Search

Understanding the Tibetan Plateau (TP) thermal processes is of utmost significance in changing climate. This study investigates the effect of soil moisture in changing the TP thermal profile and consequently summer precipitation in South Asia (SA). Soil moisture from Special Sensor Microwave Imager (SSM/I) developed from the F-08, F-11, and F-13 fundamental climate data record and atmospheric reanalysis from ERA-Interim, MERRA-2, and NCEP/CFSR during 1988–2008 are used. A generalized linear method that assesses the reciprocal forcing between two connected fields, named the coupled manifold technique (CMT), is applied to TP soil moisture and SA summer precipitation. It is revealed that interannual variations of SA precipitation are significantly (confidence level = 99%) impacted by TP soil moisture and the explained ratio of variance in SA is 0.3–0.4. Composite analysis indicates that SA summer precipitation has positive anomalies in response to dry TP soil moisture in the previous spring and vice versa. For understanding the possible mechanism, thermal processes, relative humidity, wind components, and moisture flux anomalies were calculated for dry and wet TP soil moisture and summer precipitation. The results suggested that TP soil moisture is likely to regulate near-surface energy balance and diabatic heating profile over TP. As a result, the surrounding lower-level westerlies (easterlies) (at 850 hPa) converge (diverge), associated with divergence (convergence) at the upper troposphere (200 hPa). The westerlies (easterlies) are usually moisture-rich (moisture-deficient) and thus cause more (less) precipitation in western (eastern) SA. It is thus suggested that the spring soil moisture may affect the thermal profile of TP, affecting the summer precipitation in SA as a consequence. [ABSTRACT FROM AUTHOR]

The interaction between the land surface and the atmosphere is of significant importance in the climate system because it is a key driver of the exchanges of energy and water. Several important relations to heat waves, floods, and droughts exist that are based on the interaction of soil moisture and, for instance, air temperature and humidity. Our ability to separate the elements of this coupling, identify the exact locations where they are strongest, and quantify their strengths is, therefore, of paramount importance to their predictability. A recent rigorous causality formalism based on the Liang–Kleeman (LK) information flow theory has been shown, both theoretically and in real-world applications, to have the necessary asymmetry to infer the directionality and magnitude within geophysical interactions. However, the formalism assumes stationarity in time, whereas the interactions within the land surface and atmosphere are generally nonstationary; furthermore, it requires a sufficiently long time series to ensure statistical sufficiency. In this study, we remedy this difficulty by using the square root Kalman filter to estimate the causality based on the LK formalism to derive a time-varying form. Results show that the new formalism has similar properties compared to its time-invariant form. It is shown that it is also able to capture the time-varying causality structure within soil moisture–air temperature coupling. An advantage is that it does not require very long time series to make an accurate estimation. Applying a wavelet transform to the results also reveals the full range of temporal scales of the interactions. [ABSTRACT FROM AUTHOR]