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Climate change is a major concern, as it profoundly affects many facets of our lives. It has brought about several issues, including declining water supply, reduced agricultural yields, increased drought occurrences, and increased heat waves. Amidst these challenges, the influence of short-term drought events on plant growth and irrigation schedule emerges as a critical concern. However, despite these evident consequences, a nuanced understanding of the intricate relationship between the severity and duration of short-period drought/deficit events still needs to be explored. This paper analyses fortnightly water deficit periods over different regions of India, which would be more relevant to re-scheduling the irrigation events than monthly or longer duration in preventing crops from reaching the permanent wilting point. Hence, this work considers analyzing 15-day Standardized Precipitation Index (SPI) trends and drought characteristics using conventional methods and Innovative Trend Analysis (ITA) techniques. The analysis uses gridded rainfall data from the India Meteorological Department (IMD), which has a spatial resolution of 0.250-E and 0.250-N. The data spans the period from 1970 to 2021. The ITA and Mann Kendall (MK) displayed nearly identical areas of increasing and decreasing trends, but ITA effectively identified significant trends. While MK and Modified Mann Kendall (MMK) could only indicate significant trends for 12.94%, 9.57%, and 9.9% of grid points for SPI, drought severity, and duration, respectively, ITA was able to identify significant trends at 44.31%, 10.9%, and 10.1% on an annual scale. The ITA method effectively identified the significant trends and magnitudes of fortnightly SPI and drought characteristics. The Tropical monsoon (Am), Tropical savannah (Aw), Arid desert hot (BWh), Arid steppe hot (BSh), and Temperate dry winter warm summer (Cwb) climatic zones have shown a significant increase in annual drought severity. Similarly, a significant increase in monsoon drought severity is observed across several states, including Gujarat and Mizoram, impacting diverse geographic extents. The present study can help policymakers and water resource managers decide on water allocation, irrigation, and crop management practices. [ABSTRACT FROM AUTHOR]

The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth's land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted. [ABSTRACT FROM AUTHOR]

In this paper, 16 cities representing four major architectural climate zones of China were selected, and the heating and cooling loads of office building during the period of 1961–2017 were simulated by using TRNSYS software. Daily extreme heating and cooling loads were determined by percentile methods, and the climate change impact on extreme loads was analyzed. The results showed that the days of extreme heating load of office building significantly decreased in almost all the selected cities, whereas there were no significant changes in the days of extreme cooling load. The daily extreme heating load was dominantly affected by the temperature (R2 = 0.43–0.79), but the daily extreme cooling load was related to multiple climate factors, including temperature, relative humidity, and solar radiation. Single temperature can only explain 3–37% of the changes of daily extreme cooling load, and the combination of multiple climate factors can explain 58–85%. Importantly, the effect of temperature on extreme cooling load showed decrease from the cold to hot climate zones, but the impacts of relative humidity and solar radiation gradually increased. These results suggest that the maximum design capacity of heating systems can properly decrease, and the design capacity of cooling systems may not largely increase with the climate warming. In addition, the combined effect of multiple climate factors rather than the single temperature, as well as the different responses of extreme cooling energy consumption to climate change in different climate zones, should be considered when making measures for improving operating efficiency of air-conditioning system. [ABSTRACT FROM AUTHOR]

This paper addresses two fundamental questions on climate change and variability: to what extent has climate changed and/or varied over years in two districts of different agro-ecological regions or zones and how do any changes differ between the zones or districts? Given the rural-rural migration pattern observed between the districts, understanding climate change risk to rural livelihoods cannot be overemphasised. To assess change and variability, we utilise rainfall data-records over a 36-year period from 1980 to 2016. Results show that there are wide variations and differences within and between the districts. Evidence suggests a general reduction in both annual rainfall and wet days. There is also ground to suggest that the rainy season duration is becoming shorter, given that rainfall onset is increasingly starting late, while cessation is increasingly coming early. Dry spells frequency and duration trends within rainy season show an increase over the period examined. We conclude that local climate in both areas has changed over the period investigated. However, while Livingstone seems to have experienced more droughts and unreliable rainfall, Kabwe experienced a bigger change in both rainfall and rainy season duration. We further conclude that migrants into Kabwe and other inhabitants are not any safer from climate change risk. [ABSTRACT FROM AUTHOR]

The paper discusses temporal changes in the configuration of vertical climatic belts in the Tatra Mountains as a result of current climate change. Meteorological stations are scarce in the Tatra Mountains; therefore, we modelled decadal air temperatures using existing data from 20 meteorological stations and the relationship between air temperature and altitude. Air temperature was modelled separately for northern and southern slopes and for convex and concave landforms. Decadal air temperatures were additionally used to delineate five climatic belts previously distinguished by Hess on the basis of threshold values of annual air temperature. The spatial extent and location of the borderline isotherms of 6, 4, 2, 0, and − 2 °C for four decades, including 1951–1960, 1981–1990, 1991–2000, and 2001–2010, were compared. Significant warming in the Tatra Mountains, uniform in the vertical profile, started at the beginning of the 1980s and led to clear changes in the extent and location of the vertical climatic belts delineated on the basis of annual air temperature. The uphill shift of the borderline isotherms was more prominent on southern than on northern slopes. The highest rate of changes in the extent of the climatic belts was found above the isotherm of 0 °C (moderately cold and cold belts). The cold belt dramatically diminished in extent over the research period. [ABSTRACT FROM AUTHOR]

In this paper, validation of rain climatic zone classifications for Nigeria is presented based on global radio-climatic models by the International Telecommunication Union-Radiocommunication (ITU-R) and Crane. Rain rate estimates deduced from several ground-based measurements and those earlier estimated from the precipitation index on the Tropical Rain Measurement Mission (TRMM) were employed for the validation exercise. Although earlier classifications indicated that Nigeria falls into zones P, Q, N, and K for the ITU-R designations, and zones E and H for Crane's climatic zone designations, the results however confirmed that the rain climatic zones across Nigeria can only be classified into four, namely P, Q, M, and N for the ITU-R designations, while the designations by Crane exhibited only three zones, namely E, G, and H. The ITU-R classification was found to be more suitable for planning microwave and millimeter wave links across Nigeria. The research outcomes are vital in boosting the confidence level of system designers in using the ITU-R designations as presented in the map developed for the rain zone designations for estimating the attenuation induced by rain along satellite and terrestrial microwave links over Nigeria. [ABSTRACT FROM AUTHOR]

International conferences on frequency coordination have, in recent years, required new information on radiowave propagation in tropical regions and, in particular, on propagation in Africa. The International Telecommunications Union (ITU-R) initiated 'radio-wave propagation measurement campaign' in some African countries some years back. However, none of the ITU-initiated experiments were mounted in Nigeria, and hence, there is lack of adequate understanding of the propagation mechanisms associated with this region of the tropics. The Centre for Basic Space Science (CBSS) of NASRDA has therefore embarked on propagation data collection from the different climatic zones of Nigeria (namely Coastal, Guinea Savannah, Midland, and Sahelian) with the aim of making propagation data available to the ITU, for design and prediction purposes in order to ensure a qualitative and effective communication system in Nigeria. This paper focuses on the current status of propagation data from Nigeria (collected by CBSS), identifying other parameters that still need to be obtained. The centre has deployed weather stations to different locations in the country for refractivity measurements in clear atmosphere, at the ground surface and at an altitude of 100 m, being the average height of communication mast in Nigeria. Other equipments deployed are Micro Rain Radar and Nigerian Environmental and Climatic Observing Program equipments. Some of the locations of the measurement stations are Nsukka (7.4° E, 6.9° N), Akure (5.12° E, 7.15° N), Minna (6.5° E, 9.6° N), Sokoto (5.25° E, 13.08° N), Jos (8.9° E, 9.86° N), and Lagos (3.35° E, 6.6° N). The results obtained from the data analysis have shown that the refractivity values vary with climatic zones and seasons of the year. Also, the occurrence probability of abnormal propagation events, such as super refraction, sub-refraction, and ducting, depends on the location as well as the local time. We have also attempted to identify and calculate the most important propagation factors and associated data, such as k factor, that are relevant in considerations of propagation in tropical regions like Nigeria. [ABSTRACT FROM AUTHOR]

In order to better understand the effect associated with global climate change on Iran's climate condition, it is important to quantify possible shifts in different climatic types in the future. To this end, monthly mean minimum and maximum temperature, and precipitation from 181 synoptic meteorological stations (average 1970-2005) have been collected from the meteorological organization of Iran. In this paper, to study spatial changes of Iran's climatic zones affected by climate changes, Extended De Martonne's classification (originally formulated by De Martonne and extended by Khalili ()) was used. Climate change scenarios were simulated in two future climates (average conditions during the 2050s and the 2080s) under each of the SRES A1B and A2, for the CSIRO-MK3, HadCM3, and CGCM3 climate models. Coarse outputs of GCMs were downscaled by delta method. We produced all maps for three time periods (one for the current and two for the future) according to Extended De Martonne's classification. Finally, for each climatic zone, changes between the current and the future were compared. As the main result, simulated changes indicate shifts to warmer and drier zones. For example, in the current, extra arid-cold ( A1.1m2) climate is covering the largest area of the country (21.4 %), whereas in both A1B and A2 scenarios in the 2050s and the 2080s, extra arid-moderate ( A1.1m3) and extra arid-warm ( A1.1m4) will be the climate and will occupy the largest area of the country, about 21 and 38 %, respectively. This analysis suggests that the global climate change will have a profound effect on the future distribution of severe aridity in Iran. [ABSTRACT FROM AUTHOR]

This paper presents the validation of monthly precipitation using Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA)-3B43 product with conventional rain gauge observations for the period 1998-2007 over Kyrgyzstan. This study is carried out to quantify the accuracy of TMPA-3B43 product over the high latitude and complex orographic region. The present work is quite important because it is highly desirable to compare the TMPA precipitation product with the ground truth data at a regional scale, so that the satellite product can be fine-tuned at that scale. For the validation, four different types of spatial collocation have been used: station wise, climatic zone wise, topographically and seasonal. The analysis has been done at the same spatial and temporal scales in order to eliminate the sampling biases in the comparisons. The results show that TMPA-3B43 product has statistically significant correlation ( r = 0.36-0.88) with rain gauge data over the most parts of the country. The minimum linear correlation is observed around the large continental water bodies (e.g., Issyk-Kul lake; r = 0.17-0.19). The overall result suggests that the precipitation estimated using TMPA-3B43 product performs reasonably well over the plain regions and even over the orographic regions except near the big lake regions. Also, the negative bias suggests the systematic underestimation of high precipitation by TMPA-3B43 product. The analyses suggest the need of a better algorithm for precipitation estimation over this region separately to capture the different types of rain events more reliably. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of pluviometric precipitation time series obtained from 45 data collection points, with daily rain measurements (in mm), from 45 counties within the nine climatic regions of the state of São Paulo, mostly for the period of 1950–1997. São Paulo State (Brazil) is situated between the inter-tropical climatic zone, dominated by tropical and equatorial masses, and the sub-tropical climatic zone controlled by tropical and polar air masses. Due to this location the State can be divided into three climatic zones: south-east and south-west, which are permanently humid, and north with a well defined dry period. Rescaled range analysis, or R/S analysis, has been used to investigate the scale properties of the time series. We found two clear values for the Hurst exponent, one for a period of 10 to 200 days (H1), and another for a period above 210 days (H2). The value of H1 lies between 0.6 to 0.7 for all climatic zones indicating characteristics of persistence. However, H2 is (i) close to 0.5 for the littoral area, showing random characteristics, (ii) close to 0.6 for mountain areas, indicating persistence characteristics, and (iii) close to 0.4 for the plane area, irrespective of whether the climate is dry or humid, and shows anti-persistence characteristics. [ABSTRACT FROM AUTHOR]

Gridded rainfall datasets based on various data sources and techniques have emerged to help describe the spatiotemporal features of rainfall patterns over large areas and have gained popularity in many regional/global climatic analyses. This study explored future variations of rainfall characteristics over peninsula Malaysia and Singapore region based on rainfall indices of PRCPTOT, Rx1day, Rx5day, R95pTOT, R1mm, and R20mm, under 9 CORDEX-SEA RCM datasets with RCP8.5 emission scenario. A monthly quantile delta mapping method (MQDM) was adopted for bias-correction of the RCM modelled data. It was indicated that all the studied rainfall indices have long-term variations both temporally and spatially. Generally, the further the future, the higher the variability and uncertainty of indices. For the study region, the relative increments of the medians from RCM models averaged over all climatic zones in the far future are 40.3%, 25.9%, and 4.7% for Rx1day, Rx5day and R95pTOT, respectively. The annual rainfall amount (PRCPTOT) in the long run would likely increase mainly in the northeast coastal zone and drop in most of other areas over the peninsula, with the median being -5.9% averaged over all zones. The frequency of wet days (R1mm) would generally drop over the whole peninsula, with the median averaged over all zones being -6.8% in the far future. The frequency of heavy rains (R20mm) would overall decrease (by -3.4% in average in the far future) but might still notably increase in the northeast zone (NE) at both annual and southwest monsoon. The extreme conditions implied from individual RCM models could be more alarming. The study result could be useful in revealing the essential spatiotemporal variations of rainfall over the peninsula from short- to long-term futures and supporting large-scale flood risk assessment and adaptation planning. [ABSTRACT FROM AUTHOR]

Climate modes like ENSO (El Nino Southern Oscillation) and IOD (Indian Ocean Dipole) produce an impact on the monsoon rainfall over India. Monsoon rainfall is extremely important for the agriculture of our country. The impact of these climate modes on monsoon rainfall thus in turn affects the rain-fed crops (kharif). In this study, four kharif season crops namely rice (Oryza sativa), maize (Zea mays), pulses and sugarcane (Saccharum officinarum) are chosen over four arid/semi-arid agro-climatic zones of western India to study the effect of the climate modes on selected crops. The detailed analysis has been carried out to show the impact of rainfall in the El Nino/La Nina (phases of ENSO) and IOD years on the crop productions over the mentioned zones viz. (Central plateau and hills region; Western plateau and hills region; Gujarat hills and plains region; Western dry region) from 1966–2011. The results show that rice productions which require hot and humid conditions have been largely affected during drought years associated with El Nino which results in poor rainfall over all the zones. The production of pulses which does not require excess humid conditions shows marginal improvement during the neutral years or non-El Nino/non-La Nina years. Maize production seems to be better in La Nina years and worst in the El Nino years as La Nina years are responsible for good rainfall in all zones. El Nino years provide a minor impact on sugarcane productions in different zones. La Nina years are well suited for sugarcane production in all zones of our study as sugarcane requires a good amount of moisture. Positive IOD years are associated with poor crop productions as compared to negative IOD years mostly in all zones as most of the positive IOD years happen to be El Nino years. El Nino-rainfall relation being dominant than positive IOD-rainfall relation is, therefore, responsible for negative rainfall anomalies over the selected zones. [ABSTRACT FROM AUTHOR]

The most practical methods to predict climate change are global climate models (GCMs). This research set out to evaluate the ability of 19 GCMs from the Coupled Model Intercomparison Project 6 (CMIP6) to reproduce the historical precipitation, maximum, and minimum temperature (Pr, Tmx, and Tmn) of climate prediction center data for the Amu Darya river basin (ADRB), as well as to project the climate of the basin using the chosen GCMs. The Kling-Gupta efficiency (KGE) metric was used to assess the effectiveness of GCMs to simulate the annual geographic variability of Pr, Tmx, and Tmn. A multi-criteria decision-making approach (MCDMA) was used to integrate the KGE values to rank GCMs. The findings showed that AWI-CM-1–1-MR, CMCC-ESM2, INM-CM4-8, and MPI-ESM1-2-LR best replicate observed Pr, Tmx, and Tmn in ADRB. Projection of climate employing the selected GCMs indicated an increase in precipitation (9.9–12.4%), Tmx (1.3–4.9 °C), and Tmn (1.3–5.5 °C) in the basin for all the shared socioeconomic pathways (SSPs), particularly for the far future (2060–2099). A significant variation can be seen in Tmx and Tmn over the different climatic zone. However, the intercomparison of selected GCM projected revealed high uncertainty in the projected climate. The projection uncertainty is noticed highest for Tmx. The uncertainty is also noticed higher in the far future and higher SSPs compared to the near future and lower SSPs. [ABSTRACT FROM AUTHOR]

Sufficient site-level observations are needed to resolve the discrepancies between in situ and space-based observations for reliable climate mitigation and adaptation strategies. Resolving such discrepancies from climate-sensitive and understudied Himalaya is the priority for the Indian sub-continent. This study investigates characteristics and dynamics of equivalent black carbon aerosol (eBC) including sources over a glaciated valley at the transitional climate zone between central and western Himalaya. Thermo-topographic factors influencing valley-scale dynamics of eBC were observed by coupled measurements on instantaneous eBC (Aethalometer) and meteorological state parameters at a high altitude (4000 m asl) in the Indian Himalaya covering an annual cycle (October 2015 to August 2016). Results indicate a very large variation (38–5638 ng m−3) in mean daily BC concentration (308 ± 37 ng m−3). Seasonally, the eBC concentration was found highest during the pre-monsoon (1276 ± 115 ng m−3) and lowest during the monsoon season (308 ± 37 ng m−3). In contrast, the magnitude was comparable during winter and post-monsoon seasons (400–500 ng m−3). BC-induced mean annual radiative forcing at the atmosphere was + 10.1 ± 3.0 W m−2. These results indicate a substantial eBC burden over the region even at this high tropospheric altitude in this pristine glacier environment. On the other hand, the diurnal-scale variability in eBC concentration is primarily governed by high-altitude meteorological processes. Further, source apportionment analyses underscore the seasonal scale influence of monsoon and westerly circulation systems. [ABSTRACT FROM AUTHOR]

The purpose of this study is to assess spatial and temporal changes in extreme precipitation events from 1983 to 2017 over different climatic regions of Nigeria. Ground observations of daily precipitation in 17 meteorological stations scattered over the country were methodically analysed. Twelve widely used indices for the assessment of intensity (PRCPTOT, R × 5Days, SDII, R95p, R99p and R95pIndex) and frequency (CWD, CDD, R1mm, R10mm, R20mm and R25mm) of extreme precipitation were adopted. Linear trends were calculated using a least-square-fit approach, while significant trends were identified using the Mann–Kendall non-parametric test. Results revealed general significant (at p < 0.05) downward annual trends in precipitation intensity indices [i.e. total wet day precipitation, (PRCPTOT), daily precipitation (SDII), 5-day maximum precipitation, (R × 5Days), very wet (R95p) and extremely wet days (R99p)], particularly in the Savannah and Sahel regions. The frequency indices [i.e. consecutive dry days (CDD), wet days (R1mm), heavy (R10mm), very heavy (R20mm) and extremely heavy precipitation (R25mm)] increased significantly in the Sahel but decreased in other zones. We established that R1mm decreases with decreasing SDII, while CWD declines with reducing SDII and R95p in the entire country. The study further revealed that Sahel and Savannah zones are highly vulnerable to severe droughts with potential negative implications on food security and water resources. It concluded that recent changes in climate had significantly impacted the extreme precipitation events within and across different climatic regions of Nigeria. [ABSTRACT FROM AUTHOR]

Recently in agricultural and industrial sectors, researchers have started to classify the climate of a region using empirical methods and clustering. This study aims to compare four empirical approaches to climate classification (Thornthwaite and Mather, De Martonne, the Extended De Martonne, and the IRIMO (I.R. of Iran Meteorological Organization)) with Ward's hierarchical agglomerative clustering applied to the climate of Iran. The dataset used in this study comprises maximum and minimum temperatures and precipitation data of 356 weather stations extracted from IRIMO's databases. Thirty-five synoptic weather stations are selected among 356 stations. These stations are selected regarding the best uniform distribution, elevation, windward and leeward sides of the mountain ranges, and availability of a continuous 50-year data (1966–2015). Compared with the other three empirical reference methods of climate classification, the Thornthwaite and Mather method emphasizes the role of water bodies and air masses in determining the climate type of a region. Highlighting these two factors is identified as the main advantage of this method over the other three. This advantage is the most noticeable for the highlands/mountainous regions, in the vicinity of the Zagros Mountains, and in the western regions of Iran. As a case in point, while in the De Martonne and the Extended De Martonne methods, the Zagros storm cell is climatically classified similar to patchy areas in Caspian Sea coastal zone, this cell is correctly identified as a separate zone in the Thornthwaite and Mather method. The results also reveal that the clusters obtained from Ward's algorithm are comparable to those of empirical climate classifications, particularly Thornthwaite and Mather method. [ABSTRACT FROM AUTHOR]

Extreme precipitation is the leading cause of the flood, soil erosion, and drought with significant socioeconomic impacts on human resources. Therefore, projecting future precipitation changes, especially the intensity of extreme precipitation (IEP) in the future, is very important. This study's main objective is IEP projection in Iran based on CMIP6 bias-correction (BC) multi-model ensemble (MME). The daily precipitation data of five CMIP6 BC models with 0.5 ͦ horizontal resolution was used under three shared socioeconomic pathways; SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios. Simple Daily Intensity (SDII) and maximum consecutive 1-day precipitation (RX1day) were used to measure IEP changes. Two Kling Gupta efficiency (KGE) and percent bias (PBIAS) methods evaluate the performance of the models, and the independence weighted mean (IWM) method was applied for ensemble averaging. Among the studied CMIP6 bias-correction models, the IPSL-CM6A-LR model has more underestimation than other models with a KGE score of 0.751 has the lowest performance and the MPI-ESM1-2-HR model (0.768) showed the highest performance. In general, the study results showed the uncertainties in CMIP6 models for precipitation, according to which no single model is reliable even in the BC method. The PBIAS in the region affected by Asian summer monsoon (ASM) in Iran is about 10%, based on which the bias of the mentioned models for monsoon precipitation is high. SDII and RX1day anomalies in all climatic zones of Iran except for the RX1day index in Cfa climatic zones in other zones and scenarios during the two periods 2021-2060 and 2061-2100 are positive. Also, the trend and slope of the IEP are increasing in all zones except for BWh, BWk, and Cfa zones for SSP1-2.6 and SSP3-7.0 scenarios. Investigation of trend IEP changes showed that the maximum of these changes will occur in the BWh climate zone, and the minimum would occur in the cold and mountainous climate zone of Iran (Dsc). [ABSTRACT FROM AUTHOR]

Previous studies revealed that building climatic zoning has largely changed in China due to the influence of climate change. However, the possible impacts of changing building climatic zoning on energy consumption for cooling or heating are not clear. In this study, eight representative cities were selected from changed climate zones, and the heating and cooling energy consumption of office and residential buildings of the representative cities under the conditions of the current and new climate zones was simulated to reveal the effect of the climate zone change on building energy consumption. The results showed that there was no heating or cooling energy consumption with the climates changing from hot summer and cold winter (HSCW) and cold (C) to mild (M). Also, no heating energy consumption occurred with the climate zones changing from HSCM to hot summer and warm winter (HSWW), whereas the cooling energy consumption showed a weak decrease. For the climate zones that shifted from severe cold (SC) to C, decreasing heating energy consumption and increasing cooling energy consumption trends were observed, and the total energy use exhibited a decreasing trend. However, in the climate zones changing from C to HSCW, the heating and cooling energy consumption increased, especially for residential buildings (e.g., the heating energy consumption of Zhengzhou and Baoji increased 78.7% and 77.7%, respectively). This study suggests that new climate zones should be fully considered and the new design standard according to the changes of climate zones should be adopted to improve building energy efficiency. The design of residential buildings in the climate zones changing from C to HSCW may not consider the changes of climate zone. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a fundamental element in the hydrological cycle and plays a vital role in simulating hydrological effects of climate change. Accurate estimation of reference evapotranspiration (ETo) plays a significant role in the field of hydrometeorology and agrometeorology. There are many direct or indirect methods that are employed for estimation of ETo. Furthermore, soft computing approaches are also used to solve complex problems of estimation in various disciplines. The application of the soft computing techniques for estimating evapotranspiration has only been limited to few approaches including artificial neural network, fuzzy logic, and genetic algorithm. This study is conducted to apply non-conventional soft computing approaches for estimating ETo which include single decision tree (SDT), tree boost (TB), and decision tree forest (DTF). Monthly meteorological data spanning over 30 years (1987 to 2016) for six different cities located in arid, semi-arid, and humid regions of Pakistan is used for the estimation of ETo in this study. Seventeen input combinations comprising of various climatic parameters were developed to evaluate the impact of different parameters. A total of 306 models were developed using the SDT, TB, and DTF approaches for all six selected cities of Pakistan. The results of the developed models are then compared with ETo calculated by the standard method of modified Penmen equation. The TB modeling technique is found to perform best for various cities located in different climatic zones of Pakistan. Only two climatic parameters, the mean temperature and wind velocity, are found to be sufficient for efficient ETo prediction. To further validate the results, the outcome of the study was applied on some other climatic regions located in the USA, New Zealand, and China. Finally, it is concluded that these non-conventional approaches can also be considered superior alternatives to the available methods of estimating ETo. [ABSTRACT FROM AUTHOR]

Southern Brazil has recently been the subject of many major natural hazards from weather and climatic origin, including violent floods in 2016 caused by very heavy rains. It has also experienced episodes of droughts and heat waves in recent years. The state of Paraná, located at the climatic transition zone, has densely populated urban areas, vast cultivation areas, and hydro-electric reservoirs (more than 20), so those extreme events are letting local populations vulnerable to the vagaries of the climate and their impacts on community, infrastructure, and ecosystem. This study analyzes climatic variability and trends of about ten climatic indices (with RClimDex), calculated by using daily thermal data of ten stations spread mainly in two geographic regions of Paraná. The Mann-Kendall and Pettitt tests were applied for trends analysis and determine the presence of breakpoints in the time series (1971–2014). Our results showed that for the various thermal indices, there is a reduction of the cold days on all the stations, indicating a more pronounced increase of the indices based on the maximum temperatures (TX), especially in the north. On the other hand, the indexes based on minimum temperatures (TN) show a more modest and partial increase, varying accordingly to the location of the stations. Regionally, the trends calculated were similar, that is, North region presents a more expressive increase of the indices of heat whereas in the east predominates a reduction. [ABSTRACT FROM AUTHOR]

The contributions of twelve independent factors/variables to the magnitude of the local diurnal temperature range (DTR) in Israel were examined, and five to seven were found to contribute significantly. Israel was chosen due to its complex terrain with several climatic zones and proximity to the Mediterranean Sea. The seven sites for this study represent different terrains, from mountainous with a Mediterranean climate to desert. Each site had 6 years of data available. Stepwise analysis was performed in order to determine the contribution of each factor/variable at each site. The linear correlations between the DTR and each factor were calculated. These were carried out at each site for the whole year and for each season, separately. Relative humidity was found to have the largest DTR contribution at all sites, for 3 seasons, except summer at shoreline sites and in Jerusalem. The daily cloud cover and the wind speed had small contributions in most sites. The magnitude of the DTR was found to vary largely with location and to be considerably smaller in the seashore sites than those inland. [ABSTRACT FROM AUTHOR]

Regional climate is particularly important for different activities such as forestry, agriculture, transport, coastal areas, and wildlife. In New Brunswick (NB), ten climate types were classified by combining climate and geographical data from 45 national meteorological stations for the period 1981–2010. A multiple regression technique/model was used for the interpolation of climatic parameters then clustering was done based on the three main parameters from a principal component analysis. Our results indicate a strong correlation between most climate variables with latitude and altitude while longitude and distance to the sea plays a more marginal role in climate spatial distribution. Furthermore, the climate map produced coincides with a map produced from a previous study of the NB province based on 1954–1979 data. However, the boundaries between most climate zones in those two maps changed slightly due to inconsistent period variation (1954–1979 vs 1981–2010), the methods used as well as the number and location of the weather stations (76 vs 45). Many climate type limits changes observed in the study area were probably connected with the climate change since mid-1950s. [ABSTRACT FROM AUTHOR]

Due to increasing heat-related health risks, as well as the human requirements on energy and side effects, this study attempts to figure out a methodology of quantifying the potential requirements on human thermal comfort and air humidity towards the achievements of the Sustainable Development Goals (SDGs). Based on the Köppen-Geiger climate classification and the selected 11 climate types with sample cities, the methodology has been detailed. Meanwhile, the quantified thermal and humid conditions in each city, as the primary representation of each climate type, have been presented. According to the potential application of the quantified information and based on the qualitative analysis of SDGs text, the correlation between the information of human thermal comfort and air humidity, and 12 SDGs has been summarised. Furthermore, the difference of the qualitative description between the original Köppen-Geiger climate classification and the quantified information has been discussed. For instance, obvious difference appeared in the same climate zone (e.g. climate zone C); comparing with the original climate classification, there is a different order of hot/cold conditions or wet/dry conditions. The identified differences are regarded as the enlightenments for further studies. [ABSTRACT FROM AUTHOR]

Since the extra-tropical eddies carry a huge amount of moisture, heat, and momentum from their source regions to remote places, the long-term changes in their properties can lead to substantial changes in the Earth's major climatic zones with huge socio-economic consequences. We present the long-term variability and trends in the spatial properties of the Rossby wave packets (RWPs) in the Northern Hemisphere in all seasons for the period of 1980–2013 using NCEP reanalysis for the three major storm track regions: Eurasian, North Pacific, and North Atlantic. A region of high-amplitude meandering flow in the upper troposphere that in the mid-latitudes travel in coherent wave train structures or wave packets is often referred to as a RWP. We found that the activity volume of the RWPs is largest during winter in all storm track basins. Our results suggest that the highest variability of the activity volume is in the North Atlantic region, while the minimum variability of this quantity is found during summer in the Eurasian basin. The largest relative frequency of significant wave packets is found in winter in the North Atlantic basin; however, the largest variability of this quantity is found in the North Pacific region during spring. The largest variability of the long-term daily maximum of WPA is found in the Eurasian region in winter and the minimum variability of this quantity is found in summer in the North Pacific region. The long-term northernmost point of the Rossby wave packets (which is an indicator of the meridional extent of the RWPs) shows that during autumn in the North Atlantic basin, the Rossby wave packets meander more than other seasons and regions. The minimum value of this quantity is found in the summer season in the Eurasian region. The largest variability of the northernmost edge of the RWPs is found in the autumn season in the Eurasian basin, while the minimum variability of this quantity is found in the autumn season in the North Atlantic region. We employ the non-parametric Mann-Kendall test to identify the statistically significant trends in the spatial properties of the Rossby wave packets. No significant trend is found for any diagnostic tools in any region and any season. This suggests that the global mean temperature rise or other climatic changes (over the 34-year period of this study) do not have a detectable impact on the Rossby wave packets. [ABSTRACT FROM AUTHOR]

The results of the multifractal analysis performed for meteorological time series coming from four stations in Poland and Bulgaria located in varying climatic zones are presented. To assess climatic shift response (in 2001/2002), the analysis was conducted separately for two subsets. To analyze long-distance power-law correlations within the studied time series and evaluate the differences in dynamics of the climate between the analyzed sites and periods of time, the multifractal detrended fluctuation analysis methodology (MF-DFA) was proposed. It was revealed that the multifractal properties of precipitation differ considerably from other analyzed quantities. The singularity spectra were susceptible to climatic shift, what was indicated by the changes of spectra parameters. It was especially apparent for asymmetry, which changed from being right- to left-skewed, implying the occurrence of more extreme events. Similarities in the dynamics of meteorological processes for each of the climatic zones were proven by the close relation of respective multifractal spectra parameters coming from closely spatially related localizations. [ABSTRACT FROM AUTHOR]

This study examined drought occurrence in the sub-humid eco-climatic zone of Nigeria using monthly rainfall data from 13 synoptic stations for the period 1970–2009. Standardized Precipitation Index and descriptive statistics were employed for the study. The result obtained showed 266 drought occurrences, with 65.79, 19.93, 9.77, and 4.51% as mild, moderate, severe, and extreme droughts, respectively. The period 1980–1989 was more prone to drought of different categories while 1990–1999 was wetter than other decades. Drought occurrences ranged from 14 times at Makurdi to 24 times at Bauchi. Severe drought occurred most at Kaduna and Ibi while extreme drought was mostly devastating at Minna. However, Bida was more affected by the combination of severe and extreme droughts than other stations. The result also showed considerable interannual variability characterized by oscillations in drought duration. The duration varied from 1 to 11 years while drought intensity ranged from − 0.01 to − 3.1. [ABSTRACT FROM AUTHOR]

Agricultural sustainability under the warming climate highly depends on limiting the extreme use of the blue water resources within the irrigated lands, and instead, optimally applying green water resources within the expanded rainfed lands. In this research, potentials for expanding dry farming under climate change were analyzed in five climatic zones of Iran, based on the future projections of basic weather data and drought indices under 20 general circulation models (GCMs) and four emission scenarios, including RCP2.6, RCP4.5, RCP6.5, and RCP8.5. Drought indices included aridity index (AI), expressed as precipitation divided by evapotranspiration, and green water deficit (GWD), expressed as precipitation minus mines evapotranspiration. While annual predictions show a general increase in both precipitation and air temperature over the 2041–2070 period, given results at the monthly scale well revealed the spatial and temporal non-uniformity in the climate change projections. Such heterogeneities, together with those presented for different GCMs and RCPs, well indicated the importance of undertaking a wide range of uncertainties when implementing long-term planning. Based on GWD and AI, the arid and semi-arid regions, the backbone of the rainfed agriculture in Iran, are the most vulnerable to global warming. In these regions, green water availability will reduce by 0.8–167.5% especially within the wet seasons, and drought severity will increase by 0.1–33.2% through the rainfed cropping cycles. On the other hand, future climate may provide new opportunities for expanding dry farming within the hyper-arid region, which is now the most water-stressed region of the country. In this region, global warming projections show a positive increase of 0.3–146.2% in green water availability, and a reduction of 5.1–266.4% in drought severity. However, the humid region remained as the most suitable region for producing rainfed crops, although being widely allocated to irrigated-rice production under current condition. Based on the results, achieving sustainable dryland agriculture highly depends on regionally prioritizing susceptible area for dry farming, since the criteria indices showed an extreme spatial and temporal variability over the mid twenty-first century. [ABSTRACT FROM AUTHOR]

Shifts in precipitation regimes have been given increased attention along with climate trends in the arid and semiarid Mongolian Plateau (MP), because precipitation is the dominant factor that controls vegetation growth and land-use practices in the region. However, the temporal variability and spatial heterogeneity of decadal trends in summer precipitation fraction have not been well understood. In this study, the temporal variability and spatial heterogeneity of annual and summer precipitation change were investigated with the major focus on the summer precipitation fraction across the entire MP, using monthly precipitation data from 141 meteorological stations and the Tropical Rainfall Measuring Mission (TRMM) precipitation data. The Mann–Kendall trend test, Sen's regression, and Spatial Analyst methods were used for time series analysis. Results show that the regional summer precipitation fraction declined significantly at a rate of − 1.0%/decade (p < 0.05) during 1961–2010, which was supported by TRMM satellite data with a rate of − 2.86%/decade over 1998–2016. Interestingly, rates of decrease in the summer precipitation fraction varied by ecoregion. Spatially, trend in summer precipitation fraction was very heterogeneous, with significant decreasing trends in the eastern typical steppe and southeastern agro-pastoral ecotone, but increasing trends in the southwestern desert and Gobi desert region. In conclusion, the summer precipitation fraction declined because of the asymmetric decreasing or increasing rates in summer and non-summer precipitation during both 1961–2010 and 1998–2010. This implies a major shift of precipitation regime in the region. This is likely driven by decadal changes of the East Asia monsoon system. [ABSTRACT FROM AUTHOR]

Determining agro-climatic zones (ACZs) is traditionally made by cross-comparing meteorological elements such as air temperature, rainfall, and water deficit (DEF). This study proposes a new method based on correlations between monthly DEFs during the crop cycle and annual yield and performs a multivariate cluster analysis on these correlations. This ‘correlation method’ was applied to all municipalities in the state of São Paulo to determine ACZs for coffee plantations. A traditional ACZ method for coffee, which is based on temperature and DEF ranges (Evangelista et al.; RBEAA, 6:445-452, 2002), was applied to the study area to compare against the correlation method. The traditional ACZ classified the “Alta Mogina,” “Média Mogiana,” and “Garça and Marília” regions as traditional coffee regions that were either suitable or even restricted for coffee plantations. These traditional regions have produced coffee since 1800 and should not be classified as restricted. The correlation method classified those areas as high-producing regions and expanded them into other areas. The proposed method is innovative, because it is more detailed than common ACZ methods. Each developmental crop phase was analyzed based on correlations between the monthly DEF and yield, improving the importance of crop physiology in relation to climate. [ABSTRACT FROM AUTHOR]

A new thermal index, the modified physiologically equivalent temperature (mPET) has been developed for universal application in different climate zones. The mPET has been improved against the weaknesses of the original physiologically equivalent temperature (PET) by enhancing evaluation of the humidity and clothing variability. The principles of mPET and differences between original PET and mPET are introduced and discussed in this study. Furthermore, this study has also evidenced the usability of mPET with climatic data in Freiburg, which is located in Western Europe. Comparisons of PET, mPET, and Universal Thermal Climate Index (UTCI) have shown that mPET gives a more realistic estimation of human thermal sensation than the other two thermal indices (PET, UTCI) for the thermal conditions in Freiburg. Additionally, a comparison of physiological parameters between mPET model and PET model (Munich Energy Balance Model for Individual, namely MEMI) is proposed. The core temperatures and skin temperatures of PET model vary more violently to a low temperature during cold stress than the mPET model. It can be regarded as that the mPET model gives a more realistic core temperature and mean skin temperature than the PET model. Statistical regression analysis of mPET based on the air temperature, mean radiant temperature, vapor pressure, and wind speed has been carried out. The R square (0.995) has shown a well co-relationship between human biometeorological factors and mPET. The regression coefficient of each factor represents the influence of the each factor on changing mPET (i.e., ±1 °C of Ta = ± 0.54 °C of mPET). The first-order regression has been considered predicting a more realistic estimation of mPET at Freiburg during 2003 than the other higher order regression model, because the predicted mPET from the first-order regression has less difference from mPET calculated from measurement data. Statistic tests recognize that mPET can effectively evaluate the influences of all human biometeorological factors on thermal environments. Moreover, a first-order regression function can also predict the thermal evaluations of the mPET by using human biometeorological factors in Freiburg. [ABSTRACT FROM AUTHOR]

The growing biodiesel production requires the use of new technologies and alternative feedstocks to maintain the growing demand of this biofuel. The macaw ( Acrocomia aculeata) is a palm native to Argentina whose fruits present high oil content. Due to its tolerance to prolonged drought, it is a promising crop for biodiesel and biokerosene production. The aim of this work was to design an agroclimatic zoning model to define the potential growing areas from macaw in Argentina. To define the agroclimatic suitability to produce oil, it was necessary to identify the requirements, limits, and biometeorological tolerance for this palm. In order to define the agroclimatic fitness of this crop in Argentina, the meteorological data corresponding to the period 1981-2010 were employed. The agroclimatic indices were integrated in a Geographic Information System. The maps were superimposed and the overlapping regions delineated the agroclimatic zoning. The agroclimatic zonation classified zones with homogeneous characteristics responding to bioclimatic requirements of this species, resulting in optimal, very suitable, suitable, and nonsuitable areas for macaw cultivation. The authors designed an agroclimatic zoning model based on bibliography. This model can be used in any part of the world, employing the same agroclimatic indices presented in this work. [ABSTRACT FROM AUTHOR]

Numerous studies analyze the temperature variations in the Mediterranean area due to the anticipated impact of climate change in this part of the world. A number of studies examined the temperature climate in Greece, but few are based on a large number of synoptic stations covering all regions and climatic zones and even fewer are based on homogenized data set series, despite the fact that climatological studies must use high-quality homogeneous data series. The present work reviews previous studies dealing with climatic changes in Greece and addresses changes of mean air temperature, based on a large set of homogenized data from 52 synoptic stations. A statistically significant negative trend during 1960-1976 and a positive one during 1977-2004 were revealed. During 1960-1976, the lowest negative annual temperature trend is observed in Crete. During 1977-2004, the northern region of Greece was characterized by prominent annual warming, whereas the north and central Aegean Sea and the semi-mountainous area were characterized by the lowest warming. All stations are characterized by high seasonal trends in summer; the most extreme trends are observed in the northern and eastern regions and in the Attica area. Positive temperature trends occur from May to October, while negative trends dominate from November to February. The most pronounced warming is recorded in June and July, and the most strongly decreasing trend occurs in November. Annual temperature trends in northern Greece follow the hemispheric pattern, and the overall summer warming in Greece is greater than the hemisphere's. [ABSTRACT FROM AUTHOR]

Accurate estimation of reference evapotranspiration (ET) becomes imperative for better managing the more and more limited agricultural water resources. This study examined the feasibility of developing generalized artificial neural network (GANN) models for ET estimation using weather data from four locations representing different climatic patterns. Four GANN models with different combinations of meteorological variables as inputs were examined. The developed models were directly tested with climatic data from other four distinct stations. The results showed that the GANN model with five inputs, maximum temperature, minimum temperature, relative humidity, solar radiation, and wind speed, performed the best, while that considering only maximum temperature and minimum temperature resulted in the lowest accuracy. All the GANN models exhibited high accuracy under both arid and humid conditions. The GANN models were also compared with multivariate linear regression (MLR) models and three conventional methods: Hargreaves, Priestley-Taylor, and Penman equations. All the GANN models showed better performance than the corresponding MLR models. Although Hargreaves and Priestley-Taylor equations performed slightly better than the GANN models considering the same inputs at arid and semiarid stations, they showed worse performance at humid and subhumid stations, and GANN models performed better on average. The results of this study demonstrated the great generalization potential of artificial neural techniques in ET modeling. [ABSTRACT FROM AUTHOR]

Climate change and cyclic variation are investigated based on station data of 61 years (1951-2011), representing twelve climatic zones in Iran. Climate change is investigated by applying the non-parametric Mann-Kendall test and the three-dimensional loglinear model to the12-month SPI time series, and by applying the likelihood ratio test to precipitation time series. Cyclic variation is studied by applying the three-dimensional loglinear model to the 12-month SPI time series. Analysis included entire data period, two sub-periods [(1951-1981), (1982-2011)] and three sub-periods [(1951-1971), (1972-1991), (1992-2011)]. The Mann-Kendall test results indicated combinations of different trend behaviors, whereby climate change could not be evaluated. The likelihood ratio test did not confirm climate change (at 95 % confidence level), in most of the studied stations. However, the more in-depth analysis by the three-dimensional loglinear model, i.e., detection of significant differences among drought frequencies, did not confirm climate change (at 95 % confidence level), in any of the studied stations. Cyclic variation was not confirmed by the three-dimensional loglinear model (at 95 % confidence level), in any of the studied stations. The findings of this research illustrate the need for meticulous techniques like the three-dimensional loglinear model, as a necessary tool for climate change and cyclic variation studies. [ABSTRACT FROM AUTHOR]

Cities represent thermal load areas compared with their surrounding environments. Due to climate change, summer heat events will increase. Therefore, mitigation and adaptation are needed. In this study, meteorological measurements in various local climate zones were performed to demonstrate the influence of evaporation surfaces and other factors on thermal comfort, as determined by the physiologically equivalent temperature (PET). Furthermore, a quantification of the thermal effects of several adaptation measures and varying meteorological parameters was made using model simulations (ENVI-met) in an inner-city neighborhood (Oberhausen, Germany). The results show that the most effective adaptation measure was increased wind speed (maximal 15 K PET reduction). Moreover, vegetation areas show greater PET reductions by the combination of shading and evapotranspiration than water surfaces. The creation of park areas with sufficient water supply and tall, isolated, shade-providing trees that allow for adequate ventilation can be recommended for planning. [ABSTRACT FROM AUTHOR]

In China, ten climate types were classified using the K-means cluster analysis based on monthly temperature and precipitation data from 753 national meteorological stations for the period 1966-2005. However, 11 mountain climate stations, which are located in southeast China, were classified as one type due to their distinct climate characteristic that differentiated them from other stations. This type could not represent the climate characteristic of this region because all climate stations in this type were located at high-elevation mountains. Thus, it was eliminated when defining climate zones based on climate types. Therefore, nine climate zones were defined in China. Moreover, the temporal change of climate zones was detected in 20-year intervals (1966-1985 and 1986-2005). Although 48 stations changed their climate zones between these two periods, the whole pattern of all climate zones remained stable in these two periods. However, the boundaries between some climate zones changed slightly due to inconsistent variation of regional temperature and precipitation. The most obvious change was the eastern movement of the boundary between an arid temperate zone and a sub-humid temperate zone. There was also a northern shift of the boundary between a tropic zone and a southern subtropic zone. All these changes were probably connected with the climate change in recent 40 years. [ABSTRACT FROM AUTHOR]

The knowledge of the climatic conditions of a region is crucial for its agricultural development. It is also extremely important for understanding the fact that certain cultures have to develop under prevailing temperature and humidity conditions and assist in the adoption of a suitable irrigation technique, as well as its management and operationalization. The Köppen system of climate classification is widely used for the identification of homogeneous climate zones as it considers only rainfall and temperature as the meteorological elements for classification. For this study, we used climatic databases of rainfall and temperature in a raster format, with a spatial resolution of 30″ of arc (an approximate area of 0.86 km pixel), from 1961 to 1990. Through geoprocessing techniques, we obtained a map of climatic classification for the state of Minas Gerais. We found that the state has the following three major climatic groups: A, B and C, which correspond to tropical rainy, dry and warm temperate climates, respectively. The climate classes obtained were Aw, Am, BSh, Cwa and Cwb, with Aw, Cwa and Cwb classes occupying 99.89% of the territorial area of the state. The validation of the results showed a satisfactory agreement, with 93.75% reliability. [ABSTRACT FROM AUTHOR]

Tropical North African climate variability is investigated using a Sahel rainfall index and streamflow of the Nile River in the 20th century. The mechanisms that govern tropical North Africa climate are diagnosed from NCEP reanalysis data in the period 1958–1998: spatially – using composite and correlation analysis, and temporally – using wavelet co-spectral analysis. The Sahelian climate is characterised by a decadal rhythm, whilst the mountainous eastern and equatorial regions exhibit interannual cycles. ENSO-modulated zonal circulations over the Atlantic/Pacific sector are important for decadal variations, and create a climatic polarity between South America and tropical North Africa as revealed through upper-level velocity potential and convection patterns. A more localised N–S shift in convection between the Sahel and Guinea coast is associated with the African Easterly Jet. [ABSTRACT FROM AUTHOR]