ALBERT

Description: The bio-physical feedback process between the marine ecosystem and the tropical climate system is investigated using both an ocean circulation model and a fully-coupled ocean–atmosphere circulation model, which interact with a biogeochemical model. We found that the presence of chlorophyll can have significant impact on the characteristics of the El Niño-Southern Oscillation (ENSO), including its amplitude and asymmetry, as well as on the mean state. That is, chlorophyll generally increases mean sea surface temperature (SST) due to the direct biological heating. However, SST in the eastern equatorial Pacific decreases due to the stronger indirect dynamical response to the biological effects outweighing the direct thermal response. It is demonstrated that this biologically-induced SST cooling is intensified and conveyed to other tropical-ocean basins when atmosphere–ocean coupling is taken into account. It is also found that the presence of chlorophyll affects the magnitude of ENSO by two different mechanisms; one is an amplifying effect by the mean chlorophyll, which is associated with shoaling of the mean thermocline depth, and the other is a damping effect derived from the interactively-varying chlorophyll coupled with the physical model. The atmosphere–ocean coupling reduces the biologically-induced ENSO amplifying effect through the weakening of atmospheric feedback. Lastly, there is also a biological impact on ENSO which enhances the positive skewness. This skewness change is presumably caused by the phase dependency of thermocline feedback which affects the ENSO magnitude.

Description: Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of −1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately −0.80 K. Over land, albedo bias contributes −1.20 K to the averaged cold bias of −1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.

Description: We estimate area burned in southern California at mid-century (2046–2065) for the Intergovernmental Panel on Climate Change A1B scenario. We develop both regressions and a parameterization to predict area burned in three ecoregions, and apply present-day (1981–2000) and future meteorology from the suite of general circulation models to these fire prediction tools. The regressions account for the impacts of both current and antecedent meteorological factors on wildfire activity and explain 40–46 % of the variance in area burned during 1980–2009. The parameterization yields area burned as a function of temperature, precipitation, and relative humidity, and includes the impact of Santa Ana wind and other geographical factors on wildfires. It explains 38 % of the variance in area burned over southern California as a whole, and 64 % of the variance in southwestern California. The parameterization also captures the seasonality of wildfires in three ecoregions of southern California. Using the regressions, we find that area burned likely doubles in Southwestern California by midcentury, and increases by 35 % in the Sierra Nevada and 10 % in central western California. The parameterization suggests a likely increase of 40 % in area burned in southwestern California and 50 % in the Sierra Nevada by midcentury. It also predicts a longer fire season in southwestern California due to warmer and drier conditions on Santa Ana days in November. Our method provides robust estimates of area burned at midcentury, a key metric which can be used to calculate the fire-related effects on air quality, human health, and the associated costs.

Description: Southern high latitude precipitation during austral spring in relation to the Indian Ocean Dipole (IOD) and ENSO is investigated in the present study. Both the IOD and ENSO generate Rossby waves trains that create positive and negative pressure anomalies. These anomalous pressure centres generate meridional moisture fluxes that impact the precipitation. Influence of the IOD is detected mainly in the Ross sea region, where the southward moisture transport induced by the low pressure cell enhances precipitation. During strong IOD years, east Antarctica near 100°E, is also characterised by enhanced precipitation induced by the southward moisture transport by a high pressure cell located south of Australia. In the Dronning Maud Land, precipitation is linked to the moisture advection through the Atlantic during ENSO years and not during the IOD years.

Description: This study presents a performance-based comprehensive weighting factor that accounts for the skill of different regional climate models (RCMs), including the effect of the driving lateral boundary condition coming from either atmosphere–ocean global climate models (AOGCMs) or reanalyses. A differential evolution algorithm is employed to identify the optimal relative importance of five performance metrics, and corresponding weighting factors, that include the relative absolute mean error (RAME), annual cycle, spatial pattern, extremes and multi-decadal trend. Based on cumulative density functions built by weighting factors of various RCMs/AOGCMs ensemble simulations, current and future climate projections were then generated to identify the level of uncertainty in the climate scenarios. This study selected the areas of southern Ontario and Québec in Canada as a case study. The main conclusions are as follows: (1) Three performance metrics were found essential, having the greater relative importance: the RAME, annual variability and multi-decadal trend. (2) The choice of driving conditions from the AOGCM had impacts on the comprehensive weighting factor, particularly for the winter season. (3) Combining climate projections based on the weighting factors significantly increased the consistency and reduced the spread among models in the future climate changes. These results imply that the weighting factors play a more important role in reducing the effects of outliers on plausible future climate conditions in regions where there is a higher level of variability in RCM/AOGCM simulations. As a result of weighting, substantial increases in the projected warming were found in the southern part of the study area during summer, and the whole region during winter, compared to the simple equal weighting scheme from RCM runs. This study is an initial step toward developing a likelihood procedure for climate scenarios on a regional scale using equal or different probabilities for all models.

Description: A dipole pattern in convection between the South Atlantic convergence zone and the subtropical plains of southeastern South America characterizes summer intraseasonal variability over the region. The dipole pattern presents two main bands of temporal variability, with periods between 10 and 30 days, and 30 and 90 days; each influenced by different large-scale dynamical forcings. The dipole activity on the 30–90-day band is related to an eastward traveling wavenumber-1 structure in both OLR and circulation anomalies in the tropics, similar to that associated with the Madden–Julian oscillation. The dipole is also related to a teleconnection pattern extended along the South Pacific between Australia and South America. Conversely, the dipole activity on the 10–30-day band does not seem to be associated with tropical convection anomalies. The corresponding circulation anomalies exhibit, in the extratropics, the structure of Rossby-like wave trains, although their sources are not completely clear.