Forecast skill of the Indian monsoon and its onset in the ECMWF seasonal forecasting system 5 (SEAS5)

Accurate forecasting of variations in Indian monsoon precipitation and progression on seasonal timescales remains a challenge for prediction centres. We examine prediction skill for the seasonal-mean Indian summer monsoon and its onset in the European Centre for Medium Range Weather Forecasts (ECMWF) seasonal forecasting system 5 (SEAS5). We analyse summer hindcasts initialised on 1st of May, with 51 ensemble members, for the 36-year period of 1981—2016. We evaluate the hindcasts against the Global Precipitation Climatology Project (GPCP) precipitation observations and the ECMWF reanalysis 5 (ERA5). The model has significant skill at forecasting dynamical features of the large-scale monsoon and local-scale monsoon onset tercile category one month in advance. SEAS5 shows higher skill for monsoon features calculated using large-scale indices compared to those at smaller scales. Our results also highlight possible model deficiencies in forecasting the all-India monsoon rainfall

Interdependence of Model Systematic Biases in the Tropical Atlantic and the Tropical Pacific

International audienceThe tropical climatology represented in simulations with General Circulation Models (GCMs) is affected by significant systematic biases despite the huge investments in model devlopment over the past 20 years. In this study, coupled seasonal hindcasts performed with EC-Earth and ECMWF System 4 are analyzed to understand the development of systematic biases in the tropical Atlantic and Pacific oceans. These models use similar atmosphere and ocean components (IFS and NEMO, respectively). We focus on hindcasts initialized in February and May. We discuss possible mechanisms for the evolution and origin of rapidly developing systematic biases over the tropical Atlantic during boreal spring. In addition, we look for evidence of the interrelation of systematic biases in the Atlantic and Pacific, and investigate if the errors in one ocean basin affect those in the other. We perform an upper-atmosphere wave analysis by Fourier filtering for certain ranges of temporal frequencies and zonal wavenumbers. Our results identicate common systematic biases in EC-Earth and System 4 purely attributable to the atmosphere component. Biases develop in the Atlantic basin independently of external influences, while a possible effect of such biases on the eastern Pacific is found

Utility of thermal remote sensing for evaluation of a high-resolution weather model in a city

Progress in high resolution numerical weather prediction (NWP) for urban areas will require new modelling approaches and extensive evaluation. Here, we exploit land surface temperature (LST) data from Landsat-8 to assess 100 m resolution NWP for London (UK) on four cloud-free days. The LST observations are directional radiometric temperatures with non-negligible uncertainties. We consider the challenges of informative comparison between the Landsat LST and the NWP scheme’s internal characterisation of the complete surface temperature. The LST spatial coverage allows large-scale observation-model differences to be explored. In one case, obvious spatial artifacts in the NWP surface temperature are observed relative to the Landsat LST. These are found to be related to the NWP’s initial method of downscaling of soil moisture using soil properties. Updated model runs have higher spatial correlation between model and Landsat LST. In cases where meteorological conditions favour the formation of horizontal convective rolls, warmer air temperatures associated with updraughts in the mixed layer extend inappropriately to the urban surface. This manifests as warm stripes in the model surface temperature that are not present in the Landsat LST. NWP-Landsat LST differences are larger in more built-up areas on days nearer summer solstice. This is largely attributed to urban thermal anisotropy, as Landsat preferentially views warmer urban surfaces, while the model LST represents all surfaces. We evaluate two approaches to quantify this sampling effect, but further work is needed to fully constrain it and facilitate more informative model evaluation

Extracellular N-acetylaspartate depletion in traumatic brain injury

N-Acetylaspartate (NAA) is almost exclusively localized in neurons in the adult brain and is present in high concentration in the CNS. It can be measured by proton magnetic resonance spectroscopy and is seen as a marker of neuronal damage and death. NMR spectroscopy and animal models have shown NAA depletion to occur in various types of chronic and acute brain injury. We investigated 19 patients with traumatic brain injury (TBI). Microdialysis was utilized to recover NAA, lactate, pyruvate, glycerol and glutamate, at 12-h intervals. These markers were correlated with survival and a 6-month Glasgow Outcome Score. Eleven patients died and eight survived. A linear mixed model analysis showed a significant effect of outcome and of the interaction between time of injury and outcome on NAA levels (p = 0.009 and p = 0.004, respectively). Overall, extracellular NAA was 34% lower in non-survivors. A significant non-recoverable fall was observed in this group from day 4 onwards, with a concomitant rise in lactate–pyruvate ratio and glycerol. These results suggest that mitochondrial dysfunction is a significant contributor to poor outcome following TBI and propose extracellular NAA as a potential marker for monitoring interventions aimed at preserving mitochondrial function