Weakened tropical circulation and reduced precipitation in response to geoengineering

Geoengineering by injection of reflective aerosols into the stratosphere has been proposed as a way to counteract the warming effect of greenhouse gases by reducing the intensity of solar radiation reaching the surface. Here, climate model simulations are used to examine the effect of geoengineering on the tropical overturning circulation. The strength of the circulation is related to the atmospheric static stability and has implications for tropical rainfall. The tropical circulation is projected to weaken under anthropogenic global warming. Geoengineering with stratospheric sulfate aerosol does not mitigate this weakening of the circulation. This response is due to a fast adjustment of the troposphere to radiative heating from the aerosol layer. This effect is not captured when geoengineering is modelled as a reduction in total solar irradiance, suggesting caution is required when interpreting model results from solar dimming experiments as analogues for stratospheric aerosol geoengineering.

Simulated changes in the relationship between tropical ocean temperatures and the western African monsoon during the mid-Holocene

Results from nine coupled ocean-atmosphere simulations have been used to investigate changes in the relationship between the variability of monsoon precipitation over western Africa and tropical sea surface temperatures (SSTs) between the mid-Holocene and the present day. Although the influence of tropical SSTs on the African monsoon is generally overestimated in the control simulations, the models reproduce aspects of the observed modes of variability. Thus, most models reproduce the observed negative correlation between western Sahelian precipitation and SST anomalies in the eastern tropical Pacific, and many of them capture the positive correlation between SST anomalies in the eastern tropical Atlantic and precipitation over the Guinea coastal region. Although the response of individual model to the change in orbital forcing between 6 ka and present differs somewhat, eight of the models show that the strength of the teleconnection between SSTs in the eastern tropical Pacific and Sahelian precipitation is weaker in the mid-Holocene. Some of the models imply that this weakening was associated with a shift towards longer time periods (from 3–5 years in the control simulations toward 4–10 years in the mid-Holocene simulations). The simulated reduction in the teleconnection between eastern tropical Pacific SSTs and Sahelian precipitation appears to be primarily related to a reduction in the atmospheric circulation bridge between the Pacific and West Africa but, depending on the model, other mechanisms such as increased importance of other modes of tropical ocean variability or increased local recycling of monsoonal precipitation can also play a role.

The depression of tropical snow lines at the Last Glacial Maximum: what can we learn from climate and model experiments?

Analyses of simulations of the last glacial maximum (LGM) made with 17 atmospheric general circulation models (AGCMs) participating in the Paleoclimate Modelling Intercomparison Project, and a high-resolution (T106) version of one of the models (CCSR1), show that changes in the elevation of tropical snowlines (as estimated by the depression of the maximum altitude of the 0 °C isotherm) are primarily controlled by changes in sea-surface temperatures (SSTs). The correlation between the two variables, averaged for the tropics as a whole, is 95%, and remains >80% even at a regional scale. The reduction of tropical SSTs at the LGM results in a drier atmosphere and hence steeper lapse rates. Changes in atmospheric circulation patterns, particularly the weakening of the Asian monsoon system and related atmospheric humidity changes, amplify the reduction in snowline elevation in the northern tropics. Colder conditions over the tropical oceans combined with a weakened Asian monsoon could produce snowline lowering of up to 1000 m in certain regions, comparable to the changes shown by observations. Nevertheless, such large changes are not typical of all regions of the tropics. Analysis of the higher resolution CCSR1 simulation shows that differences between the free atmospheric and along-slope lapse rate can be large, and may provide an additional factor to explain regional variations in observed snowline changes.

A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments

Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.

Comparing tropical precipitation simulated by the Met Office NWP and climate models with satellite observations

Forecasts of precipitation and water vapor made by the Met Office global numerical weather prediction (NWP) model are evaluated using products from satellite observations by the Special Sensor Microwave Imager/Sounder (SSMIS) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) for June–September 2011, with a focus on tropical areas (308S–308N). Consistent with previous studies, the predicted diurnal cycle of precipitation peaks too early (by ;3 h) and the amplitude is too strong over both tropical ocean and land regions. Most of the wet and dry precipitation biases, particularly those over land, can be explained by the diurnal-cycle discrepancies. An overall wet bias over the equatorial Pacific and Indian Oceans and a dry bias over the western Pacific warmpool and India are linked with similar biases in the climate model, which shares common parameterizations with the NWP version. Whereas precipitation biases develop within hours in the NWP model, underestimates in water vapor (which are assimilated by the NWP model) evolve over the first few days of the forecast. The NWP simulations are able to capture observed daily-to-intraseasonal variability in water vapor and precipitation, including fluctuations associated with tropical cyclones.