COST 733 - WG4: Applications of weather type classification

The main objective of the COST Action 733 is to achieve a general numerical method for assessing, comparing and classifying typical weather situations in the European regions. To accomplish this goal, different workgroups are established, each with their specific aims: WG1: Existing methods and applications (finished); WG2: Implementation and development of weather types classification methods; WG3: Comparison of selected weather types classifications; WG4: Testing methods for various applications. The main task of Workgroup 4 (WG4) in COST 733 implies the testing of the selected weather type methods for various classifications. In more detail, WG4 focuses on the following topics:• Selection of dedicated applications (using results from WG1), • Performance of the selected applications using available weather types provided by WG2, • Intercomparison of the application results as a results of different methods • Final assessment of the results and uncertainties, • Presentation and release of results to the other WGs and external interested • Recommend specifications for a new (common) method WG2 Introduction In order to address these specific aims, various applications are selected and WG4 is divided in subgroups accordingly: 1.Air quality 2. Hydrology (& Climatological mapping) 3. Forest fires 4. Climate change and variability 5. Risks and hazards Simultaneously, the special attention is paid to the several wide topics concerning some other COST Actions such as: phenology (COST725), biometeorology (COST730), agriculture (COST 734) and mesoscale modelling and air pollution (COST728). Sub-groups are established to find advantages and disadvantages of different classification methods for different applications. Focus is given to data requirements, spatial and temporal scale, domain area, specifi

COST 733 – WG4: Applications of weather type classifications

Presentación realizada para: European Geosciences Union General Assembly celebrado del 19-24 de abril de 2009 en Viena

Inter-model comparison of sub-seasonal tropical variability in aquaplanet experimets: effect of a warm pool

This study compares the simulation of sub-seasonal tropical variability by a set of six state-of-the-art AGCMs in two experiments in aqua-planet configuration: a zonally-symmetric experiment, and an experiment with a warm pool centered on the equator. In all six models, the presence of the warm pool generates zonal asymmetries in the simulated mean states in the form of a “Gill-type” response, made more complex by feedbacks between moisture, convective heating and circulation. Noticeable differences appear from one model to another. Only half the models simulate mean low-level equatorial westerlies over the warm pool area. The presence of the warm pool can also favor the development of large-scale variability consistent with observed Madden-Julian Oscillation (MJO) characteristics, but this happens only in half the models. Our results do not support the idea that the presence of the warm pool and/or of mean low-level equatorial westerlies are sufficient conditions for MJO-like variability to arise in the models. Comparing spectral characteristics of the simulated Convectively Coupled Equatorial Waves (CCEWs) in the aquaplanet experiments and the corresponding coupled atmosphere-ocean (i.e. CMIP) and atmosphere-only (i.e. AMIP) simulations, we also show that there is more consistency for a given model across its configurations, than for a given configuration across the six models. Overall, our results confirm that the simulation of sub-seasonal variability by given model is significantly influenced by the parameterization of sub-grid physical processes (most-likely cloud processes), both directly and through modulation of the mean state

Model validation and drought assessment with a regional climate model over Moldova

10.7160/sab.2012.430403We assess the drought characteristics in the Republic of Moldova based on the Standardized Precipitation Index (SPI) calculated from monthly precipitation data simulated by the Regional Climate Model RegCM3. The RegCM simulations were conducted at a horizontal resolution of 10 km in the framework of EU-FP6 project Central and Eastern Europe Climate Change Impact and Vulnerability Assessment (CECILIA). The domain was centered over Romania at 46ºN, 25ºE and included the Republic of Moldova. We validate the model ability to simulate monthly temperature and precipitation by comparing the model simulations forced by ERA40 with the observations from CRU TS2.0 dataset and station observations for the period 1961¿1990. The RegCM simulations (control and scenario runs) forced with the ECHAM5 Global Circulation Model (GCM) have been corrected against the systematic errors induced by the GCM. After the bias correction, the annual cycle of temperature and precipitation is analyzed by comparing the model simulations conducted under A1B scenario for the periods 2021¿2050 and 2071¿2100 with the control run for the period 1961¿1990.The characteristics of the drought for the current climate were assessed based on SPI calculated for 1¿24 month lags from CRU dataset and station observations. The SPI for 1, 3, 6, 12, 18, and 24-month lag was calculated and analyzed for RegCM simulations. The results show that the model underestimates the severity of droughts

Influence of the Arctic Oscillation on the vertical distribution of clouds as observed by the A-Train constellation of satellites

The main purpose of this study is to investigate the influence of the Arctic Oscillation (AO), the dominant mode of natural variability over the northerly high latitudes, on the spatial (horizontal and vertical) distribution of clouds in the Arctic. To that end, we use a suite of sensors on-board NASA's A-Train satellites that provide accurate observations of the distribution of clouds along with information on atmospheric thermodynamics. Data from three independent sensors are used (AQUA-AIRS, CALIOP-CALIPSO and CPR-CloudSat) covering two time periods (winter half years, November through March, of 2002-2011 and 2006-2011, respectively) along with data from the ERA-Interim reanalysis. We show that the zonal vertical distribution of cloud fraction anomalies averaged over 67-82 degrees N to a first approximation follows a dipole structure (referred to as "Greenland cloud dipole anomaly", GCDA), such that during the positive phase of the AO, positive and negative cloud anomalies are observed eastwards and westward of Greenland respectively, while the opposite is true for the negative phase of AO. By investigating the concurrent meteorological conditions (temperature, humidity and winds), we show that differences in the meridional energy and moisture transport during the positive and negative phases of the AO and the associated thermodynamics are responsible for the conditions that are conducive for the formation of this dipole structure. All three satellite sensors broadly observe this large-scale GCDA despite differences in their sensitivities, spatio-temporal and vertical resolutions, and the available lengths of data records, indicating the robustness of the results. The present study also provides a compelling case to carry out process-based evaluation of global and regional climate models

Systemic Inflammation Associated with Immune Reconstitution Inflammatory Syndrome in Persons Living with HIV

Antiretroviral therapy (ART) has represented a major advancement in the care of people living with HIV (PLWHH), resulting in significant reductions in morbidity and mortality through immune reconstitution and attenuation of homeostatic disruption. Importantly, restoration of immune function in PLWH with opportunistic infections occasionally leads to an intense and uncontrolled cytokine storm following ART initiation known as immune reconstitution inflammatory syndrome (IRIS). IRIS occurrence is associated with the severe and rapid clinical deterioration that results in significant morbidity and mortality. Here, we detail the determinants underlying IRIS development in PLWH, compiling the available knowledge in the field to highlight details of the inflammatory responses in IRIS associated with the most commonly reported opportunistic pathogens. This review also highlights gaps in the understanding of IRIS pathogenesis and summarizes therapeutic strategies that have been used for IRIS

Multiyear climate predictions using two initialization strategies

Multiyear climate predictions with two initialization strategies are systematically assessed in the EC-Earth V2.3 climate model. In one ensemble, an estimate of the observed climate state is used to initialize the model. The other uses estimates of observed ocean and sea ice anomalies on top of the model climatology. The ensembles show similar spatial characteristics of drift related to the biases in control simulations. As expected, the drift is less with anomaly initialization. The full field initialization overshoots to a colder state which is related to cold biases in the tropics and North Atlantic, associated with oceanic processes. Despite different amplitude of the drift, both ensembles show similar skill in multiyear global temperature predictions, but regionally differences are found. On multiyear time scales, initialization with observations enhances both deterministic and probabilistic skill scores in the North Atlantic. The probabilistic verification shows skill over the European continent

Systemic Inflammation Associated with Immune Reconstitution Inflammatory Syndrome in Persons Living with HIV

Antiretroviral therapy (ART) has represented a major advancement in the care of people living with HIV (PLWHH), resulting in significant reductions in morbidity and mortality through immune reconstitution and attenuation of homeostatic disruption. Importantly, restoration of immune function in PLWH with opportunistic infections occasionally leads to an intense and uncontrolled cytokine storm following ART initiation known as immune reconstitution inflammatory syndrome (IRIS). IRIS occurrence is associated with the severe and rapid clinical deterioration that results in significant morbidity and mortality. Here, we detail the determinants underlying IRIS development in PLWH, compiling the available knowledge in the field to highlight details of the inflammatory responses in IRIS associated with the most commonly reported opportunistic pathogens. This review also highlights gaps in the understanding of IRIS pathogenesis and summarizes therapeutic strategies that have been used for IRIS

Understanding the West African Monsoon from the analysis of diabatic heating distributions as simulated by climate models

International audienceVertical and horizontal distributions of diabatic heating in the West African monsoon (WAM) region as simulated by four model families are analyzed in order to assess the physical processes that affect the WAM circulation. For each model family, atmosphere-only runs of their CMIP5 configurations are compared with more recent configurations which are on the development path toward CMIP6. The various configurations of these models exhibit significant differences in their heating/moistening profiles, related to the different representation of physical processes such as boundary layer mixing, convection, large-scale condensation and radiative heating/cooling. There are also significant differences in the models' simulation of WAM rainfall patterns and circulations. The weaker the radiative cooling in the Saharan region, the larger the ascent in the rainband and the more intense the monsoon flow, while the latitude of the rainband is related to heating in the Gulf of Guinea region and on the northern side of the Saharan heat low. Overall, this work illustrates the difficulty experienced by current climate models in representing the characteristics of monsoon systems, but also that we can still use them to understand the interactions between local subgrid physical processes and the WAM circulation. Moreover, our conclusions regarding the relationship between errors in the large-scale circulation of the WAM and the structure of the heating by small-scale processes will motivate future studies and model development

In silico transcriptional analysis of mRNA and miRNA reveals unique biosignatures that characterizes different types of diabetes.

Diabetes (DM) has a significant impact on public health. We performed an in silico study of paired datasets of messenger RNA (mRNA) micro-RNA (miRNA) transcripts to delineate potential biosignatures that could distinguish prediabetes (pre-DM), type-1DM (T1DM) and type-2DM (T2DM). Two publicly available datasets containing expression values of mRNA and miRNA obtained from individuals diagnosed with pre-DM, T1DM or T2DM, and normoglycemic controls (NC), were analyzed using systems biology approaches to define combined signatures to distinguish different clinical groups. The mRNA profile of both pre-DM and T2DM was hallmarked by several differentially expressed genes (DEGs) compared to NC. Nevertheless, T1DM was characterized by an overall low number of DEGs. The miRNA signature profiles were composed of a substantially lower number of differentially expressed targets. Gene enrichment analysis revealed several inflammatory pathways in T2DM and fewer in pre-DM, but with shared findings such as Tuberculosis. The integration of mRNA and miRNA datasets improved the identification and discriminated the group composed by pre-DM and T2DM patients from that constituted by normoglycemic and T1DM individuals. The integrated transcriptomic analysis of mRNA and miRNA expression revealed a unique biosignature able to characterize different types of DM