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Environmental context The export of various man-made pollutants from northern India has a large impact on aerosol formation processes, their transformations and regional environmental chemistry over tropical peninsular India. The quantitative source apportionment of organic aerosols performed in this study provides a better understanding of their sources and implications for climate and air-quality management policies in South Asia. Abstract This study highlights seasonal characteristics, sources, daytime (sea-breeze) and night-time (land-breeze) variations of carbonaceous and water-soluble ionic components in PM10 (

The Amazon River Basin (ARB) plays an essential role in global climate regulation. Recent studies have revealed signs of increasing drought conditions in different parts of the basin. Although human activities have degraded large areas, little work has been done to assess whether prolonged drought may exacerbate land degradation. Among different methods for monitoring land degradation, the Sustainable Development Goal (SDG) indicator 15.3.1 adopted by the United Nations Convention to Combat Desertification (UNCCD) allows a comprehensive assessment of the impacts of land degradation due to its multi-factor nature and scalability. The aims of this study are twofold: 1) to assess the status of land degradation using the SDG indicator 15.3.1 from 2001 to 2020 in the Amazon basin; and 2) to explore the relationship between the detectability of land degradation using the UNCCD approach and long-term drought severity. The Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), and self-calibrating Palmer Drought Severity Index (scPDSI) were used as drought indices. The results revealed 757,704 km2 (12.67% of the basin) as degraded land, which was reflected by a downward trend in land productivity dynamics followed by the combined downward trend in land productivity, Soil Organic Carbon (SOC) degradation, and land cover degradation. The largest land degradation hotspot was identified along the southwestern boundary of the Amazon River Basin. Furthermore, there was strong evidence that the detection of land degradation through SDG indicator 15.3.1 is sensitive to long-term drought, particularly when applied to rainfed croplands.

Summertime heat stress future projections from multi-model mean of 18 CMIP5 models show unprecedented increasing levels in the RCP 4.5 and RCP 8.5 emission scenarios over India. The estimated heat stress is found to have more impact on the coastal areas of India having exposure to more frequent days of extreme caution to danger category along with the increased probability of occurrence. The explicit amount of change in temperature, increase in the duration and intensity of warm days along with the modulation in large scale circulation in future are seemingly connected to the increasing levels of heat stress over India. A decline of 30 to 40% in the work performance is projected over India by the end of the century due to the elevated heat stress levels which pose great challenges to the country policy makers to design the safety mechanisms and to protect people working under continuous extreme hot weather conditions.

In the present study, rainfall estimates from TRMM (Tropical Rainfall Measuring Mission) and GPM (Global Precipitation Mission) constellation of satellites are analyzed in the context of rainfall induced landslide occurrences over Western Ghats (WG) of India along with the daily gridded rainfall data developed by the India Meteorological Department (IMD) and ARW- Weather Research and Forecasting (WRF) numerical model simulations. This study aims to analyze the pattern of changes in rain rate and total rainfall triggering the large landslides over WG in TMPA (product of TRMM) and IMERG (GPM product) rainfall data sets. As a case study, performance of IMERG V5 is assessed during Malin landslide which occurred on 30 July 2014 (initial GPM era). Results indicate that IMERG shows significant increase in rain rate (> 60mm/h in half-hourly data) during Malin landslide. Near real-time IMERG V5, underestimates the rain rate but increasing pattern of rain-rate are observed which is similar to that of final version. Spatial pattern of ARW-WRF rainfall output is also close to the satellite and IMD rainfall patterns. We propose that IMERG V5 can be used as an indicator to reliably depict the higher rainfall scenario over the sites that are vulnerable to rainfall induced landslide occurrence over the WG region.

It is well recognized that the global climate has been warming and it can have adverse regional impacts in the future. Besides producing changes in mean climate, global warming can also substantially alters the weather and climate extremes. Considering the impact of weather extremes on agriculture as well as water resource management in an agrarian country like India, present study aims to characterize future changes in precipitation extremes in northeast monsoon season (October–November–December) over south peninsular India based on statistically downscaled high-resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) datasets. This NEX-GDDP dataset simulates the mean rainfall reasonably well. There may be an increase in precipitation in near (5% under RCP 4.5 and 11% under RCP 8.5) and far future (21% and 38% under RCP4.5 and RCP 8.5 respectively). Future climate projections indicate that both the intensity and frequency of precipitation extremes in most parts of the south peninsular India may increase under both the warming scenarios during northeast monsoon season.

The Brazilian semiarid region (BSR) has faced severe drought over the last three decades, which has led to a significant decline in land productivity, posing a considerable threat to food security and the local economy and communities. The United Nations Convention to Combat Desertification (UNCCD) has proposed the use of Earth observation-derived vegetation indices for monitoring land degradation across regions. In this study, we aim to evaluate three comprehensive UNCCD-recommended land productivity dynamic (LPD) approaches in the BSR by utilizing the standardized precipitation–evapotranspiration index (SPEI) at 12-month time scales as a benchmark drought index obtained from ground-based measurements. Our findings indicate that the LPD methods utilizing residual trends analysis (RESTREND), Trends.Earth (TE), and the Food and Agricultural Organization’s World Overview of Conservation Approaches and Technologies (FAO-WOCAT) are best suited for identifying degraded land areas in the BSR region compared to other approaches. However, it is advisable to use these methods with caution, since they do not fully capture the impact of drought on vegetation and may result in underestimating the extent of degraded areas. The RESTREND-based LPD, TE, and FAO-WOCAT estimate that the BSR region reached 213,248 km2, 248,075 km2, and 246,783 km2 of degraded land, respectively, between 2001 and 2015. These findings may be valuable for decision-makers involved in land management and conservation efforts in the Sertão region of Brazil.

Present study focuses on rainfall over Western Ghats (WG), a complex topographic region (elevation > 500 m) of India to evaluate and to better understand the satellite behavior in contrast with a flat region (FR) (elevation

Mean monthly Atmospheric Residence Times (ART), deduced from the global climate models of Coupled Model Intercomparison Project 5 (CMIP5) under RCP4.5 and RCP8.5 emission scenarios over Indian landmass, show a perceptible increase by the end of the 21st century. India, being a tropical country, faces prolonged ART, particularly during the June month of Southwest monsoon season (June to September) which will be an indicative measure of the increased frequency of extreme weather events. Here we show a possible connection of quasi-resonant amplification (QRA) to the recent (August 2018) Kerala heavy rains that resulted in severe floods and claimed more than 400 mortalities. Remarkable delay in residence times over India during June is shown to have an association with QRA evidenced by the higher magnitudes of amplitudes at the wavenumbers six and seven from the 19 global climate models of CMIP5 under the RCP4.5 and RCP8.5 scenarios.

The present chapter discusses the changes in moisture recycling over the monsoon core region (MCR) of India using Coupled Model Intercomparison Project Phase 5 (CMIP5) multimodel mean datasets during the southwest monsoon season for the present and future climate, in particular during the El Nino years. Our results show that the contribution of advection is more in the rainfall than that of evaporation over some parts of Indo-Gangetic Plains (IGP). Moisture recycling is about 50%–60% over the eastern parts of IGP and about 10% over the rest of the MCR. The overall trend of local evaporation contribution has shown a decreasing trend with less than 21% of the normal by the end of the 21st century under the RCP4.5 (medium) and RCP8.5 (very high) emission scenarios during future strong and very strong El Nino years

Resumen El semiárido brasileño frecuentemente se ve afectado por sequías prolongadas. Durante el período 2010-2017, la región semiárida brasileña enfrentó la “sequía del siglo”, considerada la peor registrada en la historia del país. Este artículo tiene como objetivo hacer una evaluación histórica de diferentes fases de las políticas públicas implementadas en la región, con el fin de promover la convivencia con la sequía. Con base en una investigación histórica documental y el monitoreo satelital de los impactos de las sequías, se analizaron las acciones gubernamentales que contribuyeron a brindar una mayor disponibilidad de agua en la región semiárida brasileña, con énfasis en el análisis de la efectividad de la gestión del agua y los impactos de las tecnologías sociales para el almacenamiento del agua de lluvia en comunidades rurales dispersas. Los resultados de la investigación evidenciaron que las políticas implementadas a lo largo de la historia, con frecuencia en un modelo centralizado, no fueron efectivas en el desarrollo de la región. Recientemente, el acceso a las tecnologías sociales hídricas descentralizadas en las zonas rurales, están mostrando resultados positivos. Sin embargo, aún no es una realidad universal para la población que vive en la región. Por tanto, se concluye que las políticas hídricas siguen siendo insuficientes para hacer frente a los impactos de las sequías. El estudio aporta importantes lecciones históricas para la gestión del agua en la actualidad. Resumo O Semiárido brasileiro, com frequência, é afetado por secas prolongadas. No período 2010-2017, a região semiárida brasileira enfrentou a “Seca do Século”, considerada a pior já registrada na história do País. Este artigo tem o objetivo de fazer uma avaliação histórica das várias fases de políticas hídricas, implementadas na região, com o intuito de promover a convivência com a seca. Com base em investigações históricas documentais e em monitoramento por satélites dos impactos das secas, foram analisadas as ações governamentais, que contribuíram para proporcionar uma maior disponibilidade de agua na região semiárida brasileira, com foco no estudo da efetividade da governança hídrica e nos impactos das tecnologias sociais para armazenamento de agua da chuva, em comunidades rurais difusas. Os resultados da pesquisa evidenciaram que as políticas historicamente implementadas, geralmente em um modelo centralizado, não foram efetivas para desenvolver a região. Recentemente, o acesso às tecnologias sociais hídricas descentralizadas, nas áreas rurais, tem apresentado resultados positivos. Todavia, ainda não é uma realidade universal a toda a população que vive na região. Assim, conclui-se que as políticas hídricas ainda são insuficientes para fazer frente aos impactos das secas. O estudo oferece lições históricas importantes para a governança das águas nos dias atuais.

The Caatinga semi-arid vegetation in Northeast region of Brazil (NEB) provides a unique opportunity for studying the vegetation in response to recurring droughts, because of its negative impacts on soil erosion. Surprisingly, however, the response of Caatinga vegetation to a recent multi-year drought across the entire semi-arid NEB has not been studied in detail. This study analyses the spatiotemporal patterns of drought impact on the Caatinga vegetation between 2008 and 2016. Yet previous research has shown that a linear relationship exists between rainfall and Caatinga vegetation at interannual timescale. Because of the strong large-scale control of precipitation, year-to-year rainfall variations have a notable degree of spatiotemporal heterogeneity in semi-arid NEB. We exploit this relationship by developing the local-to regional-scale rainfall-Normalized Difference Vegetation Index (NDVI) distribution over the Caatinga vegetation, using daily rainfall time series from in situ weather stations, and daily Meteosat Second Generation (MSG) NDVI time series. Results showed that the drought impact (2012–2015) through the rainfall deficit dynamics influenced the dynamics of vegetative drought in the Caatinga vegetation where exhibit a strong decrease in vegetation activity, contrasting with irrigated croplands that exhibit little sensitivity to drought. It is the longest, continuous drought on the historical record (1901 onwards). The severe drought year of 2012 affected more than 26% of the vegetated area in the region. Over the 2012–2016 period, the positive trend observed in vegetation greenness is largely explained by a positive trend in the rainfall over 45% of the Caatinga vegetation, with the three months lagged rainfall (R2 = 0.62 with p

Black Carbon (BC) mass concentration has been analysed during rainy and non-rainy days of Northeast (NE) Monsoon months of the years 2015 and 2017 over a semi-urban environment near Chennai (12.81 N, 80.03 E), located on the east coast of India. BC, measured using an Aethalometer (AE-31) has been related to the atmospheric Boundary Layer Height (BLH) obtained from the ERA Interim Reanalysis data during rainy and non-rainy days on monthly mean basis to understand the wet removal of BC over the study location. The study reveals that BLH has a profound effect on the BC concentration on rainy days and non rainy days. It is found that the BC concentration in the night time is lower on rainy days compared to non rainy days owing to wash out on rainy days and the BLH remaining nearly the same on rainy and non rainy days. On the other hand, in the daytime it is found that the BC concentration remains nearly the same on rainy and non rainy days whereas the BLH is lower on rainy days compared to non rainy days. This reveals that in daytime lower boundary layer heights compensate for the wet removal effect on BC concentration on rainy days. A quantitative relation is found between the product of BC and BLH during rainy and non-rainy days which indicates the extent of redistribution of BC during non-rainy days when compared to the rainy days. In the process of analysing BC during the wet removal processes, the basic features of BC such as its mean diurnal variations, transport pathways, local sources and its relation with relative humidity were also reported.

In the present study, we have used TRMM multi-satellite precipitation analysis (TMPA) 3B42 and global precipitation mission (GPM): IMERG “precipitation Cal” products to identify and quantify the asymmetry and distribution of rainfall in tropical cyclones formed over Bay of Bengal (BoB). For the period 2010–2013, TMPA products have been made use of and for the period 2014–2017, GPM–IMERG products are used to study the aforementioned features. Overall, 17 cyclones covering 75 events/days ranging from depression to very severe cyclonic stage of the system have been analysed. Our analysis revealed some interesting features on asymmetry, direction of maximum rain-receiving zones, relation of T-number with maximum and total rainfall in rain-receiving areas. The study reveals the direction of rainfall zone is mostly towards west and southwest directions of the storm centre in BoB. This point gains importance in the context of earlier reports, where it is mentioned that the direction of maximum rainfall is in east. The study also infers that the maximum rainfall and total rainfall need not be dependent on the intensity (indicated by T-number). We also attempted to classify the rain-receiving zones, based on both the rainfall-rate window and area covered in each window of rainfall, and a criterion has been proposed. The distribution of rainfall is classified, as sharply falling, slowly falling and nearly constant.

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

The São Francisco River Basin (SFRB) plays a key role for the agricultural and hydropower sectors in Northeast Brazil (NEB). Historically, in the low part of the SFRB, people have to cope with strong periods of drought. However, there are incipient signs of increasing drought conditions in the upper and middle parts of the SFRB, where its main reservoirs (i.e., Três Marias, Sobradinho, and Luiz Gonzaga) and croplands are located. Therefore, the assessment of the impacts of extreme drought events in the SFRB is of vital importance to develop appropriate drought mitigation strategies. These events are characterized by widespread and persistent dry conditions with long-term impacts on water resources and rain-fed agriculture. The purpose of this study is to provide a comprehensive evaluation of extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and soil moisture over different time windows between 1980 and 2020. The Standardized Precipitation-Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) at 3- and 12-month time scales derived from ground data were used as benchmark drought indices. The self-calibrating Palmer Drought Severity Index (scPDSI) and the Soil Moisture and Ocean Salinity-based Soil Water Deficit Index (SWDIS) were used to assess the agricultural drought. The Water Storage Deficit Index (WSDI) and the Groundwater Drought Index (GGDI) both derived from the Gravity Recovery and Climate Experiment (GRACE) were used to assess the hydrological drought. The SWDISa and WSDI showed the best performance in assessing agricultural and hydrological droughts across the whole SFRB. A drying trend at an annual time scale in the middle and south regions of the SFRB was evidenced. An expansion of the area under drought conditions was observed only during the southern hemisphere winter months (i.e., JJA). A marked depletion of groundwater levels concurrent with an increase in soil moisture content was observed during the most severe drought conditions, indicating an intensification of groundwater abstraction for irrigation. These results could be useful to guide social, economic, and water resource policy decision-making processes.

We have used 1° × 1° resolution maximum temperature (TMAX) data sets developed by India Meteorological Department (IMD) to examine the summer time warming over India during the period 2001–2014 in comparison with the period 1971–2000. The two study periods have been arrived at based on the drastic change of Moisture Index (IM) trends over India between the two epochs. The TMAX variations over India are discussed with the corresponding changes in Potential Evapotranspiration (PET) data of the Climate Research Unit (CRU) and Outgoing Longwave Radiation (OLR) data of NOAA ESRL. The study shows a considerable warming over northern parts of India compared to southern parts. Western Himalayas (WH) and Northwest (NW) regions experienced highest warming with 1.4 °C and 0.8 °C increases during Epoch 2 (2001–2014) as compared Epoch 1 (1971–2000) during the summer (March, April and May). Using MERRA Black Carbon Surface Mass Concentration (BCSMC) data, we have analysed the relation of increasing BCSMC with the TMAX over different homogeneous temperature regions of India and found that BCSMC has increased upto 1.6 times between the two epochs. Strong linear association is found between TMAX, PET and OLR evidenced by Coherence Wavelet Spectral analysis. It is also found that the highest warming occurred in the month of March and is 2.2 °C in WH and 1.4 °C in NW parts of India. We calculated mass stream function based on zonal mean meridional velocity for the two periods. In the recent periods we observed the weakening of polar cell and northward expansion of Hadley cell. These changes may be related to warming conditions of the atmosphere which may explain the intensification and northward expansion of the Ferrel cell with favourable conditions during the summer season.

Satellite-based rainfall is an alternative source of information for regions such as the Northeast Brazil (NEB) where there are large areas that do not have ground observation stations. In this study, the monthly rainfall derived from the satellite-based rainfall product, Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS v.2), is compared with observation from 21 ground stations in the NEB, for the period 1981–2013. Various metrics based on pairwise comparison were applied to evaluate its performance in estimating rainfall amount and rain detection capability. Results show that the CHIRPS data correlate well with observations for all stations (r = 0.94), but tend to overestimate low and underestimate high rainfall values (>100 mm/month). Although CHIRPS achieves better results during the wet season (March to May; bias = −4.60%), its ability for the rain detection is poor (probability = 0.44). The best global performance was noted in the Cerrado biome (r = 0.93; rain detection = 0.53), but fails to detect rain in other biomes (r = 0.92; rain detection = 0.16). The study concluded that the CHIRPS v.2 dataset can be a useful substitute for rain-gauge precipitation data outside the semiarid NEB.

Trends of rice, wheat, maize, sorghum (jowar) and pearl millet (bazra) yields of India are studied in relation to water irrigation for the period 1951 to 2012. These crop yields have been subjected to correlation with the Normalized Difference Vegetation Index (NDVI), obtained from NOAA Advanced Very High Resolution Radiometer (AVHRR) (for 1982 to 2000) and Moderate Imaging Spectroradiometer (MODIS) Terra (for 2001 to 2012) to understand the linear association among them. Crop products and food inadequacy in percentage along with the average food production rate, available from FAO have been used in the present study. The present study mainly focuses on the estimation of return values of crop yields for different periods using Gumbell Extreme Value analysis. The present study is very important in the context of increased global food demands by 2050 where in many studies report that food production to be doubled by the year 2050 to meet the demands of increasing population. The main results of the study are: (i) significant positive correlations between NDVI and the crop yields during the study period, (ii) rice, maize and jowar yields did not show the required incremental rate while wheat and bajra yields are able to meet the expectations by the 2050. More efforts require to an increase of additional ~8% in the rice yields as the present growth is only ~12% and ought to be enhanced to ~20%.

This article presents the tendency of the normalized difference vegetation index (NDVI) and the dependence of vegetation on the rainfall and number of rainy and non-rainy days over Western Ghats. The study makes use of MODIS Terra NDVI data with 8-day intervals and 250-m resolution from 2000 to 2010 during the southwest monsoon (June to September) season. The results show an increasing tendency of the NDVI over different test sites in Western Ghats. The relation of the NDVI with the Antecedent Precipitation Index obtained from rainfall showed good agreement, and the relation of rainfall and the NDVI was mainly dependent on the available soil moisture levels and elevations of the test sites. Correlations were significant and positive with the number of rainy days and negative with the number of non-rainy days with a nearly 2-month lag.

The Amazon River Basin (ARB) plays an important role in the hydrological cycle at the regional and global scales. According to the Intergovernmental Panel on Climate Change (IPCC), the incidence and severity of droughts could increase in this basin due to human-induced climate change. Therefore, the assessment of the impacts of extreme droughts in the ARB is of vital importance to develop appropriate drought mitigation strategies. The purpose of this study is to provide a comprehensive characterization of dry spells and extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and vegetation in the ARB during the period 1901&ndash, 2018. The Standardized Precipitation-Evapotranspiration Index (SPEI) at multiple time scales (i.e., 3, 6, and 12 months) was used as a drought index. A weak basin-wide drying trend was observed, but there was no evidence of a trend in extreme drought events in terms of spatial coverage, intensity, and duration for the period 1901&ndash, 2018. Nevertheless, a progressive transition to drier-than-normal conditions was evident since the 1970s, coinciding with different patterns of coupling between the El Ni&ntilde, o/Southern Oscillation (ENSO) phenomenon and the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Madden&ndash, Julian Oscillation (MJO) as well as an increasing incidence of higher-than-normal surface air temperatures over the basin. Furthermore, a high recurrence of short-term drought events with high level of exposure to long-term drought conditions on the sub-basins Ucayali, Japur&aacute, Caquet&aacute, Jari, Juta&iacute, Mara&ntilde, &oacute, n, and Xingu was observed in recent years. These results could be useful to guide social, economic, and water resource policy decision-making processes in the Amazon basin countries.

Black carbon (BC) aerosol emitted in incomplete combustion processes is known for causing warming in the climate system also poses serious health issues. Identification of the sources of BC is essential for the development of mitigation strategies to regulate their effects in changing climate. Among different observational and analytical techniques currently available, source apportionment methods based on optical measurements are relatively simple. For example, 'Aethalometer model' was developed based on Aethalometer observations. However, there are a few limitations with this model arising from assumption of wavelength and angstrom exponent pairs. We have developed an empirical method which also relies on Aethalometer observations named as 'Two alpha method' which assumes angstrom exponent from fossil fuel as 1 and estimates bio-mass fraction and angstrom exponent for bio-mass burning. This method has been applied to Aethalometer observations from five different locations (rural, semi-urban and urban) over Indian sub-continent to quantify sources of BC. Fossil fuel is found to be the major source of BC (∼70%) irrespective of the location. Collocated measurements of Carbon Monoxide (CO) over rural site correlated well with derived bio-mass fraction. Results from this study demonstrated the capabilities of empirical method and shall provide spatio-temporal variability in sources of BC if applied to more locations.

The short wave direct Aerosol Radiative Forcing (ARF) at a semi urban coastal location near Chennai (12.81 °N, 80.03 °E, ∼45 m amsl), a mega city on the east coast of India has been estimated for all the four seasons in the year 2013 using the SBDART (Santa Barbara Discrete ordinate Atmospheric Radiative Transfer) model. As inputs to this model, measured aerosol parameters together with modeled aerosol and atmospheric parameters are used. The ARF in the atmosphere is found to be higher in the pre-monsoon and winter seasons compared to the other seasons whereas at the surface, it is found to be higher in the south-west (SW) monsoon and winter seasons. The estimated ARF values are compared with those reported over other locations in India. The effect of Relative Humidity on ARF has been investigated for the first time in the present study. It is found that the ARF increases with increasing RH in the SW monsoon and winter seasons. An unique feature of the present study is the comparison of the net surface short wave fluxes estimated from the model (SBDART) and measured fluxes using CNR 4 net radiometer. This comparison between the estimated and measured fluxes showed good agreement, providing a ‘closure’ for the estimates.

The aim of this study is to examine the spatiotemporal patterns of vegetation dynamics and explores relationships between rainfall and normalized difference vegetation index (NDVI) over the heterogeneously vegetated region of Northeastern Brazil (NEB). The two datasets used in this study are composed of: (1) NOAA-AVHRR NDVI3g dataset processed by the Global Inventory Monitoring and Modeling Systems (GIMMS) group, and; (2) rain-gauge totals from a network of the 86 stations. This comparative analysis is based on correlation and rotated empirical orthogonal function (REOF) techniques of the standardized difference vegetation index (SDVI) and the standardized precipitation index (SPI) time series from January 1982 to December 2001 for the whole area of the NEB region. Results showed that highest correlations is achieved between SDVI and SPI with three-month lag (r =+0.60, significant at 95% level) for spatiotemporal analysis. A REOF analysis confirms this spatiotemporal relationship yielding three spatially separated modes in the southwestern, northwestern and central-eastern part of the NEB region. The study concluded that rainfall emerges as the dominant causative factor in the dynamics of vegetative drought (i.e. negative SDVI) in the region. Thus, these findings can provide some understanding of the links between NDVI and rainfall for monitoring the dynamics of vegetation in the region of NEB.

This research investigates spatial patterns of Normalized Difference Vegetation Index (NDVI) and rainfall variability in South America and their relationships based on analyses of the Standardized Difference Vegetation Index (SDVI) and the Standardized Precipitation Index (SPI) for the period April 1998–March 2012. The time series of SPOT-Vegetation 10-daily composite NDVI data at 1-km resolution was smoothed and subsequently synthesized to monthly images using the maximum value composite technique. Furthermore, 10-daily rainfall estimates at 0.25° resolution, available from the European Centre for Medium-Range Weather Forecasts through MeteoConsult and the Monitoring Agricultural ResourceS unit, were combined to retrieve monthly composites. In order to assess spatial patterns and rates of change, linear least squares trend analyses were performed on the SDVI time series and the SPI time series, taking into account the accumulated rainfall over the respective best lag. Only trends with Pearson’s correlation coefficients significantly different from zero (p

The scattering and absorption components of Aerosol Optical Depth (AOD) over a semi-urban coastal location (12.81°N, 80.03°E) near the mega city Chennai in peninsular India are separated using the collocated measurements of Black Carbon concentration and Atmospheric Boundary Layer Height (ABLH) from ERA Interim Reanalysis data assuming that most of the BC is contained and homogeneously mixed in the ABL. It is found that the absorption component to scattering component ratio has a strong seasonal variation with a pronounced maximum in the South West (SW) monsoon season. This is indicative of more effective wet removal of scattering aerosols than absorbing (BC) aerosols. There could also be an effect due to preferential removal of large particles which would have a lower content of BC. The Angstrom wavelength exponent shows a minimum in the SW monsoon season, the minimum being more pronounced for the scattering aerosols implying relative dominance of coarse mode particles. Investigation of the effect of Relative Humidity on scattering and absorption components of AOD revealed that the BC (absorbing) aerosols are non-hydrophilic/not coated with hydrophilic substance.

Six temperature homogeneous regions of India were chosen to calculate evapotranspiration (ET) using Hargreaves and Samani method on a monthly basis. Break Trend Analysis has been applied to the annual and seasonal ETs of the respective homogeneous regions as well as for whole India and the factors contributing for the changes in ET have been analysed. By considering the data of Reconnaissance Drought Index (RDI), Rainfall, Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) for South West (SW) monsoon (June to September) and Rice yield (major Khariff crop yield) of All India, we investigated the variations in ET during drought years. The trend analysis of seasonal and annual ETover the test regions have shown significant (levels of 0.05 to 0.01) increase over the past 107 years of the study period (1901 to 2007). The enhancement in ET is found to be 2.9 mm/decade overIndia and with a maximum in West Coast India (6 mm/decade), followed by Northwest India (3.9 mm/ decade). The increasing trends in ET may be due to the increase in difference of maximum and minimum tempera- tures over these regions, which is of the order of 0.64 °C/ decade on all India scale. The analysis of ET in drought years consistently shows higher values in the years when India suffered under moderate and severe droughts. It is also ob- served that lower rainfall values in the drought years such as 1983, 1987 and 2002 were associated with the higher ETs accompanied by lower NDVI and Rice yields. The analysis has been extended to the comparison of ET with rainfall through wavelet spectrum to understand the interannual vari- ations which inferred the El Nino impact on ET. The correla- tionanalysis of ETover the Interior Peninsular regionwith the number of days falling in active and break spells of monsoon by which drought can be characterised, revealed the signifi- cant negative and positive values, respectively.

Trend and interannual variability of total integrated precipitable water vapor (PWV) has been studied over India for the period 1979–2004 using NCEP/National Centre for Atmospheric Research reanalysis data with 2.5° × 2.5° resolution. The spatiotemporal variability of cycling rates (CR; units: per day), obtained from the ratio of rainfall to the PWV were presented not only for the long term (1979–2004) but also during El Niño (EN) and La Niña (LN) years of the study period to understand the intensity of hydrological cycle. The paper then dwells on obtaining the monthly atmospheric residences times over India to infer the stay of water vapor before it precipitates. The results of the present study are: all India PWV shows decreasing trend in association with the increasing/decreasing trends of Niño 3 SST/Southern Oscillation Index (SOI) for the southwest (SW) monsoon period of 1979–2004; the spatial pattern of temporal correlations of CR with SOI and Niño 3 SST displayed the significant positive and negative values in peninsular and central Indian portions of India respectively; all India atmospheric residence times varied from 9 to 2 days from premonsoon/post monsoon to SW monsoon over India.

Trends of pre-monsoon, monsoon and post-monsoon rainfall pattern were studied on decadal basis over different homogeneous monsoon regions in India for the period 1871-2008. It is attempted to understand the relation of monsoon rainfall with the global teleconnections of El Nino and La Nina, for which the correlation analysis has been carried out with Darwin pressure and Nino 3.4 sea surface temperature (Nino 3.4 SST). The correlation analysis inferred that the significant correlations were observed when monsoon rainfall is related to ENSO indices on decadal scale than on annual ones. The study also found that the north-west region is more affected by the moderate El Nino years compared to strong El Nino years. The regions Central North-East and North-East could not make any difference among weak, moderate and strong La Nina events. The authors also have carried out the extreme value analysis over different homogeneous monsoon regions of India as well as for whole India. The results show that the return values of rainfall are increasing with the return periods for the forthcoming 10, 20, 50 and 100 years. The heterogeneity in number of threshold years that were recorded for the extreme rainfall over north-east (humid climatic type) and north-west (arid climatic type) described the climate variability. The results of the present study may be useful for the policy makers in understanding the rainfall exceedance in different return periods for planning the risk management strategies.

Potential impacts of change in climate on Indian agriculture may be significantly adverse, if not disastrous. There are projections of potential loss in wheat yield due to the rise in daily minimum (Tmin) and maximum (Tmax) temperature, but only few researchers have considered the extent of such loss on a spatial scale. We therefore, systematically studied the effect of change in Tmax, Tmean (daily average temperature) and Tmin, solar radiation (Srad) and precipitation (RAIN) during wheat growing seasons (from 1986 to 2015) on wheat crop yield over five wheat growing zones across India, taking into account the effect modification by aerosol loading (in terms of aerosol optical depth, 2001–2015). We note that for the entire India, 1 °C rise in Tmean resulted a 7% decrease in wheat yield which varied disproportionately across the crop growing zones by a range of −9% (peninsular zone, PZ) to 4% (northern hills zone, NHZ). The effect of Tmean on wheat yield was identical to the marginal effect of Tmax and Tmin, while 1% increase in Srad enhance wheat yield by 4% for all India with small geographical variations (2–5%), except for the northern hill region (−4%). Rise in 1 °C Tmean exclusively during grain filling duration was noted positive for all the wheat growing regions (0–2%) except over central plain zone (−3%). When estimates of weather variables on wheat yield was combined with the estimated impact of aerosols on weather, the most significant impact was noted over the NHZ (−23%), which otherwise varied from −7% to −4%. Overall, the study brings out the conclusive evidence of negative impact of rising temperature on wheat yield across India, which we found spatially inconsistent and highly uncertain when integrated with the compounding effect of aerosols loading.

Regular measurements of Black Carbon (BC) aerosol mass concentration have been carried out since March 2011 at a tropical location (12.81°N, 80.03°E) adjoining the mega city, Chennai, on the east coast of India for the first time. As this region is influenced by both the South West and North East monsoons, the BC observations at this site assume importance in understanding the overall BC distribution over India. The data collected until August 2012 has been examined for the general and regionally distinctive features. Spectral absorption characteristics reveal that the BC is mainly from fossil fuel based emissions. The BC concentration shows significant diurnal variation only in the North East monsoon and winter seasons with night time concentration considerably higher than the day time concentration. In the other seasons the day–night contrast in BC is not significant. Seasonal variation is rather subdued with a broad maximum during the Northeast monsoon and winter months and a minimum during the southwest monsoon months. The observed diurnal and seasonal variations are examined in the light of local Atmospheric Boundary Layer dynamics and long range transport. For the first time, an inverse relationship has been established between BC and ABL height on a quantitative basis. A distinctive feature of the region is that in all the seasons transport pathways have long continental overpasses which could lead to the suppressed seasonal variation. It is found that the BC over this region shows distinct diurnal and seasonal features compared to those reported for other coastal and inland regions in India.

The global short term climate signal from the Equatorial Pacific sea surface temperature pattern in conjunction with the Southern oscillation of sea level pressure plays a crucial role in governing the global weather systems by modulating and altering the yearly climate scenario across the globe. The analysis of Normalized Difference in Vegetation Index (NDVI) fields of the five homogeneous regions of India with the index of moisture adequacy and Multivariate ENSO Index yielded the phenological metrics such as senescence in terms of greenness up and down along with the lag between maximum NDVI and index of moisture adequacy for normal (1982–2000), El Nino (1997) and La Nina (1998) years respectively. A threshold value of 60% soil moisture adequacy is considered for sustainable crop or vegetation growth in obtaining the phenological metrics for the regions under consideration. The north east, peninsular India along with west central India experienced an increase in the number of humid days both in the El Nino and La Nina years compared to normal. The annual figures of All India rice yields are increasing linearly and the trend was significant but no trend is noticed in moisture adequacy. An agro climatic model is developed for the estimation of All India rice yield and is of help in designing the agro meteorological advisories.

Eleven years (2000 to 2010) of Normalized Difference Vegetation Index (NDVI) data, derived from Moderate Imaging Spectroradiometer (MODIS) Terra with 250 m resolution is used in the present study to discuss the changes in the vegetal cover over Western Ghats, India. The NDVI over Western Ghats (number of test sites are 16) showed increasing tendency and the pronounced changes in NDVI have been studied in the context of southwest monsoon's distribution and activity. The NDVI progression is observed from June with a minimum value of 0.179 and yielded to a maximum at 0.565 during September/October, on an average. The study then relates NDVI with different rainy events to understand the connection between the ground vegetation and the south west monsoon. The results of the study inferred are as follows: i) NDVI, Antecedent Precipitation Index (API) are in good agreement throughout the monsoon which is evidenced by correlation; ii) NDVI maintained good correlation with a number of Light and Moderate Rainy days alternatively but not with the number of Heavy Rainy days; iii) Relation of NDVI with Isolated, Scattered distributions and active monsoons is substantial; and iv) Rate of Green Up is captured by the satellite during the crop growing season over the Western Ghats.

The changes in spatial distribution of Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) are stud¬ied for different seasons in India for the period 1982 to 2000. The inter-annual variability of All India NDVI (AINDVI) has been studied and related to rainfall, air temperature, soil moisture adequacy, Southern Oscillation Index (SOI) and Nino 3 Sea Surface Temperature (Nino 3 SST) to understand the influence of these variables on vegetal cover. The results show that the NDVI is high during the south-west (June to September) monsoon and retreat (October and November) seasons where in major crop seasons Kharif and Rabi take place over India. The trend of AINDVI is increasing and displayed higher values during La Niña and lower in El Niño episodes. The correlation between rainfall and NDVI of All India is not significant on monthly basis (+0.13) but it is more prominent when the cumulative annual amounts of rainfall are involved (+0.61). NDVI responded very well to the variations of soil moisture adequacy (SAD) which enumerates the strongest correlation (+0.73) of crop performance with NDVI. This significant strong correlation inferred that SAD can be taken as the indicator for the NDVI variations rather rainfall. The linear regression analysis of AINDVI and the ENSO indices revealed the strong impact of sea surface temperatures than SOI on vegetation pattern over India., Promjene prostorne raspodjele normiranog diferencijalnog vegetacijskog indeksa (NDVI) dobivenog na temelju mjerenja radiometrom vrlo visoke rezolucije (AVHRR) proučavane su za različite sezone na području Indije tijekom razdoblja od 1982. do 2000. godine. Promatrana je međugodišnja promjenjivost NDVI-a izračunatog za cijelo područje Indije (AINDVI) te njegova povezanost s oborinom, temperaturom zraka, dostatnošću vlažnosti tla, indeksom Južne oscilacije (SOI) te Niño 3 površinskom temperaturom mora (Niño 3 SST) kako bi se utvrdila povezanost tih varijabli i vegetacijskog pokrova. Rezultati pokazuju da NDVI poprima visoke vrijednosti tijekom sezone jugozapadnih monsuna (od lipnja do rujna) te tijekom prijelazne sezone povlačenja monsuna (listopad i studeni) što se uglavnom podudara sa žetvenim sezonama Kharif i Rabi. NDVI ima pozitivan trend te poprima više vrijednosti tijekom La Niña, a niže vrijednosti tijekom El Niño događaja. Iako korelacija između mjesečnih vrijednosti oborine i NDVI-a za cijelo područje Indije nije signifikantna (+0,13), ona je značajno veća ukoliko se promatraju kumulativne godišnje vrijednosti oborine (+0,61). Varijabilnost NDVI-a je u skladu s promjenama dostatnosti vlažnosti tla (SAD) što rezultira značajnim koeficijentom korelacije između indeksa NDVI i prinosa usjeva (+0,73). Ova signifikantna i jaka povezanost ukazuje da se SAD može koristiti kao uspješniji pokazatelj promjenjivosti NDVI-a nego sama oborina. Linearna regresija između AINDVI i ENSO indeksa pokazala je da su površinske temperature mora (Niño 3 SST) bolje korelirane s vegetacijskim pokrovom Indije nego indeks SOI.

Dryland ecosystems cover one third of the earth’s total land surface, comprise areas with a ratio of average annual rainfall to evapotranspiration of less than 0.65 (MEA, 2005). These regions are fragile environments characterized by unreliable rainfall patterns and support livelihoods of over 2.5 billion people (Reynolds et al., 2007). Widespread episodes of drought, heavy precipitation and heat waves have been reported as a consequence of global sea level increase (Verdin et al., 2005). However, the projections of the impacts of global warming on regional climate are largely uncertain due to the complex and site-specific interdependencies among landscape properties, environmental traits and policy decisions (Boulanger et al., 2005). The predictions of climate changes and their impacts in those dry lands are important because of their characteristics affecting economic activity based on agriculture and the role of natural ecosystems in carbon sequestration and water budget, which could lessen or mitigate the impacts of global changes in the weather system of these regions. Climate variability and change play a significant role in dryland decision making, at various time scales. Decisions affected by climate considerations include both dryland hardware (infrastructure and technology) and software (management, policies, laws, governance arrangements). Strategic (decadal scale) and tactical (seasonal or interannual scale) decisions regarding such matters as infrastructure for storing water and dryland conservation measures must be made in the face of uncertainty about interdecadal, intraseasonal and interannual flows. There is a need to understand changes that have occurred in the resources in dryland ecosystems that contain a variety of plant species that have developed special strategies to cope with the low and sporadic rainfall and extreme variability in temperatures A better understanding of various dynamics at work in drylands will put us in a better position to predict the future of the ecosystems. Sustainable land use under climate change requires

Daily rainfall datasets of 10 years (1998-2007) of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (similar to 0.9) when the study was confined to specific wet and dry spells each of about 5-8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30-50 days and 10-20 days), to be ranging respectively between similar to 30-40% and 5-10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by similar to 110 mm during southwest monsoon and overestimating by similar to 150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1 degrees x1 degrees grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5 degrees x5 degrees average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.