Major Climate Modes Research Articles

Intraseasonal Variations and Extreme Occurrence in the Local Sea Level Along the Western Coast of India Remotely Controlled by a Basin‐Scale Climate Variability

AbstractThe equatorial Kelvin waves, remotely excited by basin‐scale climate modes, and subsequent coastal trapped waves significantly influence the intraseasonal variations, their low‐frequency modulations, and the frequency of extreme sea level events along the western coast of India. This study demonstrates that the frequency of extreme events are linked to the phase of the Indian Ocean Dipole mode. The temporal changes in the occurrence frequency of extremes are simulated in an eddy‐resolving ocean model consistently with observations. However, a non‐eddying model significantly underestimate the occurrence frequency of extreme sea level events, suggesting the importance of coastal trapped wave propagations regulated by the horizontal scale with the Rossby radius of deformation. This result implies that many state‐of‐the‐art climate models with a one‐degree ocean horizontal resolution may underestimate future coastal sea level variability and the frequency of extreme events under global warming and potential modulations of major internal climate modes.

Characterising continental shelf waves and their drivers for the southeast coast of Australia

Low-lying, developed areas in New South Wales (NSW) are susceptible to extended periods of inundation, which cannot be attributed to tides or local synoptic conditions. This inundation is often associated with relatively small water level anomalies but is persistent enough to damage the built environment. Due to their long duration, continental shelf waves (CSWs) are one of the mechanisms of concern associated with extended coastal inundation. These waves are caused by a range of synoptic disturbances occurring along the mid-latitudes and they travel anticlockwise along the coast (in the southern hemisphere), reaching low latitudes of NSW. This study investigates the characteristics of CSWs that travel along the NSW coast, their generation and propagation mechanisms in relation to local synoptic and oceanic conditions, and their potential modulation by two major large-scale climate modes: the El Niño/Southern Oscillation and the Southern Annular Mode (SAM). We used time series of daily tidal residuals from 1994 to 2015 from nine locations along the NSW coast and used a peak over threshold approach to identify 29 waves which had an average amplitude of 0.3 m, mean period of 15 days (ranging from 8 to 20 days), and a highest occurrence in autumn and winter. The generation of CSWs is tightly coupled to the subpolar jet, the belt of westerlies, and the subtropical ridge, confirming that large-scale atmospheric circulation is a key element in the generation and propagation of CSWs. Through analyses of the inverse barometer, we found that CSWs propagate freely up to the north coast of NSW, independent of local weather conditions. We also found that CSWs are more frequent during the positive phase of SAM combined with La Niña and during neutral SAM combined with El Niño events. This study provides the longest database to date of CSWs for NSW, alongside new insights into their characteristics and timing and frequency of occurrence. Importantly, this information can be used to monitor their occurrence and forecast their impact, including the number of days taken for a wave to reach different locations along the NSW coast.

Quantifying the contribution of atmospheric circulation to precipitation variability and changes in the US Great Plains and southwest using self-organizing map–analogue

Abstract. The Great Plains and southwest regions of the US are highly vulnerable to precipitation-related climate disasters such as droughts and floods. In this study, we propose a self-organizing map–analogue (SOMA) approach to empirically quantify the contribution of atmospheric moist circulation (mid-tropospheric geopotential and column moisture transport) to the regional precipitation anomalies, variability, and multi-decadal changes. Our results indicate that moist circulation contributes significantly to short-term precipitation variability, accounting for 54 %–61 % of the total variance in these regions, though these contributions vary significantly across seasons. As indicated in previous research, Pacific Decadal Oscillation (PDO) is one of the major climate modes influencing the long-term multi-decadal variation in precipitation. By contrasting three multi-decadal periods (1950–1976, 1977–1998, 1999–2021) with shifting PDO phases and linking the phase shift to self-organizing map (SOM) nodes, we found that circulation changes contribute considerably to the multi-decadal changes in precipitation anomaly in terms of the mean and days of dry and wet extremes, especially for the southern Great Plains (GP) and southwest. However, these circulation-induced changes are not totally related to the PDO phase shift (mostly less than half) since internal variability or anthropogenically induced changes in circulation can also be potential contributors. Our approach improves upon flow analogue and SOM-based methods and provides insights into the contribution of atmospheric circulation to regional precipitation anomalies and variability.

Influence of climate variability modes over wind-sea and swell generated wave energy

Wave energy is one of the cleanest renewable sources of energy generated through the motion of wind-sea and swell waves. This study examines the influence of different climate variability modes over global wave energy generated from wind-sea (PW) and swell waves (PS) during 1950–2021 using the ERA5 reanalysis dataset. The major climate modes, such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Southern Annular Mode (SAM) are considered during four boreal seasons. Wave energy extremes are determined using a non-stationary generalized extreme value analysis. The significant positive influence of ENSO on mean and extreme PS is evident over the northeast and central Pacific Ocean (PO) during December–February (DJF), and weakens during March–May (MAM). The strongest NAO response to PW and PS is evident during DJF as a tripolar and dipolar pattern over the north Atlantic Ocean, respectively. Further, PW responses due to IOD include significant increases over the Bay of Bengal and eastern Indian Ocean (IO) during JJA, which extend towards the central IO during SON. Lastly, SAM influence over PW occurs as a dipole pattern in the Southern Ocean (SO), i.e., positive anomalies in between 55°S and 65°S and negative anomalies in between 30°S and 55°S.

Climate influence on compound solar and wind droughts in Australia

Solar photovoltaic and wind power are central to Australia’s renewable energy future, implying an energy sector vulnerable to weather and climate variability. Alignment of weather systems and the influence of large-scale climate modes of variability risks widespread reductions in solar and wind resources, and could induce grid-wide impacts. We therefore systematically analyse the relationship between compound solar radiation and wind speed droughts with weather systems and climate modes of variability over multiple time scales. We find that compound solar and wind droughts occur most frequently in winter, affecting at least five significant energy-producing regions simultaneously on 10% of days. The associated weather systems vary by season and by drought type, although widespread cloud cover and anticyclonic circulation patterns are common features. Indices of major climate modes are not strong predictors of grid-wide droughts, and are typically within one standard deviation of the mean during seasons with the most widespread events. However, the spatial imprints of the teleconnections display strong regional variations, with drought frequencies varying by more than ten days per season between positive and negative phases of climate modes in some regions. The spatial variability of these teleconnection patterns suggests that droughts in one region may be offset by increased resource in another. Our work highlights the opportunity for minimising the impact of energy production variability by utilising weather and climate intelligence. Exploiting the spatial variability associated with daily weather systems and the seasonal influence of climate modes could help build a more climate-resilient renewables-dominated energy system.

Attribution and Causality Analyses of Regional Climate Variability

A two-step attribution and causality diagnostic is designed by employing singular spectrum analysis to unfold the attributed climate time series into a trajectory matrix and then subjected to an empirical orthogonal function analysis to identify the evolving driving forces, which can finally be related to major climate modes through their independent frequencies by wavelet analysis. Application results from the arid and drought-prone southern Intermountain region of North America are compared with the climate or larger scale forcing diagnosed from slow feature analysis using the sources of the water and energy flux balance. The following results are noted: (i) The changes between the subsequent four 20-year periods from 1930 to 2010 suggest predominantly climate-induced forcing by the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. (ii) Land cover influences on the changing land cover are of considerably smaller magnitude (in terms of area percentage cover) whose time evolution is well documented from forestation documents. (iii) The drivers of the climate-induced forcings within the last 20 years are identified as the quasi-biennial oscillation and the El Niño–Southern Oscillation by both the inter-annual two-step attribution and the causality diagnostics with monthly scale-based slow feature analysis.

Natural decadal variability of global vegetation growth in relation to major decadal climate modes

The ongoing climate change can modulate the behavior of global vegetation and influence the terrestrial biosphere carbon sink. Past observation-based studies have mainly focused on the linear trend or interannual variability of the vegetation greenness, but could not explicitly deal with the effect of natural decadal variability due to the short length of observations. Here we put the variabilities revealed by remote sensing-based global leaf area index (LAI) from 1982 to 2015 into a long-term perspective with the help of ensemble Earth system model simulations of the historical period 1850–2014, with a focus on the low-frequency variability in the global LAI during the growing season. Robust decadal variability in the observed and modelled LAI was revealed across global terrestrial ecosystems, and it became stronger toward higher latitudes, accounting for over 50% of the total variability north of 40°N. The linkage of LAI decadal variability to major natural decadal climate modes, such as the El Niño–Southern Oscillation decadal variability (ENSO-d), the Pacific decadal oscillation (PDO), and the Atlantic multidecadal oscillation (AMO), was analyzed. ENSO-d affects LAI by altering precipitation over large parts of tropical land. The PDO exerts opposite impacts on LAI in the tropics and extra-tropics due to the compensation between the effects of temperature and growing season length. The AMO effects are mainly associated with anomalous precipitation in North America and Europe but are mixed with long-term climate change impacts due to the coincident phase shift of the AMO which also induces North Atlantic basin warming. Our results suggest that the natural decadal variability of LAI can be largely explained by these decadal climate modes (on average 20% of the variance, comparable to linear changes, and over 40% in some ecosystems) which also can be potentially important in inducing the greening of the Earth of the past decades.

Characteristics and Drivers of Marine Heatwaves in the Western Equatorial Indian Ocean

AbstractThe spatio‐temporal characteristics of the interannual variability and long‐term trend of the marine heatwaves (MHWs) and related dynamic mechanisms in the western equatorial Indian Ocean (WEIO) are investigated using satellite observations. A prominent MHW hot spot is found in a region of the WEIO (48°E−54°E, 2°S–2°N), with a mean MHWs' intensity, duration, and frequency of 1.54°C, 13.33 days, and 1.97 times, respectively. MHWs in the hot spot region have significant interannual variability after removing the long‐term trend, associated with Indo‐Pacific major climate modes. In 1982/1983, 1983/1984, 1987/1988, 1997/1998, 2006/2007, 2009/2010, 2011/2012, 2012/2013, 2014/2015, 2015/2016, and 2019/2020, the MHWs occurred with longer duration, higher frequency, and more total days. These years correspond to a positive Indian Ocean Dipole, or an El Niño event, or both. The occurrence of MHWs accompanied by anomalous positive sea surface height suggests that oceanic planetary wave processes modulate MHWs in the WEIO. Westward‐propagating downwelling equatorial Rossby waves triggered by anomalous equatorial easterly winds drive the convergence of warm upper‐ocean water and weaken the upwelling of cool subsurface water, which favor anomalously warm sea surface temperature (SST) and the occurrence of MHWs. In addition, the westward‐propagating off‐equatorial downwelling Rossby waves in the southern tropical Indian Ocean also affect MHWs in the WEIO through the propagation and reflection of waves. The annual MHW frequency, duration, and total days in the hot spot region increase up to 1.56 times, 4.95 days, and 31.72 days per decade, respectively, related to the significant increase in mean SST under global warming.

Improved Simulations of Atmospheric River Climatology and Variability in High‐Resolution CESM

AbstractAtmospheric 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.

Evidence and Implications of Hydrological and Climatic Change in the Reno and Lamone River Basins and Related Coastal Areas (Emilia-Romagna, Northern Italy) over the Last Century

Climate change and human activities have consequences on coastal areas as they affect hydrological processes in the related river basins. The riverine sediment supply to the beaches of the Emilia-Romagna coast, a highly urbanized area with high economic and naturalistic value, has been heavily impacted by human activities throughout the catchment, reducing solid transport to the coast and increasing the threat of coastal erosion and flooding. Despite the introduction of safeguard policies in the early 1980s and the consequent stoppage of such activities, the expected return in solid transport has not yet been reflected at the coast. To better understand the various processes acting at the river basin scale, we utilized empirical mode decomposition to analyze the variability in different parameters (river discharge, rainfall, air temperature, and sea level) from the headwaters to the coast of the Reno and Lamone rivers over the last century. The anthropogenic footprint, linked to the large-scale dimming/brightening phenomenon, is visible in the long-term trends. Moreover, natural signals with variable periodicity are evident and partially correlated with two major climate modes (North Atlantic Oscillation and Atlantic Multidecadal Oscillation). The coupled interactions among these processes, combined with the changes in land use and evapotranspiration during the last century, have resulted in the prolonged scarcity of river sediment supply and a long-term trend of erosion of the coastal area.

Drivers of Coral Reconstructed Salinity in the South China Sea and Maritime Continent: The Influence of the 1976 Indo‐Pacific Climate Shift

AbstractThe flow of Pacific water into the Indian Ocean via the South China Sea (SCS) and Maritime Continent (MC) plays an important role in the ocean thermohaline circulation providing the only low‐latitude pathway for the inter‐ocean exchange of heat and salt. The transport of the SCS and Indonesian throughflows is modulated by the East Asian monsoon and major climate modes associated with the Pacific and Indian Oceans. As an indicator of surface layer buoyancy, sea surface salinity (SSS) is critical to rates of exchange but instrumental records of SSS are short and sparse. Using empirical orthogonal functions, a synthesis of proxy‐based reconstructions of SSS from coral δ18O is used to study the role of climate variability on long‐term SSS behavior in the region. The leading mode of SSS variability in the boreal winter and summer responds to the influence of the 1976 Indo‐Pacific climate shift. At multi‐decadal timescales, only the East Asian monsoon and the Indian Ocean Dipole (IOD) retain their signal in winter and summer SSS after 1976. At higher frequencies, winter SSS shifts from having a strong East Asian monsoon signal to a more dominant impact of the IOD and the El Niño Southern Oscillation (ENSO) following the shift. In the summer, only a change in ENSO's influence on SSS variability is observed after 1976. The recent intensification and dominance of the IOD and ENSO in driving SSS variability in the SCS and MC may influence circulation in the regional throughflows and perhaps global thermohaline circulation.

The North Atlantic Oscillations: Lead–Lag Relations for the NAO, the AMO, and the AMOC—A High-Resolution Lead–lag Analysis

Several studies examine cycle periods and the interactions between the three major climate modes over the North Atlantic, namely the Atlantic meridional overturning circulation (AMOC), the Atlantic multidecadal oscillation (AMO), and the North Atlantic oscillation (NAO). Here, we use a relatively novel high-resolution Lead–lag (LL) method to identify short time windows with persistent LL relations in the three series during the period from 1947 to 2020. We find that there are roughly 20-year time windows where LL relations change direction at both interannual, high-frequency and multidecadal, low-frequency timescales. However, with varying LL strength, the AMO leads AMOC for the full period at the interannual timescale. During the period from 1980 to 2000, we had the sequence NAO→AMO→AMOC→NAO at the interannual timescale. For the full period in the decadal time scale, we obtain NAO→AMO→AMOC. The Ekman variability closely follows the NAO variability. Both single time series and the LL relation between pairs of series show pseudo-oscillating patterns with cycle periods of about 20 years. We list possible mechanisms that contribute to the cyclic behavior, but no conclusive evidence has yet been found.

Analysis of the interannual variability in satellite gravity solutions: detection of climate modes fingerprints in water mass displacements across continents and oceans

This study analyzes the interannual variability of the water mass transport measured by satellite gravity missions in regard to eight major climate modes known to influence the Earth’s climate from regional to global scales. Using sparsity promoting techniques (i.e., LASSO), we automatically select the most relevant predictors of the climate variability among the eight candidates considered. The El Niño–Southern Oscillation, Southern Annular Mode and Arctic Oscillation are shown to account for a large part the interannual variability of the water mass transport observed in extratropical ocean basins (up to 40%) and shallow seas (up to 70%). A combination of three Pacific and one Atlantic modes is needed to account for most (up to 60%) of the interannual variability of the terrestrial water storage observed in the North Amazon, Parana and Zambezi basins. With our technique, the impact of climate modes on water mass changes can be tracked across distinct water reservoirs (oceans, continents and ice-covered regions) and we show that a combination of climate modes is necessary to explain at best the natural variability in water mass transport. The climate modes predictions based on LASSO inversions can be used to reduce the inter-annual variability in satellite gravity measurements and detect processes unrelated with the natural variability of climate but with similar spatio-temporal signatures. However, significant residuals in the satellite gravity measurements remain unexplained at inter-annual time scales and more complex models solving the water mass balance should be employed to better predict the variability of water mass distributions.

Projected response of global runoff to El Niño-Southern oscillation

The El Niño-Southern Oscillation (ENSO) is a major mode of interannual climate variability and is expected to affect runoff variations at a global scale. While previous studies focused on the correlation analysis between ENSO and runoff and ENSO-induced amplitude changes of runoff, causal analysis considering the confounding impacts of other major climate modes is lacking. As more extreme ENSO events are projected in the future, it is crucial to enhance our understanding of the impacts of ENSO on global runoff. Here we examine the causal influences of ENSO on runoff over the future period 2015–2100 using outputs from Coupled Modeling Intercomparison Project Phase 6 model simulations. Our analyses account for the possible confounding effects of the Southern Annular Mode, the North Atlantic Oscillation and the Indian Ocean Dipole. We find that the signature of ENSO is detectable in future total runoff over various regions including limited areas in central and eastern Asia, large parts of Southeast Asia, limited areas in the eastern and southern Africa, western and eastern Australia, parts of southern and western North America, eastern Antarctica and large parts of South America. There is a high agreement across models for the causal influences of ENSO over central Asia, the eastern coast of Australia, southcentral North America and South America. Multi-model future projections demonstrate higher impacts of ENSO on total runoff over western and central Asia, the western coast of North America and southeastern South America compared to the historical period 1915–2000. All regions with substantial ENSO impacts account for 3.6% land-area in historical simulation and this fraction increases to 5.6% in the future scenario. In addition, the results underscore that surface runoff is less sensitive to ENSO compared to total runoff in most regions. These results may have implications for future water management planning based on ENSO.

Global Within-Season Yield Anomaly Prediction for Major Crops Derived Using Seasonal Forecasts of Large-Scale Climate Indices and Regional Temperature and Precipitation

AbstractWeather and climate variability associated with major climate modes is a main driver of interannual yield variability of commodity crops in global cropland areas. A global crop forecasting service that is currently in the test operation phase is based on temperature and precipitation forecasts, while recent literature suggests that crop forecasting services may benefit from the use of climate index forecasts. However, no consistent comparison is available on prediction skill between yield models relying on forecasts from temperature and precipitation and from climate indices. Here, we present a global assessment of 26-yr (1983–2008) within-season yield anomaly hindcasts for maize, rice, wheat, and soybean derived using different types of statistical yield models. One type of model utilizes temperature and precipitation for individual cropping areas (the TP model type) to represent the current service, whereas the other type relies on large-scale climate indices (the CI model). For the TP models, three specifications with different model complexities are compared. The results show that the CI model is characterized by a small reduction in the skillful area from the reanalysis model to the hindcast model and shows the largest skillful areas for rice and soybean. In the TP models, the skill of the simple model is comparable to that of the more complex models. Our findings suggest that the use of climate index forecasts for global crop forecasting services in addition to temperature and precipitation forecasts likely increases the total number of crops and countries where skillful yield anomaly prediction is feasible.

Oxygen Isotopic Signatures of Major Climate Modes and Implications for Detectability in Speleothems

AbstractNatural and social systems worldwide are impacted by climate modes such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO), making it imperative to understand their sensitivity to climate change. Paleoclimate studies extend the observational climate baseline, and speleothem records (δ18Ospel) are a common data source. However, relationships between δ18Ospel and climate modes are uncertain; climate models provide a way to test the strength and stability of these relationships. Here, we use the isotope‐enabled Community Earth System Model's Last Millennium Ensemble combined with a forward proxy model to delineate the global expression of modal variability in “pseudo‐stalagmite” (δ18Ospel) records worldwide. The modeled δ18Ospel spatially correlates with modal signatures. However, substantial changes in modal variance only modestly affect individual δ18Ospel variance. A network of δ18Ospel records, particularly one that straddles the Pacific, significantly improves the reconstructability of ENSO variance.

On the interconnections among major climate modes and their common driving factors

Abstract. The variations in oceanic and atmospheric modes on various timescales play important roles in generating global and regional climate variability. Many efforts have been devoted to identifying the relationships between the variations in climate modes and regional climate variability, but these have rarely explored the interconnections among these climate modes. Here we use climate indices to represent the variations in major climate modes and examine the harmonic relationship among the driving forces of climate modes using slow feature analysis (SFA) and wavelet analysis. We find that all of the significant peak periods of driving-force signals in the climate indices can be represented as harmonics of four base periods: 2.32, 3.90, 6.55, and 11.02 years. We infer that the period of 2.32 years is associated with the signal of the quasi-biennial oscillation (QBO). The periods of 3.90 and 6.55 years are linked to the intrinsic variability of the El Niño–Southern Oscillation (ENSO), and the period of 11.02 years arises from the sunspot cycle. Results suggest that the base periods and their harmonic oscillations related to QBO, ENSO, and solar activities act as key connections among the climatic modes with synchronous behaviors, highlighting the important roles of these three oscillations in the variability of the Earth's climate. Highlights. i. The harmonic relationship among the driving forces of climate modes was investigated by using slow feature analysis and wavelet analysis.ii. All of the significant peak periods of driving-force signals in climate indices can be represented as the harmonics of four base periods.iii. The four base periods related to QBO, ENSO, and solar activities act as the key linkages among different climatic modes with synchronous behaviors.

Wintertime Arctic Oscillation and North Atlantic Oscillation and their impacts on the Northern Hemisphere climate in E3SM

The characteristics of the wintertime Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) and their impacts on climate variability over the Northern Hemisphere are important metrics for evaluating a climate system model. Observational analyses reveal that the horizontal and vertical structures in the AO and NAO exhibit a meridional dipole and a large-scale barotropic pattern between the Arctic and mid-latitudes. Historical model simulations from the Energy Exascale Earth System Model (E3SM-HIST) are used to identify how well it captures these major climate modes. It is found that the simulated AO and NAO modes have spatial structures similar to the observed features. In addition, the observed frequency bands in the AO and NAO-related time variability are captured well in the E3SM-HIST simulation. Associated with the positive phase in wintertime AO and NAO, zonal flow and warm advection in mid-latitude continents are enhanced, along with stronger cold flow from enhanced northerly winds over high latitudes. These features are linked to the atmospheric circulation pattern reflected by lower SLP anomalies over the Arctic and higher SLP anomalies over the mid‐latitudes. In E3SM-HIST, these spatial associations and main structural features are analogous to those in observations. In the time-height evolution related to winter AO and NAO modes, it can also be seen that the simulations reproduce the downward propagating patterns in observations. Nevertheless, the vertical structures associated with AO and NAO in E3SM-HIST exhibit substantial biases in the lower stratosphere. The cause of these stratospheric biases is investigated using the strength of climatological stratospheric polar vortex (SPV) and wave activity fluxes. The results herein suggest that E3SM-HIST has a reasonable skill in reproducing the observed characteristics related to the winter AO and NAO, although there exist systematic biases in the associated climate variability.

Relations between Interannual Variability of Regional-Scale Indonesian Precipitation and Large-Scale Climate Modes during 1960–2007

AbstractRegional-scale precipitation responses over Indonesia to major climate modes in the tropical Indo–Pacific Oceans, namely canonical El Niño, El Niño Modoki, and the Indian Ocean dipole (IOD), and how the responses are related to large-scale moisture convergences are investigated. The precipitation responses, analyzed using a high-spatial-resolution (0.5° × 0.5°) terrestrial precipitation dataset for the period 1960–2007, exhibit differences between the dry (July–September) and wet (November–April) seasons. Canonical El Niño strongly reduces precipitation in central to eastern Indonesia from the dry season to the early wet season and northern Indonesia in the wet season. El Niño Modoki also reduces precipitation in central to eastern Indonesia during the dry season, but conversely increases precipitation in western Indonesia in the wet season. Moisture flux analysis indicates that corresponding to the dry (wet) season precipitation reduction due to the canonical El Niño and El Niño Modoki anomalous divergence occurs around the southern (northern) edge of the convergence zone when one of the two edges is located near the equator (10°S–15°N) associated with their seasonal migration. This largely explains the seasonality and regionality of precipitation responses to canonical El Niño and El Niño Modoki. IOD reduces precipitation in southwestern Indonesia in the dry season, associated with anomalous moisture flux divergence. The seasonality of precipitation response to IOD is likely to be controlled by the seasonality of local sea surface temperature anomalies in the eastern pole of the IOD.

Response of global evaporation to major climate modes in historical and future Coupled Model Intercomparison Project Phase 5 simulations

Abstract. Climate extremes, such as floods and droughts, might have severe economic and societal impacts. Given the high costs associated with these events, developing early-warning systems is of high priority. Evaporation, which is driven by around 50 % of solar energy absorbed at surface of the Earth, is an important indicator of the global water budget, monsoon precipitation, drought monitoring and the hydrological cycle. Here we investigate the response of global evaporation to main modes of interannual climate variability, including the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO) and the El Niño–Southern Oscillation (ENSO). These climate modes may have an influence on temperature, precipitation, soil moisture and wind speed and are likely to have impacts on global evaporation. We utilized data of historical simulations and RCP8.5 (representative concentration pathway) future simulations derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results indicate that ENSO is an important driver of evaporation for many regions, especially the tropical Pacific. The significant IOD influence on evaporation is limited in western tropical Indian Ocean, while NAO is more likely to have impacts on evaporation of the North Atlantic European areas. There is high agreement between models in simulating the effects of climate modes on evaporation of these regions. Land evaporation is found to be less sensitive to considered climate modes compared to oceanic evaporation. The spatial influence of major climate modes on global evaporation is slightly more significant for NAO and the IOD and slightly less significant for ENSO in the 1906–2000 period compared to the 2006–2100 period. This study allows us to obtain insight about the predictability of evaporation and hence, may improve the early-warning systems of climate extremes and water resource management.