Subseasonal Scales Research Articles

Transport From the Asian Summer Monsoon Anticyclone Over the Western Pacific

AbstractThe subseasonal scale dynamics of the Asian summer monsoon (ASM) upper troposphere (UT) anticyclone has been identified as a primary mechanism for convectively lofted Asian boundary layer air to leave the confinement of the anticyclone and impact the global UT and lower stratosphere (UTLS). This work quantifies eastward eddy shedding associated with the subseasonal scale oscillation of the anticyclone and associated chemical transport. Using reanalysis data together with satellite trace gas data, we examine the correlation between enhanced tropospheric trace gas species and the presence of a secondary anticyclone over the western Pacific Ocean. To diagnose the role of the western Pacific anticyclone (WPA) in the transport of ASM air into the global UTLS, transport pathways and transit times of air found within the WPA are analyzed using Lagrangian kinematic trajectories. Results show that about two thirds of the air within the WPA originates from, or is influenced by, the greater region of the Tibetan anticyclone. After leaving the WPA, air favors two pathways forward: eastward following the subtropical jet and southwestward following UTLS anticyclonic flow. Approximately 60% of the air parcels cross the tropopause into the lower stratosphere within 30 days, though most cross within a few days. These results highlight opportunities for investigating the impact of the ASM on global UTLS chemical and aerosol composition over the western Pacific via research aircraft.

Subseasonal Variability of Elevated Dust Concentrations Over South Florida

AbstractDust mass concentrations have been measured daily at Miami, Florida, in the summer months, and biweekly throughout the remaining months, since 1974. The 43‐year record of dust mass concentrations indicate large daily, seasonal, and interannual variations, with most of the dust arriving within 5–8 episodes each summer. On average, dust arrives to Miami, Florida, 10 days after emission from North Africa, with measured concentrations depending on characteristics of the lower free‐tropospheric winds due to the vast travel distance. Daily dust mass concentrations from July and August, the months that contribute the most to the annual mean, are used to characterize the synoptic conditions most favorable for dust transport. Two key regions are linked with the highest daily dust mass concentrations above Miami: (i) easterly winds, averaged over 850–500 mb, over the Tropical West Atlantic [15–25°N, 45–80°W], and (ii) southerly winds, similarly averaged, over the Florida Peninsula [20–30°N,75–80°W]. Winds within these two regions are enhanced when the North Atlantic subtropical high is displaced south and zonally elongated, relocating the western edge over Florida. A dust‐transport‐efficiency index, based on the maximum potential for dust to arrive above Miami with limited loss to deposition or mixing, identifies high‐dust loading cases on the subseasonal scale. Monthly dust‐transport‐efficiency values agree well with the monthly dust trends over the 43‐year time span. While seasonal dust loadings have been decreasing over Florida in the past decade, the transport efficiency has been increasing, possibly due to trends in the North Atlantic subtropical high.

GEOS-S2S Version 2: The GMAO High Resolution Coupled Model and Assimilation System for Seasonal Prediction.

The Global Modeling and Assimilation Office (GMAO) has recently released a new version of the Goddard Earth Observing System (GEOS) Sub-seasonal to Seasonal prediction (S2S) system, GEOS-S2S-2, that represents a substantial improvement in performance and infrastructure over the previous system. The system is described here in detail, and results are presented from forecasts, climate equillibrium simulations and data assimilation experiments. The climate or equillibrium state of the atmosphere and ocean showed a substantial reduction in bias relative to GEOS-S2S-1. The GEOS-S2S-2 coupled reanalysis also showed substantial improvements, attributed to the assimilation of along-track Absolute Dynamic Topography. The forecast skill on subseasonal scales showed a much-improved prediction of the Madden-Julian Oscillation in GEOS-S2S-2, and on a seasonal scale the tropical Pacific forecasts show substantial improvement in the east and comparable skill to GEOS-S2S-1 in the central Pacific. GEOS-S2S-2 anomaly correlations of both land surface temperature and precipitation were comparable to GEOS-S2S-1, and showed substantially reduced root mean square error of surface temperature. The remaining issues described here are being addressed in the development of GEOS-S2S Version 3, and with that system GMAO will continue its tradition of maintaining a state of the art seasonal prediction system for use in evaluating the impact on seasonal and decadal forecasts of assimilating newly available satellite observations, as well as to evaluate additional sources of predictability in the earth system through the expanded coupling of the earth system model and assimilation components.

Developing a model for forest fire risk forecast at sub-seasonal scale in Finland

Developing a model for forest fire risk forecast at sub-seasonal scale in Finland

El Niño–Related Summer Precipitation Anomalies in Southeast Asia Modulated by the Atlantic Multidecadal Oscillation

AbstractHow the Atlantic multidecadal oscillation (AMO) affects El Niño–related signals in Southeast Asia is investigated in this study on a subseasonal scale. Based on observational and reanalysis data, as well as numerical model simulations, El Niño–related precipitation anomalies are analyzed for AMO positive and negative phases, which reveals a time-dependent modulation of the AMO. 1) In May–June, the AMO influences the precipitation in southern China (SC) and the Indochina peninsula (ICP) by modulating the El Niño–related air–sea interaction over the western North Pacific (WNP). During negative AMO phases, cold sea surface temperature anomalies (SSTAs) over the WNP favor the maintaining of the WNP anomalous anticyclone (WNPAC). The associated southerly (westerly) anomalies on the northwest (southwest) flank of the WNPAC enhance (reduce) the climatological moisture transport to SC (the ICP) and result in wetter (drier) than normal conditions. In contrast, during positive AMO phases, weak SSTAs over the WNP lead to limited influence of El Niño on precipitation in Southeast Asia. 2) In July–August, the teleconnection impact from the North Atlantic is more manifest than that in May–June. During positive AMO phases, the warmer than normal North Atlantic favors anomalous wave trains, which propagate along the “great circle route” and result in positive pressure anomalies over SC, consequently suppressing precipitation in SC and the ICP. During negative AMO phases, the anomalous wave trains tend to propagate eastward from Europe to Northeast Asia along the summer Asian jet, exerting limited influence on Southeast Asia.

Tornado-days in the United States by phase of the Madden–Julian oscillation and global wind oscillation

Tornado activity in the United States varies over multiple time scales. The Madden–Julian oscillation (MJO) and global wind oscillation (GWO) are sources of climate variability at the seasonal and subseasonal scales. The univariate distributions of tornado-days across the phases of these oscillations have been documented, but the bivariate distribution of tornado-days across both oscillations has not been. Here, the bivariate distribution of tornado-days across the phases of the MJO and GWO is documented and analyzed. Results herein refine the previously reported univariate distributions and highlight variability across the phases of one of the oscillations while holding the phase of the other constant (e.g., tornado-days are more likely during phase 2 of the GWO, but the likelihood varies across the phase of MJO).

Observation and Attribution of Temperature Trends Near the Stratopause From HALOE.

This study considers time series of temperature versus pressure, T(p), from the Halogen Occultation Experiment (HALOE) across the stratopause region, where the effects of radiative forcings from the greenhouse gases (CO2 and H2O) and from ozone are most pronounced. Trend analyses of HALOE T(p) values for 1993-2005 are for six levels from 2.0 to 0.3 hPa with a vertical resolution of about 4 km and for eight latitude zones from 65°S to 65°N. The analyses account for the forcing effects from the 11-yr solar cycle. HALOE trends at 2.0 hPa are of the order of -1.0 K/decade across the tropics and subtropics but then become smaller (-0.5 K/decade) at the middle latitudes. Near-global T(p) trends are of order -0.5 K/decade but have a minimum of -0.2 K/decade at 1.0 hPa; they are clearly negative in the southern but slightly positive in the northern hemisphere. The combined radiative forcings from CO2, H2O, and ozone vary between -0.4 and -0.7 K/decade for 1993-2005 and are hemispherically symmetric. The HALOE temperature trend and total radiative cooling profiles differ from those reported from observations and calculations for 1980-2000, mainly because the ozone trends changed from clearly negative in the 1980s through mid-1990s to slightly positive during the time of HALOE. Trends at low latitudes for the tracer, methane (CH4), increase from 2% to 4%/decade from 50 to 10 hPa and then to ~6%/decade by 5 hPa. Analyses of time series of CH4 across the stratopause reveal subseasonal scale variability within the northern hemisphere that reduces the significance of the T(p) trends.

Bay of Bengal branch of Indian summer monsoon and its association with spatial distribution of rainfall patterns over India

Indian summer monsoon rainfall is characterized by a considerable variability on the spatial and temporal scale, though the standard deviation of rainfall on the temporal scale is much smaller (ca. 10% of annual long-term mean) compared with that of the spatial scale. It is known that the seasonal rainfall amplitude over India as well as the statistical properties of the subseasonal variability is strongly linked to the Pacific teleconnection on interannual timescales, such as El Nino-Southern Oscillation (ENSO) and La Nina, and the teleconnection is primarily arising from central and eastern Pacific Ocean. But, the west Pacific controls on the southwest monsoonal flow, and in turn, the modulation of rainfall variability in the subseasonal scale by this low-frequency seasonal to interannual background over India is poorly understood. Here, we examine the moisture pathways by which the spatial pattern of rainfall variability in the subseasonal scale is envisaged to be arising due to the interplay between the Bay of Bengal (BoB) summer monsoon circulation and the South China Sea (SCS) moisture dynamics under different background conditions provided by ENSO or the subseasonal movement of the Inter Tropical Convergence Zone (ITCZ). We observe that the south BoB branch of the summer monsoon could occasionally extend up to 120° E in the SCS and reverse back to Indian mainland. We propose a mechanism by which the south BoB branch interacts with the SCS (viz. western Pacific) atmospheric system, thereby facilitating a pathway of the west Pacific moisture intrusion into the Indian subcontinent. The study concludes that the changes in surface temperature/pressure spatial pattern between India and SCS region play an important role in the distribution of the rainfall. In this study, for the first time, the life cycle of south Bay monsoon flow and its interaction with the SCS are discussed, likely to warrant special attention for modelers trying to understand the spatial distribution of rainfall over India.

Can the Direct Effect of Aerosols Improve Subseasonal Predictability?

Abstract The fact that aerosols are important players in Earth’s radiation balance is well accepted by the scientific community. Several studies have shown the importance of characterizing aerosols in order to constrain surface radiative fluxes and temperature in climate runs. In numerical weather prediction, however, there has not been definite proof that interactive aerosol schemes are needed to improve the forecast. Climatologies are instead used that allow for computational efficiency and reasonable accuracy. At the monthly to subseasonal range, it is still worth investigating whether aerosol variability could afford some predictability, considering that it is likely that persisting aerosol biases might manifest themselves more over time scales of weeks to months and create a nonnegligible forcing. This paper explores this hypothesis using the ECMWF’s Ensemble Prediction System for subseasonal prediction with interactive prognostic aerosols. Four experiments are conducted with the aim of comparing the monthly prediction by the default system, which uses aerosol climatologies, with the prediction using radiatively interactive aerosols. Only the direct aerosol effect is considered. Twelve years of reforecasts with 50 ensemble members are analyzed on the monthly scale. Results indicate that the interactive aerosols have the capability of improving the subseasonal prediction at the monthly scales for the spring/summer season. It is hypothesized that this is due to the aerosol variability connected to the different phases of the Madden–Julian oscillation, particularly that of dust and carbonaceous aerosols. The degree of improvement depends crucially on the aerosol initialization. More work is required to fully assess the potential of interactive aerosols to increase predictability at the subseasonal scales.

Detecting the Causal Effect of Soil Moisture on Precipitation Using Convergent Cross Mapping

As a vital land surface parameter, soil moisture influences climate through its impact on water and energy cycles. However, the effect of soil moisture on precipitation has been strongly debated. In this study, a new causal detection method, convergent cross mapping (CCM), was applied to explore the causality between soil moisture and precipitation over low- and mid- latitude regions in the Northern Hemisphere. CCM method generally identified a strong effect of soil moisture on precipitation. Specifically, the optimal effect of soil moisture on precipitation occurred with a lag of one month and clearly decreased after four months, suggesting that soil moisture has potentials to improve the accuracy of precipitation forecast at a sub-seasonal scale. In addition, as climate (i.e., aridity index) changed from dry to wet, the effect of soil moisture on precipitation first increased and then decreased with peaks in semi-arid and semi-humid areas. These findings statistically support the hypothesis that soil moisture impacts precipitation and also provide a reference for the design of climate prediction systems.

Close linkage between quasi‐biweekly oscillation and tropical cyclone intensification over the western North Pacific

Forecasting tropical cyclone (TC) intensity is challenging, particularly at the subseasonal scale. In this study, we found that compared to the 30−90‐day Madden–Julian oscillation (MJO), the activity of 10−30‐day quasi‐biweekly oscillation (QBWO) has a closer connection with the intensity change of TCs over the tropical western North Pacific. Both the TC growth rate (24‐hr increases in maximum sustained wind speed) and the probability of TC intensification during the active phases of QBWO increase significantly compared to those during the inactive QBWO phases. The effects of QBWO on TC intensification take place mainly through alteration of the large‐scale dynamic conditions. During the active convection phase of QBWO, the 10–30‐day cyclonic vorticity and convergence in the lower troposphere, divergence in the upper troposphere, and the circulation‐induced moistening anomalies provide a favorable environment for TC growth. The thermodynamic conditions of atmospheric instability, sea surface temperature (SST), and ocean heat potential show negative but insignificant contributions to TC intensification at the quasi‐biweekly time scale. These results not only aid our understanding of the influences of QBWO‐related environmental conditions on TC intensification, but also suggest the potential predictability of TC intensity at an extended range (10–30 days) once the QBWO has been successfully predicted.

Multi-pentad prediction of precipitation variability over Southeast Asia during boreal summer using BCC_CSM1.2

Precipitation is highly variable in space and discontinuous in time, which makes it challenging for models to predict on subseasonal scales (10–30 days). We analyze multi-pentad predictions from the Beijing Climate Center Climate System Model version 1.2 (BCC_CSM1.2), which are based on hindcasts from 1997 to 2014. The analysis focus on the skill of the model to predict precipitation variability over Southeast Asia from May to September, as well as its connections with intraseasonal oscillation (ISO). The effective precipitation prediction length is about two pentads (10 days), during which the skill measured by anomaly correlation is greater than 0.1. In order to further evaluate the performance of the precipitation prediction, the diagnosis results of the skills of two related circulation fields show that the prediction skills for the circulation fields exceed that of precipitation. Moreover, the prediction skills tend to be higher when the amplitude of ISO is large, especially for a boreal summer intraseasonal oscillation. The skills associated with phases 2 and 5 are higher, but that of phase 3 is relatively lower. Even so, different initial phases reflect the same spatial characteristics, which shows higher skill of precipitation prediction in the northwest Pacific Ocean. Finally, filter analysis is used on the prediction skills of total and subseasonal anomalies. The results of the two anomaly sets are comparable during the first two lead pentads, but thereafter the skill of the total anomalies is significantly higher than that of the subseasonal anomalies. This paper should help advance research in subseasonal precipitation prediction.

Quantifying oceanic moisture exports to mainland China in association with summer precipitation

Oceanic moisture exports (OMEs) are considered the major moisture sources for precipitation over Mainland China during the boreal summer season. In this study, a Lagrangian particle dispersion and transport model [FLEXible PARTicle dispersion model (FLEXPART)] driven with European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA)-Interim data was used to conduct 35-year modeling of the summer season (May–August) for 1980–2014. Based on the 6-h output over 35 years, a relatively sophisticated approach was adopted that considers the change in specific humidity with trajectory tracking to diagnose OME-based precipitation during the summer season in China. We specifically explored the spatiotemporal structure of OME-based precipitation over Mainland China with a focus on quantifying the relative contributions of three specific oceanic sub-regions: the Arabian Sea (AS), the Bay of Bengal (BOB), and the South China Sea (SCS). The relevance of the OME anomalies from the three sub-regions and the observed precipitation changes on an interannual scale were also explored. The main research conclusions are summarized as follows: (1) The diagnosed OME-based precipitation and gauge observations exhibit similar spatial patterns in both seasonal and sub-seasonal scales, further evidencing the robustness of the approach used in this study. (2) Climatologically, the OMEs originating from the AS, the BOB, and the SCS made roughly equivalent contributions to the entire areal-averaged precipitation over Mainland China on a seasonal scale, but the preferred regions influenced by the three oceanic sources differ strongly from each other. (3) The relative contributions of OME from three specific subsections to precipitation varied significantly on the sub-seasonal scale. During the onset of summer monsoons, the AS region ranked first as an important oceanic source, followed by the BOB and the SCS, whereas during the withdrawal of summer monsoons, this order was reversed. (4) The interannual anomalies of OME-based precipitation from the SCS and the BOB regions are negatively correlated with those outside the AS region.

On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States

The central United States is plagued by frequent catastrophic flooding, such as the flood events of 1993, 2008, 2011, 2013, 2014 and 2016. The goal of this study is to examine whether it is possible to describe the occurrence of flood and heavy precipitation events at the sub-seasonal scale in terms of variations in the climate system. Daily streamflow and precipitation time series over the central United States (defined here to include North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, West Virginia, Kentucky, Ohio, Indiana, and Michigan) are used in this study. We model the occurrence/non-occurrence of a flood and heavy precipitation event over time using regression models based on Cox processes, which can be viewed as a generalization of Poisson processes. Rather than assuming that an event (i.e., flooding or precipitation) occurs independently of the occurrence of the previous one (as in Poisson processes), Cox processes allow us to account for the potential presence of temporal clustering, which manifests itself in an alternation of quiet and active periods. Here we model the occurrence/non-occurrence of flood and heavy precipitation events using two climate indices as time-varying covariates: the Arctic Oscillation (AO) and the Pacific-North American pattern (PNA). We find that AO and/or PNA are important predictors in explaining the temporal clustering in flood occurrences in over 78% of the stream gages we considered. Similar results are obtained when working with heavy precipitation events. Analyses of the sensitivity of the results to different thresholds used to identify events lead to the same conclusions. The findings of this work highlight that variations in the climate system play a critical role in explaining the occurrence of flood and heavy precipitation events at the sub-seasonal scale over the central United States.

Dual effects of the winter monsoon on haze‐fog variations in eastern China

AbstractPrevious studies have revealed a negative correlation between the East Asian winter monsoon and wintertime haze‐fog events in China. The winter monsoon reduces haze‐fog by advecting away aerosol particles and supplying clean air through cold waves. However, it is found that the frequency of haze‐fog events on subseasonal time scales displays no correlation with typical winter monsoon indices. The results show that the accumulating and maintaining effects of calm weather related to the Siberian High, which is also a part of the monsoon circulation system, are equally important for the development of haze‐fog events during winter. Correlation analysis indicates that subseasonal variations in haze‐fog are closely related to the intensity of the Siberian High (r = 0.49). The Siberian High may increase the occurrence of haze‐fog events by reducing the near surface wind speed and enhancing the stratification stability. To quantify the contribution of these diverse effects of the winter monsoon on the variations in haze‐fog events, we analyzed haze‐fog events during periods of cold wave activity and calm weather separately and contrasted the relative contributions of these two effects on different time scales. On the subseasonal scale, the effect of the Siberian High was 2.0 times that of cold waves; on the interannual scale, the effect of cold waves was 2.4 times that of the Siberian High. This study reveals the dual effects of the East Asian winter monsoon on wintertime haze‐fog variations in eastern China and provides a more comprehensive understanding of the relationship between the monsoon and haze‐fog events.

Weather noise impact on the uncertainty of simulated water balance components of river basins

ABSTRACTAssessments of hydrological response to climatic changes are characterized by different types of uncertainties. Here, the uncertainty caused by weather noise associated with the chaotic character of atmospheric processes is considered. A technique for estimating such uncertainty in simulated water balance components based on application of the land surface model SWAP and the climate model ECHAM5 is described. The technique is applied for estimating the uncertainties in the simulated water balance components (precipitation, river runoff and evapotranspiration) of some northern river basins of Russia. It is shown that the larger the area of a basin the less the uncertainty. This dependency is smoothed by differences in natural conditions of the basins. Analysis of the spectral densities of water balance components shows that a river basin filters out high-frequency harmonics of spectral density of precipitation (corresponding to synoptic or sub-seasonal scale) during its transformation into evapotranspiration and especially into runoff.EDITOR D. KoutsoyiannisASSOCIATE EDITOR H. Kreibich

CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States

Abstract. This paper explored the potential of a global climate model for sub-seasonal forecasting of precipitation and 2 m air temperature. The categorical forecast skill of 10 precipitation and temperature indices was investigated using the 28-year sub-seasonal hindcasts from the Climate Forecast System version 2 (CFSv2) over the contiguous United States (CONUS). The forecast skill for mean precipitation and temperature as well as for the frequency and duration of extremes was highly dependent on the forecasting indices, regions, seasons, and leads. Forecasts for 7- and 14-day temperature indices showed skill even at weeks 3 and 4, and generally were more skillful than precipitation indices. Overall, temperature indices showed higher skill than precipitation indices over the entire CONUS region at sub-seasonal scale. While the forecast skill related to mean precipitations was low in summer over the CONUS, the number of rainy days, number of consecutive rainy days, and number of consecutive dry days showed considerably high skill for the western coastal region. The presence of active Madden–Julian Oscillation (MJO) events improved CFSv2 weekly mean precipitation forecast skill over most parts of the CONUS, but it did not necessarily improve the weekly mean temperature forecasts. The 30-day forecasts of precipitation and temperature indices calculated from the downscaled monthly CFSv2 forecasts were less skillful than those calculated directly from CFSv2 daily forecasts, suggesting the usefulness of CFSv2 for sub-seasonal hydrological forecasting.

Sub-seasonal Predictability of the Onset and Demise of the Rainy Season over Monsoonal Regions

Sub-seasonal to seasonal (S2S) retrospective forecasts from three global coupled models are used to evaluate the predictability of the onset and demise dates of the rainy season over monsoonal regions. The onset and demise dates of the rainy season are defined using only precipitation data. The forecasts of the onset and demise dates of the rainy season are based on a hybrid methodology that combines observations and simulations. Although skillful model precipitation predictions remain challenging in many regions, our results show that they are skillful enough to identify onset and demise dates of the rainy season in many monsoon regions at sub-seasonal (approximately 30 days) lead-times in retrospective forecasts. We verify sub-seasonal prediction skill for the onset and demise dates of the rainy season over South America, East Asia, and Northern Australia. However, we find low prediction skill for the onset and demise of the rainy season on sub-seasonal scales over the Indian monsoon region. This information would be valuable to sectors related to water management.

Investigation of the drought–flood abrupt alternation of streamflow in Poyang Lake catchment during the last 50 years

Drought–flood abrupt alternation (DFAA) is one of the remarkable manifestations of the summer monsoon anomaly at the subseasonal scale and can result in severe damage. This study identified and analyzed DFAA in terms of streamflow in the Poyang Lake catchment over the last 50 years based on a DFAA index (DFAAI). The study also investigated the intra-annual distribution characteristics and long-term tendencies associated with DFAA, as well as the relationship with precipitation patterns. A statistical analysis showed that drought-to-flood events in the Poyang Lake catchment generally occur in March and April, while flood-to-drought events occur in July and August. A Mann–Kendall test indicated a long-term decreasing trend in DFAAI in March and April and a slight increasing trend in July and August; however, the trends were not statistically significant. Flood-to-drought events occurred more frequently than did drought-to-flood events at the decadal scale, especially in the 1960s and 1970s. The particular distribution of precipitation in the Poyang Lake catchment mainly determined the occurrence patterns of DFAA events, but intensive human activities are also significant factors that have decreased and mitigated DFAA disasters since the 1980s in the Poyang Lake catchment.

The 20th century transitions in basic and extreme monsoon rainfall indices in India: Comparison of the ETCCDI indices

The mean and extreme matrices of the monsoon rainfall in India not only play an important role in depicting the global monsoon climate, but also their spatiotemporal patterns influence the socio-economic profile of a major proportion of the country's huge population. Given the reported conflicting trends at the global and national scales, the present study investigates the 20th century (1901–2004) changes in monsoon rainfall of India, particularly focusing the indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) to facilitate a global comparison. Result of this comprehensive analysis, which includes the response of fifteen indices over two study periods (i.e., 1901–1940 and 1961–2004), indicates clear signals of change with respect to the period and region of study and the choice of the ETCCDI indices. While wet day frequency, low-to-moderate events and consecutive wet days (CWD) exhibit a prominent transition from a pre-1940 wetting to a post-1960 drying tendency over a large part of the central-north India (CNI), both the wet and dry extremes have occurred in a spatially less consistent manner during the recent decades. For consecutive dry days (CDD), the reported less clear global signals could be related to the timescale of analysis, as our sub-seasonal scale results display consistent changes compared to that of the seasonal and annual scales. The Palmer Drought Severity Index (PDSI) provides clear indications of a post-1960 non-stationarity, showing changes in the mean as well as variance. Based on the partial Mann–Kendall test (PMK), some of the identified rainfall trends during 1961–2004 are found to be influenced more by the tropical Indian Ocean sea surface temperatures than the El Niño–Southern Oscillation index. These results have important implications for formulating the water resource management strategy, particularly over the drying central and northern parts of the country.