Variability Of Monsoon Rainfall Research Articles

Climate warming and summer monsoon breaks drive compound dry and hot extremes in India

Considering the severe impacts of compound dry and hot extremes, we examine the primary drivers of CDHEs during the summer monsoon in India. Using ERA5 reanalysis, we show that most of the CDHEs in India occur during the droughts caused by the summer monsoon rainfall deficit. Despite a decline in the frequency of summer monsoon droughts in recent decades, increased CDHEs are mainly driven by warming and dry spells during the summer monsoon particularly in the Northeast, central northeast, and west central regions. A strong land-atmospheric coupling during droughts in the summer monsoon season leads to frequent CDHEs in the Northwest and southern peninsular regions. Furthermore, regional variations in land-atmospheric coupling cause substantial differences in the CDHE occurrence in different parts of the country. Summer monsoon rainfall variability and increased warming can pose a greater risk of compound dry and hot extremes with severe impacts on various sectors in India.

The mechanism linking the variability of the Antarctic sea ice extent in the Indian Ocean sector to Indian summer monsoon rainfall.

The study investigates the mechanism of teleconnection between the variability of sea ice extent (SIE) in the Indian Ocean sector of the Southern Ocean and the variability of Indian summer monsoon rainfall. We utilized reanalysis, satellite, in-situ observation data, and model output from the coupled model intercomparison project phase 5 (CMIP5) from 1979 to 2013. The empirical orthogonal function (EOF) and correlation analysis show that the first and third modes of principal component (PC1 and PC3) of SIE in the Indian Ocean sector during April–May–June (AMJ) are significantly correlated with the second mode of principal component (PC2) of Indian summer monsoon rainfall. The reanalysis data revealed that the changes in the SIE in the Indian Ocean sector excite meridional wave train responses along the Indian Ocean for both principal component modes. Positive (negative) SIE anomalies based on first and third EOFs (EOF1 and EOF3), contribute to the strengthening (weakening) of the Polar, Ferrel, and Hadley cells, inducing stronger (weaker) convective activity over the Indian latitudes. The stronger (weaker) convective activity over the Indian region leads to more (less) rainfall over the region during high (low) ice phase years. Furthermore, a stronger (weaker) polar jet during the high (low) ice phase is also noted. The selected CMIP5 models captured certain atmospheric teleconnection features found in the reanalysis. During AMJ, the SIE simulated by the NorESM1-M model was significantly positively correlated with Indian summer monsoon rainfall, whereas the IPSL-CM54-LR model showed a negative correlation.

Effect of ENSO on Seasonal Temperature Over Tamil Nadu

Increased concentration of greenhouse gases is expected to alter the radiative balance of atmosphere, causing increase in temperature and changes in precipitation patterns. Climate variability has been principal source of fluctuations in Indian food production. Even though there is no long-term trend, inter - annual variability of Indian monsoon rainfall leading to frequent droughts and floods has profound influence on agriculture and intern, national economy. It is well recognized that El Niño / Southern Oscillation (ENSO) is the dominant mode of climate variability on seasonal to inter-annual scales and its impacts are felt worldwide. ENSO often affects seasonal temperature, precipitation and thus crop yields in many regions, however, the overall impacts of ENSO on global yields are uncertain Maximum and minimum average temperature was calculated for different seasons such as Cold Weather Period (CWP), Hot Weather Period (HWP), South West Monsoon (SWM), North East Monsoon (NEM) for each El Niño, La Niña and neutral years at various districts of Tamil Nadu. Relation between ENSO and temperature was analyzed by computing the anomaly in temperature at different districts of Tamil Nadu. The temperature deviation between the ENSO and neutral phases was not significant as the deviation was within + 0.3oC in all the seasons.

Amplitude modulation of sunspot cycles and its influence on monsoon rainfall variability and occurrences of major droughts in India

Amplitude modulation of sunspot cycles and its influence on monsoon rainfall variability and occurrences of major droughts in India

Indian Monsoon Teleconnections and the Impact of Correcting Tropical Diabatic Heating

Abstract The Indian summer monsoon is partly modulated by persistent remote forcing from the tropical Indo-Pacific, evident in the dominant observed teleconnection patterns, namely, El Niño–Southern Oscillation (ENSO) and the equatorial Indian Ocean Oscillation (EQUINOO). In the atmosphere, these teleconnections are presumably driven by diabatic heating, primarily associated with the release of latent heat in condensation with rainfall. However, in coupled atmosphere–ocean models, biases result in large systematic errors in tropical heating. This study seeks to understand the extent that teleconnections are forced by tropical heating and whether or not correcting tropical heating biases improves monsoon prediction skill. We examine a series of reforecasts made with the NCEP Climate Forecast System version 2 in which the “added heating” technique is applied to largely remove tropical heating biases. We isolate the ENSO and EQUINOO signals and examine the ability to reproduce and predict these teleconnections in the model run with and without tropical heating correction. Improving ENSO and EQUINOO-related heating does result in increased prediction skill in monsoon circulation teleconnection patterns. Prediction of other relevant tropical and subtropical circulation indices is improved; however, the impact on the Indian monsoon as a whole is limited. EQUINOO exhibits large internal variability in the model, and despite imposing realistic EQUINOO heating, the monsoon circulation is relatively insensitive in the model. This suggests that either the EQUINOO teleconnection in nature does not emerge as a forced response to tropical heating, and/or the model is unable to reproduce the relationship due to separate deficiencies. Significance Statement India receives over 80% of its annual rainfall during the summer in association with the monsoon. A strong socioeconomic dependence on agriculture makes India sensitive to year-to-year variations in monsoon rainfall, thus predicting and understanding such variations is of great value. Coincident changes in tropical atmospheric heating (and cooling) may be more predictable and presumably impact the monsoon; however, causality has yet to be demonstrated and quantified, particularly for the tropical Indian Ocean. This motivates our modeling study to diagnose the role of tropical heating for the Indian monsoon and whether or not correcting heating errors improves monsoon prediction.

Link between monsoon rainfall variability and agricultural drought in the semi-arid region of Maharashtra, India

Link between monsoon rainfall variability and agricultural drought in the semi-arid region of Maharashtra, India

Aerosol distribution during spring and summer and its relationship with Inter-Annual variability of summer monsoon rainfall over Indian region

The inter-annual variability of aerosol over Indian region and its possible implications on the Indian summer monsoon is investigated using Aerosol Optical Depth (AOD) data from Moderate Resolution Imaging Spectrometer (MODIS) during the period 2001 to 2016. An attempt has been made to link the seasonal aerosol distribution over South Asia during spring and summer season to Indian Summer Monsoon Rainfall (ISMR) distribution. AOD derived from MODIS Terra observations shows large spatial inhomogeneity and characteristic variability with distinct temporal distributions. The pre-monsoon (spring) seasons (March-April-May; MAM) is characterized by high aerosol concentration over north-west part of India along with IGP region. During the south-west monsoon (summer) seasons (June-July-August-September; JJAS), wide area of high aerosol loading along Indo Gangetic plains extending from North Arabian sea through north-west India and up to Himalayan foothills. The regional rainfall distribution and its relationship with spatial and temporal aerosol distribution are then evaluated. Further, distinct variability in the aerosol distribution with respect to excess, deficit and normal monsoon years are analysed to understand the role of aerosols on the inter-annual variability of ISMR. Monthly aerosol distribution over Central India [CI;15°-25oN;75°-88oE] and Indo Gangetic plain [IGP;25°- 350N;70°- 900E] shows increased aerosol loading during deficit rainfall years and corresponding delay in the monthly rainfall peak. This study emphasises the active role of regional aerosol loading on regulating the inter-annual variability of regional Indian summer monsoon rainfall.

Temporal Trends of Rainfall and Temperature over Two Sub-Divisions of Western Ghats

Rainfall, along with temperature, is the major component of the hydrological cycle, and its spatiotemporal variability is essential from both scientific and practical perspectives. Due to the recent rise in temperatures all over the world, there are quite a number of conflicting trends in inter-annual variability in monsoon rainfall and temperature over the Western Ghats. The Western Ghats, next to the Himalayas, are the major watershed for the major south Indian rivers. In this study, an attempt has been made to understand the monthly, inter-seasonal, and inter-annual trends of rainfall and temperature over the two meteorological sub-divisions, namely Konkan Goa, and Coastal Karnataka. Monthly rainfall data for the period of 1977 to 2016 and temperature data from 1980 to 2016 are used. According to the analysis, maximum rainfall occurs during the summer, whereas the least rainfall occurs during the winter. The parametric, linear regression analysis and student t-test have been used to identify the existence of trends and to determine the changes in rainfall over the time period. An effort has been made to understand the relationship between ISMR (Indian Summer Monsoon Rainfall) and the ENSO phenomenon and to investigate whether the rainfall over WG is influenced by the ENSO phenomenon or not. Results reveal that although there is increased rainfall over Konkan and Goa, while declining over coastal Karnataka, the changes over both the sub-divisions were statistically significant. Considering rainfall in different seasons, there is a significant change during the monsoon season only. The study further reveals that there is increasing rainfall over Konkan and Goa and decreasing rainfall over Coastal Karnataka. Furthermore, no statistically significant trend (positive or negative) was evident in any of the seasons. All temperature trends were positive. The results of this study may prove useful in the preparation of climate change mitigation and adaptation strategies by understanding the patterns of rainfall over WG. Doi: 10.28991/HIJ-SP2022-03-03 Full Text: PDF

Dominant Anomalous Circulation Patterns of Tibetan Plateau Summer Climate Generated by ENSO-Forced and ENSO-Independent Teleconnections

Abstract The interannual variability of Tibetan Plateau (TP) summer climate has tremendous impacts on both regional hydrological cycles and global climate. In this study, we extract four dominant modes of the summertime large-scale circulation over the TP and surrounding areas from both the observation and simulations by a coupled general circulation model, CAS-FGOALS-f3-L. Based on the 10-member tropical Pacific pacemaker experiments, the ENSO-forced and ENSO-independent signals are isolated, each of which is represented by two dominant modes. The two ENSO-forced modes correspond to ENSO developing and decaying summer, respectively. The positive phase of the developing (decaying) ENSO-related mode is characterized by an anomalous baroclinic cyclone (anticyclone) over the western TP excited by the variations of the tropical summer monsoon rainfall. During the El Niño developing summer, the Indian monsoon rainfall variation is driven by an eastward shift of the Walker circulation due to warm anomalies in the equatorial central-eastern Pacific, whereas during the El Niño decaying summer it is caused by the basinwide warming in the tropical Indian Ocean. The two ENSO-independent modes are associated with the summer North Atlantic Oscillation (SNAO) and the circumglobal teleconnection (CGT) pattern, respectively. The positive phases of the SNAO- and CGT-related modes are characterized by an anomalous anticyclone over the western TP and zonal cyclone–anticyclone dipole pattern over the TP, respectively, both of which are associated with mid- and high-latitude stationary Rossby wave trains.

Interannual crisscross pattern observed in South Asian monsoon rainfall and its relationship with aerosols

This study examines the interannual variability of South Asian summer monsoon rainfall (SAMR) using a linear trend analysis for the recent 17-year period from 2000 to 2016. The trends in SAMR analyzed from multiple rainfall datasets show a unique crisscross like pattern over South Asia and its surrounding oceans. Significant positive trends in SAMR occur over the middle and south Bay of Bengal (BOB) and North-West India (NWI) aligned in SE-NW direction. Similarly, significant negative trends are observed over North-East India and head Bay of Bengal (NEI) as well as over the middle and south Arabian Sea (AS) oriented in SW-NE direction. Western Ghats make an exception to this pattern, where significant positive trends have been observed. Interestingly, the trends in aerosol optical depth (AOD) for the same period closely follow the trends in SAMR. The relationship of AOD averaged over each of the significant aerosol trend regions with the SAMR suggest aerosol induced suppression in moisture transport from a region covering Southern Arabian Sea and Bay of Bengal played a dominant role over the negative trend regions. However, the decreased aerosols over the Northwest India due to significant positive trends in rainfall reduced dust transport from the Arabian Peninsula towards eastern parts of South Asia resulting in an increase in anthropogenic aerosols from local sources. This caused significant drying over the NEI and AS regions through aerosol indirect effects. Further, Aerosol direct radiative effects due to natural and anthropogenic sources inferred from the climate forcing estimates confirmed their role in positive trends and the indirect effects inferred from satellite cloud products depicted a strong association with negative trends, thus maintaining the observed crisscross pattern.

How extreme could the near term evolution of the Indian Summer Monsoon rainfall be?

We provide a methodology to estimate possible extreme changes in seasonal rainfall for the coming decades. We demonstrate this methodology using Indian summer monsoon rainfall as an example. We use an ensemble of 1669 realizations of Indian summer monsoon rainfall from selected seasonal prediction systems to estimate internal variability and show how it can exacerbate or alleviate forced climate change. Our estimates show that for the next decade there is a ∼60% chance of wetting trends, whereas the chance of drying is ∼40%. Wetting trends are systematically more favoured than drying with the increasing length of the period. However, internal variability can easily negate or overwhelm the wetting trends to give temporary drying trends in rainfall. This provides a quantitative explanation for the varying trends in the past observational record of rainfall over India. We also quantify the likelihood of extreme trends and show that there is at least a 1% chance that monsoon rainfall could increase or decrease by one fifth over the next decade and that more extreme trends, though unlikely, are possible. We find that monsoon rainfall trends are influenced by trends in sea-surface temperatures over the Niño3.4 region and tropical Indian Ocean, and ∼1.5° cooling or warming of these regions can approximately double or negate the influence of climate change on rainfall over the next two decades. We also investigate the time-of-emergence of climate change signals in rainfall trends and find that it is unlikely for a climate change signal to emerge by the year 2050 due to the large internal variability of monsoon rainfall. The estimates of extreme rainfall change provided here could be useful for governments to prepare for worst-case scenarios and therefore aid disaster preparedness and decision-making.

Dynamical and moist thermodynamical processes associated with Western Ghats rainfall decadal variability

The Western Ghats (WG) is a vast montane forest ecosystem known for its biodiversity and endemism. The decadal variability of WG summer monsoon rainfall is higher than most of the other regions of India. Spectrum and wavelet analysis of century-long rainfall observation confirm significant decadal variability (at 90% confidence level) in WG rainfall, with amplification of magnitude (about 1.5–2 times) in the recent years compared to the previous half-century. Correlation analysis of WG rainfall with Indian (Pacific) Ocean sea surface temperature (SST) shows a significant relationship during 1901–1942 (1943–1977 and 1978–2010). The analysis associated with decadal rainfall variability reveals the dominance of dynamical processes during 1901–1942 and moist thermodynamical processes during 1943–1977 and 1978–2010. The study concludes that decadal variability of WG rainfall is robust and the forcing mechanisms are essentially maintained by the Indian and Pacific Oceans variability, adding value in developing decadal prediction systems and may also contribute towards understanding the evolution of WG ecosystem.

Extent of diurnal cycle of rainfall and its intra seasonal variation over coastal Tamil Nadu during north east monsoon season

The diurnal variation of north east monsoon rainfall of coastal Tamil Nadu represented by four coastal stations Chennai Nungambakkam (Nbk), Chennai Meenambakkam (Mbk), Nagapattinam (Npt) and Pamban (Pbn) was studied in detail based on hourly rainfall data of rainy days only, for the period 1 Oct-31 Dec for the 47/48 year period 1969-2016/2017. Mean Octet rainfall and its anomaly were computed for the 8 octets 00-03,…., 21-24 hrs of the day and the anomaly was tested for statistical significance. Various analysis for the individual months of Oct, Nov, Dec and the entire period Oct-Dec were separately conducted. The basic technique of evolutionary histogram analysis supplemented by harmonic analysis of octet mean rainfall anomaly was used to detect the diurnal cycle signal. Two indices named as diurnal variation of rainfall index and coefficient of mean absolute octet rainfall anomaly representing the intensity of diurnal variation in dimensionless numbers were defined, computed and interpreted.
 The analysis based on the above techniques revealed that the diurnal signal which shows an early morning maximum and late afternoon minimum of octet rainfall is well defined in Oct, decreases in Nov and further decreases in Dec for all the 4 stations. Though the diurnal variation manifests a well defined pattern in Dec the signal is not statistically significant in most cases. For Nbk and Mbk there is a weak secondary peak of octet rainfall anomaly occurring in the forenoon and afternoon respectively in Oct and Dec suggesting the presence of semi-diurnal variation of rainfall. Stationwise, the diurnal signal is most well defined for each month/season in Pbn followed by Npt, Nbk and then Mbk.
 
 The physical causes behind the diurnal signal and its decrease as the north east monsoon season advances from Oct to Dec have been deliberated. The well known feature of nocturnal maximum of oceanic convection influencing a coastal station with maritime climate and the higher saturation at the lower levels of the upper atmosphere in the early morning hours have been advanced as some of the causes. For the much more complex feature of decrease of diurnal signal with the advancement of the season, the decrease of minimum surface temperature over coastal Tamil Nadu from Oct to Dec causing an early morning conceptual land breeze has been shown as one of the plausible causes based on analysis of temperature and wind. Scope for further work based on data from automatic weather stations, weather satellites and Doppler Weather Radars has been discussed.

Assessment of Indian Ocean upwelling changes and its relationship with the Indian monsoon

Present study aims to assess the Indian Ocean upwelling zones and its relationship with the Indian monsoon. Assessment of upwelling zones are examined by using fine resolution satellite sea surface temperature (SST), chlorophyll-a concentration and reanalysis nitrate (NO 3 ), surface wind speed, mean sea level pressure (MSLP) and precipitation products. This study uses the high-resolution (12 km) satellite era reanalysis Indian Monsoon Data Assimilation and Analysis (IMDAA) data for the evaluation of upwelling and summer monsoon relationship. Long-term and decadal trends of SST, chlorophyll-a and NO 3 are estimated by employing the non-parametric Mann–Kendall test and Sen's slope method for the summer monsoon (June–September) and winter monsoon (October–December) season. Long-term seasonal trends suggest the significant warming and weakening of upwelling over western tropical Indian Ocean, however, decadal trends reveals that signal is more prominent during the period 1999–2008. In the northern Bay of Bengal, the NO 3 trend shows significant seasonality. A zonal SST gradient-based index (upwelling index (UI)) is adopted to identify the upwelling zones, results are presented for the prominent upwelling zones of Somalia and Oman. The UI is used to understand the long-term and decadal variation of Somalia and Oman upwelling intensity with the Indian summer monsoon MSLP, surface wind and rainfall variations. Results suggest that Oman upwelling intensity is highly correlated with the monsoon heat low over the northwest India and Pakistan and Indian summer monsoon rainfall over the core region. However, MSLP over the Indian subcontinent and rainfall over the west coast of India is correlated with the Somalia upwelling intensity. Here, we show that surface wind over the central Arabian Sea (monsoon trough) region are correlated with the intensity of UI of Oman (Somalia). The decadal study provides compelling evidence that the relationship between MSLP, near surface wind, upwelling and ISMR weakens over time in Somalia coast but in the Oman coast this relationship strengthens with recent decades. • Long-term and decadal trends of SST, chlorophyll-a and NO 3 are investigated over the Indian Ocean. • Significant warming and decline of chlorophyll-a is depicted in the western and North Indian Ocean. • Recovery of upwelling zones in the western Indian Ocean is evident in the recent decade (2009-2018). • Strong correlation between the Oman upwelling intensity and Indian summer monsoon rainfall is found in the recent decades.

Assessment of regional and global climate models for the investigation of monsoon rainfall variability over the North‐West Himalayan region

AbstractPresent study is an attempt to evaluate the rainfall pattern obtained from the selected Regional Climate Models (RCMs) which participated in Coordinated Regional Climate Downscaling Experiment for the South Asia region (CORDEX‐SA) and the Global Climate Models (GCMs) which participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) with respect to the high‐resolution ground‐based Indian Meteorological Department (IMD) rainfall data during the principal monsoon season (i.e., June 1 to September 30) from 1976 to 2000 over the states of Himachal Pradesh (HP) and Uttarakhand (UK) in North‐West Himalayan Region (NWH). Considering the inter‐model differences, the multimodel means (MMM) of both of the CORDEX‐SA and CMIP5 models have been compared with the IMD gridded rainfall data set so as to find out the suitable set of models (whether CORDEX‐SA or CMIP5) for assessing the rainfall variability over this region. The CORDEX‐MMM indicates a poor relationship with IMD data compared with the CMIP5‐MMM over both the NWH states of HP and UK. CMIP5‐MMM demonstrates better ability to represent extreme rainfall events as compared with the CORDEX‐MMM. Significant bias has been noted for both of the CORDEX‐MMM and CMIP5‐MMM with respect to the IMD data sets, nevertheless, differences were found to be minimal in case of CMIP5‐MMM in comparison to CORDEX‐MMM. In case of the simulated rainfall from CMIP5‐MMM over both HP and UK regions, RMSE, MAE and bias, all are much smaller than that of the CORDEX‐MMM simulations with respect to the IMD rainfall data. Further to this, CMIP5‐MMM notably performs better in case of delineating extreme cases of inter‐annual variability except CORDEX‐MMM for the state of UK. Results presented here encompass the entire spectrum of summer monsoon rainfall variability, for example, daily, monthly, seasonal, inter‐annual and extreme rainfall over the NWH region. Based on the comprehensive analysis of global and regional models, it is noted that the CMIP5‐MMM has better ability to simulate rainfall pattern during monsoon season compared with the finer resolution CORDEX‐MMM for both the states of UK and HP. Therefore, it is suggested that CMIP5 models may be utilized to investigate the rainfall variability at daily, seasonal and interannual scales over the NWH region for various forcing scenarios rather than the outputs from CORDEX‐SA domain.

Multi-scale variability and predictability of Indian summer monsoon rainfall

Multi-scale variability and predictability of Indian summer monsoon rainfall

Inter-annual variability of Indian monsoon rainfall in the JMA’s seasonal ensemble prediction system in relation to ENSO and IOD

Inter-annual variability of Indian monsoon rainfall in the JMA’s seasonal ensemble prediction system in relation to ENSO and IOD

Simulation of Indian summer monsoon rainfall, interannual variability and teleconnections: evaluation of CMIP6 models

We analyse the performance of global climate models of 6 $$\mathrm{th}$$ generation of Coupled Model Intercomparison Project (CMIP6) in simulating climatological summer monsoon rainfall over India, interannual variability (IAV) of all-India summer monsoon rainfall (ISMR) and its teleconnections with rainfall variability over equatorial Pacific and Indian Oceans. The multimodel ensemble mean (MME) of 61 CMIP6 models shows the best skill in simulating mean monsoon rainfall over India compared to the MMEs of 6 $$\mathrm{th}$$ generation atmosphere-only models (AMIP6) and the previous generations of Atmospheric and Coupled Model Intercomparison Projects (AMIPs and CMIPs). Systematic improvement and reduction in bias are evident from lower to higher AMIPs/CMIPs. Still, there exists dry bias over a narrow region of the monsoon zone of central India besides wet and cold bias over the surrounding oceans. The persistence of errors in atmosphere-only models hints that the source of errors could be with atmosphere models. Fifteen CMIP6 models selected through objective criteria, perform the best in simulating mean monsoon, IAV of ISMR, the strong inverse relationship between ISMR and Boreal summer El Niño-Southern Oscillation (ENSO), and the inverse relationship between all-India rainfall and north–west tropical Pacific rainfall in June. Several models reproduce the dipole structure of Equatorial Indian Ocean Oscillation (EQUINOO) with the centres over western and eastern equatorial Indian Ocean. But, ISMR-EQUINOO relationship in many of them is opposite to the observed. Our analysis implies the need for capturing ISMR-EQUINOO link to improve the simulation of IAV of ISMR which is crucial for reliable monsoon prediction and projection.

The application of generalized additive models (GAMs) for assessing the teleconnection of ENSO and IOD with monsoon rainfall variability over Krishna river basin, India

The present study examines the teleconnection of ENSO andIOD with monsoon rainfall (MN) and low, moderate and heavy rainfall events (LREs, MREs and HREs) over the Krishna river basin, using generalized additive models (GAMs) with suitable distribution. The outputs of GAMs indicate that, Poisson distribution is superior to the other distributions in assessing the teleconnection of ENSO-MN-IOD in the study area. Further, study resultsshowed that ENSO and IOD has significant (p < 0.001) non-linear responses to theLREs, MREs,HREs and MN. The influence of IOD on MN, LREs, MREs and HREs found positive on some parts, while negative on the other parts of the study area (i.e. heterogeneous in nature). While, ENSO has consistent negative influence on MN, LREs, MREs and HREsin the study area. Furthermore, La Niña and El Niño had positive and negative influenceon the MN, LREs, MREs and HREs respectively. The study outcomes will help the hydro-meteorologist and water related policy makers in modeling the impact of monsoon rainfall system on water, agriculture and allied sectors.

Summer monsoon rainfall variations and its association with atmospheric circulations over Sudan

This work investigates the factors influencing summer (June–September: JJAS) monsoon rainfall variability over Sudan using monthly datasets from multiple sources from 1980 to 2018. Sequential Mann-Kendall, Empirical Orthogonal Function (EOF), composite and correlation analysis were utilized to investigate the spatio-temporal rainfall variability in Sudan, and its associated circulations and teleconnections. Results revealed a significant increase in JJAS rainfall during the study period. The wet condition was found with accompanying convergence winds at low levels and divergence in the upper levels, while the dry conditions were due to the weakening of convergence moisture transport. A hot Sea Surface Temperature anomalies over the Eastern Pacific Ocean (Nino3.4) are associated with dry conditions,whilst cold anomalies are associated with wet conditions. There was correlation between the first EOFs JJAS rainfall and EOFs SSTs teleconnections NINO3.4. IOD, PDO, and NAO, exhibited moderate to strong positive correlations of 62.5% in average. However, the second mode of SSTs teleconnections EOFS revealed a low positive correlation of 46.4% in average, excluding the strong negative impact of NINO3.4–73%. In different regions in Sudan, the influences of NINO3.4 are much stronger in the south, west and central regions (0.71, −0.71 and −0.72). And IOD exhibited much impact in the south and west regions (0.73, 0.74). The southern and western regions had the highest correlation with PDO and NAO. ENSO and IOD also tend to extend summer rainfall season. Therefore, this research serves as the baseline study for further work to examine the impact of SSTs teleconnections on summer rainfall in Sudan (starting, cessation and extremes), thereby providing a reasonable basis for monitoring and predicting similar conditions in the future.