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Inter-decadal modulation of ENSO teleconnections to the Indian Ocean in a coupled model: Special emphasis on decay phase of El Niño
No full textInter-decadal modulation of El Niño-Southern Oscillation (ENSO) teleconnections to tropical Indian Ocean (TIO) is investigated in the coupled general circulation model Climate Forecast System (CFS) using a hundred year integration. The model is able to capture the periodicity of El Niño variability, which is similar to that of the observations. The maximum TIO/north Indian Ocean (NIO) SST warming (during spring following the decay phase of El Niño) associated with El Niño is well captured by the model. Detailed analysis reveals that the surface heat flux variations mainly contribute to the El Niño forced TIO SST variations both in observations and model. However, spring warming is nearly stationary throughout the model integration period, indicating poor inter-decadal El Niño teleconnections. The observations on the other hand displayed maximum SST warming with strong seasonality from epoch to epoch. The model El Niño decay delayed by more than two seasons, results in persistent TIO/NIO SST warming through the following December unlike in the observations. The ocean wave adjustments and persistent westerly wind anomalies over the equatorial Pacific are responsible for late decay of El Niño in the model. Consistent late decay of El Niño, throughout the model integration period (low variance), is mainly responsible for the poor inter-decadal ENSO teleconnections to TIO/NIO. This study deciphers that the model needs to produce El Niño decay phase variability correctly to obtain decadal-modulations in ENSO teleconnection
A new method to compute the principal components from self-organizing maps: An application to monsoon intraseasonal oscillations
No full textThe study develops a self-organizing map (SOM)-based local principal component analysis (PCA) to obtain the linearly decorrelated principal components (PCs) of monsoon intraseasonal oscillations (MISOs). Although the SOM-derived feature maps are not orthogonal like empirical orthogonal function (EOFs), we show that in the case of MISOs simple mathematical substitution can make the SOM-derived PCs linearly decorrelated to each other. Thus, the SOM-based local PCA is seen also to be statistically equivalent to extended EOF analysis when applied to MISO analysis. The life cycle and phase evolution of MISO through SOM-based PCA is robust and conforms to the results based on extended EOFs besides having potential to give new information. The remarkable similarity of results with the symmetric SOM configurations shows the effectiveness of these methods for use as empirical reduction models for climate patterns. The asymmetric SOM lattice configurations derive similar phase evolution as compared to a symmetric lattice, but asymmetric temporal evolutions in the PC-defined phase space. The results once again endorse the mathematical basis of PCA through SOM for geophysical applications
Evolution of Vertical Moist Thermodynamic Structure Associated with the Indian Summer Monsoon 2010 in a Regional Climate Model
No full textThe 2010 boreal summer marked a worldwide abnormal climate. An unprecedented heat wave struck East Asia in July and August 2010. In addition to this, the tropical Indian Ocean was abnormally warm during the summer of 2010. Several heavy rainfall events and associated floods were also reported in the Indian monsoon region. During the season, the monsoon trough (an east-west elongated area of low pressure) was mostly located south of its normal position and monsoon low pressure systems moved south of their normal tracks. This resulted in an uneven spatial distribution with above-normal rainfall over peninsular and Northwest India, and deficient rainfall over central and northeastern parts of India, thus prediction (and simulation) of such anomalous climatic summer season is important. In this context, evolution of vertical moist thermodynamic structure associated with Indian summer monsoon 2010 is studied using regional climate model, reanalysis and satellite observations. This synergised approach is the first of its kind to the best of our knowledge. The model-simulated fields (pressure, temperature, winds and precipitation) are comparable with the respective in situ and reanalysis fields, both in intensity and geographical distribution. The correlation coefficient between model and observed precipitation is 0.5 and the root-mean-square error (RMSE) is 4.8 mm day-1. Inter-comparison of model-simulated fields with satellite observations reveals that the midtropospheric temperature Water vapour mixing ratio (WVMR) has RMSE of 0.5 K (1.6 g kg-1), whereas the surface temperature (WVMR) has RMSE of 3.4 K (2.2 g kg-1). Similarly, temporal evolution of vertical structure of temperature with rainfall over central Indian region reveals that the baroclinic nature of monsoon is simulated by the model. The midtropospheric warming associated with rainfall is captured by the model, whereas the model failed to capture the surface response to high and low rainfall events. The model has strong water vapour loading in the whole troposphere, but weaker coherent response with rainfall compared to observations. Thus, strong water vapour loading and overestimation of rainfall are reported in the model. This study put forward that the discrepancy in the model-simulated structure may be reduced by assimilation of satellite observations
Precipitation analysis over southwest Iran: Trends and projections
No full textAnalysis of trends and projection of precipitation are of significance for the future development and management of water resource in southwest Iran. This research has been divided into two parts. The first part consists of an analysis of the precipitation over 50 stations in the study region for the period 1950-2007. The trends in this parameter were detected by linear regression and significance was tested by t test. Mann-Kendall rank test was also employed to confirm the results. The second part of the research involved future projection of precipitation based on four models. The models used were Centre National de Recherches Meteorologiques (CNRM), European Center Hamburg Model (ECHAM), Model for Interdisciplinary Research on Climate (MIROCH) and United Kingdom Meteorological Office (UKMOC). Precipitation projections were done under B1 and A1B emissions scenarios. The results of precipitation series indicated that most stations showed insignificant trend in annual and seasonal series. The highest numbers of stations with significant trends occurred in winter while no significant trends were detected by statistical tests in summer precipitation. No decreasing significant trends were detected by statistical tests in annual and seasonal precipitation series. The result of projections showed that precipitation may decrease according to majority of the models under both scenarios but the decrease may not be large, except according to MIROCH model. Autumn precipitation may increase with higher rates than other seasons at the end of this century
Evaluation of brightness temperature from a forward model of ground-based microwave radiometer
Get PDFGround-based microwave radiometers are getting great attention in recent years due to their capability to profile the temperature and humidity at high temporal and vertical resolution in the lower troposphere. The process of retrieving these parameters from the measurements of radiometric brightness temperature (TB) includes the inversion algorithm, which uses the background information from a forward model. In the present study, an algorithm development and evaluation of this forward model for a ground-based microwave radiometer, being developed by Society for Applied Microwave Electronics Engineering and Research (SAMEER) of India, is presented. Initially, the analysis of absorption coefficient and weighting function at different frequencies was made to select the channels. Further the range of variation of TB for these selected channels for the year 2011, over the two stations Mumbai and Delhi is discussed. Finally the comparison between forward-model simulated TBs and radiometer measured TBs at Mahabaleshwar (73.66°E and 17.93°N) is done to evaluate the model. There is good agreement between model simulations and radiometer observations, which suggests that these forward model simulations can be used as background for inversion models for retrieving the temperature and humidity profiles
Large-scale and spatio-temporal extreme rain events over India: A hydrometeorological study
No full textFrequency, intensity, areal extent (AE) and duration of rain spells during summer monsoon exhibit large intra-seasonal and inter-annual variations. Important features of the monsoon period large-scale wet spells over India have been documented. A main monsoon wet spell (MMWS) occurs over the country from 18 June to 16 September, during which, 26.5 of the area receives rainfall 26.3 mm/day. Detailed characteristics of the MMWS period large-scale extreme rain events (EREs) and spatio-temporal EREs (ST-EREs), each concerning rainfall intensity (RI), AE and rainwater (RW), for 1 to 25 days have been studied using 1° gridded daily rainfall (1951-2007). In EREs, 'same area' (grids) is continuously wet, whereas in ST-EREs, 'any area' on the mean under wet condition for specified durations is considered. For the different extremes, second-degree polynomial gave excellent fit to increase in values from distribution of annual maximum RI and RW series with increase in duration. Fluctuations of RI, AE, RW and date of occurrence (or start) of the EREs and the ST-EREs did not show any significant trend. However, fluctuations of 1° latitude-longitude grid annual and spatial maximum rainfall showed highly significant increasing trend for 1 to 5 days, and unprecedented rains on 26-27 July 2005 over Mumbai could be a realization of this trend. The Asia-India monsoon intensity significantly influences the MMWS RW
On understanding the land–ocean CO2 contrast over the Bay of Bengal: A case study during 2009 summer monsoon
No full textShip-based observations of atmospheric carbon dioxide (CO2) concentration over the Bay of Bengal (BoB) between 17 July 2009 and 17 Aug 2009 offered an excellent opportunity to evaluate the land–ocean contrast of surface CO2 and facilitated its comparison with model simulated CO2 concentrations. Elevated values of CO2 with large variability near the coastal region and relatively low values with correspondingly lower variability over the open ocean suggest that this observed CO2 variability over the ocean essentially captures the differences in terrestrial and oceanic CO2 fluxes. Although the region under investigation is well known for its atmospheric intraseasonal oscillations of Indian summer monsoon during July and August, the limited duration of observations performed from a moving ship in a research cruise, is not able to capture any high-frequency variability of atmospheric CO2 concentrations. But band-passed sea surface temperature and wind anomalies do indicate strong intraseasonal variability over the study region during the observational period. The synoptic data, albeit quite short in duration, thus offer a clear benchmark for abrupt variability of CO2 concentration between land and ocea
Addendum to: Global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus
No full textThe screening of measurement-based precipitation chemistry and wet and dry deposition data involved detailed assessments of site representativeness, sampling protocols, laboratory analyses, data completeness and overall measurement quality
A numerical study of coastal inundation and its validation for Thane cyclone in the Bay of Bengal
No full textThe numerical modeling of coastal inundation from severe cyclones is a challenging area for coastal hazard mapping, emergency planning and evacuation measures. There is a need for realistic estimate of onshore coastal inundation by the operational weather centers for precise warnings to minimize loss of life and property. At present, there is no modeling effort to evaluate the extent of coastal inundation for any coastal state in India. The operational center disseminates information only on peak surge and its location just before cyclone landfall, with no prior information about onshore inundation. To bridge this gap, the present study applies the state-of-art ADCIRC hydrodynamic model to evaluate peak surge and onshore inundation along coastal Tamil Nadu for the December 2011 Thane cyclone event. Post-storm analysis and field reconnaissance survey report from IMD and ICMAM were available for the Thane cyclone to skill assess model computation. The model that computed peak surge and onshore inundation is in good concurrence with field measurements. The study signifies that near-shore beach slope has a direct bearing on onshore inundation, and its importance in numerical modeling is highlighted. This study being first of its kind for Indian coast, emphasized that coastal inundation modeling should form an integral part in a storm surge prediction system for operational needs
Does bias correction in the forecasted SST improve the extended range prediction skill of active-break spells of Indian summer monsoon rainfall
No full textImpact of bias correction of sea surface temperature (SST) forecast on extended range (ER, ∼3–4 weeks) prediction skill is studied using the bias-corrected forecasted SST from Climate Forecast System version 2 (CFSv2) as the boundary condition for running the Global Forecast System version 2 (GFSv2) model. Potential predictability limit is comparable (∼16 days) for both bias-corrected GFSv2 (GFSv2bc) and CFSv2. Prediction skills of active and break spells and of low-frequency monsoon intraseasonal oscillations is higher for GFSv2bc at all lead pentads. Although initially same, predictability error after 14 days grows slightly faster for GFSv2bc compared to CFSv2. Bias correction in SST has minimal impact in short-to-medium range, while substantial influence is felt in ER between 12–18 days