Indian Monsoon Index Research Articles

Weakening Indian monsoon favors vegetation growth in humid but not in semi-arid ecosystems

The weakening Indian monsoon during recent warmer decades has caused greening and browning trends in water- and energy-limited terrestrial ecosystems of the Tibetan Plateau, respectively. Little is known, however, on the underlying mechanisms of such divergent responses of vegetation to the monsoon weakening. Herein, using the Indian monsoon index, high-resolution vegetation indices and multi-source climate data, we assessed the response of vegetation greenness to the Indian monsoon from 2000 to 2018 in two adjacent basins dominated by water- and energy-limited ecosystems and located in the southeastern Tibetan Plateau. The two basins showed opposite greenness trends due to direct and indirect effects of the weakening monsoon. The weakening monsoon increased vegetation greenness in the humid sites due to more heat exposure and solar radiation, but not in dry sites because of amplified drought stress. Thus, a weaker monsoon would not favor productivity in drought-prone ecosystems, whereas it would benefit energy-limited sites due to more radiation and warmer conditions associated to lower cloudiness. The effect of atmospheric circulation and its inter-decadal oscillation on basin-scale ecological processes should be therefore taken into account to refine earth system models and climate forecasts.

Investigating the unprecedented summer 2022 penetration of the Indian monsoon to Iran and evaluation of global and regional model forecasts

The Indian Summer Monsoon (ISM) significantly impacts the climate of the Asian continent. During the summer of 2022, the penetration of monsoonal waves towards higher latitudes led to severe and unprecedented floods in various parts of Iran, Pakistan, and southern Afghanistan. In this study, we utilized meteorological data from weather stations, satellite remote sensing, reanalysis data, and teleconnection indices to investigate the penetration of monsoonal waves at higher latitudes in Iran. We also employed outputs from two global models, the Global Forecast System (GFS) and Climate Forecast System (CFS), and the Weather Research and Forecasting Model (WRF) regional model, to examine their forecasts of heavy monsoon rains. Our analysis of teleconnection indices revealed that La Niña, combined with a negative or neutral Dipole Mode Index (DMI) and a positive Indian Monsoon Index (IMI), intensified monsoon-related rainfall in the region. The low-pressure system over India weakened, while the system over central Iran strengthened. Additionally, we observed a meridional rotation of the Somali low-level jet. Generally, southern to southwestern Iran, as well as central and eastern regions, receive moisture from the Arabian Sea due to southerly and easterly winds from water surfaces. Comparing forecasts with 2–7 days lead times and extended 10–15 days from the CFS and GFS global models demonstrated that neither of models accurately predicted the observed range of rainfall over Iran in the extended period. However, the WRF regional model predictions were significantly better. We also discovered that the 48-hour forecast from the WRF model outperformed other forecasts for this case study.

Maximum July–September temperatures derived from tree‐ring densities on the western Loess Plateau, China

AbstractTree‐ring densitometric studies conducted in semi‐arid regions are exceedingly rare. In this study, we evaluate a new maximum latewood density chronology from a collection of Picea purpurea trees growing in semi‐arid northwestern China for climatic reconstruction purposes. We find statistically significant correlations between annual maximum density variations and July–September maximum temperatures over the 1957–2014 calibration period. Using a linear model to transfer the density variations to temperature estimates, we then reconstruct maximum summer temperatures from 1840 to 2014. Statistical analyses and verification tests demonstrate that the resulting transfer function is both reliable and stable. The reconstructed temperature series shows strong inter‐annual and decadal variability. Several extremely cool and warm years are apparent on an inter‐annual scale, while three extended cool periods and a warm period are observed on a decadal scale. In addition, the reconstructed temperature series exhibits a pattern synchronous with that of the Indian monsoon index, as well as a moderate relationship to volcanic eruptions. This densitometric study reveals typical climatic variation characteristics and provides useful data for deepening our understanding of climate history in the semi‐arid regions of China.

Multi-year monitoring of atmospheric total gaseous mercury at a remote high-altitude site (Nam Co, 4730 m a.s.l.) in the inland Tibetan Plateau region

Abstract. Total gaseous mercury (TGM) concentrations were continuously measured at Nam Co Station, a remote high-altitude site (4730 m a.s.l.), on the inland Tibetan Plateau, China, from January 2012 to October 2014 using a Tekran 2537B instrument. The mean concentration of TGM during the entire monitoring period was 1.33±0.24 ng m−3 (mean ± standard deviation), ranking it as the lowest value among all continuous TGM measurements reported in China; it was also lower than most of sites in the Northern Hemisphere. This indicated the pristine atmospheric environment on the inland Tibetan Plateau. Long-term TGM at the Nam Co Station exhibited a slight decrease especially for summer seasons. The seasonal variation of TGM was characterized by higher concentrations during warm seasons and lower concentrations during cold seasons, decreasing in the following order: summer (1.50±0.20 ng m−3) > spring (1.28±0.20 ng m−3) > autumn (1.22±0.17 ng m−3) > winter (1.14±0.18 ng m−3). Diurnal variations of TGM exhibited uniform patterns in different seasons: the daily maximum was reached in the morning (around 2–4 h after sunrise), followed by a decrease until sunset and a subsequent buildup at night, especially in the summer and the spring. Regional surface reemission and vertical mixing were two major contributors to the temporal variations of TGM while long-range transported atmospheric mercury promoted elevated TGM during warm seasons. Results of multiple linear regression (MLR) revealed that humidity and temperature were the principal covariates of TGM. Potential source contribution function (PSCF) and FLEXible PARTicle dispersion model (WRF-FLEXPART) results indicated that the likely high potential source regions of TGM to Nam Co were central and eastern areas of the Indo-Gangetic Plain (IGP) during the measurement period with high biomass burning and anthropogenic emissions. The seasonality of TGM at Nam Co was in phase with the Indian monsoon index, implying the Indian summer monsoon as an important driver for the transboundary transport of air pollution onto the inland Tibetan Plateau. Our results provided an atmospheric mercury baseline on the remote inland Tibetan Plateau and serve as new constraint for the assessment of Asian mercury emission and pollution.

Quantification of Seasonal Precipitation over the upper Chao Phraya River Basin in the Past Fifty Years Based on Monsoon and El Niño/Southern Oscillation Related Climate Indices

For better water resources management, we proposed a method to estimate basin-scale seasonal rainfall over selected areas of the Chao Phraya River Basin, Thailand, from existing climate indices that represent variations in the Asian summer monsoon, the El Niño/Southern Oscillation, and sea surface temperatures (SST) in the Pacific Ocean. The basin-scale seasonal rainfall between 1965 and 2015 was calculated for the upper Ping River Basin (PRB) and the upper Nan River Basin (NRB) from a gridded rainfall dataset and rainfall data collected at several gauging stations. The corresponding climate indices, i.e., the Equatorial-Southern Oscillation Index (EQ-SOI), Indian Monsoon Index (IMI), and SST-related indices, were examined to quantify seasonal rainfall. Based on variations in the rainfall anomaly and each climate index, we found that IMI is the primary variable that can explain variations in seasonal rainfall when EQ-SOI is negative. Through a multiple regression analysis, we found that EQ-SOI and two SST-related indices, i.e., Pacific Decadal Oscillation Index (PDO) and SST anomalies in the tropical western Pacific (SSTNW), can quantify the seasonal rainfall for years with positive EQ-SOI. The seasonal rainfall calculated for 1975 to 2015 based on the proposed method was highly correlated with the observed rainfall, with correlation coefficients of 0.8 and 0.86 for PRB and NRB, respectively. These results suggest that the existing indices are useful for quantifying basin-scale seasonal rainfall, provided a proper classification and combination of the climate indices are introduced. The developed method could forecast seasonal rainfall over the target basins if well-forecasted climate indices are provided with sufficient leading time.

Decreasing Indian summer monsoon on the northern Indian sub-continent during the last 180 years: evidence from five tree-ring cellulose oxygen isotope chronologies

Abstract. We have constructed a regional tree-ring cellulose oxygen isotope (δ18O) record for the northern Indian sub-continent based on two new records from northern India and central Nepal and three published records from northwestern India, western Nepal and Bhutan. The record spans the common interval from 1743 to 2008 CE. Correlation analysis reveals that the record is significantly and negatively correlated with the three regional climatic indices: all India rainfall (AIR; r = −0.5, p < 0.001, n = 138), Indian monsoon index (IMI; r = −0.45, p < 0.001, n = 51) and the intensity of monsoonal circulation (r = −0.42, p < 0.001, n = 51). The close relationship between tree-ring cellulose δ18O and the Indian summer monsoon (ISM) can be explained by oxygen isotope fractionation mechanisms. Our results indicate that the regional tree-ring cellulose δ18O record is suitable for reconstructing high-resolution changes in the ISM. The record exhibits significant interannual and long-term variations. Interannual changes are closely related to the El Niño–Southern Oscillation (ENSO), which indicates that the ISM was affected by ENSO in the past. However, the ISM–ENSO relationship was not consistent over time, and it may be partly modulated by Indian Ocean sea surface temperature (SST). Long-term changes in the regional tree-ring δ18O record indicate a possible trend of weakened ISM intensity since 1820. Decreasing ISM activity is also observed in various high-resolution ISM records from southwest China and Southeast Asia, and may be the result of reduced land–ocean thermal contrasts since 1820 CE.

Perceptible changes in Indian summer monsoon rainfall in relation to Indian Monsoon Index

The changes in the summer monsoon rainfall over 30 meteorological subdivisions of India with respect to changes in circulation and the Indian Monsoon Index (IMI) have been studied for the period 1953–2012. The relationship between the IMIs in different months and whole season and the corresponding summer monsoon rainfall is studied and tested. The positive and negative extremes are evaluated basing on the normalized values of the deviations from the mean of the IMI. Composite rainfall distributions over India and the zonal wind distributions in the lower and upper troposphere of IMI's both positive and negative extremes are evaluated separately and discussed. In the recent three decades of global warming, the negative values of IMI in July and August lead to weakening of the monsoon system over India. It is observed that the rainfall variations in the Northeast India are different from the rest of India except Tamil Nadu in general.

Analyzing the non-linear trend and multiscale teleconnections of regional monsoon indices using empirical mode decomposition

This paper first performs the analysis of linear and non-linear trends of four representative monsoon Indices namely Indian Monsoon Index (IMI) and Webster-Yang index (WYI), Western North Pacific Monsoon Index (WNPMI) and Australian Monsoon Index (AMI) for the period 1948–2015. The study evaluates the trend in the time series of different monsoon months and seasonal (JJA/JJAS/DJF) series, of all the indices using Mann–Kendall test, Sen’s slope method, linear fitting and the Empirical Mode Decomposition (EMD) method. The trend analysis showed significant reduction in all the series of WYI index and the August month series of IMI. The results of sequential version of MK test revealed that the WYI time series of different months and monsoon season showed statistically significant reduction in the past with differences in commencement year of statistical significance of MK value. The comparison of long term trend of monsoon indices and ElNino Southern Oscillation (ENSO) displayed an opposing trend for different indices except for WNPMI. Further for a detailed examination of association of different indices with ENSO in multiple time scales, the running correlations between the oscillatory modes of monsoon indices and ENSO are performed by employing the time dependent intrinsic correlation analysis. The association between ENSO and monsoon indices at different time scales is found to be strongly negative and consistent for WNPMI and AMI while for rest of the indices, the nature of association is found to be positive in inter annual and inter decadal time scales.

Impacts of Climate Modes on Air–Sea Heat Exchange in the Red Sea

Abstract The impacts of various climate modes on the Red Sea surface heat exchange are investigated using the MERRA reanalysis and the OAFlux satellite reanalysis datasets. Seasonality in the atmospheric forcing is also explored. Mode impacts peak during boreal winter [December–February (DJF)] with average anomalies of 12–18 W m−2 to be found in the northern Red Sea. The North Atlantic Oscillation (NAO), the east Atlantic–west Russia (EAWR) pattern, and the Indian monsoon index (IMI) exhibit the strongest influence on the air–sea heat exchange during the winter. In this season, the largest negative anomalies of about −30 W m−2 are associated with the EAWR pattern over the central part of the Red Sea. In other seasons, mode-related anomalies are considerably lower, especially during spring when the mode impacts are negligible. The mode impacts are strongest over the northern half of the Red Sea during winter and autumn. In summer, the southern half of the basin is strongly influenced by the multivariate ENSO index (MEI). The winter mode–related anomalies are determined mostly by the latent heat flux component, while in summer the shortwave flux is also important. The influence of the modes on the Red Sea is found to be generally weaker than on the neighboring Mediterranean basin.

Indo-China monsoon indices.

Myanmar and Thailand often experience severe droughts and floods that cause irreparable damage to the socio-economy condition of both countries. In this study, the Southeastern Asian Summer Monsoon variation is found to be the main element of interannual precipitation variation of the region, more than the El Niño/Southern Oscillation (ENSO). The ENSO influence is evident only during the boreal spring season. Although the monsoon is the major factor, the existing Indian Monsoon Index (IMI) and Western North Pacific Monsoon Index (WNPMI) do not correlate well with the precipitation variation in the study regions of Southern Myanmar and Thailand. Therefore, a new set of indices is developed based on the regional monsoon variations and presented here for the first time. Precipitation variations in Southern Myanmar and Thailand differ as well as the elements affecting the precipitation variations in different seasons. So, separate indices are proposed for each season for Southern Myanmar and Thailand. Four new monsoon indices based on wind anomalies are formulated and are named as the Indochina Monsoon Indices. These new indices correlate better with the precipitation variations of the study region as compared to the existing IMI and WNPMI.

Impact of Northward-Propagating Intraseasonal Variability on the Onset of Indian Summer Monsoon

Abstract The onset of the Indian summer monsoon (ISM) has a pronounced interannual variability, part of which originates from the large-scale circulation and its thermodynamic properties. While the northward-propagating intraseasonal variabilities (ISVs) are a prominent characteristic of the ISM, they tend to initiate an early onset by transferring moisture and momentum from the deep tropics to the Indian subcontinent. However, not all early onsets of ISM are attributable to strong ISVs and not all strong ISVs can lead to early ISM onsets. With a daily Indian monsoon index and a simple regression model, the onsets of ISM from 1982 to 2011 are separated into two groups. The years in which the early onsets of ISM are closely related to the northward-propagating ISVs are categorized as the ISVO years, and the other years in which the ISM onsets are not closely related to ISVs are categorized as non-ISVO years. The former category is the focus of this study. Before the onset of ISM in the ISVO years, the convective features are prominent, such as a cyclone over the Bay of Bengal (BoB) and the associated strong convection. The ocean–atmosphere interaction is found to be important for the northward-propagating ISVs before the ISM onset in the ISVO years. Evidence shows that warm SST anomalies drive the atmosphere and lead to atmospheric instability and convection. This reinforces the more recent view that the ocean does not just play a passive role in the northward-propagating ISVs. This process understanding helps shape the path to enhancing predictive understanding and monsoon prediction skills with obvious implications for the prediction of El Niño–Southern Oscillation.

Long-Lead Prediction Skill of Indian Summer Monsoon Rainfall Using Outgoing Longwave Radiation (OLR): an Application of Canonical Correlation Analysis

There is a statistical linkage between tropical outgoing longwave radiation (OLR) and all-India summer monsoon rainfall (AISMR). A positive and significant correlation is observed over the surrounding areas of northeast Australia and the Arafura Sea during the months of January and February (J&F) which drops down as the lead month decreases. The OLR index as an area average over the surrounding areas of northeast Australia and the Arafura Sea is found to have 0.4 correlation with AISMR. The index is also found to be strongly correlated with the Indian monsoon index. In view of the teleconnection pattern, the OLR index is used for the development of statistical models using the concept of linear regression (LR) and canonical correlation analysis (CCA). Potential of CCA over LR is observed for the prediction of seasonal rainfall over the northwest, west central and over the whole country as well. The seasonal rainfall predictability basically comes from the months of June and September.

On the predictability of Indian summer monsoon rainfall in general circulation model at different lead time

The objective of this present study is to analyze the predictability of all India summer monsoon rainfall (AISMR) and its dependence on lead time using general circulation model (GCM) output. For the purpose, six GCMs for the hindcast run from 1982 to 2008 are used at three different initializations viz. April (lead 2), May (lead 1), and June (lead 0) for seasonal mean rainfall of June–July–August–September (JJAS). Among these models, four of them are the coupled ocean–atmosphere GCMs (CGCMs) and the remaining two are the atmospheric GCMs (AGCMs). The analysis is made on the basis of statistical measures of predictability including climatology, interannual variability, root mean square error, correlation, signal to noise ratio, potential model predictability and index of agreement. On the basis of these measures it is found that all the GCM having the minimum prediction skill is at lead 2 compare to lead 1 and lead 0. It is also noticed that higher predictability in the lead-1 forecasts is found in coupled models whereas, the predictability of atmospheric models exhibit high in lead 0. Rather than rainfall, teleconnection of rainfall with large scale features (such as sea surface temperature, zonal wind at 850hPa) and monsoon dynamic index (Indian monsoon index (IMI)) are also examined in GCMs. The results depicted that there is not much variation in the teleconnection pattern in two leads (lead 0 and lead 1) whereas; the dynamic index being predicted closer to the observed value at lead 1 in the CGCMs. The GCMs are also examined during four typical monsoon (excess/deficit) years, among which 1983 and 1988 are excess and 1987 and 2002 are deficit. Results indicate that the coupled (atmospheric) models capture the extreme rainfall signal in lead 1 (lead 0). The probabilistic prediction skill of GCM predicted rainfall is also evaluated which supports our initial analysis and results.

Influence of Indian Summer Monsoon on Aerosol Loading in East Asia

AbstractThe spatial and temporal variations of aerosol loading over eastern Asia specified in terms of the aerosol optical depth (AOD) at the 550-nm wavelength during July are examined in conjunction with the intensity of the Indian summer monsoon. AOD derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, gridded reanalyses, and ground-based measurements are used in the analysis. Two contrasting years, 2002 and 2003, which represent weak and active Indian summer monsoon events, respectively, are selected for the study, with a focus on an eastern Asian southern subregion (SR; 23°–32°N, 105°–120°E) and an eastern Asian northern subregion (NR; 35°–44°N, 115°–130°E). It is shown that the interannual variation of July mean wind intensity is a major factor in regulating the midsummer spatial pattern of aerosols over eastern Asia when the Indian monsoon index is anomalously large. The AOD anomalies in the NR and SR are positive and negative, respectively, during an active monsoon year, whereas the opposite is observed during a weak monsoon year. The variation patterns of less cloudy-day visibility, observed at four meteorological stations in the SR and NR subregions, also show spatial–temporal aerosol variability evident in the MODIS AOD data. Relative to the case of a weak monsoon year, meridional winds and convection are stronger and more clouds and precipitation are observed in the NR subregion during the active monsoon year. The opposite pattern is observed in the SR subregion. The spatial–temporal variation pattern of aerosols over eastern Asia illustrates the nonnegligible role of transport and dispersal mechanisms associated with the Indian summer monsoon in the region.

A reconstructed dynamic Indian monsoon index extended back to 1880

The authors present a reconstruction of summer (June–July–August) mean dynamic Indian monsoon index (DIMI) back to 1880 based on a large number of historical surface observation data as well as information from the upper air data. The reconstruction shows a satisfying skill in terms of both the value of reduction of error and an evaluation against other independent monsoon indices. The skill of reconstruction increases over time with more predictor data (in particular upper-level data) becoming available. A comparison with the observed all Indian summer monsoon rainfall index (AIRI) shows a high consistence in both inter-decadal and inter-annual variability. The reconstruction shows stronger than normal monsoon during the 1880s, 1915–1925 (around 1920) and 1930–1945 (around 1940) as the AIRI. The El Nino/Southern Oscillation (ENSO)—monsoon relationship is reasonably captured in the reconstruction. Powers concentrating within quasi-biennial band stand out in the reconstruction as well as in the AIRI. A comparison of the reconstruction against an atmospheric general circulation model simulation with specified SST and external forcing agents spanning 1901–1999 indicates a slightly higher reproducibility of monsoon circulation than monsoon rainfall in terms of interannual variability. The relationship between the Asian continent warming and the ENSO–monsoon connection is also discussed by using the new dynamic index.

Soluble ionic and oxygen isotopic compositions of a shallow firn profile, Baishui glacier No. 1, southeastern Tibetan Plateau

AbstractIn the summer of 2004, a firn profile, 18.3 m long, extending down to glacier ice, was recovered in the accumulation area of the largest glacier, Baishui No. 1, on Yulong mountain, the southernmost glacier-covered area in mainland Eurasia. Multivariate empirical orthogonal function (EOF) and statistical correlation analyses of major-ion data from the profile demonstrate that three distinct types of ionic material contribute to the chemical characteristics of firn in this monsoonal region: material of marine origin, which is transported by the Indian southwest monsoon; crustal materials, which come from local sources; and anthropogenic pollutants, which are produced by industrial and agricultural activities in South Asia. Although the influence of post-depositional processes on the seasonal isotopic and soluble ionic compositions is significant, dust layers in the firn profile are clearly visible. Due to the effects of meltwater percolation, the dust layers generally coincide with late-summer snow surfaces. We therefore use the dust layers, combined with the seasonal variations of electrical conductivity (EC), Ca2+ and Mg2+, to establish a depth/age scale for the firn profile. The reconstructed net accumulation has a significant negative correlation with the temperature at Lijiang, whereas the correlation between the net accumulation and the precipitation amount at Lijiang is weak. Although the δ18O time series of the firn profile was modified significantly by meltwater percolation, the correlation between annual mean δ18O values and the Indian southwest monsoon index (WSI1) is significant. This result suggests that δ18O records from monsoon-influenced temperate glaciers can provide a valuable record of past variations of the Indian southwest monsoon.

Teleconnections between Indian monsoon and Sahel rainfall and the Mediterranean

AbstractThe teleconnections with Indian monsoon and Sahel rainfall indices are investigated here on an interannual time scale in terms of meteorological and marine dynamics over the Mediterranean area. Sea‐level pressure from gridded data sets and from individual stations, together with sea‐level data from stations all around the Mediterranean coastlines, are used.In summer (July–August–September, JAS) the sea‐level pressure field over the eastern Mediterranean anticorrelates with the Indian monsoon index (correlation coefficient C = −0.5 on average). A Mediterranean pressure index (MPI), defined as the standardized difference between sea‐level atmospheric pressure at Mersa Matruh (southeastern Mediterranean) and Marseille (northwestern Mediterranean) stations, anticorrelates with Indian monsoon index even more (C = −0.68). The MPI is proportional to the mean geostrophic surface flow field across an imaginary line joining the two stations and turns out to be significantly correlated with the meridional wind component over the eastern Mediterranean, known as the low‐level Etesian wind regime. This wind regime represents the inflow surface field into the African inter‐tropical convergence zone and, therefore, has an association with the Indian monsoon regime. The ocean response, evident by sea‐level anomalies at coastal stations, shows a maximum anticorrelation with Indian monsoon index in late summer and autumn (September–October–November, SON).The Sahel index anticorrelates with sea‐level pressure, with the maximum absolute value in June–July–August. This may be interpreted as a tendency of the Mediterranean sea‐level pressure anomalies to precede those of Sahel precipitation, which is characterized by maximum rainfall in July–September. The MPI anticorrelates with Sahel index during and before JAS, indicating that the Etesian wind regime intensity is connected to Sahel rainfall. The sea level again anticorrelates with the Sahel index, with the maximum absolute value in SON, as for the sea‐level–Indian monsoon correlation. Copyright © 2003 Royal Meteorological Society.

Asynchronous Holocene optimum of the East Asian monsoon

The spatial and temporal distribution of summer monsoon precipitation (or effective moisture) during the Holocene has been reconstructed on the basis of geological data, including lake levels, pollen profiles, and loess/paleosol records. In addition, the summer (July) precipitation increment, effective precipitation, and monsoon strength index have been obtained from numerical modeling experiments. Both geological data and numerical modeling indicate that the Holocene optimum, as defined by peak East Asian summer monsoon precipitation, was asynchronous in central and eastern China, reaching a maximum at different times in different regions, e.g., ca. 10,000–8000 yr ago in northeastern China, 10,000–7000 yr ago in north-central and northern east-central China, ca. 7000–5000 yr ago in the middle and lower reaches of the Yangtze River, and ca. 3000 yr ago in southern China. In southwestern China the maximum appeared ca. 11,000 yr ago, but probably was related to the maximum landward extension of the Indian summer monsoon. The regional shift in the maximum precipitation belt from northwest to southeast over the past 10,000 yr is interpreted as a response to changing seasonality related to orbital forcing of the climate. The southeastward shift of the East Asian summer monsoon maximum is consistent with the progressive weakening of the summer monsoon as the summer solar radiation anomaly decreased progressively through the Holocene and the East Asian monsoon index declined, while the early maximum in southwestern China matches the maximum of the Indian monsoon index.

Observed lead-lag relationships between Indian summer monsoon and some meteorological variables

Lagged relationships between the Indian summer monsoon and several climate variables are investigated. The variables examined are gridded fields of snow cover (14 years), sea surface temperature (41 years) and 500 hPa geopotential height north of 20 °N (42 years). We also used series of global air temperature (108 years) and Southern Oscillation index (112 years). Precipitation over all India during June–September over a 112 year period are used as Indian monsoon index. Emphasis is put on early monsoon precursors. In agreement with the tendency for a low frequency oscillation in the ocean-atmosphere system, several precursor patterns are identified as early as the year preceding the monsoon. The most important key regions and seasons of largest correlations are selected and the corresponding series are used to perform a monsoon prediction. The prediction shows however a relatively moderate score mainly due to the not highly significant correlations. To improve the predictions we filtered the variables into their biennial (1.5–3.5 years) and low frequency (3.5–7.5 years) modes. Correlations between the monsoon and the filtered variables are higher than those obtained without filtering especially for the biennial mode. The two modes are out-of-phase before the monsoon and in-phase during and after. This phasing is found in all variables except for snow cover for which the two modes are in-phase before the monsoon and out-of-phase during and after. It is suggested that such phasing may be important for the formation of snow and could explain the higher correlations when variables are concomitant or are lagging the monsoon. Early predictions of the monsoon based on those two modes show improved scores with highly significant correlations with the actual monsoon.