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Article

Regional models were originally developed to serve weather forecasting and regional process studies. Typical simulations encompass time periods in the order of days or weeks. Thereafter regional models were also used more and more as regional climate models for longer integrations and climate change downscaling. Regional climate modeling or regional dynamic downscaling, which are used interchangeably, developed as its own branch in climate research since the end of the 1990s out of the need to bridge the obvious inconsistencies at the interface of global climate research and climate impact research. The primary aim of regional downscaling is to provide consistent regional climate change scenarios with relevant spatial resolution to serve detailed climate impact assessments. Similar to global climate modeling, the early attempts at regional climate modeling were based on uncoupled atmospheric models or stand-alone ocean models, an approach that is still maintained as the most common on the regional scale. However, this approach has some fundamental limitations, since regional air-sea interaction remains unresolved and regional feedbacks are neglected. This is crucial when assessing climate change impacts in the coastal zone or the regional marine environment. To overcome these limitations, regional climate modeling is currently in a transition from uncoupled regional models into coupled atmosphere-ocean models, leading to fully integrated earth system models. Coupled ice-ocean-atmosphere models have been developed during the last decade and are currently robust and well established on the regional scale. Their added value has been demonstrated for regional climate modeling in marine regions, and the importance of regional air-sea interaction became obvious. Coupled atmosphere-ice-ocean models, but also coupled physical-biogeochemical modeling approaches are increasingly used for the marine realm. First attempts to couple these two approaches together with land surface models are underway. Physical coupled atmosphere-ocean modeling is also developing further and first model configurations resolving wave effects at the atmosphere-ocean interface are now available. These new developments now open up for improved regional assessment under broad consideration of local feedbacks and interactions between the regional atmosphere, cryosphere, hydrosphere, and biosphere.

Article

B.N. Goswami and Soumi Chakravorty

Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales. The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient. The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.

Article

Saji N. Hameed

Discovered at the very end of the 20th century, the Indian Ocean Dipole (IOD) is a mode of natural climate variability that arises out of coupled ocean–atmosphere interaction in the Indian Ocean. It is associated with some of the largest changes of ocean–atmosphere state over the equatorial Indian Ocean on interannual time scales. IOD variability is prominent during the boreal summer and fall seasons, with its maximum intensity developing at the end of the boreal-fall season. Between the peaks of its negative and positive phases, IOD manifests a markedly zonal see-saw in anomalous sea surface temperature (SST) and rainfall—leading, in its positive phase, to a pronounced cooling of the eastern equatorial Indian Ocean, and a moderate warming of the western and central equatorial Indian Ocean; this is accompanied by deficit rainfall over the eastern Indian Ocean and surplus rainfall over the western Indian Ocean. Changes in midtropospheric heating accompanying the rainfall anomalies drive wind anomalies that anomalously lift the thermocline in the equatorial eastern Indian Ocean and anomalously deepen them in the central Indian Ocean. The thermocline anomalies further modulate coastal and open-ocean upwelling, thereby influencing biological productivity and fish catches across the Indian Ocean. The hydrometeorological anomalies that accompany IOD exacerbate forest fires in Indonesia and Australia and bring floods and infectious diseases to equatorial East Africa. The coupled ocean–atmosphere instability that is responsible for generating and sustaining IOD develops on a mean state that is strongly modulated by the seasonal cycle of the Austral-Asian monsoon; this setting gives the IOD its unique character and dynamics, including a strong phase-lock to the seasonal cycle. While IOD operates independently of the El Niño and Southern Oscillation (ENSO), the proximity between the Indian and Pacific Oceans, and the existence of oceanic and atmospheric pathways, facilitate mutual interactions between these tropical climate modes.