Theoretical and Applied Climatology最新文献

Studies have explored concurrent hot extremes and dry events across the world, however, the modulation of average temperature regimes during droughts is lacking. This study explores the differential intensification rates in average temperatures in the historical past and projected future for different climatologies (dry, wet, and average) over the Indian subcontinent, and the intensification rates are linked with established atmospheric feedback mechanisms. Thereafter, future differential shifts in temperatures associated with different climatologies were studied under climate change for the 2 °C and 3 °C warming worlds using CMIP6 simulations. Results show that temperature intensification rates are much more pronounced under dry/wet climatology than average climatology. Dry climatology temperatures (Td) exhibit extensive cooling trends in northern India while warming trends are reported in southern India. Wet climatology temperatures (Tw) show extensive warming trends in northern India. Further, analysis of atmospheric moisture and aridity metrics such as vapor pressure deficit (VPD) and relative humidity (RH) show a stronger linkage with temperatures during the dry/wet climatology compared to the long-term average. Multi-model shifts under climate change project cooling and warming Td shifts under 2 °C and 3 °C levels, respectively with greater pronounced temperature shifts in northern regions. The results of this study have implications for water resource management, drought risk reductions, and mitigation of agricultural crop losses.

Algeria, a semi-arid Mediterranean country, is distinguished by a more marked interannual variability in solid inputs compared to liquid inputs. This study aimed to comprehensively analyze hydrometeorological variables, such as rainfall, suspended sediment load, and flood flows in the Wadi Mina basin (6048 km²), using both traditional and advanced statistical techniques. These techniques included the MK trend tests MMK, and TFPWMK, as well as newer methods such as ITA and IPTA. To identify breakpoints, the CUSUM test and the SQ-MK test were used. The study was based on monthly data covering 40 years of rainfall (1970–2010) and 41 years of data on flood flows and suspended sediment load (1969–2010). The results indicated stable annual rainfall across the stations, suggesting a consistent rainfall regime over time. However, notable variability in sediment loads and flood flows was observed, with stations like Ain Hamara, Sidi Aek Djilali, and Wadi El Abtal displaying marked decreases in annual sediment loads, hinting at effective erosion control or natural attenuation of erosive processes. In contrast, a significant increase in flood events was recorded at Ain Hamara, attributed to climatic fluctuations or land use changes affecting runoff. Monthly analyses further demonstrated the enhanced sensitivity of ITA and IPTA over traditional methods, effectively uncovering subtle trends not detected by MK, MMK, and TFPWMK. For example, increasing rainfall trends during winter at Takhmert station and significant sediment transport patterns at Ain Hamara during colder months suggested dynamic seasonal hydrological behaviors. Additionally, critical insights into abrupt changes were revealed through CUSUM and SQ-MK tests, such as a pivotal shift in flood regimes at Takhmert in 2003 and a critical change in rainfall patterns at Ain Hamara in 2008, necessitating adjustments in water management and agricultural practices.

Increasing population density leads to higher building density and significant alterations in urban land use and land cover (LULC). Particularly, the expansion of built-up areas substantially influences land surface temperature (LST), contributing to the formation of urban heat islands (UHI). This study aims to determine the relationship between UHI formations and the presence of urban grey infrastructure versus green spaces over a 22-year period. The research involves developing maps of NDVI, NDBI, LULC, LST, UHI, and UTFVI using Landsat 4–5 TM and 8–9 OLI/TIRS satellite images for the years 2000 and 2022. Data processing was conducted using ArcGIS Desktop and ERDAS Imagine, with results assessed in MATLAB and Excel. The findings reveal significant changes in NDVI, NDBI, and LST in the study area over time, highlighting the UHI effect characterized by a temperature increase of approximately 5–6 °C. Conversely, the UTFVI study indicated an improvement in ecological conditions in some areas by 2022 due to increased NDVI. This study underscores the importance of comprehensive land-use strategies to promote a sustainable and climate-resilient future for Chandigarh by mitigating the UHI effect through the enhancement of green vegetation in regions with rising LST. Furthermore, the LULC mapping accuracy is tested with an outstanding precision of 95%.

Nondimensionalization, a theoretical approach for establishing interconnections among parameters within a set of equations, has proven to be an effective tool for the analysis of atmospheric turbulence. By applying nondimensionalization to turbulence equations, a concise form of dimensionless turbulence functions can be obtained. This process also yields several dimensionless parameters, defined as combinations of characteristic scales. From the dimensionless tensor ({B}) and vector ({{varvec{beta}}}_{theta}) introduced in this study, the characteristic length scale, ({z}^{s}), can be defined as an alternative of length scale in similarity theories. Using the data from observational station in Horqin Sandy Land, quantified verifications of similarity relationships are carried out. The dimensionless parameters derived from nondimensionalization is not only in accordance with traditional turbulence theories but also facilitate the derivation of relationships among other dimensionless parameters. This reveals new similarity relationships that supplement the Monin–Obukhov theory. Under conditions of flat terrain and steady motions, the new length scale gives rise to similarity relationships exhibiting “4/3” exponential and near-linear patterns, which are associated with turbulent transport. These results make it possible to obtain the turbulent fluxes directly from the statistics of meteorological elements, even in stable stratifications. Consequently, the method of nondimensionalization can be taken as a reference in parameterization schemes of turbulence and climate models, and is fruitful in prospect of further study on atmospheric turbulence.

Climate models are indispensable tools for decision-making, yet their efficacy in characterizing climatic conditions in regions of complex topography, such as Central-Western Argentina (CWA), remains challenging. Therefore, the main objective of this study was to evaluate mean and extreme values of temperature and precipitation simulations from a set of CMIP6 climate models in CWA. The mean values were compared against CRU TS 4.05 for the period 1950–2014; and the extreme values against ERA5 for the temperature and ERA5, CPC, and CHIRPS for the precipitation during 1981–2010. To evaluate the mean values, we considered several statistical metrics that accounted for the representation of the annual cycle, the long-term trends, and the spatial patterns, followed by a selection of the climate models that best represent the region. Subsequently, we analyzed 20 climate extreme indices using Taylor Diagrams and box-and-whiskers plots. The CMIP6 models tended to exhibit a wet bias over CWA, with temperature simulations warmer (colder) than observations over the Andes (Lowlands). Moreover, most models adequately captured the increase in temperature, as well as the increase in precipitation in the lowlands and its decrease in the Andes. From the set of 24 precipitation and 12 temperature simulations, we evaluated the performance for the representation of climate extremes, finding that most models had difficulties with the quantification of indices based on percentiles. This climate information can be valuable to obtain more accurate climate projections for CWA and to aid decision-making in a region with significant wine production and high reliance on water resources.

Inter-basin water transfers are implemented to counter the uneven geographical distribution of natural water sources. This paper’s novelty consists of providing a system-dynamics framework to evaluate inter-basin water transfers based on integrated water governance. The Big Karun Basin, Iran, has long been of interest to water managers due to its discharge potential. It houses several water-transfer projects that are under operation or under study for possible future implementation. This study implements system dynamics modeling (SDM) in the Big Karun Basin considering existing inter-basin water transfers. This study’s results estimate an average annual 8 to 10 billion cubic meters of water are transfered from the Karun River to the Persian Gulf. Part of this flow can be used to meet some of the water demands in Iran’s central and eastern basins subject to social and environmental assessment of impacts. SDM modeling was also implemented accounting for the existing water transfers plus the under-study water transfers. This study’s results indicate the firm energy from hydropower produced by the Big Karun Basin system would decrease by 28% relative to existing water transfer conditions. This issue raises concerns given the Big Karun Basin contribution to electricity production Iran. The water supply to several sectors would be marginally impacted by future water tranfers, yet water quality would be compromised in some instances. Therefore, the Big Karun Basin water system was simulated considering inter-basin water governance based on hedging rules for the under-study water transfers. Results indicate the minimum drinking and industrial demands could be met. In addition, the firm energy from hydropower produced by the Big Karun Basin system would decline by 12% relative to existing water-transfer conditions and the vulnerability of the water system would decline in terms of required quality for downstream demands and water users in comparison with the full-transfer water condition.

This study explores the features of leading modes of Subtropical Indian Ocean (SIO) sea surface temperature (SST) variability and their representation in CMIP6 models. The first EOF mode of SIO SST, featured by an SST anomaly elongated from the northwestern to the southeastern SIO region is triggered by the El Niño/Southern Oscillation (ENSO). ENSO-induced wind anomalies over the SIO region weaken the climatological southeasterlies, reduce evaporative cooling, and consequently warm the SST in subtropics. The first SIO mode is closely related to the Indian Ocean Basin Mode. The CMIP6 models’ skill in simulating this mode is attributable to their accurate representation of ENSO impacts in this region. At the same time, the skill of simulation of the second mode, the Subtropical Indian Ocean Dipole (SIOD), is poor in most models due to the misrepresentation of the pure tropical Indian Ocean Dipole (IOD) events. As pure IOD events generate SIOD, underestimation of the occurrence of pure IOD events will affect the development of SIOD in models. The CMIP6 model experiments reveal the absence of ENSO forcing on SIOD. Notably, regardless of the bias in co-occurred and pure IOD events, most of the models overestimate IOD strength due to the easterly surface wind bias and the associated thermocline depth bias. The easterly bias in the equatorial Indian Ocean surface wind weakens the Wyrtki jet, creating a shallow (deep) thermocline bias in the eastern (western) TIO. This induces an overestimation of warm (cold) SST in the western (eastern) TIO during positive IODs.

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.