Modelling monsoons: understanding and predicting current and future behaviour

The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal time scales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Niño—Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Absent aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting current and future behaviour of monsoons

A Multivariate Assessment of Climate Change Projections over South America Using the Fifth Phase of the Coupled Model Intercomparison Project

This study presents results from an assessment of climate change projections over South America using fifth phase of the Coupled Model Intercomparison Project models. Change in near‐surface temperature, precipitation, evapotranspiration, integrated water vapour transport (IVT), sea level pressure (SLP), and wind at three pressure levels is quantified across the multi‐model suite. Additionally, model agreement for the sign and significance of projected change is assessed within the ensemble. Models are in strong agreement that the highest magnitude of projected warming will be over tropical regions. The CMIP5 models project a decrease in precipitation for all seasons over southern South America, especially along the northern portions of the present‐day mid‐latitude storm track. This is consistent with a robustly projected poleward shift of the Pacific extratropical high‐pressure system and mid‐latitude storm track indicated by a systematic increase in SLP and decrease in westerly wind magnitude over the region. Decreased precipitation for the months of September, October, and November is also projected, with strong model agreement, over portions of northern and northeastern Brazil, coincident with decreases in SLP and increases in evapotranspiration. IVT is broadly projected to decrease over southern South America, coincident with the projected poleward shift of the mid‐latitude storm track, with increases projected in the vicinity of the South Atlantic Convergence Zone in spring and summer. Results provide a comprehensive picture of climate change across South America and highlight where model consensus on change is most robust

Characterizing Monthly Temperature Variability States and Associated Meteorology Across Southern South America

Key spatiotemporal patterns of monthly scale temperature variability are characterized over southern South America using k‐means clustering. The resulting clusters reveal patterns of temperature variability, referred to as temperature variability states. Analysis is performed over summer and winter months separately using data covering the period 1980–2015. Results for both seasons show four primary temperature variability states. In both seasons, one state is primarily characterized by warm temperature anomalies across the domain while another is characterized by cold anomalies. The other two patterns tend to be characterized by a warm north–cold south and cold north–warm south feature. This suggests two primary modes of temperature variability over the region. Composites of synoptic‐scale meteorological patterns (wind, geopotential height, and moisture fields) are computed for months assigned to each cluster to diagnose the driving meteorology associated with these variability states. Results suggest that low‐level temperature advection promoted by anomalies in atmospheric circulation patterns is a key process for driving these variability states. Moisture‐related processes also are shown to play a role, especially in summer. The El Niño–Southern Oscillation and the Southern Annular Mode exhibit some relationship with temperature variability state frequency, with some states more common during amplified phases of these two modes than others. However, the climate modes are not a primary driver of the temperature variability states

Relationships among Intermodel Spread and Biases in Tropical Atlantic Sea Surface Temperatures

State-of-the-art general circulation models show important systematic errors in their simulation of sea surface temperatures (SST), especially in the tropical Atlantic. In this work the spread in the simulation of climatological SST in the tropical Atlantic by 24 CMIP5 models is examined, and its relationship with the mean systematic biases in the region is explored. The modes of intermodel variability are estimated by applying principal component (PC) analysis to the SSTs in the region 70ºW–20ºE, 20ºS–20ºN. The intermodel variability is approximately explained by the first three modes. The first mode is related to warmer SSTs in the basin, shows worldwide connections with same-signed loads over most of the tropics, and is connected with lower low cloud cover over the eastern parts of the subtropical oceans. The second mode is restricted to the Atlantic, where it shows negative and positive loads to the north and south of the equator, respectively, and is connected to a too weak Atlantic meridional overturning circulation (AMOC). The third mode is related to the double intertropical convergence zone bias in the Pacific and to an interhemispheric asymmetry in the net radiation at the top of the atmosphere. The structure of the second mode is closer to the mean bias than that of the others in the tropical Atlantic, suggesting that model difficulties with the AMOC contribute to the regional biases. State-of-the-art general circulation models show important systematic errors in their simulation of sea surface tem- peratures (SST), especially in the tropical Atlantic. In this work the spread in the simulation of climatological SST in the tropical Atlantic by 24 CMIP5 models is examined, and its relationship with the mean systematic biases in the region is explored. The modes of intermodel variability are estimated by applying principal component (PC) analysis to the SSTs in the region 708W–208E, 208S–208N. The intermodel variability is approximately explained by the first three modes. The first mode is related to warmer SSTs in the basin, shows worldwide connections with same-signed loads over most of the tropics, and is connected with lower low cloud cover over the eastern parts of the subtropical oceans. The second mode is restricted to the Atlantic, where it shows negative and positive loads to the north and south of the equator, respectively, and is connected to a too weak Atlantic meridional overturning circulation (AMOC). The third mode is related to the double intertropical convergence zone bias in the Pacific and to an interhemispheric asymmetry in the net radiation at the top of the atmosphere. The structure of the second mode is closer to the mean bias than that of the others in the tropical Atlantic, suggesting that model difficulties with the AMOC contribute to the regional biases.European Union Seventh Framework Programme (FP7/2007-2013)Gobierno de EspañaNOAA's Climate Program Office, Climate Variability and Predictability ProgramJuan de la Cierva-Incorporacion ProgrammeDepto. de Física de la Tierra y AstrofísicaFac. de Ciencias FísicasTRUEpu

High Bit Rate Experiments Over ACTS

This paper describes two high data rate experiments chat are being developed for the gigabit NASA Advanced Communications Technology Satellite (ACTS). The first is a telescience experiment that remotely acquires image data at the Keck telescope from the Caltech campus. The second is a distributed global climate application that is run between two supercomputer centers interconnected by ACTS. The implementation approach for each is described along with the expected results. Also. the ACTS high data rate (HDR) ground station is also described in detail

The Concordiasi Project in Antarctica

International audienceThe Concordiasi project is making innovative observations of the atmosphere above Antarctica. The most important goals of the Concordiasi are as follows: 1. To enhance the accuracy of weather prediction and climate records in Antarctica through the assimilation of in situ and satellite data, with an emphasis on data provided by hyperspectral infrared sounders. The focus is on clouds, precipitation, and the mass budget of the ice sheets. The improvements in dynamical model analyses and forecasts will be used in chemical-transport models that describe the links between the polar vortex dynamics and ozone depletion, and to advance the understanding of the Earth system by examining the interactions between Antarctica and lower latitudes. 2. To improve our understanding of microphysical and dynamical processes controlling the polar ozone, by providing the first quasi-Lagrangian observations of stratospheric ozone and particles, in addition to an improved characterization of the 3D polar vortex dynamics. Techniques for assimilating these Lagrangian observations are being developed. A major Concordiasi component is a field experiment during the austral springs of 2008-10. The field activities in 2010 are based on a constellation of up to 18 long-duration stratospheric super-pressure balloons (SPBs) deployed from the McMurdo station. Six of these balloons will carry GPS receivers and in situ instruments measuring temperature, pressure, ozone, and particles. Twelve of the balloons will release drop-sondes on demand for measuring atmospheric parameters. Lastly, radiosounding measurements are collected at various sites, including the Concordia station