ALBERT

Description: A stochastic multicloud model (SMCM) convective parameterization, which mimics the interactions at subgrid scales of multiple cloud types, is incorporated into the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), model (CFSsmcm) in lieu of the preexisting simplified Arakawa–Schubert (SAS) cumulus scheme. A detailed analysis of the tropical intraseasonal variability (TISV) and convectively coupled equatorial waves (CCEW) in comparison with the original (control) model and with observations is presented here. The last 10 years of a 15-yr-long climate simulation are analyzed. Significant improvements are seen in the simulation of the Madden–Julian oscillation (MJO) and most of the CCEWs as well as the Indian summer monsoon (ISM) intraseasonal oscillation (MISO). These improvements appear in the form of improved morphology and physical features of these waves. This can be regarded as a validation of the central idea behind the SMCM according to which organized tropical convection is based on three cloud types, namely, the congestus, deep, and stratiform cloud decks, that interact with each other and form a building block for multiscale convective systems. An adequate accounting of the dynamical interactions of this cloud hierarchy thus constitutes an important requirement for cumulus parameterizations to succeed in representing atmospheric tropical variability. SAS fails to fulfill this requirement, which is evident in the unrealistic physical structures of the major intraseasonal modes simulated by CFSv2 as documented here.

Description: With the goal of building an Earth system model appropriate for detection, attribution, and projection of changes in the South Asian monsoon, a state-of-the-art seasonal prediction model, namely the Climate Forecast System version 2 (CFSv2) has been adapted to a climate model suitable for extended climate simulations at the Indian Institute of Tropical Meteorology (IITM), Pune, India. While the CFSv2 model has been skillful in predicting the Indian summer monsoon (ISM) on seasonal time scales, a century-long simulation with it shows biases in the ocean mixed layer, resulting in a 1.5°C cold bias in the global mean surface air temperature, a cold bias in the sea surface temperature (SST), and a cooler-than-observed troposphere. These biases limit the utility of CFSv2 to study climate change issues. To address biases, and to develop an Indian Earth System Model (IITM ESMv1), the ocean component in CFSv2 was replaced at IITM with an improved version, having better physics and interactive ocean biogeochemistry. A 100-yr simulation with the new coupled model (with biogeochemistry switched off) shows substantial improvements, particularly in global mean surface temperature, tropical SST, and mixed layer depth. The model demonstrates fidelity in capturing the dominant modes of climate variability such as the ENSO and Pacific decadal oscillation. The ENSO–ISM teleconnections and the seasonal leads and lags are also well simulated. The model, a successful result of Indo–U.S. collaboration, will contribute to the IPCC’s Sixth Assessment Report (AR6) simulations, a first for India.

Description: While many of the previous positive Indian Ocean dipole (IOD) years were associated with above (below)-normal monsoon rainfall over central (southern) India during summer monsoon months [June–September (JJAS)], the IOD event in 2008 is associated with below (above)-normal rainfall in many parts of central (southern peninsular) India. Because understanding such regional organization is a key for success in regional prediction, using different datasets and atmospheric model simulations, the reasons for this abnormal behavior of the monsoon in 2008 are explored. Compared to normal positive IOD events, sea surface temperature (SST) and rainfall in the southern tropical Indian Ocean (STIO) in JJAS 2008 were abnormally high. Downwelling Rossby waves and oceanic heat advection played an important role in warming SST abnormally in the STIO. It was also found that the combined influence of a linear warming trend in the tropical Indian Ocean and warming associated with the IOD have resulted in abnormal warming of the STIO. This abnormal SST warming resulted in enhancement of convection in the southwest tropical Indian Ocean and forced anticyclonic circulation anomalies over the Bay of Bengal and central India, leading to suppressed rainfall over this region in JJAS 2008. The above mechanism is tested by conducting several model sensitivity experiments with an atmospheric general circulation model (AGCM). These experiments confirmed that the subsidence over central India and the Bay of Bengal was forced mainly by the anomalous warming in the STIO region driven by coupled ocean–atmosphere processes. This study provides the first evidence of combined Indian Ocean warming, associated with global warming, and IOD-related warming influence on Indian summer monsoon rainfall. The combined influence may force below-normal rainfall over central India by inducing strong convection in the STIO region. The conventional seesaw in convection between the Indian subcontinent and the eastern equatorial Indian Ocean may shift to the central equatorial Indian Ocean and the Bay of Bengal if the central Indian Ocean consistently warms in the global warming scenario.

Description: New satellite and in situ observations show large intraseasonal (10–60 day) variability of surface winds and upper-ocean current in the equatorial Indian Ocean, particularly in the east. An ocean model forced by the Quick Scatterometer (QuikSCAT) wind stress is used to study the dynamics of the intraseasonal zonal current. The model has realistic upper-ocean currents and thermocline depth variabilities on intraseasonal to interannual scales. The quality of the simulation is directly attributed to the accuracy of the wind forcing. At the equator, moderate westerly winds are punctuated by strong 10–40-day westerly wind bursts. The wind bursts force swift, intraseasonal (20–50 day) eastward equatorial jets in spring, summer, and fall. The zonal momentum balance is between local acceleration, stress, and pressure, while nonlinearity deepens and strengthens the eastward current. The westward pressure force associated with the thermocline deepening toward the east rapidly arrests eastward jets and, subsequently, generates (weak) westward flow. Thus, in accord with direct observations in the east, the spring jet is a single intraseasonal event, there are intraseasonal jets in summer, and the fall jet is long lived but strongly modulated on an intraseasonal scale. The zonal pressure force is almost always westward in the upper 120 m, and changes sign twice a year in the 120–200-m layer. Transient eastward equatorial undercurrents in early spring and late summer are associated with semiannual Rossby waves generated at the eastern boundary following thermocline deepening by the spring and fall jets. An easterly wind stress is not necessary to generate the undercurrents. Experiments with a single westerly wind burst forcing show that apart from the intraseasonal response, the zonal pressure force and current in the east have an intrinsic 90-day time scale that arises purely from equatorial adjustment.

Description: Change in significance and multidecadal variability of the Northern Hemispheric winter MJO during 1948–2006 is examined using NCEP–NCAR reanalysis data. Variation of the MJO power relative to a red background is estimated by isolating the MJO signal through frequency–wavenumber spectral analysis using a 10-yr sliding window. It is shown that during the period of study, the rate of increase of background power has been larger than the rate of increase of the MJO power, leading to a decreasing trend of significant MJO power. It is also found that a multidecadal variation rides on the decreasing trend of significant power of the MJO. Another finding is that the zonal mean component of the zonal wind at 200 hPa on a MJO time scale has a significant increasing trend. Both of the above trends are statistically significant at the 95% confidence level. Energetics calculations in the wavenumber domain were carried out to understand why the significant MJO power is not increasing as fast as the red background. It is shown that long waves (wavenumbers 1–3, i.e., the MJO scale) lose energy to the zonal mean flow and the rate of kinetic energy gain by the zonal mean flow from the long waves has a linear increasing trend. Thus, while the MJO is also being energized by a warming ocean, it is losing increasingly more energy to the zonal mean flow, making the zonal mean more energetic while losing its own significance at the same time. It is found that the observed multidecadal variability of the significant MJO power has no relationship with other well-known multidecadal variability. However, the authors find that the multidecadal variability of the MJO and the rate of kinetic energy exchange between the zonal mean flow and long waves are closely linked, indicating that the observed multidecadal variability of the MJO is internally driven.

Description: An analysis of a 5-yr (from 1 January 2009 to 31 December 2013) free run of the superparameterized (SP) Climate Forecast System (CFS) version 2 (CFSv2) (SP-CFS), implemented for the first time at a spectral triangular truncation at wavenumber 62 (T62) atmospheric horizontal resolution, is presented. The SP-CFS simulations are evaluated against observations and traditional convection parameterized CFSv2 simulations at T62 resolution as well as at some higher resolutions. The metrics for evaluating the model performance are chosen in order to mainly address the improvement in systematic biases observed in the CFSv2 documented in earlier studies. While the primary focus of this work is on evaluating the improvement of the simulation of the Indian summer monsoon (ISM) by the SP-CFS model, some results are also presented within the context of the global climate. The SP-CFS significantly reduces the dry bias of precipitation over the Indian subcontinent and better captures the monsoon intraseasonal oscillation (MISO) modes. SP-CFS also improves the northward and eastward propagation of high- and low-frequency modes of ISM. Compared to CFSv2, the SP-CFS model simulates improved convectively coupled equatorial waves; better temperature structures both spatially and vertically, leading to a significantly improved relative distribution of variance for the synoptic disturbances and low-frequency tropical intraseasonal oscillations (ISOs). This analysis of the development of SP-CFS is particularly important as it shows promise for improving the cloud process representation through an SP framework and is able to improve the mean as well as intraseasonal characteristics of CFSv2 within the context of the ISM.

Description: Factors responsible for limited predictability of the Asian summer monsoon (ASM) are investigated within a conceptual framework for predictability. Predictability of the seasonal mean depends on the interannual variability (IAV) of the monsoon annual cycle (MAC) and is determined by relative contribution of the predictable “external” component of IAV compared to the unpredictable “internal” IAV. Contributions of slow processes such as those involving air–sea interactions associated with the El Niño–Southern Oscillation (ENSO) or local warm ocean–atmosphere interactions in generating IAV of the MAC are reviewed. Empirical evidence that these air–sea interactions modulate the MAC is presented. Estimates of internal IAV have been made from observations as well as atmospheric model simulations. In contrast to a large part of the Tropics where the summer climate is predictable, with the internal variability being much smaller than the external one, the limited predictability of the Asian monsoon appears to be due to the fact that the contribution from the external IAV over the region is relatively weak and comparable to that from internal IAV. Cause for large internal IAV over the ASM region is investigated, and it is proposed that the internal IAV of the MAC is primarily due to interaction between the MAC and the summer intraseasonal oscillations (ISOs). Two mechanisms through which ISOs lead to internal IAV of the MAC are unraveled. The seasonal bias of the ISO anomalies can influence the seasonal mean if the spatial structure of the ISO has significant projection on that of the seasonal mean and if frequency of occurrence of positive and negative phases is unequal. Evidence supporting this is presented. In addition, it is demonstrated that the chaotic summer ISOs modulated by the annually varying forcing associated with the “slow annual cycle” can lead to IAV of the seasonal mean. Empirical evidence that IAV of ISO activity is related to IAV of the seasonal mean or MAC is also presented. Thus, the Asian monsoon would remain a difficult system to predict. To exploit the predictable signal, however, it is imperative that systematic bias of the models is improved and the space–time structure of the summer ISOs is simulated accurately.