Microphysics of Convective and Stratiform Precipitation During the summer monsoon season over the Yangtze–Huaihe River Valley, China

Precipitation microphysics are critical for precipitation estimation and forecasting in numerical models. Using six years of observations from the Global Precipitation Measurement satellite, the spatial characteristics of precipitation microphysics are examined during the summer monsoon season over the Yangtze–Huaihe River valley. The results indicate that the heaviest convective rainfall is located mainly between the Huaihe and Yangtze Rivers, associated with a smaller mass-weighted mean diameter (Dm = ∼1.65 mm) and a larger mean generalized intercept parameter (Nw) (∼41 dBNw) at 2 km in altitude than those over the surrounding regions. Further, the convection in this region also has the lowest polarization-corrected temperature at 89 GHz (PCT89 < 254 K), indicating high concentrations of ice-hydrometeors. For a given rainfall intensity, stratiform precipitation is characterized by a smaller mean Dm than convective precipitation. Below 4.5 km in altitude, the vertical slope of medium reflectivity factor varies with the rainfall intensity, which decreases slightly downwards for light rain (< 2.5 mm h−1), increases slightly for moderate rain (2.5–7.9 mm h−1), and increases more sharply for heavy rain (≥8 mm h−1) for both convective and stratiform precipitation. The increase in the amplitude of heavy rain for stratiform precipitation is much higher than that for convective precipitation, probably due to more efficient growth by warm rain processes. The PCT89 values have a greater potential to inform the near-surface microphysical parameters in convective precipitation compared with stratiform precipitation.

Modulation of summer monsoon sub-seasonal surface air temperature over India by soil moisture-temperature coupling

The influence of soil moisture on the sub-seasonal warmer surface air temperature anomalies during drier soil conditions associated with break spells in the Indian summer monsoon precipitation is explored using observations. The multi-model analysis of land surface states and fluxes available from the Second Global Soil Wetness Project (GSWP-2) are found useful in understanding the mechanism for this soil moisture-temperature coupling on sub-seasonal timescales. The analysis uses a soil moisture-temperature coupling diagnostic computed based on linear correlations of daily fields. It is shown that the summer surface air temperature variations are linked to intraseasonal variations of the Indian monsoon precipitation, which control the land-climate coupling by modulating the soil moisture variations. Strong coupling mainly occurs during dry soil states within the summer monsoon season over the transition zones between wet and dry climates of central to north-west India. In contrast, the coupling is weak for constantly wet and energy-limited evaporative regimes over eastern India during the entire summer monsoon season. This observational based analysis provided a better understanding of the linkages between the sub-seasonal dry soil states and warm conditions during the Indian summer monsoon season. A proper representation of these aspects of land-atmosphere interactions in weather and climate models used for sub-seasonal and seasonal monsoon forecasting could be critical for several applications, in particular agriculture. The soil moisture-temperature coupling diagnostic used in this study will be a useful metric for evaluating the performance of weather and climate models.

Study of trend analysis and extreme events of temperature over Varanasi during summer monsoon season

Temporal changes in the monthly and seasonal temperatures over Varanasi District were analysed, based on the 40 years of time series databases of daily temperatures from 1971 to 2010. The temperature changes during the two tricades of 1971-2000 and 1981-2010 and also for four decades starting from 1971 to 2010 were investigated and both the Mann–Kendall (MK) trend test and simple linear regression analyses were employed to detect trends in the mean maximum temperatures and mean minimum temperatures. Various extreme temperatures criteria, as well as their corresponding frequencies, were chosen to explore the trends of extreme climate change over Varanasi. The warming of seasonal mean temperature is mainly attributed to changes in the minimum temperature, particularly during the last three decades. A pre-monsoon cooling and its association with increase in heat wave days suggest that, alongwith large-scale circulation, regional and local factors may have played a vital role in influencing the observed climate in the studied area.

Evaluation of heavy rainfall warning over India during summer monsoon season

India Meteorological Department (IMD) issues heavy rainfall warning for a meteorological sub-division when the expected 24 hours rainfall over any rain gauge station in that sub-division is likely to be 64.5 mm or more. Though these warnings have been provided since the inception of IMD, a few attempts have been made for quantitative evaluation of these warnings. Hence, a study is undertaken to verify the heavy rainfall warnings over 36 meteorological sub-divisions of India during monsoon months (June-September) and season as a whole. For this purpose, data of recent 5 years (2002-2006) has been taken into consideration. In this connection, the day when heavy rainfall is recorded over at least one station in a sub-division, has been considered as a heavy rainfall day for that sub-division. There is a large spatial and temporal variability in skill scores of heavy rainfall warnings over India during summer monsoon season. Considering the monsoon season as a whole, the Heidke Skill Score (HSS) is relatively less (<0.20) over the regions with less frequent heavy rainfall like Lakshadweep, southeast peninsula, Vidarbha, Marathwada, Jammu & Kashmir, Arunachal Pradesh and Nagaland, Manipur, Mizoram & Tripura (NMMT). It is higher (> 0.50) over Konkan & Goa, Madhya Maharashtra and Gujarat region. There has been improvement in the forecast skill with gradual increase in the critical success index and Heidke skill score over the years mainly due to the Numerical Weather Prediction (NWP) models' guidance available to the forecasters. However, the false alarm rate and missing rate are still very high (> 0.50), especially over many sub-divisions of northwest India, southeast peninsula and NMMT.

Large scale fluctuations of the Continental Tropical Convergence Zone (CTCZ) during pilot CTCZ phase-2009 and the evolution of monsoon drought in 2009

Summer monsoon season of the year 2009 resulted in a major drought on the scale of India with rainfall deficiency of 23% from the normal. This was the monsoon season when a pilot phase of the programme Continental Tropical Convergence Zone (CTCZ), a planned multiyear programme to understand the complex interactions among the land, ocean, atmosphere, biosphere components of the regional monsoon climate system, was undertaken. The paper attempts to document the major features in the evolution of monsoon 2009 and provides a preliminary diagnosis of the causes for monsoon drought.

Stochastic modeling of the occurrence of rainfall over some districts of Assam during 1987-1992

The Primary aim in this paper is to find an alternative approach that consists of modeling the pattern of dry and wet spell over some districts of Assam. The Markov Chain Model is used to predict the length of dry and wet spells during the Indian summer monsoon season (June to September). This information may help the agronomists and agricultural scientists in crop planning. Five districts viz., Dibrugarh, Kamrup, Sonitpur, Dhemaji and North­ Lakhimpur are considered here for this study. Markov Chain Model is fitted for each of the district and the results of the five districts are pooled. This pooled result reveals that during the period 1987-1992, the probability for the day being wet when the immediately preceding day is dry for different years varies from 0.44 to 0.54 while the probability of the day being wet when the immediately preceding day is wet for different years varies from 0.74 to 0.86. It is also found that in the Indian summer monsoon season after about every consecutive 4 - 7 wet days a dry day is expected to occur whereas alter about consecutive 2 dry days, a wet day is expected to occur. The number of days required for the process to reach the state of equilibrium varies from 4 - 7 days.