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S. Trivikrama Rao, Ph.D.There is scientific consensus that climate change has been contributing to rising surface temperatures, changing weather pattens, and extreme weather events leading to extre...

The frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman’s formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1–2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman.

The coronavirus pandemic is one of the most fast-spreading diseases in the history, and the transmission of this virus has crossed rapidly over the whole world. In this study, we intend to detect the effect of temperature, precipitation, and wind speed on the Coronavirus infected cases throughout climate seasons for the whole year of epidemic starting from February 20, 2020 to February 19, 2021 with considering data patterns of each season separately; winter, spring, summer, autumn, in Mediterranean European regions, whereas those are located at the similar temperature zone in southern Europe. We apply the panel data approach by considering the developed robust estimation of clustered standard error which leads to achieving high forecasting accuracy. The main finding supports that temperature and wind speed have significant influence in reducing the Coronavirus cases at the beginning of this epidemic particularly in the first-winter, spring, and early summer, but they have very weak effects in the autumn and second-winter. Therefore, it is important to take into account the changes throughout seasons, and to consider other indirect factors which influence the virus transmission. This finding could lead to significant contributions to policymakers in European Union and European Commission Environment to limit the Coronavirus transmissions. As the Mediterranean region becomes more crowded for tourism purposes particularly in the summer season.

The variability and dynamics of the Asian monsoon (AM, hereafter indicates both of the summer and winter monsoons.) at orbital and millennial timescales has attracted wide interest. Chinese loess deposits, covering an area of ~500 × 103 km2 and with a thickness of several tens to more than three hundred meters, is an ideal continental archive to reconstruct AM variations during the Quaternary epoch. Over the past thirty years, since the earliest paper published in an international journal that linked the Asian monsoon and Chinese loess deposits, many studies have been undertaken focusing on this research topic. These results have greatly deepened our understanding of the variations of the AM climate and their driving mechanisms during the past ~2.6 Myr. In this paper, we emphasize recent progress on the AM variability and dynamics revealed by Chinese loess records; in particular, we discuss the reliability and precision of the timescale and the monsoon proxy indicators for the loess-paleosol sequences, which are two fundamental aspects for understanding AM behavior. We analyze what we know and discuss what we do not know about the AM. We refine the timescale for the typical loess-paleosol sequence in the central Chinese Loess Plateau (CLP), which can be used as a new timescale to study palaeoclimate and palaeoenvironmental changes in the monsoonal Asia. We conclude that low-latitude insolation changes induced by precession, and global ice volume, temperature at high-latitudes, as well as sea-level changes forced variations of the AM at orbital time scales. High-latitude cooling events and low-latitude hydroclimate process at millennial time scales, such as climate changes associated with Heinrich events and Dansgaard-Oeschger cycles in Northern Atlantic and Greenland, have also modulated AM variability. We suggest that high-latitude forcing of AM variations occurs through ocean and atmospheric circulation linkages, although the roles of atmospheric CO2, ocean and vegetation feedbacks need further investigation. In future study, high-resolution independent dating, novel proxy indices and transient numerical simulations are still basic tools to understand the loess deposition and AM variations that require considerably more work. Issues such as reliable spatial comparison and regional linkages of records (dependent on precise and accurate numerical chronologies), and quantitative reconstruction of the AM variations, should be given priority in the study the past climate change in Asia, and low-latitude hydroclimate process.

Monthly rainfall data for Blue Nile Basin (BNB) were obtained from the Ethiopian Meteorological Authority (1950–2018). Long-term trends in the BNB annual and monthly rainfall are investigated in this study. The challenges of the paper were to explore the impact of climate change on the study area using sound practical methods. The paper used the widely used statistical methods to find precisely the significance of the impact of climate change rainfall variability and distribution both spatially and temporally in the BNB. The statistical significance of the trend in the study is calculated by the Mann-Kendall (MK) test. Data were analyzed using the coefficient of variation, anomaly index, and precipitation concentration index. The coefficient of variation is high in Kiremt rainfall which implies more inter-annual variability of Bega rainfall than Kiremt (Coefficient of Variation (CV): Bega˃ Belg˃ Kiremt season). Based on Precipitation Concentration Index (PCI) value, the number of moderate concentration years (89.9%) has been increasing through time and the study area has encountered successive years of drought. The results showed that the annual, Bega, Belg, and Kiremt precipitation over the whole of BNB is significantly decreasing except Bega season with a magnitude of 36.38, 3.8, 7.8, and 24.7 mm per decade respectively. The rainfall in the study area is characterized by a high CV. Moreover, prolonged droughts have become common which adversely affects the agricultural system. It was also found that very low values of rainfall anomalies that correspond to severe droughts were associated with El Nino Southern Oscillation (ENSO) events.

This paper presents a new index to determine meteorological drought conditions, the Drought Exceedance Probability Index (DEPI), derived from monthly precipitation time series. Its formulation is simple and undemanding in terms of baseline information requirements. This makes the DEPI suitable for routine application to any climate, similar to the well-known Standardized Precipitation Index (SPI). The index is based on the calculation of cumulative rainfall anomalies and their subsequent standardization, similarly to other indices. The hallmarks of the DEPI, and its main comparative advantages, are the process of accumulating anomalies and their standardization process. The paper compares the DEPI with the SPI in several different climates across the world and in all cases the results show the complementarity of both indices. The DEPI shows an excellent ability to reflect the actual severity and duration of droughts, without requiring application on different time scales, unlike the SPI. It is also valid for all types of climates, including arid and semiarid or Mediterranean, for which the literature has shown that using the SPI is problematic.

This research paper presents the investigation of design consideration to achieve thermal comfort and the warm humid climatic zone of West Bengal is considered as the primary study area for the investigation. The varying thermal comfort behavior of humans in different climate conditions and seasons clearly demonstrates that the building design strategy must conform with the region of the building. In this paper, first studying the climatic characteristics of the warm humid region design factors are selected like building materials, cross ventilation, building orientation, roofing orientation, and materials, etc. After that, all those design factors are studied and the effect of all those factors on building in various conditions is observed. Keywords: Warm Humid Climate, Thermal Comfort, Building Materials, U-value, Cross Ventilation, Building Orientation

This paper provides an outlook on the effects of climate change and the severity and frequency of extreme weather events on the performance of flexible pavements across North America. Now more than ever, the climate is changing at a rapid pace, which will alter long-term environmental loading parameters and extreme weather events. Such alterations will pose implications for the design, maintenance, and rehabilitation of flexible pavements, especially in terms of their serviceability, safety, and functionality. In northern Canada, roads are founded on various terrain types, including thaw-sensitive ice-rich permafrost underlying terrains. Such roads have experienced signs of embankment and pavement damage, which are usually induced by the degradation of the underlying permafrost due to climate change. Therefore, the development and implementation of new permafrost thaw mitigation techniques for vulnerable roads are essential and will be discussed in this paper. Resilient flexible roads should be designed to withstand the conditions that are likely to occur during their design life, taking into account the impact of the climate change on pavement performance in response to daily and seasonal changes in heat, precipitation, freeze–thaw cycles, and extreme weather events.

This paper contains a large number of radar data information, analyzes the radar scattering characteristics of water masses in different imaging areas, such as quiet open area, wave area, agricultural area, and compares with the application of high-resolution SAR image extraction algorithm. We also use the data analysis of the data center to explore the evolution characteristics of the high-level and low-level atmospheric circulation and water vapor transport field before and after the beginning and end of the rainy season precipitation anomaly in Southwest China. Then, the low-frequency evolution characteristics of the precipitation anomaly series in the rainy season in Southwest China are analyzed, and eight phases are divided according to the 20–60 day intraseasonal oscillation of precipitation, which provides convenience for the transportation of low-frequency water and air. Thirdly, the method is applied to aerobic exercise. However, people with low blood glucose regulation are generally overweight, and drug treatment itself cannot change their health. Exercise has always been the most effective way of muscle strength training. If aerobic exercise and resistance exercise are combined, it can be combined exercise training. If the sequence and duration are long enough, excess sugar in the body can be burned. Training resistance can be used to improve muscle function and maintain strength. Therefore, the process of aerobic exercise is very important for people with poor blood glucose regulation, and it can also provide more meaningful and targeted concept development for the treatment of diabetes. In order to promote the development and application of SAR map, this paper studies the relationship between abnormal precipitation in rainy season and blood glucose regulation of teenagers during aerobic exercise, and applies it to the study of SAR map.

Climate change is becoming a reason for the increased frequency of drought reported in many parts of the world. An increase in temperature results in the increase in soil evaporation, thus rendering low precipitation periods drier under otherwise cooler conditions. For drought prediction, it is important to quantify the drought conditions. Several types of research have been conducted to develop univariate and multivariate drought indicators based on meteorological data and historical data. This paper gives thorough information about several indices which can be used for drought assessment, monitoring, and prediction purpose. The countries with the worst experience in drought are counted on herewith to compile the list of indices. This review paper attempts to summarize the global acceptability of various indices, reported accuracy, and identify the reasons for the wider acceptability of certain indices.

The paper analyzes the meteorological conditions in the city of Krasnoyarsk in the period from January 1, 2019, to December 31, 2020. The relationship between temperature inversions in the surface layer of the atmosphere and air pollution by suspended solid particles PM25 is investigated. The paper uses a set of meteorological data of the NCEP GFS weather forecast model on the air temperature on three isobaric surfaces of 1000, 925, and 850 Mb; on wind gusts and the height of the atmospheric boundary layer. Data on PM25 solid particle concentrations and wind speed are provided by the air monitoring system of the KSC SB RAS. The relationship between the presence of temperature inversions in the lower layer of the atmosphere and periods of significant air pollution is shown, as well as the dependence of changes in wind speed and the height of the boundary layer of the atmosphere with changes in the average daily PM25 concentration. The results of the data analysis allow us to conclude that there is a high degree of correlation between these parameters. The possibility of using the meteorological data of the NCEP GFS model to study the surface layer of the atmosphere and the periods of its pollution, predicting the deterioration of the environmental situation in Krasnoyarsk, is demonstrated.

Changes in winter low flow (WLF) in cold-region rivers affect engineering design, water quality, and river ecosystem health. This paper aims to quantify to what extent WLF will change under climate warming and to propose a practical forecasting model for WLF predictions. The new concept of cumulative watershed temperature (CWT) is used as a convenient lumped surrogate for complicated hydrological processes that influence WLF. Statistical analyses of century-long flow data from the Fraser River in British Columbia, Canada show a strong dependence of WLF on CWT. In winter season, time series of CWT and WLF are shown to each divide into a falling and a rising limb at the data point of their lowest values, being −358 °C and 827 m3/s (historical averages), respectively. The falling and rising limbs describe the cumulative freezing and thawing effects of air temperatures fluctuating around the freezing point on WLF changes. The correlation between CWT and WLF (time series) data points on the rising limbs forms the forecasting model, expressing WLF as a function of CWT in terms of their z-scores. The model takes input of Global Circulation Model (GCM) projections of temperature increases by the end of 21st century under different Representative Concentration Pathways (RCPs), and predicts changes of Fraser River WLF from the historical average. RCP4.5 causes a 22.6% increase (ensemble average from six GCMs). RCP8.5 increases WLF by 20% (for some future years) to 44% (for others). The methods reported in this paper can be adapted to other cold regions.

Water supply management for hydroclimatic extremes has commonly been analysed using the cumulative difference between inflow and demand, a concept known as the Residual Mass Curve. This paper extends the residual mass concept to develop a new method to quantify water availability, termed the Residual Mass Severity Index (RMSI). The RMSI improves on the Residual Mass Curve by allowing extreme deficit periods to be easily identified without the need for manual inspection of the Residual Mass Curve. Another advantage of the RMSI is that it does not require a temporal window to be specified to characterise extreme deficit periods, which is needed for many drought indices such as the Standardized Precipitation Index (SPI). This paper develops the method for calculating the RMSI using precipitation time series and compares it to the SPI for different drought durations across Australia. Major hydroclimatic extremes during the instrumental period are assessed using RMSI, SPI, and by comparing the RMSI estimates with streamflow data from 467 catchments with varying sizes and climate across Australia. RMSI is a useful index for water managers interested in assessing water availability with potential applicability in summarising the features of historical hydroclimatic extremes as well as future changes in water availability due to anthropogenic climate change.

The “Crossing the Desert” mini-game needs to consider a variety of mutually restrictive factors. Players must coordinate funding and path issues to find the optimal strategy to reach the end within the specified time. Based on the study of crossing the desert when the weather conditions are known, this paper establishes a topology model, and uses priority search and game theory to solve the player’s optimal strategy for passing through the barriers. First, the entire map is digitized and represented by a general topological map; then, given the map and weather distribution, the highest profit of each path is calculated. Specific calculation details require further analysis to arrive at a more practical and efficient route planning plan. The model proposed in this paper only provides a more effective solution for this problem from the perspective of mathematical modeling.

Although salinity satellites can provide high-resolution global sea surface salinity (SSS) data, the satellite data still display large errors close to the coast. In this paper, a nonlinear empirical method based on random forest is proposed to correct two Soil Moisture and Ocean Salinity (SMOS) L3 products in the tropical Indian Ocean, including SMOS BEC and SMOS CATDS data. The agreement between in-situ data and the corrected SMOS data is better than that between in-situ data and the original satellite data. The root-mean-square deviation (RMSD) of the satellite SSS data decreased from 0.366 to 0.275 and from 0.367 to 0.255 for SMOS BEC and SMOS CATDS, respectively. The effect of the correction model was better in the Arabian Sea than in the Bay of Bengal. The RMSD of corrected BEC (CATDS) SSS was reduced from 0.44 (0.48) to 0.276 (0.269), and the correlation coefficient was increased to 0.915 from 0.741(0.801) in the Arabian Sea while the correlation coefficient improved less than 0.02 in the Bay of Bengal. The cross-validation results highlight the robustness and effectiveness of the correction model. Additionally, the effects of different features on the correction model are discussed to demonstrate the vital role of geographical information in the correction of satellite SSS data. The proposed method outperformed other machine-learning methods with respect to the RMSD and correlation coefficient.

Resumo Esse trabalho apresenta uma análise da relação entre a climatologia das chuvas e as ocorrências de incêndios em vegetação nos municípios do Estado do Ceará no entorno da Rodovia CE-060 (Maracanaú, Pacatuba, Guaiuba, Redenção, Acarape, Aracoiaba e Baturité), rota que vai da capital Fortaleza/CE até o município de Baturité/CE (área de Proteção Ambiental da Serra de Baturité), região de interesse econômico do Estado do Ceará. Foram analisadas as ocorrências de incêndios utilizando os dados do programa BDQueimadas do Instituto Nacional de Pesquisas Espaciais - INPE e correlacionadas com os dados de precipitação obtidos nas Plataformas de Coletas de Dados (PCD) da Fundação Cearense de Meteorologia e Recursos Hídricos (FUNCEME). Os resultados mostram que a prática das queimadas nestas regiões ocorre com maiores intensidades no segundo semestre do ano (período seco da região), fato que explica a baixa correlação estatística entre o total de precipitação acumulada e total de focos de incêndio observados na região. Em adição, observa-se que a ocorrência de focos de incêndios em vegetação no período que antecipa a estação chuvosa, devido a prática da limpeza de áreas para o plantio, encontra condições atmosféricas que contribui para grandes incêndios em vegetação nestas regiões. Abstract This paper presents an analysis of the relationship between the climatology of rainfall and the occurrence of vegetation fires in municipalities in the State of Ceará around Highway CE-060 (Maracanaú, Pacatuba, Guaiuba, Redenção, Acarape, Aracoiaba and Baturité), a route that it runs from the capital Fortaleza/CE to the municipality of Baturité/CE (Serra de Baturité Environmental Protection Area), a region of economic interest in the State of Ceará. Fire occurrences were analyzed using data from the BDQueimadas program of the National Institute for Space Research - INPE and correlated with precipitation data obtained from the Data Collection Platforms (PCD) of the Cearense Foundation of Meteorology and Water Resources (FUNCEME). The results show that the practice of burning in these regions occurs with greater intensity in the second half of the year (dry period in the region), a fact that explains the low statistical correlation between the total accumulated precipitation and the total number of fires observed in the region. In addition, it is observed that the occurrence of fires in vegetation in the period that anticipates the rainy season, due to the practice of cleaning areas for planting, encounters atmospheric conditions that contribute to large fires in vegetation in these regions.

Tropical cyclones undergo extratropical transition (ET) in every ocean basin. Projected changes in ET frequency under climate change are uncertain and differ between basins, so multimodel studies are required to establish confidence. We used a feature-tracking algorithm to identify tropical cyclones and performed cyclone phase-space analysis to identify ET in an ensemble of atmosphere-only and fully coupled global model simulations, run at various resolutions under historical (1950–2014) and future (2015–50) forcing. Historical simulations were evaluated against five reanalyses for 1979–2018. Considering ET globally, ensemble-mean biases in track and genesis densities are reduced in the North Atlantic and western North Pacific when horizontal resolution is increased from ∼100 to ∼25 km. At high resolution, multi-reanalysis-mean climatological ET frequencies across most ocean basins as well as basins’ seasonal cycles are reproduced better than in low-resolution models. Skill in simulating historical ET interannual variability in the North Atlantic and western North Pacific is ∼0.3, which is lower than for all tropical cyclones. Models project an increase in ET frequency in the North Atlantic and a decrease in the western North Pacific. We explain these opposing responses by secular change in ET seasonality and an increase in lower-tropospheric, pre-ET warm-core strength, both of which are largely unique to the North Atlantic. Multimodel consensus about climate change responses is clearer for frequency metrics than for intensity metrics. These results help clarify the role of model resolution in simulating ET and help quantify uncertainty surrounding ET in a warming climate. All authors received financial support from the PRIMAVERA project (European Commission Horizon2020 Grant Agreement 641727) with data access via JASMIN (https://jasmin.ac.uk) supported by IS-ENES3 (Grant Agreement 824084). AJB also received support from National Environmental Research Council (NERC) national capability grant for the North Atlantic Climate System: Integrated study (ACSIS) program (Grants NE/N018001/1, NE/N018044/1, NE/N018028/1, and NE/N018052/1). KL received funding from the German Federal Ministry of Education and Research (BMBF) through JPI Climate/JPI Oceans NextG-Climate Science-ROADMAP (FKZ: 01LP2002A). The authors are grateful to the editor and to three anonymous reviewers, whose recommendations improved this paper. AJB, PLV, RJH, and MJR conceived the study. Simulations were performed by MJR, ET, KL, CDR, and LT. Output data were managed by JS. MJR performed the cyclone tracking. BV computed the Eady growth rate. AJB undertook cyclone phase-space analysis and all other data analyses, figure preparation, and wrote the manuscript. All authors provided input in interpreting results and approved the final manuscript. The authors declare no competing interests. Peer Reviewed "Article signat per 13 autors/es: Alexander J. Baker, Malcolm J. Roberts, Pier Luigi Vidale, Kevin I. Hodges, Jon Seddon, Benoît Vannière, Rein J. Haarsma, Reinhard Schiemann, Dimitris Kapetanakis, Etienne Tourigny, Katja Lohmann, Christopher D. Roberts, and Laurent Terray"

Climate change has become a real challenge in different fields, including the building sector. Understanding and assessing the impact of climate change on building energy performance is still necessary to elaborate new climate-adaptive design measures for future buildings. The building energy consumption for heating and cooling is mainly related to the building envelope thermal performance. In this study, the winter heat loss and summer heat gain indicators are proposed to assess and analyse the potential impact of climate change on opaque building envelope elements for different climate zones in Morocco over the next 40 years. For that purpose, a one-dimensional heat transfer model is used to simulate the heat transfer through the multi-layer structure of the wall/roof. A medium climate change scenario is considered in this study. The results showed that the current average walls and roof summer heat gain is expected to increase of about 19.2–54.3% by the 2060s depending on the climate zone, versus a less important decrease in winter heat loss varies between –10.6 and –20.6%. This paper provides a reliable evaluation of the climate change impact on building envelope thermal performance, which leads to better adjustments in future building envelope designs.

Equilibrium modelling, also known as spin-up, is a technique for initializing a stable thermal regime in ground temperature models for permafrost regions. The results act as a baseline for subsequent transient analyses of ground temperature response to climate change or infrastructure. In practice, spin-up procedures are often loosely described or neglected, and the criteria by which a stable thermal regime is evaluated are rarely defined or presented explicitly. In this paper, model results show that no single criterion based on thresholds of inter-cycle temperature change can be used to identify a stable thermal regime in all spin-up scenarios. Results from simulations using a wide range of initialization temperatures and conditions show the number of spin-up cycles can range between 10 and 10 000, and a spin-up criterion as fine as 0.00001 °C/cycle is required to achieve a stable thermal regime suitable for deeper warm permafrost models. The implications of selected threshold criteria are examined in follow-up transient analyses and show that warm permafrost models can be highly sensitive to initial temperature profiles based on the criterion used. The results alert scientists and engineers to the importance of initialization on site-specific and regional permafrost models for transient ground temperature analyses.

Significance Statement: It is well established that human activity (particularly increased greenhouse gas emissions) is the primary driving mechanism of the recent dramatic warming in the Arctic. However, the causes of a similar warming here in the first half of the twentieth century remain uncertain. The limited knowledge about the climate of that period—which mainly results from the low resolution of data—is a significant obstacle to a definitive determination of the forcing mechanisms. Therefore, the main aim of our paper is to improve our understanding of specific aspects of weather and climate (including extremes) using long-term series of daily and subdaily data that have rarely been applied for this purpose. This new, more comprehensive knowledge about the historical Arctic climate should allow the scientific community (particularly climate modelers) to better validate both climate models and reanalysis products and, consequently, to more precisely identify the causes of the early-twentieth-century Arctic warming. Data availability statement: Datasets for this research were derived from the following public domain resources: 1) All-Russia Research Institute of Hydrometeorological Information–World Data Centre (RIHMI-WDC), http://meteo.ru/; 2) The Government of Canada (Environment and Climate Change Canada), https://climate.weather.gc.ca/; 3) Danish Meteorological Institute (DMI), https://www.dmi.dk/publikationer/ [as cited in Cappelen (2020)]. A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the early-twentieth-century Arctic warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and subdaily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from 10 individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days, day-to-day temperature variability, and the onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the contemporary Arctic warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7°C) and Canadian Arctic (1.9°C) regions. A shortening of winter and lengthening of summer were noted. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW.

One of the most prolific tornado outbreaks ever documented occurred on 26–27 April 2011 and comprised three successive episodes of tornadic convection that culminated with the development of numerous long-track, violent tornadoes over the southeastern United States during the afternoon of 27 April. This notorious afternoon supercell outbreak was preceded by two quasi-linear convective systems (hereinafter QLCS1 and QLCS2), the first of which was an anomalously severe nocturnal system that rapidly grew upscale during the previous evening. Here in Part II, we use a series of RUC 1-h forecasts and output from convection-permitting WRF-ARW simulations configured both with and without latent heat release to investigate how environmental modifications and upscale feedbacks produced by the two QLCSs contributed to the evolution and exceptional severity of this multiepisode outbreak. QLCS1 was primarily responsible for amplifying the large-scale flow pattern, inducing two upper-level jet streaks, and promoting secondary surface cyclogenesis downstream from the primary baroclinic system. Upper-level divergence markedly increased after QLCS1 developed, which yielded strong isallobaric forcing that rapidly strengthened the low-level jet (LLJ) and vertical wind shear over the warm sector and contributed to the system’s upscale growth and notable severity. Moreover, QLCS2 modified the mesoscale environment prior to the supercell outbreak by promoting the downstream formation of a pronounced upper-level jet streak, altering the midlevel jet structure, and furthering the development of a highly ageostrophic LLJ over the Southeast. Collectively, the flow modifications produced by both QLCSs contributed to the notably favorable shear profiles present during the afternoon supercell outbreak. Significance Statement The tornado outbreak that impacted the United States on 26–27 April 2011 was part of an extended outbreak that produced 343 tornadoes and numerous fatalities. This paper is Part II of a study that describes the meteorological factors supporting such a prolific event. Herein we investigate the convectively forced environmental modifications that occurred during a 36-h period encompassing three successive convective episodes. The first two episodes collectively altered the upper-level flow pattern and markedly enhanced low-level winds throughout the warm sector. These modifications served as upscale feedbacks that contributed to the first episode’s exceptional severity and to the remarkable vertical shear profiles that supported numerous long-track and violent tornadoes during the final episode on the afternoon of 27 April.

A cloud-resolving model is used to examine the intensification of tilted tropical cyclones from depression to hurricane strength over relatively cool and warm oceans under idealized conditions where environmental vertical wind shear has become minimal. Variation of the SST does not substantially change the time-averaged relationship between tilt and the radial length scale of the inner core, or between tilt and the azimuthal distribution of precipitation during the hurricane formation period (HFP). By contrast, for systems having similar structural parameters, the HFP lengthens superlinearly in association with a decline of the precipitation rate as the SST decreases from 30° to 26°C. In many simulations, hurricane formation progresses from a phase of slow or neutral intensification to fast spinup. The transition to fast spinup occurs after the magnitudes of tilt and convective asymmetry drop below certain SST-dependent levels following an alignment process explained in an earlier paper. For reasons examined herein, the alignment coincides with enhancements of lower–middle-tropospheric relative humidity and lower-tropospheric CAPE inward of the radius of maximum surface wind speed rm. Such moist-thermodynamic modifications appear to facilitate initiation of the faster mode of intensification, which involves contraction of rm and the characteristic radius of deep convection. The mean transitional values of the tilt magnitude and lower–middle-tropospheric relative humidity for SSTs of 28°–30°C are respectively higher and lower than their counterparts at 26°C. Greater magnitudes of the surface enthalpy flux and core deep-layer CAPE found at the higher SSTs plausibly compensate for less complete alignment and core humidification at the transition time.

The frontal structures of extratropical cyclones developing in the northwestern Pacific storm track are relatively poorly understood compared with those in Europe and the Atlantic Ocean, for which representative conceptual models have been developed. In this paper, the structures of cyclones and their associated fronts in the northwestern Pacific (NP), as well as in the Okhotsk Sea and Sea of Japan (OJ), are examined at their developing and mature stages using Japanese 55-year Reanalysis dataset. Furthermore, the frontal structures in the NP are compared with those in the northwestern Atlantic (NA). At the time of maximum deepening rate, cyclones in the NP are accompanied by strong warm and cold fronts, whereas cyclones in the OJ are more frequently accompanied by cold fronts than by warm fronts and tend to have stronger cold fronts than warm fronts. The weaker warm fronts than cold fronts to the east and northeast of cyclones in the OJ is likely due to the cyclones developing to the north and away from the region where the horizontal gradient of environmental potential temperature is strong. A comparison between mature cyclones in the NP and NA shows that the warm fronts in the NA tend to extend northeastward, whereas those in the NP extend more southeastward. These differences in warm fronts between NP and NA are suggested to be due to the difference in the horizontal structures of the warm currents between NP and NA.

Interdecadal variations of the relationship between El Niño–Southern Oscillation (ENSO) and the Indo-China Peninsula (ICP) surface air temperature (SAT) in winter are investigated in the study. Generally, there exists a positive correlation between them during 1958–2015 because the ENSO-induced anomalous western North Pacific anticyclone (WNPAC) is conducive to pronounced temperature advection anomalies over the ICP. However, such correlation is unstable in time, having experienced a high-to-low transition around the mid-1970s and a recovery since the early 1990s. This oscillating relationship is owing to the anomalous WNPAC intensity in different decades. During the epoch of high correlation, the anomalous WNPAC and associated southwesterly winds over the ICP are stronger, which brings amounts of warm temperature advection and markedly heats the ICP. In contrast, a weaker WNPAC anomaly and insignificant ICP SAT anomalies are the circumstances for the epoch of low correlation. It is also found that substantial southwesterly wind anomalies over the ICP related to the anomalous WNPAC occur only when large sea surface temperature (SST) anomalies over the northwest Indian Ocean (NWIO) coincide with ENSO (viz., when the ENSO–NWIO SST connection is strong). The NWIO SST anomalies are capable of driving favorable atmospheric circulation that effectively alters ICP SAT and efficiently modulates the ENSO–ICP SAT correlation, which is further supported by numerical simulations utilizing the Community Atmospheric Model, version 4 (CAM4). This paper emphasizes the non-stationarity of the ENSO–ICP SAT relationship and also uncovers the underlying modulation factors, which has important implications for the seasonal prediction of the ICP temperature.

Model simulations suggest that Madden-Julian Oscillation (MJO) activity changes under the anthropogenic climate change background. However, satellite observations, which provide information of MJO convection activity, are not available before the 1970s, hindering research on the historical long-term variability of MJO. This study aims at extending the data length of MJO indices that include both MJO circulation and convection features, such as the widely used Real-Multivariate MJO (RMM) index, to the pre-satellite era. This paper introduces a new MJO index construction method, of which the outgoing longwave radiation (OLR) input is derived from upper-level geopotential, and names it as the Geopotential-based Multivariate MJO (GMM) index. The GMM index is derived over 1902–2008 and compared with the filtered version of RMM (FMM) index during 1981–2008. The GMM index is shown to (1) have the same climatological properties as the FMM index, (2) be statistically highly correlated to the FMM index, and (3) be able to indicate MJO activities and its convection features in the pre-satellite era. The overall bivariate correlation between FMM index and GMM index based on ERA-20C ranges from 0.959 to 0.968 in different phases. Evaluation results confirm the validity of the proposed MJO index construction method, which could capture MJO convection activity in the pre-satellite era and can be applied to all MJO indices that require input of OLR. This study provides an alternative way that overcomes the difficulty of historical MJO studies, and will be beneficial to our understanding of the long-term change of MJO.

17 pages, 13 figures, 1 table.-- Data availability: The product (Martínez et al., 2019) is freely distributed on the BEC (Barcelona Expert Center) web page (http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019) and on the Digital CSIC server: https://digital.csic.es/handle/10261/219679 (last access: 25 January 2022). Data can be downloaded from the FTP service: http://bec.icm.csic.es/bec-ftp-service/ (last access: 25 January 2022). The maps are distributed in the standard grid EASE-Grid 2.0, which has a spatial resolution of 25 km. In addition to the product validated in this work (L3 with temporal resolution of 9 d), L3 products having a temporal resolution of 3 and 18 d and the L2 product are available. These Arctic SSS products cover the period from 2011 to 2019.-- This work represents a contribution to the CSIC Thematic Interdisciplinary Platform PTI Teledetect and PolarCSIC. Argo data were collected and made freely available by the International Argo program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org, last access: 25 January 2022). The Argo program is part of the Global Ocean Observing System, Measuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K psu−1), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K psu−1), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, the ESA launched a specific initiative in 2019, the Arctic+Salinity project (AO/1-9158/18/I-BG), to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product (Martínez et al., 2019) . The product consists of 9 d averaged maps in an EASE 2.0 grid of 25 km. The product is freely distributed from the Barcelona Expert Center (BEC, http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019). The major change in this new product is its improvement of the effective spatial resolution that permits better monitoring of the mesoscale structures (larger than 50 km), which benefits the river discharge monitoring, This work has been carried out as part of the ESA Arctic+Salinity project (AO/1-9158/18/I-BG), which permitted the production of the database, and the Ministry of Economy and Competitiveness, Spain, through the National R&D Plan under L-BAND project ESP2017-89463-C3-1-R. [...] With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

Starting in mid-November, China was hit by several cold events during the early winter of 2020/21. The lowest temperature observed at Beijing station on 7 January reached −19.6°C. In this paper, we show that the outbreak of the record-breaking extreme cold event can be attributed to a huge merging Ural blocking (UB) ridge over the Eurasian region. The sea-ice cover in the Kara and East Siberia Seas (KESS) in autumn was at its lowest value since 1979, which could have served as a precursor signal. Further analysis shows that several successive UB episodes occurred from 1 September 2020 to 10 January 2021. The persistent UB that occurred in late September/early October 2020 may have made an important contribution to the October historical minimum of sea ice in the KESS region. Our results also show that, after each UB episode in winter, significant upward propagation of wave activity occurred around 60°E, which resulted in weakening the stratospheric vortex. Meanwhile, each UB episode also caused a significant reduction in sea-ice extent in KESS and a significant weakening of the westerly jet in mid–high-latitude Eurasia. Results suggest that the Arctic vortex, which is supposed to enhance seasonally, became weaker and more unstable than the climatic mean under the seasonal cumulative effects of UB episodes, KESS warming, and long-lasting negative-phase North Atlantic Oscillation (NAO–). Those seasonal cumulative effects, combined with the impact of La Niña winter, led to the frequent occurrence of extreme cold events.

Monitoring precipitation forecast skill in global numerical weather prediction (NWP) models is an important yet challenging task. Rain gauges are inhomogeneously distributed, providing no information over large swathes of land and the oceans. Satellite-based products, on the other hand, provide near-global coverage at a resolution of ∼10–25 km, but limitations on data quality (e.g., biases) must be accommodated. In this paper the stable equitable error in probability space (SEEPS) is computed using a precipitation climatology derived from the Tropical Rainfall Measuring Mission (TRMM) TMPA 3B42 V7 product and a gauge-based climatology and then applied to two global configurations of the Met Office Unified Model (UM). The representativeness and resolution effects on an aggregated SEEPS are explored by comparing the gauge scores, based on extracting the nearest model grid point, with those computed by upscaling the model values to the TRMM grid and extracting the TRMM grid point nearest the gauge location. The sampling effect is explored by comparing the aggregate SEEPS for this subset of ∼6000 locations (dictated by the number of gauges available globally) with all land points within the TRMM region of 50°N and 50°S. The forecast performance over the oceanic areas is compared with performance over land. While the SEEPS computed using the two different climatologies should never be expected to be identical, using the TRMM climatology provides a means of evaluating near-global precipitation using an internally consistent dataset in a climatologically consistent way.

ISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1° grid, all other gridded products at 1.0°-equivalent equal area, separate satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data, expanded documentation, the processing code, and an operations guide are available online. Notable changes are 1) a lowered ice–liquid temperature threshold, 2) a treatment of the radiative effects of aerosols and surface temperature inversions, 3) refined specification of the assumed cloud microphysics, and 4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high cloud and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud-top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events.

The daily evolution of the Equatorial Ionization Anomaly (EIA) and the Equatorial Electrojet (EEJ) exhibits phase difference, which reflects the response time of the F-region equatorial plasma fountain to the E-region electric field variation. Studies on this response time contribute to clarifying the relative importance of different influence factors on the low-latitude E- and F-region coupling process. However, the solar-cycle, seasonal and longitudinal dependence of this response time has not yet been comprehensively revealed. In this paper, the occurrence time of the daytime most developed northern EIA crest (TEIA), the occurrence time of the daytime strongest EEJ (TEEJ), and their time delay (δT = TEIA-TEEJ) during 2008 to 2018 are derived from total electron content and magnetometer data, and the seasonal and solar-cycle variations of these parameters are analyzed and compared between the eastern Asian and American sectors. Main results are as follows. (1) TEIA and δT share similar seasonal and solar-cycle variation patterns, which are different from TEEJ. (2) The prevailing seasonal variation pattern of TEIA is generally consistent in the two sectors, which is earlier (later) in the boreal winter (summer). This feature is not determined by the variations of TEEJ or EEJ strength. (3) The solar-cycle variation pattern of TEIA is different between the eastern Asian and American sectors, but the 11-yr averaged TEIA is nearly the same in the two sectors. The solar-cycle and longitudinal dependencies are probably due to the combined effect of electric field, meridional wind, and local geomagnetic field configuration.

In this paper, the different effects of the eastern equatorial Pacific (EP) and central equatorial Pacific (CP) Ocean El Niño–Southern Oscillation (ENSO) events on interannual variation in the diurnal sea surface temperature (SST) are explored in both the Niño-3 and Niño-4 regions. In the Niño-3 region, the diurnal SST anomaly (DSSTA) is negative during both EP and CP El Niño events and becomes positive during both EP and CP La Niña events. However, the DSSTA in the Niño-4 region is positive in El Niño years and negative in La Niña years, which is opposite to that in the Niño-3 region. Further analysis indicates that the incident shortwave radiation (SWR), wind stress (WS), and upward latent heat flux (LHF) are the main factors causing the different interannual variations in the DSST. In the Niño-3 region, decreased SWR and increased LHF lead to a negative DSSTA in EP El Niño years, and enhanced WS and increased LHF cause a negative DSSTA in CP El Niño years. Conversely, in that same region, increased SWR and decreased LHF lead to a positive DSSTA in EP La Niña years, and reduced WS and decreased LHF cause a positive DSSTA in CP La Niña years. In the Niño-4 region, the reduced trade wind plays a key role in producing the positive DSSTA, whereas the decreased SWR has an opposite effect that reduces the range of the DSSTA during both EP and CP El Niño events, and conversely the enhanced trade wind plays a key role in producing the negative DSSTA, whereas the increased SWR has an opposite effect that increases the range of the DSSTA during both EP and CP La Niña events.

In this paper, the China’s first global ocean Climate Data Records (CDRs) are used to analyze and predict the sea level changes in the Yellow Sea with obvious seasonal changes. Based on the singular spectrum analysis (SSA) method, the spatiotemporal and time series of sea level anomalies (SLAs) in the Yellow Sea are decomposed and de-noised. Then the long short-term memory (LSTM) neural network is combined with the SSA to establish the SSA-LSTM combined model to predict the sea level trends of the Yellow Sea. Compared with the traditional methods, the prediction accuracy of SSA-LSTM combined model is significantly improved with minimum 35.04 mm RMSE values for the SLA time series prediction. For the one-year prediction of spatiotemporal series of SLA, the minimum RMSE values are only 19.68 mm. The law of spatial and temporal differentiation of the sea level change in the Yellow Sea is also analyzed by temporal empirical orthogonal function. It is found that the sea level trend of the Yellow Sea is highly consistent and significantly related to the season and latitude. According to the SSA-LSTM combined model, the sea level rise rate of the Yellow Sea will remain at 3.65 ± 0.79 mm/year in the next ten years.

Secondary eyewall formation and the ensuing eyewall replacement cycles may take place in mature tropical cyclones (TCs) during part of their lifetime. A better understanding of the underlying dynamics is beneficial to improving the prediction of TC intensity and structure. Previous studies suggested that the barotropic instability (BI) across the moat (aka type-2 BI) can make a substantial contribution to the inner-eyewall decay through the associated eddy radial transport of absolute angular momentum (AAM). Simultaneously, the type-2 BI can also increase the AAM of the outer eyewall. While the previous studies focused on the early stage of the type-2 BI, this paper explores the long-term effect of the type-2 BI and the underlying processes in forced and unforced shallow-water experiments. Under the long-term effect, it will be shown that the inner eyewalls repeatedly weaken and strengthen (while the order is reversed for the outer eyewalls). Sensitivity tests are conducted to examine the sensitivity of the long-term effect of the type-2 BI to different vortex parameters and the strength of the parameterized diabatic heating. Implication of the long-term effect for the intensity changes of the inner and outer eyewalls of real TCs are also discussed.

Purpose This study aims to prove that land-use change plays a role in the occurrence of hydro-meteorological disasters in Central Java, especially in relation to its upstream and downstream. Design/methodology/approach The paper presents empirical findings from quantitative research using a spatial analysis and descriptive analysis. Findings The upstream and downstream area of Central Java is categorized as a rapid development area that results in changes in land use and land cover. The findings showed that there was an increasing number of hydrometeorological disasters such as floods and landslides as the impact of land-use change and rainfall conditions. Research limitations/implications Analysis of the relationship between rainfall and disaster events with more technical and specific analysis could be done in the further research. Originality/value In this study, more analysis in the context of river basin systems including upstream and downstream in different periods to examine the linkage between them have been considered and incorporated.

This paper presents a detailed spatiotemporal analysis of the rainfall variability, seasonality, and the extreme characteristics of Tehri catchment located in the lower Himalayan region in India. To this end, the daily rainfall data is extracted from 22 grids for 117 years (1901–2017) from the high-resolution (0.25° × 0.25°) gridded observation dataset. Monthly rainfall distribution is evaluated using precipitation concentration index (PCI) and seasonality index. The extreme rainfall indices, viz., maximum 1-day rainfall (Rx1Day), maximum 5-day rainfall (Rx5Day), number of rainy days (NxRainy), total precipitation in rainy days (PRCPTOT), number of heavy rainfall events (NxHeavy), maximum consecutive wet days (CWD), and simple daily intensity index (SDII) are computed for each year considering the thresholds suggested by India Meteorological Department (IMD). The Mann–Whitney-Pettitt test when applied to the annual rainfall time series revealed the year 1958 to be the statistically significant change point. The non-parametric modified Mann–Kendall and Sen’s slope tests are employed to detect the trend in monthly, seasonal, annual rainfall time series, extreme precipitation indices, and seasonality indices for both the pre- and post-1958 periods. The annual rainfall over the grids mostly possessed higher negative trends during 1959–2017 than those during 1901–1958, mainly due to the decreasing trends in post-monsoon and winter seasons. Compared to 1901–1958, NxRainy, CWD, and PRCPTOT exhibited a remarkable decreasing trend whereas NxHeavy, Rx1Day, Rx5Day, and SDII exhibited higher positive trends during 1959–2017, indicating intensification of precipitation. The precipitation over the catchment has been more concentrated in the latter epochs of monsoon season and annual rainfall and it is also evident from the increasing trends of the seasonality indices. There is no such study dealing comprehensively with identification of extreme characteristics, seasonality/concentration characteristics, and various categorical trends of precipitation in a Himalayan region reported in literature. This study will be useful in understanding the decreasing trend of precipitation volume coupled with increasing intensity and concentration and it is quite critical for a Himalayan catchment.

In 2016–2018, the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project undertook 3-month-long deployments to the southeastern (SE) Atlantic Ocean using research aircraft to better understand the impact of biomass burning (BB) aerosol transport to the SE Atlantic Ocean on climate. In this (part 1 of the meteorological overview) paper, the climatological features at monthly timescales are investigated. The southern African easterly jet (AEJ-S), defined as the zonal easterlies over 600–700 hPa exceeding 6 m s−1 around 5–15∘ S, is a characteristic feature of the mid-level circulation over southern Africa that was also during the deployment months of August 2017, September 2016, and October 2018. Climatologically, the AEJ-S develops at lower altitudes (∼ 3 km; 700 hPa) between 5–10∘ S in August, while it develops at around 4 km (∼ 600 hPa) and further south (5–15∘ S) in September and October, largely driven by the strong sensible heating over the African plateau. Notable meteorological anomalous characteristics during the 3 deployment months, compared to climatology (2000–2018), include the following: (1) during August 2017, the AEJ-S was weaker than the climatological mean, with an additional anomalous upper-level jet aloft (∼ 6 km) around 10∘ S. August 2017 was also drier over the SE Atlantic at 600–700 hPa than climatology, with a stronger Benguela low-level jet (LLJ) at 925–950 hPa along the Namibian coast of the SE Atlantic. Consistent with this, the southern Atlantic anticyclone was also stronger and closer to the coast than the August climatological mean. (2) During September 2016, the AEJ-S intensity was similar to the climatological mean, although the heat low and vertical motion over the land was slightly stronger compared to the September climatology. The LLJ and the large-scale southern Atlantic anticyclone were stronger than the climatological mean. (3) During October 2018, the AEJ-S was slightly weaker compared to the climatological mean, as was the LLJ and the southern Atlantic anticyclone. October 2018 was wetter over the Benguela coastal region at 600 hPa than the climatological mean. During all the deployment months, the sea surface temperatures (SST) over the SE Atlantic were warmer than the climatological means, but the monthly mean low cloud fraction was only noticeably reduced in August 2017. A weak August 2017 AEJ-S can explain low offshore black carbon (BC) mixing ratios within the European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, although the BC peak altitude, at 2–3 km, is below that of the AEJ-S. The upper-level wave disturbance and the associated anomalous circulation also explain the weakening of AEJ-S through the reduction of the strength of the heat low over the land during August 2017.

This paper investigates links between rainfall variability in the Ogooué River Basin (ORB) and El Niño Southern Oscillation (ENSO) in the Pacific Ocean. Recent hydroclimatology studies of the ORB and surrounding areas resulting in contrasting conclusions about links between rainfall variability and ENSO. Thus, to make the issue clearer, this study investigates the links between ENSO and rainfall in the ORB over the period 1940–1999. The principal component analysis of monthly rainfall in the ORB was done. The temporal mode of the first component corresponds to the interannual variations of rainfall on the ORB. Also, the pattern of the spatial mode of the first component shows that the ORB is a homogeneous hydroclimatic zone. However, no leading mode is significantly correlated to the ENSO index. A cross-wavelet analysis of the time series of basin-scale rainfall and the ENSO index was therefore carried out. The result is a set of periodogram structures corresponding to some ENSO episodes recorded over the study period. And wavelet coherence analysis of both time series confirms that there are significant links between ENSO and rainfall in the ORB.

Climate change leads to a more frequent occurrence of hot days (HDs) and hot nights (HNs). The consecutive occurrence of HDs and HNs (COHs) is often used as a measure of the persistence of an extremely hot spell. Nonetheless, the combined effect of air temperature and relative humidity on the changing COHs has never been studied. In this paper, we use an ensemble of global climate models and multiple thermal indices to robustly examine the combined effect of air temperature and relative humidity on COHs globally on an hourly basis. Our findings reveal that COHs show an increasing trend in the future and a strong latitudinal gradient increasing from high latitudes to the equator. Compared to COHs based on air temperature, the frequency of COHs based on perceived temperature is amplified by the combined effects of high temperature and humidity for both boreal and austral summers. To investigate the underlying mechanisms, we examine two different diurnal temperature ranges (DTRs), derived from air temperature and perceived temperature, for their corresponding types of COHs. Both DTRs are projected to increase in the future relative to the historical period from 1980 to 2004, but the DTR changes derived from perceived temperature are consistently larger than those derived from air temperature. Due to the nonlinearity in thermal indices, the perceived temperature in HDs and HNs rising faster than air temperature leads to a larger increase in perceived COHs. The COHs are further amplified by the increasing number of HNs and HDs that occur consecutively under wet conditions.

In recent decades, warming temperatures have caused sharp reductions in the volume of sea ice in the Arctic Ocean. Predicting changes in Arctic sea ice thickness is vital in a changing Arctic for making decisions about shipping and resource management in the region. We propose a statistical spatio-temporal two-stage model for sea ice thickness and use it to generate probabilistic forecasts up to three months into the future. Our approach combines a contour model to predict the ice-covered region with a Gaussian random field to model ice thickness conditional on the ice-covered region. Using the most complete estimates of sea ice thickness currently available, we apply our method to forecast Arctic sea ice thickness. Point predictions and prediction intervals from our model offer comparable accuracy and improved calibration compared with existing forecasts. We show that existing forecasts produced by ensembles of deterministic dynamic models can have large errors and poor calibration. We also show that our statistical model can generate good forecasts of aggregate quantities such as overall and regional sea ice volume. Supplementary materials accompanying this paper appear on-line.

For those involved in planning for regional and local scale changes in future climate, there is a requirement for climate information to be available in a context more usually associated with meteorological timescales. Here we combine a tool used in numerical weather prediction, the 30 weather patterns produced by the Met Office, which are already applied operationally to numerical weather prediction models, to assess changes in the UK Climate Projections (UKCP) Global ensemble. Through assessing projected changes in the frequency of the weather patterns at the end of the 21st Century, we determine that future changes in large-scale circulation tend towards an increase in winter of weather patterns associated with cyclonic and westerly wind conditions at the expense of more anticyclonic, settled/blocked weather patterns. In summer, the results indicate a shift towards an increase in dry settled weather types with a corresponding reduction in the wet and windy weather types. Climatologically this suggests a shift towards warmer, wetter winters and warmer, drier summers; which is consistent with the headline findings from the UK Climate Projections 2018. This paper represents the first evaluation of weather patterns analysis within UKCP Global. It provides a detailed assessment of the changes in these weather patterns through the 21st Century and how uncertainty in emissions, structural and perturbed parameters affects these results. We show that the use of these weather patterns in tandem with the UKCP projections is useful for future work investigating changes in a range of weather-related climate features such as extreme precipitation.

Thunderstorms accompanied with squalls cause a serious damage in Agartala and its neighbouring areas in the pre-monsoon season. In this paper, the synoptic conditions, stability indices and lower level wind pattern associated with squalls at Agartala (23.90° N, 93.25° E) during 2011 - 2020 are analysed to obtain their percentage contributions and critical values in occurrence of the events. Five major synoptic conditions are found to have contribution to the events, with varying percentages. The critical values of Showalter Index, Lifted Index, K-Index, SWEAT Index, Total Totals Index are obtained based on their contribution for at least 80% of the events. Wind direction at 925 hPa and 850 hPa with southerly component is found to be another important precursor for occurrence of the squalls.

In this paper we analyze Atlantic Ocean hurricane activity in the European Centre for Medium-Range Weather Forecasts (ECMWF) monthly hindcasts for the period 1998–2017. The main climatological characteristics of Atlantic tropical cyclone (TC) activity are considered at different lead times and across the entire ECMWF ensemble using three diagnostic variables: the number of tropical cyclones, the number of hurricanes, and the accumulated cyclone energy. The impacts of changing horizontal resolution and stochastic parameterization are clear in these diagnostic variables. The model skill scores for the number of tropical cyclones and accumulated cyclone energy by lead time are also computed. Using cluster analysis, we compare the characteristics of the forecast TC tracks with observations. Although four of the ECMWF clusters have similar characteristics to observed ones, one of the ECMWF clusters does not have a corresponding one in observations. We consider the predictability of each of these clusters, as well the modulation of their frequency by climate modes, such as the El Niño–Southern Oscillation and the Madden–Julian oscillation, taking advantage of the very large sample size of TC datasets in these hindcasts.

In this paper, we investigate the relationship between upper ocean heat content (OHC) and El Niño–Southern Oscillation (ENSO) sea surface temperature (SST) anomalies mainly using the neutral recharge oscillator (NRO) model both analytically and numerically. Previous studies showed that spring OHC, which leads SST by 6–12 months, represents a major source of predictability for ENSO. It is suggested that this seasonality is caused by the seasonally varying growth rate in SST anomalies. Moreover, a shortened ENSO period will lead to a reduced SST predictability from OHC, with the most significant decrease occurring in the latter half of the calendar year. The cross-correlation relationship between OHC and ENSO SST anomalies is further identified in the damped and self-excited version of the recharge oscillator model. Finally, we suggest that the seasonal growth rate of ENSO anomalies is the cause of the seasonality in the effectiveness of OHC as a predictor in ENSO forecasting, particularly as it relates to the boreal spring persistence barrier and associated spring predictability barrier. We also explain the shorter lead time between spring OHC and ENSO SST anomalies after the turn of the twenty-first century in terms of the apparent higher frequency of the ENSO period.

Line loss rate (LLR) is an important indicator of the service quality of power grid, and reducing line loss is the key to the sustainable development of electric power. Currently many researches focus on the LLR, however, most of them are based on theoretical data or a small amount of actual data, and rare studies on large scale actual data. In this paper, based on the data of China from 2013 to 2017, a comprehensive analysis in time domain and space domain of large-scale LLR is carried out through K-means clustering and temperature response model, including the time-domain evolution of LLR, the relationship between LLR and seasons, the composition of LLR level area, energy consumption characteristics and LLR distribution. It is found that, first, the annual LLR of China shows a downward trend, and the significant change cycle is similar to the per capita GDP. Second, the LLR in spring is significantly lower than that in other seasons, and shows a downward trend with the increase of temperature, which is consistent with the cumulative ownership ratio of air conditioning in that year. Third, in areas with high LLR, commercial users account for a large part of all users, and the proportion of users stealing electricity is significantly higher than that in general areas. Fourth, a novel healthy gradient evaluation index of LLR is established, and it is found that the distribution of LLR in unhealthy areas is close to normal distribution, while that in healthy areas is close to lognormal distribution.

Atmospheric CO2 anomaly (△XCO2) is essential in evaluating regional carbon balance. However, it is difficult to understand △XCO2 variation characteristics due to regional differences. This paper explored the inter-annual and inter-monthly variation patterns of △XCO2 in different regions of China based on satellite observations. The relation model between regional △XCO2 and anthropogenic emissions, gross primary productivity (GPP), wind speed, upwind region’s emission, and upwind region’s CO2 concentration was established. Results show that the annual average △XCO2 in the northwest and southeast regions is stable at around 0 and 1–2 ppm, respectively. Some municipalities directly under the central government and the southern coastal areas showed relatively intense inter-annual fluctuations. Four inter-monthly △XCO2 variation patterns were observed: the northern region has a stable change, the northeast region has the lowest in summer, the southwest region has the highest in summer, and the central region has no obvious change rule. Furthermore, △XCO2 in most areas can be explained by the emission–absorption–transportation model. Significant positive △XCO2 in the southern coastal region in summer may be related to the stable GPP seasonal variation and increased power generation. In the southwestern plateau region, it may be related to the low wind speed and increased soil emission with rising temperature. The stability of the plateau carbon sink and inter-regional cooperation cannot be ignored for improving regional atmospheric environments.

A twice-daily record of barometric pressure exists for Durham Observatory (54.768 °N, 1.584 °W, barometer cistern 107.3 m above mean sea level, MSL) from 23 July 1843 to 31 December 1960, and is published here for the first time. The Durham record, which is 98.7% complete, is by far the longest digital barometric pressure series in northern England, and fills a very large temporal and spatial gap in the International Surface Pressure Database (ISPD: Cram et al, 2015). In what is believed to be the first study of its kind, the record has been independently quality-controlled against the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3; Slivinski et al, 2019, 2020), which did not include the Durham records in its assimilation set. This paper describes the instruments used and their exposure, the sources of the record, digitisation work undertaken to generate the digital time series (including quality control assessments using 20CRv3), reduction to mean sea level pressure from station level observations, and examines consistency over the period of record against 20CRv3, concluding with a summary of monthly and annual means and extremes over the 117 year series and the details of the new dataset.

Accurate gridded precipitation data with high spatial and temporal scales are required for diverse studies such as climatology, meteorology, and hydrology. Currently, one of the sources of global precipitation estimation is the satellite-based precipitation estimate products. Nonetheless, their spatial resolution is often too coarse for usage in local region and basin scales or for parameterizing of meteorological and hydrological models at regional scales. In the present paper, a reconstruction method of satellite-based monthly precipitation was developed to attain improved pixel-based precipitation data with high spatial resolution on Golestan province in Northern Iran. In this endeavor, we considered the spatially heterogeneous relationships between tropical rainfall measuring mission (TRMM) precipitation and environmental variables utilizing the moving-window regression methods, the geographically weighted regression (GWR) and the mixed geographically weighted regression (MGWR) models. By in situ observations from rain gauges in the study area, the calibration and validation were performed, and the following conclusions were derived: (1) the proposed procedure had the ability to enhance both the spatial resolution and accuracy of satellite-based precipitation estimates; (2) the monthly reconstructed precipitation using the GWR model (CC = 0.69, bias = 0.75) and using the MGWR model (CC = 0.72, bias = 0.64) outperformed the TRMM-3B43V7 data (CC = 0.58, bias = 0.84) against ground observations; (3) this research offered a potential solution for producing gridded precipitation estimates at high spatial resolution.

This paper studies the influences of the Madden Julian Oscillation (MJO) on East Asian (EA) winter rainfall using the Singular Value Decomposition (SVD) approach. This method uses two-dimensional instead of the latitudinally-averaged variables in the commonly used Real-time Multivariate MJO (RMM) index. A comparison of the two approaches is made using the same OLR and zonal wind data over 37 boreal winter seasons of December – March. The SVD composite reveals a more conspicuous and coherent variation throughout the MJO cycle, while the RMM composite is more ambiguous. In particular, the SVD analysis identifies the convection anomalies over the Maritime Continent and the subtropical western Pacific (MCWP) as a major cause of enhanced rainfall in EA at RMM phases 8 and 1. This is at least one-eighth cycle earlier than the phases of convection development over Indian Ocean (IO) that were emphasized by previous studies. A linearized global baroclinic model is used to demonstrate the mechanism of MJO forcing on EA rainfall during various phases, with a focus on the MCWP cooling. The result shows that the anomalous MCWP cooling and the resultant low-level anticyclonic flow interact with the East Asian Jet, leading to an overall weakened EA winter monsoon circulation. The associated anomalous overturning circulation, with ascending motion and low-level horizonal moisture convergence in EA, contributes to the enhanced rainfall. This model result supports the interpretation of the SVD analysis, in that the MCWP-cooling induced anomalous meridional circulation is a more direct cause of enhanced EA rainfall than the IO-heating (or the IO-MCWP heating dipole) induced Rossby wave teleconnection.

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement.

Global warming projections of dynamics are less robust than projections of thermodynamics. However, robust aspects of the thermodynamics can be used to constrain some dynamical aspects. This paper argues that tropospheric expansion under global warming (a thermodynamical process) explains changes in the amplitude of the Quasi-Biennial Oscillation (QBO) in the lower and middle stratosphere (a dynamical process). A theoretical scaling for tropospheric expansion of approximately 6 hPa K−1 is derived, which agrees well with global climate model (GCM) experiments. Using this theoretical scaling, the response of QBO amplitude to global warming is predicted by shifting the climatological QBO amplitude profile upwards by 6 hPa per Kelvin of global warming. In global warming simulations, QBO amplitude in the lower- to mid-stratosphere shifts upwards as predicted by tropospheric expansion. Applied to observations, the tropospheric expansion framework suggests a historical weakening of QBO amplitude at 70 hPa of 3% decade−1 from 1953-2020. This expected weakening trend is half of the 6% decade−1 from 1953-2012 detected and attributed to global warming in a recent study. The previously reported trend was reinforced by record low QBO amplitudes during the mid-2000s, from which the QBO has since recovered. Given the modest weakening expected on physical grounds, past decadal modulations of QBO amplitude are reinterpreted as a hitherto unrecognized source of internal variability. This large internal variability dominates over the global warming signal, such that despite 65 years of observations, there is not yet a statistically significant weakening trend.