USING VARIOUS VISUALIZATION TECHNIQUES TO OUTLINE VULNERABILITY TO DROUGHT IN THE REPUBLIC OF MOLDOVA

Using visualization techniques to outline vulnerability to drought in the Republic of Moldova. This paper is a demonstration of use of various visualization techniques in representing the results on vulnerability to drought at various times scales in the Republic of Moldova. Monthly precipitation totals from simulated data at 10 km horizontal resolution with a regional climatic model RegCM, CRU TS2.10 land observation data set at 0.5ºx0.5º horizontal resolution and observations recorded at 15 meteorological stations in Moldova were used to compare the annual cycle of precipitation, seasonal variability of precipitation, and the spatial and temporal evolution of drought. The Empirical Orthogonal Functions (EOF) analysis was used to identify the principal modes of seasonal variability of precipitation over the country and the Standardized Precipitation Index (SPI) was calculated as an indicator of drought or wetness at various time scales (1 to 24 months). The period of analysis was 1960-1997. One of the visualization techniques was the Grid Analysis and Display System (GrADS) which is an easy manipulation and visualization tool for gridded and station meteorological data. We used it to represent the RegCM and CRU data on their grids. The kriging interpolation with a Gaussian model variance was selected as a suitable interpolation tool for the spatial distribution of the SPI and EOF over Moldova. For temporal diagram and mapping, Golden Software Surfer 9.0 and ArcGis Software 9.1 were used. The results presented with these visualization tools emphasize precipitation and drought characteristics over Moldova domain

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

Predicted chance that global warming will temporarily exceed 1.5 °C

The Paris Agreement calls for efforts to limit anthropogenic global warming to less than 1.5 °C above preindustrial levels. However, natural internal variability may exacerbate anthropogenic warming to produce temporary excursions above 1.5 °C. Such excursions would not necessarily exceed the Paris Agreement, but would provide a warning that the threshold is being approached. Here we develop a new capability to predict the probability that global temperature will exceed 1.5 °C above preindustrial levels in the coming 5 years. For the period 2017 to 2021 we predict a 38% and 10% chance, respectively, of monthly or yearly temperatures exceeding 1.5 °C, with virtually no chance of the 5‐year mean being above the threshold. Our forecasts will be updated annually to provide policy makers with advanced warning of the evolving probability and duration of future warming events

Late-Spring Severe Blizzard Events over Eastern Romania: A Conceptual Model of Development

In this paper, the mechanism and model-representation of a late-spring severe blizzard event on eastern Romania are studied. The mechanism relies on the coupled contribution of the tropospheric ageostrophic circulations associated to jet streaks. These circulations: (1) interact under local and regional forcing (sea surface temperature, topography and latent heat) and (2) feedback on enhancing an upper-level jet’s secondary streak, leading to a persistent, severe event. The enhanced secondary jet streak appears only for developing systems that lead to extreme impact, as shown by 40 years of knowledge of late-spring severe blizzards over the area. It is shown that actual regional high-resolution models are able to represent the occurrence and the mechanism of late-spring severe blizzard events, thus increasing the confidence on their ability to represent current and future climate extreme variability. Understanding the preconditioning of dynamic and thermodynamic processes indicated by this analysis could be useful in supporting the operational forecast analysis

Assessing the changes in drought conditions during summer in the Republic of Moldova based on RegCM simulations

We assess the changes in drought conditions during summer in the Republic of Moldova based on the Standardized Precipitation Index (SPI) calculated from monthly precipitation data simulated by the regional climatic model RegCM3. The RegCM simulations were conducted at a horizontal resolution of 10 km in the framework of EU-FP6 project -CECILIA. The domain was centered over Romania at 46°N, 25°E and included the Republic of Moldova

Recent Changes in Storm Track over the Southeast Europe: A Mechanism for Changes in Extreme Cyclone Variability

Recent changes in cyclone tracks crossing Southeast Europe are investigated for the last few decades (1980–1999 compared with 2000–2019) using a developed objective method. The response in number, severity, and persistence of the tracks are analyzed based on the source of origin (the Mediterranean Sea sub-domains) and the target area (Romania-centered domain). In winter, extreme cyclones became more frequent in the south and were also more persistent in the northeast of Romania. In summer, these became more intense and frequent, mainly over the south and southeast of Romania, where they also showed a significant increase in persistence. The regional extreme changes are related to polar jet displacements and further enhanced by the coupling of the sub-tropical jet in the Euro-Atlantic area, such as southwestwards shift in winter jets and a split-type configuration that shifts northeastwards and southeastwards in the summer. These provide a mechanism for regional variability of extreme cyclones through two paths, respectively, by shifting the origins of the tracks and by shifting the interaction between the anomaly jet streaks and the climatological storm tracks. Large-scale drivers of these changes are analyzed in relation to the main modes of atmospheric variability. The tracks number over the target domain is mainly driven during the cold season through a combined action of AO and Polar–European modes, and in summer by the AMO and East-Asian modes. These links and the circulation mode’s recent variability are consistent with changes found in the jet and storm tracks

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2 m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations. © 2011 The Author(s)

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

CECILIA Regional Climate Simulations for Future Climate : Analysis of Climate Change Signal

Regional climate models (RCMs) are important tools used for downscaling climate simulations from global scale models. In project CECILIA, two RCMs were used to provide climate change information for regions of Central and Eastern Europe. Models RegCM and ALADIN-Climate were employed in downscaling global simulations from ECHAM5 and ARPEGE-CLIMAT under IPCC A1B emission scenario in periods 2021-2050 and 2071-2100. Climate change signal present in these simulations is consistent with respective driving data, showing similar large-scale features: warming between 0 and 3 degrees C in the first period and 2 and 5 degrees C in the second period with the least warming in northwestern part of the domain increasing in the southeastern direction and small precipitation changes within range of +1 to -1 mm/day. Regional features are amplified by the RCMs, more so in case of the ALADIN family of models