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Small data learning problems are characterized by a significant discrepancy between the limited number of response variable observations and the large feature space dimension. In this setting, the common learning tools struggle to identify the features important for the classification task from those that bear no relevant information and cannot derive an appropriate learning rule that allows discriminating among different classes. As a potential solution to this problem, here we exploit the idea of reducing and rotating the feature space in a lower-dimensional gauge and propose the gauge-optimal approximate learning (GOAL) algorithm, which provides an analytically tractable joint solution to the dimension reduction, feature segmentation, and classification problems for small data learning problems. We prove that the optimal solution of the GOAL algorithm consists in piecewise-linear functions in the Euclidean space and that it can be approximated through a monotonically convergent algorithm that presents—under the assumption of a discrete segmentation of the feature space—a closed-form solution for each optimization substep and an overall linear iteration cost scaling. The GOAL algorithm has been compared to other state-of-the-art machine learning tools on both synthetic data and challenging real-world applications from climate science and bioinformatics (i.e., prediction of the El Niño Southern Oscillation and inference of epigenetically induced gene-activity networks from limited experimental data). The experimental results show that the proposed algorithm outperforms the reported best competitors for these problems in both learning performance and computational cost. [ABSTRACT FROM AUTHOR]

The dynamical tropopause as a transport barrier between the tropical upper troposphere and extratropical lowermost stratosphere is characterized by steep gradients in potential vorticity (PV) along an isentropic surface. Hence, the latitudinal separation between the dynamical tropopause in the northern and southern hemispheres can be used as a metric of upper tropospheric width for assessing climate change impacts. Here, we obtain the PV gradient-based dynamical tropopause (PVG tropopause) from four meteorological satellite-era reanalyses (ERA5, ERA-Interim, JRA-55, MERRA-2) and investigate its climatology, variability and long-term trends ranging from 1980 to 2017. Our results show a distinct seasonal cycle with larger PV values and a poleward movement of the PVG tropopause in summer. The climatological tropopause PV values are substantially different between different reanalyses, but the tropopause latitude is similar. Significant inter-annual variability in the PVG tropopause latitude is related to El Niño Southern Oscillation (ENSO) and weaker variability also to the Quasi-Biennial Oscillation (QBO), and is consistently represented in reanalyses. In particular, El Niño causes equatorward shifts of the PVG tropopause, hence a decrease of upper tropospheric width. Long-term trends in the PVG tropopause over the period 1980–2017 exhibit a distinct vertical structure with poleward shifts below 340 K potential temperature, equatorward shifts between 340–370 K and poleward shifts between 370–380 K, implying an expansion of the troposphere at lower levels, a narrowing at upper levels and an expansion near the tropical tropopause. [ABSTRACT FROM AUTHOR]

The dynamical prediction of the Asian-Australian monsoon (AAM) has been an important and long-standing issue in climate science. In this study, the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide. Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences, especially for the second mode. The first AAM mode, from various seasonal sequences, coincides with the El Niño phase transition in the eastern-central Pacific. The second mode, initialized from boreal summer and autumn, leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring. Our findings hint that ENSO, as an early signal, is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes. Still, the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features. The multimodel ensemble (MME) mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features. The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes. The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services. [ABSTRACT FROM AUTHOR]

Three recently published papers including Napier et al. (2022, https://doi.org/10.1029/2021PA004355) utilize novel microanalytical approaches with varved marine sediments to demonstrate the potential to reconstruct seasonal and inter‐annual climate variability. Obtaining paleoclimate data at a resolution akin to the observational record is vitally important for improving our understanding of climate phenomena such as monsoons and modes of variability such as the El Niño Southern Oscillation, for which appraisals of past inter‐annual variability is critical. The ability to generate seasonal and inter annual resolution sea surface temperature proxy time series spanning a thousand years or more is revolutionary and has the potential to fill gaps in our knowledge of climate variability. Although generally limited to sediments from regions with oxygen depleted bottom waters, there is great potential to integrate shorter seasonal resolution climate "snap shots" from other archives such as annually banded corals into composite time series. But as paleoceanographic data are used more by the observational and modeling fields, we make the case for conducting a thorough case‐by‐case assessment of the processes that influence the climate signal recovered from proxies, using careful replication to validate new approaches. Understanding or exploring the potential influence of processes which effectively filter the climate signal will lead to more quantitative paleoceanographic data that will better serve the broader climate science community. Plain Language Summary: Year to year differences in the strength of climate phenomena like monsoons and El Niño drive droughts and floods with dramatic consequences for human society. The longest records of measurements of climate generally only extend back to the 1800s, meaning we have a very short period of data to assess the changing climate and test climate model predictions. To obtain longer records of climate we use proxies which relate a variable we can measure in an archive such as the width of growth bands of coral skeletons to a climate observation such as the temperature of the sea surface. Usually, proxy climate records from marine sediments would provide sea surface temperature (SST) values that are the average of some 100 or 1,000 years. However, a new technique to measure climate proxies at sub mm resolution now allows for marine sediments, especially those that accumulate distinctive dark and light layers with changing seasons, to be used in principle to produce SST proxy data for individual seasons and years. This enables records of year‐to‐year differences that extend for thousands of years to be created. These records will undoubtedly revolutionize our understanding of the climate system and how climate proxies work. Key Points: Novel micro‐analytical techniques allow seasonally resolved climate proxy data from varved marine sedimentsPotential to generate seasonal and inter annual resolution sea surface temperature proxy time series spanning >1,000 yearsThorough assessment of processes that influence the climate signal recovered from proxies, validated with careful replication, is required [ABSTRACT FROM AUTHOR]

Climate change is expected to make droughts more frequent and severe all over the world. South Korea is no exception and is already suffering from extreme droughts such as one that prolonged from 2013 to 2015 and caused nation‐wide damage. To mitigate drought damages, better management of existing water infrastructure is essential. A promising opportunity to improve operational decisions is to make use of seasonal weather forecasts that are provided by general circulation models and can be downscaled to the catchment scale. This study hence assesses the skill of seasonal forecasts over 20 catchments in South Korea, where the largest reservoirs are located. Datasets from four weather forecasting centres (ECMWF, UK Met Office, Météo France and DWD) have been evaluated over the period 2011–2020, and their skill quantified using the Continuous Ranked Probability Skill Score (CRPSS). We analyse how skill varies across the seasons and years, and if it can be linked to catchments characteristics. In doing so, we develop a methodology and a Python package to implement it, which is freely available for future applications to other regions. As for the study case, our results showed that among the four forecasting centres, ECMWF's forecasts were the most skilful in South Korea. In particular, seasonal forecasts outperform the climatology for 2 months of lead time and are more skilful during the wet season and in dry years. Linear bias correction is found to be useful to correct systematic seasonal biases, whereas we found no significant correlation between the catchment characteristics and forecast skill. We also investigated the possibility of anticipating dry years from seasonal forecasts and/or ENSO indices but found no significant link. [ABSTRACT FROM AUTHOR]

Here, I create a dataset of fronts in mid- and high latitudes by applying an objective front detection method to the JRA-55 reanalysis and try climate classification based on dynamic climatology from temperate to polar regions. Additionally, I describe the interannual variations and long-term trends in the frontal zone. The unique feature of this study lies in the methods used for frontal data creation. This includes adding the geopotential height condition at 500-hPa to the conventional thermal-based objective method with equivalent potential temperature, including incorporating latitude-dependent parameters. The former increased the similarity between fronts created by the objective method and manually counted fronts on surface weather maps, while the latter enabled an examination of climate classification based on dynamic climatology by increasing the frontal frequency at high latitudes. The areas where climatic zones can be clearly defined are limited to the east of the great mountains in the midlatitudes and the region where the Siberia-Canada Arctic frontal zone exists due to the obscuration or unclear seasonal movement of the frontal zones in other areas. The interannual variability in frontal zones is generally consistent with the characteristics of the regional climate variability associated with the El Niño Southern Oscillation, Pacific Decadal Oscillation, and Arctic Oscillation, as reported by previous studies. This study also reveals significant trends in some frontal zones since 1979, such as the northward shift in the eastern part of the North Pacific polar frontal zone during boreal autumn and winter and the decreasing frontal frequency on the northern coast of Norway in the European Arctic frontal zone from boreal winter to summer, including around the Beaufort Sea in the Siberia-Canada Arctic frontal zone in boreal summer. [ABSTRACT FROM AUTHOR]

Ultraviolet solar radiation that reaches the surface of the Earth has a very important role in the energy budget of our planet, although at certain amounts of exposure it can be harmful not only for human health, but animals and plants. Brazil is a tropical country receiving high intensity of UV radiation mostly of the year. UV radiation, specially UV-B is mainly absorbed in the ozone layer, changes in ozone content or ozone distribution directly affects UV radiation attenuation, so that surface UV. Ozone hole is characterized by an intense ozone depletion in the stratosphere in Antarctic region, happening during spring in the south hemisphere. There is evidence of poor-ozone air masses detachment from polar vortex and reaching mid-latitude regions, such as South of Brazil. Those air masses cause impact on the regions which they act due to low ozone content, allowing more radiation to reach the surface. UV index data from a Brewer Spectrophotometer (MKIII #167), located in south of Brazil, in the Southern Space Observatory (29.42° S, 53.87° W) was analysed with data collected between 2005 and 2017. Ground data was compared to satellite-derived from OMI/Aura, resulting in a correlation coefficient of 0.95 %. The climatology of Brewer data was done, analysing seasonal and interannual variability. Wavelet analysis showed the influence of ENSO, QBO and solar cycle on the variability of UV index. The results show a typical seasonal behaviour of UV Index, reaching extreme during summer season. Events of secondary effects of Antarctic ozone hole, identified between 2005 and 2016 (Bittencourt, 2018), were selected and the behavior of UV index and UV-B non-weighted during those events were studied. All ten events studied showed a significant increase in UV radiation at the days of events, the majority resulted in an increase of 4 % of UV index for each 1 % ozone total column decrease. One specific event was described in detail due to the major ozone depletion. Occurred in October 2016, ozone depletion was of almost 20 % while UV index increased 88 % in relation to the climatological mean, raising the concern with public health regarding excess exposure to UV radiation. [ABSTRACT FROM AUTHOR]

The Indian Ocean dipole (IOD) is one of the leading modes of interannual climate variability in the tropical Indian Ocean (IO). The paleoclimate provides real climate scenarios to examine IOD behaviors and the linkage to basic states. Based on 18 models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5/6), the IOD change from the preindustrial period to the mid-Holocene is investigated. The multimodel mean reveals that the IOD variability weakens by 14%, as measured by the standard deviation of the dipole mode index, which is defined using the zonal sea surface temperature (SST) difference. Such attenuation is dominated by the spatially consistent suppression in the western-pole SST variability, while the eastern pole contributes little due to the opposite-signed changes in its northwestern and southeastern portions. The primary reason for the aforementioned changes comes from the altered climatic background, which displays a positive IOD-like pattern during IOD growing seasons, with intensified westward currents along the equator and northwestward currents in the southeastern equatorial IO. Such changes in the mean-state currents modulate the strength of the IOD-related anomalous advection and subsequently cause alterations in the IOD variability. Further analyses show that the IOD attenuation in the mid-Holocene is unlikely to be caused by the concurrently subdued El Niño–Southern Oscillation in the tropical Pacific, partially because of the diminished connections between the two oscillations themselves. The above simulated changes in both the IO mean climatology and IOD variability agree well with the available paleo records in literature. Significance Statement: Understanding variations in the Indian Ocean dipole (IOD) and its relationship to the altered background mean state can advance our knowledge of tropical climate dynamics. The paleoclimate provides the opportunity to address this issue under real climate scenarios in the past. Based on multiple models from CMIP5/6, we investigate IOD changes during the mid-Holocene compared to the preindustrial period. The result shows a weakening of the IOD, and the main mechanism lies in the altered anomalous advection modulated by changes in the mean-state currents. The simulated changes in both the mean state and IOD variability are consistent with available paleo data. The present study extends the research scale of IOD dynamics beyond instrumental periods and provides scientific bases for deciphering geological records. [ABSTRACT FROM AUTHOR]

The global impacts of El Niño on precipitation have been long‐recognized, but more understanding of the mechanisms behind this influence is needed. For instance, previous studies have largely overlooked the potential impacts of El Niño on terrestrial moisture recycling (TMR). We perform a 40‐year forward tracking simulation to derive a global climatology of recycled precipitation and use a composite analysis to investigate how El Niño affects TMR. We identify seven regions where the El Niño impact on TMR is most significant and find that, in these regions, changes in precipitation and TMR are directly related: they increase or decrease together. In addition, we find a marked latitudinal contrast between the Southern Hemisphere, where TMR increases during El Niño, and the Northern Hemisphere and the tropics, where it decreases. Our results indicate that the weakening and strengthening of TMR can be behind precipitation changes caused by El Niño globally. Plain Language Summary: El Niño is recognized as a climate variability phenomenon with significant impacts on precipitation worldwide. However, the mechanisms behind these impacts are not fully understood. Here we use model simulations to argue that one of those mechanisms is the effect of El Niño on terrestrial moisture recycling (TMR), that is, the fraction of precipitation fed by atmospheric moisture originating not in the ocean but on the continents. We show that El Niño significantly affects TMR globally, especially in seven regions of South America, Africa, North America, Europe, and Asia. In these regions, precipitation and TMR increase or decrease together. We find a contrast between the South and North of the planet: during El Niño, TMR increases in the Southern Hemisphere while decreasing in the Northern Hemisphere and the tropics. Overall, our results indicate that TMR weakening or strengthening are previously overlooked mechanisms behind precipitation changes caused by El Niño globally. Key Points: El Niño exerts significant effects on terrestrial moisture recycling worldwideEl Niño's impacts on terrestrial moisture recycling are most significant in seven regions worldwidePrecipitation and terrestrial moisture recycling increase or decrease together due to El Niño [ABSTRACT FROM AUTHOR]

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly through the teleconnection to El Niño/Southern Oscillation (ENSO), which is expected to be altered by climate change. Natural variability in this teleconnection has not been robustly quantified, complicating the detection of anthropogenic climate change. Here, we use a linear inverse model (LIM) to quantify natural variability in the ENSO‐SWUS teleconnection. The LIM yields realistic teleconnection patterns with century‐scale variability comparable to simulations from the Last Millennium Ensemble project and the Climate Model Intercomparison Project Phases 5 and 6. The variability quantified by the LIM illuminates two aspects of our understanding of ENSO and its impacts: the inherent statistics of the observable system can produce century‐long periods with a wide range of correlations to SWUS hydroclimate, including nonsignificant correlations, and thus that detecting changes in ENSO‐related hydroclimate variability is challenging in a changing climate. Plain Language Summary: The El Niño/Southern Oscillation (ENSO) affects weather and climate across the globe through teleconnections. For example, when sea surface temperatures in the tropical Pacific Ocean are warmer than normal (e.g., during an El Niño), higher than normal precipitation is typically observed in the southwest United States (SWUS). However, because we have temporally limited observations of climate, we do not know how often El Niños actually bring more rain to the SWUS. Assessing this natural variability is difficult with commonly used approaches from the climate sciences. Here, we use a statistical model to emulate the characteristics of ENSO teleconnections from observations. Doing so demonstrates that there is considerable natural variability in the ENSO teleconnection to the SWUS. This suggests that even though ENSO and its impact on weather and climate are expected to change due to climate change, detecting such changes will be difficult. Key Points: A linear inverse model is used to quantify the natural variability in the El Niño/Southern Oscillation‐southwest United States (ENSO‐SWUS) teleconnection, and it suggests considerable intrinsic variabilityThis natural variability demonstrates that detecting anthropogenic changes in the ENSO‐SWUS hydroclimate teleconnection will be difficultCMIP6 shows an improvement in modeling the ENSO‐SWUS teleconnection, but uncertainty remains in the projected future climate [ABSTRACT FROM AUTHOR]

Precipitation often happens along organized filaments or bands of moisture such as convergence zones. Recent regional studies have shown that these moisture filaments arise from synoptic-scale mixing features known as attracting Lagrangian coherent structures (LCSs). In this study, we present a climatology of synoptic-scale mixing and investigate its covariability with precipitation on temporal scales ranging from weekly to interannual. We characterize mixing with the finite-time Lyapunov exponent (FTLE), a measure of parcel deformation, in ERA5 data between 1980 and 2009. Attracting LCSs are identified as ridges of the FTLE. At the interannual time scale, we compare El Niño and La Niña events and find that composites of precipitation and mixing anomalies share similar spatial patterns. We also compare summer and winter seasons and find that composites of seasonal-mean precipitation and mixing anomalies present similar characteristics, with precipitation being particularly intense (weak) where mixing is strong (weak). In particular, these patterns closely match the typical signatures of the intertropical convergence zone (ITCZ) and monsoon systems and the migrations of extratropical cyclone tracks. At the subseasonal scale, we employ daily composites to investigate the influence of the Madden–Julian oscillation and the North Atlantic Oscillation on the mixing regimes of the Atlantic and east Pacific; our results indicate that these oscillations control the synoptic-scale horizontal mixing and the occurrence of LCSs as to suppress or enhance precipitating systems like the ITCZ and the South Atlantic convergence zone. The results presented in this first climatology of synoptic-scale mixing and LCSs indicate that these are powerful diagnostics to identify circulation mechanisms underlying precipitation variability. [ABSTRACT FROM AUTHOR]

Climate patterns are natural processes that drive climate variability in the short, medium, and long term. Characterizing the patterns behind climate variability is essential to understand the functioning of the regional atmospheric system. Since investigations typically reveal only the link and extent of the influence of climate patterns in specific regions, the magnitude of that influence in meteorological records usually remains unclear. The central Peruvian Andes are affected by most of the common climate patterns of tropical areas, such as Intertropical Convergence Zone (ITCZ), Sea Surface Temperature (SST), solar irradiance, Madden Julian Oscillation (MJO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO). They are also affected by regional processes that are exclusive from South America, such as the South American Low-Level Jet (SALLJ), South American Monsoon System (SAMS), Bolivian High (BH), and Humboldt Current. The aim of this research is to study the climate variability of precipitation, maximum and minimum temperature records over Cordillera Blanca (Peru), and its relationship with the intensity and periodicity of the common climate patterns that affect this region. To achieve this aim, a spectral analysis based on Lomb's Periodogram was performed over meteorological records (1986–2019) and over different climate pattern indexes. Results show a coincidence in periodicity between MJO and SALLJ, with monthly cycles for precipitation and temperature (27-day, 56-day, and 90-day cycles). Moreover, the most intense periodicities, such as annual (365 days) and biannual (182 and 122 days) cycles in meteorological variables, possibly would be led by ITCZ and ENSO together, as well as a combination of the Humboldt Current and SALLJ. Additionally, interannual periodicities (3-year, 4.5-year, 5.6–7-year and 11-year cycles) would have coincidence with the ENSO–solar combination, while the longest cycles (16 years) could match PDO variability. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems are fully coupled with the climate. The planet has been greening owing to the increased vegetation growth in response to the changing atmosphere, which in turn has feedback on the climate. Greening has slowed down the rise in global land-surface air temperature mainly through a coincident increase of evapotranspiration and precipitation in wet regions. In dry regions, greening intensifies the decrease in soil moisture induced by greening-enhanced transpiration. Uncertain, however, is how the climate effects of greening in semi-arid lands might differ for variable wet and dry conditions. Here, we focus on the biosphere–atmosphere interactions in Australia by modeling the perturbation of vegetation changes under various states of sea surface temperature (SST), including the climatology mean, El Niño, and La Niña conditions. For the dry conditions of El Niño, greening exacerbates water stress and largely depletes the soil moisture, while for the wet conditions of La Niña, greening-enhanced evapotranspiration and precipitation resupply the soil moisture. For the normal conditions using the climatology mean SST, a small decrease in soil moisture occurs but with large spatial contrast because of heterogeneous changes of evapotranspiration and precipitation induced by greening. We emphasize that the alternating dry and wet conditions modulated by the large-scale climate variability are vital to understanding the response of climate to greening. Furthermore, vegetation-based warming mitigation policies need to be cautious when inferring distinct climate effects associated with greening. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs), referring to long and narrow filamentary bands of intense water vapor transport in the atmosphere, can cause extreme precipitation, floods, and drought events. Their variability has been linked to various climate modes, such as El Niño/Southern Oscillation, Pacific Decadal Oscillation, and Pacific‐North America pattern. Understanding and improving simulation of this linkage can provide the potential to predict ARs at subseasonal‐to‐decadal timescales. Up to now, the extent to which climate model simulations of ARs are dependent on model resolutions has not been fully assessed. Here, we compare and evaluate ARs in a pair of high‐resolution (HR) and a low‐resolution (LR) Community Earth System Model (CESM) simulations against the observations. The results show that within this CESM framework, climatological AR strength and associated precipitation are severely underestimated by LR compared to the observations, and their relationships with major modes of climate variability are also poorly reproduced. These deficiencies in LR are alleviated to a significant extent in HR. Using a linear regression analysis, we show that HR is able to capture with high fidelity the observed relationships between ARs and major climate modes in the Northern Hemisphere at seasonal‐to‐decadal time scales. These results suggest that the use of HR CESM may potentially lead to an improved forecast skill of ARs at season‐to‐decadal time scales. Plain Language Summary: Atmospheric rivers (ARs) can trigger extreme rainfall and snowfall events, causing high risk of flooding. Meanwhile, they are sometimes responsible for the occurrence and break of drought events. So, it is of great importance for weather and climate forecast models to accurately represent ARs. Studies have shown that AR variability is linked to various climate modes, such as El Niño/Southern Oscillation, Pacific Decadal Oscillation, Pacific‐North America pattern, providing the potential for predicting ARs at subseasonal‐to‐decadal timescales. In this study, we examine the impact of climate model resolution on AR simulations and their relationship with major climate modes by comparing a pair of high‐resolution and a low‐resolution (LR) Community Earth System Model (CESM) simulations against the observations. The results reveal major deficiencies in LR that include underestimated climatological AR strength and associated precipitation, and inaccurate representations of ARs relationships with climate modes. Significant improvements are observed by increasing CESM horizontal resolution, suggesting a path for more accurate prediction of ARs. Key Points: Simulated atmospheric rivers (ARs) are dependent on horizontal resolutions of coupled Community Earth System Model (CESM)High‐resolution (HR) CESM simulates more realistic ARs' strength and associated rainfall than low‐resolution (LR)ARs' response to large‐scale climate modes is better simulated in HR CESM than in LR CESM [ABSTRACT FROM AUTHOR]

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Atmospheric rivers (ARs) that reach the complex terrain of High Mountain Asia (HMA) cause significant hydrological impacts for millions of people. While ARs are often associated with precipitation extremes and can cause floods and debris flows affecting populated communities, little is known about ARs that reach as far inland as HMA. This paper characterizes AR types and investigates dynamical mechanisms associated with the development of ARs that typically affect HMA. Combined empirical orthogonal function (cEOF) analysis using integrated water vapor transport (IVT) is applied to days where an AR reaches HMA. K-means cluster analysis applied to the first two principal components uncovered three subtypes of AR events with distinct synoptic characteristics during winter and spring months. The first subtype increases precipitation and IVT in Western HMA and is associated with a zonally oriented wave train propagating within the westerly jet waveguide. The second subtype is associated with enhanced southwesterly IVT, anomalous upper-level cyclonic circulation centered on 45 ∘ E, and precipitation in Northwestern HMA. The third subtype shows anomalous precipitation in Eastern HMA and southwesterly IVT across the Bay of Bengal. Interannual variations in the frequency of HMA ARs and relationships with various teleconnection patterns show that western HMA AR subtypes are sensitive to well-known remote large-scale climate factors, such as the El Niño Southern Oscillation, Arctic Oscillation, and the Siberian High. These results provide synoptic characterization of the three types of ARs that reach HMA and reveal the previously unexplored significance of their contribution to winter and spring precipitation. [ABSTRACT FROM AUTHOR]

To study the forced variability of atmospheric circulation regimes, the use of model ensembles is often necessary for identifying statistically significant signals as the observed data constitute a small sample and are thus strongly affected by the noise associated with sampling uncertainty. However, the regime representation is itself affected by noise within the atmosphere, which can make it difficult to detect robust signals. To this end we employ a regularised k‐means clustering algorithm to better identify the signal in a model ensemble. The approach allows for the identification of six regimes for the wintertime Euro‐Atlantic sector and leads to more pronounced regime dynamics, compared to results without regularisation, both overall and on sub‐seasonal and interannual time‐scales. We find that sub‐seasonal variability in the regime occurrence rates is mainly explained by changes in the seasonal cycle of the mean climatology. On interannual time‐scales relations between the occurrence rates of the regimes and the El Niño Southern Oscillation (ENSO) are identified. The use of six regimes captures a more detailed response of the circulation to ENSO compared to the common use of four regimes. Predictable signals in occurrence rate on interannual time‐scales are found for the two zonal flow regimes, namely a regime consisting of a negative geopotential height anomaly over the Norwegian Sea and Scandinavia, and the positive phase of the NAO. The signal strength for these regimes is comparable between observations and model, in contrast to that of the NAO‐index where the signal strength in the observations is underestimated by a factor of 2 in the model. Our regime analysis suggests that this signal‐to‐noise problem for the NAO‐index is primarily related to those atmospheric flow patterns associated with the negative NAO‐index as we find poor predictability for the corresponding NAO− regime. [ABSTRACT FROM AUTHOR]

During strong El Niño events, below-average rainfall is expected in large parts of southern Africa. The 1992 El Niño season was associated with one of the worst drought episodes in large parts of South Africa. Using reanalysis data set from NCEP-NCAR, this study examined circulation types (CTs) in Africa south of the equator that are statistically related to the El Niño signal in the southwest Indian Ocean and the implication of this relationship during the 1992 drought episode in South Africa. A statistically significant correlation was found between the above-average Nino 3.4 index and a CT that features widespread cyclonic activity in the tropical southwest Indian Ocean, coupled with a weaker state of the south Indian Ocean high-pressure. During the analysis period, it was found that the El Niño signal enhanced the amplitude of the aforementioned CT. The impacts of the El Niño signal on CTs in southern Africa, which could have contributed to the 1992 severe drought episode in South Africa, were reflected in (i) robust decrease in the frequency of occurrence of the austral summer climatology pattern of atmospheric circulation that favors southeasterly moisture fluxes, advected by the South Indian Ocean high-pressure; (ii) modulation of easterly moisture fluxes, advected by the South Atlantic Ocean high-pressure, ridging south of South Africa; (iii) and enhancement of the amplitude of CTs that both enhances subsidence over South Africa, and associated with the dominance of westerlies across the Agulhas current. Under the ssp585 scenario, the analyzed climate models suggested that the impact of radiative heating on the CT significantly related to El Niño might result in an anomalous increase in surface pressure at the eastern parts of South Africa. [ABSTRACT FROM AUTHOR]

Objective: In 2011-2012, severe El Niño Southern Oscillation (ENSO) conditions (La Niña) led to massive flooding and temporarily displacement in the Peruvian Amazon. Our aims were to examine the impact of this ENSO exposure on child diets, in particular: (1) frequency of food consumption patterns, (2) the amount of food consumed (g/d), (3) dietary diversity (DD), (4) consumption of donated foods, among children aged 9-36 months living in the outskirts of City of Iquitos in the Amazonian Peru.Design: This was a longitudinal study that used quantitative 24-h recall dietary data collection from children aged 9-36 months from 2010 to 2014 as part of the MAL-ED birth cohort study.Setting: Iquitos, Loreto, Peru.Participants: Two hundred and fifty-two mother-child dyads.Results: The frequency of grains, rice, dairy and sugar in meals reduced by 5-7 %, while the frequency of plantain in meals increased by 24 % after adjusting for covariates. ENSO exposure reduced girl's intake of plantains and sugar. Despite seasonal fluctuations in the availability of fruits, vegetables and fish, DD remained constant across seasons and as children aged. However, DD was significantly reduced under moderate La Niña conditions by 0·32 (P < 0·05) food groups. Adaptive social strategies such as consumption of donated foods were significantly higher among households with girls.Conclusions: This is the first empirical study to show differential effect of the ENSO on the dietary patterns of children, highlighting differences by gender. Public health nutrition programmes should be climate- and gender-sensitive in their efforts to safeguard the diets of vulnerable populations. [ABSTRACT FROM AUTHOR]

The predominance of swells or wind-seas at a location can be inferred from the spectral peak wave period (Tp). The present study examines the climatology of Tp and its variability in the Bay of Bengal (BoB) during the last 40 years based on reanalysis data. The Andaman and Nicobar Islands and Sri Lanka significantly alter the spatial distribution of Tp in the BoB. Spatial variation in Tp was less than 10% for 1° latitude, except for regions blocked by the landmass. Inter-annual changes in the annual average Tp were 8–18% at different locations. In most areas, climatological monthly Tp was largest in March, April, and October, when the winds were weak. The high Tp tongue extends to the BoB through the eastern side of the bay. The study also examines the relationship between three major natural climate variabilities; El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Southern Annular Mode (SAM) with Tp anomalies in the BoB. We observed that negative ENSO and SAM events enhance the long-period waves in the BoB, while a negative IOD event generates more short-period waves in the BoB. [ABSTRACT FROM AUTHOR]

An extensive search has been carried out to find all major flood and very heavy rainfall events in Victoria since 1876 when Southern Oscillation (SOI) data became available. The synoptic weather patterns were analysed and of the 319 events studied, 121 events were found to be East Coast Lows (ECLs) and 82 were other types of low-pressure systems. Tropical influences also played a large role with 105 events being associated with tropical air advecting down to Victoria into weather systems. Examples are presented of all the major synoptic patterns identified. The SOI was found to be an important climate driver with positive SOIs being associated with many events over the 144 years studied. The 1976 Climate Shift and its influence on significant Victorian rainfall events is studied and negative SOI monthly values were shown to dominate following the Shift. However, one of the most active periods in 144 years of Victorian heavy rain occurred after the shift with a sustained period of positive SOI events from 2007 to 2014. Therefore, it is critical for forecasting future Victorian heavy rainfall is to understand if sequences of these positive SOI events continue like those preceding the Shift. Possible relationships between the Shift and Global Temperature rises are also explored. Upper wind data available from some of the heaviest rainfall events showed the presence of anticyclonic turning of the winds between 850hPa and 500hPa levels which has been found to be linked with extreme rainfall around the Globe. [ABSTRACT FROM AUTHOR]

Surface temperature is a vital metric of Earth's climate state but is incompletely observed in both space and time: over half of monthly values are missing from the widely used HadCRUT4.6 global surface temperature dataset. Here we apply the graphical expectation–maximization algorithm (GraphEM), a recently developed imputation method, to construct a spatially complete estimate of HadCRUT4.6 temperatures. GraphEM leverages Gaussian Markov random fields (also known as Gaussian graphical models) to better estimate covariance relationships within a climate field, detecting anisotropic features such as land–ocean contrasts, orography, ocean currents, and wave-propagation pathways. This detection leads to improved estimates of missing values compared to methods (such as kriging) that assume isotropic covariance relationships, as we show with real and synthetic data. This interpolated analysis of HadCRUT4.6 data is available as a 100-member ensemble, propagating information about sampling variability available from the original HadCRUT4.6 dataset. A comparison of Niño-3.4 and global mean monthly temperature series with published datasets reveals similarities and differences due in part to the spatial interpolation method. Notably, the GraphEM-completed HadCRUT4.6 global temperature displays a stronger early twenty-first-century warming trend than its uninterpolated counterpart, consistent with recent analyses using other datasets. Known events like the 1877/78 El Niño are recovered with greater fidelity than with kriging, and result in different assessments of changes in ENSO variability through time. Gaussian Markov random fields provide a more geophysically motivated way to impute missing values in climate fields, and the associated graph provides a powerful tool to analyze the structure of teleconnection patterns. We close with a discussion of wider applications of Markov random fields in climate science. [ABSTRACT FROM AUTHOR]

The interannual variability, trends, and the mean climatology of East African long rains are difficult for models to simulate. This is in part because long rains do not respond in a simple way to large-scale modes of variability such as ENSO and because of interactions with complex topography. Here we focus on the Kenyan regional climate in the ERA-Interim dataset during the long rains to create a set of atmospheric diagnostics that can be applied to the evaluation of climate models. Subseasonal observed rainfall and reanalysis reveal that very wet seasons and very dry seasons develop differently at the beginning of the season. Subseasonal aggregation periods (days 60–80, 80–100, 90–120, 120–150) highlight local (e.g., midtropospheric ascent, moisture flux convergence in the lower to midtroposphere, and midtropospheric moisture) and large-scale (e.g., midtropospheric zonal winds over central Africa, upper-tropospheric velocity potential) diagnostics that are useful to evaluate model atmospheric circulation affecting Kenyan rainfall in mean and wet or dry extremes. [ABSTRACT FROM AUTHOR]

The most destructive wildfires recently in Northern California have been linked to the occurrences of Diablo Winds (DWs). This study investigates the climatology of DWs during September–December 1979–2018, and their relationships with various climate modes using observations and two high-resolution reanalysis datasets. Our finding shows that DWs do not have a long-term trend in terms of the annual total number, total duration, and associated maximum wind speeds of DWs over the past 4 decades. However, their associated minimum relative humidity (RH) has decreased significantly, especially in October, which suggests that the dryness during DWs has become more severe with time, possibly leading to an increased chance of fires, and their destructive potential. We also find that the annual total number and duration of DWs have exhibited an quasi-periodic variation, with intervals ranging from 2 to 4 years. The periodic variability of DWs might be attributed to the teleconnections between DWs and climate oscillations, specifically the El Niño–Southern Oscillation (ENSO) and the quasi-biennial oscillation (QBO), through their modulation of pressure systems near California and the location of the Pacific jet stream. It is suggested that when La Niña and the QBO westerly phases co-occur in the spring, DWs in the following fall and winter tend to occur more frequently, and are associated with more intense high winds and dryness as compared to other springtime QBO and ENSO phases. This relationship may be used to predict the seasonal outlook of DWs. [ABSTRACT FROM AUTHOR]

In this study, future change of El Niño-related East Asian (EA) rainfall and the diversity of this relationship are investigated on the basis of the historical and representative concentration pathway 8.5 (RCP 8.5) simulations taken from the Coupled Model Intercomparison Project phase 5 (CMIP5). By evaluating the East Asian Summer Monsoon (EASM) climatology and interannual variations in simulations contributing to CMIP5, nine models are verified to be capable of reproducing El Niño diversity and EASM simultaneously. Six of these models are selected for projecting the multi-model ensemble (MME) mean of two types of El Niño-related EA/western North Pacific (WNP) rainfall patterns and low-level atmospheric circulations under global warming, considering the realism in their simulated El Niño and EASM phenomena. It was found that, under a warmer background climate, the general patterns of anomalous circulation and rainfall will persist, but with amplification of the rainfall intensity during mature boreal winter and decaying summer for both Eastern-Pacific (EP) and Central-Pacific (CP) El Niño. Amplification of CP type-related rainfall seems to be stronger than that for EP type El Niño. Further analyses show that a moister atmosphere tends to always strengthen the rainfall variations for both El Niño flavors, regardless of how the El Niño-related circulation amplitude is modulated in various seasons. However, in boreal summer during the El Niño decaying phase, strengthened anomalous circulation also enhances the rainfall variability, with an effect comparable to the background moisture increase. Some of these atmospheric circulation changes might be associated with modified sea surface temperature anomalies (SSTA) of El Niño and its diversity, under global warming. Our results indicate the importance of better preparedness and higher resilience in the EA region to enhanced El Niño-induced hydrological variations under a warming climate. [ABSTRACT FROM AUTHOR]

The influence of a new spectral cumulus parametrization (the spectral scheme) on simulating global tropical cyclone (TC) activity in an Atmospheric General Circulation Model (AGCM) is investigated. Experiments are performed using AFES (AGCM for the Earth Simulator) and two different convection schemes – the original convection scheme of the AGCM (the Emanuel scheme) and the spectral scheme. The result shows that the both schemes can capture qualitative features of global TC activity in terms of climatology, variability, and intensity. However, the spectral scheme simulates TC genesis and track density better than the original convection scheme by improving the cold bias in the upper troposphere. The spectral scheme also provides better results for TC response to interannual variability (i.e., El Niño Southern Oscillation, ENSO) by suppressing excessive convection response to ENSO. The spectral scheme is capable of simulating the variability of TC genesis related to the Madden–Julian Oscillation (MJO) much better than the original convection scheme. Consequently, the spectral scheme can outperform the original convection scheme in simulating global TC activity from various perspectives, and thus the scheme is expected to be useful for TC prediction and future projections. [ABSTRACT FROM AUTHOR]

The 2015–2016 El Niño had large impacts globally. The effects were not as great as anticipated in Kenya, however, leading some commentators to call it a 'non-event'. Our study uses a novel combination of participatory Climate Vulnerability and Capacity Analysis tools, and new and existing social and biophysical data, to analyse vulnerability to, and the multidimensional impacts of, the 2015–2016 El Niño episode in southern coastal Kenya. Using a social-ecological systems lens and a unique dataset, our study reveals impacts overlooked by conventional analysis. We show how El Niño stressors interact with and amplify existing vulnerabilities to differentially impact local ecosystems and people. The policy significance of this finding is that the development of specific national capacities to deal with El Niño events is insufficient; it will be necessary to also address local vulnerabilities to everyday and recurrent stressors and shocks to build resilience to the effects of El Niño and other extremes in climate and weather. [ABSTRACT FROM AUTHOR]

The atmospheric river (AR) is a unique mover of moisture from the low latitudes to mid- and high latitudes and a potential cause for regional flooding. This study explores the ARs' influence on wintertime precipitation (including extreme precipitation) over the pan-North Pacific during 1996–2018 from the climatological perspective and during the ENSO condition, via distinguishing precipitation and moisture transport between the AR-group and the non-AR-group. Climatologically, the AR-group contributes 30%–45% of total winter precipitation, and up to 70% of total extreme precipitation over the eastern Pacific and along the North American west coast between 25° and 45°N. The above area is the core region of the ARs' influence on precipitation. The AR-group's precipitation in the core region is mostly determined by AR-produced in situ moisture convergence, while the non-AR-group's precipitation is attributed to evaporation from Earth's surface. The AR frequency is increased (decreased) in the core region during El Niño (La Niña) winters. As a result, the AR-group contributes more than half of the positive (negative) anomalies in total precipitation in the core region, due to AR-related moisture convergence anomalies. Besides, during El Niño winters, the AR-group also contributes almost half of negative anomalies in total precipitation over the middle basin between 40° and 55°N. An anomalous moisture sink (source) always acts to increase (decrease) in situ precipitation for both the AR-group and the non-AR-group. It is also shown that the moisture transport and its divergence anomalies are primarily decided by changes in wind fields and second by moisture. Furthermore, changes in moisture can cause asymmetric features of anomalies in moisture transport and its divergence between El Niño and La Niña but with limited effects. [ABSTRACT FROM AUTHOR]

The climatology of atmospheric rivers (ARs) and their roles on precipitation extremes have been extensively researched over western North America and Europe, yet ARs in Asia, especially for those affecting the densely populated countries including Bangladesh, China, India, Thailand and Vietnam are not adequately understood. Here, the climatological characteristics of landfalling ARs, including their frequency and intensity, in the Asian monsoon region for the period 1979–2017 are investigated using the ECMWF ERA‐Interim reanalysis dataset. The inter‐annual variability of landfalling ARs associated with the combination of the El Niño–Southern Oscillation (ENSO) and the Quasi‐Biennial Oscillation (QBO) is presented. The results suggest frequent AR activities over southern India, Indochina Peninsula, southern China, Korea and Japan from May to September. ARs are found to contribute up to 44% of the total summer precipitation over the coastal regions of East Asia and up to 36% in South Asia. Also, ARs are associated with up to 68% of the summer extreme precipitation amount in East Asia and 52–56% in South Asia. The connection between ARs and extreme precipitation is partly explained by the increased precipitation efficiency when ARs occur, indicating a stronger ability of the atmospheric dynamical factors to deplete moisture and generate strong precipitation. The analyses of the combined ENSO–QBO effects on ARs show that ARs in the subtropics tend to become less frequent in the years preceded by an El Niño event due to the weakening of the low‐level monsoonal flows associated with the weakened land–sea thermal contrast and upper‐level tropical easterly jet, and such modulations tend to become more significant under the easterly phase of QBO. [ABSTRACT FROM AUTHOR]

Downslope winds are mesoscale mountain meteorological phenomena that contribute to localized temperature extremes and contribute to numerous societal and environmental impacts. Whereas previous studies have examined local downslope winds, no known efforts have attempted to identify and characterize meso‐ to synoptic‐scale downslope winds globally using a common approach. We use a conceptual model for downslope winds that employs cross‐barrier wind speed, near‐mountain top static stability, and downward vertical velocity using thresholds guided by a chronology of local downslope winds and meta‐analysis of downslope wind case studies. This approach was applied to ERA‐5 reanalysis during 1979–2018 to develop a global atlas of downslope winds. Downslope winds adhered to distinct geographic and seasonal patterns, with peak occurrence in north–south oriented midlatitude mountains in the winter hemisphere associated with strong cross‐mountain winds and stability. However, we identify numerous locations from the tropics to the high‐latitudes where downslope winds occur at least 60 days a year as a byproduct of the general circulation and local‐scale circulation interacting with topography. The four‐decade‐long data set is also used to examine statistical relationships between the occurrence of downslope winds and El Niño‐Southern Oscillation as well as long‐term trends in downslope wind occurrence. [ABSTRACT FROM AUTHOR]

Delays in waterfowl autumn migration have been widely reported by hunters and ornithologists throughout North America. The implications of such delays are vast, with potential effects on the efficacy of population management, reduced social and economic opportunities, and reduced resource availability by overuse and over-grazing in key staging areas. In this study, we tested for changes in autumn migration timing for six abundant species of dabbling ducks in southern Ontario, Canada. We applied generalized linear mixed models to test for effects of year and climate indices El Niño Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) on the Julian date of peak abundance as observed during aerial surveys conducted throughout the lower Great Lakes. Our analyses revealed delays of 11–18 days between 1968 and 2011 for four of six focal species: mallard, American black duck, American wigeon and gadwall. La Niña and El Niño events had no effect on migration timing for American black duck, American green-winged teal or American wigeon, while an increase in the annual NAO index resulted in a delayed migration for American wigeon. There was an NAO:ENSO interaction for mallard and gadwall migration; an increase in NAO advanced peak migration dates during La Niña events. However, an increase in NAO delayed migration for gadwall during the neutral phase of the ENSO and delayed migration for both species during El Niño events. Blue-winged teal and American green-winged teal showed no change in migration timing. Given that climate forecasts indicate continued positive-value phases, the autumn migrations for mallard, American black duck, gadwall and American wigeon may become increasingly delayed. Wildlife managers should use all available data, including from standardized aerial surveys, citizen science and climate models to inform and direct adaptive population management, hunting regulations, wildlife emergency response and habitat conservation. [ABSTRACT FROM AUTHOR]

The short‐term concurrent hot and dry extreme (SCHDE) event has recently stimulated intensive scientific interests due to its rapid onset, severe intensity, and devastating impacts on agriculture and natural ecosystems. The SCHDE is mainly caused by an increase in actual evapotranspiration (ET) accompanied with a decrease in soil moisture (SM) due to anomalously high surface temperature (Tair). Based on the daily datasets of precipitation (P), Tair, ET, and SM from four global modelling products as well as large‐scale climate indices, we analyse globally the spatio‐temporal evolution of SCHDE events at both grid and basin scales. Results indicate that SCHDE events occur mostly in Northern Hemisphere regions with relatively low P. During 1980–2010, due to significant global warming (0.30°C·decade−1) the global mean occurrence frequency of SCHDE has an increasing trend (0.34%·decade−1) along with a weakly decreasing trend of SM (~−0.08%·decade−1) and a significantly increasing trend of ET (~8.34 mm·decade−1). Overall, North America and Asia have a higher frequency of SCHDE occurrence than other continents. The variability of Tair is mainly responsible for the variability of SCHDE occurrence over the equator regions, while the variability of ET (SM) plays an important role in SCHDE occurrence variability in the cropland‐dominant (mid‐ and high‐latitude) regions. Globally, the relative contribution of Tair to SCHDE variability is the largest, followed by ET and SM. Lastly, we found that the cold phases of the Pacific Decadal Oscillation during the La Niña events (i.e., negative Multivariate ENSO Index) are conducive to the intensification of SCHDE events in southern South America and Australia. [ABSTRACT FROM AUTHOR]

The large-scale atmospheric circulation of the North Pacific associated with two types of El Niño--the eastern Pacific (EP) and central Pacific (CP)--is studied in relation to Hawaiian winter (December-February) rainfall and temperature. The eastern and central equatorial Pacific undergo active convective heating during EP El Niño winters. The local Hadley circulation is enhanced and an upper-level westerly jet stream of the North Pacific is elongated eastward. Due to the impact of both phenomena, stronger anomalous descending motion, moisture flux divergence anomalies near Hawaii, and reduction of easterly trade winds, which are characteristic of EP winters, are unfavorable for winter rainfall in Hawaii. As a result of this robust signal, dry conditions prevail in Hawaii and the standard deviation of rainfall during EP winters is smaller than the climatology. For CP winters, the maximum equatorial ocean warming is weaker and shifted westward to near the date line. The subtropical jet stream retreats westward relative to EP winters and the anomalously sinking motion near Hawaii is variable and generally weaker. Although the anomalous moisture flux divergence still exists over the subtropical North Pacific, its magnitude is weaker relative to EP winters. Without strong external forcing, rainfall in the Hawaiian Islands during CP winters is close to the long-term mean. The spread of rainfall from one CP event to another is also larger. The near-surface minimum temperature from three stations in Hawaii reveals cooling during EP winters and slight warming during CP winters. [ABSTRACT FROM AUTHOR]

The Indian coastal regions encountered frequently by extreme weather events such as heavy precipitation events (HPE). In the present study, an assessment has been made to understand the climatological relationship between atmospheric rivers (ARs) and HPEs for Indian coastal regions. For this purpose, India Meteorological Department gridded rainfall dataset, and four different reanalyses datasets for the occurrence of ARs were analysed for different seasons during 1980–2015. The influence of ARs towards the cause of HPEs was stronger over the West coast (WC) compared to the East coast of India (ECI). Over the WC the association between HPE with ARs is ~40% (for rainfall events >124.4·mm·day−1) than East coast (EC) by ~28%. The 64.4–124.4·mm·day−1 events are higher over the WC by ~18% compared to ~5% over the EC. While for the events (<64.4·mm·day−1), the percentage of occurrence is moreover the WC (~7%) compared to the EC (~2%). The study reveals that ARs is in good correlation with the occurrence of HPE. Using Poisson regression model, investigated the relationship between the AR totals in the summer and Northeast monsoon and the large‐scale climate indices. A sufficiently significant negative (positive) dependency observed between ARs and the Southern Oscillation Index (SOI) (Indian Ocean Dipole [IOD] and Niño 3.4 indices) with a larger rate of AR occurrence associated with lower SOI values and larger frequency of AR occurrence associated with larger IOD and Niño 3.4 values for both the coasts of India. [ABSTRACT FROM AUTHOR]

Climate warming generally is expected to increase drought, but arguments about China's past drought trends persist. PDSIARTS, a revised self‐calibrating Palmer Drought Severity Index, was computed for China over 1982–2016 using satellite leaf‐area indices combined with monthly climate data interpolated from 2000 high‐density stations. Drought climatology was analysed against climate factors. The results show that temperature has increased at a rate of 0.38°C per decade (p <.001) in China in the past 35 years (1982–2016). However, over the same interval, China and the northern China region became wetter. PDSIARTS increased at a rate of 0.03 yr−1 (p <.001) across China during 1982–2016. The analogous increase of PDSIARTS in northern China was 0.05 yr−1 (p <.001). In China, the 5‐year interval from 2012 to 2016 was the wettest 5 years in the 35‐year interval. This arises from the coupled effects of decreased potential evaporation (Ep) and increased precipitation (Pr). The implication is that temperature increase does not necessarily indicate increased drought. A potential complication is that the 2015/16 El Niño event induced the highest Pr in southern China for 1982–2016, and northern China still had plentiful Pr in 2015/16, which further contributed to the wettest 2‐years (2015/16) during the past 35 years in the whole of China. This study highlights the joint impacts of Pr and Ep on the dry/wet changes and the possibility of extremely wet events in the warming future. [ABSTRACT FROM AUTHOR]

Previous studies indicated that the wintertime North Pacific Oscillation (NPO) could exert marked impacts on the following winter El Niño-Southern Oscillation (ENSO) via the seasonal footprinting mechanism (SFM). Here, we examine this winter NPO-ENSO relationship in a 50-member ensemble of historical simulations conducted with the Canadian Centre for Climate Modeling and Analysis second generation Canadian Earth System Model (CanESM2) over the period of 1950–2005. The observed NPO pattern, featured by a meridional dipole atmospheric anomaly over the North Pacific, can be well reproduced by all of the 50 ensemble members. The multi-member ensemble (MME) mean can well simulate the observed NPO-ENSO relationship, as well as the SFM process. However, there exists a large spread of the results among the 50 members due to internal climate variability. Internal climate variability influences the winter NPO-ENSO relationship through modulating the subtropical center of the NPO. Specifically, the ensemble members with high NPO-ENSO correlations tend to have strong atmospheric anomalies over the subtropical North Pacific in winter. The atmospheric circulation anomaly brings strong sea surface temperature and precipitation anomalies in the tropical central Pacific and westerly wind anomalies over the tropical western Pacific in the following spring. These anomalies sustain in the following seasons and eventually lead to ENSO events in the following winter. [ABSTRACT FROM AUTHOR]

Global warming is changing the global wave climate, making waves stronger. In this study, we find that the wave climate in the South China Sea (SCS) undergoes an intensifying trend under global warming background, by examining the ERA-5 wave reanalysis data over 1979–2018. Results show a significant increase in most of the SCS, of 0.2% per year in significant wave height (SWH) and 0.15% per year in wave period (WP), but there is no significant change in surface wind speed (WS), which may correspond to the weakening of the Asian monsoon. The increase of the swell is the main characteristic of wave climate change in the SCS. We further examined the possible factors to cause the increasing of SWH, and found that the frequency of gale events occurring in the SCS and its adjacent regions increased over study period. The more frequent gale events can explain the significant increasing tendency of the SWH in the SCS by causing the occurrence of swell. The increasing appearance of gale events is closely related to the intensification of El Niño/Southern Oscillation (ENSO). ENSO activities also can regulate the interannual variability of wave climate in the SCS through the surface wind. Therefore, ENSO activities play an important role in the change of wave climate in the SCS. [ABSTRACT FROM AUTHOR]

The Equatorial Undercurrent (EUC) is a vital component of tropical Pacific circulation, helping to modulate the state of the equatorial Pacific Ocean. Here we compare the representation of the EUC in models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) with observations of the undercurrent. We find that the CMIP5 models consistently underestimate both the magnitude and variability of the EUC. Insufficient resolution as well as diffusivity parameterizations both contribute to a representation of the EUC that is too weak and too diffuse. Given the strong influence of theEUCon the evolution of tropical Pacific sea surface temperatures, model deficiencies in theEUCcontribute to shortcomings in capturing ENSO dynamics and Pacific decadal variability. Further evaluation of the impact of EUC simulation on the climatology and variability in the tropical Pacific is necessary. [ABSTRACT FROM AUTHOR]

The seasonal cycle of the evaporative stress index (ESI) over Australia, and its relationship to observed rainfall and temperature, is examined. The ESI is defined as the standardized anomaly of the ratio of actual evapotranspiration to potential evapotranspiration, and as such, is a measure of vegetation moisture stress associated with agricultural or ecological drought. The ESI is computed using the daily output of version 6 of the Bureau of Meteorology's landscape water balance model [Australian Water Resource Assessment Landscape (AWRA-L)] on a 5-km horizontal grid over a 45-yr period (1975-2019). Here we show that the ESI exhibits marked spatial and seasonal variability and can be used to accurately monitor drought across Australia, where ESI values less than negative one indicate drought. While the ESI is highly correlated with rainfall as expected, its relationship with temperature only becomes significant during the warmer seasons, suggesting a threshold above which temperature may affect vegetation stress. Our analysis also shows that the ESI tends to be strongly negative (i.e., indicating drought) during El Niño and positive phases of the Indian Ocean dipole (IOD), when conditions tend to be anomalously hot and dry. A negative phase of the southern annular mode also tends to drive negative ESI values during austral spring with a one-month delay. [ABSTRACT FROM AUTHOR]

The characteristic spatial sampling length scales (for example, in the longitudinal direction) to adequately resolve the variability associated with a quantity to be observed, depends on the typical length scales of its variability. For example, if temporal variations in the longitudinal direction are correlated over thousands of Kilometers then an observing network with a similar spatial density may be enough to sample the variability with adequate fidelity. Given the importance of surface wind stress in the equatorial tropical Pacific in determining sub-surface oceanic variability, particularly in relation to the evolution of El Niño—Southern Oscillation (ENSO), in this analysis the horizontal length scales of surface wind stress variability based on two reanalysis products—the Climate Forecast System Reanalysis and the ERA-Interim—are documented. The analysis is of relevance to the future evolution of the Tropical Pacific Observing System. As the current design of the Tropical Atmosphere Ocean [that has a wider (narrower) separation in the longitudinal (latitudinal) direction] was originally envisioned following estimates of the length scales of wind variability based on the observational record from tropical Pacific Islands (Harrison and Luther in J Clim 3:251–271, 1990), we find a similar characteristics for length scales for the surface wind variability based on reanalyses datasets. Further, the inferences based on two reanalysis products have a large degree of similarity, and thereby, give us some confidence in the reanalysis products for the purposes of analyzing the length scales of surface wind stress variability, and further, providing some basic information about the requirements for a sustained observing system in the tropical Pacific to monitor and to predict ENSO. [ABSTRACT FROM AUTHOR]

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Almost half of the tributaries of the Amazon River originate in the tropical Andes and support large populations in mountain regions and downstream areas. However, it is difficult to assess hydroclimatic conditions or to evaluate future scenarios due to the scarcity of long, high‐quality instrumental records. Data from the Global Precipitation Climatology Project (GPCP) provide a complete record since 1979 and offer a good representation of rainfall over the tropical Andes. Longer records are needed to improve our understanding of rainfall variability and summer monsoon behavior at various scales. We developed the first annually resolved precipitation reconstruction for the tropical Andes in Peru, based on tree‐ring chronologies of Cedrela and Juglans species. The annual (November–October) reconstruction extends the short instrumental records back to 1817, explaining 68% of the total variance of precipitation over the 1979–2007 calibration period. The reconstruction reveals the well‐documented influence of El Niño‐Southern Oscillation (ENSO) on Amazon Rainfall at interannual scales (~19% of total variance) and significant multidecadal variability with alternating periods of about 40 years (~13% of rainfall variability) related to the Atlantic Multidecadal Oscillation (AMO). Both oscillatory modes can explain dry and humid periods observed within the reconstruction and are likely associated with the negative trends of rainfall in the short instrumental records and the increased drought recurrence in recent decades. Our results show that montane tropical tree rings can be used to reconstruct precipitation with exceptionally high fidelity, characterize the interannual to multidecadal variability, and identify remote forcings in the hydroclimate over the Andean Amazon Basin of Peru. Key Points: Tree rings from the Andean headwaters of the Peruvian Amazon Basin allow the reconstruction of regional rainfall variability since 1817Reconstructed rainfall reveals imprints of El Niño and the Atlantic Multidecadal OscillationThere is a recurrent alternation between wet and dry periods in the past two centuries, but an increase in droughts is evident from 1980 to present [ABSTRACT FROM AUTHOR]

Previous observational and modeling studies indicate that the wintertime North Pacific Oscillation (NPO) could significantly impact the following winter El Niño-Southern Oscillation (ENSO) variability via the seasonal footprinting mechanism (SFM). This study explores climate projections of this winter NPO-ENSO relation in a warming climate based on a 50-member large ensemble of climate simulations conducted with the second-generation Canadian Earth System Model (CanESM2). The ensemble mean of the 50 members can well reproduce the observed winter NPO pattern, the NPO-ENSO relationship, and the SFM process over the historical period 1950–2003. These 50 members are then employed to examine climate projections of the NPO-ENSO connection over the anthropogenic forced period 2020–2073. Results indicate that there exists a large spread of projected NPO-ENSO connections across these 50 ensemble members due to internal climate variability. Internal climate variability brings uncertainties in the projection of the winter NPO-ENSO connection originally seen in projected changes of the subtropical center of the winter NPO. The spread of projections of winter NPO-associated atmospheric anomalies over the subtropical North Pacific further results in various responses in the projections of winter and spring precipitation anomalies over the tropical North Pacific, as well as spring zonal wind anomalies over the tropical western Pacific, which eventually lead to uncertainties in the projection of the sea surface temperature anomalies in the tropical central-eastern Pacific from the following summer to winter. [ABSTRACT FROM AUTHOR]

Paleoclimate modelling has long been regarded as a strong out-of-sample test-bed of the climate models that are used for the projection of future climate changes. For the first time, the EC-Earth model contributes to the Paleoclimate Model Intercomparison Project (PMIP) phase 4, which is part of the current sixth phase of the Coupled Model Intercomparison Project (CMIP6). Here, we document the model setup for PMIP4 experiments with EC-Earth3-LR and present the results on the large-scale features from the completed production simulations for the three past warm periods (mid-Holocene, Last Interglacial, and mid-Pliocene). Using the pre-industrial climate as a reference state, we show the changes in global temperature, large scale Hadley circulation and Walker circulation, polar warming and global monsoons, as well as the climate variability modes (ENSO, PDO, AMO). The EC-Earth3-LR simulates reasonable climate responses during past warm periods as shown in the other PMIP4- CMIP6 model ensemble. The systematic comparison of these climate changes in three past warm periods in an individual model demonstrates the ability of the model to capture the climate response under different climate forcings, providing potential implications for confidence in future projections with EC-Earth model. [ABSTRACT FROM AUTHOR]

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This paper describes the development and analysis of an objective climatology of warm and cold fronts over North America from 1979 to 2018. Fronts are detected by a convolutional neural network (CNN), trained to emulate fronts drawn by human meteorologists. Predictors for the CNN are surface and 850-hPa fields of temperature, specific humidity, and vector wind from the ERA5 reanalysis. Gridded probabilities from the CNN are converted to 2D frontal regions, which are used to create the climatology. Overall, warm and cold fronts are most common in the Pacific and Atlantic cyclone tracks and the lee of the Rockies. In contrast with prior research, we find that the activity of warm and cold fronts is significantly modulated by the phase and intensity of El Niño–Southern Oscillation. The influence of El Niño is significant for winter warm fronts, winter cold fronts, and spring cold fronts, with activity decreasing over the continental United States and shifting northward with the Pacific and Atlantic cyclone tracks. Long-term trends are generally not significant, although we find a poleward shift in frontal activity during the winter and spring, consistent with prior research. We also identify a number of regional patterns, such as a significant long-term increase in warm fronts in the eastern tropical Pacific Ocean, which are characterized almost entirely by moisture gradients rather than temperature gradients. [ABSTRACT FROM AUTHOR]

In this study, we analyze the realism with which tropical cyclones (TCs) are simulated in the fully coupled low‐ and high‐resolution Energy Exascale Earth System Model (E3SM) version 1, with a focus on the latter. Compared to the low‐resolution (grid spacing of ∼1°), the representation of TCs improves considerably in the high‐resolution configuration (grid spacing of ∼0.25°). Significant improvements are found in the global TC frequency, TC lifetime maximum intensities, and the relative distribution of TCs among the different basins. However, at both resolutions, spurious TC activity is found in some basins, notably in the subtropical regions. Contrasting the simulated large‐scale TC environment with observations reveals that the model environment is unrealistically conducive for TC development in those regions. Further analysis indicates that these biases are likely related to those in thermodynamic potential intensity, caused by systematic SST biases, and vertical wind shear in the coupled model. TC‐ocean interaction is also examined in the high‐resolution configuration of the model. The salient features of the ocean's response to TC‐induced mixing and the ocean's impact on TC intensification are well‐reproduced. Finally, an evaluation of the influence of El Niño Southern Oscillation (ENSO) on TCs in the high‐resolution configuration of the model reveals that the ENSO‐TC relationship in the model has the right sign and is significant for the North Atlantic and Northwest Pacific, albeit weaker than in observations. In summary, the high‐resolution configuration of the E3SM model simulates TC activity reasonably and hence could be a useful tool for TC‐related research. Plain Language Summary: Considering the wide range of spatiotemporal scales governing tropical cyclones (TCs), high‐resolution numerical models that can resolve both small‐scale and large‐scale processes are needed to simulate TCs realistically. In this study, we describe the simulation of TCs in version 1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) model with a focus on results from the high‐resolution configuration (spatial resolution of 0.25° in the atmosphere). When compared to the simulation at the low or standard resolution configuration (spatial resolution of 1° in the atmosphere), the salient features of TCs, such as their frequency distribution among the various basins and their strength, improve considerably in the high‐resolution configuration, underlining the value of high‐resolution modeling. Further, the high‐resolution configuration of the model realistically simulates the interaction between TCs and the ocean beneath them, which is a fundamental aspect of their development. However, our analysis also reveals that systematic errors in the simulated climate can cause misrepresentation of the model TC environment, leading to spurious TC activity in certain regions and a weaker control exerted by El Niño‐Southern Oscillation. Overall, the high‐resolution E3SM well represents the global TC climatology, supporting it as a valuable tool for studying TCs. Key Points: Under a variety of metrics, simulated TCs are significantly improved in high‐resolution versus low‐resolution E3SM configurationsSpurious TC activity in the model can be well‐explained by errors in the simulation of sea surface temperatures and the vertical wind shearTC‐induced oceanic cooling and the ocean's negative feedback on TCs are well‐simulated in the high‐resolution configuration of the model [ABSTRACT FROM AUTHOR]

The central aim of this work is to investigate the characteristics of fog events over the United Arab Emirates (UAE) and identify the underlying physical processes responsible for fog initiation and dissipation. To achieve this, hourly meteorological measurements at eight airport stations, along with ERA5 reanalysis data (1995–2018), are utilized. The analysis indicates the dominance of radiation fog (RAD) as, on average, 70% of the observed events fall under this category. Fog in the UAE typically forms between 2000 and 0200 local time (LT) and dissipates between 0600 and 0900 LT. During a typical dense fog event recorded during 22–23 December 2017, cooling and moistening tendencies of up to 1.2 K h−1 and 0.7 g kg−1 h−1 are observed ~5–6 h before fog onset. In the vertical, a dry and warm layer above 750 hPa gradually descends from above 500 hPa to promote the development of fog. Similar conclusions are reached when analyzing composites of fog events. Further, the variability of fog occurrence associated with El Niño–Southern Oscillation (ENSO) patterns is explored. It is concluded that the El Niño (warm) and La Niña (cold) phases exhibit very different spatial characteristics with respect to surface meteorological variables. In particular, during El Niño events, the near-surface atmosphere is cooler and moister compared to La Niña events, favoring RAD fog formation over the UAE. Besides, fog events during El Niño years tend to last longer compared to La Niña years due to an earlier onset. [ABSTRACT FROM AUTHOR]

The El Niño-Southern Oscillation (ENSO) is one of the most significant climate variability signals. Studying the changes in ENSO-induced precipitation variability (ENSO precipitation) in the past climate offers a possibility to a better understanding of how they may change under future climate conditions. This study uses simulations performed with the European community Earth-System Model (EC-Earth) to investigate the relative contributions of dynamic effect (the circulation anomalies together with the climatological specific humidity) and thermodynamic effect (the specific humidity anomalies together with the climatological circulation) on the changes in ENSO precipitation in the past warm and cold climates, represented by the Pliocene and the Last Glacial Maximum (LGM), respectively. The results show that the changes in ENSO precipitation are intensified (weakened) over the tropical western Pacific but weakened (intensified) over the tropical central Pacific in Pliocene (LGM) compared with the pre-industrial (PI) simulation. Based on the decomposed moisture budget equation, these changes in ENSO precipitation patterns are highly related to the dynamic effect. The mechanism can be understood as follows: the zonal gradient of the mean sea surface temperature (SST) over the tropical Indo-Pacific is increased (reduced) during the Pliocene (LGM), leading to the strengthening (weakening) of Pacific Walker Circulation as well as a westward (eastward) shift. In the Pliocene, the westward shift of Walker Circulation results in an increased (decreased) ENSO-induced low-level vertical velocity variability in the tropical western Pacific (central Pacific), and, in turn, favoring convergent (divergent) moisture transport through a dynamic process, and then causing intensified (weakened) ENSO precipitation there. The opposite mechanism exists in LGM. These results suggest that changes in the zonal SST gradient over tropical Indo-Pacific under different climate conditions determine the changes in ENSO precipitation through a dynamic process. [ABSTRACT FROM AUTHOR]

The research clarifies which climatic factors induce annual and intra-annual ring formation in merkus pine (Pinus merkusii) growing in the low lying plains of central Thailand and reconstructs the past climate by using climate modelling derived from climate-growth response. Not only are climate variations longer than a century in central Thailand explained, but the study also explores for the first time the variability in climate using the formation of intra-annual rings in Thai merkus pines. The tree-ring analysis of wood core samples indicated that the pine stand was more than 150 years old with the oldest tree being 191 years old. The annual variation in tree growth significantly correlated with local climate variables, the number of rainy days in each year (r=0.520, p<0.01) and the extreme maximum temperature in April (r=-0.377, p<0.01). The regional climate of the Equatorial Southern Oscillation in March (EQ_SOIMarch) also highly correlated with the pine growth (r=0.360, p<0.01). The climate reconstruction indicated a declining trend in the number of rainy days during the 20th century and a decline in the number of rainy days was observed during the first and second decades of the 21st century, respectively, while the past climate reconstruction of maximum temperature in April and EQ SOIMarch indicated a decline during the previous century and an increase in this century. A multiple regression analysis indicated that the extreme maximum temperature, which declined at the beginning of the wet season and increased around the transitional period of the late rainy and the cold seasons, influenced the formation of intraannual rings (r2=40.5%, p<0.05). It can be summarized that the number of rainy days increasing in each year associated with the declining temperature at the beginning of the wet season indicated a rapid growth in P. merkusii, while the anomalous temperature declining at the beginning and increasing at the end of the wet season was the main factor inducing the intra-annual ring formation. Therefore the activity of forest and planation management, especially in the watering at the beginning of the wet season when anomalous increased temperature occurred, shall be specified in the forest management plan in order to increase annual pine growth and wood formation. [ABSTRACT FROM AUTHOR]