Articles written in Journal of Earth System Science
Volume 116 Issue 2 April 2007 pp 159-169
Using the ISCCP–FD surface radiative ﬂux data for the summer season (June to September) of the period 1992 to 1995, an analysis was done to understand the role of clouds on the surface radiation budget over the Asian monsoon region. At the top of atmosphere (TOA) of convective regions of the Asian monsoon region, the short wave radiative forcing (SWCRF) and long wave radiative forcing (LWCRF) do not cancel each other resulting in occurrence of the net cloud radiative forcing values exceeding $−$30W/m2. This type of imbalance between SWCRF and LWCRF at TOA is reﬂected down on the earth surface–atmosphere system also as an imbalance between surface netcloud radiative forcing (NETCRF) and atmospheric NETCRF.
Based on the regression analysis of the cloud effects on the surface radiation budget quantities, it has been observed that generally, the variance explained by multiple type cloud data is 50% more than that of total cloud cover alone. In case of SWCRF, the total cloud cover can explain about 3% (7%) of the variance whereas the three cloud type descriptions of clouds can explain about 44% (42%) of the variance over oceanic (land) regions. This highlights the importance of cloud type information in explaining the variations of surface radiation budget. It has been observed that the clouds produce more cooling effect in short-wave band than the warming effect in long-wave band resulting in a net cooling at the surface. Over the oceanic region, variations in high cloud amount contribute more to variations in SWCRF while over land regions both middle and high cloud variations make substantial contributions to the variations in both SWCRF and NETCRF.
Volume 119 Issue 3 June 2010 pp 229-247
In this paper, we suggest criteria for the identification of active and break events of the Indian summer monsoon on the basis of recently derived high resolution daily gridded rainfall dataset over India (1951–2007). Active and break events are defined as periods during the peak monsoon months of July and August, in which the normalized anomaly of the rainfall over a critical area, called the monsoon core zone exceeds 1 or is less than −1.0 respectively, provided the criterion is satisfied for at least three consecutive days. We elucidate the major features of these events. We consider very briefly the relationship of the intraseasonal fluctuations between these events and the interannual variation of the summer monsoon rainfall.
We find that breaks tend to have a longer life-span than active spells. While, almost 80% of the active spells lasted 3–4 days, only 40% of the break spells were of such short duration. A small fraction (9%) of active spells and 32% of break spells lasted for a week or longer. While active events occurred almost every year, not a single break occurred in 26% of the years considered. On an average, there are 7 days of active and break events from July through August. There are no significant trends in either the days of active or break events. We have shown that there is a major difference between weak spells and long intense breaks. While weak spells are characterized by weak moist convective regimes, long intense break events have a heat trough type circulation which is similar to the circulation over the Indian subcontinent before the onset of the monsoon.
The space-time evolution of the rainfall composite patterns suggests that the revival from breaks occurs primarily from northward propagations of the convective cloud zone. There are important differences between the spatial patterns of the active/break spells and those characteristic of interannual variation, particularly those associated with the link to ENSO. Hence, the interannual variation of the Indian monsoon cannot be considered as primarily arising from the interannual variation of intraseasonal variation. However, the signature over the eastern equatorial Indian Ocean on intraseasonal time scales is similar to that on the interannual time scales.
Volume 121 Issue 2 April 2012 pp 355-371
A prediction model based on the perfect prognosis method was developed to predict the probability of lightning and probable time of its occurrence over the south-east Indian region. In the perfect prognosis method, statistical relationships are established using past observed data. For real time applications, the predictors are derived from a numerical weather prediction model. In the present study, we have developed the statistical model based on Binary Logistic Regression technique. For developing the statistical model, 115 cases of lightning that occurred over the south-east Indian region during the period 2006–2009 were considered. The probability of lightning (yes or no) occurring during the 12-hour period 0900–2100 UTC over the region was considered as the predictand. The thermodynamic and dynamic variables derived from the NCEP Final Analysis were used as the predictors. A three-stage strategy based on Spearman Rank Correlation, Cumulative Probability Distribution and Principal Component Analysis was used to objectively select the model predictors from a pool of 61 potential predictors considered for the analysis. The final list of six predictors used in the model consists of the parameters representing atmospheric instability, total moisture content in the atmosphere, low level moisture convergence and lower tropospheric temperature advection. For the independent verifications, the probabilistic model was tested for 92 days during the months of May, June and August 2010. The six predictors were derived from the 24-h predictions using a high resolution Weather Research and Forecasting model initialized with 00 UTC conditions. During the independent period, the probabilistic model showed a probability of detection of 77% with a false alarm rate of 35%. The Brier Skill Score during the independent period was 0.233, suggesting that the prediction scheme is skillful in predicting the lightning probability over the south-east region with a reasonable accuracy.
Volume 121 Issue 3 June 2012 pp 611-623
Northwestern parts of India receive considerable amount of precipitation during the winter months of December–March. Although, it is only about 15% of the annual precipitation, the precipitation is very important for rabi crops and to maintain the glaciers extend in the Himalaya, which melt and supply water to the rivers during other seasons. The precipitation is mainly associated with the sequence of synoptic systems known as ‘western disturbances’. The precipitation has considerable spatial and temporal variability, with maximum precipitation occurring particularly over northern hilly regions, with decreasing influence southwards. The spatially coherent winter precipitation series has been prepared for the largest possible area comprising nine meteorological subdivisions of northwest India, which constitute about 32% of the total area of the country, having similar precipitation characteristics. The precipitation series has been statistically analysed to understand its characteristics and variability. The seasonal precipitation series is found to be homogeneous, Gaussian (normal) distributed and free from persistence. The precipitation variability has increased during the most recent three decades with more excess and deficient years.
Volume 122 Issue 3 June 2013 pp 573-588
Daily rainfall datasets of 10 years (1998–2007) of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (∼0.9) when the study was confined to specific wet and dry spells each of about 5–8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30–50 days and 10–20 days), to be ranging respectively between ∼30–40% and 5–10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by ∼110 mm during southwest monsoon and overestimating by ∼150 mm during northeast monsoon season.
At high spatio-temporal scales, viz., 1° × 1° grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5° × 5° average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.
Volume 129, 2020
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