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The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

In this paper we introduce an objective definition for the onset and the retreat of the northern Australian rainy season that overlaps significantly with the Australian monsoon season. We define onset and retreat dates of the northern Australian rainy season as being the first and the last day of the year when the daily rain rate exceeds and falls below the climatological annual mean rain rate, respectively. However, our definition of onset/demise is not as restrictive as the traditional monsoon season that seeks the arrival of the westerlies and the equatorward retreat of the trough at its onset and demise, respectively. As defined in this paper, the length of the rainy season is longer than the monsoon season and includes the pre- and post-monsoon rainfall. It is noted that an early or later onset date of the northern Australian rainy season is associated with a longer or shorter, wetter or drier, and colder or warmer season, respectively. Similar relationship is also observed with demise date variations, which are, however, weaker than the onset date variations. Furthermore, we find that the relationship of the northern Australian seasonal rainfall variations with ENSO variability becomes stronger when we account for variations in the length of the rainy season compared to the fixed (December-- February) monsoon season length. We also find a significant linear trend over the time period of the analysis from 1901 to 2015 toward an increasing length of the northern Australian rainy season that influences the corresponding rising trend of seasonal rainfall anomalies. [ABSTRACT FROM AUTHOR]

The paper presents a discussion on an opinion about the stability margin towards an emergency in local climate dynamics from the bifurcation analysis viewpoint. With this purpose we propose to attract the practice-oriented bifurcation analysis, where the conflict-of-units between notions used to understand natural evolution processes and notions used to describe desirable artificial regimes is resolved by integrating analytics on the basis of modified bifurcation diagrams. The discussion focuses on the phenomenon of interannual temperature variability, where local annual maximums and minimums are analyzed with daily details in both time and temperature coordinates. This phenomenon is considered via the probable, periodical and regulator conceptions. Advantages of the regulator conception are verified by results of processing the data of temperature meteorological observations on daily means over the last 135 years. This conception is based on the HDS-hypothesis, in accordance to which local climate dynamics is determined by the natural competition between the amplitude quantization (restricted by the temperature Hysteresis) and time quantization (caused by the Double Synchronization). Thus an alternation between three elementary processes with the same period (year) and different patterns of annual warming–cooling cycles is supposed as a typical behavior for local climate systems, and the idea on high-dynamic local climate ensembles is developed instead of the conventional opinion on quasi-static local climate norms. Mechanisms of temperature changes due to abrupt shifts (so-called change-points) of the HDS-regulator parameters are distinguished from mechanisms of temperature changes due to bifurcations. The notion of a stability margin is used as a distance to an emergency and is visualized in the parametrical space. So, in spite of the mechanisms of temperature changes with/without bifurcations are different, their conflict-free sewing becomes conceptually possible in the context of the stability margin towards emergencies determined relatively bifurcation boundaries in the parametrical space. Since the discussed dynamics is not supposed to exist in terms of the traditional estimations concerning the observed local climate changes, then we believe that the paper would be interesting for scientists in the field of bifurcation analysis as well as for scientists and specialists, activity areas of which relate to the contemporary challenges connected with climate changes. [ABSTRACT FROM AUTHOR]

Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

In a comment on a 2017 paper by Cheung et al., Kravtsov states that the results of Cheung et al. are invalidated by errors in the method used to estimate internal variability in historical surface temperatures, which involves using the ensemble mean of simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to estimate the forced signal. Kravtsov claims that differences between the forced signals in the individual models and as defined by the multimodel ensemble mean lead to errors in the assessment of internal variability in both model simulations and the instrumental record. Kravtsov proposes a different method, which instead uses CMIP5 models with at least four realizations to define the forced component. Here, it is shown that the conclusions of Cheung et al. are valid regardless of whether the method of Cheung et al. or that of Kravtsov is applied. Furthermore, many of the points raised by Kravtsov are discussed in Cheung et al., and the disagreements of Kravtsov appear to be mainly due to a misunderstanding of the aims of Cheung et al. [ABSTRACT FROM AUTHOR]

Recent observations suggest that El Niño–Southern Oscillation (ENSO) impacts basal melting of West Antarctic ice shelves, yet sparse ocean observations limit our understanding of the associated processes. Here we investigate how ENSO events modulate subsurface West Antarctic shelf temperatures using high‐resolution global ocean‐sea ice model simulations. During El Niño, the subsurface shelf warming between 150 m and the shelf bottom can be up to 0.5°C in front of ice shelves. This warming arises from a weaker Amundsen Sea Low (ASL) and weaker coastal easterlies that reduce on‐shelf Ekman transport of cold surface waters, enabling enhanced transport of warm Circumpolar Deep Water (CDW) onto the shelf. A largely opposite response occurs during La Niña, with a stronger ASL and stronger Ekman transport that results in less cross‐shelf CDW transport and cooling in the subsurface. These findings have implications for interpreting basal melting on interannual to decadal time‐scales in West Antarctica. Plain Language Summary: El Niño‐Southern Oscillation (ENSO) is the Earth's dominant year‐to‐year climate variation. The impacts of its two phases, El Niño and La Niña, extend from the tropics to Antarctica through atmospheric waves. Past studies have suggested that West Antarctic ice shelves melt more during El Niño because of warmer ocean waters at the ice shelf bases. However, oceanic changes during El Niño lead to warming on the shelf near the ice which is difficult to isolate. That is because ENSO is only one of many drivers that impact shelf water temperatures. In this work, we simulate isolated ENSO events using an ocean circulation model. We show that during El Niño, the on‐shelf flow of cold surface waters in West Antarctica, driven by coastal easterly winds, is reduced because the winds weaken. To balance out this mass deficit at the surface, more warm CDW flows onto the continental shelf below. During La Niña, we see a largely opposite response. Stronger coastal easterlies increase the on‐shelf flow of cold surface waters and less CDW is flowing onto the shelf. Our results show the link between ENSO and mass loss of the West Antarctic ice shelves and ice sheet. Key Points: Ocean‐sea ice model simulations of El Niño and La Niña events illustrate how they modulate West Antarctic shelf temperaturesEl Niño weakens coastal easterlies, reduces on‐shelf Ekman flow of cold waters, increasing cross‐shelf flow of warm Circumpolar Deep Water (CDW)The La Niña shelf circulation response is largely opposite and reduces cross‐shelf transport of warm CDW [ABSTRACT FROM AUTHOR]

In a recent article, Li et al. examined changes in the summer-season location of the western ridge of the North Atlantic subtropical high from 1948 to 2007 because there has been an increase in interannual summer rainfall variability in the southeastern United States. The following major conclusions by Li et al. are incorrect: the western ridge has undergone a significant westward trend since the late 1970s; the western ridge had increased meridional movement during 1978-2007 compared to 1948-1977; and global warming appears to be contributing to the westward expansion of the western ridge. Results presented in this paper reveal that the western ridge has been moving eastward over the past three decades, there was no change in latitudinal variance, and a westward movement of the western ridge should not be linked to global warming. [ABSTRACT FROM AUTHOR]

The East Asian winter monsoon (EAWM) is characterized by the frequent cold surges and associated closely with the Siberia High, East Asian Trough, and high-level westerly jet stream. The ENSO cycle can modulate the EAWM since it has co-variability with the sea surface temperature over the Indo-Western-Pacific which can tune the land-sea thermal contrast for the EAWM. This paper, by analyzing the EAWM, ENSO, and associated atmosphere-ocean variability, documents the weakening of the EAWM-ENSO relationship after the 1970s. The significant out-of-phase inter-relationship is found to be diminished after the 1970s. Further study in this work suggests that the weakened co-variability of the tropical Indo-Western-Pacific climate associated with ENSO after the 1970s is partly responsible for the weakened inter-relationship. Meanwhile, the reduced EAWM interannual variability and northward retreat of the EAWM-associated climate variability are favorable to the weakened ENSO-EAWM connection. [ABSTRACT FROM AUTHOR]

Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade-1, SAT increasing 0.10°C decade-1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future.

Changes in internal variability of seasonal and annual mean 2-m temperature in response to anthropogenic forcing are quantified for a global domain using climate models driven by a twenty-first-century high-emissions scenario. While changes in variance have been quantified previously in a univariate sense, the field significance of such changes has remained unclear. This paper proposes a new field significance test for changes in variance that accounts for spatial and temporal relationships within the domain. The test proposed here uses an optimization technique based on discriminant analysis, yielding results that are invariant to linear transformations of the data and therefore independent of normalization procedures. Multiple significance tests are employed because spatial fields can differ in many ways in a multivariate space. All climate models investigated here predict significant changes in internal variability of temperature in response to anthropogenic forcing. The models consistently predict decreases to temperature variance in regions of seasonal sea ice formation and across the Southern Ocean by the end of the twenty-first century. While more than half the models also predict significant changes in variance over ENSO regions and the North Atlantic Ocean, the direction of this change is model dependent. Seasonal mean changes are remarkably similar to annual mean changes, but there are model-dependent exceptions. Some models predict future variability that is more than double their preindustrial control variability, raising questions about the adequacy of doubling uncertainty estimates to test robustness in detection and attribution studies. [ABSTRACT FROM AUTHOR]

The vulnerability of water supplies to shortage depends on the complex interplay between streamflow variability and the management and demands of the water system. Assessments of water supply vulnerability to potential changes in streamflow require methods capable of generating a wide range of possible streamflow sequences. This paper presents a method to generate synthetic monthly streamflow sequences that reproduce the statistics of the historical record and that can express climate-induced changes in user-specified streamflow characteristics. The streamflow sequences are numerically simulated through random sampling from a parametric or a nonparametric distribution fitted to the historical data while shuffling the values in the time series until a sequence matching a set of desired temporal properties is generated. The desired properties are specified in an objective function which is optimized using simulated annealing. The properties in the objective function can be manipulated to generate streamflow sequences that exhibit climate-induced changes in streamflow characteristics such as interannual variability or persistence. The method is applied to monthly streamflow data from the Thames River at Kingston (UK) to generate sequences that reproduce historical streamflow statistics at the monthly and annual time scales and to generate perturbed synthetic sequences expressing changes in short-term persistence and interannual variability. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) climatology (1980-2010) is developed and analyzed across the U.S. Corn Belt using state climate division weather and historic corn yield data using analysis of variance (ANOVA) and correlation analysis. Findings provide insight to agroclimatic conditions under different ENSO and AO episodes and are analyzed with a perspective for potential impacts to agricultural production and planning, with findings being developed into a web-based tool for the U.S. Corn Belt. This study is unique in that it utilizes the oceanic Niño index and explores two teleconnection patterns that influence weather across different spatiotemporal scales. It is found that the AO has a more frequent weak to moderate correlation to historic yields than ENSO when correlated by average subgrowing season index values. Yield anomaly and ENSO and AO episode analysis affirms the overall positive impact of El Niño events on yields compared to La Niña events, with neutral ENSO events in between as found in previous studies. Yields when binned by the AO episode present more uncertainty. While significant temperature and precipitation impacts from ENSO and AO are felt outside of the primary growing season, correlation between threshold variables of episode-specific temperature and precipitation and historic yields suggests that relationships between ENSO and AO and yield are present during specific months of the growing season, particularly August. Overall, spatial climatic variability resulting from ENSO and AO episodes contributes to yield potential at regional to subregional scales, making generalization of impacts difficult and highlighting a continued need for finescale resolution analysis of ENSO and AO signal impacts on corn production. [ABSTRACT FROM AUTHOR]

Using the newly available decade-long Argo data for the period 2004-13, a detailed study is carried out on deriving four-dimensional (4D) modality of sea temperature in the upper ocean with emphasis on its interannual variability in terms of amplitude, phase, and periodicity. Three principal modes with central periodicities at 19.2, 33.8, and 50.3 months have been identified, and their relationship with El Niño-Southern Oscillation (ENSO) is investigated, yielding a number of useful results and conclusions: 1) A striking tick-shaped pipe-like feature of interannual variability maxima, which is named the 'Niño pipe' in this paper, has been revealed within the 10°S-10°N upper Pacific Ocean. 2) The pipe core extends downward from ~50 m at 130°E to ~250 m near the date line before tilting upward to the sea surface at about 275°E, coinciding nicely with the pathway of the Pacific equatorial undercurrent (EUC). 3) The double-peak zonal modality pattern of the Niño pipe in the upper Pacific is echoed in the subsurface Atlantic and Indian Oceans through Walker circulation, while its single-peak meridional modality pattern is mirrored in the subsurface North and South Pacific through Hadley circulation. 4) A coherent three-peak modal structure implies a strong coupling between sea level variability at the surface and sea temperature variability around the thermocline. Accumulating evidence suggests that Rossby/Kelvin wave dynamics in tandem with EUC-based thermocline dynamics are the main mechanisms of the three-mode Niño pipe in ENSO cycles. [ABSTRACT FROM AUTHOR]

Global warming will have direct impacts on regional water resources by accelerating the hydrological cycle. Hydrological simulation is an important approach to studying climate change impacts. In this paper, a snowmelt-based water balance model (SWBM) was used to simulate the effect of climate change on runoff in the Kuye River catchment of the Loess Plateau, China. Results indicated that the SWBM is suitable for simulating monthly discharge into arid catchments. The response of runoff in the Kuye River catchment to climate change is nonlinear, and runoff is more sensitive to changes in precipitation than to changes in temperature. The projections indicated that the Kuye River catchment would undergo more flooding in the 2020s, and global warming would probably shorten the main flood season in the catchment, with greater discharge occurring in August. Although projected changes in annual runoff are uncertain, the possibilities of regional water shortages and regional flooding are essential issues that need to be fully considered. [ABSTRACT FROM AUTHOR]

Climate change impacts on wave conditions can increase the risk of offshore and coastal hazards. The present paper investigates wave climate multidecadal trends and interannual variability in the Bay of Biscay during the past decades (1958-2001). Wave fields are computed with a wave modeling system based on the WAVEWATCH III code and forced by 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) wind fields. It provides both an extended spatiotemporal domain and a refined spatial resolution over the Bay of Biscay. The validation of the wave model is based on 11 buoys, allowing for the use of computed wave fields in the analysis of mean and extreme wave height trends and variability. Wave height, period, and direction are examined for a large array of wave conditions (by seasons, high percentiles of wave heights, different periods). Several trends for recent periods are identified, notably an increase of summer significant wave height, a southerly shift of autumn extreme wave direction, and a northerly shift of spring extreme wave direction. Wave fields exhibit high interannual variability, with a normalized standard deviation of seasonal wave height greater than 15%% in wintertime. The relationship with Northern Hemisphere teleconnection patterns is investigated at regional scale, especially along the coast. It highlights a strong correlation between local wave conditions and the North Atlantic Oscillation and the east Atlantic pattern indices. This relationship is further investigated at the local scale with a new method based on bivariate diagrams, allowing the identification of the type of waves (swell, storm, intermediate waves) impacted. These results are discussed in terms of comparison with previous studies and coastal risk implications. [ABSTRACT FROM AUTHOR]

Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment. [ABSTRACT FROM AUTHOR]

Overlying the challenge of managing within natural hydroclimatic variability is the likely modification of runoff variability along with average runoff due to anthropogenic enhancement of greenhouse gas concentrations. In this paper analytical models are developed in which runoff mean and variability, the latter defined by the variance (or standard deviation) of annual runoff, are related to the variances and the covariance of annual precipitation and potential evapotranspiration, and the aridity index (mean annual potential evapotranspiration divided by mean annual precipitation). The method was validated using observed runoff data for 699 worldwide catchments. It was concluded that combining the Schreiber function, which relates the ratio of annual actual evapotranspiration to annual precipitation, with the analytical models provided satisfactory estimates of observed annual runoff mean and interannual variability. It was also concluded that estimates of annual runoff variability based on the simplified model of Koster and Suarez were unsatisfactory. By way of illustrating the new methodology, the approach was applied to projected annual values of precipitation from the Hadley Centre Global Environment Model version 1 (HadGEM) and it showed that considerable changes in reservoir yield are likely to occur if climate change projections of precipitation from HadGEM are realistic. Finally, further simplifications of the equations, based on the Schreiber function, are developed to estimate the mean and standard deviation of annual runoff that allow climate analysts to estimate the impact of potential climate changes on annual runoff characteristics and reservoir yield performance without having to resort to the calibration and application of a rainfall-runoff model or rely on the runoff output from general circulation models to examine such characteristics. [ABSTRACT FROM AUTHOR]

Water management in Australia has traditionally been carried out on the assumption that the historical record of rainfall, evaporation, streamflow, and recharge is representative of current and future climatic conditions. However, in many circumstances, this does not adequately address the potential risks to supply security for towns, industry, irrigators, and the environment. This is because the Australian climate varies markedly due to natural cycles that operate over periods of several years to several decades. There is also serious concern about how anthropogenic climate change may exacerbate drought risk in the future. In this paper, the frequency and severity of droughts are analyzed during a range of “climate states” (e.g., different phases of the Pacific, Indian, and/or Southern Oceans) to demonstrate that drought risk varies markedly over interannual through to multidecadal time scales. Importantly, by accounting for climate variability and change on multitemporal scales (e.g., interdecadal, multidecadal, and the palaeo scale), it is demonstrated that the risk of failure of current drought management practices may be better assessed and more robust climate adaptation responses developed. [ABSTRACT FROM AUTHOR]

The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index (NDVI) dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982–2002. The temporal variation also exhibits striking regional differences: an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability. [ABSTRACT FROM AUTHOR]

Advancing spring phenology is a well documented consequence of anthropogenic climate change, but it is not well understood how climate change will affect the variability of phenology year to year. Species' phenological timings reflect the adaptation to a broad suite of abiotic needs (e.g., thermal energy) and biotic interactions (e.g., predation and pollination), and changes in patterns of variability may disrupt those adaptations and interactions. Here, we present a geographically and taxonomically broad analysis of phenological shifts, temperature sensitivity, and changes in interannual variability encompassing nearly 10,000 long‐term phenology time series representing more than 1000 species across much of the Northern Hemisphere. We show that the timings of leaf‐out, flowering, insect first‐occurrence, and bird arrival were the most sensitive to temperature variation and have advanced at the fastest pace for early‐season species in colder and less seasonal regions. We did not find evidence for changing variability in warmer years in any phenophase groups, although leaf‐out and flower phenology have become moderately but significantly less variable over time. Our findings suggest that climate change has not to this point fundamentally altered the patterns of interannual phenological variability. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that a major part of the observed variability in vegetation state might be associated with variability in climatic drivers during relatively short periods within the year. Identification of such critical climate periods, when a particular climate variable most likely has a pronounced influence on the vegetation state of a particular ecosystem, becomes increasingly important in the light of climate change. In this study, we present a method to identify critical climate periods for eight different semi-natural ecosystem categories in Hungary, in Central Europe. The analysis was based on the moving-window correlation between MODIS NDVI/LAI and six climate variables with different time lags during the period 2000–2020. Distinct differences between the important climate variables, critical period lengths, and direction (positive or negative correlations) have been found for different ecosystem categories. Multiple linear models for NDVI and LAI were constructed to quantify the multivariate influence of the environmental conditions on the vegetation state during the late summer. For grasslands, the best models for NDVI explained 65–87% variance, while for broad-leaved forests, the highest explained variance for LAI was up to 50%. The proposed method can be easily implemented in other geographical locations and can provide essential insight into the functioning of different ecosystem types. [ABSTRACT FROM AUTHOR]

The Atlantic meridional overturning circulation (AMOC) has received considerable attention, motivated by its major role in the global climate system. Observations of AMOC strength at 26°N made by the Rapid Climate Change (RAPID) array provide the best current estimate of the state of the AMOC. The period 2004-11 when RAPID AMOC is available is too short to assess decadal variability of the AMOC. This modeling study introduces a new AMOC index (called AMOCSV) at 26°N that combines the Florida Straits transport, the Ekman transport, and the southward geostrophic Sverdrup transport. The main hypothesis in this study is that the upper midocean geostrophic transport calculated using the RAPID array is also wind-driven and can be approximated by the geostrophic Sverdrup transport at interannual and longer time scales. This index is expected to reflect variations in the AMOC at interannual to decadal time scales. This estimate of the surface branch of the AMOC can be constructed as long as reliable measurements are available for the Gulf Stream and for wind stress. To test the reliability of the AMOCSV on interannual and longer time scales, two different numerical simulations are used: a forced and a coupled simulation. Using these simulations the AMOCSV captures a substantial fraction of the AMOC variability and is in good agreement with the AMOC transport at 26°N on both interannual and decadal time scales. These results indicate that it might be possible to extend the observation-based AMOC at 26°N back to the 1980s. [ABSTRACT FROM AUTHOR]

The strong relationship between eastern Australian winter-spring rainfall and tropical modes of variability such as the El Niño-Southern Oscillation (ENSO) does not extend to the heavily populated coastal strip east of the Great Dividing Range in southeast Australia, where correlations between rainfall and Niño-3.4 are insignificant during June-October. The Indian Ocean dipole (IOD) is found to have a strong influence on zonal wind flow during the winter and spring months, with positive IOD increasing both onshore winds and rainfall over the coastal strip, while decreasing rainfall elsewhere in southeast Australia. The IOD thus opposes the influence of ENSO over the coastal strip, and this is shown to be the primary cause of the breakdown of the ENSO-rainfall relationship in this region. [ABSTRACT FROM AUTHOR]

To study the potential impacts of climate change on air quality and public health over the eastern United States, a coupled global/regional-scale modeling system consisting of the NASA-Goddard Institute for Space Studies Atmosphere–Ocean model, the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) model for air quality has been developed. Evaluation results of the modeling system used to simulate climate and ozone air quality over the eastern United States during the five summers of 1993–1997 are presented in this paper. The results indicate that MM5 and CMAQ capture interannual and synoptic-scale variability present in surface temperature and ozone observations in the current climate, while the magnitude of fluctuations on shorter time scales is underestimated. A comparison of observed and predicted spatial patterns of daily maximum ozone concentrations shows best performance in predicting patterns for average and above-average ozone concentrations. The frequency distributions of the duration of extreme heat and ozone events show similar features for both model predictions and observations. Finally, application of a synoptic map-typing procedure reveals that the MM5/CMAQ system succeeded in simulating the average ozone concentrations associated with several frequent pressure patterns, indicating that the effects of synoptic-scale meteorology on ozone concentrations are captured by the modeling system. It is concluded that the GCM/MM5/CMAQ system is a suitable tool for the simulation of summertime surface temperature and ozone air quality conditions over the eastern United States in the present climate. [Copyright &y& Elsevier]

This study investigates what forms the spatial pattern of the amplitude changes in tropical intraseasonal and interannual variability—represented by the two most important variables, precipitation (ΔP′) and circulation (Δω′)—under global warming, based on 24 models from the phase 5 of the Coupled Model Intercomparison Project (CMIP5). Diagnostic analyses reveal that the moisture budget and thermodynamic energy equations related to the ΔP′ and Δω′ proposed separately in previous studies are simultaneously tenable. As a result, we investigate the mechanism for the spatial pattern of Δω′ from the perspective of the moist static energy (MSE) balance mainly considering the positive contribution from vertical advection. Therefore, based on the simplified MSE balance, the spatial pattern of Δω′ can be approximately projected based on three factors: background circulation variability ω′, the vertical gradient of mean-state MSE M̅, and its future change Δ M̅ . Under global warming, the middle-level vertical gradient of MSE increases slightly over the Indian Ocean and the Maritime Continent and decreases over the equatorial Pacific where the increase in sea surface temperature (SST) exceeds the tropical mean. The vertical gradient of mean-state MSE is modified by the increase in vertical gradients of moisture and dry static energy (DSE) simultaneously. In short, the change in the vertical gradient of mean-state MSE under global warming can influence the moisture budget and thermodynamic energy balances, resulting in the spatial pattern of ΔP′ and Δω′ at intraseasonal and interannual time scales consequently, mainly determined by the lower boundary moisture condition in the response of the SST change pattern. [ABSTRACT FROM AUTHOR]

Long-term variabilities in daily precipitation and temperature are critical for assessing the impacts of climate change on ecosystems. We characterized intra- and interannual variabilities in daily precipitation and temperature obtained from 1960 to 2015 at 78 meteorological stations on the Qinghai–Tibetan Plateau. The results show the following. 1) the intra-annual variability of daily precipitation increases for 55 meteorological stations with a rate of 0.08 mm decade−1. In contrast, the intra-annual variability markedly decreases for daily mean, daytime mean, and nighttime mean temperatures with a rate of 0.09°, 0.07°, and 0.12°C decade−1, respectively, at 90% or more of stations. 2) Variabilities of daily precipitation and temperatures are very sensitive to high altitudes (>3500 m). The intra- and interannual variabilities of daily precipitation significantly decrease at 1.0 and 0.07 mm (1000 m)−1, respectively. However, variations of high altitudes increase the intra- and interannual variabilities of daily mean temperature at 1.0° and 0.2°C (1000 m)−1, respectively. Moreover, the interannual variability of nighttime mean temperature varies at 0.3°C (1000 m)−1, the fastest rate among three temperature indices. 3) A larger mean annual precipitation is accompanied by a higher intra- and interannual variability of daily precipitation on the Qinghai–Tibetan Plateau; however, a higher mean annual temperature leads to lower variabilities of daily temperatures. This study illustrates that long-term climatic variability is understudied in alpine ecosystems characterized by high climatic sensitivity. Precipitation and temperature variabilities should be characterized to improve predictions of vulnerable ecosystems responding to climate change. [ABSTRACT FROM AUTHOR]

Changes in precipitation variability can have large societal consequences, whether at the short time scales of flash floods or the longer time scales of multiyear droughts. Recent studies have suggested that in future climate projections, precipitation variability rises more steeply than does its mean, leading to concerns about societal impacts. This work evaluates changes in mean precipitation over a broad range of spatial and temporal scales using a range of models from high-resolution regional simulations to millennial-scale global simulations. Results show that changes depend on the scale of aggregation and involve strong regional differences. On local scales that resolve individual rainfall events (hours and tens of kilometers), changes in precipitation distributions are complex and variances rise substantially more than means, as is required given the well-known disproportionate rise in precipitation intensity. On scales that aggregate across many events, distributional changes become simpler and variability changes smaller. At regional scale, future precipitation distributions can be largely reproduced by a simple transformation of present-day precipitation involving a multiplicative shift and a small additive term. The "extra" broadening is negatively correlated with changes in mean precipitation: in strongly "wetting" areas, distributions broaden less than expected from a simple multiplicative mean change; in "drying" areas, distributions narrow less. Precipitation variability changes are therefore of especial concern in the subtropics, which tend to dry under climate change. Outside the tropics, variability changes are similar on time scales from days to decades (i.e., show little frequency dependence). This behavior is highly robust across models, suggesting it may stem from some fundamental constraint. [ABSTRACT FROM AUTHOR]

Weather systems in the southern Indian Ocean (SIO) drive synoptic-scale precipitation variability in East Antarctica and southern Australia. Improved understanding of these dynamical linkages is beneficial to diagnose long-term climate changes from climate proxy records as well as informing regional weather and climate forecasts. Self-organizing maps (SOMs) are used to group daily 500-hPa geopotential height (z500; ERA-Interim) anomalies into nine regional synoptic types based on their dominant patterns over the SIO (30°-75°S, 40°-180°E) from January 1979 to October 2018. The pattern anomalies represented include four meridional, three mixed meridional-zonal, one zonal, and one transitional node. The frequency of the meridional nodes shows limited association with the phase of the southern annular mode (SAM), especially during September-November. The zonal and mixed patterns were nevertheless strongly and significantly correlated with SAM, although the regional synoptic representation of SAM+ conditions was not zonally symmetric and was represented by three separate nodes. We recommend consideration of how different synoptic conditions vary the atmospheric representation of SAM+ in any given season in the SIO. These different types of SAM+ mean a hemispheric index fails to capture the regional variability in surface weather conditions that is primarily driven by the synoptic variability rather than the absolute polarity of the SAM. [ABSTRACT FROM AUTHOR]

Changes in atmospheric CO2 variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO2 for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO2 simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO2 was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO2 showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO2 and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO2 also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO2 increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.

In 2018, central and northern parts of Europe experienced heat and drought conditions over many months from spring to autumn, strongly affecting both natural ecosystems and crops. Besides their impact on nature and society, events like this can be used to study the impact of climate variations on the terrestrial carbon cycle, which is an important determinant of the future climate trajectory. Here, variations in the regional net ecosystem exchange (NEE) of CO2 between terrestrial ecosystems and the atmosphere were quantified from measurements of atmospheric CO2 mole fractions. Over Europe, several observational records have been maintained since at least 1999, giving us the opportunity to assess the 2018 anomaly in the context of at least two decades of variations, including the strong climate anomaly in 2003. In addition to an atmospheric inversion with temporally explicitly estimated anomalies, we use an inversion based on empirical statistical relations between anomalies in the local NEE and anomalies in local climate conditions. For our analysis period 1999–2018, we find that higher-than-usual NEE in hot and dry summers may tend to arise in Central Europe from enhanced ecosystem respiration due to the elevated temperatures, and in Southern Europe from reduced photosynthesis due to the reduced water availability. Despite concerns in the literature, the level of agreement between regression-based NEE anomalies and temporally explicitly estimated anomalies indicates that the atmospheric CO2 measurements from the relatively dense European station network do provide information about the year-to-year variations of Europe's carbon sources and sinks, at least in summer. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'. [ABSTRACT FROM AUTHOR]

Long-term climate variations have the potential to amplify or dampen (human-induced) trends in temperature. Understanding natural climate variability is therefore of vital importance, especially since the variability itself may change with a changing climate. Here, we quantify the magnitude and other characteristics of interannual to decadal variability in Arctic temperature and their dependence on the climate state. Moreover, we identify the processes responsible for the state dependency of the variations, using five quasi-equilibrium climate simulations of a state-of-the-art global climate model with 0.25, 0.5, 1, 2, and 4 times present-day atmospheric CO2 forcing. The natural fluctuations in Arctic temperature, including their dependence on the state of the climate, are linked to anomalous atmospheric and oceanic heat transports toward the Arctic. Model results suggest that atmospheric heat transport leads (and also controls) Arctic temperature variations on interannual time scales, whereas oceanic transport is found to govern the fluctuations on decadal time scales. This time-scale transition of atmospheric to oceanic dominance for Arctic temperature variations is most obvious when there is interannual to decadal variability in Arctic sea ice cover. In warm climates (without Arctic sea ice cover), there is no correlation between oceanic transport and surface air temperature on any time scale. In cold climates (with full Arctic sea ice cover), interaction between ocean and atmosphere is limited, leaving poleward atmospheric heat transport to be the primary driver on all time scales (interannual and decadal). [ABSTRACT FROM AUTHOR]

This study disentangles the changes in Indian Ocean (IO) dipole (IOD)-related SST and rainfall variability under global warming projected by the RCP8.5 runs in 29 CMIP5 models. The IOD rainfall changes consist of the thermodynamic component due to the surface moisture increase and the dynamic component due to the changes in IOD-related circulation. The IOD circulation changes are dominated by the IOD SST changes, which were further clarified using the amplitude and structural decomposition. The amplitudes of IOD SST and circulation are both decreased at rates of around 7.2% and 13.7% °C−1, respectively. The structural changes in IOD SST and circulation show a pattern with increases from the eastern to the western coast of the equatorial IO, similar to the pattern of so-called extreme IOD events in previous studies. Disentangling previous mechanisms and projections, we conclude that the increased atmospheric stability suppresses the amplitudes in IOD SST and circulation, whereas the positive IOD (pIOD)-like mean-state SST changes, leading to greater warming in the west than the east, mainly alter the structure of IOD SST and circulation. Both the amplitude and structural changes in the IOD SST and circulation are robust among the CMIP5 models, but their distinct patterns and out-of-step changes lead to an uncertain projection of IOD changes defined by the dipole mode index or EOF analysis in previous studies. Furthermore, the structural changes, dominated by the pIOD-like mean-state SST changes, are significantly correlated with the historical IOD amplitude among the models. Considering the commonly overestimated IOD amplitude as an emergent constraint, the structural changes in IOD SST and circulation should not be as robust as the original multimodel projection. [ABSTRACT FROM AUTHOR]

This study applies the maximum temperatures at more than 2000 Chinese stations to investigate the dominant modes of China summer heat waves (HWs). The first empirical orthogonal function (EOF) mode of the HW days reflects an increased frequency of HWs in northern China (NC), while the second and third modes represent two distinct interannual modes, with key regions over the Yangtze River valley (YRV) and southern China (SC), respectively. The NC HWs are possibly associated with the Atlantic–Eurasian teleconnection, showing zonally propagating wave trains over the North Atlantic and Eurasian continent. The YRV HWs are proposed to be linked to the North Atlantic Oscillation, which may trigger a southeastward-propagating wave train over northern Russia and East Asia that results in a high pressure anomaly over the YRV. The SC HWs are obviously dominated by the Indian Ocean and northwest Pacific warm SSTs owing to the transition from the preceding El Niño to La Niña, which excites above-normal highs over SC. The anomalously high pressures over NC, the YRV, and SC are usually accompanied by descending air motions, clear skies, decreased precipitation, and increased solar radiation, which jointly cause a drier and hotter soil condition that favors the emergence of HWs. The GFDL HiRAM experiments are able to reproduce the historical evolution of NC and SC HWs, but fail to capture the YRV HWs. The correlation coefficient between model PC1 (PC2) and observed PC1 (PC3) for the period of 1979–2008 is 0.65 (0.38), which significantly exceeds the 95% (90%) confidence level, indicating that this model has a more faithful representation for the SST-forced HWs. [ABSTRACT FROM AUTHOR]

Soil moisture anomalies within the root zone (roughly, soil depths down to ~0.4 m) typically persist only a few months. Consequently, land surface–related climate predictability research has often focused on subseasonal to seasonal time scales. However, in this study of multidecadal in situ datasets and land data assimilation products, we find that root zone soil moisture anomalies can recur several or more seasons after they were initiated, indicating potential interannual predictability. Lead–lag correlations show that this recurrence often happens during one fixed season and also seems related to the greater memory of soil moisture anomalies within the layer beneath the root zone, with memory on the order of several months to over a year. That is, in some seasons, notably spring and summer when the vertical soil water potential gradient reverses sign throughout much of North America, deeper soil moisture anomalies appear to return to the surface, thereby restoring an earlier root zone anomaly that had decayed. We call this process "reemergence," in analogy with a similar seasonally varying process (with different underlying physics) providing winter-to-winter memory to the extratropical ocean surface layer. Pronounced spatial and seasonal dependence of soil moisture reemergence is found that is frequently, but not always, robust across datasets. Also, some of its aspects appear sensitive to spatial and temporal sampling, especially within the shorter available in situ datasets, and to precipitation variability. Like its namesake, soil moisture reemergence may enhance interannual-to-decadal variability, notably of droughts. Its detailed physics and role within the climate system, however, remain to be understood. [ABSTRACT FROM AUTHOR]

Understanding the extent to which Atlantic sea surface temperatures (SSTs) are predictable is important due to the strong climate impacts of Atlantic SST on Atlantic hurricanes and temperature and precipitation over adjacent landmasses. However, models differ substantially on the degree of predictability of Atlantic SST and upper-ocean heat content (UOHC). In this work, a lower bound on predictability time scales for SST and UOHC in the North Atlantic is estimated purely from gridded ocean observations using a measure of the decorrelation time scale based on the local autocorrelation. Decorrelation time scales for both wintertime SST and UOHC are longest in the subpolar gyre, with maximum time scales of about 4–6 years. Wintertime SST and UOHC generally have similar decorrelation time scales, except in regions with very deep mixed layers, such as the Labrador Sea, where time scales for UOHC are much larger. Spatial variations in the wintertime climatological mixed layer depth explain 51%–73% (range for three datasets analyzed) of the regional variations in decorrelation time scales for UOHC and 26%–40% (range for three datasets analyzed) of the regional variations in decorrelation time scales for wintertime SST in the extratropical North Atlantic. These results suggest that to leading order decorrelation time scales for UOHC are determined by the thermal memory of the ocean. [ABSTRACT FROM AUTHOR]

Phytoplankton community structure was analysed from 2010 to 2017 at C1-LTER, the coastal Long- Term Ecological Research station located in the Gulf of Trieste, which is the northernmost part of the Mediterranean Sea. Phytoplankton abundance and relevant oceanographic parameters were measured monthly in order to describe the seasonal cycle and interannual variability of the main phytoplankton taxa (diatoms, dinoflagellates, coccolithophores and flagellates) and to analyse their relationship with environmental conditions. Overall, phytoplankton abundances showed a marked seasonal cycle characterised by a bloom in spring, with the peak in May. During the summer, phytoplankton abundances gradually decreased until September, then slightly increased again in October and reached their minima in winter. In general, the phytoplankton community was dominated by flagellates (generally <10 µm) and diatoms co-occurring in the spring bloom. In this period, diatoms were also represented by nano-sized species, gradually replaced by larger species in summer and autumn. Phytoplankton assemblages differed significantly between seasons (Pseudo-F = 9.59; p < 0.01) and temperature and salinity were the best predictor variables explaining the distribution of the multivariate data cloud. At the interannual scale, a strong decrease of the late-winter bloom was observed in recent years with the spring bloom being the main phytoplankton increase of the year. [ABSTRACT FROM AUTHOR]

The Canadian Regional Climate Model (CRCM5) Large Ensemble (CRCM5-LE) consists of a dynamically downscaled version of the CanESM2 50-member initial-conditions ensemble (CanESM2-LE). The downscaling was performed at 12-km resolution over two domains, Europe (EU) and northeastern North America (NNA), and the simulations extend from 1950 to 2099, following the RCP8.5 scenario. In terms of validation, warm biases are found over the EU and NNA domains during summer, whereas during winter cold and warm biases appear over EU and NNA, respectively. For precipitation, simulations are generally wetter than the observations but slight dry biases also occur in summer. Climate change projections for 2080–99 (relative to 2000–19) show temperature changes reaching 8°C in summer over some parts of Europe, and exceeding 12°C in northern Québec during winter. For precipitation, central Europe will become much dryer during summer (−2 mm day−1) and wetter during winter (>1.2 mm day−1). Similar changes are observed over NNA, although summer drying is not as prominent. Projected changes in temperature interannual variability were also investigated, generally showing increasing and decreasing variability during summer and winter, respectively. Temperature variability is found to increase by more than 70% in some parts of central Europe during summer and to increase by 80% in the northernmost part of Québec during the month of May as the snow cover becomes subject to high year-to-year variability in the future. Finally, CanESM2-LE and CRCM5-LE are compared with respect to extreme precipitation, showing evidence that the higher resolution of CRCM5-LE allows a more realistic representation of local extremes, especially over coastal and mountainous regions. [ABSTRACT FROM AUTHOR]

According to the sea surface temperature anomaly (SSTA) intensity in the Niño-3.4 region and the east–west gradient across the Pacific, three types of El Niño are identified in this work. An event with larger than average intensity is defined as a strong El Niño, all others are considered to be weak events. Almost all strong El Niños are concurrent with a large gradient, which is featured by negative SSTAs in the western Pacific and positive SSTAs in the equatorial eastern Pacific (EP) and Indian Ocean (IO). According to the east–west gradient, the weak events can be subdivided into gradient-weak (GW) El Niño and equatorial-weak (EW) El Niño. The GW El Niño characterizes a great east–west gradient without a significant IO SSTA. In contrast, the EW event features a positive SSTA over the tropical IO and EP. The impact of GW El Niño on the North Atlantic–Eurasia continent (NA–Eurasia) displays a negative North Atlantic Oscillation (NAO)-like atmospheric anomaly, resulting in a drier and cooler-than-normal winter over Eurasia. Observational and numerical evidence indicate that the prolonged subtropical jet from the North Pacific to NA acts as a waveguide that captures the planetary Rossby waves generated by the GW El Niño. This waveguide favors the propagation of the perturbations into the downstream regions, which would affect the NA–Eurasian climate. However, the EW El Niño is accompanied by a relatively weak subtropical jet that cannot impact the NA–Eurasian climate significantly. For the strong El Niño, the absence of the NAO signal can be attributed to the counteracting of the teleconnections triggered by the Pacific and the tropical IO. [ABSTRACT FROM AUTHOR]

As an essential source of freshwater river flow comprises ~80% of the water consumed in China. Per capita water resources in China are only a quarter of the global average, and its economy is demanding in water resources; this creates an urgent need to quantify the factors that contribute to changes in river flow. Here, we used an offline process-based land surface model (ORCHIDEE) at high spatial resolution (0.1° × 0.1°) to simulate the contributions of climate change, rising atmospheric CO2 concentration, and land-use change to the change in natural river flow for 10 Chinese basins from 1979 to 2015. We found that climate change, especially an increase in precipitation, was responsible for more than 90% of the changes in natural river flow, while the direct effect of rising CO2 concentration and land-use change contributes at most 6.3%. Nevertheless, rising CO2 concentration and land-use change cannot be neglected in most basins as these two factors significantly change transpiration. From 2003 to 2015, the increase in water consumption offset more than 30% of the increase in natural river flow in northern China, especially in the Yellow River basin (~140%), but it had little effect on observed river flow in southern China. Although the uncertainties of rainfall data and the statistical water consumption data could propagate the uncertainties in simulated river flow, this study could be helpful for water planning and management in China under the context of global warming. [ABSTRACT FROM AUTHOR]

Large-scale tracer transport in the upper troposphere and lower stratosphere (UTLS) is investigated using simulations of the Whole Atmosphere Community Climate Model (WACCM) over the period 1955–2099. The analyses are based on e90, an artificial passive tracer with constant emissions and atmospheric loss rates. The separate contributions of advection by the residual circulation, eddy mixing, and subgrid convection to total transport are explicitly evaluated. The results highlight distinct large-scale transport regimes in the tropics, characterized by efficient vertical tracer transport, and the extratropics, dominated by isentropic mixing. One novel result is the important role of vertical eddy mixing in the tropical upper troposphere. It is shown that interannual variability in e90 is largely driven by El Niño–Southern Oscillation and the quasi-biennial oscillation. The long-term trends emphasize a strong impact of a rising tropopause with climate change on UTLS dynamics and tracer transport. The analyses directly attribute the e90 trends to changes in the different transport components. Stronger residual circulation in the future leads to increased tracer concentrations in the tropical lower stratosphere. Enhanced eddy mixing increases e90 in the extratropical lowermost stratosphere, linked to an upward shift of wave dissipation tied to the tropopause rise. In the troposphere, reduced concentrations in the future are due to weaker convective transport out of the boundary layer and weaker extratropical isentropic eddy mixing. [ABSTRACT FROM AUTHOR]

The boreal summer monsoon (BSM), which includes the monsoons over India (IND), the western North Pacific (WNP), East Asia (EA), North America (NAM), and North Africa (NAF), shows prominent interannual variation (IAV) in summer precipitation and affects the areas with the largest populations in the world. In the present, the EOF analysis is used to extract the BSM dominant covariation mode during 1979-2014. This mode is featured by the out-of-phase rainfall IAV over the WNP compared with the other BSM members. The BSM covariation mode is closely associated with the upper- and lower-level coupled circulations, which are characterized by two anomalous zonal circulations over the tropical oceans coupled near the date line and an abnormal meridional cell over the WNP and EA regions, respectively. Furthermore, the strength of this mode depends on the phase relationship of rainfall IAV between the WNP and NAM monsoon regions, which is modulated by the seasonal evolution of ENSO events and the resultant SST anomalies (SSTAs) in the tropical Indian Ocean (TIO). The weaker mode is accompanied by the in-phase rainfall IAV between these two regions, along with the persisting ENSO events and stronger SSTAs in the TIO from winter to summer. In the years with fast-decaying ENSO events and the related weaker TIO SSTA, the out-of-phase rainfall IAV between the WNP and NAMregion takes place to enhance this mode.A series of AGCM sensitivity experiments could reproduce the anomalies of atmospheric circulation related to the distinct seasonal evolution of ENSO events. [ABSTRACT FROM AUTHOR]

Climate variability and its response to increasing greenhouse gases are important considerations for impacts and adaptation. Modeling studies commonly assess projected changes in variability in terms of changes in the variance of climate variables. Despite the distant and impactful covariations that climate variables can exhibit, the covariance response has received much less attention. Here, a novel ensemble framework is developed that facilitates a unified assessment of the response of the regional variances and covariances of a climate variable to imposed external forcings and their time of emergence from an unforced climate state. Illustrating the framework, the response of variability and covariability of land and ocean temperatures is assessed in the Community Earth System Model Large Ensemble under historical and RCP8.5 forcing. The results reveal that land temperature variance emerges from its preindustrial state in the 1950s and, by the end of the twenty-first century, grows to 1.5 times its preindustrial level. Demonstrating the importance of covariances for variability projections, the covariance between land and ocean temperature is considerably enhanced by 2100, reaching 1.4 times its preindustrial estimate. The framework is also applied to assess changes in monthly temperature variability associated with the Arctic region and the Northern Hemisphere midlatitudes. Consistent with previous studies and coinciding with sea ice loss, Arctic temperature variance decreases in most months, emerging from its preindustrial state in the late twentieth century. Overall, these results demonstrate the utility of the framework in enabling a comprehensive assessment of variability and its response to external climate forcings. [ABSTRACT FROM AUTHOR]

Accurate knowledge of the impact of internal atmospheric variability is required for the detection and attribution of climate change and for interpreting glacier records. However, current knowledge of such impacts in high-mountain regions is largely based on statistical methods, as the observational data required for process-based assessments are often spatially or temporally deficient. Using a case study of Kilimanjaro, 12 years of convection-permitting atmospheric modeling are combined with an 8-yr observational record to evaluate the impact of climate oscillations on recent high-altitude atmospheric variability during the short rains (the secondary rain season in the region). The focus is on two modes that have a well-established relationship with precipitation during this season, El Niño--Southern Oscillation and the Indian Ocean zonal mode, and demonstrate their strong association with local and mesoscale conditions at Kilimanjaro. Both oscillations correlate positively with humidity fluctuations, but the association is strongest with the Indian Ocean zonal mode in the air layers near and above the glaciers because of changes in zonal circulation and moisture transport, emphasizing the importance of the moisture signal from this basin. However, it is found the most anomalous conditions during co-occurring positive events because of the combined effects of the (i) extended positive sea surface temperature anomalies, (ii) enhanced atmospheric moisture capacity from higher tropospheric temperatures, (iii) most pronounced weakening of the subsiding branch of the Indian Ocean Walker circulation over East Africa, and (iv) stronger monsoonal moisture fluxes upstream from Kilimanjaro. This study lays the foundation for unraveling the contribution of climate modes to observed changes in Kilimanjaro's glaciers. [ABSTRACT FROM AUTHOR]

In this study, a microwave-based multisatellite merged product released from the European Space Agency's Climate Change Initiative (ESA CCI) and two model-based simulations from the Community Land Model 4.5 (CLM4.5) and Global Land Data Assimilation System (GLDAS) were used to investigate interannual variations and trends of soil moisture in China between 1979 and 2010. They were also evaluated using in situ observations from the nationwide agrometeorological network. These three datasets show consistent drying trends for surface soil moisture in northeastern and central China, as well the eastern portion of Inner Mongolia, and wetting trends in the Tibetan Plateau, which are also identified by in situ observations. Trends in the root-zone soil moisture are in line with those of surface soil moisture seen in the CLM4.5 and GLDAS simulations obtained from most areas in China (78%-88%), except for northwestern China and southwest of the Tibetan Plateau. Moreover, the drying trend intensifies with increasing soil depth. Taking the in situ measurements as reference, it is found that ESA CCI has better accuracy in identifying the significant drying trends while CLM4.5 and GLDAS capture wetting trends better. Compared to temperature, precipitation is the primary factor responsible for these trends, which controls the direction of soil moisture changes, while increasing temperatures can also enhance soil drying during periods of decreased precipitation. [ABSTRACT FROM AUTHOR]

Work published in 2012 revealed that annual minimum temperatures over the coterminous United States (USA) have increased faster than mean temperatures, causing a pronounced poleward shift in the positions of hardiness zones defined by the expected annual minimum temperature. Here, estimates of increases in annual minimum temperatures are updated and extended to other land areas where station temperature records are available. Annual minimum temperatures have increased faster than mean temperatures in seasonally cold regions globally, but have warmed at about the same rate as mean temperatures in tropical climates. The mean increase in annual minimum temperature across the available weather stations was 2.0 °C between 1970 and 2016 (or almost 0.5 °C per decade), as compared to an increase of 1.2 °C in mean temperature. Recent cold winters in regions such as Eastern North America did not clearly break with this trend and were within the range of variability seen in past decades. Overall, annual minimum temperatures appear to be increasing steadily, though with considerable inter-annual variability. [ABSTRACT FROM AUTHOR]

Climate change and its potential threats on water security call for reliable predictions of evapotranspiration (ET) and runoff Q at different time scales, but current knowledge of the differences in their predictability between humid and nonhumid regions is limited.Based on spatially distributed catchments inChina, the authors characterized their predictability and provided plausible explanations. Using the Budyko framework, it was confirmed that annualET is predictable in nonhumid regions but less predictable in humid regions, and annualQ is predictable in humid regions but less reliable in nonhumid regions. Themain cause of the varied predictability lies in the variation of water storage change DS in the water balance equation. It affects both the estimation and the variability ofQin nonhumid catchmentsmore than that in humid catchments, which increases the challenge of predicting annual Q in nonhumid regions, while the opposite effect occurs in annual ET prediction between humid and nonhumid catchments.Moreover, the differences between the controlling factors of ET variability in different regions add more differences in their predictability. The dominant control of precipitation makes it easy to predict annual ET in nonhumid regions. By contrast, precipitation, potential evaporation, and their covariance take considerable effort to determine annualETvariations,which leads to less reliableETestimation and predictability in humid catchments. Therefore, one can accurately predict annual ET in nonhumid catchments andQ in humid catchments based on commonly used hydrological models.With proper consideration of ΔS, the predictability of annual ET and Q in both humid and nonhumid catchments can be improved. [ABSTRACT FROM AUTHOR]