In Bolivia, a large proportion of the water supply of the capital city, La Paz, is provided by meltwater from glaciers. During the year glaciers tend to melt when conditions are dry and warm, and so they provide water when it is needed most. However, these glaciers are shrinking rapidly due to climate change, and their reduction and possible total disappearance will reduce the water available for La Paz for drinking water, agriculture and hydropower. It is therefore important to understand exactly how important glaciers are for water supplies and how glacier runoff interacts with vegetation and peatlands, especially during very dry conditions when other sources of water are lacking. It is also necessary to build modelling tools that will allow us to predict how the glaciers and water resources from the catchments will change in the future, since this information can be used to better manage and adapt to the future change in water supply. Our new project will combine scientists that work with state-of-the-art glacier and hydrological models from Northumbria University, UK, with Bolivian glaciologists and hydrologists from Universidad Mayor de San Andrés, Bolivia and experts on operational melt models from CIMA Research Foundation in Italy. We will first collect high resolution satellite data for the catchment, create a map of landcover by classifying satellite imagery and install a new weather station on one of the glaciers in the catchment. These data will be used, together with existing datasets and satellite derived products, to run a detailed model that can represent in a physical manner all of the processes that affect the amount of water available for use in the catchment, including from glacier melt, groundwater, evapotranspiration and all the main hydrological processes occurring in high mountain catchments. We will also run a simpler, but faster model over the glacier areas and compare the results of the models. We will then construct a model that can represent the melt of Bolivian glaciers well while remaining efficient enough for use by water managers and for modelling into the future. Through this work, the project will meet the following objectives: 1. Provide a new baseline of glaciological and hydrological data for the La Paz/El Alto water supply catchments; 2. Determine the drivers of glacier melt water contribution to water supply and its interannual fluctuations, including during droughts; 3. Determine the importance of feedback mechanisms between glaciers, snow, hydrology and vegetation in the magnitude and seasonality of catchment runoff and; 4. Establish the model complexity required to adequately represent glacier runoff in operational water resource modelling. The results of our work will be published in peer-reviewed journals, but we will also write a briefing document in Spanish for local stakeholders (water managers and government officials) which will be presented at a dissemination workshop in Bolivia. The project will lead to: a new partnership between the organisations involved; new knowledge of Bolivian glaciers and their importance to water supplies; and the development of operational modelling tools that work well in the region. This will allow us to apply for future funding with the long-term aim of predicting glacier change over the entire Cordillera Real and its effect on water supplies into the future - thereby providing the information needed to better manage Bolivian water resources. This will allow planning for additional catchment water storage, implementation of water use efficiency measures, or the implementation of improved drought prediction systems to enhance decision making about water resources.

Precipitation is unanimously recognized as one of the central variables of the global water and energy cycle, mainly because of its direct significance for the availability of water for human beings, agriculture and life on Earth in general, but also because of its impact on the energy budget and the atmospheric circulation through the associated latent heat release. Precipitation processes play a decisive role in controlling and thus predicting both weather phenomena and climate evolution in numerical weather prediction and general circulation models. Despite the importance of water to all creatures on Earth and to the Earth system as a whole, the life cycle of clouds and precipitation is not well understood; a seemingly simple process like the rapid formation of warm rain is still puzzling, and remains far from having a community-consensus explanation or model. The complexity of the microphysical processes underpinning the cloud evolution into the rain process represents the major obstacle for a considerable leap forward in this field and urgently calls for an effort towards combining modeling and observations. While the temporal and spatial scales of both Large-Eddy Simulation and Cloud Resolving Models are now suitable for studying cloud lifecycles, remote sensing observations (the only practically possible to look at such phenomena) have always suffered by the uncertainties deriving from ill-posed inversion problems. For instance the radar reflectivity signal is by definition strongly dependent on the drop size distribution of the scatterers, e.g., raindrops, in the beam volume and its interpretation is therefore related to the microphysical processes responsible for the formation of drop size distributions and their evolution. A unique deployment (to be completed by end of 2010) of multi-wavelength scanning radar with radiometric mode at all ARM facilities will provide unprecedented independent observations which should narrow down the uncertainties in the retrieval process and provide detailed observations of all phases of cloud evolution, from initiation, to development of updrafts and downdrafts, to hydrometeor evolution in time and space, to partitioning of condensate into precipitation and outflow anvils. We propose to take advantage of this upcoming opportunity by developing an optimal estimation approach capable of integrating different sensors in a consistent physical way. We will combine active (radar reflectivity) and passive (brightness temperatures) measurements because both yield different kinds of cloud microphysics information throughout the vertical extension: cloud and weather radars allow to range-resolve cloud structure, whereas passive microwave signals contain information about along-sight integrated water/ice contents. Our proposed technique combines measurements (and their error characteristics) with a priori information (and knowledge about its representativeness) into an optimal estimation framework to provide the atmospheric state together with uncertainty estimates. In order to optimally exploit the information content of remote sensing observations a first guess of the atmospheric state is iterated through the forward model - connecting atmospheric state with the measurement - up to a point where measurements and a priori information best match the retrieved atmospheric state. The ultimate product of the retrieval is represented by profiles of cloud and precipitation water content for the observed atmospheric columns, which will be extensively validated by independent methodologies during the MC3E campaign, planned for 2011 at the Oklahoma Southern Great Plain site. This cutting-edge product will help in developing, evaluating, and ultimately improving parameterization of cloud-precipitation processes in numerical models. As a test bed, a detailed cloud resolving model study oriented at the evaluation of different microphysical packages will be conducted in coincidence with MC3E.

EUREC4A-OA will implement ad-hoc innovative observations and a hierarchy of numerical simulations focusing on mesoscale and submesoscale ocean dynamics and the atmospheric boundary layer at scales ranging from 20 m to 1000 km over the northwest tropical North Atlantic. The aim is to advance our knowledge of the phenomenology and representation of air-sea interactions, physical and biogeochemical ocean small-scale non-linear processes in ESMs but also in NWPs, S2Ss and decadal forecasts operational systems. EUREC4A-OA will bring together international specialists of ocean, atmosphere physical and biogeochemical observations and numerical modelling as well as scientists working on numerical parameterization, operational systems and future projections to address four objectives: 1) Assessing the impact of the diurnal cycle on energy, water and CO2 ocean-atmosphere exchanges and quantifying the modification of diurnal cycle and the related exchanges by meso-scale and submeso-scale features and other extreme conditions; 2) The identification and quantification of the processes ruling the ocean-atmosphere exchanges and uptake of heat, momentum and CO2 at the ocean nonlinear small scales (from a few tens of meters to 500 km); 3) The role of various processes (diurnal cycle, ocean nonlinear small scales, boundary layer aerosols) on the atmosphere shallow convection and cloud formation; 4) To provide improved models metrics and parameterizations for the above processes to be integrated in operational prediction systems and ESMs. EUREC4A-OA associated partners (12 international institutions contributing with more than 35 scientists) will cooperate in integrating new knowledge into improved model metrics and parameterizations. EUREC4A-OA results will enhance capability to deliver novel information that will have a significant impact on science and society.