Interannual Variations of Sea Surface Temperature over the Arabian Sea and the Indian Monsoon: A New Perspective

The interannual variation of surface fields over the Arabian Sea and Bay of Bengal are studied using data between 1900 and 1979. It is emphasized that the monthly mean sea surface temperature (SST) over the north Indian Ocean and monsoon rainfall are significantly affected by synoptic systems and other intraseasonal variations. To highlight the interannual signals it is important to remove the large-amplitude high-frequency noise and very low frequency long-term trends, if any. By suitable spatial and temporal averaging of the SST and the rainfall data and by removing the long-term trend from the SST data, we have been able to show that there exists a homogeneous region in the southeastern Arabian Sea over which the March�April (MA) SST anomalies are significantly correlated with the seasonal (June�September) rainfall over India. A potential of this premonsoon signal for predicting the seasonal rainfall over India is indicated. It is shown that the correlation between the SST and the seasonal monsoon rainfall goes through a change of sign from significantly positive with premonsoon SST to very small values with SST during the monsoon season and to significantly negative with SST during the post-monsoon months. For the first time, we have demonstrated that heavy or deficient rainfall years are associated with large-scale coherent changes in the SST (although perhaps of small amplitude) over the north Indian 0cean. We also indicate possible reasons for the apparent lack of persistence of the premonsoon SST anomalies.

The Skill of ECMWF Medium-Range Forecasts during the Year of Tropical Convection 2008

This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics are evaluated against the Tropical Rainfall Measuring Mission (TRMM) estimates. It has been shown that the model was able to capture the monthly to seasonal mean features of tropical convection reasonably. Northward propagation of convective bands over the Bay of Bengal was also forecasted realistically up to 5 days in advance, including the onset phase of the monsoon during the first half of June 2008. However, large errors exist in the daily datasets especially for longer lead times over smaller domains. For shorter lead times (less than 4-5 days), forecast errors are much smaller over the oceans than over land. Moreover, the rate of increase of errors with lead time is rapid over the oceans and is confined to the regions where observed precipitation shows large day-to-day variability. It has been shown that this rapid growth of errors over the oceans is related to the spatial pattern of near-surface air temperature. This is probably due to the one-way air-sea interaction in the atmosphere-only model used for forecasting. While the prescribed surface temperature over the oceans remain realistic at shorter lead times, the pattern and hence the gradient of the surface temperature is not altered with change in atmospheric parameters at longer lead times. It has also been shown that the ECMWF model had considerable difficulties in forecasting very low and very heavy intensity of precipitation over South Asia. The model has too few grids with ``zero'' precipitation and heavy (>40 mm day(-1)) precipitation. On the other hand, drizzle-like precipitation is too frequent in the model compared to that in the TRMM datasets. Further analysis shows that a major source of error in the ECMWF precipitation forecasts is the diurnal cycle over the South Asian monsoon region. The peak intensity of precipitation in the model forecasts over land (ocean) appear about 6 (9) h earlier than that in the observations. Moreover, the amplitude of the diurnal cycle is much higher in the model forecasts compared to that in the TRMM estimates. It has been seen that the phase error of the diurnal cycle increases with forecast lead time. The error in monthly mean 3-hourly precipitation forecasts is about 2-4 times of the error in the daily mean datasets. Thus, effort should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model.

Atmospheric boundary-layer across Hadley and Ferrel cells over the Indian Ocean

A Southern Ocean Pilot cruise covering the latitudes from 10 degrees N to 56 degrees S in the open Indian Ocean was carried out during January February 2004. Surface and upper air data collected during this cruise are reported here. It is shown that the broad features of the atmosphere, in particular that of temperature, follow the tropical and mid-latitude weather expected during January February in this region. However, the atmospheric boundary-layer shows large variations, both in its height and structure between tropics and high latitudes. Strong influence of the surface heat flux on boundary layer structure is clearly seen. Humidity field reveals several local maxima and minima, suggesting a laminated atmosphere with air from different sources moving almost unmixed in adjacent layers.

Meridional propagation of large-scale monsoon convective zones

Observational studies indicate that the convective activity of the monsoon systems undergo intraseasonal variations with multi-week time scales. The zone of maximum monsoon convection exhibits substantial transient behavior with successive propagating from the North Indian Ocean to the heated continent. Over South Asia the zone achieves its maximum intensity. These propagations may extend over 3000 km in latitude and perhaps twice the distance in longitude and remain as coherent entities for periods greater than 2-3 weeks. Attempts to explain this phenomena using simple ocean-atmosphere models of the monsoon system had concluded that the interactive ground hydrology so modifies the total heating of the atmosphere that a steady state solution is not possible, thus promoting lateral propagation. That is, the ground hydrology forces the total heating of the atmosphere and the vertical velocity to be slightly out of phase, causing a migration of the convection towards the region of maximum heating. Whereas the lateral scale of the variations produced by the Webster (1983) model were essentially correct, they occurred at twice the frequency of the observed events and were formed near the coastal margin, rather than over the ocean. Webster's (1983) model used to pose the theories was deficient in a number of aspects. Particularly, both the ground moisture content and the thermal inertia of the model were severely underestimated. At the same time, the sea surface temperatures produced by the model between the equator and the model's land-sea boundary were far too cool. Both the atmosphere and the ocean model were modified to include a better hydrological cycle and ocean structure. The convective events produced by the modified model possessed the observed frequency and were generated well south of the coastline. The improved simulation of monsoon variability allowed the hydrological cycle feedback to be generalized. It was found that monsoon variability was constrained to lie within the bounds of a positive gradient of a convective intensity potential (I). The function depends primarily on the surface temperature, the availability of moisture and the stability of the lower atmosphere which varies very slowly on the time scale of months. The oscillations of the monsoon perturb the mean convective intensity potential causing local enhancements of the gradient. These perturbations are caused by the hydrological feedbacks, discussed above, or by the modification of the air-sea fluxes caused by variations of the low level wind during convective events. The final result is the slow northward propagation of convection within an even slower convective regime. The ECMWF analyses show very similar behavior of the convective intensity potential. Although it is considered premature to use the model to conduct simulations of the African monsoon system, the ECMWF analysis indicates similar behavior in the convective intensity potential suggesting, at least, that the same processes control the low frequency structure of the African monsoon. The implications of the hypotheses on numerical weather prediction of monsoon phenomenon are discussed.

Polarimetric Measurements in a Severe Hailstorm

This study explores the utility of polarimetric measurements for discriminating between hydrometeor types with the emphasis on (a) hail detection and discrimination of its size, (b) measurement of heavy precipitation, (c) identification and quantification of mixed-phase hydrometeors, and (d) discrimination of ice forms. In particular, we examine the specific differential phase, the backscatter differential phase, the correlation coefficient between vertically and horizontally polarized waves, and the differential reflectivity, collected from a storm at close range. Three range–height cross sections are analyzed together with complementary data from a prototype WSR-88D radar. The case is interesting because it demonstrates the complementary nature of these polarimetric measurands. Self-consistency among them allows qualitative and some quantitative discrimination between hydrometeors.

Origin of a trend in ECMWF wind analysis and its objective removal

The suitability of the European Centre for Medium Range Weather Forecasting (ECMWF) operational wind analysis for the period 1980-1991 for studying interannual variability is examined. The changes in the model and the analysis procedure are shown to give rise to a systematic and significant trend in the large scale circulation features. A new method of removing the systematic errors at all levels is presented using multivariate EOF analysis. Objectively detrended analysis of the three-dimensional wind field agrees well with independent Florida State University (FSU) wind analysis at the surface. It is shown that the interannual variations in the detrended surface analysis agree well in amplitude as well as spatial patterns with those of the FSU analysis. Therefore, the detrended analyses at other levels as well are expected to be useful for studies of variability and predictability at interannual time scales. It is demonstrated that this trend in the wind field is due to the shift in the climatologies from the period 1980-1985 to the period 1986-1991.

Forecasting rain for groundnut farmers�how good is good enough

: We illustrate how climatological information about adverse weather events and meteorological forecasts (when available) can be used to decide between alternative strategies so as to maximize the long-term average returns for rainfed groundnut in semi-arid parts of Karnataka, We show that until the skill of the forecast, i.e. probability of an adverse event occurring when it is forecast, is above a certain threshold, the forecast has no impact on the optimum strategy, This threshold is determined by the loss in yield due to the adverse weather event and the cost of the mitigatory measures, For the specific case of groundnut, it is found that while for combating some pests/diseases, climatological information is adequate, for others a forecast of sufficient skill would have a significant impact on the productivity.

Simulation of ENSO-Related Surface Winds in the Tropical Pacific by an Atmospheric General Circulation Model Forced by Observed Sea Surface Temperatures

The authors present the simulation of the tropical Pacific surface wind variability by a low-resolution (R15 horizontal resolution and 18 vertical levels) version of the Center for Ocean-Land-Atmosphere Interactions, Maryland, general circulation model (GCM) when forced by observed global sea surface temperature. The authors have examined the monthly mean surface winds acid precipitation simulated by the model that was integrated from January 1979 to March 1992. Analyses of the climatological annual cycle and interannual variability over the Pacific are presented. The annual means of the simulated zonal and meridional winds agree well with observations. The only appreciable difference is in the region of strong trade winds where the simulated zonal winds are about 15%-20% weaker than observed, The amplitude of the annual harmonics are weaker than observed over the intertropical convergence zone and the South Pacific convergence zone regions. The amplitudes of the interannual variation of the simulated zonal and meridional winds are close to those of the observed variation. The first few dominant empirical orthogonal functions (EOF) of the simulated, as well as the observed, monthly mean winds are found to contain a targe amount of high-frequency intraseasonal variations, While the statistical properties of the high-frequency modes, such as their amplitude and geographical locations, agree with observations, their detailed time evolution does not. When the data are subjected to a 5-month running-mean filter, the first two dominant EOFs of the simulated winds representing the low-frequency EI Nino-Southern Oscillation fluctuations compare quite well with observations. However, the location of the center of the westerly anomalies associated with the warm episodes is simulated about 15 degrees west of the observed locations. The model simulates well the progress of the westerly anomalies toward the eastern Pacific during the evolution of a warm event. The simulated equatorial wind anomalies are comparable in magnitude to the observed anomalies. An intercomparison of the simulation of the interannual variability by a few other GCMs with comparable resolution is also presented. The success in simulation of the large-scale low-frequency part of the tropical surface winds by the atmospheric GCM seems to be related to the model's ability to simulate the large-scale low-frequency part of the precipitation. Good correspondence between the simulated precipitation and the highly reflective cloud anomalies is seen in the first two EOFs of the 5-month running means. Moreover, the strong correlation found between the simulated precipitation and the simulated winds in the first two principal components indicates the primary role of model precipitation in driving the surface winds. The surface winds simulated by a linear model forced by the GCM-simulated precipitation show good resemblance to the GCM-simulated winds in the equatorial region. This result supports the recent findings that the large-scale part of the tropical surface winds is primarily linear.

Predictive uncertainty of chaotic daily streamflow using ensemble wavelet networks approach

Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%-50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

Vertical thermal structure of the atmosphere during active and weak phases of convection over the north Bay of Bengal: Observation and model results

Owing to the lack of atmospheric vertical profile data with sufficient accuracy and vertical resolution, the response of the deep atmosphere to passage of monsoon systems over the Bay of Bengal. had not been satisfactorily elucidated. Under the Indian Climate Research Programme, a special observational programme called 'Bay of Bengal Monsoon Experiment' (BOBMEX), was conducted during July-August 1999. The present study is based on the high-resolution radiosondes launched during BOBMEX in the north Bay. Clear changes in the vertical thermal structure of the atmosphere between active and weak phases of convection have been observed. The atmosphere cooled below 6 km height and became warmer between 6 and 13 km height. The warmest layer was located between 8 and 10 km height, and the coldest layer was found just below 5 km height. The largest fluctuations in the humidity field occurred in the mid-troposphere. The observed changes between active and weak phases of convection are compared with the results from an atmospheric general circulation model, which is similar to that used at the National Centre for Medium Range Weather Forecasting, New Delhi. The model is not able to capture realistically some important features of the temperature and humidity profiles in the lower troposphere and in the boundary layer during the active and weak spells.

Numerical Modelling of the Observed Diurnal Cycle of Indian Monsoon Rainfall

We have analysed the diurnal cycle of rainfall over the Indian region (10S-35N, 60E-100E) using both satellite and in-situ data, and found many interesting features associated with this fundamental, yet under-explored, mode of variability. Since there is a distinct and strong diurnal mode of variability associated with the Indian summer monsoon rainfall, we evaluate the ability of the Weather Research and Forecasting Model (WRF) to simulate the observed diurnal rainfall characteristics. The model (at 54km grid-spacing) is integrated for the month of July, 2006, since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST), by using two different SST datasets, namely, Final Analyses (FNL) and Real-time Global (RTG). It was found that with RTG SST the rainfall simulation over central India (CI) was significantly better than that with FNL. On the other hand, over the Bay of Bengal (BoB), rainfall simulated with FNL was marginally better than with RTG. However, the overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the role of the convective parameterization scheme on the simulation of diurnal cycle of rainfall. We found that the Kain-Fritsch (KF) scheme performs significantly better than Betts-Miller-Janjić (BMJ) and Grell-Devenyi schemes. We also studied the impact of other physical parameterizations, namely, microphysics, boundary layer, land surface, and the radiation parameterization, on the simulation of diurnal cycle of rainfall, and identified the “best” model configuration. We used this configuration of the “best” model to perform a sensitivity study on the role of various convective components used in the KF scheme. In particular, we studied the role of convective downdrafts, convective timescale, and feedback fraction, on the simulated diurnal cycle of rainfall. The “best” model simulations, in general, show a good agreement with observations. Specifically, (i) Over CI, the simulated diurnal rainfall peak is at 1430 IST, in comparison to the observed 1430-1730 IST peak; (ii) Over Western Ghats and Burmese mountains, the model simulates a diurnal rainfall peak at 1430 IST, as opposed to the observed peak of 1430-1730 IST; (iii) Over Sumatra, both model and observations show a diurnal peak at 1730 IST; (iv) The observed southward propagating diurnal rainfall bands over BoB are weakly simulated by WRF. Besides the diurnal cycle of rainfall, the mean spatial pattern of total rainfall and its partitioning between the convective and stratiform components, are also well simulated. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over CI and BoB. While, the 54km and 18km simulations were conducted for the whole of July, 2006, the 6km simulation was carried out for the period 18 - 24 July, 2006. The results of our coarse- and fine-scale numerical simulations of the diurnal cycle of monsoon rainfall will be discussed.

Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold's SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold's and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold's SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold's SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold's SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.

Altitude variation of aerosol properties over the Himalayan range inferred from spatial measurements

Altitude variations of the mass concentration of black carbon, number concentration of composite aerosols are examined along with the columnar spectral aerosol optical depths using state of the art instruments and the Angstrom parameters are inferred from the ground based measurements at several altitude levels, en route from Manora Peak, Nainital (similar to 1950 m above mean sea level) to a low altitude station Haldwani (similar to 330 m above mean sea level) at its foothill within an aerial distance of <10,000 m. The measurements were done during the winter months (November-February) of 2005, 2006 and 2007 under fair weather conditions. The results show a rapid decrease in all the measured parameters with increase in altitude, with >60% contribution to the AOD coming from the regions below 1000 m. The Angstrom wavelength exponent remained high in the well mixed region, and decreased above. The normalized AOD gradient was used to estimate aerosol mixing height, which was found to be in the altitude range 1000-1500 m, above which the particle concentrations are slowly varying as a function of altitude. The heating rate at the surface is found to be maximum but decreases sharply with increase in altitude. Analysis of the wavelength dependence of absorption aerosol optical depth (AAOD) showed that the aerosol absorption over the site is generally due to mixed aerosols. (C) 2011 Elsevier Ltd. All rights reserved.

Vegetative phenology of tropical montane forests in the Nilgiris, South India

Spatial and temporal variation in foliar phenology plays a significant role in growth and reproduction of a plant species. Foliar phenology is strongly influenced by environmental factors such as rainfall. A study on phenology of tropical montane forests was undertaken in three different forest patches of the Nilgiri Mountains in peninsular India above 2000 meters ASL. Since August 2000, 500 trees belonging to 70 species of angiosperms were monitored for both vegetative and reproductive phenologies on a monthly basis. Climate data were collected from nearby weather stations. This paper reports results of the study from August 2000 - August 2003 on foliar phenology. Non-parametric correlations and multiple regressions were performed to analyse the influence of environmental factors such as rainfall, temperature and sunshine on foliar phenology. It was found that moisture related factors had a negative influence on the leaf initiation. Circular statistical analyses were performed to understand the seasonality in different phenophases of foliar phenology. Different phenophases of leafing were not significantly seasonal. Results are discussed and compared among three different forest patches on the Nilgiri plateau and also with other montane forest patches across the globe.