Intraseasonal Rainfall Research Articles

Aerosols cause intraseasonal short-term suppression of Indian monsoon rainfall

Aerosol abundance over South Asia during the summer monsoon season, includes dust and sea-salt, as well as, anthropogenic pollution particles. Using observations during 2000–2009, here we uncover repeated short-term rainfall suppression caused by coincident aerosols, acting through atmospheric stabilization, reduction in convection and increased moisture divergence, leading to the aggravation of monsoon break conditions. In high aerosol-low rainfall regions extending across India, both in deficient and normal monsoon years, enhancements in aerosols levels, estimated as aerosol optical depth and absorbing aerosol index, acted to suppress daily rainfall anomaly, several times in a season, with lags of a few days. A higher frequency of prolonged rainfall breaks, longer than seven days, occurred in these regions. Previous studies point to monsoon rainfall weakening linked to an asymmetric inter-hemispheric energy balance change attributed to aerosols, and short-term rainfall enhancement from radiative effects of aerosols. In contrast, this study uncovers intraseasonal short-term rainfall suppression, from coincident aerosol forcing over the monsoon region, leading to aggravation of monsoon break spells. Prolonged and intense breaks in the monsoon in India are associated with rainfall deficits, which have been linked to reduced food grain production in the latter half of the twentieth century.

Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events

The sub-seasonal variation of Indian summer monsoon rainfall highly impacts Kharif crop production in comparison with seasonal total rainfall. The rainfall frequency and intensity corresponding to various rainfall events are found to be highly related to crop production and therefore, the predictability of such events are considered to be diagnosed. Daily rainfall predictions are made available by one of the coupled dynamical model National Centers for Environmental Prediction Climate Forecast System (NCEPCFS). A large error in the simulation of daily rainfall sequence influences to take up a bias correction and for that reason, two approaches are used. The bias-corrected GCM is able to capture the inter-annual variability in rainfall events. Maximum prediction skill of frequency of less rainfall (LR) event is observed during the month of September and a similar result is also noticed for moderate rainfall event with maximum skill over the central parts of the country. On the other hand, the impact of rainfall weekly rainfall intensity is evaluated against the Kharif rice production. It is found that weekly rainfall intensity during July is having a significant impact on Kharif rice production, but the corresponding skill was found very low in GCM. The GCM are able to simulate the less and moderate rainfall frequency with significant skill.

Joint Modulation of Intraseasonal Rainfall in Tropical Australia by the Madden‐Julian Oscillation and El Niño‐Southern Oscillation

AbstractRainfall in tropical Australia is a critical resource for the agricultural sector. However, its high variability implores improvements in our understanding of its variability. Australian tropical rainfall is influenced by both the Madden‐Julian Oscillation (MJO) on intraseasonal time scales and El Niño‐Southern Oscillation (ENSO) on interannual time scales. This study examines the joint relationship between the MJO, ENSO, and tropical Australian rainfall variability. We analyze daily precipitation data from stations across tropical Australia during the wet season (November to April). The wet season rainfall response to the MJO is found to be greater during El Niño than La Niña. We demonstrate that this relationship is not due to the statistical relationship between the MJO and ENSO indices but instead due to differences in how the MJO modulates the large‐scale circulation during El Niño versus during La Niña.

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

The middle and lower reaches of the Yangtze River basin (MLRYB) are prone to flooding because their orientation is parallel to the East Asian summer monsoon rain belt. Since the East Asian summer monsoon presents pronounced intraseasonal variability, the subseasonal prediction of summer precipitation anomalies in the MLRYB region is an imperative demand nationwide. Based on rotated empirical orthogonal function analysis, 48 stations over the MLRYB with coherent intraseasonal (10–80-day) rainfall variability are identified. Power spectrum analysis of the MLRYB rainfall index, defined as the 48-station-averaged intraseasonal rainfall anomaly, presents two dominant modes with periods of 20–30 days and 40–60 days, respectively. Therefore, the intraseasonal (10–80-day) rainfall variability is divided into 10–30-day and 30–80-day components, and their predictability sources are detected separately. Spatial-temporal projection models (STPM) are then conducted using these predictability sources. The forecast skill during the period 2003–2010 indicates that the STPM is able to capture the 30–80-day rainfall anomalies 5–30 days in advance, but unable to reproduce the 10–30-day rainfall anomalies over MLRYB. The year-to-year fluctuation in forecast skill might be related to the tropical Pacific sea surface temperature anomalies. High forecasting skill tends to appear after a strong El Niño or strong La Niña when the summer seasonal mean rainfall over the MLRYB is enhanced, whereas low skill is apparent after neutral conditions or a weak La Niña when the MLRYB summer seasonal mean rainfall is weakened. Given the feasibility of STPM, the application of this technique is recommended in the real-time operational forecasting of MLRYB rainfall anomalies during the summer flooding season.

Origins and interrelationship of Intraseasonal rainfall variations around the Maritime Continent during boreal winter

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.

Intraseasonal rainfall variability in the Bay of Bengal during the Summer Monsoon: coupling with the ocean and modulation by the Indian Ocean Dipole

AbstractThe Indian Summer Monsoon rainfall exhibits pronounced intraseasonal variability in the Bay of Bengal (BoB). This study examines the intraseasonal rainfall variability with foci on the coupling with sea surface temperatures (SST) and its interannual modulation. The lagged composite analysis reveals that, in the northern BoB, SST warming leads the onset of intraseasonal rainfall by 5 days. Latent heat flux is reduced before the rain event but is greatly amplified during the rainfall maxima. Further analysis reveals that this intraseasonal rainfall‐SST relationship through latent heating is strengthened in negative Indian Ocean Dipole (IOD) years when the bay‐wide local SST is anomalously warm. Latent heat flux is further increased during the intraseasonal rainfall maxima leading to strengthened rainfall variability. The moisture budget analysis shows this is primarily due to stronger low‐level moisture convergence in negative IOD years. The results provide important predictive information on the monsoon rainfall and its active/break cycles.

Intraseasonal rainfall variability in North Sumatra and its relationship with Boreal Summer Intraseasonal Oscillation (BSISO)

The Boreal Summer Intraseasonal Oscillation (BSISO) is a mode of climate variability on intraseasonal timescales that dominantly occurs during Northern Hemisphere summer monsoon. Its propagation and activity can be monitored by using indices namely as BSISO1 and BSISO2. The rainfall anomalies and extremes in North Sumatra may be potentially affected by BSISO due to its location within the path of their propagations. This study analyzes the relationship of BSISO with daily rainfall anomalies and extremes during different phases and types of BSISO. The results of spectral analysis show some agreements in the periodicity of BSISO1 and BSISO2 with daily rainfall anomaly. This study also identifies extreme rainfall during different phases of BSISO, showing the increase in the number of extreme rainfall events. High number of extreme rainfall events beyond thresholds at 90th and 95th percentiles are mostly found during phase 1, 2 and 3 of BSISO1 and phase 1 and 2 of BSISO2. Composite analysis conducted separately for spatial standard deviations of daily rainfall anomalies are also performed in this study. Similar results are found, where BSISO influences on rainfall variability especially during phase 1, 2 and 3 of BSISO1, and phase 1 and 2 of BSISO2.

Patterns of Dekadal Rainfall Variation Over a Selected Region in Lake Victoria Basin, Uganda

Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March–May season using the Mann–Kendall ( M K ) trend test and simple linear regression ( S L R ) over the period 2000–2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days ( S L R = 0.181; M K = 0.350) and wet days ( S L R = 0.092; M K = 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: S L R = 0.020; M K = 0.279 and wet days: S L R = 0.146; M K = 0.376) was slightly greater than during the seventh dekad (light rain days: S L R = 0.014; M K = 0.018 and wet days: S L R = 0.061; M K = 0.315) dekad. Seventy-four percent accounted for 2–4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third ( M K = 0.363) and seventh ( M K = 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43–0.72).

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (∼5–6 mo) and at short scales (∼1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (∼3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (∼5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (∼2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that distinct strategies for coping with seasonality underlie phenological diversity. Observed drought responses highlight the importance of non-linear community responses to climate. Community phenology exhibits scale-specific patterns highlighting the need for multi-scale approaches to community dynamics.

Maximum covariance analysis to identify intraseasonal oscillations over tropical Brazil

A reliable prognosis of extreme precipitation events in the tropics is arguably challenging to obtain due to the interaction of meteorological systems at various time scales. A pivotal component of the global climate variability is the so-called intraseasonal oscillations, phenomena that occur between 20 and 100 days. The Madden–Julian Oscillation (MJO), which is directly related to the modulation of convective precipitation in the equatorial belt, is considered the primary oscillation in the tropical region. The aim of this study is to diagnose the connection between the MJO signal and the regional intraseasonal rainfall variability over tropical Brazil. This is achieved through the development of an index called Multivariate Intraseasonal Index for Tropical Brazil (MITB). This index is based on Maximum Covariance Analysis (MCA) applied to the filtered daily anomalies of rainfall data over tropical Brazil against a group of covariates consisting of: outgoing longwave radiation and the zonal component u of the wind at 850 and 200 hPa. The first two MCA modes, which were used to create the { MITB}_1 and { MITB}_2 indices, represent 65 and 16 % of the explained variance, respectively. The combined multivariate index was able to satisfactorily represent the pattern of intraseasonal variability over tropical Brazil, showing that there are periods of activation and inhibition of precipitation connected with the pattern of MJO propagation. The MITB index could potentially be used as a diagnostic tool for intraseasonal forecasting.

Origins of intraseasonal rainfall variations over the southern South China Sea in boreal winter

AbstractThis study investigates the origins of intraseasonal rainfall variations over the southern South China Sea (SCS) region in boreal winter. It is found that intraseasonal rainfall variations over the southern SCS have different origins on the 10–20-day and 30–60-day time scales. On the 10–20-day time scale, large rainfall anomalies over the southern SCS are preceded by strong northerly wind anomalies associated with the East Asian winter monsoon (EAWM), by about two days. On the 30–60-day time scale, the strong EAWM-related northerly wind anomalies almost appear simultaneously with large rainfall anomalies over the southern SCS. In addition, obvious large rainfall anomalies occur over the southeastern tropical Indian Ocean about one week before the peak southern SCS rainfall anomalies. It indicates that the convection and related circulation anomalies with origins over the tropical Indian Ocean may play an important role in inducing intraseasonal rainfall variations over the southern SCS on the 30–6...

An analysis of extreme intraseasonal rainfall events during January–March 2010 over eastern China

The precipitation over eastern China during January–March 2010 exhibited a marked intraseasonal oscillation (ISO) and a dominant period of 10-60days. There were two active intraseasonal rainfall periods. The physical mechanisms responsible for the onset of the two rainfall events were investigated using ERA-interim data. In the first ISO event, anomalous ascending motion was triggered by vertically integrated (1000–300hPa) warm temperature advection. In addition to southerly anomalies on the intraseasonal (10–60-day) timescale, synoptic-scale southeasterly winds helped advect warm air from the South China Sea and western Pacific into the rainfall region. In the second ISO event, anomalous convection was triggered by a convectively unstable stratification, which was caused primarily by anomalous moisture advection in the lower troposphere (1000–850hPa) from the Bay of Bengal and the Indo-China Peninsula. Both the intraseasonal and the synoptic winds contributed to the anomalous moisture advection. Therefore, the winter intraseasonal rainfall events over East Asia in winter could be affected not only by intraseasonal activities but also by higher frequency disturbances.

Intraseasonal Rainfall Variability over Madagascar

Using daily rain gauge records for Madagascar and nearby islands, this paper investigates rainfall intraseasonal variability at local and regional scales during the austral summer season (November–February), as well as the respective influences of recurrent convective regimes over the southwest Indian Ocean (SWIO) and the Madden–Julian oscillation (MJO). The results show a general consistency between local-scale rainfall variability in Madagascar and regional-scale features of climate variability. The influence of tropical temperate troughs in their mature phase and/or their easternmost locations is first underlined. The development of such systems over southern Africa and the Mozambique Channel can be considered as precursors for Malagasy wet spells, especially over the southern part of the island. Regional and local effects of the MJO are weaker on average, and only concern the northwest of the island and the north of the Mozambique Channel. MJO and convective regimes are finally shown to explain distinct fractions of regional rainfall variability.

The statistical extended-range (10–30-day) forecast of summer rainfall anomalies over the entire China

The extended-range (10–30-day) rainfall forecast over the entire China was carried out using spatial–temporal projection models (STPMs). Using a rotated empirical orthogonal function analysis of intraseasonal (10–80-day) rainfall anomalies, China is divided into ten sub-regions. Different predictability sources were selected for each of the ten regions. The forecast skills are ranked for each region. Based on temporal correlation coefficient (TCC) and Gerrity skill score, useful skills are found for most parts of China at a 20–25-day lead. The southern China and the mid-lower reaches of Yangtze River Valley show the highest predictive skills, whereas southwestern China and Huang-Huai region have the lowest predictive skills. By combining forecast results from ten regional STPMs, the TCC distribution of 8-year (2003–2010) independent forecast for the entire China is investigated. The combined forecast results from ten STPMs show significantly higher skills than the forecast with just one single STPM for the entire China. Independent forecast examples of summer rainfall anomalies around the period of Beijing Olympic Games in 2008 and Shanghai World Expo in 2010 are presented. The result shows that the current model is able to reproduce the gross pattern of the summer intraseasonal rainfall over China at a 20-day lead. The present study provides, for the first time, a guide on the statistical extended-range forecast of summer rainfall anomalies for the entire China. It is anticipated that the ideas and methods proposed here will facilitate the extended-range forecast in China.

Investigation of summer monsoon rainfall variability in Pakistan

This study analyzes the inter-annual and intra-seasonal rainfall variability in Pakistan using daily rainfall data during the summer monsoon season (June to September) recorded from 1980 to 2014. The variability in inter-annual monsoon rainfall ranges from 20 % in northeastern regions to 65 % in southwestern regions of Pakistan. The analysis reveals that the transition of the negative and positive anomalies was not uniform in the investigated dataset. In order to acquire broad observations of the intra-seasonal variability, an objective criterion, the pre-active period, active period and post-active periods of the summer monsoon rainfall have demarcated. The analysis also reveals that the rainfall in June has no significant contribution to the increase in intra-seasonal rainfall in Pakistan. The rainfall has, however, been enhanced in the summer monsoon in August. The rainfall of September demonstrates a sharp decrease, resulting in a high variability in the summer monsoon season. A detailed examination of the intra-seasonal rainfall also reveals frequent amplitude from late July to early August. The daily normal rainfall fluctuates significantly with its maximum in the Murree hills and its minimum in the northwestern Baluchistan.

Experimental 15-day-lead statistical forecast of intraseasonal summer monsoon rainfall over Eastern China

This study utilizes daily Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) gridded rainfall and the U.S. National Centers for Environmental Predicti...

On the Differences in the Intraseasonal Rainfall Variability between Western and Eastern Central Africa: Case of 25 - 70-Day Oscillations

The intraseasonal timescale is critical in Central Africa, because the resources of the region are highly rainfall dependent. In this paper, we use 1DD GPCP rainfall product to investigate the differences in the space-time structures of the 25 - 70-day intraseasonal variability of rainfall, over the Western Central Africa (WCA) and the Eastern Central Africa (ECA), with different climate features. The results of Empirical Orthogonal Functions (EOFs) analysis have shown that the amount of variance explained by the leading EOFs is greater in ECA (58.4%) than in WCA (49.8%). For both WCA and ECA, the power spectra of the Principal Components (PCs) peaked around 40 days, indicating a MJO signal. The seasonality of ISO is evident, but this seasonality is much noticeable in ECA where almost 80% of the total yearly ISO power occurs during November-April season, against only around 60% for WCA. Moreover, the lagged cross correlations computed between WCA and ECA PCs time series showed that most of the WCA PCs led ECA PCs time series with a timescale of 8 - 12 days, revealing that the eastward propagation could potentially be the relationship between WCA and ECA modes. The interannual variations in the ISO activity are weak in WCA, when compared with ECA where the signal exhibits larger interannual variations, quite linked with ENSO.

What aspects of future rainfall changes matter for crop yields in West Africa?

AbstractHow rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA‐H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall‐related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

Crop-climate ensemble scenarios to improve risk assessment and resilience in the semi-arid regions of West Africa

Estimation of the response of rainfed crops to heat stress and water stress must ade- quately account for the uncertainty in climatic and non-climatic factors that affect impact assess- ments. The objective of this research was to narrow the range of values characterizing the limits within which estimates are expected to fall in the diagnostics of agroclimatic risks. Assessments were made by analyzing historical observations and evaluating the influence of heat stress and rainfall variability on crop water demand, biomass and grain yields of short-cycle cultivars of pearl millet and maize. We used a wide range of consistent and practical sets of crop model ensemble analyses (based on crop management practices such as plant density, fertilization levels, early/late sowing dates and soil types) and climate model ensembles from 2 climate change hypothesis (A1b and RCP8.5) over the West African Sudan-Sahel. Recent rainfall developments show that haz- ardous intra-seasonal rainfall distribution affects crop productivity, with increased frequency and intensity of daily rainfall, false start and early cessation of the rainy season and decreasing diurnal temperature range. In 2011�2050 perspectives, relative to the 1981�2010 baseline, a slight in - crease in temperature (i.e. +0.6 to +0.8°C) combined with a stationary to moderate decrease in precipitation leads to a 10 to 15% (8 to 15%) decrease in aboveground biomass production (grain yield). When the warming is moderate (i.e. +1.4 to 1.8°C), the decline in grain yield worsens (10 to 20%), despite a slight increase in rainfall projections. At these rates of loss in crop production, resilience can be reinforced. However, it will require that climate-smart crop management prac- tices be embedded in sub-seasonal and interannual monitoring and early warning systems.

What is the Role of the Sea Surface Temperature Uncertainty in the Prediction of Tropical Convection Associated with the MJO?

Abstract This study investigated the influence of the uncertainty in the sea surface temperature (SST) on the representation of the intraseasonal rainfall variability associated with the Madden–Julian oscillation (MJO) and how this influence varies with convection parameterization. The study was motivated by the fact that there exist substantial differences in observational SST analyses, and by the possibility that lacking sufficient accuracy for SSTs in dynamical models may degrade the MJO simulation and prediction. Experiments for the DYNAMO intensive observing period were carried out using the NCEP atmospheric Global Forecast System (GFS) with three convection schemes forced by three SST specifications. The SST specifications included the widely used National Climatic Data Center (NCDC) daily SST analysis, the TRMM Microwave Imager (TMI) SST retrieval, and an SST climatology that only contains climatological seasonal cycle. The experiments show that for all convection schemes, the advantage of using observed (TMI and NCDC) SSTs over the climatology SSTs can be seen as early as 5 days to 1 week after the start of the forecast. Further, the prediction with TMI SSTs was more skillful than that with the NCDC SSTs, indicating that the current level of SST uncertainties in the observational analyses can lead to large differences when they are used as the lower boundary conditions. The results suggest that the simulation and prediction can be improved with an atmosphere-only model forced by more accurate SSTs, or with a coupled atmosphere–ocean model that has a more realistic representation of the SST variability. Differences in the prediction among the convection schemes are also presented and discussed.