A promising alternative to prediction of seasonal mean all India rainfall

Prediction of seasonal mean All India Rainfall (AIR) is useful during extreme monsoon years (droughts and floods) when the rainfall anomaly is homogeneous over the country. It is, however, useless for any regional hydro-meteorological applications during 'normal' monsoon years (70 per cent of available record), when the rainfall anomaly is quite inhomogeneous within the country. Further, there exists an intrinsic limit to predict the seasonal mean monsoon. The theoretically achievable skill (with perfect model and near perfect data) for seasonal prediction of rainfall being barely useful, there is a need to explore an alternative strategy for monsoon prediction even if it is with a shorter lead time. Based on some of our previous work, we propose here that predicting the phases of the monsoon sub-seasonal oscillation (active and break spells) 3-4 weeks in advance is such an alternative strategy. We argue that such predictions would be more useful for regional hydro-meteorological applications. Potential for such extended range prediction is demonstrated. Using an empirical model, it is further demonstrated that this potential can be achieved and useful prediction of monsoon breaks three weeks in advance could be made. Future direction in improving such extended range prediction of sub-seasonal spells is discussed

Extension of potential predictability of Indian summer monsoon dry and wet spells in recent decades

An understanding of the limit on potential predictability is crucial for developing appropriate tools for extended-range prediction of active/break spells of the Indian summer monsoon (ISM). The global low-frequency changes in climate modulate the annual cycle of the ISM and can influence the intrinsic predictability limit of the ISM intraseasonal oscillations (ISOs). Using 104-year (1901-2004) long daily rainfall data, the change in potential predictability of active and break spells are estimated by an empirical method. It is found that the potential predictability of both active and break spells have undergone a rapid increase during the recent three decades. The potential predictability of active spells has shown an increase from one week to two weeks while that for break spells increased from two weeks to three weeks. This result is interesting and intriguing in the backdrop of recent finding that the potential predictability of monsoon weather has decreased substantially over the same period compared to earlier decades due to increased potential instability of the atmosphere. The possible role of internal dynamics and external forcing in producing this change has been explored. The changes in energy exchange between the synoptic and ISO scale and the different ISO modes as evidenced by energetics computations in frequency domain also support the increased potential predictability of ISO. Our finding provides optimism for improved and useful extended-range prediction of monsoon active and break spells

Pacific coral oxygen isotope and the tropospheric temperature gradient over the Asian monsoon region: A tool to reconstruct past Indian summer monsoon rainfall

Having recognized that it is the tropospheric temperature (TT) gradient rather than the land-ocean surface temperature gradient that drives the Indian monsoon, a new mechanism of El Niño/Southern Oscillation (ENSO) monsoon teleconnection has been unveiled in which the ENSO influences the Indian monsoon by modifying the TT gradient over the region. Here we show that equatorial Pacific coralline oxygen isotopes reflect TT gradient variability over the Indian monsoon region and are strongly correlated to monsoon precipitation as well as to the length of the rainy season. Using these relationships we have been able to reconstruct past Indian monsoon rainfall variability of the first half of the 20th century in agreement with the instrumental record. Additionally, an older coral oxygen isotope record has been used to reconstruct seasonally resolved summer monsoon rainfall variability of the latter half of the 17th century, indicating that the average annual rainfall during this period was similar to that during the 20th century

Indian summer monsoon precipitation climatology in a high-resolution regional climate model: Impacts of convective parameterization on systematic biases

In an attempt to develop a better simulation of the climatology of monsoon precipitation in climate models, this paper investigates the impacts of different convective closures on systematic biases of an Indian monsoon precipitation climatology in a high-resolution regional climate model. For this purpose, the Weather Research Forecast (WRF) model is run at 45- and 15-km (two-way nested) resolution with three convective parameterization schemes, namely the Grell-Devenyi (GD), the Betts-Miller-Janji (BMJ), and the Kain-Fritsch (KF), for the period 1 May-31 October 2001-07. The model is forced with the NCEP-NCAR reanalysis data as the initial and boundary conditions. The simulated June-September (JJAS) mean monsoon rainfall with the three convective schemes is compared with the observations. KF is found to have a high moist bias over the central and western coastal Indian region while GD shows the opposite. Among the three, BMJ is able to produce a reasonable mean monsoon pattern. In an attempt to get further insight into the seasonal bias and its evolution, the probability distribution function (PDF) of different rain-rate categories and their percentage contribution to the seasonal total are computed. BMJ and KF underestimate the observations for lighter rain rates and overestimate for rain-rate categories of more than 10 mm day -1. GD shows an overestimation for lighter rain and an underestimation of PDF for moderate categories. The seasonal patterns of evolution of PDF plots of three rain-rate categories are analyzed to determine whether the convective schemes show any systematic bias throughout the season or if they have problems during certain phases of the monsoon. This shows that the GD systematically overestimates the lighter rain rate and underestimates the moderate rain rate throughout the season, whereas BMJ and KF have problems in the initial stages. The heavy rain category is systematically overestimated by the KF compared to the other two. To further evaluate the proportionate contribution of each rain-rate bin to the total rain, the percentage contribution of each rain rate to the seasonal total is computed. Analyzing all the rain-rate simulations produced by the three schemes, it is found that KF has a moist bias and GD has a dry bias in the spatiotemporal distribution of the monsoon precipitation. Further, this paper investigates the causes behind the mean monsoon precipitation bias. It is shown that GD produces a model climate where the vertical velocity is less than that of the observations up to 500 hPa and the vertically integrated moist instability is also weaker. KF, on the other hand, shows a higher than the observed vertical velocity and a stronger moist instability. Along with this, the vertical profile of heating suggests a warmer middle level in the KF case and significantly reduced midlevel heating for GD. Thus, KF (GD) has produced a model atmosphere that has a stronger (weaker) convective instability to produce the observed bias in the model precipitation. BMJ is found to simulate a reasonable heating profile, along with the realistic moist instability and seasonal cycle of evaporation and condensation. Insight derived from the analysis is expected to help improve the convective parameterizations

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over central India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. It is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate

Aerosol and cloud feedbacks on surface energy balance over selected regions of the Indian subcontinent

We investigate aerosol and cloud forcing on the surface energy balance over selected regions in India. Four regions were selected with different surface characteristics and have considerable differences in the long-term trends and seasonal distribution of clouds and aerosols. These regions are described as (1) northern semiarid, (2) humid subtropical, (3) populated central peninsula, and (4) northeast monsoon impacted. Modern Era Retrospective-analysis for Research and Applications (MERRA) data and Climate Forecast System Reanalysis version 2 (CFSR) data are used in this study. An intercomparison of cloud fractions from both data sets shows that CFSR systematically underestimates high-cloud fraction during premonsoon and monsoon seasons. However, there are fewer low-cloud fraction biases. The positive temporal trend over 31years (1979-2009) from MERRA in high clouds is greater than that of low clouds. This is due to positive anomalies in the cloud ice and supercooled liquid water content in MERRA. Biases in the radiative fluxes and surface fluxes show a strong relationship (correlations exceeding 0.8) with cloud fraction biases, more so for the high clouds. During the premonsoon season, aerosol forcing causes a change in surface shortwave radiation of -24.5, -25, -19, and -16Wm -2 over regions 1 -4, respectively. The corresponding longwave radiation decrease is -9.8, -6.8, -4.5, and -1.9Wm -2 over these same regions, respectively. The maximum surface shortwave reduction due to clouds, which is observed during the monsoon season, is -86, -113, -101, and -97Wm -2 for these same regions, respectively. A decreasing trend in the boundary layer height is noticed both in MERRA and CFSR. The variation in the Bowen ratio and its relation to aerosol and cloud effect anomalies are also discussed

Scale interactions near the foothills of Himalayas during CAIPEEX

Scale interactions associated with small scale (<100 km) dynamics might play a crucial role in the distribution of aerosol in the Himalayan foothills region. Turbulence measurements from a horizontal flight path during Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) are used to illustrate the scale interactions in the vertically sheared flow below the high-level subtropical westerly jet, which is important in the transport of pollution. Data analysis reveals the three dimensional property of large eddies that scale 10-12 km near the slopes, which could bring pollution from the valley to the Tibetan Plateau through a circulation adhering to the slopes. This circulation has a subsidence region away from the slopes and may also contribute to the buildup of pollution in elevated layers over the Plains. The vertical velocity and temperature spectra from research flight data showed clear indications of (-5/3) slope in the mesoscale range. The isotropic behavior of the velocity spectra was noticed for cloud-free traverses, while this behavior is distorted for cloudy conditions with the enhancement of energy at smaller scales as well as with low frequency gravity wave generation. A high-resolution cloud allowing model simulation over the flight path is used to examine the representation of these dynamical interactions in the numerical model. Based on the analysis of observational data and model inferences, a conceptual understanding of the flow in the region close to the foot hills and its role in the distribution of aerosol and cloud condensation nuclei is presented

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models