This PDF file contains the front matter associated with SPIE Proceedings Volume 9876, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

Numerical climate and weather models depend on measurements from space-borne satellites to complete model validation and improvements. Precipitation profiling capabilities are currently limited to a few instruments deployed in Low Earth Orbit (LEO), which cannot provide the temporal resolution necessary to observe the evo- lution of short time-scale weather phenomena and improve numerical weather prediction models. A constellation of cloud- and precipitation-profiling instruments in LEO would provide this essential capability, but the cost and timeframe of typical satellite platforms and instruments constitute a possibly prohibitive challenge. A new radar instrument architecture that is compatible with low-cost satellite platforms, such as CubeSats and SmallSats, has been designed at JPL. Its small size, moderate mass and low power requirement enable constellation missions, which will vastly expand our ability to observe weather systems and their dynamics and thermodynamics at sub-diurnal time scales down to the temporal resolutions required to observe developing convection. In turn, this expanded observational ability can revolutionize weather now-casting and medium-range forecasting, and enable crucial model improvements to improve climate predictions.

Simulation and prediction of Indian monsoon rainfall at scales from days-to-season is a challenging task for numerical modelling community worldwide. Gridded estimates of daily rainfall data are required for both land and oceanic regions for model validation, process studies and in turn for model development. Due to recent developments in satellite meteorology, it has become possible to produce realistic near real-time gridded rainfall datasets at operational basis by combining satellite estimates with rain gauge values and other available in-situ observations. Microwave and space based radar based estimates of rainfall has revolutionised the preparation of rainfall datasets especially for tropics. However, a variety of multi-satellite products are available over Indian monsoon region from a variety of sources. Popular products like TRMM TMPA3B42 (RT and V7), GsMaP, CPC/RFE, GPCP and GPM are available to end users in various space/time scales for applications and model validation. In this study, we show the representation and skill of monsoon rainfall from a variety of multi-satellite products over the Indian region. The bias and skill of multi-satellite rainfall are evaluated against gauge based observations. It was found that the TRMM based TMPA was one of the best dataset for Indian monsoon region. Attempt is made to compare the latest GPM based data with other products. The GPM based rainfall product is seen to be superior compared to TRMM.

The climate of India is dominated by monsoon systems. The remotely sensed estimates obtained from the Tropical Rainfall Measuring Mission (TRMM) are used to examine the most of the Indian monsoon systems. This study deals with the diurnal and spatial variation of precipitation over the Indian region. The precipitation data from TRMM Multi-satellite Precipitation Analysis (TMPA), blended from a variety of sources (including rain gauges over land) and having both daily and 3- hourly output are being used for evaluation of the Numerical Weather Prediction models Basu (2007) of National Centre for Medium Range Weather Forecasting. The precipitation obtained from TRMM 3B42 for this study period has a spatial resolution of 0.25º X 0.25º latitude-longitude. The 3-hourly averaged values are centered at the middle of each 3 hr period. South Asian regions are dominated by seasonal climatic fluctuations and the major rainy season is the southwest monsoon season. In addition to the seasonal fluctuations, Indian summer monsoon is modulated by diurnal fluctuations; nature of diurnal variation of rainfall varies from place to place and depends upon the locations, topography of the region. Diurnal variation of rain-rate, frequency of rain, conditional rain rate, and maximum and minimum rain occurrence is studied. Over Indian tropical region, maximum rainfall over land and Bay of Bengal regions is observed during the late-afternoon and early-morning period, respectively. Drizzle or less rainfall occur frequently in the morning over most land areas, whereas convective activity occurs during the afternoon. The model predicted diurnal cycle of precipitation peaks too early (by ~3h) and the amplitude is too strong over Indian land region and tropical ocean region.

Many people in Asia regions have been suffering from disastrous rainfalls year by year. The rainfall from typhoons or tropical cyclones (TCs) is one of their key water supply sources, but from another perspective such TCs may also bring forth unexpected heavy rainfall, thereby causing flash floods, mudslides or other disasters. So far we cannot stop or change a TC route or intensity via present techniques. Instead, however we could significantly mitigate the possible heavy casualties and economic losses if we can earlier know a TC’s formation and can estimate its rainfall amount and distribution more accurate before its landfalling. In light of these problems, this short article presents methods to detect a TC’s formation as earlier and to delineate its rainfall potential pattern more accurate in advance. For this first part, the satellite-retrieved air-sea parameters are obtained and used to estimate the thermal and dynamic energy fields and variation over open oceans to delineate the high-possibility typhoon occurring ocean areas and cloud clusters. For the second part, an improved tropical rainfall potential (TRaP) model is proposed with better assumptions then the original TRaP for TC rainfall band rotations, rainfall amount estimation, and topographic effect correction, to obtain more accurate TC rainfall distributions, especially for hilly and mountainous areas, such as Taiwan.

An algorithm is developed to identify precipitation affected pixels and quantitatively measure the precipitation using Megha-Tropiques humidity sounder (SAPHIR) channels around water vapor absorption line at 183 GHz. Based on observed brightness temperatures at all the six channels of the SAPHIR, a probabilistic rain identification algorithm is proposed. The rain thus identified is subjected to intensive testing using SAPHIR and PR collocated dataset, that showed that false alarm and missing rain is below 0.9 mm/h. Further a radiative transfer simulations supported rain retrieval algorithm is developed that explained a correlation of 0.7 and rmse of 0.81 mm/h. When both precipitation detection and retrieval algorithms are applied the correlation marginally deteriorates but rmse reduces to 0.55 mm/h. Further comparisons are made of monthly, daily and instantaneous rain over different geographical regions from SAPHIR with corresponding rain values from GSMap, TRMM-3B42 V7 and TRMM-TMI/PR, etc. The paper provides details of algorithm development and validation results.

Even though both the rain measuring instruments, radar and radiometer onboard the TRMM observe the same rain scenes, they both are fundamentally different instruments. Radar is an active instrument and measures backscatter component from vertical rain structure; whereas radiometer is a passive instrument that obtains integrated observation of full depth of the cloud and rain structure. Further, their spatial resolutions on ground are different. Nevertheless, both the instruments are observing the same rain scene and retrieve three dimensional rainfall products. Hence it is only natural to seek answer to the question, what type of information about radiometric observations can be directly retrieved from radar observations. While there are several ways to answer this question, an informational theoretic approach using neural networks has been described in the present work to find if radiometer observations can be predicted from radar observations. A database of TMI brightness temperature and collocated TRMM vertical attenuation corrected reflectivity factor from the year 2012 was considered. The entire database is further classified according to surface type. Separate neural networks were trained for land and ocean and the results are presented.

Clouds strongly modulate the Earths energy balance and its atmosphere through their interaction with the solar and terrestrial radiation. They interact with radiation in various ways like scattering, emission and absorption. By observing these changes in radiation at different wavelength, cloud properties can be estimated. Cloud properties are of utmost importance in studying different weather and climate phenomena. At present, no satellite provides cloud microphysical parameters over the Indian region with high temporal resolution. INSAT-3D imager observations in 6 spectral channels from geostationary platform offer opportunity to study continuous cloud properties over Indian region. Visible (0.65 μm) and shortwave-infrared (1.67 μm) channel radiances can be used to retrieve cloud microphysical parameters such as cloud optical thickness (COT) and cloud effective radius (CER). In this paper, we have carried out a feasibility study with the objective of cloud microphysics retrieval. For this, an inter-comparison of 15 globally available radiative transfer models (RTM) were carried out with the aim of generating a Look-up- Table (LUT). SBDART model was chosen for the simulations. The sensitivity of each spectral channel to different cloud properties was investigated. The inputs to the RT model were configured over our study region (50°S - 50°N and 20°E - 130°E) and a large number of simulations were carried out using random input vectors to generate the LUT. The determination of cloud optical thickness and cloud effective radius from spectral reflectance measurements constitutes the inverse problem and is typically solved by comparing the measured reflectances with entries in LUT and searching for the combination of COT and CER that gives the best fit. The products are available on the website www.mosdac.gov.in

A tool for the entire Indian weather radar network using the static composite QI (Quality Index) map is generated. Various customized modules are used for this generation of the radar mosaic. The characterization of quality of DWR (Doppler weather Radar) data in terms of their QI is essential for assimilating the data into NWP (Numerical Weather Prediction) models. The static QI maps give a quick overview about the inherent errors in the DWR data. Quality control algorithms are applied for the generation of composite QI. The near real time access to the DWR data at NCMRWF enables the generation of an accumulated gridded radar rainfall product. This gridded rainfall map is useful for generating products like high resolution rainfall product, QPE (quantitative precipitation estimate) and for other applications. Results of some case studies shall be presented.

Variation of raindrop size distribution (DSD) are investigated using long-term (2007-2014) measurements made at Thumba (8.5°N, 76.9°E) by Joss-Waldvogel disdrometer. The DSD is observed to be distinctly different for NE and SW monsoon seasons. Results show a significant difference in the diurnal pattern of rainfall with large amplitude in the diurnal variation of rainfall in the monsoon with an evening (19:00 LT) to midnight (04:00 LT) peak and a weak diurnal variation in the Pre-monsoon and Post monsoon seasons. Probability of occurrence of rain is minimum during 10:00 – 13:00 LT for all seasons. The diurnal variation of DSD parameter Dm (mass-weighted mean diameter) also shows a distinct pattern with smaller values in monsoon compared to pre-, and post monsoon seasons. During monsoon season due to the presence of large number of small drops reduces the Dm value. While the presence of fewer small drops and relatively more big drops in the post and pre monsoon increases the values of Dm.

Cirrus clouds play a significant role in the Earths radiation budget. Therefore, knowledge of geometrical and optical properties of cirrus cloud is essential for the climate modeling. In this paper, the cirrus clouds microphysical and optical properties are made by using a ground based lidar measurements over an inland tropical station Gadanki (13.5°N, 79.2°E), Andhra Pradesh, India. The variation of cirrus microphysical and optical properties with mid cloud temperature is also studied. The cirrus clouds mean height is generally observed in the range of 9-17km with a peak occurrence at 13- 14km. The cirrus mid cloud temperature ranges from -81°C to -46°C. The cirrus geometrical thickness ranges from 0.9- 4.5km. During the cirrus occurrence days sub-visual, thin and dense cirrus were at 37.5%, 50% and 12.5% respectively. The monthly cirrus optical depth ranges from 0.01-0.47, but most (<80%) of the cirrus have values less than 0.1. Optical depth shows a strong dependence with cirrus geometrical thickness and mid-cloud height. The monthly mean cirrus extinction ranges from 2.8E-06 to 8E-05 and depolarization ratio and lidar ratio varies from 0.13 to 0.77 and 2 to 52 sr respectively. A positive correlation exists for both optical depth and extinction with the mid-cloud temperature. The lidar ratio shows a scattered behavior with mid-cloud temperature.

Understanding the cloud microphysical processes and precise retrieval of parameters governing the same are crucial for weather and climate prediction. Advanced remote sensing sensors and techniques offer an opportunity for monitoring micro-level developments in cloud structure. . Using the observations from a visible and near-infrared lidar onboard CALIPSO satellite (part of A-train) , the spatial variation of cloud structure has been studied over the Tropical monsoon region . It is found that there is large variability in the cloud microphysical parameters manifesting in distinct precipitation regimes. In particular, the severe storms over this region are driven by processes which range from the synoptic to the microphysical scale. Using INSAT-3D data, retrieval of cloud microphysical parameters like effective radius (CER) and optical depth (COD) were carried out for tropical cyclone Phailine. It was observed that there is a general increase of CER in a top–down direction, characterizing the progressively increasing number and size of precipitation hydrometeors while approaching the cloud base. The distribution of CER relative to cloud top temperature for growing convective clouds has been investigated to reveal the evolution of the particles composing the clouds. It is seen that the relatively high concentration of large particles in the downdraft zone is closely related to the precipitation efficiency of the system. Similar study was also carried using MODIS observations for cyclones over Indian Ocean (2010-2013), in which we find that that the mean effective radius is 24 microns with standard deviation 4.56, mean optical depth is 21 with standard deviation 13.98, mean cloud fraction is 0.92 with standard deviation 0.13 and mainly ice phase is dominant. Thus the remote observations of microstructure of convective storms provide very crucial information about the maintenance and potential devastation likely to be associated with it. With the synergistic observations from A-Train , geostationary and futuristic imaging spectroscopic sensors, a multi-dimensional, and multi-scalar exploration of cloud systems is anticipated leading to accurate prediction of high impact weather events.

Doppler Weather Radar (DWR) can provide tropospheric wind observations with high temporal and spatial resolutions. The Volume Velocity Processing (VVP) technique is one of the processing methods which can provide vertical profiles of mean horizontal winds. The DWR observed VVP winds gives a continuous observation of the wind field at various atmospheric levels. The quality of the VVP winds is studied against the short-range forecast of the NCUM model (model background). The biases of the observation are calculated against model background. This study focuses on the quality of VVP winds and seasonal variation of bias of the observed wind. This results shows that the VVP winds provides reasonably accurate estimates of the vertical wind structure in the troposphere over radar locations which can be effectively used in the numerical weather prediction system.

The continuous observations from visible and thermal infrared (TIR) channels of geostationary satellites are highly useful for obtaining the features associated with the shape and dynamics of cloud structures within the tropical cyclones (TCs). As TC develops from an unstructured cloud cluster and intensifies, the cloud structures become more axisymmetric around the centre of the TC. To better understand the structure of TC during different stages of its evolution i.e. from its cyclogenesis to maturity and dissipation, the continuous satellite observations plays a key role. The high spatial and temporal resolution observations from geostationary satellites are very useful in order to analyze the cloud organization during the cyclogenesis. The gradient of the brightness temperatures measures the level of symmetry of each structure, which characterizes the degree of cloud organization of the TC. In the present work, the structural analysis of TC during its life period using the observations from Indian geostationary satellite INSAT-3D has been discussed. The visible and TIR observations from INSAT-3D satellite were used to fix the center position of the cyclone which is an input for the cyclone track and intensity prediction models. This data is also used to estimate the intensity of cyclone in the advanced Dvorak technique (ADT), and in the estimation of radius of maximum winds (R_max) of TC which is an essential input parameter for the prediction of storm surge associated to the cyclones. The different patterns of cloud structure during the intensification stage, eye-wall formation and dissipation have been discussed. The early identification of these features helps in predicting the rapid intensification of TC which in turn improves the intensity predictions.

Satellite based Nowcasting technique is customized version of Forecast and Tracking the Evolution of Cloud Clusters (ForTraCC), it uses the extrapolation technique that allows for the tracking of Mesoscale convective systems (MCS) radiative and morphological properties and forecasts the evolution of these properties (based on cloud-top brightness temperature and area of the cloud cluster) up to 360 minutes, using infrared satellite imagery. The Thermal Infrared (TIR) channel of the weather satellite has been broadly used to study the behaviour of the cloud systems associated with deep convection. The main advantage of this approach is that for most of the globe the best statistics can only be obtained from satellite observations. Such a satellite survey would provide the statistics of MCSs covering the range of meteorological conditions needed to generalize the result and on the other hand only satellite observations can cover the very large range of space and time scale. The algorithm script is taken from Brazilian Scientist Dr. Danial Vila and implemented it into the Indian environment and made compatible with INSAT-3D hdf5 data format. For Indian region it utilizes the INSAT-3D satellite data of TIR1 (10.8 μm) channel and creates nowcast. The output is made compatible with GUI based software MIAS by generating the output in hdf5 format for better understanding and analysis of forecast. The main features of this algorithm are detection of Cloud Cluster based on Cloud Top Brightness Temperature (CTBT) and area i.e. ≤235 ºK and ≥2400 km2 respectively. The tracking technique based on MCS overlapping areas in successive images. The script has been automized in Auxiliary Data Processing System (ADPS) and generating the forecast file in every half an hour and convert the output file in geotiff format. The geotiff file is easily converted into KMZ file format using ArcGIS software to overlay it on google map and hosted on the web server.

Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere which is associated with thunder, squall lines and lightening. On 13 April 2010, a severe storm struck parts of Bangladesh and eastern India which lasted about 90 minutes, with the most intense portion spanning 30–40 minutes. The severe Thunderstorm on 13^th April 2010 spawned a large tornado, which lasted about 20 minutes and was the first tornado recorded in Bihar history. In the year 2015, Bihar experienced a similar storm on 21 April during which multiple microbursts were observed. Various meteorological parameters have been analyzed to study the factors affecting the development of the thunderstorm. Satellite images from KALPANA and Meteosat has been analyzed to capture the temporal and spatial evolution of these storms. The satellite images show the development of a convective clouds system in the early afternoon hours which developed further into the severe storms by late evening. The analysis carried out further using K-index, lifted index, CAPE etc also shows the development of multiple cells of convection. Further analysis of these storms is presented in the paper.

During the month of June 2015, the South Asian (or Southwest) monsoon advanced steadily from the southern to the northwestern states of India. The progression of the monsoon had an apparent effect on the relative strength of convective storm downbursts that occurred during June and July 2015. A convective downburst prediction algorithm, involving the Microburst Windspeed Potential Index (MWPI) and a satellite-derived three-band microburst risk product, and applied with meteorological geostationary satellite (KALPANA-1 VHRR and METEOSAT-7) and MODIS Aqua data, was evaluated and found to effectively indicate relative downburst intensity in both pre-monsoon and monsoon environments over various regions of India. The MWPI product, derived from T574L64 Global Forecast System (NGFS) model data, is being generated in real-time by National Center for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences, India. The validation process entailed direct comparison of measured downburst-related wind gusts at airports and India Meteorological Department (IMD) observatories to adjacent MWPI values calculated from GFS and India NGFS model datasets. Favorable results include a statistically significant positive correlation between MWPI values and proximate measured downburst wind gusts with a confidence level near 100%. Case studies demonstrate the influence of the South Asian monsoon on convective storm environments and the response of the downburst prediction algorithm.

Atmospheric convection is a natural phenomena associated with heat transport. Convection is strong during daylight periods and rigorous in summer months. Severe ground heating associated with strong winds experienced during these periods. Tropics are considered as the source regions for strong convection. Formation of thunder storm clouds is common during this period. Location of cloud base and its associated dynamics is important to understand the influence of convection on the atmosphere. Lidars are sensitive to Mie scattering and are the suitable instruments for locating clouds in the atmosphere than instruments utilizing the radio frequency spectrum. Thunder storm clouds are composed of hydrometers and strongly scatter the laser light.

Recently, a lidar technique was developed at National Atmospheric Research Laboratory (NARL), a Department of Space (DOS) unit, located at Gadanki near Tirupati. The lidar technique employs slant path operation and provides high resolution measurements on cloud base location in real-time. The laser based remote sensing technique allows measurement of atmosphere for every second at 7.5 m range resolution. The high resolution data permits assessment of updrafts at the cloud base. The lidar also provides real-time convective boundary layer height using aerosols as the tracers of atmospheric dynamics. The developed lidar sensor is planned for up-gradation with scanning facility to understand the cloud dynamics in the spatial direction.

In this presentation, we present the lidar sensor technology and utilization of its technology for high resolution cloud base measurements during convective conditions over lidar site, Gadanki.

Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes associated with the aerosolcloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regional of the world. Contrary to the cloud-free scenario over dark surface, for which aerosols are known to produce a net cooling effect (negative radiative forcing) on climate, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud depends directly on the aerosol loading, microphysical-optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of optical depth of absorbing aerosols above clouds retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA’s Aura platform. The presence of absorbing aerosols above cloud reduces the upwelling radiation reflected by cloud and produces a strong ‘color ratio’ effect in the near-UV region, which can be unambiguously detected in the OMI measurements. Physically based on this effect, the OMACA algorithm retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. The algorithm architecture and results from a ten-year global record including global climatology of frequency of occurrence and above-cloud aerosol optical depth, and a discussion on related future field campaigns are presented.

The dynamical characteristics of atmospheric aerosols over the Indo-Gangetic (IG) region are primarily dependent on the geographical settings and meteorological conditions. Detailed analysis of multi satellite data and ground observations have been carried out over three different cities i.e. Kanpur, Greater Noida and Amritsar during 2010-2013. Level-3 Moderate Resolution Imaging Spectroradiometer (MODIS) terra daily global grid product with spatial resolution of 1° × 1° shows the mean AOD at 500 nm wavelength value of 0.73, 0.70 and 0.67 with the standard deviation of 0.43, 0.39 and 0.36 respectively over Amritsar, Greater Noida and Kanpur. Our detailed analysis shows characteristic behavior of aerosols from west to east in the IG region depending upon the proximity of desert regions of Arabia. We have observed large influx of dusts from the Thar desert and Arabia peninsula during pre-monsoon season (April–June), highly affecting Amritsar which is close to the desert region.

In view of the increasing anthropogenic presence and influence of aerosols in the northern polar regions, long-term continuous measurements of aerosol optical parameters have been investigated over the Svalbard region of Norwegian Arctic (Ny-Ålesund, 79°N, 12°E, 8 m ASL). This study has shown a consistent enhancement in the aerosol scattering and absorption coefficients during spring. The relative dominance of absorbing aerosols is more near the surface (lower single scattering albedo), compared to that at the higher altitude. This is indicative of the presence of local anthropogenic activities. In addition, long-range transported biomass burning aerosols (inferred from the spectral variation of absorption coefficient) also contribute significantly to the higher aerosol absorption in the Arctic spring. Aerosol optical depth (AOD) estimates from ground based Microtop sun-photometer measurements reveals that the columnar abundance of aerosols reaches the peak during spring season. Comparison of AODs between ground based and satellite remote sensing indicates that deep blue algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over Arctic snow surfaces overestimate the columnar AOD.

In the present study, the effect of horizontal and vertical localization scales on the assimilation of direct SAPHIR radiances is studied. An Artificial Neural Network (ANN) has been used as a surrogate for the forward radiative calculations. The training input dataset for ANN consists of vertical layers of atmospheric pressure, temperature, relative humidity and other hydrometeor profiles with 6 channel Brightness Temperatures (BTs) as output. The best neural network architecture has been arrived at, by a neuron independence study. Since vertical localization of radiance data requires weighting functions, a ANN has been trained for this purpose. The radiances were ingested into the NWP using the Ensemble Kalman Filter (EnKF) technique. The horizontal localization has been taken care of, by using a Gaussian localization function centered around the observed coordinates. Similarly, the vertical localization is accomplished by assuming a function which depends on the weighting function of the channel to be assimilated. The effect of both horizontal and vertical localizations has been studied in terms of ensemble spread in the precipitation. Aditionally, improvements in 24 hr forecast from assimilation are also reported.

In the present work, we have evaluated the satellite estimated daily downwelling shortwave (Q_I) and Longwave (Q_A) radiation from Moderate Resolution Imaging Spectrometer (MODIS) /Clouds and the Earth's Radiant Energy System (CM) with moored buoy observations of Global Tropical Moored Buoy Array (GTMBA) during 2001-2009. The global observed mean of Q_I and Q_A in GTMBA (CM) are 228 (233) W/m² and 410 (405) W/m² respectively. The mean Q_I shows a positive bias (~3- 7 W/m²) whereas Q_A underestimates with a mean negative bias of ~3-6 W/m² in the tropical Pacific, Atlantic and Indian Ocean. CM underestimates the buoy observed variability in both Q_I and Q_A in all the tropical oceans. The correlation coefficient (CC) values in Q_I (Qa) are 0.79(0.88) 0.79(0.84) and 0.81(0.94) over the Pacific, Atlantic and Indian ocean respectively. The Root Mean Square Error (RMSE) values in Q_I ranged between 35-43 W/m² with lowest values in the Atlantic Ocean and highest in the Indian Ocean. The RMSE values in Q_A are less as compared to Q_I and it is ~9 W/m² in all the tropical ocean. The spatial distributions of Q_I and Q_A shows seasonality with lower and higher values coinciding with the Inter Tropical Convergence Zone(ITCZ) locations in the Q_I and Q_A.

INSAT-3D, the first Indian geostationary satellite with sounding capability, provides valuable information over India and the surrounding oceanic regions which are pivotal to Numerical Weather Prediction. In collaboration with UK Met Office, NCMRWF developed the assimilation capability of INSAT-3D Clear Sky Brightness Temperature (CSBT), both from the sounder and imager, in the 4D-Var assimilation system being used at NCMRWF. Out of the 18 sounder channels, radiances from 9 channels are selected for assimilation depending on relevance of the information in each channel. The first three high peaking channels, the CO₂ absorption channels and the three water vapor channels (channel no. 10, 11, and 12) are assimilated both over land and Ocean, whereas the window channels (channel no. 6, 7, and 8) are assimilated only over the Ocean. Measured satellite radiances are compared with that from short range forecasts to monitor the data quality. This is based on the assumption that the observed satellite radiances are free from calibration errors and the short range forecast provided by NWP model is free from systematic errors. Innovations (Observation – Forecast) before and after the bias correction are indicative of how well the bias correction works. Since the biases vary with air-masses, time, scan angle and also due to instrument degradation, an accurate bias correction algorithm for the assimilation of INSAT-3D sounder radiance is important. This paper discusses the bias correction methods and other quality controls used for the selected INSAT-3D sounder channels and the impact of bias corrected radiance in the data assimilation system particularly over India and surrounding oceanic regions.

This paper reports the development of a millimeter-wave space-borne atmospheric Temperature Sounding Unit (TSU) in Indian Space Research Organization (ISRO). This is ISRO’s first leap towards millimeter-wave technology. The sensor has several new accomplishments to its credit which include among others, the philosophy of sounding channel selection, the new assortment of temperature sounding channels, simultaneous observation of both polarizations of all channels, compact dual-band scanning Gregorian reflector antenna, indigenously developed black-body target for in-orbit calibration, in-house developed millimeter-wave RF front-end and pre-detection automatic gain control method. The prime feature of this instrument is its unique set of channels which can profile the earth’s atmosphere from surface to 40 km altitude with vertical resolution ranging from less than a km near surface to ±2.5 km at 30km altitude. The channels are predominantly off-resonant frequencies in the 50―60 GHz O₂ absorption spectrum which offer near-uniform attenuation and hence more channel-bandwidth and better temperature sensitivity and yet have adequate overlap of their weighting functions to achieve the desired vertical resolution. These channels are different and have fewer bands from what has been flown in all earlier sounding missions worldwide e.g. AMSU-A, SSMIS, ATMS etc. The TSU radiometer has been characterized thoroughly using ingenious methods such as low-power active RF energizing along with frequency sweep. This is a compact, low-mass, low-power instrument and has been configured for the ISRO mini-satellite (IMS-2) bus. The flight model with improved hardware performance is being built and a suitable opportunity of flying it is being explored.

We examined the spatio-temporal variability of atmospheric CO₂ over India and its surrounding based on Goddard Earth Observation System Chemical (GEOS-Chem) transport model, satellite and in-situ observations. The model was employed at 2x2.5⁰ spatial resolution over the globe with 47 vertical layers between pressure levels 1006-0.01 hPa. It is driven by GEOS meteorological fields along with surface boundary fluxes and anthropogenic emissions from different sources. The model run was performed for the period 2006-2013 and the solutions at three hourly intervals were stored for the analysis. In this paper, we are discussing the seasonal and inter-annual characteristics of simulated atmospheric CO₂ highlighting the uncertainties associated with input data sets in the model. There exist good coherences between model and satellite observation. Simulated CO₂ shows strong seasonality near the surface and has showed decrease in its amplitude upward. Amplitudes of the seasonal and annual cycles are stronger over the northern hemisphere, especially over the land regions.

Formaldehyde (HCHO) is a significant constituent of the atmospheric chemistry involved in a lot of chemical reactions. It is directly emitted by anthropogenic and biogenic sources and, more significantly, by production during oxidation of methane and other VOCs. So HCHO is used as an indicator of local pollution by VOCs.

HCHO has a sufficiently large absorption cross-section in the UV spectral region to be detected by the technique of the differential optical absorption spectroscopy (DOAS). We present here new version 1.3a of the algorithm for retrieval of the HCHO total content in the troposphere from DOAS observations of the scattered solar radiation developed in A.M. Obukhov Institute of Atmospheric Physics (IAP). The new version has reduced retrieval error but negligible bias with respect to the previous versions. DOAS measurements of scattered solar radiation are performed at Zvenigorod Scientific Station (ZSS, 55°41'49''N, 36°46'29''E) located in 38 km west from Moscow Ring Road by a MAX-DOAS instrument since 2008. We provide preliminary results of the HCHO total content measurements in the troposphere observed in 2010-2012 obtained by the revised retrieval algorithm.

Raindrop size distribution (RSD) characteristic variations between two southern Indian stations [Gadanki (13.5° N, 79.2° E) Kadapa (14.47° N, 78.82° E)] using ground based parsivel disdrometer data are studied. Number concentration of mid and large drops is more over Gadanki when compared to Kadapa precipitation. The mean value of mass weighted mean diameter (D_m) is higher in Gadanki than Kadapa precipitation. Both monthly and diurnal variations of D_m show higher values of D_m over Gadanki than Kadapa. After classifying the precipitations systems into stratiform and convective, Gadanki has higher (lower) D_m than Kadapa in stratiform (convective).

Based on their interaction with solar radiations, aerosols may be categorized as absorbing or scattering in nature. The absorbing aerosols are coarser and influence precipitation mainly due to microphysical effect (participating in the formation of Cloud Condensation Nuclei) and radiative forcing (by absorbing electromagnetic radiations). The prominent absorbing aerosols found in India are Black Carbon, soil dust, sand and mineral dust. Their size, distribution, and characteristics vary spatially and temporally. This paper aims at showing the spatio-temporal variation of Absorbing Aerosol Index (AAI) and precipitation over the four most polluted zones of Indian sub-continent (Indo-Gangetic plains 1, Indo-Gangetic plains 2, Central and Southern India) for monsoon season (June, July, August, September) during the last decade (2005 to 2014). Zonal averages AAI have been found to be exhibiting an increasing trend, hence region-wise correlations have been computed between AAI and precipitation during monsoon. Daily Absorption Aerosol Index (AAI) obtained from Aura OMI Aerosol Global Gridded Data Product-OMAEROe (V003) and monthly precipitation from TRMM 3B42-V7 gridded data have been used.

Satellites play a major role in understanding the spatial and vertical distribution of aerosols and cloud microphysical parameters over a large area. However, the inherent limitations in satellite retrievals can be improved through inter-comparisons with airborne platforms. Over the Indian sub-continent, the vertical profiles retrieved from space-borne lidar such as CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) on board the satellite CALIPSO and Cloud Profiling Radar (CPR) on board the satellite CloudSat were inter- compared with the aircraft observations conducted during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX). In the absence of high clouds, both aircraft and CALIOP showed similar features of aerosol layering and water-ice cloud signatures. As CALIOP could not penetrate the thick clouds, the aerosol information below the cloud is missed. While the aircraft could measure high concentrations below the cloud base and above the low clouds in the presence of high clouds. The aircraft derived liquid water content (LWC) and droplet effective radii (R_e) showed steady increase from cloud base to cloud top with a variable cloud droplet number concentration (CDNC). While the CloudSat derived LWC, CDNC and R_e showed increase from the cloud top to cloud base in contradiction to the aircraft measurements. The CloudSat profiles are underestimated as compared to the corresponding aircraft profiles. Validation of satellite retrieved vertical profiles with aircraft measurements is very much essential over the tropics to improve the retrieval algorithms and to constrain the uncertainties in the regional cloud parameterization schemes.

Cirrus clouds are mainly composed of ice crystals and are known to be the major natural contributors to radiative forcing in the Earth’s atmosphere system. Describing the formation and microphysical properties of cirrus clouds and their role in climate models remain a challenging study. Lidar is a unique instrument, which provides the information on the optical and microphysical properties of cirrus clouds with good spatial and temporal resolutions. In this study we present the microphysical properties of cirrus clouds and their temporal variability, obtained using the ground based dual polarisation lidar at the tropical station Gadanki (13.5° N and 79.2° E), India, during the period January2009 to March 2011. Using the method developed in house for deriving range dependent lidar ratio (LR), the lidar measurements are used for deriving the extinction coefficient and to obtain the nature of the scatterers present in the cloud. It is noted that lidar ratio plays an important role and its measurements indicate directly the type of the ice nucleating aerosol particles present in the cloud. The long term data obtained on the structure of the cirrus in this regard are useful in the climate modelling studies.

Convective downdraft motions and related outflow wind considered as an eventual source of potential damage which can be more severe in the aviation sector. A great variety of atmospheric environments can produce these downdraft motions. These events are not easily detectable using conventional weather radar or wind shear alert systems, while Doppler radars are useful for identifying these Downbursts. In order to identify the situations that can cause these downdraft events different diagnostic tools are designed. Recently launched Indian satellite INSAT-3D, with atmospheric sounder and imager on board, is capable of identifying regions of downburst occurrence and can help in monitoring them in real time. Some Downburst events reported over different parts of India, during January-April period is investigated using Microburst Wind Speed Potential Index (MWPI) and thermodynamic characteristics derived from the NCMRWF GFS (NGFS) model. An attempt is made to make a short range prediction of these events using MWPI computed from NGFS model forecasts. The results are validated with in-situ observations and also by employing INSAT-3D data and it is shown that the method has a reasonable success. All the investigated downdraft events are associated with the hybrid Microburst environment.

The concentration of atmospheric pollutants and greenhouse gases needs to be precisely monitored for sustainable industrial development and to predict the climate shifts caused by global warming. Such measurements are made on a continuous basis in ecologically sensitive and urban areas in the advanced countries. Tunable diode laser spectroscopy (TDLS) is the most versatile non-destructive technology currently available for remote measurements of multiple gases with very high selectivity (low cross-sensitivity), very high sensitivity (on the order of ppm and ppb) and under hazardous conditions. We demonstrate absolute measurements of acetylene, methane and carbon dioxide using a fielddeployable fully automated TDLS system that uses calibration-free 2f wavelength modulation spectroscopy (2f WMS) techniques with sensitivities of low ppm levels. A 40 mW, 1531.52 nm distributed feedback (DFB) diode laser, a 10 mW, 1650 nm DFB laser and a 1 mW, 2004 nm vertical cavity surface emitting laser (VCSEL) are used in the experiments to probe the P9 transition of acetylene, R4 transition of methane and R16 transition of carbon dioxide respectively. Data acquisition and on-board analysis comprises a Raspberry Pi-based embedded system that is controllable over a wireless connection. Gas concentration and pressure are simultaneously extracted by fitting the experimental signals to 2f WMS signals simulated using spectroscopic parameters obtained from the HITRAN database. The lowest detected concentration is 11 ppm for acetylene, 275 ppm for methane and 285 ppm for carbon dioxide using a 28 cm long single-pass gas cell.

The cirrus clouds play an important role in the Earth’s radiation budget due to their high frequency of occurrence, non-spherical ice crystal formations, and variability in the scattering/absorption characteristics. Mostly, the tropical cirrus clouds are considered as greenhouse modulators. Thus the parameterization of tropical cirrus clouds in terms of the micro- physical properties and the corresponding radiative effects are highly important for the climate studies. For characterizing the radiative properties of cirrus clouds, which depend on the size, shape and number of the ice crystals, the knowledge of extinction coefficient (σ) and optical depth (τ) are necessary. The σ provides information needed for understanding the influence of the scatterers on the radiative budget whereas the τ gives an indication on the composition and thickness of the cloud. Extensive research on the tropical cirrus clouds has been carried out by using a ground based and satellite based lidar systems. In this work, the characteristics of tropical cirrus cloud derived by using the data from the ground based lidar system over the tropical site Gadanki [13.5°N, 79.2°E], India during 2010 are presented. Some of the results are compared with those obtained by us from satellite based CALIOP lidar observations of the CALIPSO mission. It is observed that there is a strong dependence of the some of the physical properties such as occurrence height, cloud temperature and the geometrical thickness on the microphysical parameters in terms of extinction coefficient and optical depth. The correlation of both the σ and τ with temperature is also observed.

A compact dual polarization lidar (DPL) was designed and developed at National Atmospheric Research Laboratory (NARL) for daytime measurements of the boundary layer aerosol distribution and depolarization properties with very high vertical and temporal resolution. The lidar employs a compact flashlamp pumped Q-switched Nd:YAG laser and operates at 532 nm wavelength. The lidar system uses a stable biaxial configuration between transmitter and receiver units. The receiver utilizes a 150 mm Schmidt Cassegranin telescope for collecting laser returns from the atmosphere. The collected backscattered light is separated into co and cross-polarization signals using a polarization beam splitter cube. A set of mini-PMTs have been used for detection of light from atmosphere during daylight period. A two channel transient recorder system with built-in ADC has been employed for recording the detected light. The entire lidar system is housed in a compact cabinet which can be easily transported for field measurements. During 2014, the lidar system was installed at the Banaras Hindu University (BHU) campus, Varanasi (25.28° N, 82.96° E, 82 m AMSL) and operated for a period of three months in to support the cloud aerosol interaction and precipitation enhancement experiment (CAIPEEX) conducted by Indian Institute of tropical meteorology (IITM). During this campaign period, the lidar measurements were carried out in the vertical direction with spatial resolution of 7.5 m and time sampling of 30s. The lidar measurements revealed the occurrence of boundary layer growth during convective periods and also detected the long-range transport dust layers with significant depolarization. In the present paper, we present the lidar measurements obtained during the campaign period and discuss the observation of transport of dust layer over the experimental site with support of back trajectory analysis and satellite data. The Lidar observations were compared with the available satellite observations also presented here.

A synergistic use of satellite and ground based remote sensing data has been utilized to analyze recent changes in the aerosol column loading over the Indo Gangetic Plain (IGP). Despite an overall statistically significant increase in the trend of annual mean aerosol optical depth (AOD) over the past decade, a prominent difference within seasons was observed. Summer and monsoon seasons have a slight decreasing trend, while post monsoon and winter have significant increasing trend. The optically equivalent composition inferred from ground based long term measurements of aerosol size and absorption characteristics reveals that summer and monsoon season are mostly dust dominated. Whereas, post monsoon and winter seasons are dominated by black carbon (BC) and/or other absorbing aerosols. We find that the observed decrease in AOD is associated with decrease in dust loading in the atmosphere with a large spatial extent covering the whole of North-Western part of India and IGP. Similar changes are associated with absorbing carbonaceous aerosol species during the periods showing an increasing trend. The decreasing dust loading over Indian region during summer along with increase in absorbing black carbon aerosols during the pre-monsoon and the monsoon period may have significant impact on aerosol radiative forcing and hence Indian summer monsoon rainfall.

Tropospheric carbon monoxide (CO) is an air pollutant and indirect greenhouse gas which plays a major role in atmospheric chemistry involving hydroxyl (OH) radical. We utilised the remote-sensing retrievals of lower-tropospheric CO (at 900 hPa) from Measurements of Pollution in the Troposphere (MOPITT) aboard Terra-satellite for the period of ~15 years. Using simple linear regression model, we estimated the decreasing trend of ~0-2 %year^-1 in the lowertropospheric CO over the globe. Utilising the in-situ measurements of surface-CO over 83 locations carried out by the NOAA (National Oceanic and Atmospheric Administration) network, we confirmed the observed negative trend as surface-CO showed decreasing trend over most of the locations. To estimate the trend in columnar CO, we utilised multiple retrievals of from different satellites, MOPITT, AIRS (Atmospheric InfraRed Sounder), and TES (Tropospheric Emission Spectrometer). All data sets show the decreasing trend of 0.2-0.5 %year^-1 in columnar CO when averaged over entire globe. However, the heterogeneity in the trend is observed on regional basis. The retrievals of upper-tropospheric CO (at 200 hPa) from MOPITT and AIRS show an increasing trend of 1-4 %year^-1 over the globe. However, the retrievals of upper-tropospheric CO from MLS (Microwave Limb Sounder) show decreasing trend. Further investigations are needed to confirm the trend in the upper-tropospheric CO over the globe. The decreasing trend in lower-tropospheric CO and columnar CO could be due to moistening of troposphere and/or increase in tropospheric ozone, causing increase in OH radical (strengthening the depletion of lower-tropospheric CO).

Aerosol Optical Depth (AOD) products available from MODIS and MISR observations are widely used for aerosol characterization, and global/environmental change studies. These products are based on different retrieval-algorithms, resolutions, sampling, and cloud-screening schemes, which have led to global/regional biases. Thus a merged product is desirable which bridges this gap by utilizing strengths from each of the sensors. In view of this, we have developed a “merged” AOD product based on MODIS and MISR AOD datasets, using Bayesian principles which takes error distributions from ground-based AOD measurements (from AERONET). Our methodology and resulting dataset are especially relevant in the scenario of combining multi-sensor retrievals for satellite-based climate data records; particularly for long-term studies involving AOD. Specifically for MISR AOD product, we also developed a methodology to produce a gap-filled dataset, using geostatistical methods (e.g. Kriging), taking advantage of available MODIS data. Merged and spatially-complete AOD datasets are inter-compared with other satellite products and with AERONET data at three stations- Kanpur, Jaipur and Gandhi College, in the Indo-Gangetic Plains. The RMSE of merged AOD (0.08-0.09) is lower than MISR (0.11-0.20) and MODIS (0.15-0.27). It is found that merged AOD has higher correlation with AERONET data (r within 0.92-0.95), compared to MISR (0.74-0.86) and MODIS (0.69-0.84) data. In terms of Expected Error, the accuracy of valid merged AOD is found to be superior as percent of merged AOD within error envelope are larger (71-92%), compared to MISR (43-61%) and MODIS (50-70%).

Impact of aerosols on the Indian summer monsoon (ISM) variability is well documented; however there are limited studies which have quantified the role of aerosols in modifying the amount of rainfall. To address this research problem, we make use of the remotely sensed data set of precipitation and aerosols from different observations. In the present study remotely sensed precipitation data set has been utilised to define contrasting monsoon conditions over the Himalayan region. As per the classical definition, active and break spells are defined over the central part of the Indian land region, and during the break spells over the central Indian region, the Himalayan region receives substantial amount of rainfall. It is found that accumulation of more dust over the Uttarakhand region significantly (negative correlation with rainfall; significant at 5% significance level) suppresses the rainfall during break spells. We propose that the substantial aerosol loading and its associated dynamical feedback over the Himalayan foothills may have considerable impact on the amount of rainfall over the mountainous regions of the Indian subcontinent. Results presented in this paper are supported by the statistically robust significance test and would be useful to develop the understanding of the role of aerosols in modulating the rainfall intensity during the summer monsoon season.

This paper aims at comparing the INSAT-3D AOD with other space based observations over the continental regions. INSAT-3D launched in 2013 is an advanced geostationary weather satellite of India at 82° East longitude provides Aerosol Optical Depth (AOD) observations at 650 nm over both land and ocean. The level-3 daily AOD measurements from MODIS (both Aqua and Terra) and MISR are used for comparison with that from INSAT-3D. This work is applied during premonsoon season of 2015. Overall statistical scores and systematic errors are compared to characterize various error sources. Our study indicates that significant differences exist between different aerosol observations which may be partly due to retrieval algorithm, sensor configurations and temporal sampling. Comparison of INSAT observed AOD shows less bias towards MISR and MODIS-Terra observed AOD than with MODIS-Aqua. The INSAT observations over oceanic region have better correlation, minimum bias and rmse than land region. Overall, the mean bias of the dataset is ±0.05, with a root mean square error of 0.22, but these errors are also found highly dependent on geographical region. Additionally, we compared INSAT 660 nm AOD with two AERONET ground stations. The comparison of INSAT with different observations shows that the retrieved AOD is closer to the ground-based data than the MISR and MODIS AOD.

In the present study, an intense unseasonal dust storm has been analyzed during third week of March 2012 from multi satellite datasets and from surface measurements over National Capital Region (NCR), Delhi. The intrusion of dust over study region has increased the MODIS Aerosol Optical Depth at 550 nm more than 1.0 whereas significant decrease in Angstrom Exponent (α) has been observed . Very high UV aerosol Index (> 2) over study location indicates the presence of UV absorbing aerosols . Fire activities are found to be negligible over the source region confirming the effect of dust storm. Strong southwesterly winds prevailed over northern Arabian Sea which trans ported the dust plume across the oceanic region towards Indian capital region. In-situ measurements of PM 2.5 and PM10, obtained from CPCB observational site over the IGI airport, NCR Delhi, showed abrupt increase on 20, 21 March. Eight hourly average concentration of the particulate matters less than 10 μm (PM10) is found to be ~990 μg/m³ and particulate matters less than 2.5 μm (PM2.5) is found to be ~900 μg/m³ over IGI Airport, NCR Delhi. These values are remarkably higher as compared to the daily National Ambient Air Quality Standards (NAAQS) i.e. 100 μg/m³ and 60 μg/m³ for PM10 and PM2.5 respectively. In addition, Vertical distribution of dust has been examined using CALIPSO observation. The layer of dust is found to be trapped within lower 3 km in altitude. The Potential Source Contribution Function (PSCF) modeling has been carried out to identify the specific source locations.

Atmospheric aerosols in the Indo-Gangetic Plain (IGP) depicts high spatial and temporal heterogeneity in their radiative properties. Despite the fact that significant advancement in terms of characterizing aerosols radiative and physiochemical properties in the IGP have been made, information regarding the organic content towards total absorbing aerosol budget is lacking. In the present study we have analyzed two years of aerosol spectral light absorption measurements from the central-IGP, Gorakhpur (26.75°N, 83.38°E, 85m amsl), in order to study their seasonal behavior and to quantify their magnitude in terms of absorbing aerosols loading and source speciation. Remote sensing data in the form of 'Cloud corrected Fire Count' from MODIS Terra and 'Absorption Aerosol Index' from OMI satellites platform have been used to identify absorbing aerosol source regions. Spectral absorption analysis reveals a four-fold enhancement in absorption in the winter (W) and the post-monsoon (PoM) seasons at UV wavelengths as compared to 880 nm on account of increased biomass aerosol contribution to total absorbing aerosol load. Despite having higher fire events and absorption aerosol index, both indicating high biomass burning activities, in the pre-monsoon (PM) season, aerosols from the biomass sources contribute ~ 27% during the W and the PoM seasons as against ~17% in the PM season to the total absorbing aerosol content. This is due to near stagnant wind conditions and shallow height of air masses travelling to the central IGP in the W and the PoM seasons.

During the Northeast monsoon season, India receives about 11% of its annual rainfall. Many districts in South Peninsula receive 30-60% of their annual rainfall. Coastal Tamil Nadu receives 60% of its annual rainfall and interior districts about 40-50 %. During the month of November, 2015, three synoptic scale weather systems affected Tamil Nadu and Pondicherry causing extensive rainfall activity over the region. Extremely heavy rains occurred over districts of Chennai, Thiruvallur and Kancheepuram, due to which these 3 districts were fully inundated. 122 people in Tamil Nadu were reported to have died due to the flooding, while over 70,000 people had been rescued. State government reported flood damage of the order of around Rs 8481 Crores. The rainfall received in Chennai district during 1.11.2015 to 5.12.2015 was 1416.8 mm against the normal of 408.4 mm. The extremely heavy rains were found to be associated with strong wind surges at lower tropospheric levels, which brought in lot of moisture flux over Chennai and adjoining area. The subtropical westerly trough at mid-tropospheric levels extended much southwards than its normal latitude, producing favorable environment for sustained rising motions ahead of approaching trough over coastal Tamil Nadu. Generated strong upward velocities in the clouds lifted the cloud tops to very high levels forming deep convective clouds. These clouds provided very heavy rainfall of the order of 150-200 mm/hour. In this paper we have used radar data to examine and substantiate the cloud burst that led to these torrential rains over Chennai and adjoining areas during the Northeast Monsoon period, 2015.

Space based remote sensing provides continuous and contiguous information about the state of the Earth-atmosphere system which is crucial to Numerical Weather Prediction (NWP). Since 1960, after the successful launch of the first weather satellite TIROS-1, a range of weather satellites carrying different sensors to monitor atmospheric parameters used in NWP have not only improved the weather forecasting but also enhanced our understanding of the physical and dynamical processes in the atmosphere. Satellite based earth observing system provides data in different spatial and temporal resolutions from the geostationary and low-earth orbits. This review briefly describes general introduction to both active and passive satellite remote sensing, various satellite sensors used for NWP applications in the past an d in the present and observational data requirements for future NWP models. The presentation also includes the importance of re-calibration of satellite observations of the past, especially the data from Indian satellites (INSAT series) which can be used in the atmospheric reanalysis in the future.

Arid regions of North Africa are considered as one of the major dust source. Present study focuses on the forecast of aerosol optical depth (AOD) of dust over different regions of North Africa. NCMRWF Unified Model (NCUM) produces dust AOD forecasts at different wavelengths with lead time upto 240 hr, based on 00UTC initial conditions. Model forecast of dust AOD at 550 nm up to 72 hr forecast, based on different initial conditions are verified against satellite and ground based observations of total AOD during May–June 2014 with the assumption that except dust, presence of all other aerosols type are negligible. Location specific and geographical distribution of dust AOD forecast is verified against Aerosol Robotic Network (AERONET) station observations of total and coarse mode AOD. Moderate Resolution Imaging Spectroradiometer (MODIS) dark target and deep blue merged level 3 total aerosol optical depth (AOD) at 550 nm and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrieved dust AOD at 532 nm are also used for verification. CALIOP dust AOD was obtained by vertical integration of aerosol extinction coefficient at 532 nm from the aerosol profile level 2 products. It is found that at all the selected AERONET stations, the trend in dust AODs is well predicted by NCUM up to three days advance. Good correlation, with consistently low bias (~ ±0.06) and RMSE (~ 0.2) values, is found between model forecasts and point measurements of AERONET, except over one location Cinzana (Mali). Model forecast consistently overestimated the dust AOD compared to CALIOP dust AOD, with a bias of 0.25 and RMSE of 0.40.

In recent years, the aerosol loading in India is increasing that has significant impact on the weather/climatic conditions. The present study discusses the analysis of temporal (monthly and seasonal) variation of aerosol optical depth(AOD) by the ground based observations from sun photometer and estimate the aerosol radiative forcing and heating rate over selected station Dehradun in North western Himalayas, India during 2015. The in-situ measurements data illustrate that the maximum seasonal average AOD observed during summer season AOD at 500nm ≈ 0.59±0.27 with an average angstrom exponent, α ≈0.86 while minimum during winter season AOD at 500nm ≈ 0.33±0.10 with angstrom exponent, α ≈1.18. The MODIS and MISR derived AOD was also compared with the ground measured values and are good to be in good agreement. Analysis of air mass back trajectories using HYSPLIT model reveal that the transportation of desert dust during summer months. The Optical Properties of Aerosols and clouds (OPAC) model was used to compute the aerosol optical properties like single scattering albedo (SSA), Angstrom coefficient (α) and Asymmetry(g) parameter for each day of measurement and they are incorporated in a Discrete Ordinate Radiative Transfer model, i.e Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) to estimate the direct short-wave (0.25 to 4 μm) Aerosol Radiative forcing at the Surface (SUR), the top-of-atmosphere (TOA) and Atmosphere (ATM). The maximum Aerosol Radiative Forcing (ARF) was observed during summer months at SUR ≈ -56.42 w/m², at TOA ≈-21.62 w/m² whereas in ATM ≈+34.79 w/m² with corresponding to heating rate 1.24°C/day with in lower atmosphere.

Current study uses Satellite and Reanalysis data to quantify the effect of aerosol on ET at various space and time scales. All the data are obtained for the period June 2008 to May 2009 over Dibrugarh district, Assam, Indi a where NDVI has limited change of through the year. Monthly Evapo-Transpiration (ET, cumulative), Normalized Difference Vegetation Index (NDVI) and Aerosol Optical Depth (AOD) are retrieved from satellite images of Terra-MODIS. The AOD data are evaluated against in-situ observations. Maximum values of AOD are observed in the pre-monsoon season while minimum AOD values are perceived in October and November. Aerosol Radiative Forcing (ARF) is calculated by using the MERRA data sets of ‘clean-clear radiation’ and ‘clear-radiation’ at surface over the study area. Maximum aerosol radiative forcing is observed during the pre-monsoon season; this is in tune with ground observations. Strong positive correlation (r=0.75) between ET and NDVI is observed and it is found that the dense vegetative surfaces exhibit higher rate of evapo-transpiration. A strong positive correlation (r= -0.85) between ARF at surface and AOD is observed with radiative forcing efficiency of 35 W/m2. A statistical regression equation of ET a s a function of NDVI and AOD i.e. ET = 0.25 + (-84.27) * AOD + (131.51) * NDVI, is obtained that shows a correlation of 0.824.

Cirrus clouds have been identified as one of the atmospheric component which influence the radiative processes in the atmosphere and plays a key role in the Earth Radiation Budget. CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) is a joint NASA-CNES satellite mission designed to provide insight in understanding of the role of aerosols and clouds in the climate system. This paper reports the study on the variation of cirrus cloud optical properties of over the Indian sub - continent for a period of two years from January 2009 to December 2010, using cloud-aerosol lidar and infrared pathfinder satellite observations (Calipso). Indian Ocean and Indian continent is one of the regions where cirrus occurrence is maximum particularly during the monsoon periods. It is found that during the south-west monsoon periods there is a large cirrus cloud distribution over the southern Indian land masses. Also it is observed that the north-east monsoon periods had optical thick clouds hugging the coast line. The summer had large cloud formation in the Arabian Sea. It is also found that the land masses near to the sea had large cirrus presence. These cirrus clouds were of high altitude and optical depth. The dependence of cirrus cloud properties on cirrus cloud mid-cloud temperature and geometrical thickness are generally similar to the results derived from the ground-based lidar. However, the difference in macrophysical parameter variability shows the limits of space-borne-lidar and dissimilarities in regional climate variability and the nature and source of cloud nuclei in different geographical regions.

Gorakhpur (26.75°N, 83.38°E and 85 m amsl), is strategically located in the central Indo-Gangetic Plain (IGP), near the foot hills of Himalayas and hence is an ideal place for studying long-range transport as well as local sources of aerosols and its radiative implications. Here we present results from two years, October 2013 until September 2015, of measurements of spectral aerosol optical depth (AOD) utilizing ground based, Multi- Wavelength Radiometer (MWR), and satellite, MODIS Terra remote sensing platforms. Mean AOD at 500 nm (AOD₅₀₀) is 0.63±0.35, associated with a moderate Angstrom exponent (α) of 1.03±0.22 is found for the study period using MWR measurements. Highest AOD₅₀₀ is found during the pre-monsoon months of May and June while lowest AOD₅₀₀ in the post-monsoon months of October and November. The MWR observations have been compared with MODIS Terra derived AOD and a good correlation of 0.74 is found. We used HYSPLIT Lagrangian trajectory model to investigate long-range transport of aerosols to the study region. Aerosol sources in winter season are from the North-West part of the study region while that during pre-monsoon season lies in the south-westerly arid regions. This finding is also reflected in the α values which are high during winter months suggesting significant urban and biomass-burning contribution. α values are low and the turbidity coefficient (β) is high during pre-monsoon months indicating long-range transport of coarse dust particles carried by south westerly winds from the westerly desert regions.

This study examines the influence of Purdue-Lin microphysical parameterization scheme (Lin et al.,1983) on quantitative precipitation for pre-monsoon/monsoon conditions over southern peninsular India in the Weather Research and Forecasting (WRF) model. An ideal microphysical scheme has to describe the formation, growth of cloud droplets and ice crystals and fall out as precipitation. Microphysics schemes can be broadly categorized into two types: bin and bulk particle size distribution (Morrison, 2010). Bulk schemes predict one or more bulk quantities and assume some functional form for the particle size distribution. For better parameterization, proper interpretation of these hydrometeors (Cloud Droplets, Raindrops, Ice Crystals and Aggregates, Rimed Ice Particles, Graupel, Hail) and non-hydrometeors (Aerosols vs. Condensation Nuclei vs. Cloud Condensation Nuclei vs. Ice Nuclei) is very important. The Purdue-Lin scheme is a commonly used microphysics scheme in WRF model utilizing the “bulk” particle size distribution, meaning that a particle size distribution is assumed. The intercept parameter (N₀) is, in fact, turns out to be independent of the density. However, in situ observations suggest (Haddad et al., 1996, 1997) that the mass weighted mean diameter is correlated with water content per unit volume (q), leading to the fact that N0 depends on it. Here, in order to analyze the correlation of droplet size distribution with the convection, we have carried out simulations by implementing a consistent methodology to enforce a correlation between N0 and q in the Purdue-Lin microphysics scheme in WRF model. The effect of particles in Indian Summer Monsoon has been examined using frequency distribution of rainfall at surface, daily rainfall over the domain and convective available potential energy and convective inhibition. The simulations are conducted by analyzing the maximum rainfall days in the pre-monsoon/monsoon seasons using Tropical Rainfall Measuring Mission (TRMM) accumulated rainfall data for 24 hours.

Thar desert located in northwest part of India is considered as one of the major dust source. Dust storms originate in Thar desert during pre-monsoon season, affects large part of Indo-Gangetic plains. High dust loading causes the deterioration of the ambient air quality and degradation in visibility. Present study focuses on the identification of dust events and verification of the forecast of dust events over Delhi and western part of IG Plains, during the pre-monsoon season of 2015. Three dust events have been identified over Delhi during the study period. For all the selected days, Terra-MODIS AOD at 550 nm are found close to 1.0, while AURA-OMI AI shows high values. Dust AOD forecasts from NCMRWF Unified Model (NCUM) for the three selected dust events are verified against satellite (MODIS) and ground based observations (AERONET). Comparison of observed AODs at 550 nm from MODIS with NCUM predicted AODs reveals that NCUM is able to predict the spatial and temporal distribution of dust AOD, in these cases. Good correlation (~0.67) is obtained between the NCUM predicted dust AODs and location specific observations available from AERONET. Model under-predicted the AODs as compared to the AERONET observations. This may be mainly because the model account for only dust and no anthropogenic activities are considered. The results of the present study emphasize the requirement of more realistic representation of local dust emission in the model both of natural and anthropogenic origin, to improve the forecast of dust from NCUM during the dust events.

The latent heat released/absorbed in the Earth’s atmosphere due to phase change of water molecule plays a vital role in various atmospheric processes. It is now well established that the latent heat released in the clouds is the secondary source of energy for driving the atmosphere, the Sun being the primary. In this context, studies on latent heat released in the atmosphere become important to understand the some of the physical processes taking place in the atmosphere. One of the important implications of latent heat release is its role in driving the circulations on various temporal and spatial scales. Realizing the importance of latent heat released in the clouds, a comprehensive study is carried out to understand its role in driving the mesoscale circulation. As Indian summer monsoon (ISM) serves as natural laboratory for studying the clouds and their microphysics, an attempt is made to explore the latent heat distribution over this region using 13 years of Tropical Rainfall Measuring Mission (TRMM) observations. The observed profiles of latent heating over ISM region showed large spatial and temporal variability in the magnitude thus reflecting the presence of organization of convection on mesoscale. The latent profiles in convective and stratiform regions are segregated to study the differences in their interaction with large-scale environment. Various re-analysis dataset were used to examine the role of latent heating distribution on the mesoscale circulation. The significance of the present study lies in establishing the vertical distribution of latent heating and their impact on the background circulation.

In recent years, PM2.5 air pollution is a social and transboundary environmental issue with the rapid economic growth in many countries. As PM2.5 is small and includes various ingredients, the detection of PM2.5 air pollutions by using satellite data is difficult compared with the detection of dust and sandstorms. In this paper, we examine various images (i.e., s