Yogesh K. Tiwari

Impact of climate variability on NDVI over the Indian region during 1981–2010

The normalized difference vegetation index (NDVI), derived from the Advanced Very High Resolution Radiometer (AVHRR) (1981–2000), and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua data (2000–2010) are analysed to examine their spatio-temporal variability over the Indian region. Climatic factors are well known to be associated with vegetation. Therefore, an attempt has also been made in this study to examine the impact of climate variability on NDVI over the Indian region. The average spatio-temporal patterns of NDVI suggest that the variability in NDVI is well associated with climatic factors such as rainfall and temperature. During hot weather, the all-India NDVI shows the lowest values; the values increase from the onset of the summer monsoon season (June–September) onwards over the Indian region. The NDVI attains its peak value in the month of October. The composite annual cycles of NDVI during drought and flood years also show similar features. During drought years, there is a decrease in all-India NDVI for all months. Opposite features are seen during flood years, with a substantial increase in all-India NDVI from the month of October onwards compared to normal years. This clearly indicates the impact of heavy summer monsoon rainfall over the country on NDVI during winter (October–December) and suggests that soil moisture gained by flood conditions helps the NDVI to increase. In contrast, drought conditions show an immediate effect on NDVI but the incremental changes are of smaller magnitude. Spatial patterns also show similar features, with negative anomalies in NDVI over large parts of the country during drought years and positive anomalies during flood years. There exist year-to-year variations in NDVI depending on the performance of the monsoon. NDVI is positively correlated with rainfall during the southwest (June–September) and northeast (October–December) monsoons over a large part of the country. Also, there exists strong lag correlation between summer monsoon rainfall of the current year and NDVI of the next year, indicating that an increase (decrease) in rainfall during the rainy seasons is favourable (unfavourable) for vegetation during the winter (January and February) and the pre-monsoon season (March–May) of the following year. Thus, the analysis shows significant impact of inter-annual variability of climate on the NDVI over the Indian region. Strong lag correlations between rainfall and NDVI indicate the potential for estimating NDVI over India by the regression method.

Tropical urban aerosol distributions during pre-sunrise and post-sunset as observed with lidar and solar radiometer at Pune, India

Abstract The pre-sunrise and post-sunset differences in the tropical urban aerosol distributions have been studied by conducting coordinated experiments using a continuous wave, bistatic Argon ion lidar and a spectroradiometer at the Indian Institute of Tropical Meteorology, Pune, India during 1997–2000. The results of the study indicate higher aerosol concentration in the air layers close to the ground, and lower concentration aloft on all the days of observations. Further, the concentrations are found to be greater in the early-morning (pre-sunrise) hours and lower in the late-evening (post-sunset) hours during the winter season and vice versa during the pre-monsoon season. These deviations are considered to be due to the convective activity and associated turbulent mixing during the pre-monsoon and close-to-ground and elevated haze layer formations during the winter months over the experimental station.

Influence of monsoons on atmospheric CO2 spatial variability and ground-based monitoring over India.

This study examines the role of Asian monsoons on transport and spatial variability of atmospheric CO2 over the Indian subcontinent, using transport modeling tools and available surface observations from two atmospheric CO2 monitoring sites Sinhagad (SNG) and Cape Rama (CRI) in the western part of peninsular India. The regional source contributions to these sites arise from the horizontal flow in conduits within the planetary boundary layer. Greater CO2 variability, greater than 15 ppm, is observed during winter, while it is reduced nearly by half during summer. The SNG air sampling site is more susceptible to narrow regional terrestrial fluxes transported from the Indo-Gangetic Plains in January, and to wider upwind marine source regions from the Arabian Sea in July. The Western Ghats mountains appear to play a role in the seasonal variability at SNG by trapping polluted air masses associated with weak monsoonal winds. A Lagrangian back-trajectory analysis further suggests that the horizontal extent of regional sensitivity increases from north to south over the Indian subcontinent in January (Boreal winter).

Results of Sun Photometer¿Derived Precipitable Water Content over a Tropical Indian Station

Abstract A compact, hand-held multiband sun photometer (ozone monitor) has been used to measure total precipitable water content (PWC) at the low-latitude tropical station in Pune, India (18°32′N, 73°51′E). Data collected in the daytime (0730–1800 LT) during the period from May 1998 to September 2001 have been used here. The daytime average PWC value at this station is 1.13 cm, and the average for only the clear-sky days is 0.75 cm. PWC values between 0.75 and 1.0 cm have the maximum frequency of occurrence. There is a large day-to-day variability due to varied sky and meteorological conditions. Mainly two types of diurnal variations in PWC are observed. The one occurs in the premonsoon summer months of April and May and shows that forenoon values are smaller than afternoon values. The other type occurs in November and December and shows a minimum around noontime. There is a diurnal asymmetry in PWC in which, on the majority of the days, the mean afternoon value is greater than the forenoon value. This as...

Evaluation of Television Infrared Observation Satellite (TIROS‐N) Operational Vertical Sounder (TOVS) spaceborne CO2 estimates using model simulations and aircraft data

CO2 mixing ratio derived from spaceborne measurements of the Television Infrared Observation Satellite (TIROS-N) Operational Vertical Sounder (TOVS) instrument onboard NOAA-10 available for the time period 1987 - 1991 are evaluated against modeling results and aircraft measurements. The model simulations are based on two transport models and two sets of surface fluxes which have been optimized in order to fit near-surface atmospheric CO2 measurements through a transport model ( using an inverse procedure). In the tropics the zonal mean annual cycle and growth rate of the satellite product are consistent with those of the models. However, north-to-south gradients and spatial distributions for a given month show large differences. There are large regional patterns that can reach 7 ppm in the satellite retrievals ( over regions of a few thousand kilometers wide) but are absent in the model predictions. The root-mean-square (RMS) differences between the models and the satellite product are around 1.7 ppm. One time series of the model CO2 trend is used to extrapolate to the airborne measurement periods ( 1991 - 2003) both the satellite and the model monthly products to the airborne measurement period. The RMS difference between the airborne measurements and the extrapolated model predictions is around 1 ppm, while it is 2 ppm for the satellite estimate. These comparisons suggest that the large spatial variability of TOVS retrievals reflects substantial regional biases and noise which need to be reduced before remotely sensed CO2 from TOVS will help constrain our knowledge of the carbon cycle.

AIRS retrieved CO2 and its association with climatic parameters over India during 2004-2011.

Atmospheric Infrared Sounder (AIRS) retrieved mid-tropospheric Carbon Dioxide (CO2) have been used to study the variability and its association with the climatic parameters over India during 2004 to 2011. The study also aims in understanding transport of CO2 from surface to mid-troposphere over India. The annual cycle of mid-tropospheric CO2 shows gradual increase in concentration from January till the month of May at the rate ~0.6 ppm/month. It decreases continuously in summer monsoon (JJAS) at the same rate during which strong westerlies persists over the region. A slight increase is seen during winter monsoon (DJF). Being a greenhouse gas, annual cycle of CO2 show good resemblance with annual cycle of surface air temperature with correlation coefficient (CC) of +0.8. Annual cycle of vertical velocity indicate inverse pattern compared to annual cycle of CO2. High values of mid-tropospheric CO2 correspond to upward wind, while low values of mid-tropospheric CO2 correspond to downward wind. In addition to vertical motion, zonal winds are also contributing towards the transport of CO2 from surface to mid-troposphere. Vegetation as it absorbs CO2 at surface level, show inverse annual cycle to that of annual cycle of CO2 (CC-0.64). Seasonal variation of rainfall-CO2 shows similarities with seasonal variation of NDVI-CO2. However, the use of long period data sets for CO2 at the surface and at the mid-troposphere will be an advantage to confirm these results.

Atmospheric observations show accurate reporting and little growth in India’s methane emissions

Changes in tropical wetland, ruminant or rice emissions are thought to have played a role in recent variations in atmospheric methane (CH4) concentrations. India has the world’s largest ruminant population and produces ~ 20% of the world’s rice. Therefore, changes in these sources could have significant implications for global warming. Here, we infer India’s CH4 emissions for the period 2010–2015 using a combination of satellite, surface and aircraft data. We apply a high-resolution atmospheric transport model to simulate data from these platforms to infer fluxes at sub-national scales and to quantify changes in rice emissions. We find that average emissions over this period are 22.0 (19.6–24.3) Tg yr−1, which is consistent with the emissions reported by India to the United Framework Convention on Climate Change. Annual emissions have not changed significantly (0.2 ± 0.7 Tg yr−1) between 2010 and 2015, suggesting that major CH4 sources did not change appreciably. These findings are in contrast to another major economy, China, which has shown significant growth in recent years due to increasing fossil fuel emissions. However, the trend in a global emission inventory has been overestimated for China due to incorrect rate of fossil fuel growth. Here, we find growth has been overestimated in India but likely due to ruminant and waste sectors.India’s methane emissions have been quantified using atmospheric measurements to provide an independent comparison with reported emissions. Here Ganesan et al. find that derived methane emissions are consistent with India’s reports and no significant trend has been observed between 2010–2015.

Variability in AIRS CO2 during active and break phases of Indian summer monsoon.

Due to human activities, the atmospheric concentration of Carbon Dioxide (CO2) has been rising extensively since the Industrial Revolution. Indian summer monsoon (ISM) has a dominant westerly component from ocean to land with a strong tendency to ascend and hence may have role in CO2 distribution in lower and middle troposphere over Indian sub-continent. A substantial component of ISM variability arises from the fluctuations on the intra-seasonal scale between active and break phases which correspond to strong and weak monsoon circulation. In view of the above, an attempt is made in this study to examine the AIRS/AQUA satellite retrieved CO2 distribution in response to atmospheric circulation with focus on active and break phase. Correlation analysis indicates the increase in AIRS CO2 linked with strong monsoon circulation. Study also reveals that anomalous circulation pattern during active and break phase show resemblance with high and low values of AIRS CO2. Homogeneous monsoon regions of India show substantial increase in CO2 levels during active phase. Hilly regions of India show strong contrast in CO2 and vertical velocity during active and break phases.

WRF model sensitivity to choice of PBL and microphysics parameterization for an advection fog event at Barkachha, rural site in the Indo-Gangetic basin, India

The present study evaluates the performance of four planetary boundary layer (PBL) parameterization schemes combined with five cloud microphysics schemes in Weather Research Forecasting (WRF) model, specifically for an advection fog event occurred during 4–6 December 2014 at Barkachha, rural site in the Indo-Gangetic plain (IGP). For this purpose, the model was configured over the IGP with 2-km horizontal resolution, and results are compared with detailed micrometeorological data (surface meteorological parameters and fluxes, radiative fluxes, and surface layer wind profiles) gathered during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) Integrated Ground Observational Campaign (IGOC) site located in the IGP. The meteorological conditions conducive for the fog formation have been evaluated. All of the tested PBL-microphysics combination showed substantial bias for surface temperature, radiation fluxes, and wind speed. None of the combination found to be superior in predicting the fog event; however, the local MYNN2.5 combination with the WSM3, WSM6, and Lin microphysics obtained slightly better result at the study location. In general, judging from all simulations of liquid water content (as an indicator for the fog), the above combinations were able to simulate the current fog event but the fog onset, duration, and dissipation were particularly offset.

Remote sensing of spectral signatures of tropospheric aerosols

AbstractWith the launch of the German Aerospace Agencys (DLR) Modular Opto-electronic Scanner (MOS) sensor on board the Indian Remote Sensing satellite (IRS-P3) launched by the Indian Space Research Organization (ISRO) in March 1996, 13 channel multi-spectral data in the range of 408 to 1010 nm at high radiometric resolution, precision, and with narrow spectral bands have been available for a variety of land, atmospheric and oceanic studies. We found that these data are best for validation of radiative transfer model and the corresponding code developed by one of the authors at Space Applications Centre, and called ATMRAD (abbreviated for ATMospheric RADiation). Once this model/code is validated, it can be used for retrieving information on tropospheric aerosols over ocean or land. This paper deals with two clear objectives, viz.,1Validation of ATMRAD model/code using MOS data and synchronously measured atmospheric data, and if found performing well, then to2derive relationship between MOS radiances and Aerosol Optical Thickness (AOT). The data validation procedure essentially involves•near-synchronous measurements of columnar aerosol optical thickness and altitude profiles of aerosol concentration using ground-based multi-filter solar radiometers and Argon-ion Lidar, respectively and•computation of the top-of-the-atmosphere (TOA) radiances from a low reflecting target (near clear water reservoir in the present study) using the ATMRAD model. The results show that the model performance is satisfactory and a relationship between the spectral parameters of MOS radiances and aerosol optical thickness can be established. In this communication, we present the details of the experiments conducted, database, validation of the ATMRAD model and development of the relationship between AOT and MOS radiance.