Empirical Subseasonal Prediction of Summer Rainfall Anomalies over the Middle and Lower Reaches of the Yangtze River Basin Based on Atmospheric Intraseasonal Oscillation

The Pacific meridional mode (PMM) can modulate El Niño–Southern Oscillation (ENSO) and is also affected by ENSO-related tropical Pacific sea surface temperature anomalies (SSTAs). Two tropical feedbacks on the PMM have been proposed: a positive one of central tropical Pacific SSTAs and a negative one of eastern tropical Pacific (ETP) SSTAs, the latter of which is suggested to be active only during strong eastern Pacific (EP) El Niño events like those in 1982/83 and 1997/98. However, we find that no strong, negative PMM-like SSTAs appeared, although the PMM indices (PMMIs) were strongly negative in spring of 1983 and 1998. Observation and model experiments show that tropical warming in 1983 and 1998 not only occurred in the ETP but also extended to the date line, thus inducing wind anomalies unfavorable for establishing the wind–evaporation–SST feedback for a negative PMM in the subtropics. To understand the discrepancy between the large negative PMMIs and weak PMM-related subtropical cooling during strong EP El Niño events, we isolate the relative contributions of subtropical and tropical SSTAs to the PMMIs by calculating their spatial projections on the PMM. Analysis combined using observation and CMIP6 models shows that despite the large contribution from subtropical SSTAs, the large tropical SSTAs, especially the extreme ETP warming, could cause large negative PMMIs during strong EP El Niño events even without strong, negative subtropical SSTAs. Our study clarifies the impact of ETP warming in causing a negative PMM and indicates the overstatement of negative PMMIs by tropical SSTAs during strong EP El Niño events. Significance Statement This paper aims to reevaluate the previously proposed effect of strong eastern Pacific El Niño events, like those in 1982/83 and 1997/98, on exciting a negative Pacific meridional mode (PMM). We find that although the PMM indices were strongly negative during the decay of strong eastern Pacific El Niño events, the large negative PMM sea surface temperature anomalies (SSTAs) could not be observed in the subtropical Pacific. Further diagnosis indicates that the PMM index can be large if strong SSTAs occur in eastern tropical Pacific even without subtropical SSTAs, implying that one should be careful when using the PMM index.

Relationship between Meridional Displacement of the Monthly East Asian Jet Stream in the Summer and Sea Surface Temperature in the Tropical Central and Eastern Pacific

A gridded daily rainfall dataset prepared from observations at 3700 stations is used to analyze the intraseasonal and interannual variability of the summer monsoon rainfall over India. It is found that the major drought years are characterized by large-scale negative rainfall anomalies covering nearly all of India and persisting for the entire monsoon season. The intraseasonal variability of rainfall during a monsoon season is characterized by the occurrence of active and break phases. During the active phase, the rainfall is above normal over central India and below normal over northern India (foothills of the Himalaya) and southern India. This pattern is reversed during the break phase. It is found that the nature of the intraseasonal variability is not different during the years of major droughts or major floods. This suggests that a simple conceptual model to explain the interannual variability of the Indian monsoon rainfall should consist of a linear combination of a large-scale persistent s...

Rwanda is a landlocked country in central-eastern Africa. As a country highly dependent on rain-fed agriculture, Rwanda is vulnerable to rainfall variability. Observational data show that there are two rainy seasons in Rwanda, i.e., the long rainy season and the short rainy season. This study mainly focuses on the dominant intraseasonal rainfall mode during the long rainy season (February–May), and evaluates the forecast skill for the intraseasonal variability (ISV) over Rwanda and its surrounding regions in a state-of-the-art dynamic model. During the long rainy season, observational results reveal that the dominant intraseasonal rainfall mode in Rwanda exhibits a significant variability on the 10–25-day time scale. One-point-correlation analysis further unveils that the 10–25-day intraseasonal rainfall variability in Rwanda co-varies with that in its adjacent areas, indicating that the overall 10–25-day rainfall variability in Rwanda and its adjacent regions (8°S–3°N, 29°–37°E) should be considered collectively when studying the dominant intraseasonal rainfall variability in Rwanda. Composite results show that the development of the 10–25-day rainfall variability is associated with the anomalous westerly wind in Rwanda and its surrounding regions, which may trace back to a pair of westward-propagating equatorial Rossby waves. Based on the observational findings, an ISO_rainfall_index and an ISO_wind_index are proposed for quantitatively evaluating the forecast skill. The ECMWF model has a comparable skill in predicting the wind index and the rainfall index, with both indices showing a skill of 18 days.摘要非洲中东部地区的经济主要依靠自给农业支撑, 该地区农业经济对降水的变化尤为敏感. 本文以卢旺达为例, 观测分析指出卢旺达的次季节降雨主要集中在10–25天; 根据次季节尺度降水变率的单点相关方法, 发现卢旺达的次季节降水变率和周围区域变化一致; 进一步合成结果显示该地区次季节降水变率与异常西风有关, 这可追溯到赤道地区西传的赤道Rossby波. 最后, 本文评估了当前动力模式ECMWF对卢旺达地区(即非洲中东部)次季节降水变率的预报能力, 发现EC模式在对该区域降水和相关风场指数的预报技巧都在18天左右, 且预报技巧表现出一定的年际差异, 这可能与热带太平洋的背景海温信号有关. 该工作增进了当前对非洲中东部地区的次季节降水变率和预测水平的认知, 并且对该地区国家粮食安全和防灾减灾具有启示性意义.

Intraseasonal variability of rainfall over the Indian subcontinent (IS) and the Tibetan Plateau (TP) has been discussed widely but often separately. In this study, we investigate the covariability of rainfall across the IS and the TP on intraseasonal time scales and its impact on interannual variability of regional rainfall. The most dominant mode of rainfall intraseasonal variability across the region features a dipole pattern with significant out-of-phase rainfall anomalies between the southeastern TP and the central and northern IS. This dipole rainfall pattern is associated with intraseasonal oscillations (ISOs) of 10–20 days and 30–60 days, especially the latter. An active spell of rainfall in the central and northern IS (southeastern TP) is associated with the strengthening (northward shift) of water vapor transport of the Indian summer monsoon, resulting in more water vapor entering into the central and northern IS (southeastern TP) and thus more rainfall. The 10–20-day ISO of the dipole rainfall pattern is caused by the 10–20-day atmospheric ISO in both the tropics and the extratropics, whereas the 30–60-day ISO of the dipole rainfall pattern is only associated with atmospheric ISO in the tropics. The dipole rainfall pattern resembles the most dominant mode of interannual variability of July–August mean rainfall. The 30–60-day ISO of the dipole rainfall pattern has an important contribution to the dipole pattern of July–August mean rainfall anomalies on an interannual time scale due to the different frequencies of occurrence of the active and break phases.

This study evaluates the ability of the Coupled Model Intercomparison Project phase 6 (CMIP6) climate models to simulate the observed effects of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) on Indian summer monsoon rainfall (ISMR) variability. Using observational data and the large ensemble historical simulations of seven CMIP6 models from 1950 to 2014, we applied a cyclostationary linear inverse model (CS-LIM) to isolate the impacts of tropical Pacific SSTAs, Indian Ocean SSTAs, and their interaction on the interannual variability of ISMR. Overall, these CMIP6 models well reproduced the observed enhanced (reduced) ISMR variability from Pacific SSTAs (Indian Ocean SSTAs and the Indo-Pacific interaction), though with varying spatial patterns and magnitudes. Among them, CESM2 and Energy Exascale Earth System Model version 2.0 (E3SM-2-0) showed the best agreement with observations for the effects of Pacific SSTAs and the Indo-Pacific interaction, respectively. Composite analysis of ISMR anomalies during the developing phases of pure and co-occurring El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events revealed that the impacts from Pacific SSTAs were captured reasonably well by E3SM-2-0, CESM2, MIROC6, and MPI-ESM1-2-LR, while E3SM-2-0 also showed the best agreement with observations for the effects from the Indo-Pacific interaction. However, all seven models exhibited substantial biases in simulating the Indian Ocean SSTA impacts on ISMR, particularly during pure El Niño events. Overall, this study provides new insights into how individual CMIP6 models simulate the isolated impacts from the tropical Pacific and Indian Oceans, which have important applications for improving ISMR predictions and interpreting ISMR future projections.

Low-frequency sea level variations with periods longer than interannual time scales have been receiving much attention recently, with the aim of distinguishing the anthropogenic regional sea level change signal from the natural fluctuations. Based on the available sea level products, this study finds that the dominant low-frequency sea level mode in the Pacific basin has both quasi-decadal variations and a multidecadal trend reversal in the early 1990s. The dominant sea level modes on these two time scales have different tropical structures: a west–east seesaw in the tropical Pacific on the multidecadal time scale and a dipole between the western and central tropical Pacific on the quasi-decadal time scale. These two sea level modes in the Pacific basin are closely related to the ENSO-like low-frequency climate variability on respective time scales but feature distinct surface wind forcing patterns and subbasin climate processes. The multidecadal sea level mode is associated with the Pacific decadal oscillation (PDO) and Aleutian low variations in the North Pacific and tropical Pacific sea surface temperature anomalies toward the eastern basin, while the quasi-decadal sea level mode is accompanied by tropical Pacific sea surface temperature anomalies centered in the central basin along with the North Pacific part, which resembles the North Pacific Oscillation (NPO) and its oceanic expressions [i.e., the North Pacific Gyre Oscillation (NPGO) and the Victoria mode]. The authors further conclude that the ENSO-like low-frequency variability, which has dominant influences on the Pacific sea level and climate, comprises at least two distinct modes with different spatial structures on quasi-decadal and multidecadal time scales, respectively.

Large intraseasonal rainfall variations are identified over the southern South China Sea (SSCS), tropical southeastern Indian Ocean (SEIO), and east coast of the Philippines (EPHI) in boreal winter. The present study contrasts origins and propagations and investigates interrelations of intraseasonal rainfall variations on the 10–20- and 30–60-day time scales in these regions. Different origins are identified for intraseasonal rainfall anomalies over the SSCS, SEIO, and EPHI on both time scales. On the 10–20-day time scale, strong northerly or northeasterly wind anomalies related to the East Asian winter monsoon (EAWM) play a major role in intraseasonal rainfall variations over the SSCS and EPHI. On the 30–60-day time scale, both the intraseasonal signal from the tropical Indian Ocean and the EAWM-related wind anomalies contribute to intraseasonal rainfall variations over the SSCS, whereas the EAWM-related wind anomalies have a major contribution to the intraseasonal rainfall variations over the EPHI. No relation is detected between the intraseasonal rainfall variations over the SEIO and the EAWM on both the 10–20-day and 30–60-day time scales. The anomalies associated with intraseasonal rainfall variations over the SSCS and EPHI propagate northwestward and northeastward, respectively, on the 10–20- and 30–60-day time scales. The intraseasonal rainfall anomalies display northwestward and northward propagation over the Bay of Bengal, respectively, on the 10–20- and 30–60-day time scales.

This study provides an empirical description of intraseasonal rainfall variability within the North American monsoon (NAM) region. Applying particular definitions to historical daily rainfall observations, it demonstrates that distinct intraseasonal rainfall modes exist and that these modes differ considerably from the monsoon core region in northwest Sonora (SON), California, to its northward extension in southeast Arizona (AZ). To characterize intraseasonal rainfall variability (ISV), separate P-mode principal component (PC) analyses were performed for SON and AZ. The results indicate that in each area, much of the ISV in rainfall can be described by three orthogonal modes. The correlations between ISV modes and total seasonal rainfall reinforce the notion of differing behaviors between the monsoon’s core and extension. For SON all three ISV modes exhibit significant correlation with seasonal rainfall, with the strongest relationship in evidence for the ISV mode, which is related to rainfall intensity. For AZ, total rainfall exhibits the strongest correlation with the ISV mode, which emphasizes season length and rainfall consistency. Examination of longer-period behavior in the ISV modes indicates that, for SON, there is a positive linear trend in intensity, but a countervailing trend toward a shorter monsoon season along with less consistent rainfall in the form of shorter wet spells. For AZ, the evidence for trend in the ISV modes is not nearly as compelling, though one of the modes appears to exhibit distinct multidecadal variability. This study also evaluates teleconnectivity between ENSO, the Pacific decadal oscillation (PDO), and the NAM’s intraseasonal rainfall variability. Results indicate that part of the intraseasonal rainfall variability in both SON and AZ is connected to ENSO while only SON exhibits a teleconnection with the long-period fluctuations of the PDO.

The space–time structure of intraseasonal (10–90 day) rainfall variability in the western tropical Pacific is studied using daily 3B42 TRMM and ERA-Interim reanalysis data for the period 1998–2014. Empirical orthogonal function (EOF) analysis of 10–90-day filtered daily rainfall anomalies identifies two leading modes in both May–October and November–April; together these modes explain about 11%–12% of the total intraseasonal variance over the domain in both seasons and up to 60% over large areas of the western Pacific in both climatological periods. The two leading modes in May–October are linearly related to each other and both are well correlated with the Madden–Julian oscillation (MJO) indices. Although the two leading EOF modes in November–April are linearly independent of each other, both show statistically significant correlations with the MJO. The phase composites of 30–80-day filtered data show that the two leading modes are associated with strong eastward and northward propagation of rainfall anomalies in May–October, and eastward and southward propagation of rainfall anomalies in November–April. The eastward propagation of rainfall anomalies in both seasons and southeastward propagation related with EOF2 in November–April is linked to the development of low-level moisture flux convergence ahead of the active convection. Similarly, the northward propagation in May–October is also connected with low-level moisture flux convergence, but surface wind and evaporation variations are also important. The wind–evaporation–SST feedback mechanism drives the southeastward propagation of rainfall anomalies associated with EOF1 in November–April. The different mechanisms for southeastward propagation associated with two leading modes in November–April suggest dynamically different relations with the MJO.

Previous research has shown that seasonal-mean boreal winter variations in the subtropical/extratropical sea level pressure and wind stress fields over the central North Pacific are significantly related to the state of the El Niño–Southern Oscillation (ENSO) 12–15 months later. Results presented in this note indicate that boreal winter ENSO events are also preceded by increased intraseasonal variance in the antecedent boreal winter atmospheric circulation patterns over the extratropical central North Pacific as well. Low (high) surface pressure anomalies associated with intraseasonal variability in this region are related to intraseasonal wind stress anomalies that represent a weakening (strengthening) of the trade winds over both the north and south subtropical/tropical Pacific. There is also a concurrent increase (decrease) in the central and eastern subtropical North Pacific sea surface temperatures that projects onto the seasonal-mean SST anomalies that precede mature ENSO events by 9–12 months. Overall these results suggest that similar to seasonal-mean subtropical surface pressure and wind stress fields, enhanced transient variability in the midlatitudes can subsequently induce changes in the atmospheric and oceanic structure of the tropical Pacific that may serve as a precursor to ENSO variability.

Abstract. Climate change is expected to modify intra-seasonal rainfall variability, arising from shifts in rainfall frequency, intensity and seasonality. These intra-seasonal changes are likely to have important ecological impacts on terrestrial ecosystems. Yet, quantifying these impacts across biomes and large climate gradients is largely missing. This gap hinders our ability to better predict ecosystem services and their responses to climate change, especially for arid and semi-arid ecosystems. Here we use a synthetic weather generator and an independently validated vegetation dynamic model (SEIB-Dynamic Global Vegetation Model, DGVM) to virtually conduct a series of "rainfall manipulation experiments" to study how changes in the intra-seasonal rainfall variability affect continent-scale ecosystem responses across Africa. We generate different rainfall scenarios with fixed total annual rainfall but shifts in (i) frequency vs. intensity, (ii) rainy season length vs. frequency, (iii) intensity vs. rainy season length. These scenarios are fed into SEIB-DGVM to investigate changes in biome distributions and ecosystem productivity. We find a loss of ecosystem productivity with increased rainfall frequency and decreased intensity at very low rainfall regimes (<400 mm year−1) and low frequency (<0.3 event day−1); beyond these very dry regimes, most ecosystems benefit from increased frequency and decreased intensity, except in the wet tropics (>1800 mm year−1) where radiation limitation prevents further productivity gains. This result reconciles seemingly contradictory findings in previous field studies on the impact of rainfall frequency/intensity on ecosystem productivity. We also find that changes in rainy season length can yield more dramatic ecosystem responses compared with similar percentage changes in rainfall frequency or intensity, with the largest impacts in semi-arid woodlands. This study demonstrates that intra-seasonal rainfall characteristics play a significant role in influencing ecosystem function and structure through controls on ecohydrological processes. Our results suggest that shifts in rainfall seasonality have potentially large impacts on terrestrial ecosystems, and these understudied impacts should be explicitly examined in future studies of climate impacts.

Many features of the El Nino-Southern Oscillation (ENSO) display significant interdecadal changes. These include general characteristics such as amplitude, period, and developing features, and also nonlinearities, especially the El Nino-La Nina asymmetry. A review of previous studies on the interdecadal changes in the ENSO nonlinearities is provided. In particular, the methods for measuring ENSO nonlinearities, their possible driving mechanisms, and their interdecadal changes are discussed. Two methods for measuring ENSO nonlinearities are introduced; the maximum potential intensity, which refers to the upper and lower bounds of the cold tongue temperature, and the skewness, which represents the asymmetry of a probability density function. For example, positive skewness (a strong El Nino vs. a weak La Nina) of the tropical Pacific sea surface temperature (SST) anomalies is dominant over the eastern tropical Pacific, with an increase seen during recent decades (e.g., 1980–2000). This positive skewness can be understood as a result of several nonlinear processes. These include the warming effect on both El Nino and La Nina by nonlinear dynamic heating (NDH), which intensifies El Nino and suppresses La Nina; the asymmetric negative feedback due to tropical oceanic instability waves, which has a relatively stronger influence on the La Nina event; the nonlinear physics of the ocean mixed layer; the Madden-Julian-Oscillation/Westerly-Wind-Burst and ENSO interaction; the biological-physical feedback process; and the nonlinear responses of the tropical atmospheric convection to El Nino and La Nina conditions. The skewness of the tropical eastern Pacific SST anomalies and the intensities of the above-mentioned mechanisms have both experienced clear decadal changes in a dynamically associated manner. In particular, there is a dynamic linkage between the decadal changes in the El Nino-La Nina asymmetry and those in NDH. This linkage is based on the recent decadal changes in mean climate states, which provided a favorable condition for thermocline feedback rather than for zonal advection feedback, and thus promoted the eastward propagation of the ENSO-related atmospheric and oceanic fields. The eastward propagating ENSO mode easily produces a positive NDH, resulting in asymmetric ENSO events in which El Nino conditions are stronger than La Nina conditions.

A tropical Pacific sea surface temperature (SST) anomaly is included in a global general circulation model with a hybrid convection scheme. Results are compared with a similar version of the same model that includes a simple moist convective adjustment scheme and with observed data analyses from the European Centre for Medium-Range Weather Forecasts. The model with the hybrid scheme transports proportionately more heat and moisture higher into the troposphere in the vicinity of the SST anomaly, and the extratropical sensitivity to the SST anomaly is greater (larger-amplitude anomalies). Improvements in the simulated mean climate with the hybrid scheme result in an altered and more realistic extratropical response to the tropical SST anomaly. This is especially true for the Southern Hemisphere where the improvements to the mean climate simulation are most dramatic. This result is consistent with linear models that show a great dependence on the mean extratropical climate simulation for the type of...

This study introduces four univariate regional indices to improve the representation of intraseasonal rainfall variability across South America throughout the year, focusing on Brazil. These indices are constructed using two distinct approaches: the linear Empirical Orthogonal Functions (EOF) method and the unsupervised machine‐learning Self‐Organizing Maps (SOM) technique. Both methods are applied to Outgoing Longwave Radiation (OLR) and precipitation‐filtered anomalies in the 30–90‐day band over the South American domain. Results demonstrate that regional indices provide valuable insights into intraseasonal South American rainfall variability, including phase and strength, compared to global indices of the Madden‐Julian Oscillation (MJO). Despite being computed using only the South American domain, the regional indices capture the tropical‐tropical MJO teleconnection through the zonal wavenumber‐1 structure. The diversity in amplitude and evolution of precipitation, primarily influenced by tropical‐extratropical teleconnections through Rossby wave trains, is more evident when using the non‐linear SOM index. The regional indices also accurately measure the impacts of intraseasonal variability on extreme precipitation events over Brazil. Case studies, such as the 2013/2014 summer drought episode, highlight this ability, when a deficient rainy season severely affected the Southeast Region of Brazil, impacting agricultural production and hydroelectric power generation. During this episode, the regional indices show agreement between drought periods and suppressed precipitation phases, while global indices indicate an inactive MJO phase. These findings underscore the effectiveness of regional indices in capturing intraseasonal variability, offering significant implications for extreme weather prediction and their impacts on South American water resources and socio‐economic activities.