| dc.description.abstract | The interpretation of proxies of paleo monsoons has been based primarily on changes in incident solar
radiation. The role of feedbacks has not been examined in depth. In this thesis, we have used a diagnostic
model of monsoons to quantitatively discern the role of various forcings and feedbacks on monsoons in
idealized as well as realistic simulations of the climate over the last 22,000 years. The diagnostic model
is based on the energetic framework of monsoons. This model ascribes precipitation to net energy fluxes
into the atmosphere (top + bottom; referred to as Qdiv) and a measure of the efficiency of the atmosphere
in exporting moist static energy (MSE) known as the total gross moist stability (TGMS). We start
by evaluating the contribution of Qdiv and TGMS to changes in precipitation. This is followed by an
investigation of the parameters that led to changes in Qdiv and TGMS.
We find that on orbital timescales, the role of changes in circulation on the amount of MSE exported
out of the Indian subcontinent is small. The changes in precipitation over India are mainly driven by
changes in insolation. Over land, net energy fluxes at the surface are negligible. Hence, Qdiv is influenced
mainly by insolation and cloud radiative feedbacks. Over the Bay of Bengal, however, the perturbations
in surface latent heat flux are large enough to counter the changes in insolation forcing. This results in
a different response of precipitation over land and ocean to variations in insolation. Hence insolation
can be a trigger for changes in precipitation on orbital timescales, but the final response is a result of
complex feedbacks.
The role of TGMS is important during cold periods (glacials) and periods of large variations in
greenhouse gases and ice sheets (such as the deglacial). We have shown that greenhouse gases and ice
sheets do not affect Qdiv, but influence only TGMS. These variations in TGMS are due to the effect of water vapor. We have demonstrated that insolation drives monsoon through different pathways during
cold and warm periods, thereby highlighting the changing role of internal factors. Since water vapor has
similar fluctuations over India and the Bay of Bengal, during TGMS dominant periods, precipitation
over these two regions is in phase. The phase shift between India and the Bay of Bengal depends on the
relative contribution of Qdiv.
These results are supported by proxies. It is well known that the terrestrial proxies for precipitation
are nearly in phase with the insolation. Several marine proxies indicate a lag of 9 Kyrs with respect
to insolation. For example, the proxies for the southwesterly winds in the Arabian Sea, as well as
a proxy for the sea surface salinity in the Bay of Bengal, agree with our predictions. These marine
proxies were, however, interpreted in the previous literature as a measure of monsoon strength over
India. Thus, sparking off a longstanding debate due to these differences in terrestrial and marine proxies.
The large phase lag with insolation was attributed to the role of water vapor transported from the southern
hemisphere. Our results tend to resolve several aspects of this debate.
The vertical moist stability, along with water vapor, determines the netMSE exported from the monsoon
domain at decadal-to-millennial timescales. Circulation, however, plays a crucial role at interannual
timescales. The diagnostic model provides new insights on how El Niño Southern Oscillation (ENSO)
impacts the Indian monsoon. We find that ENSO primarily affects precipitation over India through its
impact on TGMS, whereas it also modulates Qdiv over the Bay of Bengal. We have further elucidated
the versatility of the diagnostic model, by using it to explain the influence of volcanic eruptions on tropical
precipitation. We find that volcanoes of different magnitude affect precipitation differently. Only
the large eruptions (global annual mean AOD > 0.15) affect precipitation through Qdiv, whereas all the
other smaller eruptions affect the export of MSE. The response of precipitation over land and ocean to
the large eruptions are different. Precipitation over ocean has a lag of about 2 years with respect to the
peak in AOD following an eruption. The impact of Qdiv lasts longer over land than over the ocean.
In this thesis, we have formulated a hierarchy of diagnostic models for the Indian monsoon. We find
that it is enough to attribute the orbital scale variability of monsoons to Qdiv and water vapor. Thermodynamics
governs monsoons on the decadal-to-millennial timescales, whereas circulation controls
the interannual variability. This diagnostic approach suggested in this thesis can be used to examine
monsoon response to future climate change. | en_US |
