Interannual Rainfall Variability Research Articles

Regional-scale seasonal forecast of surface water availability in a semi-arid environment: The case of Ceará State in Northeast of Brazil

Study region:Ceará (Brazil). Study focus:Considerable intra- and inter-annual variability of rainfall in this semi-arid region lead to strong temporal variations in water availability. To store and supply water in times of water scarcity, tens of thousands of freshwater reservoirs have been built over time, most of which are unmonitored. Here, we develop a hydrological forecasting system for the entire state of Ceará which integrates satellite-based monitoring of reservoir water storage, bias-corrected seasonal weather forecasts and hydrological modeling of freshwater availability. We test and demonstrate the applicability of this system by conducting experiments with historic data, hindcasts and forecasts. New hydrological insights for the region:The assimilation of in-situ and Sentinel-1 based observations of reservoir fillings into the hydrological model WASA-SED proved to be feasible and an important step in the modeling of available water resources dynamics. Hydrological simulations for January to June from 1990–2019 based on meteorological observations resulted in a median average NRMSE between observed and modeled reservoir fillings of strategic reservoirs of 29.51%. The comparison of observed and predicted precipitation from two different seasonal forecasting systems were in the same order of magnitude (i.e. 19.51% and 24.52%). Hindcast experiments suggested the superposition of uncertainties of different model components. Efforts are currently being made to further test and improve the developed integrated framework as part of the operational service.

Impact of shifting patterns of the South Asian High on interannual variability of Indian summer monsoon rainfall in homogeneous regions

AbstractThe movement and intensity indices of the South Asian High (SAH), an upper‐level anticyclonic‐circulation over the Tibetan Plateau, play a crucial role in Indian summer monsoon rainfall (ISMR) during June–September. The present study aims to document (i) the association between SAH and ISMR in the periods of June–July–August (JJA) and July–August–September (JAS), and (ii) the ISMR changes at different spatial and temporal scales. The Bayesian change‐point detection method identifies 1981 as change point and the dataset has been split into two groups (past climate:1940–1980 and current climate:1981–2020) to analyze temporal variations in ISMR. Results indicate that the northwest–southeast index (INW–SE), north–south index (INS) and intensity index (IINT) of the SAH are strongly correlated (˜0.67, ˜0.60, and ˜0.51, respectively) with ISMR whereas the east–west index (IEW) is negatively correlated (˜−0.52) during the JAS season. This relation was stronger in the past climate than the current climate, except for the IINT index during the JAS season. The INW–SE and INS indices are closely associated with all‐India, northwest India (NWI), and central India (CI) rainfall, whereas IINT is associated with south peninsular India (SPI) during the JAS season. The increased rainfall over NWI and SPI in the current climate is strongly associated with positive INS and IINT indices, respectively, during the JAS season. The northeast India (NEI) rainfall did not show any association with SAH indices; however, the IEW is strongly associated with increased NEI rainfall during El Niño years. A significant positive (negative) relation between meridional (zonal) wind shear and SAH indices except the IEW index is observed. Further, the positive (negative) SAH indices favor more (moderate) ISMR due to strong positive (negative) moisture anomalies. The study demonstrates the movement and intensity of the SAH in the dynamical shifts of seasonal rainfall patterns across the Indian homogeneous regions.

Hydrological classification of mine pit lakes using modelling experiments

With the growing global prevalence of open-pit mining activities, there is an increasing necessity for sustainable mine life cycle plans with an early outlook towards mine closure. A major consideration in mine closure planning is the potential formation of lakes in the mine void and how these “pit lakes” can be managed to minimise risks and, if possible, create benefits. Understanding the long-term interactions between pit lakes, groundwater, and surface water systems is essential for that purpose. While numerous site-specific studies have been undertaken, there have been no studies that aim to provide a general, broadly applicable understanding of how pit lake hydrology relates to geographical context, and no efforts to hydrologically classify pit lakes using geographical criteria. This research employs an integrated generic pit lake water balance model to examine mine pit lake interactions with the surrounding surface water and groundwater. Simulating 243 scenarios, the influence of five input factors (climate, hydraulic conductivity, regional groundwater level, catchment area and pit slope) on pit lake behaviour up to 6000 years beyond the closure of the mine was considered. The assessment focused on four pit lake hydrological attributes once the system reached equilibrium: water level, time to equilibrium, the fraction of days where the pit recharges groundwater, and the fraction of days where there is surface overflow from the lake. All scenarios were assigned to one of five hydrological classes based on the interactions between the pit lake and the surrounding surface water and groundwater. Our findings show that, in many contexts, general data on climate type and subsurface hydraulic conductivity can yield reliable predictions of a pit lake's long-term hydrological classification without having to develop a detailed, site-specific pit lake model. The classification needs improvements in non-arid climates where inter-annual variation in rainfall is pronounced. The pit lake classification is particularly valuable for first-pass risk assessments to determine whether site-specific modelling is required.

Basin shift of tropical convection impact on the Western China Autumn Rainfall interannual variability

Basin shift of tropical convection impact on the Western China Autumn Rainfall interannual variability

Influence of mixed Rossby-Gravity waves on the North-East monsoon rainfall over south India

The northeast (NE) monsoon contributes considerable annual rainfall over southern peninsular India. Here, an attempt has been made to evaluate the role of convectively coupled mixed Rossby-Gravity (MRG) waves on the variabilities of NE monsoon rainfall. The gridded rainfall data from 1980 to 2021 from the India Meteorological Department shows large interannual variability in NE monsoon rainfall over southern peninsular India. Wavelet analysis of outgoing longwave radiation (OLR) data shows the dominance of short-period waves over the equatorial Indian Ocean during the years with above-normal NE monsoon rainfall compared to below-normal rainfall years. The space–time spectral analysis further confirms the dominance of short-period westward propagating convectively coupled equatorial waves (CCEW) during above-normal NE monsoon rainfall years. In contrast, the eastward component of CCEWs dominates during the below-normal rainfall years. The empirical orthogonal function (EOF) analysis of MRG waves filtered OLR data shows that the first two leading modes explain more than 14 % of variability over the Indian Ocean domain. Moreover, the vertically integrated moisture flux convergence indicates the role of MRG wave in triggering the extreme rainfall over southern peninsular India and also offers favorable conditions for the formation of cyclogenesis and, thereby, inducing heavy rainfall over the South Indian domain. Thus, the results suggest that the westward propagating MRG waves play a seminal role in modulating the NE monsoon rainfall over southern peninsular India.

Unraveling the role of the western North Pacific circulation anomaly in modulating Indian summer monsoon rainfall variability beyond ENSO

The Indian summer monsoon (ISM) rainfall interannual variability is known to be strongly linked to the El-Niño–Southern Oscillation (ENSO). This linear relationship is the primary factor in controlling the interannual variation in ISM precipitation. However, there are many outlier cases, and such deviations pose significant challenges in seasonal prediction over this region. Here we show that such challenges can be attributed to anomalous atmospheric pressure patterns in the Western North Pacific (WNP) region. The anticyclonic circulation anomaly over WNP region causes the easterly wind toward the Indian subcontinent, leading to positive precipitation anomalies with stronger low-level moist convergence, while the cyclonic circulation decreases ISM precipitation. The linear baroclinic model simulation results further support that the WNP circulation pattern can serve as an independent factor for forecasting precipitation over India. The WNP circulation anomaly play the crucial role generating ISM precipitation particularly for July and September. Our study suggests that the role of the WNP circulation anomaly should be carefully considered as the secondary prevailing mechanism on the subseasonal timescale during the boreal summer in addition to the ENSO signal.

Intensifying droughts render more Sahel drylands unsuitable for cultivation

Two-fifth of the world's population will be confronted by dire land and water shortage for food production by 2050. Here we provide nuanced insights into the Sahel dryland dynamics and rationale behind its underperforming croplands amid climate extremes. We develop a gridded multi-criteria drought index for the growing season (June-October) and analyse its spatial and temporal degree of uniformity to designate the drought, climate and cultivable zones. Evidence is drawn from Sahelian Sudan, representing 1.03 million km2 of the African Sahel, during 1940–2020. Results show that cultivation of marginal lands has persisted apace. The peak areas of these marginal lands explain ∼50 % of the variations in crop yield, considering the two staple crops, sorghum and millet. Furthermore, the low yields mismatch the steadily growing planted areas of these crops. Compared to wet conditions, droughts expand (shrink) the median size of hyper-arid (arid) area by 466 % (46 %), limiting farming opportunities for 3.5–35.8 % of the croplands. The northernmost borderline of the arid zone determines the rainfed suitability, but potentially cultivable arid areas require contingency risk-reduction plans. Conversely, semi-arid and dry sub-humid zones reveal areas endowed with uniform climate. Skillful climate forecasting should thus guide policymaking towards sustainable agriculture therein. The paper suggests paths towards more effective agricultural policy interventions. Agricultural production entails the Sahel drought being defined in terms of agricultural impacts instead of meteorological conditions. Land use planners and inhabitants must relieve the plight of misconceiving and overlooking the fact of intrinsic interannual rainfall variability. Determining what a dangerous drought is for the Sahel agriculture sector or system is crucial. Sahel farming systems should opt for highly flexible agricultural practices based on the above-identified cultivable areas.

Using the Observed Variations of the Start Date of the Rainy Season over Central America for Its Reliable Seasonal Outlook

Abstract We introduce a simple method to define the start and the end of the rainiest part of the year as the first and the last day of the year when the daily rain rate is more or less than the annual mean climatological rain rate for a region or at a given grid point of the rainfall analysis, respectively. A novelty of this work is the adoption of a perturbation technique to generate a total of 1001 ensemble members to account for observational and analysis uncertainties. This allows for a probabilistic estimate of the start and retreat dates of the rainy season at the granularity of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), version 6, rainfall analysis over Central America. The seasonal cycle of the IMERG rainfall analysis is also found to verify with in situ observations in the region. Many large-scale climate drivers affect regional rainfall, often with complex interactions that affect the onset date, retreat date, and magnitude of the seasonal rainfall cycle, making it difficult to predict the length or total quantity of seasonal rainfall using climate drivers alone. Once an onset date is established, however, this metric alone can be more indicative of both the length and total seasonal rainfall anomaly than predicting how the climate drivers will interact to affect the quantity and duration of upcoming seasonal rainfall. The local relationships of the start date with seasonal length and rainfall anomaly are leveraged to produce effective seasonal outlooks of the rainy season for the region by just monitoring the start date variations. Significance Statement The start date and retreat date of the rainy season in Central America are defined every year, precisely to a specific date from our proposed definition of it. This is possible because the region exhibits a strong seasonality of the rainfall. As a result, the year-to-year (interannual) variation of the seasonal rainfall during the rainy season is also determined by the variations in the length of the season that are usually overlooked in fixed calendar seasons. We define the start or retreat date of the rainy season as the first or the last day of the year when the daily rain rate exceeds or falls below the average daily rainfall from 2001 to 2022, respectively. We also find that both start and retreat date variations independently influence the length and total seasonal rainfall of the rainy season. Consequently, these relationships are leveraged to provide an outlook of the forthcoming rainy season from the diagnosis of the variations of its onset date, which is shown to be an effective predictor with significant useful seasonal prediction skills.

Interannual variation of summer southwest monsoon rainfall over the monsoon core regions of the eastern Bay of Bengal and its relationship with oceans

The study looked at how summer monsoon rainfall in the eastern Bay of Bengal area changes from year to year due to Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Study used rainfall data and sea surface temperature data to see these variations. It's found that during ENSO positive phase, rainfall decreased in the eastern coastal region of the Bay of Bengal but increased in the northern Indo-Myanmar region. The opposite happened during ENSO negative phase. The study used a special analysis method called EOF and Morlet wavelet power-spectrum analysis to look for important patterns in the rainfall data and did correlation analysis to understand what causes abnormal rainfall in these regions. The study also found that the local convection and water vapor flux during ENSO positive phase are related to the anomalous rainfall in the Monsoon Core region. Rainfall is made stronger by the unusual anticyclone circulation in the upper troposphere. A strong/weak Mainland Indochina southwest monsoon (MSwM) in the positive or negative phase of ENSO can bring excess/less moisture to wet/dry the local southwest summer rainfall. In northern Indo-Myanmar, the anomalous rainfall is not only relied on the intensity of the MSwM but also the frequency of western disturbances also influences the regional rainfall, and further study need to develop.

Annual and Interannual Rainfall Variability in Indonesia Using Empirical Orthogonal Function (EOF) Analysis and Its Response to Ocean-Atmosphere Dynamics

We investigate rainfall variability in Indonesia using the Empirical Orthogonal Function (EOF) method. The analysis starts by taking three main modes of EOF results, namely EOF1, EOF2, and EOF3. The EOF1 region is southern Indonesia, from southern Sumatra to Timor Island, parts of Kalimantan, parts of Sulawesi, and parts of Irian Jaya. The EOF2 region is located in northwestern Indonesia and includes the northern part of Sumatra and the northwestern part of Kalimantan. The EOF3 region covers Maluku. This study aims to analyze the annual and inter-annual variability of rainfall in anticipation of the threat of hydrometeorological disasters. Based on the correlation value of the principal component (PC) with the dipole mode index (DMI) and Niño3.4 index, it has a period similar to El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Rainfall in Indonesia is very sensitive to sea surface temperature (SST) in the southeastern Indian Ocean and the central Pacific Ocean, which means that rainfall patterns in Indonesia can change significantly if SST in the region changes.

Diverse impacts of the Indian summer monsoon on ENSO among CMIP6 models and its possible causes

Abstract This study examines the performance of 52 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in capturing the effects of the Indian summer monsoon (ISM) on the evolution of El Niño–Southern Oscillation (ENSO). The ISM’s impacts on ENSO show a substantial diversity among the models. While some models simulate the strength of the impacts comparable to observations, others represent much weaker influences. Results indicate that the diversity is highly related to inter-model spread in interannual variability of ISM rainfall among the models. Models with a larger ISM rainfall variability simulate stronger ISM-induced anomalies in precipitation and atmospheric circulation over the western North Pacific during the monsoon season. As a result, these models exhibit larger wind anomalies induced by monsoon on the south flank of the anomalous circulation in the western Pacific, thereby influencing subsequent ENSO evolution more significantly by causing stronger air-sea coupling processes over the tropical Pacific.

Causal Relationships between Monsoon Systems, the Mascarene High, and Rainfall Variability over Botswana, Southern Africa

Climate change and variability pose significant threats to southern Africa, with projected continuous drought in Botswana. This study examines the causal relationships between African-Indian monsoon systems (East Africa, West Africa, and Peninsula India), the Mascarene High, and interannual rainfall variability over Botswana. Using statistical analysis and mapping techniques (Pearson correlation statistics and convergent cross mapping (CCM)), the authors analysed the impact of these weather systems on rainfall variability from 1979 to 2021. The findings reveal significant negative associations between these weather systems and interannual rainfall variability in Botswana, shedding light on their crucial roles in shaping the region's rainfall patterns. Bidirectional causation between different regions and the Mascarene High was observed, emphasising the interconnectedness of rainfall patterns. Significant findings include the bidirectional causation between Botswana and West Africa rainfall during March–May (MAM) and October–December (OND) seasons. In addition, the authors also observed bidirectional causation between Botswana and Peninsula Indian rainfall during the OND season. The study highlights the potential of these factors in predicting extreme events and assists in planning for potential risks associated with rainfall variability in Botswana to promote community awareness and education on climate change and variability, water conservation, and sustainable livelihood.

Little evidence of hysteresis in regional precipitation, when indexed by global temperature rise and fall in an overshoot climate simulation

Abstract Society has set the aim of stabilising climate at key temperature thresholds, such as global warming at or below 1.5°C or 2.0°C above preindustrial levels. However, greenhouse gas emissions are failing to decline, and if they continue on their current trajectory it is likely that such thresholds will be crossed in the decades ahead. Because of this risk, there is an emerging focus on overshoot, where, for a temporary period, global warming is allowed to cross critical thresholds to reach a peak value before decreasing to the desired limit. A key question about overshoots is whether there are hysteresis effects—that is, whether global or regional climate has properties that differ between the phase of global warming increase and the phase of decreasing. Here, we analyse temperature and precipitation data from five Earth System Models (ESMs) forced by the SSP5-3.4-OS CMIP6 overshoot scenario. We look at the level of precipitation during two periods of near-identical global warming: one whilst temperatures are rising, and the other when they are falling. For global means, we find a statistically significant difference between precipitation values during the two periods. This is an example of hysteresis, as the reversion to an earlier global warming state results in a level of global rainfall which is different from that observed when warming was increasing. Spatial disaggregation of rainfall differences between the two near-identical warming levels shows the largest differences in the tropical region, which are statistically significant for four of the five ESMs. When considering much smaller regions, including parts of the tropics, there remains some evidence of hysteresis. However, the differences are no longer statistically significant against a background of substantial interannual rainfall variability. We discuss the implications of our findings for climate impacts assesments.

Routine Climate Monitoring in the State of Hawai‘i: Establishment of State Climate Divisions

Abstract The Hawaiian Islands have some of the most spatially diverse rainfall patterns on Earth, affected by prevailing trade winds, midlatitude disturbances, tropical cyclones, and complex island topography. However, it is the only state in the United States that does not have assigned climate divisions (boundaries defining climatically homogeneous areas), which excludes it from many national climate analyses. This study establishes, for the first time, official climate divisions for the state of Hawai‘i using cluster analysis applied to monthly gridded rainfall data from 1990 to 2019. Twelve climate divisions have been identified: two divisions were found each for the islands of Kaua‘i (Leeward Kaua‘i and Windward Kaua‘i), O‘ahu (Waianae and Ko‘olau), and Maui County (Leeward Maui Nui and Windward Maui Nui), and six divisions were identified for Hawai‘i Island (Leeward Kohala, Windward Kohala, Kona, Hawai‘i Mauka, Ka‘u, and Hilo). The climate divisions were validated using a statewide area-weighted division-average rainfall index which successfully captured the annual cycle and interannual rainfall variations in the statewide average rainfall series. Distinct rainfall seasonality features and interannual/decadal variability are found among the different divisions; Leeward Maui Nui, Leeward Kaua‘i, Kona, and Hawai‘i Mauka displayed the most significant rainfall seasonality. The western Hawai‘i Island divisions show the most significant long-term decreasing trends in annual rainfall during the past 100 years (ranging from −2.5% to −5.0% per decade). With these climate divisions now available, Hawai‘i will have access to numerous operational climate analyses that will greatly improve climatic research, monitoring, education, and outreach, as well as forecasting applications.

CON-SST-RAIN: Continuous Stochastic Space–Time Rainfall generation based on Markov chains and transposition of weather radar data

In this study, we present CON-SST-RAIN, a novel stochastic space–time rainfall generator specialized for model-based urban drainage design and planning. CON-SST-RAIN is based on Markov Chains for sequences of dry/rainy days and uses stochastic storm transposition (SST) to generate realistic rainfall fields from weather radar data. CON-SST-RAIN generates continuous areal rainfall time series at arbitrary lengths. We propose a method for updating the Markov Chains by each passing year to better incorporate low-frequency variation in inter-annual rainfall values. The performance of CON-SST-RAIN is tested against multi-year records from rain gauges at both point and catchment scales. We find that updating the Markov Chains has a significant impact on the inter-annual variation of rainfall, but has little effect on mean annual/seasonal precipitation and dry/wet spell lengths. CON-SST-RAIN shows good preservation of extreme rain rates (including sub-hourly values) compared to observed rain gauge data and the original SST framework.

Investigating the Morphometry and Hydrometeorological Variability of a Fragile Tropical Karstic Lake of the Yucatán Peninsula: Bacalar Lagoon

Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more than 52.7 km in length, with widths varying from 0.18 km to 2.28 km. It has a volume of 554.4 million cubic meters, with an average depth of 8.85 m, reaching depths of up to 26 m in the north and featuring sub-lacustrine dolines in the south, with depths of 38 m, 48.5 m, and 63.6 m. The study reveals seasonal variations in surface water temperature, closely linked to air temperature (r = 0.89), and immediate responses of water levels to hydrometeorological events. Water level fluctuations also exhibit seasonal patterns that are correlated with regional aquifer conditions, with a lag of 2 months after seasonal rainfall. Interannual variability in rainfall and water levels was observed. From 2010 to 2012, rainfall consistently remained below its mean climatic value, due to a prolonged La Niña event, while the exceptionally wet conditions in 2020 were also associated with La Niña. Extreme and anomalous hydrometeorological events, such as those following tropical storm Cristobal in 2020, revealed the fragility of Bacalar Lagoon, causing a notable transformation in lake color and transparency, shifting it from its typical oligotrophic state to eutrophic conditions that lasted longer than a year. These color changes raise questions about the factors impacting ecological health in tropical karstic regions. Additional factors affecting water quality in the BL in 2020, such as deforestation, coastline changes, and urban growth, warrant further investigation. Our study can serve as a starting landmark.

Projections of future streamflow for Australia informed by CMIP6 and previous generations of global climate models

Projections of streamflow under future climate are essential for developing adaptation strategies in the water and related sectors. This paper presents nationwide streamflow projections for Australia informed by climate change signals in CMIP6 GCMs and compares the projections with those from CMIP5 GCMs. The modelled future runoff projections driven by CMIP5 and CMIP6 GCMs are relatively similar for far southern Australia. The median projection is a 50% reduction in mean annual runoff in far southwest Australia and 20% reduction in far southeast Australia by 2046–2075 relative to 1976–2015 under the high SSP5-8.5/RCP8.5 global warming scenario. The vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. As most of the runoff in far southern Australia occurs in winter and spring, the lower winter rainfall translates to a significant reduction in annual runoff. It is therefore prudent to plan and manage for a reduction in future water resources, particularly in the densely populated and important agricultural regions in southeast Australia. There is less agreement between GCMs in the summer rainfall projection, with the CMIP6 GCMs generally projecting a wetter future (or smaller decrease in rainfall) than the CMIP5 GCMs. The modelled median projection for mean annual runoff is a 10% reduction in the south-east coast, 5% reduction in the north-east coast and little change in northern Australia. More GCMs project an increase rather than a decrease in the interannual variability of rainfall, and this would further amplify multi-year hydrological droughts.

Trend analysis and change-point detection of monsoon rainfall in Uttarakhand and its impact on vegetation productivity

This study analyzes the long-term spatio-temporal changes and trend analysis in rainfall using the data from 1901 to 2020 and its impact on vegetation from 2000 to 2020 across districts of Uttarakhand. The Pettitt test was employed to detect the abrupt change point in time frame, while the Mann-Kendall (MK) test was performed to analyze the rainfall trend. Results show that the most of the districts exhibited significant negative trend of rainfall in monsoon, except two districts. Out of 13 districts, 4 districts recorded noteworthy rainfall declining trend for the monsoon season at 0.05% significance level, while the insignificant negative trend of rainfall was detected for 7 districts of Uttarakhand. Furthermore, the significant negative trend (-2.23) was recorded for overall monsoon rainfall of Uttarakhand. Based on the findings of change detection, the most probable year of change detection was occurred primarily after 1960 for most of the districts of Uttarakhand. A significant decline rainfall was detected after 1960 while after 1970 interannual variability of rainfall was recorded to be increased. The analysis of month wise cumulative gross primary productivity (GPP) for 13 districts with rainfall trends shows that there is significant impact of rainfall trend on GPP during month of June and it gradually reduces for subsequent monsoon months. It was observed that the GPP of region is increasing at rate of 9.1 gCm-2d-1 in the region since 2000. Based on sensitivity analysis, the GPP of cropped area of region is more sensitive towards rainfall than forest area of Uttarakhand.

Correction: The Southern Annular Mode: its influence on interannual variability of rainfall in North Australia

Correction: The Southern Annular Mode: its influence on interannual variability of rainfall in North Australia

Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations

Abstract. We present the Monsoon Mission Coupled Forecast System version 2.0 (MMCFSv2) model, which substantially upgrades the present operational MMCFSv1 (version 1) at the India Meteorology Department. The latest 25 years (1998–2022) of retrospective seasonal coupled hindcast simulations of the Indian summer monsoon with April initial conditions from Coupled Forecast System Reanalysis are discussed. MMCFSv2 simulates the tropical wind, rainfall, and temperature structure reasonably well. MMCFSv2 captures surface winds well and reduces precipitation biases over land, except over India and North America. The dry bias over these regions remained like in MMCFSv1. MMCFSv2 captures significant features of the Indian monsoon, including the intensity and location of the maximum precipitation centers and the large-scale monsoon circulation. MMCFSv2 improves the phase skill (anomaly correlation coefficient) of the interannual variation of Indian summer monsoon rainfall (ISMR) by 17 % and enhances the amplitude skill (normalized root mean square error) by 20 %. MMCFSv2 shows improved teleconnections of ISMR with the equatorial Indian and Pacific oceans. This 25-year hindcast dataset will serve as the baseline for future sensitivity studies of MMCFSv2.