Context of the added value in coupled atmosphere-land RegCM4–CLM4.5 in the simulation of Indian summer monsoon

Climate Dynamics - The potential of the RegCM4–CLM4.5 model for value addition over the MIROC5 GCM for Indian Summer Monsson (ISM) simulation for the present climate (1975–2005) has...     

Vulnerability and adaptation to climate variability and water stress in Uttarakhand State, India

This paper presents a participatory approach to investigate vulnerability and adaptive capacity to climate variability and water stress in the Lakhwar watershed in Uttarakhand State, India. Highly water stressed microwatersheds were identified by modelling surface runoff, soil moisture development, lateral runoff, and groundwater recharge. The modelling results were shared with communities in two villages, and timeline exercises were carried out to allow them to trace past developments that have impacted their lives and livelihoods, and stimulate discussion about future changes and possible adaptation interventions.     

Study of seasonal variation of PM2.5 concentration associated with meteorological parameters at residential sites in Delhi,India

The seasonal variation of particulate matter and its relationship with meteorological parameters were measured at five different residential sites in Delhi. Sampling was carried out for one year including all three seasons (summer, monsoon, and winter). The yearly average concentration of particulate matter (PM_2.5) was 135.16 ± 41.34 µg/m³. The highest average values were observed in winter (208.44 ± 43.67 µg/m³) and the lowest during monsoon season (80.29 ± 39.47 µg/m³). The annual average concentration of PM_2.5 was found to be the highest at the Mukherjee Nagar site (242.16 µg/m³ ) during the winter and lowest at (Jawaharlal Nehru University) JNU (35.65 µg/m³) during the monsoon season. The strongest correlation between PM mass and a meteorological parameter was a strong negative correlation with temperature (R2=0.55). All other parameters were weakly correlated (R2<0.2) with PM mass.

     

The Indian summer monsoon drought of 2002 and its linkage with tropical convective activity over northwest Pacific

The Indian subcontinent witnessed a severe monsoon drought in 2002, which largely resulted from a major rainfall deficiency in the month of July. While moderate El Nino conditions prevailed during this period, the atmospheric convective activity was anomalously enhanced over northwest and north-central Pacific in the 10–20°N latitude belt; and heavy rainfall occurred over this region in association with a series of northward moving tropical cyclones. Similar out-of-phase rainfall variations over the Indian region and the northwest (NW) Pacific have been observed during other instances of El Nino/Southern Oscillation (ENSO). The dynamical linkage corresponding to this out-of-phase rainfall variability is explored in this study by conducting a set of numerical experiments using an atmospheric general circulation model. The results from the model simulations lend credence to the role of the tropical Pacific sea surface temperature anomalies in forcing the out-of-phase precipitation variability over the NW Pacific and the Indian monsoon region. It is seen that the ENSO induced circulation response reveals an anomalous pattern comprising of alternating highs and lows which extend meridionally from the equatorial region into the sub-tropic and mid-latitude regions of west-central Pacific. This meridional pattern is associated with an anomalous cyclonic circulation over NW Pacific, which is found to favor enhanced tropical cyclonic activity and intensified convection over the region. In turn, the intensified convection over NW Pacific induces subsidence and rainfall deficiency over the Indian landmass through anomalous east-west circulation in the 10–20°N latitude belt. Based on the present findings, it is suggested that the convective activity over NW Pacific is an important component in mediating the ENSO-monsoon teleconnection dynamics.     

An analysis of prediction skill of monthly mean climate variability

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30?C40?days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability.     

How predictable is the northern hemisphere summer upper-tropospheric circulation?

The retrospective forecast skill of three coupled climate models (NCEP CFS, GFDL CM2.1, and CAWCR POAMA 1.5) and their multi-model ensemble (MME) is evaluated, focusing on the Northern Hemisphere (NH) summer upper-tropospheric circulation along with surface temperature and precipitation for the 25-year period of 1981–2005. The seasonal prediction skill for the NH 200-hPa geopotential height basically comes from the coupled models’ ability in predicting the first two empirical orthogonal function (EOF) modes of interannual variability, because the models cannot replicate the residual higher modes. The first two leading EOF modes of the summer 200-hPa circulation account for about 84% (35.4%) of the total variability over the NH tropics (extratropics) and offer a hint of realizable potential predictability. The MME is able to predict both spatial and temporal characteristics of the first EOF mode (EOF1) even at a 5-month lead (January initial condition) with a pattern correlation coefficient (PCC) skill of 0.96 and a temporal correlation coefficient (TCC) skill of 0.62. This long-lead predictability of the EOF1 comes mainly from the prolonged impacts of El Niño-Southern Oscillation (ENSO) as the EOF1 tends to occur during the summer after the mature phase of ENSO. The second EOF mode (EOF2), on the other hand, is related to the developing ENSO and also the interdecadal variability of the sea surface temperature over the North Pacific and North Atlantic Ocean. The MME also captures the EOF2 at a 5-month lead with a PCC skill of 0.87 and a TCC skill of 0.67, but these skills are mainly obtained from the zonally symmetric component of the EOF2, not the prominent wavelike structure, the so-called circumglobal teleconnection (CGT) pattern. In both observation and the 1-month lead MME prediction, the first two leading modes are accompanied by significant rainfall and surface air temperature anomalies in the continental regions of the NH extratropics. The MME’s success in predicting the EOF1 (EOF2) is likely to lead to a better prediction of JJA precipitation anomalies over East Asia and the North Pacific (central and southern Europe and western North America).