Theoretical and Applied Climatology最新文献

This study investigates the origins and the atmospheric circulation patterns that led to the occurrence of Wet-Cold compound events (WCCEs) recorded by the Hellenic National Meteorological Service (HNMS) between 1980 and 2004. The study employed two methods to provide insights into the issue. The first method involved identifying clusters from backward trajectories (BTs) at three heights above the arrival point (500, 1500 and 5500 m). The second method aimed at detecting weather patterns (WPs) that result from the clustering of atmospheric pressure at sea level (SLP) and the geopotential height (GH500) at 500 hPa using ERA5 reanalysis data. To detect clusters for both methods, k-means clustering was applied. The analysis of backward trajectories produced seven clusters of BTs at each height level. Most of these clusters originated from the northwest or north, with medium, short, and long-distance clusters observed at the heights of 500 m, 1500 m and 5500 m, respectively. Despite analysing the temporal data, no clear connection was established between the clusters and months. From the cluster of GH500 and SLP variables for 94 different dates, we derived three main weather patterns. All weather patterns showed high GH500 values in Western Europe and lower GH500 values in Eastern Europe. Although SLP values differed significantly among the clusters, they helped to identify distinct weather patterns. Finally, we found that on 7 out of a total of 94 different dates with WCCEs, large amounts of moisture are transported through the atmosphere to Greece over long distances by atmospheric rivers (ARs).

Atmospheric convection across the northern inter-Americas is modulated by trade-wind subsidence and subtropical easterly waves from June to October. Northward migration of the equatorial trough is coupled to the meridional circulation (MC) and surface temperatures above 27ºC. Forming a MC index via S-N height sections of total and anomalous streamfunction, statistical relationships are examined which focus on Jun-Oct season when the South American monsoon is quiescent. Both east Pacific and tropical north Atlantic exhibit cool ocean – dry atmosphere response to an intensified MC. During periods of faster MC, composite humidity is depleted over the Caribbean 10–25 N in conjunction with westerly wind shear, thereby limiting atmospheric convection. The ocean response to intensified MC is evaporative cooling and a deep layer of increased salinity in the Caribbean, that may sustain anomalous air-sea interactions. Long-term trends reveal intensification of the MC in boreal summer: rising over the Amazon, subsiding over the Caribbean, inter-connected by lower and upper airflows. The annually pulsed MC conspires with inter-decadal trends to produce many of the features presented.

The analysis of extreme precipitation events plays a crucial role in the management of water resources, infrastructure, public water supply, agriculture, fire control, and public health. For an accurate characterization of precipitation events using historical series, the observed variations must be solely attributable to weather and climate conditions. This study aimed to identify homogeneous gauge stations in Paraná State, southern Brazil, based on four statistical tests (SNHT, Buishand, Pettitt, and Von Neumann) and conduct a homogeneity analysis of daily rainfall data. Missing values were imputed into the time series, and only stations with up to 25% of data gaps were included. Of the 482 stations analyzed in the state, 73.7% (n = 355) demonstrated homogeneity, 11.6% (n = 56) were considered doubtful, and 14.7% (n = 71) were deemed suspect. The highest number of homogeneity breaks was recorded from 1990 to 2005. The number of breaks during this period was estimated at 75 (59.1%) by SNHT, 86 (67.7%) by the Buishand test, and 89 (70.1%) by the Pettitt test. The year with the highest number of homogeneity breaks was 1998, with 81 breaks identified by the Pettitt test. These breaks may be related to El Niño and La Niña phenomena, given that a large sample of rainfall stations was analyzed in the study.

This study investigates the variability and forecasting ability of time-trend in mean annual surface air temperatures in Greece. Using Gaussian time-trend models, we first investigate some basic statistical characteristics associated with time-trends, such the mean and variance. This can reveal whether temperatures’ mean and volatility changes are associated with time. To do so, we have used mean measures of the minimum and maximum air temperatures observed at several meteorological stations of the Hellenic Meteorological Service located in Greece for the 1960-2010 period. As a second experiment, we investigate whether temperature trends are forecastable or not using various Gaussian time-trend and no-time-trend models. The results are highly significant since they reveal the seasons, the periods and the type of models for which the inter-annual trends out-perform the no-trend ones. Moreover, they also show the statistical characteristics, such as the mean and variability of the time-trend under various seasons and sub-periods.

El Niño Southern Oscillations (ENSO), being the largest global air-sea interaction phenomena, has a profound effect on global monsoon. In this study, for the first time we have examined the ENSO – Monsoon relation through nonlinear kinetic energy (KE) exchanges outlook across scales. Indian summer monsoon (ISM) and Western North Pacific Summer Monsoon (WNPSM) are considered to be the two major components of global monsoon on which ENSO has a huge impact. The ENSO – Monsoon nonlinearity can be explored by unraveling the unstable (stable) relation between ENSO and Monsoon during El Niño (La Niña) period through the mechanism of scale interactions among El Niño / La Niña, dominant high (HFO) and low frequency oscillation (LFO) considering ENSO itself as a LFO of time period 12–18 months. It is found from the analysis that more (less) KE is transferred to synoptic scale and 10-20 day LFO from El Niño 1997-98 compared to that from 2015 - 16 episode over ISM (WNPSM) region. Moreover, the opposite energy exchange between El Niño and 30-60 day wave is observed over these regions, attributing to contrasting rainfall variation over ISM and WNPSM zone. Sharp (comparatively less) variability in energy exchange among El Niño (La Niña), HFO and LFO over ISM and WNPSM regions make El Niño – Monsoon relation highly unstable whereas La Niña – Monsoon relation a stable one. Unveiling El Niño-ISM, El Niño-WNPSM, La Niña-ISM and La Niña-WNPSM relations in terms of inter-scale KE exchanges for the two El Niño and two La Niña events may lead to enhance the understanding of ENSO-monsoon nonlinearity. This work will make an avenue for further research in the space of nonlinearity between the two large scale systems that may be expected to be more complex due to the global warming and climate change as a futuristic study.

This study has been undertaken to predict the Surface Latent Heat Flux (SLHF) over the North Indian Ocean (NIO) in the future period (2020–2099) under different emission scenarios. For this 12 Coupled Model Inter-comparison Project 6 (CMIP6), Global Climate Models (GCMs) SLHF and ERA5 SLHF data have been used. It is observed that the SLHF is going to increase in the far future (2060–2099) under all emission scenarios probably due to higher warming. In the near future (2020–2059) particularly in the first half (2020–2039) a clear fall in the SLHF is noticed. It is also observed that the SLHF rise under the Shared Socioeconomic Pathways 5 (SSP5) is more than that under the SSP2 in the far future due to higher warming. Seasonal variation of the SLHF depicts that under SSP5 in the far future, the rise in the SLHF is the maximum in MAM. The rise of the SLHF in the far future can be attributed to the rise in the SST over the NIO but the reason for the fall of the SLHF in the first half of the near future is not clear.

Droughts and climate change are causing severe and persistent dust storms in the arid and hot regions. The potential existence of significant relationships between the Oceanic Niño Index (ONI), Indian Ocean Dipole (IOD), and the MERRA-2 dust column mass density data are thus investigated in the State of Kuwait during 1990–2021 as a study case in the hot and arid regions. The findings show that the correlation starts from ONI-DJF (December–January-February) with the Pearson test value of -0.36 and increasing to a value of -0.55 on ONI-AMJ (April-May-June), the same results were obtained when applying the Spearman correlation test. The correlation exists between the July dust column mass density and IOD-January with a value of -0.484 and − 0.544 over Pearson and ' ‘Spearman’s test, respectively, all estimated p-values are lower than 0.05. The results of the One-Way ANOVA show that the output is pretty straightforward and statistically significant at p > 0.05, which was confirmed by the nonparametric Kruskal–Walli’s test and Mann-Whitney Test. This considerable correlation means that active dust storms are linked with La Niña, while light dust storms occur during the El Niño event. A positive correlation occurs between precipitation and ONI - SON (September-October-November), while a negative correlation is found between precipitation and IOD-July. Our preliminary findings in this paper indicate that an appearance of -0.7°C in ONI-DJF could serve as a definitive marker of the La Nina phase and an indicator for at-risk communities to prepare for the expected activity dust storm.

Punjab state has set the standard for agricultural growth and was the initiator of the Green Revolution in India, producing the highest quality wheat, rice, cotton and other crops. Although Punjab’s land is fertile but over time, but ecological resources, i.e. climate, soil and groundwater have got altered due to which farmers are still unaware to decide which crops are best to grow in their areas for the highest yields and highest financial returns. Agro-Eco-Resource zonation (AERZ) is a classification technique that uses meteorological, soil and groundwater data of the targeted region for proper zonation with higher priority towards crop suitability factors. In the present study 8 major factors (minimum temperature, maximum temperature, rainfall, soil organic carbon, soil texture, soil pH, groundwater depth and groundwater level fluctuations) were used for creating zones for the entire state of Punjab. Analytical Hierarchy Process (AHP) was used for assigning weightage to each factor and the inverse distance weighting interpolation was used to create the thematic maps after importing the data into a Geographic Information Systems (GIS) using attribute tables. These maps were then superimposed so that it would be possible for zoning by using all the stated factors. Based on the degree of suitability for agriculture from highest to lowest, AERZ were identified on a final map. The AERZ map were then validated by comparing them with the rice and wheat productivity data maps. The state was classified into 4 major classes, wherein the zone 4 had conditions most suitable for agricultural crops while zone 1 had constraints and so was least suitable for cultivating crops. The geographical area under zone 3 was nearly 50% followed by zone 4 (30%), zone 2 (19%) and zone 1 (0.7%). The roadmap for sustaining the agricultural productivity in the state revealed that cultivation of resource intensive crops (Rice/ Basmati rice, Wheat, Maize and Vegetables) should be curtailed to only 30% (zone 4) of the total geographical area of the state. Further, the agro-eco-resource constrained ~ 1% (zone 1) of the land area may preferably be kept fallow or used for forest cover. Therefore, AERZ using AHP and GIS techniques is a useful tool for agricultural planning and management. It helps in identifying the best crops that can be grown in a particular region, which in turn helps in improving the efficiency and productivity of agricultural production.

We analyzed long-term soil CO₂ concentrations, soil temperature and moisture, with simultaneous canopy microclimate measurements, in a subtropical 20 years old oak forest in Huainan, China, in the East Asian monsoon region. Daily soil CO₂ effluxes were quantified using the gradient method. We investigated the relationship between soil CO₂ concentrations and efflux, and both soil temperature and water content, and the effects of phenological stages and seasons. explored how abiotic factors (soil temperature and moisture) along with LAI influence soil CO₂ efflux. Subsurface soil CO₂ concentration and efflux showed clear seasonal variations, with an increase in spring to a small peak, reaching a maximum in summer, then a decrease in autumn but with a sharp second peak when precipitation season began, and finally a decrease to a minimum in winter. In this forest ecosystem, the calculated soil subsurface CO₂ efflux at 0.02 m averaged 1.40 µmol m⁻² s⁻¹ and ranged from 0.24 to 4.11 µmol m⁻² s⁻¹ over a whole year from September 1, 2018 to August 31, 2019. Seasonal fluctuations in soil CO₂ concentrations and efflux were primarily influenced by soil temperature, with soil moisture exerting secondary effects throughout the entire study period and in most cases. However, during warm, dry periods like summer or maturity stages, soil water content emerged as the primary factor governing CO₂ efflux. The combined influences of soil temperature and water content were different in different phenological stages, and highly regulated by drought and rains. For instance, in the phenological mature stage, soil CO₂ concentration was mainly affected by soil water content. In the mature stage, soil CO₂ efflux correlated more closely with soil water content than with soil temperature following a spring drought episode.

By using ERA5 reanalysis data, this paper combined existing research definitions of gale processes to analyze the variation characteristics of gale processes occurring in the South China Sea region, and to study the response of the gale process to East Pacific sea surface temperature. The results indicate that the gale process shows the significant annual variation and the most frequent in winter and least frequent in summer. While there is no significant trend in the frequency of gale processes in each season. There is a significant negative correlation between the frequency of gale process and the East Pacific sea surface temperature in spring, autumn, and winter. When the sea surface temperature in the eastern Pacific rises abnormally, the frequency of gale processes in the South China Sea decreases. When abnormally high, the frequency of gale process in the South China Sea increases. In summer, this relationship is the opposite. When sea surface temperature is abnormal, the anomalous anticyclone triggered in the western Pacific, and has a weakening effect on the prevailing winds in the South China Sea, leading to a reduction in high wind speed and gale events, thereby reducing the frequency of gale process.