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Net heat flux (Qnet) and its components from four reanalysis (NCEP‐2, CFSR, ERA5, and MERRA) and two blended products (OAFlux & TropFlux) are compared with in situ observation (two Research Moored Array for African‐Asian‐Australian Monsoon Analysis and Prediction buoys and one Woods Hole Oceanographic Institution buoy) over the north Indian Ocean to quantify their uncertainties in daily, seasonal, and annual scales. These comparisons provide the present status of Qnet error in most state of the art reanalysis/blended products. The root‐mean‐square error (RMSE) remains similar to the RMSE a decade earlier, despite more observation and improved models and reanalysis methods. However, there is a clear separation of flux quality from the older generation of reanalysis (NCEP‐2) to the newer production of reanalysis (MERRA, CFSR, and ERA5). While individually ERA5 provides the best estimate, the ensemble mean (i.e., average of ERA5, CFSR, MERRA, TropFlux, and OAFlux) is very close to ERA5 both in terms of correlations and RMSE and provides the most reliable estimate by virtue of removal of some of the uncertainties in estimation of flux by each of the flux products. A significant reduction of RMSE in Qnet estimates from 100 W/m2 (in NCEP‐2) to 45 W/m2 (in the ensemble mean) is considerable progress. It is noteworthy that all the recent flux products estimate the increasing trend of Qnet in the north Bay of Bengal and subseasonal fluctuations with significant fidelity. Also, in the south of equator location vigorous subseasonal fluctuations in boreal winter are well captured. We believe that this is significant progress in the estimation of Qnet over the Indian Ocean.

Simulation of the spatial and temporal structure of the monsoon intraseasonal oscillations (MISOs), which have effects on the seasonal mean and annual cycle of Indian summer monsoon (ISM) rainfall, remains a grand challenge for the state-of-the-art global coupled models. Biases in simulation of the amplitude and northward propagation of MISOs and related dry rainfall bias over ISM region in climate models are limiting the current skill of monsoon prediction. Recent observations indicate that the convective microphysics of clouds may be critical in simulating the observed MISOs. The hypothesis is strongly supported by high fidelity in simulation of the amplitude and space-time spectra of MISO by a coupled climate model, when our physically based modified cloud microphysics scheme is implemented in conjunction with a modified new Simple Arakawa Schubert (nSAS) convective parameterization scheme. Improved simulation of MISOs appears to have been aided by much improved simulation of the observed high cloud fraction and convective to stratiform rain fractions and resulted into a much improved simulation of the ISM rainfall, monsoon onset and the annual cycle.

The quest for one of the most dominant processes controlling the large-scale circulations in the tropics is unraveled. The impact of cloud microphysical processes is known to have effects on rainfall and local atmospheric thermodynamics, however, its effect on the prevailing mean circulations is not yet studied. Two sets of coupled global climate model experiments (ICE and NO ICE microphysics) reveal that ice microphysics improves the strength of the Hadley circulation with respect to observation. Results pinpoint that ICE simulation enhances high cloud fraction (global tropics: ~59 %, India: ~51 %) and stratiform rain (global tropics: ~5 %, India: ~15 %) contribution. ICE and NO ICE cloud microphysics impacts differently on the outgoing longwave radiation (OLR), tropospheric temperature, surface shortwave and longwave radiation. The effect of ice microphysics reduces OLR, which signifies deeper convection in the ICE run. The global annual average of the net radiation flux (shortwave and longwave) at the surface in ICE run (108.1 W/m2) is close to the observation (106 W/m2), which is overestimated in NO ICE run (112 W/m2). The result of apparent heat source term over the land and ocean surface eventually modifies regional Hadley circulation. Thus, the effect of ice microphysics in the global coupled model is important not only because of microphysics but also due to the radiation feedbacks. Therefore, better ice-phase microphysics is required in the new generation of climate forecast model, which may lead to improvements in the simulation of monsoon.

This study examines the relationship between clouds and sea surface temperatures (SSTs) during Indian Summer Monsoon (ISM). Observation reveals dominance of high-level clouds in the monsoon region. NCEP Climate Forecast System version 2 (CFSv2) is able to replicate the observed high-level cloud fractions although it underestimates the magnitude. Cloud–SST relationship for observation depicts dominance of positive correlation over equatorial Indian Ocean region which is well recapitulated in CFSv2 simulations. To investigate the most dominating patterns of interannual variability of rainfall, SST and clouds, empirical orthogonal function (EOF) analysis is performed on seasonal JJAS (June–September) dataset. EOF analysis signifies that high-level clouds are highly correlated with rainfall for observations during ISM season. This study has also investigated relationship of clouds and El Nino Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD) during ISM period. Interannual variations of clouds connote significant correlation with ENSO index (Nino 3/Nino 3.4). First principal component (PC1) of high-level clouds and ENSO index indicate significant negative correlation. EOF analysis based on observation also connotes that first mode (second) of EOF analysis is associated with ENSO (IOD). It is also confirmed by maximum covariance analysis (MCA). CFSv2 is also able to depict the significant negative correlation between PC1 of high-level clouds and ENSO index. Observation based second principal component (PC2) of high-level clouds and IOD index exhibits significant positive correlation. It gives indication that PC2 of observed high-level clouds can be associated with IOD. In contrast, PC2 of CFSv2 simulated high-level cloud and IOD index are not correlated. EOF analysis based on CFSv2 shows that the first mode of EOF analysis is associated with ENSO; however, second mode of EOF is not related with IOD. MCA analysis also supports these findings. It means that CFSv2 has good ability to represent ENSO as compared with IOD.

The budget analysis of microphysical process rates based on Modern Era Retrospective-analysis for Research and Applications (MERRA) products are presented in the study. The relative importance of different microphysical process rates, which is crucial for GCMs, is investigated. The autoconversion and accretion processes are found to be vital for Indian Summer Monsoon (ISM). The map-to-map correlations are examined between observed precipitation and MERRA reanalysis. The pattern correlations connote the fidelity of the MERRA datasets used here. Results of other microphysical parameters (e.g. ice water content from CloudSat, high cloud fraction from CALIPSO and MODIS, latent heating from TRMM, cloud ice mixing ratio from MERRA) are presented in this study. The tropospheric temperature from reanalysis product of MERRA and NCEP are also analyzed. Furthermore, the linkages between cloud microphysics production rates and dynamics, which are important for North–South tropospheric temperature gradient for maintaining the ISM circulation, are also discussed. The study demonstrates the microphysical process rates, which are actually responsible for the cloud hydrometeors and precipitation formation on the monsoon intraseasonal oscillations timescale. Cloud to rain water auto-conversion and snow accretion rates are the dominant processes followed by the rain accretion. All these tendency terms replicates the similar spatial patterns as that of precipitation. The quantification of microphysical process rates and precipitation over different regions are shown here. The freezing rate is also imperative for the formation of cloud ice as revealed by the observation. Freezing rates at upper level and snow accretion at middle level may have effect on latent heating release. Further it can modulate the north–south temperature gradient which can influence the large-scale monsoon dynamics. The rain water evaporation is also considered as a key aspect for controlling the low level moisture convergence (source of water vapor) in ISM. This study has highlighted the importance of detailed microphysical production rates for warm and mixed-phase cloud processes, which is a major source of uncertainty in the climate models. Better understanding of these processes will definitely add value to the present generation climate models. Therefore the hypothesis/pathway emerged from the present study may be helpful for the future model development research.

A detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and Pacific Ocean basin, with special emphasis on the Indian land region. The simulated seasonal mean and the inter-annual standard deviations of rainfall, upper and lower level atmospheric circulations and Sea Surface Temperature (SST) tend to be more skillful as the lead forecast time decreases (5 month lead to 0 month lead time i.e. L5–L0). In general spatial correlation (bias) increases (decreases) as forecast lead time decreases. This is further substantiated by their averaged value over the selected study regions over the Indian and Pacific Ocean basins. The tendency of increase (decrease) of model bias with increasing (decreasing) forecast lead time also indicates the dynamical drift of the model. Large scale lower level circulation (850 hPa) shows enhancement of anomalous westerlies (easterlies) over the tropical region of the Indian Ocean (Western Pacific Ocean), which indicates the enhancement of model error with the decrease in lead time. At the upper level circulation (200 hPa) biases in both tropical easterly jet and subtropical westerlies jet tend to decrease as the lead time decreases. Despite enhancement of the prediction skill, mean SST bias seems to be insensitive to the initialization. All these biases are significant and together they make CFSv2 vulnerable to seasonal uncertainties in all the lead times. Overall the zeroth lead (L0) seems to have the best skill, however, in case of Indian summer monsoon rainfall (ISMR), the 3 month lead forecast time (L3) has the maximum ISMR prediction skill. This is valid using different independent datasets, wherein these maximum skill scores are 0.64, 0.42 and 0.57 with respect to the Global Precipitation Climatology Project, CPC Merged Analysis of Precipitation and the India Meteorological Department precipitation dataset respectively for L3. Despite significant El-Nino Southern Oscillation (ENSO) spring predictability barrier at L3, the ISMR skill score is highest at L3. Further, large scale zonal wind shear (Webster–Yang index) and SST over Nino3.4 region is best at L1 and L0. This implies that predictability aspect of ISMR is controlled by factors other than ENSO and Indian Ocean Dipole. Also, the model error (forecast error) outruns the error acquired by the inadequacies in the initial conditions (predictability error). Thus model deficiency is having more serious consequences as compared to the initial condition error for the seasonal forecast. All the model parameters show the increase in the predictability error as the lead decreases over the equatorial eastern Pacific basin and peaks at L2, then it further decreases. The dynamical consistency of both the forecast and the predictability error among all the variables indicates that these biases are purely systematic in nature and improvement of the physical processes in the CFSv2 may enhance the overall predictability.

The present study explores the impact of two different microphysical parameterization schemes (i.e. Zhao and Carr, Mon Wea Rev 125:1931-1953, 1997:called as ZC; Ferrier, Amer Meteor Soc 280-283, 2002: called as BF) of National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) on Indian summer monsoon (ISM). Critical relative humidity (RHcrit) plays a crucial role for the realistic cloud formation in a general circulation model (GCM). Hence, impact of RHcrit along with microphysical scheme on ISM is evaluated in the study. Model performance is evaluated in terms of simulation of rainfall, lower and upper tropospheric circulations, cloud fraction, cloud condensate and outgoing longwave radiation (OLR). Climatological mean features of rainfall are better represented by all the sensitivity experiments. Overall, ZC schemes show relatively better rainfall patterns as compared to BF schemes. BF schemes along with 95 % RHcrit (called as BF95) show excess precipitable water over Indian Ocean basin region, which seems to be unrealistic. Lower and upper tropospheric features are well simulated in all the sensitivity experiments; however, upper tropospheric wind patterns are underestimated as compared to observation. Spatial pattern and vertical profile of cloud condensate is relatively better represented by ZC schemes as compared to BF schemes. Relatively more (less) cloud condensate at upper level has lead to relatively better (low) high cloud fraction in ZC (BF) simulation. It is seen that OLR in ZC simulation have great proximity with observation. ZC (BF) simulations depict low (high) OLR which indicates stronger (weaker) convection during ISM period. It implies strong (weak) convection having stronger (weaker) updrafts in ZC (BF). Relatively more (less) cloud condensate at upper level of ZC (BF) may produce strong (weak) latent heating which may lead to relatively strong (weak) convection during ISM. The interaction among microphysics, thermodynamics, and dynamics works in tandem through a closed feedback loop.

A possible link between preonset land atmospheric conditions and the Indian summer monsoon rainfall (ISMR) is explored. It is shown that, the preonset positive (negative) rainfall anomaly over northwest India, Pakistan, Afghanistan, and Iran is associated with decrease (increase) in ISMR, primarily in the months of June and July, which in turn affects the seasonal mean. ISMR in the months of June and July is also strongly linked with the preonset 2 m air temperature over the same regions. The preonset rainfall/2 m air temperature variability is linked with stationary Rossby wave response, which is clearly evident in the wave activity flux diagnostics. As the predictability of Indian summer monsoon relies mainly on the El Nino–Southern Oscillation (ENSO), the found link may further enhance our ability to predict the monsoon, particularly during a non-ENSO year.

Simulation of Indian summer monsoon features by latest coupled model of National Centers for Environmental Prediction (NCEPs) Climate Forecast System version 2 (CFSv2) is attempted in its long run. Improvements in the simulation of Indian summer monsoon as compared with previous version (CFSv1) is accessed and areas which still require considerable refinements are introduced. It is found that, spatial pattern of seasonal mean rainfall and wind circulations are more realistic in CFSv2 as compared with CFSv1. Variance and northward propagation of intraseasonal oscillation (ISO), which also contribute to the seasonal mean rainfall are remarkably improved. However, the central Indian dry bias still persists and amplified. Pervasive cold bias in surface (2m air temperature) as well as in the whole troposphere is further increased in CFSv2. These cold biases may be partly attributed to the lack of model's ability to realistically simulate the ratio of convective and stratiform rainfall. Sea-surface temperature (SST) over the Indian Ocean is underestimated in CFSv2. However, CFSv1 shows east-west dipole structure in the bias. The teleconnection of El Nino Southern Oscillation (ENSO) and Indian summer monsoon rainfall (ISMR) in terms of NiA±o3 SST and monsoon rainfall correlation is more realistic in the latest version of the model. Overall, there are substantial improvements in CFSv2 as compared with CFSv1, but it has to evolve further to realistically simulate the mean and variability of ISMR.

This study investigates the El Nino Southern Oscillation (ENSO) teleconnections to tropical Indian Ocean (TIO) and their relationship with the Indian summer monsoon in the coupled general circulation model climate forecast system (CFS). The model shows good skill in simulating the impact of El Nino over the Indian Oceanic rim during its decay phase (the summer following peak phase of El Nino). Summer surface circulation patterns during the developing phase of El Nino are more influenced by local Sea Surface Temperature (SST) anomalies in the model unlike in observations. Eastern TIO cooling similar to that of Indian Ocean Dipole (IOD) is a dominant model feature in summer. This anomalous SST pattern therefore is attributed to the tendency of the model to simulate more frequent IOD events. On the other hand, in the model baroclinic response to the diabatic heating anomalies induced by the El Nino related warm SSTs is weak, resulting in reduced zonal extension of the Rossby wave response. This is mostly due to weak eastern Pacific summer time SST anomalies in the model during the developing phase of El Nino as compared to observations. Both eastern TIO cooling and weak SST warming in El Nino region combined together undermine the ENSO teleconnections to the TIO and south Asia regions. The model is able to capture the spatial patterns of SST, circulation and precipitation well during the decay phase of El Nino over the Indo-western Pacific including the typical spring asymmetric mode and summer basin-wide warming in TIO. The model simulated El Nino decay one or two seasons later, resulting long persistent warm SST and circulation anomalies mainly over the southwest TIO. In response to the late decay of El Nino, Ekman pumping shows two maxima over the southern TIO. In conjunction with this unrealistic Ekman pumping, westward propagating Rossby waves display two peaks, which play key role in the long-persistence of the TIO warming in the model (for more than a season after summer). This study strongly supports the need of simulating the correct onset and decay phases of El Nino/La Nina for capturing the realistic ENSO teleconnections. These results have strong implications for the forecasting of Indian summer monsoon as this model is currently being adopted as an operational model in India.

Cloud dynamics played a fundamental role in defining Indian summer monsoon (ISM) rainfall during drought of 2009. The anomalously negative precipitation was consistent with cloud properties. Although, aerosols inhibited the growth of cloud effective radius in the background of sparse water vapor, their role is secondary. The primary role, however, is played by the interactive feedback between cloud microphysics and dynamics owing to reduced efficient cloud droplet growth, lesser latent heating release and shortage of water content. Cloud microphysical processes were instrumental for the occurrence of ISM drought 2009.

This study has identified probable factors that govern ISMR predictability. Furthermore, extensive analysis has been performed to evaluate factors leading to the predictability aspect of Indian Summer Monsoon Rainfall (ISMR) using uncoupled and coupled version of National Centers for Environmental Prediction Coupled Forecast System (CFS). It has been found that the coupled version (CFS) has outperformed the uncoupled version [Global Forecast System (GFS)] of the model in terms of prediction of rainfall over Indian land points. Even the spatial distribution of rainfall is much better represented in the CFS as compared to that of GFS. Even though these model skills are inadequate for the reliable forecasting of monsoon, it imparts the capacious knowledge about the model fidelity. The mean monsoon features and its evolution in terms of rainfall and large-scale circulation along with the zonal and meridional shear of winds, which govern the strength of the monsoon, are relatively closer to the observation in the CFS as compared to the GFS. Furthermore, sea surface temperature–rainfall relation is fairly realistic and intense in the coupled version of the model (CFS). It is found that the CFS is able to capture El Nino Southern Oscillation ISMR (ENSO-ISMR) teleconnections much strongly as compared to GFS; however, in the case of Indian Ocean Dipole ISMR teleconnections, GFS has the larger say. Coupled models have to be fine-tuned for the prediction of the transition of El Nino as well as the strength of the mature phase has to be improved. Thus, to sum up, CFS tends to have better predictive skill on account of following three factors: (a) better ability to replicate mean features, (b) comparatively better representation of air–sea interactions, and (c) much better portrayal of ENSO-ISMR teleconnections. This study clearly brings out that coupled model is the only way forward for improving the ISMR prediction skill. However, coupled model’s spurious representation of SST variability and mean model bias are detrimental in seasonal prediction.

The latest version of the state-of-the-art global land–atmosphere–ocean coupled climate forecast system of NCEP has shown considerable improvement in various aspects of the Indian summer monsoon. However, climatological mean dry bias over the Indian sub-continent is further increased as compared to the previous version. Here we have attempted to link this dry bias with climatological mean bias in the Eurasian winter/spring snow, which is one of the important predictors of the Indian summer monsoon rainfall (ISMR). Simulation of interannual variability of the Eurasian snow and its teleconnection with the ISMR are quite reasonable in the model. Using composite analysis it is shown that a positive snow anomaly, which is comparable to the systematic bias in the model, results into significant decrease in the summer monsoon rainfall over the central India and part of the Equatorial Indian Ocean. Decrease in the summer monsoon rainfall is also found to be linked with weaker northward propagation of intraseasonal oscillation (ISO). A barotropic stationary wave triggered by positive snow anomaly over west Eurasia weakens the upper level monsoon circulation, which in turn reduces the zonal wind shear and hence, weakens the northward propagation of summer monsoon ISOs. A sensitivity experiment by reducing snow fall over Eurasian region causes decrease in winter and spring snow depth, which in turn leads to decrease in Indian summer monsoon rainfall. Results from the sensitivity experiment corroborate with those of composite analysis based on long free run. This study suggests that further improvements in the snow parametrization schemes as well as Arctic sea ice are needed to reduce the Eurasian snow bias during winter/spring, which may reduce the dry bias over Indian sub-continent and hence predictability aspect of the model.

Level 3 (3A25) TRMM Precipitation Radar (PR) data are used for 13 years period (1998–2010) to prepare climatology of TRMM PR derived near surface rain (Total rain) and rain fractions for the 4-months duration of Indian Summer Monsoon season (June–September) as well as for individual months. It is found that the total rain is contributed mostly (99 %) by two rain fractions i.e. stratiform and convective rain fractions for the season as well as on the monthly basis. It is also found that total rain estimates by PR are about 65 % of the gauge measured rain over continental India as well as on sub-regional basis. Inter-annual variability of TRMM-PR rain estimates for India mainland and its sub-regions as well as over the neighboring oceanic regions, in terms of coefficient of variability (CV) is discussed. The heaviest rain region over north Bay of Bengal (BoB) is found to have the lowest CV. Another sub-region of low CV lies over the eastern equatorial Indian ocean (EEIO). The CVs of total rain as well as its two major constituents are found to be higher on monthly basis compared to seasonal basis. Existence of a well known dipole between the EEIO and the north BoB is well recognized in PR data also. Significant variation in PR rainfall is found over continental India between excess and deficit monsoon seasons as well as between excess and deficit rainfall months of July and August. Examination of rainfall fractions between the BoB and Central India on year to year basis shows that compensation in rainfall fractions exists on monthly scale on both the regions. Also on the seasonal and monthly scales, compensation is observed in extreme monsoon seasons between the two regions. However, much less compensation is observed between the north BoB and EEIO belts in extreme rain months. This leads to speculation that the deficit and excess seasons over India may result from slight shift of the rainfall from Central India to the neighboring oceanic regions of north BoB. Contribution of stratiform and convective rain fractions have been also examined and the two fractions are found to contribute almost equally to the total rain. Results are further discussed in terms of the possible impact of the two rain fractions on circulation based on possible difference is vertical profiles of latent heat of two types of rain. Substantial differences in the lower and upper tropospheric circulation regimes are noticed in both deficit and excess monsoon months/seasons, emphasizing the interaction between rainfall (latent heat) and circulation.

El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Indian Summer Monsoon rainfall features are explored statistically and dynamically using National Centers for Environment Prediction (NCEP) Climate Forecast System (CFSv1) freerun in relation to observations. The 100 years of freerun provides a sufficiently long homogeneous data set to find out the mean state, periodicity, coherence among these climatic events and also the influence of ENSO and IOD on the Indian monsoon. Differences in the occurrence of seasonal precipitation between the observations and CFS freerun are examined as a coupled ocean–atmosphere system. CFS simulated ENSO and IOD patterns and their associated tropical Walker and regional Hadley circulation in pure ENSO (PEN), pure IOD (PIO) and coexisting ENSO-IOD (PEI) events have some similarity to the observations. PEN composites are much closer to the observation as compared to PIO and PEI composites, which suggest a better ENSO prediction and its associated teleconnections as compared to IOD and combined phenomenon. Similar to the observation, the model simulation also show that the decrease in the Indian summer monsoon rainfall during ENSO phases is associated with a descending motion of anomalous Walker circulation and the increase in the Indian summer monsoon rainfall during IOD phase is associated with the ascending branch of anomalous regional Hadley circulation. During co-existing ENSO and IOD years, however, the fate of Indian summer monsoon is dictated by the combined influence of both of them. The shift in the anomalous descending and ascending branches of the Walker and Hadley circulation may be somewhat attributed to the cold (warm) bias over eastern (western) equatorial Indian Ocean basin, respectively in the model. This study will be useful for identifying some of the limitations of the CFS model and consequently it will be helpful in improving the model to unravel the realistic coupled ocean–atmosphere interactions for the better prediction of Indian Summer Monsoon.

The present study is an attempt to examine some of the probable causes of the unusually low tropospheric column ozone observed over eastern India during the exceptional drought event in July 2002. We examined horizontal wind and omega (vertical velocity) anomalies over the Indian region to understand the large-scale dynamical processes which prevailed in July 2002. We also examined anomalies in tropospheric carbon monoxide (CO), an important ozone precursor, and observed low CO mixing ratio in the free troposphere in 2002 over eastern India. It was found that instead of a normal large-scale ascent, the air was descending in the middle and lower troposphere over a vast part of India. This configuration was apparently responsible for the less convective upwelling of precursors and likely caused less photochemical ozone formation in the free troposphere over eastern India in July 2002. The insight gained from this case study will hopefully provide a better understanding of the process controlling the distribution of the tropospheric ozone over the Indian region.

The exchange of surface freshwater, heat and moisture fluxes across the air-sea interface strongly influences the oceanic circulation and its variability at all time scales. The goal of this paper is to estimate and examine surface freshwater flux at monthly scale exclusively from the Tropical Rainfall Measuring Mission (TRMM) measurements over the tropical oceans for the period of 1998 - 2010. The monthly mean fields of TRMM Microwave Imager (TMI) sea surface temperature (SST), wind speed (WS), and total precipitable water (W) are used to estimate the surface evaporation utilizing the bulk aerodynamics parameterization formula. The merged TRMM Multisatellite Precipitation Analysis (TMPA)-3B43 product is combined with the estimated evaporation to compute the surface freshwater flux. A preliminary comparison of the satellite derived evaporation, precipitation and freshwater flux has been carried out with the Hamburg Ocean Atmosphere Parameters and Fluxes (HOAPS-3) datasets. Also, the estimated evaporation and TMPA-3B43 precipitation are validated with in-situ observations from the moored buoys in the different oceans. The results suggest that the TRMM has great potential to estimate surface freshwater flux for climatological and oceanic hydrological applications.

The introduction of gases and particulate contaminants in the atmosphere due to natural or human activities causes air pollution. The concentration and toxicity of these contaminants define air quality and in the long term contribute to climate change. Both air pollution and climate change influence each other through complex interactions in the atmosphere. This issue has 9 very interesting manuscripts, touching various aspects of air pollution and air quality and their impact on climate change