Nikos Kalivitis, Tabea Hennig, Giorgos Maneas, and Evangelos Gerasopoulos. "The Atmospheric Aerosol over Western Greece-Six Years of Aerosol Observations at the Navarino Environmental Observatory." Atmosphere 12, no. 4 (March 31, 2021): 445. http://dx.doi.org/10.3390/atmos12040445.
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The Eastern Mediterranean is a highly populated area with air quality problems. It is also where climate change is already noticed by higher temperatures and s changing precipitation pattern. The anthropogenic aerosol affects health and changing concentrations and properties of the atmospheric aerosol affect radiation balance and clouds. Continuous long-term observations are essential in assessing the influence of anthropogenic aerosols on climate and health. We present six years of observations from Navarino Environmental Observatory (NEO), a new station located at the south west tip of Peloponnese, Greece. The two sites at NEO, were evaluated to show the influence of the local meteorology and to assess the general background aerosol possible. It was found that the background aerosol was originated from aged European aerosols and was strongly influenced by biomass burning, fossil fuel combustion, and industry. When subsiding into the boundary layer, local sources contributed in the air masses moving south. Mesoscale meteorology determined the diurnal variation of aerosol properties such as mass and number by means of typical sea breeze circulation, giving rise to pronounced morning and evening peaks in pollutant levels. While synoptic scale meteorology, mainly large-scale air mass transport and precipitation, strongly influenced the seasonality of the aerosol properties.
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Bezrukova, N. A., and A. V. Chernokulsky. "Russian Studies on Clouds and Precipitation in 2019–2022." Известия Российской академии наук. Физика атмосферы и океана 59, no. 7 (December 1, 2023): 882–914. http://dx.doi.org/10.31857/s0002351523070039.
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Results of Russian studies on cloud physics, precipitation, and weather modification in 2015–2018 are presented based on a survey prepared for the Russian National Report on Meteorology and Atmospheric Sciences to the 28th General Assembly of the International Union of Geodesy and Geophysics. Results concerning general issues of observation and modeling of clouds and precipitation, including convective clouds, issues of studying microphysical and optical characteristics of clouds, and weather modification are discussed.
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Fan, J., L. R. Leung, P. J. DeMott, J. M. Comstock, B. Singh, D. Rosenfeld, J. M. Tomlinson, et al. "Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution vs. long-range transported dust." Atmospheric Chemistry and Physics Discussions 13, no. 7 (July 26, 2013): 19921–70. http://dx.doi.org/10.5194/acpd-13-19921-2013.
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Abstract. Mineral dust aerosols often observed over California in winter/spring, associated with long-range transport from Asia and Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model, to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations are carried out for two cloud cases with contrasting meteorology and cloud dynamics that occurred on 16 February (FEB16) and 2 March (MAR02) from the CalWater 2011 field campaign. In both cases, observations show the presence of dust or dust/biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust/biological aerosol layers increase the accumulated precipitation by 10–20% from the Central Valley to the Sierra Nevada Mountains for both FEB16 and MAR02 due to a 40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by few percent due to increased snow formation when dust is present but reduces precipitation by 5–8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology including the strength of the Sierra Barrier Jet, and cloud dynamics. This study further underscores the importance of the interactions between local pollution, dust, and environmental conditions for assessing aerosol effects on cold season precipitation in California.
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Fan, J., L. R. Leung, P. J. DeMott, J. M. Comstock, B. Singh, D. Rosenfeld, J. M. Tomlinson, et al. "Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution versus long-range transported dust." Atmospheric Chemistry and Physics 14, no. 1 (January 3, 2014): 81–101. http://dx.doi.org/10.5194/acp-14-81-2014.
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Abstract. Mineral dust aerosols often observed over California in winter and spring, associated with long-range transport from Asia and the Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model in order to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations are carried out for two cloud cases (from the CalWater 2011 field campaign) with contrasting meteorology and cloud dynamics that occurred on 16 February (FEB16) and 2 March (MAR02). In both cases, observations show the presence of dust and biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust and biological aerosol layers increase the accumulated precipitation by 10–20% from the Central Valley to the Sierra Nevada for both FEB16 and MAR02 due to a ~40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by a few percent due to increased snow formation when dust is present, but reduces precipitation by 5–8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology, including cloud dynamics and the strength of the Sierra Barrier Jet. This study further underscores the importance of the interactions between local pollution, dust, and environmental conditions for assessing aerosol effects on cold-season precipitation in California.
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Suess, Elizabeth J., Cinzia Cervato, William A. Gallus, and Jonathon M. Hobbs. "Weather Forecasting as a Learning Tool in a Large Service Course: Does Practice Make Perfect?" Weather and Forecasting 28, no. 3 (June 1, 2013): 762–71. http://dx.doi.org/10.1175/waf-d-12-00105.1.
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Abstract Each spring roughly 200 students, mostly nonmajors, enroll in the Introduction to Meteorology course at Iowa State University and are required to make at least 25 forecasts throughout the semester. The Dynamic Weather Forecaster (DWF) forecasting platform requires students to forecast more than just simple “numeric” forecasts and includes questions on advection, cloudiness, and precipitation factors that are not included in forecast contests often used in meteorology courses. The present study examines the evolution of forecasting skill for students enrolled in the class in spring 2010 and 2011 and compares student performance with that of an “expert forecaster.” The expert forecasters were chosen from meteorology students in an advanced forecasting course who showed exemplary forecasting skill throughout the previous semester. It is shown that these introductory students improve in forecast skill over only the first 10–15 days that they forecast, a number smaller than the 25 days found in an earlier study examining meteorology majors in an upper-level course. The skill of both groups plateaus after that time. An analysis of two types of questions in the DWF reveals that students do have skill slightly better than that of a persistence forecast when predicting parameters traditionally used in forecasting contests, but fail to outperform persistence when predicting more complex atmospheric processes like temperature advection and factors influencing precipitation such as moisture content and instability. The introduction of a contest “with prizes” halfway through the semester in 2011 was found to have at best mixed impacts on forecast skill.
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Davenport, Casey E., Christian S. Wohlwend, and Thomas L. Koehler. "Motivation for and Development of a Standardized Introductory Meteorology Assessment Exam." Bulletin of the American Meteorological Society 96, no. 2 (February 1, 2015): 305–12. http://dx.doi.org/10.1175/bams-d-13-00157.1.
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Abstract Education research has shown that there is often a disconnect between what instructors teach and what students actually comprehend. Much of this disconnect stems from students’ previous conceptions of the subject that often remain steadfast despite instruction. The field of meteorology is particularly susceptible to misconceptions as a result of the years of personal experience students have with weather before instruction. Consequently, it is often challenging for students to accurately integrate course material with their observations and personal explanations. A longitudinal assessment exam of the meteorology program at the U.S. Air Force Academy revealed that misconceptions of fundamental, introductory content can propagate through years of instruction, potentially impeding deeper understanding of advanced topics and hindering attainment of professional certifications. Thus, it is clear that such misconceptions must be identified and corrected early. This manuscript describes the development of the Fundamentals in Meteorology Inventory (FMI), a multiple-choice assessment exam designed to identify the common misconceptions of fundamental topics covered in introductory meteorology courses. In developing the FMI, care was taken to avoid complex vocabulary and to include plausible distractors identified by meteorology faculty members. Question topics include clouds and precipitation, wind, fronts and air masses, temperature, stability, severe weather, and climate. Applications of the exam for the meteorology community are discussed, including identifying common meteorology misconceptions, assessing student understanding, measuring teaching effectiveness, and diagnosing areas for improvement in introductory meteorology courses. Future work to be completed to ensure the efficacy of the FMI will also be acknowledged.
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Taqui, Muhammad, Jabir Hussain Syed, and Ghulam Hassan Askari. "ROUTINE, EXTREME AND ENGINEERING METEOROLOGY ANALYSIS FOR KARACHI COASTAL AREA." Earth Science Malaysia 4, no. 1 (February 25, 2020): 15–22. http://dx.doi.org/10.26480/esmy.01.2020.15.22.
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Pakistan’s largest city, Karachi, which is industrial centre and economic hub needs focus in research and development of every field of Engineering, Science and Technology. Urbanization and industrialization is resulting bad weather conditions which prolongs until a climate change. Since, Meteorology serves as interdisciplinary field of study, an analytical study of real and region-specific meteorological data is conducted which focuses on routine, extreme and engineering meteorology of metropolitan city Karachi. Results of study endorse the meteorological parameters relationship and establish the variability of those parameters for Karachi Coastal Area. The rise of temperature, decreasing trend of atmospheric pressure, increment in precipitation and fall in relative humidity depict the effects of urbanization and industrialization. The recorded extreme maximum temperature of 45.50C (on June 11, 1988) and the extreme minimum temperature of 4.5 0C(on January 1, 2007) is observed at Karachi south meteorological station. The estimated temperature rise in 32 years is 0.9 0C, which is crossing the Intergovernmental Panel on Climate Change (IPCC) predicted/estimated limit of 2oC rise per century. The maximum annual precipitation of 487.0mm appearing in 1994 and the minimum annual precipitation of 2.5mm appearing in 1987 is observed at same station which is representative meteorological station for Karachi Coast. Further Engineering meteorological parameters for heating ventilation air condition (HVAC) system design for industrial purpose are deduced as supporting data for coastal area site study for industrial as well as any follow-up engineering work in the specified region.
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Smith, Ronald B. "100 Years of Progress on Mountain Meteorology Research." Meteorological Monographs 59 (January 1, 2019): 20.1–20.73. http://dx.doi.org/10.1175/amsmonographs-d-18-0022.1.
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ABSTRACT Mountains significantly influence weather and climate on Earth, including disturbed surface winds; altered distribution of precipitation; gravity waves reaching the upper atmosphere; and modified global patterns of storms, fronts, jet streams, and climate. All of these impacts arise because Earth’s mountains penetrate deeply into the atmosphere. This penetration can be quantified by comparing mountain heights to several atmospheric reference heights such as density scale height, water vapor scale height, airflow blocking height, and the height of natural atmospheric layers. The geometry of Earth’s terrain can be analyzed quantitatively using statistical, matrix, and spectral methods. In this review, we summarize how our understanding of orographic effects has progressed over 100 years using the equations for atmospheric dynamics and thermodynamics, numerical modeling, and many clever in situ and remote sensing methods. We explore how mountains disturb the surface winds on our planet, including mountaintop winds, severe downslope winds, barrier jets, gap jets, wakes, thermally generated winds, and cold pools. We consider the variety of physical mechanisms by which mountains modify precipitation patterns in different climate zones. We discuss the vertical propagation of mountain waves through the troposphere into the stratosphere, mesosphere, and thermosphere. Finally, we look at how mountains distort the global-scale westerly winds that circle the poles and how varying ice sheets and mountain uplift and erosion over geologic time may have contributed to climate change.
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Areerachakul, Nathaporn, Sethakarn Prongnuch, Peeranat Longsomboon, and Jaya Kandasamy. "Quantitative Precipitation Estimation (QPE) Rainfall from Meteorology Radar over Chi Basin." Hydrology 9, no. 10 (October 11, 2022): 178. http://dx.doi.org/10.3390/hydrology9100178.
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This study of the Quantitative Estimation Precipitation (QEP) of rainfall, detected by two Meteorology Radars over Chi Basin, North-east Thailand, used data from the Thai Meteorological Department (TMD). The rainfall data from 129 rain gauge stations in the Chi Basin area, covering a period of two years, was also used. The study methodology consists of: firstly, deriving the QPE between radar and rainfall based on meteorological observations using the Marshall Palmer Stratiform, the Summer Deep Convection, and Regression Model and calibrating with rain gauge station data; secondly, Bias Correction using statistical method; thirdly, determining spatial variation using three methods, namely Kriging, Inverse Distance Weight (IDW), and the Minimum Curvature Method. The results of the study demonstrated the accuracy of estimating precipitation using meteorological radar. Estimated precipitation compared against an equivalent of 2 years of rain station measurement had a probability of detection (POD) of 0.927, where a value of 1 indicated perfect agreement, demonstrating the effectiveness of the method used to calibrate the radar data. The bias correction method gave high accuracy compared with measured rainfall. Furthermore, of the spatial estimation of rainfall methods, the Kriging methodology showed the best fit between estimation of rainfall distribution and measured rainfall distribution. Therefore, the results of this study showed that the rainfall estimation, using data from a meteorology radar, has good accuracy and can be useful, especially in areas where it is not possible to install and operate rainfall measurement stations, such as in heavily forested areas and/or in steep terrain. Additionally, good accuracy rainfall data derived from radar data can be integrated with other data used for water management and natural disasters for applications to reduce economic losses, as well as losses of life and property.
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Villarrasa Sapiña, Israel, LAURA ANTON GONZALEZ, and MIQUEL PANS. "APPLICATION OF SELF-ORGANIZING MAP (SOM) ANALYSIS FOR ESTIMATING BICYCLE SHARING: A NEW PERSPECTIVE." DYNA DYNA-ACELERADO (April 19, 2023): [6 pp]. http://dx.doi.org/10.6036/10788.
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Meteorology may be key to forecasting whether people will use it or not (depending on city studied), but so to date, the predictions made have generated some controversy because they have not been analyzed using non-linear analysis. The objective of this study is to analyse the relationship between the time spent using the València bike sharing service (SBC) as a means of active transport and the weather. A self-organising map analysis (SOM) was performed to generate profiles (clusters) of days on SBC use and meteorological factors and a non-parametric analysis was performed to compare the different profiles generated. The results showed 8 profiles of days, which obtained multiple significant differences. These results show that, although there are variables with greater weight than others for estimating the use of the SBC, their relationship is not always linear and a combination of them is needed for greater rigor in the predictions. In this study has been observed that, in order to predict a high use of the SBC, days should be warm if humidity is low to moderate, although temperature is limited if humidity is high, with virtually no precipitation and low average wind speed. On the other hand, to estimate low SBC use, days should be characterized by high relative humidity, precipitation and wind speed. On these days, if the humidity is not high and there is no precipitation, low temperatures would be taken into account. In conclusion, the use of non-linear analyses such as SOM proves to be an effective tool for estimating the use of SBC in relation to meteorology. Keywords: Active transport, bike-sharing, SOM, meteorology, non-lineal analyses.
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Zittis, George, Adriana Bruggeman, Panos Hadjinicolaou, Corrado Camera, and Jos Lelieveld. "Effects of Meteorology Nudging in Regional Hydroclimatic Simulations of the Eastern Mediterranean." Atmosphere 9, no. 12 (November 30, 2018): 470. http://dx.doi.org/10.3390/atmos9120470.
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In this study, we investigated the effects of grid and spectral nudging in regional hydroclimatic simulations over the Eastern Mediterranean climate change hot-spot. We performed year-long simulations for the hydrological year October 2001–September 2002 using the Weather Research and Forecasting (WRF) model at 12-km resolution, driven by the ERA-Interim reanalyses. Six grid and three spectral nudging options were tested using a number of model configurations. Due to the large uncertainty of regional observations, we compared the model with various satellite- and station-based meteorological datasets. The effect of nudging was tested for mean weather conditions and precipitation characteristics and extremes. For certain parts of the study domain, WRF was found to reproduce both aspects of rainfall over the Eastern Mediterranean reasonably well. Our findings highlighted that, for the WRF modeling system, nudging is critical for the simulation of rainfall; however, the application of interior constraint methods was found to have different impacts on various locations and climatic regimes. For the hyperarid parts of the domain, nudging did not improve the simulation of precipitation amounts (about 20% additional drying was introduced), while it added much value for the wetter rainfall regimes of the Eastern Mediterranean (corrections of about 30%). Improvements in the simulated precipitation were mostly introduced by spectral nudging; however, this option required significant computational resources. For these ERA-Interim-driven simulations, grid nudging that involves specific humidity within the planetary boundary layer is not recommended for the simulation of precipitation since it introduces dry biases up to 75–80%.
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Vidal-Gutiérrez, Pedro, Sergio Contreras-Espinoza, and Francisco Novoa-Muñoz. "Modeling High-Frequency Zeros in Time Series with Generalized Autoregressive Score Models with Explanatory Variables: An Application to Precipitation." Axioms 13, no. 1 (December 25, 2023): 15. http://dx.doi.org/10.3390/axioms13010015.
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An extension of the Generalized Autoregressive Score (GAS) model is presented for time series with excess null observations to include explanatory variables. An extension of the GAS model proposed by Harvey and Ito is suggested, and it is applied to precipitation data from a city in Chile. It is concluded that the model provides adequate prediction, and furthermore, an analysis of the relationship between the precipitation variable and the explanatory variables is shown. This relationship is compared with the meteorology literature, demonstrating concurrence.
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Sarmadi, Fahimeh, Yi Huang, Steven T. Siems, and Michael J. Manton. "Characteristics of Wintertime Daily Precipitation over the Australian Snowy Mountains." Journal of Hydrometeorology 18, no. 10 (October 1, 2017): 2849–67. http://dx.doi.org/10.1175/jhm-d-17-0072.1.
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Abstract The relationship between orographic precipitation, low-level thermodynamic stability, and the synoptic meteorology is explored for the Snowy Mountains of southeast Australia. A 21-yr dataset (May–October, 1995–2015) of upper-air soundings from an upwind site is used to define synoptic indicators and the low-level stability. A K-means clustering algorithm was employed to classify the daily meteorology into four synoptic classes. The initial classification, based only on six synoptic indicators, distinctly defines both the surface precipitation and the low-level stability by class. Consistent with theory, the wet classes are found to have weak low-level stability, and the dry classes have strong low-level stability. By including low-level stability as an additional input variable to the clustering method, statistically significant correlations were found between the precipitation and the low-level stability within each of the four classes. An examination of the joint PDF reveals a highly nonlinear relationship; heavy rain was associated with very weak low-level stability, and conversely, strong low-level stability was associated with very little precipitation. Building on these historical relationships, model output statistics (MOS) from a moderate resolution (12-km spatial resolution) operational forecast were used to develop stepwise regression models designed to improve the 24-h forecast of precipitation over the Snowy Mountains. A single regression model for all days was found to reduce the RMSE by 7% and the bias by 75%. A class-based regression model was found to reduce the overall RMSE by 30% and the bias by 85%.
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Kotowski, Andrzej, and Bartosz Kaźmierczak. "Probabilistic Models of Maximum Precipitation for Designing Sewerage." Journal of Hydrometeorology 14, no. 6 (November 22, 2013): 1958–65. http://dx.doi.org/10.1175/jhm-d-13-01.1.
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Abstract Pluviographic measurement results from the Institute of Meteorology and Water Management (IMGW) Wrocław–Strachowice meteorological station from the years 1960–2009 constitute the basis for this paper. While conducting the statistical analysis of precipitation occurrence frequency, the criterion of interval precipitation amounts was assumed in order to isolate the intensive rainfalls from the pluviograms, which made it possible to select a number of the most intensive rainfalls in each year. A total of 514 synthetic rainfall instances were isolated, which were then were arranged according to non-increasing amounts in 16 duration intervals. This was the basis to propose the unification of the development methodology of probabilistic models for maximum precipitation amounts, reliable in the designing and verification of drain flow capacity, especially for low probability of precipitation occurrence. Maximum precipitation models for Wrocław were developed (average annual precipitation H = 590 mm).
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Junkermann, W., J. Hacker, T. Lyons, and U. Nair. "Land use change suppresses precipitation." Atmospheric Chemistry and Physics Discussions 9, no. 3 (May 8, 2009): 11481–500. http://dx.doi.org/10.5194/acpd-9-11481-2009.
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Abstract. A feedback loop between regional scale deforestation and climate change was investigated in an experiment using novel, small size airborne platforms and instrument setups. Experiments were performed in a worldwide unique natural laboratory in Western Australia, characterized by two adjacent homogeneous observation areas with distinctly different land use characteristics. Conversion of several ten thousand square km of forests into agricultural land began more than a century ago. Changes in albedo and surface roughness and the water budget of soil and the planetary boundary layer evolved over decades. Besides different meteorology we found a significant up to now overseen source of aerosol over the agriculture. The enhanced number of cloud condensation nuclei is coupled through the hydrological groundwater cycle with deforestation. Modification of surface properties and aerosol number concentrations are key factors for the observed reduction of precipitation. The results document the importance of aerosol indirect effects on climate due to nanometer size biogenic aerosol and human impact on aerosol sources.
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Junkermann, W., J. Hacker, T. Lyons, and U. Nair. "Land use change suppresses precipitation." Atmospheric Chemistry and Physics 9, no. 17 (September 10, 2009): 6531–39. http://dx.doi.org/10.5194/acp-9-6531-2009.
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Abstract. A feedback loop between regional scale deforestation and climate change was investigated in an experiment using novel, small size airborne platforms and instrument setups. Experiments were performed in a worldwide unique natural laboratory in Western Australia, characterized by two adjacent homogeneous observation areas with distinctly different land use characteristics. Conversion of several ten thousand square km of forests into agricultural land began more than a century ago. Changes in albedo, surface roughness, the soil water budget and the planetary boundary layer evolved over decades. Besides different meteorology, we found a significant up to now overlooked source of aerosol over the agriculture area. The enhanced number of cloud condensation nuclei is coupled through the hydrological groundwater cycle with deforestation. Modification of surface properties and aerosol number concentrations are key factors for the observed reduction of precipitation. The results document the importance of aerosol indirect effects on climate due to nanometer size biogenic aerosol and human impact on aerosol sources.
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Su, Chun-Hsu, Nathan Eizenberg, Peter Steinle, Dörte Jakob, Paul Fox-Hughes, Christopher J. White, Susan Rennie, Charmaine Franklin, Imtiaz Dharssi, and Hongyan Zhu. "BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia." Geoscientific Model Development 12, no. 5 (May 24, 2019): 2049–68. http://dx.doi.org/10.5194/gmd-12-2049-2019.
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Abstract. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12 km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2 m temperature, 10 m wind speed, and surface pressure observations. It also shows reduced biases in daily 2 m temperature maximum and minimum at 5 km resolution and a higher frequency of very heavy precipitation days at 5 and 25 km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10 m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (<2 km) models.
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Lonitz, Katrin, Bjorn Stevens, Louise Nuijens, Vivek Sant, Lutz Hirsch, and Axel Seifert. "The Signature of Aerosols and Meteorology in Long-Term Cloud Radar Observations of Trade Wind Cumuli." Journal of the Atmospheric Sciences 72, no. 12 (November 20, 2015): 4643–59. http://dx.doi.org/10.1175/jas-d-14-0348.1.
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Abstract The signature of aerosols and meteorology on the development of precipitation from shallow cumuli in the trades is investigated with ground-based lidar and radar remote sensing. The measurements are taken from a cloud observatory recently established on the windward shore of Barbados. Cloud microphysical development is explored through an analysis of the radar echo of shallow cumuli before the development of active precipitation. The increase of reflectivity with height (Z gradient) depends on the amount of cloud water, which varies with meteorology, and cloud droplet number concentration N, which varies with the aerosol. Clouds with a large Z gradient have a higher tendency to form precipitation than clouds with a small Z gradient. Under similar meteorological conditions, the Z gradient is expected to be large in an environment with few aerosols and small in an environment with many aerosols. The aerosol environment is defined using three methods, but only one (based on the Raman lidar linear-depolarization ratio) to measure dusty conditions correlates significantly with the Z gradient. On average, nondusty days are characterized by a larger Z gradient. However, the dust concentration varies seasonally and covaries with relative humidity. Large-eddy simulations show that small changes in the relative humidity can have as much influence on the development of precipitation within the cloud layer as large changes in N. When clouds are conditioned on their ambient relative humidity, the sensitivity of the Z gradient to dust vanishes.
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Li, Gang, Kai Xiao, Qianqian Wang, Yan Zhang, Haitao Li, and Hailong Li. "The Regulating Role of Meteorology in the Wetland-Air CO2 Fluxes at the Largest Shallow Grass-Type Lake on the North China Plain." Water 15, no. 1 (December 30, 2022): 139. http://dx.doi.org/10.3390/w15010139.
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Lakes are hot spots of carbon cycles in inland aquatic systems. As a vital factor, meteorology, including air temperature, precipitation, wind speed and evapotranspiration, is profoundly affecting or even regulating the wetland-air CO2 exchanges. Compared with some other similar lakes in China, the largest shallow grass-type Baiyangdian Lake (BYDL) acts as a vital CO2 sink on the North China Plain. The purpose of this study is to reveal the effects of meteorology on the process of CO2 flux variation. Based on the method of the eddy covariance, the daily average wetland-air CO2 flux at the BYDL over the monitoring period from April 2019 to November 2020, reached −0.63 μmol m−2 s−1, and the annual average reached −0.71 μmol m−2 s−1 from 12 April 2019 to 12 April 2020. The CO2 sink fluxes varied with the seasons and reached the maximum in summer. Temperature and evapotranspiration are two major driving factors, whose higher values can positively improve the wetland CO2 sinks. Precipitation generally coincides with the CO2 sinks, but the relatively larger summertime precipitation (0.39 m in 2020, compared with that of 0.17 m in 2019) inhibits the CO2 uptakes on longer timescales. A moderate wind speed in the range of 1.6~3.3 m s−1, promoted the CO2 sinks for the shallow grass-type lake. Compared with previous studies at the same or similar wetlands, consistent CO2 sink fluxes are found. Further in this study, the variation trends of CO2 sinks with the changing meteorological factors are revealed for the first time in this type of wetland. Once meteorology is determined under both the anthropogenic and climatic impacts, the evaluation and prediction of the lacustrine carbon cycling could be more precise. Generally, this study will serve as an important data point into the global understanding of lake carbon fluxes.
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Sodré, Giordani Rafael Conceição, and Letícia Lorena Moreira Rodrigues. "Comparação entre Estimativa da Precipitação Observada pela Técnica Cmorph e Estações Meteorológicas do Inmet em Diferentes Regiões do Brasil (Comparison Between the Observed Precipitation Estimates and Technical CMORPH Weather Stations of INMET in ...)." Revista Brasileira de Geografia Física 6, no. 2 (September 5, 2013): 301–7. http://dx.doi.org/10.26848/rbgf.v6.2.301-307.
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A Técnica CMORPH é uma das fontes atuais de dados de precipitação mais completas, onde, seu uso no meio científico é cada vez maior. Assim, nesse trabalho buscou-se avaliar as observações do CMORPH em comparação com estações meteorológicas do Instituto Nacional de Meteorologia (INMET) em diferentes regiões do Brasil, observou-se que as informações do CMORPH possuem uma acurácia muito boa, exceto na região nordeste do Brasil, onde essa técnica não consegue acompanhar as curvas pluviométricas subestimando muito a precipitação, mostrando não ser uma informação confiável para essa localidade. A B S T R A C T The Technical CMORPH is one of the current sources of precipitation data more complete, where its use in the scientific community is increasing. Thus, this study aimed to assess the remarks of CMORPH compared with meteorological stations of the National Institute of Meteorology (INMET) in different regions of Brazil, noted that the information CMORPH have a very good accuracy, except in northeastern Brazil, where this technique can not follow the curves very underestimating rainfall precipitation, showing not a reliable information for that location. Keywords: Technical CMORPH, INMET Stations, comparison.
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Islam, Tanvir, and Miguel A. Rico-Ramirez. "An overview of the remote sensing of precipitation with polarimetric radar." Progress in Physical Geography: Earth and Environment 38, no. 1 (December 24, 2013): 55–78. http://dx.doi.org/10.1177/0309133313514993.
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Recent advances in radar remote sensing of precipitation include the development of polarimetric radar, which has the capability of transmitting in both the horizontal ( H) and vertical ( V) polarization states, thus providing additional information on the target precipitation particles. Radar polarimetry has not only been proven to improve data quality and precipitation estimation, but also improves characterization of precipitation particles; thus it has great potential in weather monitoring and forecasting. Realizing the potential of this state-of-the-art technology, meteorological departments across the world are upgrading their radar networks to polarimetric capabilities. Commensurate with this new era in precipitation remote sensing, this article provides an overview of polarimetric radar measurements, emphasizing the intrinsic signatures and their association to precipitation particle shapes, sizes and distributions. The potential research and applications of polarimetric radar signatures in meteorology are discussed. A considerable number of recent peer reviewed journal articles dealing with the topic are included in the bibliography.
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Lewis, Cameron J., Yi Huang, Steven T. Siems, and Michael J. Manton. "Wintertime orographic precipitation over western Tasmania." Journal of Southern Hemisphere Earth Systems Science 68, no. 1 (2018): 22. http://dx.doi.org/10.1071/es18003.
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The wintertime (April - October) precipitation across western Tasmania (west of 147°E) has been studied for two years (2014 and 2015). Using the AWAP precipitation analysis, the average daily rainfall across western Tasmania was found to be 4.49 mm day-1 for all winter days and 6.99 mm day-1 for rain days (average precipitation greater than 1 mm day-1). Rain days were observed for ~63% of all days during the winter months. Rain days were frequently recorded after the pas-sage of a cold front, when winds are typically from the west and southwest, off the open Southern Ocean. The daily precipitation was found to be highly correlated (r = 0.55) with the 12 UTC ERA-Interim 1000 m wind speed at a point upwind of Tasmania, roughly 100 km off the west coast.Given the highly variable meteorology of the Southern Ocean storm track and the complex topography, western Tasmania is a natural testbed for studying orographic precipitation. Both locally blocked and unblocked flows, caused by changes in the low-level thermodynamic stability, occur frequently over the course of a winter with a stable environment having a lower average precipitation rate (3.66 mm day-1) than an unstable environment (8.40 mm day-1), although only a weak correlation (r = -0.07) was found between precipitation and Ĥ2(the square of non-dimensional mountain height).Simulated precipitation from the Australian Bureau of Meteorology’s ACCESS-VT model was found to underestimate the AWAP precipitation by ~20%. The greatest negative relative errors between the AWAP and ACCESS-VT precipitation in unblocked flow were in the lee of the mountains, over central and south-central Tasmania. For days when the flow was blocked, this region had large positive relative errors in precipitation. Over the upwind side of western Tasmania, ACCESS-VT underestimated precipitation in comparison to AWAP in both un-blocked and blocked flows. However, the network of surface sites is quite sparse over this region, which limits our confidence in both the ACCESS-VT and the AWAP precipitation products. A more detailed investigation is necessary to better appreciate limitations in the ACCESS-VT forecasts in this region.
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Mugnai, A., D. Casella, E. Cattani, S. Dietrich, S. Laviola, V. Levizzani, G. Panegrossi, et al. "Precipitation products from the hydrology SAF." Natural Hazards and Earth System Sciences 13, no. 8 (August 6, 2013): 1959–81. http://dx.doi.org/10.5194/nhess-13-1959-2013.
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Abstract. The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) was established by the EUMETSAT Council on 3 July 2005, starting activity on 1 September 2005. The Italian Meteorological Service serves as Leading Entity on behalf of twelve European member countries. H-SAF products include precipitation, soil moisture and snow parameters. Some products are based only on satellite observations, while other products are based on the assimilation of satellite measurements/products into numerical models. In addition to product development and generation, H-SAF includes a product validation program and a hydrological validation program that are coordinated, respectively, by the Italian Department of Civil Protection and by the Polish Institute of Meteorology and Water Management. The National Center of Aeronautical Meteorology and Climatology (CNMCA) of the Italian Air Force is responsible for operational product generation and dissemination. In this paper we describe the H-SAF precipitation algorithms and products, which have been developed by the Italian Institute of Atmospheric Sciences and Climate (in collaboration with the international community) and by CNMCA during the Development Phase (DP, 2005–2010) and the first Continuous Development and Operations Phase (CDOP-1, 2010–2012). The precipitation products are based on passive microwave measurements obtained from radiometers onboard different sun-synchronous low-Earth-orbiting satellites (especially, the SSM/I and SSMIS radiometers onboard DMSP satellites and the AMSU-A + AMSU-B/MHS radiometer suites onboard EPS-MetOp and NOAA-POES satellites), as well as on combined infrared/passive microwave measurements in which the passive microwave precipitation estimates are used in conjunction with SEVIRI images from the geostationary MSG satellite. Moreover, the H-SAF product generation and dissemination chain and independent product validation activities are described. Also, the H-SAF program and its associated activities that currently are being carried out or are planned to be performed within the second CDOP phase (CDOP-2, 2012–2017) are presented in some detail. Insofar as CDOP-2 is concerned, it is emphasized that all algorithms and processing schemes will be improved and enhanced so as to extend them to satellites that will be operational within this decade – particularly the geostationary Meteosat Third Generation satellites and the low-Earth-orbiting Core Observatory of the international Global Precipitation Measurement mission. Finally, the role of H-SAF within the international science and operations community is explained.
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Mendel, M. "Meteorology in field artillery ballistic calculations." Journal of Physics: Conference Series 2090, no. 1 (November 1, 2021): 012149. http://dx.doi.org/10.1088/1742-6596/2090/1/012149.
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Abstract The most important meteorological data are:ambient temperature, precipitation quantity, air humidity, amount and type of clouds, atmospheric pressure, wind direction and speed, visibility, weather phenomena. These coefficients impact the effectiveness of various combat activities, especially those conducted in an open space. Knowledge of future weather conditions is essential for planning the location, calculating times, choice of means, and other aspects relevant to the upcoming operations. Taking weather conditions into account is vital, specifically when it comes to planning combat operations, where the accuracy in cooperation is of paramount importance. Rocket forces and artillery is a particular type of armed forces where weather conditions are critical. The effectiveness of artillery depends on ballistic calculation precision, and so knowledge of atmospheric conditions is fundamental. Atmospheric data are collected from sounding using a single probe attached to a balloon. It is generally known that particular meteorological parameters change in a smooth spatial manner depending on various coefficients. Information about the atmosphere collected by a single probe may be insufficient, due to the possibility of a balloon drifting away from the area of interest, and the calculations are based on data received from its probe. In this paper, I will suggest a method for preparing artillery use meteorologically, which takes into account the distribution of particular meteorological coefficients over a given area.
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Новак, В. Г. "AGRICULTURAL METEOROLOGY TERMS 2020–2021 AGRICULTURAL YEAR FROM DATA OF WEATHER-STATION UMAN." Bulletin of Uman National University of Horticulture 1 (August 2022): 23–26. http://dx.doi.org/10.31395/2310-0478-2022-1-23-26.
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The article presents data on air temperature and precipitation from October 2020 to September 2021, as well as analyzes them in comparison with the average long-term data (for 30 years - from 1991 to 2020). A characteristic feature of this agricultural year was a favorable temperature background and sufficient rainfall. The average air temperature in the agricultural year was 9.2° С, e it was only 0.4° С higher than the long-term average. At the same time, in the cold period (December – March) the total excess temperature was 1.4° С, and in the warm period (April – September) the total decrease was 1.9° С. The total amount of precipitation for the year was 655.7 mm, which is 69 mm higher than the long-term average.
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Chakraborty, A., S. K. Satheesh, R. S. Nanjundiah, and J. Srinivasan. "Impact of absorbing aerosols on the simulation of climate over the Indian region in an atmospheric general circulation model." Annales Geophysicae 22, no. 5 (April 8, 2004): 1421–34. http://dx.doi.org/10.5194/angeo-22-1421-2004.
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Abstract. The impact of anthropogenic absorbing aerosols (such as soot) on the climate over the Indian region has been studied using the NCMRWF general circulation model. The absorbing aerosols increase shortwave radiative heating of the lower troposphere and reduce the heating at the surface. These effects have been incorporated as heating of the lower troposphere (up to 700hPa) and cooling over the continental surface based on INDOEX measurements. The heating effect is constant in the pre-monsoon season and reduces to zero during the monsoon season. It is shown that even in the monsoon season when the aerosol forcing is zero, there is an overall increase in rainfall and a reduction in surface temperature over the Indian region. The rainfall averaged over the Tropics shows a small reduction in most of the months during the January to September period. The impact of aerosol forcing, the model's sensitivity to this forcing and its interaction with model-physics has been studied by changing the cumulus parameterization from the Simplified Arakawa-Schubert (SAS) scheme to the Kuo scheme. During the pre-monsoon season the major changes in precipitation occur in the oceanic Inter Tropical Convergence Zone (ITCZ), where both the schemes show an increase in precipitation. This result is similar to that reported in Chung2002. On the other hand, during the monsoon season the changes in precipitation in the continental region are different in the SAS and Kuo schemes. It is shown that the heating due to absorbing aerosols changes the vertical moist-static stability of the atmosphere. The difference in the precipitation changes in the two cumulus schemes is on account of the different responses in the two parameterization schemes to changes in vertical stability. Key words. Atmospheric composition and structure (aerosols and particles) – Meteorology and atmospheric dynamics (tropical meteorology; precipitation)
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Souza Júnior, Sérgio André de, Pedro Victor Cabral de Freitas, Yohanna do Valle Hamberger, Luisa Weber Bisol, and Fábio Gomes de Matos e. Souza. "Low temperature, high relative humidity and higher precipitation are associated with a higher number of deaths from COVID-19." Research, Society and Development 11, no. 4 (March 24, 2022): e49111427616. http://dx.doi.org/10.33448/rsd-v11i4.27616.
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Background: Meteorological variables play a major role in the transmission of infectious diseases such as coronavirus disease 2019 (COVID-19). Objective: To analyze the correlation between climatic variables and COVID-19 deaths/cases. Methods: An exploratory-descriptive study based on secondary data on deaths, cases of COVID-19 and climatic variables from March 2020-May 2021 in Fortaleza, Brazil. Data from the COVID-19 surveillance system of the Ministry of Health were used. The climatic indicators were extracted from the National Institute of Meteorology. The variables under study were temperature (minimum, mean and maximum in °C), relative air humidity (%), total precipitation (mm) and total daily insolation (h). Pearson's correlation and the linear regression model were used for statistical analysis. Correlations were considered significant when P ≤ 0.05 and a 95% confidence interval was adopted. Results: All meteorologic variables were correlated with deaths from COVID-19, temperature minimum (r = -0,126; P < 0,01), mean temperature (r = -0,146; P < 0,05), maximum temperature (r = -0,190; P < 0,001), insolation (r = -0,214; P < 0,001), precipitation (r = 0,216; P < 0,001) and relative humidity (r = 0,348; P < 0,001). In relation to the new cases of COVID-19, only maximum temperature (r = -0,116; P < 0,05), insolation (r = -0,141; P < 0,01) and relative humidity (r = 0,231; P < 0,001) were correlated are significantly. Conclusion: There were significant correlations between meteorological variables and COVID-19 deaths/cases. It was found that meteorologic variables had the most influence on COVID-19 deaths.
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Wei, Chih-Chiang. "RBF Neural Networks Combined with Principal Component Analysis Applied to Quantitative Precipitation Forecast for a Reservoir Watershed during Typhoon Periods." Journal of Hydrometeorology 13, no. 2 (April 1, 2012): 722–34. http://dx.doi.org/10.1175/jhm-d-11-03.1.
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Abstract The forecast of precipitations during typhoons has received much attention in recent years. It is important in meteorology and atmospheric sciences. Hence, the study on precipitation nowcast during typhoons is of great significance to operators of a reservoir system. This study developed an improved neural network that combines the principal component analysis (PCA) technique and the radial basis function (RBF) network. The developed methodology was employed to establish the quantitative precipitation forecast model for the watershed of the Shihmen Reservoir in northern Taiwan. The results obtained from RBF, multiple linear regression (MLR), PCA–RBF, and PCA–MLR models included the forecasts of L-ahead (L = 1, 3, 6) hourly accumulated precipitations. The deducted prediction results were compared in terms of four measures [mean absolute error (MAE), RMSE, coefficient of correlation (CC), and coefficient of efficiency (CE)] and four skill scores [percentage error (PE), area-weighted error score (AWES), bias score (BIAS), and equitable threat score (ETS)]. The results showed that predictions obtained using RBF and PCA–RBF were better than those produced by MLR and PCA–MLR. Although both RBF and PCA–RBF can provide good results on average, the network architecture and the learning speed of the PCA–RBF network are superior to those of the simple RBF network. This is because PCA technique could greatly reduce the input parameters and simplify concurrently the network structure. Consequently, the PCA–RBF neural networks can be regarded as a reliable model for predicting precipitation during typhoons.
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Handoko, Eko Yuli, Akbar Kurniawan, Putra Maulida, and Norma Aji Cemara. "Precipitation Water Vapour Variation in the East Java Region from Data CORS Using GIPSY." IOP Conference Series: Earth and Environmental Science 936, no. 1 (December 1, 2021): 012001. http://dx.doi.org/10.1088/1755-1315/936/1/012001.
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Abstract The Global Navigation Satellite System is being developed as an atmospheric remote sensing system through the calculation of Zenith Total Delay. The development of the Continous Operating Reference Station encourages research investigations into Zenith Tropospheric Delay with continuous data and good spatial resolution. This research studies the characteristics of spatial and temporal variations of the Zenith Wet Delay in East Jawa. The case study in East Jawa Province uses 16 Continous Operating Reference Stations. As a comparison, meteorological data from the Badan Meteorologi, Klimatologi, and Geofisika stations are used.The Zenith Total Delay and Zenith Wet Delay values from the Continous Operating Reference Station data are calculated using GIPSY 6.4 Software. The Zenith Wet Delay values are gridded using the kriging method with the size of the grids being 0,25 x 0,25. The ZWD value comparison from the Continous Operating Reference Station and meteorology data has a strong correlation with a coefficient value of 0,712. The mean of Zenith Wet Delay’s trend is increasing by about 0,712 mm/yr. The characteristics of the spatial and temporal variations of the ZWD value are influenced by the monsoon of Asia-Australian, which causes dry and rainy seasons, global phenomena such as El Nino and La Nina, rainfall, local meteorological conditions such as temperature and humidity, weather, and the topography of the stations.
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Santos, Eliane Barbosa, and Gilberto Barbosa Diniz. "OCEANIC INDICES AND THEIR RELATIONS WITH THE MONTHLY PRECIPITATION IN RIO GRANDE DO SUL STATE, BRAZIL." Revista Brasileira de Geofísica 32, no. 3 (September 1, 2014): 371. http://dx.doi.org/10.22564/rbgf.v32i3.496.
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ABSTRACT. Climatic indices were obtained from the Sea Surface Temperature (SST) in the Atlantic and Pacific oceans, available on the website of the EarthSystem Research Laboratory (ESRL), which belongs to the Physical Science Division (PSD) of the National Oceanic and Atmospheric Administration (NOAA). Theseindices were created to represent the variations of SST in the Southwest Atlantic, Equatorial Pacific and South Pacific, with the aim of studying their influence on precipitationvariability in the state of Rio Grande do Sul (RS), Brazil. The precipitation dataset was obtained from the National Institute of Meteorology – Instituto Nacional de Meteorologia (INMET – 8◦ Distrito de Meteorologia – Porto Alegre) and State Foundation for Agricultural Research – Fundação Estadual de Pesquisas Agropecuárias(FEPAGRO). Afterwards, there were made cross-correlations between the indices, and correlations between the indices and the precipitations of the RS for the period 1948-2009. The precipitation correlations were simultaneous and lagged, with the indices preceding the precipitation up to 2 months, to determine the predictive powerof the indices, and estimate the evolution of this variable in the spatiotemporal domain. The index of the Southwest Atlantic SST was not significant for the precipitationof RS in the months from November to February. The highest degree of association between the indices of the Equatorial Pacific and South Pacific with precipitationwere found in November. In general, it was observed that the significant coefficients in the simultaneous correlations remained until lag 2, i.e., the SST in the Equatorial Pacific and South Pacific can be good predictors of the rain quality for the state of the RS, up to 2 months in advance.Keywords: Equatorial Pacific, South Pacific, Southwest Atlantic, correlation analysis. RESUMO. Foram determinados índices climáticos obtidos da Temperatura da Superfície do Mar (TSM) nos oceanos Atlântico e Pacífico, disponíveis na página dainternet do Earth System Research Laboratory (ESRL), pertencente à Physical Science Division (PSD) da National Oceanic and Atmospheric Administration (NOAA).Esses índices foram criados para representar as variações de TSM no Atlântico Sudoeste e Pacífico Equatorial e Sul, com o objetivo de estudar suas influências navariabilidade da precipitação do Estado do Rio Grande do Sul (RS). Os dados de precipitação foram obtidos do Instituto Nacional de Meteorologia (INMET, 8◦ Distritode Meteorologia – Porto Alegre) e Fundação Estadual de Pesquisas Agropecuárias (FEPAGRO). Posteriormente, foram realizadas correlações cruzadas entre os índices, e correlações entre os índices e as precipitações do RS para o período de 1948-2009. As correlações com as precipitações foram simultˆaneas e com defasagem, comos índices precedendo a precipitação em até 2 meses, para determinar o caráter preditivo do índice em questão, e estimar a evolução dessa variável no domínio espaço temporal.O índice das TSMdo Atlântico Sudoeste não foi significativo para as precipitações do RS nos meses de novembro a fevereiro. Omaior grau de associação entreos índices do Pacífico Equatorial e Sul com as precipitações foi encontrado em novembro. No geral, foi observado que os coeficientes significativos nas correlações simultâneas, permaneceram até o lag 2, ou seja, as TSM do Pacífico Equatorial e Sul podem ser bons previsores da qualidade da chuva para o Estado do RS, com até 2 meses de antecedência.Palavras-chave: Pacífico Equatorial, Pacífico Sul, Atlântico Sudoeste, análise de correlação.
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Pu, Kang, Xichuan Liu, Hongbing He, Yu Sun, Shuai Hu, and Yi Wu. "Microphysical Characteristics of Winter Precipitation in Eastern China from 2014 to 2019." Water 12, no. 3 (March 24, 2020): 920. http://dx.doi.org/10.3390/w12030920.
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To improve solid precipitation monitoring in the hydrology and meteorology field, 1-min precipitation data observed by the PARticle SIze VELocity (PARSIVEL) disdrometer in Nanjing, eastern China, from February 2014 to February 2019 for all days with solid precipitation, were used to study the microphysical characteristics of winter precipitation. In this study, the empirical V-D (velocity–diameter) relationships and observed surface temperature are used for matching precipitation types, and the precipitation data are divided into rain, graupel, wet snow and dry snow. The results show that dry snow and wet snow have maximum Dm (mass-weighted mean diameter) and minimum log10Nw (normalized intercept parameter), while rain shows the opposite. Additionally, the μ-Λ (shape parameter–slope parameter) curve of dry snow and wet snow is very close, and the μ value of dry snow and wet snow is higher than that of graupel and higher than that of rain for the same Λ value. Furthermore, the Ze-S (equivalent reflectivity factor–precipitation intensity) relationships among different types of precipitation are significantly different. If only the Ze-S relationship of rain is used for quantitative precipitation estimation (QPE), then, for small precipitation intensity, solid precipitation will be overestimated, while, for large precipitation intensity, it will be underestimated.
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Kumar, R., M. Naja, G. G. Pfister, M. C. Barth, and G. P. Brasseur. "Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem): set-up and meteorological evaluation." Geoscientific Model Development 5, no. 2 (March 20, 2012): 321–43. http://dx.doi.org/10.5194/gmd-5-321-2012.
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Abstract. The configuration and evaluation of the meteorology is presented for simulations over the South Asian region using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Temperature, water vapor, dew point temperature, zonal and meridional wind components, precipitation and tropopause pressure are evaluated against radiosonde and satellite-borne (AIRS and TRMM) observations along with NCEP/NCAR reanalysis fields for the year 2008. Chemical fields, with focus on tropospheric ozone, are evaluated in a companion paper. The spatial and temporal variability in meteorological variables is well simulated by the model with temperature, dew point temperature and precipitation showing higher values during summer/monsoon and lower during winter. The index of agreement for all the parameters is estimated to be greater than 0.6 indicating that WRF-Chem is capable of simulating the variations around the observed mean. The mean bias (MB) and root mean square error (RMSE) in modeled temperature, water vapor and wind components show an increasing tendency with altitude. MB and RMSE values are within &pm;2 K and 1–4 K for temperature, 30% and 20–65% for water vapor and 1.6 m s−1 and 5.1 m s−1 for wind components. The spatio-temporal variability of precipitation is also reproduced reasonably well by the model but the model overestimates precipitation in summer and underestimates precipitation during other seasons. Such a behavior of modeled precipitation is in agreement with previous studies on South Asian monsoon. The comparison with radiosonde observations indicates a relatively better model performance for inland sites as compared to coastal and island sites. The MB and RMSE in tropopause pressure are estimated to be less than 25 hPa. Sensitivity simulations show that biases in meteorological simulations can introduce errors of &pm;(10–25%) in simulations of tropospheric ozone, CO and NOx. Nevertheless, a comparison of statistical metrics with benchmarks indicates that the model simulated meteorology is of sufficient quality for use in chemistry simulations.