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Intensification of upwelling along Oman coast in a warming scenario
No full textThe oceanic impact of poleward shift in monsoon low-level jet (MLLJ) is examined using a Regional Ocean Modeling System (ROMS). Two sets of downscaling experiments were conducted using ROMS with boundary and initial conditions from six CMIP5 models. While outputs from the historical run (1981–2000) acts as forcing for the first, the second uses RCP8.5 (2080–2099). By comparing the outputs, it is found that Oman coast will experience an increase in upwelling in tune with MLLJ shift. Consistent with the changes in upwelling and zonal Ekman transport, temperature, salinity, and productivity show significant changes near the Oman coast. The changes in MLLJ causes the coastal wind to angle against the Oman coast in such a fashion that the net upwelling increases in the next century and so does the marine productivity. This study contrasts the general view of weakening of upwelling along the Arabian coasts due to the weakening of monsoon winds
On the variability and increasing trends of heat waves over India
Get PDFOver India, heat waves occur during the summer months of April to June. A gridded daily temperature data set for the period, 1961–2013 has been analyzed to examine the variability and trends in heat waves over India. For identifying heat waves, the Excess Heat Factor (EHF) and 90th percentile of maximum temperatures were used. Over central and northwestern parts of the country, frequency, total duration and maximum duration of heat waves are increasing. Anomalous persistent high with anti-cyclonic flow, supplemented with clear skies and depleted soil moisture are primarily responsible for the occurrence of heat waves over India. Variability of heat waves over India is influenced by both the tropical Indian Ocean and central Pacific SST anomalies. The warming of the tropical Indian Ocean and more frequent El Nino events in future may further lead to more frequent and longer lasting heat waves over India
Predictability of Global Monsoon Rainfall in NCEP CFSv2
No full textThis study evaluates the actual and potential prediction skill of the global monsoon rainfall using hindcast simulations by NCEP CFSv2 at zero to three lead forecast months (L0–L3). It is shown that the model has moderate skill in global monsoon rainfall (GMR) prediction, where the boreal summer monsoon rainfall forecast is more skillful than that of the austral summer. In general, the prediction skill of the GMR (actual and potential) increases with the decrease in lead forecast time, which is true for the all major regional monsoons, except the Australian monsoon. Over the Australian monsoon region, both actual and potential prediction skills in rainfall increase with increase in lead forecast. The forecast skill of tropical SST during austral summer is a maximum at 3 months lead forecast (i.e. July initial conditions) and that is associated with spring predictability barrier. Using partial least square (PLS) regression method, it is shown that the major predictor (first latent vector) of the boreal and austral summer monsoon rainfall variability is ENSO, and the influence of ENSO on rainfall variability is much stronger in the model as compared to the observation. The second PLS regression mode is associated with the non-ENSO variability like tropical Atlantic, Indian, subtropical northwest Pacific Ocean variability, midlatitude interactions etc. However, the model has very poor skill in reproducing the second mode, particularly during the boreal summer monsoon season. It is also shown that a significant part of the Indian summer monsoon rainfall variability is controlled by other than ENSO variability and the model has limited success in capturing that
Significant cooling effect on the surface due to soot particles over Brahmaputra River Valley region, India: An impact on regional climate
No full textBlack carbon (BC) is an important atmospheric aerosol constituent that affects the climate by absorbing (directly) the sunlight and modifying cloud characteristics (indirectly). Here, we present first time yearlong measurements of BC and carbon monoxide (CO) from an urban location of Guwahati located in the Brahmaputra River valley (BRV) in the northeast region of India from 1st July 2013 to 30th June 2014. Daily BC concentrations varied within the range of 2.86 to 11.56μgm(-3) with an annual average of 7.17±1.89μgm(-3), while, CO varied from 0.19 to 1.20ppm with a mean value of 0.51±0.19ppm during the study period. The concentrations of BC (8.37μgm(-3)) and CO (0.67ppm) were ~39% and ~55% higher during the dry months (October to March) than the wet months (April to September) suggesting that seasonal changes in meteorology and emission sources play an important role in controlling these species. The seasonal ΔBC/ΔCO ratios were highest (lowest) in the pre-monsoon (winter) 18.1±1.4μgm(-3)ppmv(-1) (12.6±2.2μgm(-3)ppmv(-1)) which indicate the combustion of biofuel/biomass as well as direct emissions from fossil fuel during the pre-monsoon season. The annual BC emission was estimated to be 2.72Gg in and around Guwahati which is about 44% lower than the mega city 'Delhi' (4.86Gg). During the study period, the annual mean radiative forcing (RF) at the top of the atmosphere (TOA) for clear skies of BC was +9.5Wm(-2), however, the RF value at the surface (SFC) was -21.1Wm(-2) which indicates the net warming and cooling effects, respectively. The highest RF at SFC was in the month of April (-30Wm(-2)) which is coincident with the highest BC mass level. The BC atmospheric radiative forcing (ARF) was +30.16 (annual mean) Wm(-2) varying from +23.1 to +43.8Wm(-2). The annual mean atmospheric heating rate (AHR) due to the BC aerosols was 0.86Kday(-1) indicates the enhancement in radiation effect over the study region. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) captured the seasonal cycle of observed BC fairly well but underestimated the observed BC during the month of May-August. Model results show that BC at Guwahati is controlled mainly by anthropogenic emissions except during the pre-monsoon season when open biomass burning also makes a similar contribution
On the relationship between Iran surface temperature and northwest India summer monsoon rainfall
No full textThis study examines the role of Iran surface temperature in modulating rainfall over northwest (NW) India during summer season spanning from June through September. The analysis is based on trend analysis, correlations and regressions performed using ERA-Interim data and India Meteorological Department rainfall records based on station data from 1979 to 2013. The summer season shows increasing trends in surface temperature and rainfall over Iran and NW India, respectively. The increase of surface temperature over Iran is the consequence of mid-latitude wave train that propagates from the northeastern Atlantic/NW Europe and traverses through Eurasian region to Iran. This increases the geopotential height (GPH) anomaly at upper to middle troposphere over Iran, which increases the tropospheric temperature along the vertical cross-section of atmospheric column with maximum warming at the lower troposphere due to the strong descent at the middle tropospheric level. This increase in surface temperature intensifies the surface low-pressure area over Iran and anomalous cyclonic circulation with northerlies and westerlies over Persian Gulf and north Arabian Sea, respectively. These winds converge towards NW India with abundant of moisture supply, favouring deep convection. The increase of GPH anomaly at upper to middle troposphere over Iran also intensifies the Tibetan High westward, accordingly shifting the monsoon rainfall westward. In most of the cases, it dynamically develops into blocking ridges over East and West Asia and an anomalous high-amplitude mid-latitude trough intrusion into NW India favouring very heavy rainfall events
Aerosol indirect effects from ground-based retrievals over the rain shadow region in Indian subcontinent
No full textAerosol-induced changes in cloud microphysical and radiative properties have been studied for the first time using ground-based and airborne observations over a semiarid rain shadow region. The study was conducted for nonprecipitating, ice-free clouds during monsoon (July to September) and postmonsoon (October) months, when cloud condensation nuclei (CCN) concentrations over the region of interest increased monotonically and exhibited characteristics of continental origin. A multifilter rotating shadowband radiometer and microwave radiometric profiler were used to retrieve the cloud optical depth and liquid water path (LWP), respectively, from which cloud effective radius (CER) was obtained. CER showed wide variability from 10–18 µm and a decreasing trend toward the postmonsoon period. During monsoon, the estimated first aerosol indirect effect (AIE) increased from 0.01 to 0.23 with increase in LWP. AIE at different super saturations (SS) showed maximum value (significant at 95%) at 0.4% SS and higher LWP bin (250–300 g/m2). Also, statistically significant AIE values were found at 0.6% and 0.8% SSs but at lower LWP bin (200–250 g/m2). The relationship between CCN and CER showed high correlation at 0.4% SS at higher LWP bin, while at higher SSs good correlations were observed at lower LWPs. Data combined from ground-based and aircraft observations showed dominance of microphysical effect at aerosol concentrations up to 1500 cm−3 and radiative effect at higher concentrations. This combined cloud microphysical and aerosol radiative effect is more prominent during postmonsoon period due to an increase in aerosol concentration
Extremes in June rainfall during Indian summer monsoons of 2013 and 2014: Observational Analysis and Extended range prediction
No full textThe onset/progression phase of theIndian summer monsoon (ISM) is very crucial for the agricultural sector of the country as it has strong bearing on the sowing of kharif crops, which in turn affects overall food grain production and hence food security. The recent ISMs of 2013 and 2014 exhibited quite distinct progression phases. While 2013 had one of the fastest advancement in the last 70 years, 2014 witnessed a comparatively lethargic progression phase. The major difference was felt in the early monsoon month of June, with 2013 (2014) monthly rainfall being +34% (−43%) of its long period average. Observational investigations reveal that, during June 2013, the monsoon trough was very active in its normal position favouring low-level positive vorticity generation and moisture convergence, whereas the absence of monsoon trough during June 2014 facilitated the prevalence of a strong low-level anticyclonic circulation over central India hampering the northward progression of the ISM. It is found that June 2013 (2014) was associated with (i) stronger (weaker) north-south tropospheric temperature (TT) gradient with positive (negative) TT anomalies over Eurasia and north of 60°N; (ii) negative (positive) SST anomalies over the equatorial Indian Ocean, northwestern Arabian Sea and equatorial eastern Pacific; (iii) stronger (weaker) monsoonal Hadley circulation; and (iv) stronger (weaker) Walker circulation in response to the negative (positive) SST anomalies over the equatorial Pacific. The study also examines the skill of an Ensemble Prediction System (EPS) in predicting the observed contrasting behaviour during June 2013/2014 on extended range (∼15–20 days in advance) in real time. The EPS not only forecasted the observed discrepancy, but also predicted the influential role of the large-scale meteorological conditions prevalent during June 2013 (2014), thus demonstrating the remarkable skill of the EPS in predicting June extremes
Analysis of sunlight absorption spectra related to atmospheric trace gases in the tropics
No full textZenith sky-scattered light intensity spectra of wavelength ranges of 325–500 nm have been recorded with UV-visible spectrometer over tropical station Pune (18° 31′ N, 73° 55′ E). Zenith scattered light spectra in the spectral range of 346–358 nm are analysed to find out differential optical depth (DOD) for the period 15–18 November 2010. In DOD spectra, depths are noticed at relevant wavelength due to the absorption by atmospheric gases such as NO2 (nitrogen dioxide), O3 (ozone), BrO (bromine monoxide), and OClO (chlorine dioxide). These DOD spectra are analysed by a matrix inversion technique to calculate individual DOD spectrum of the gases. The observed and calculated DODs are found to be in a good agreement. The coefficient of determination (R2) between observed and calculated DODs of NO2, O3, BrO, OClO, O4 (oxygen dimer), and Ring effect are observed to be 0.55, 0.77, 0.73, 0.75, 0.82, and 0.91, respectively. Filling-in of solar Fraunhofer lines in the observed zenith scattered sunlight is known as ‘Ring effect’. The slant column densities of the above gases are found to be increased due to increasing absorption path length with solar zenith angles. The vertical column densities (VCDs) of O3 and NO2 derived using ground-based spectrometer are compared with the Ozone Monitoring Instrument (OMI) on board Aura satellite during the period 1 March–31 December 2010. The day-to-day variations are found to be similar; however, the percentage differences in VCDs of O3 between ground-based spectrometer and satellite-based OMI are observed to be varying from 1% to 15%, while for NO2, they vary from 1% to 10%. Also, the seasonal mean values of VCDs of O3 and NO2 are discussed. The O3 mean values in the rainy season are found to be higher than that of in the summer and winter seasons from both ground- and satellite-based measurement. Whereas, the NO2 mean values in the winter season are found to be higher than that of in the summer and rainy seasons from both the measurement techniques. The VCDs of O3 are observed to be lowest in winter season due to the loss of ozone within NO2 and O3 reaction active during the winter season
Tropical Indian Ocean surface salinity bias in Climate Forecasting System coupled models and the role of upper ocean processes
No full textIn the present study sea surface salinity (SSS) biases and seasonal tendency over the Tropical Indian Ocean (TIO) in the coupled models [Climate Forecasting System version 1 (CFSv1) and version 2 (CFSv2)] are examined with respect to observations. Both CFSv1 and CFSv2 overestimate SSS over the TIO throughout the year. CFSv1 displays improper SSS seasonal cycle over the Bay of Bengal (BoB), which is due to weaker model precipitation and improper river runoff especially during summer and fall. Over the southeastern Arabian Sea (AS) weak horizontal advection associated with East Indian coastal current during winter limits the formation of spring fresh water pool. On the other hand, weaker Somali jet during summer results for reduced positive salt tendency in the central and eastern AS. Strong positive precipitation bias in CFSv1 over the region off Somalia during winter, weaker vertical mixing and absence of horizontal salt advection lead to unrealistic barrier layer during winter and spring. The weaker stratification and improper spatial distribution of barrier layer thickness (BLT) in CFSv1 indicate that not only horizontal flux distribution but also vertical salt distribution displays large discrepancies. Absence of fall Wyrtki jet and winter equatorial currents in this model limit the advection of horizontal salt flux to the eastern equatorial Indian Ocean. The associated weaker stratification in eastern equatorial Indian Ocean can lead to deeper mixed layer and negative Sea Surface Temperature (SST) bias, which in turn favor positive Indian Ocean Dipole bias in CFSv1. It is important to note that improper spatial distribution of barrier layer and stratification can alter the air–sea interaction and precipitation in the models. On the other hand CFSv2 could produce the seasonal evolution and spatial distribution of SSS, BLT and stratification better than CFSv1. However CFSv2 displays positive bias in evaporation over the whole domain and negative bias in precipitation over the BoB and equatorial Indian Ocean, resulting net reduction in the fresh water availability. This net reduction in fresh water forcing and the associated weaker stratification lead to deeper (than observed) mixed layer depth and is primarily responsible for the cold SST bias in CFSv2. However overall improvement of mean salinity distribution in CFSv2 is about 30 % and the mean error has reduced by more than 1 psu over the BoB. This improvement is mainly due to better fresh water forcing and model physics. Realistic run off information, better ocean model and high resolution in CFSv2 contributed for the improvement. Further improvement can be achieved by reducing biases in the moisture flux and precipitation
Observational and simulated cloud microphysical features of rain formation in the mixed phase clouds observed during CAIPEEX
No full textCloud microphysical observations of rain formation in mixed phase monsoon clouds (from 10 to − 9 °C) using instrumented aircraft during Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) are presented. The drop size and particle size distributions are broader in the mixed phase region, indicating efficient growth of liquid as well as ice phase. Aircraft observations noticed higher ice particle concentrations in Hallet–Mossop zone (− 3 to − 8 °C) with existence of smaller and larger cloud droplets, rimed needles columns, and graupel particles. Observations strongly suggested the active presence of Hallet–Mossop (1974) process in this cloud. The higher correlations found between slope and intercept parameters of exponential size distributions can be attributed to the efficient secondary ice production as well as to the aggregation growth of ice particles. Large Eddy Simulation (LES) of these clouds are compared with observed cloud microphysical properties, also illustrated the important role of Hallet–Mossop (HM) process and its link with warm rain and graupel formation. The raindrop freezing plays a crucial role in graupel formation in early stage of ice development. The observed mean values of microphysical parameters including liquid water content, ice water content, ice number concentrations, and reflectivity showed good agreement with model simulations. Primary ice nuclei have only a minor role in the total ice mass in these clouds