1. VAMOS Overall Goals To better understand the American monsoons in the context of the global climate system. To improve capacity for seasonal to interannual climate predictions. To assess the implications of anthropogenic climate change for the Americas.

2. Strategy To identify climate phenomena that are scientifically important and have demonstrated potential for predictable components. To encourage partnerships between scientists in interested countries, and to help in the development of research programmes to be sponsored by national and international agencies. To promote broad participation in field programs, both to bring local expertise to an international setting and to enhance scientific exchange and the building of scientific and technical infrastructure.

5. VAMOS Implementation Plan A better understanding of monsoon components and their variability. A better understanding of the role of monsoons in the global water cycle. Improved simulation and monthly-to-seasonal prediction of the monsoon and regional water resources. Improved observational datasets. VAMOS implementation is based on two internationally coordinated monsoon experiments: MESA in South America and NAME in North America. Their objectives are:

7. MESA - Tier 1 The Moisture Corridor east of the Andes What are the structure and variability of the South American Low-Level Jet (SALLJ) and associated moisture transports? What role does the SALLJ play in the precipitation and hydrology of central South America? What are the relative roles of remote variations in SST and local variations in land-surface parameters (topography, soil moisture and vegetation cover) in modulating the SALLJ? What are the structure and variability of stratocumulus decks along the coast of South America, and how is this variability linked to that of convection over land?

9. Main Goals of ALLS To understand the role of American low-level jet in moisture and energy exchange between the tropics and extratropics and related aspects of regional hydrology, climate and climate variability. To provide validation datasets for model simulations and analyses, both in the large and mesoscale, with initial focus on the South American data void.

10. ALLS - Hypotheses Water vapor transports by ALLS are key components of the water cycles over the continents. ALLS have substantial variability on daily, intraseasonal and interannual time scales. This variability is influenced by ENSO as well as by climate anomalies in the Atlantic and Interamerican Seas. Improved observational datasets on ALLS will contribute to more successful weather and climate forecasts. Comparative analyses of LLJs over North and South America will contribute to improve our understanding of the phenomenon in view of interhemispheric similarities and differences.

24. VEPIC - Hypotheses The large-scale subsidence over the eastern Pacific is linked to the rising motion associated with convection over the Amazons and the Altiplano. Daily and seasonal variations of the subsidence inversion and stratocumulus decks over the eastern Pacific are associated with those of upslope flow west of the Altiplano. These processes affect the east-west slope of the capping inversion along the coast, where regional variations in circulations and cloudiness develop. A more precise knowledge of the different properties of stratocumulus decks from southern Chile up to the US will contribute to better understand and model the behavior and radiative properties of those clouds.

25. Project for Improving the Capacity to Forecast and Assess the “El Niño” Weather Phenomenon to Prevent and Mitigate its Effects in Peru Prepared by The Sea Institute of Peru (IMARPE) The National Weather and Hydrological Service of Peru (SENAMHI) The Geophysical Institute of Peru (IGP) The Hydrographic and Navigation Directorate of the Peruvian Navy (DHN) Angel Cornejo, SENAMHI

26. Components of the Project 1. Atmospheric Component –Regional Weather Models: MM5, ETA, RAMS –Basins Hydrological Models: HEC, NWS –Regional Climate Models: Numerical, Statistical 2. Oceanographic Component –Regional Ocean Models (COAST) –Waves height 3. Biological - Fishing Component –Response of marine species to changes in environmental conditions.

27. Subsystems of the Project 1. Observations –6 Oceanographic buoys –40 Automatic Meteorological stations –15 Automatic hydrometeorological stations –9 Automatic ocean-meteorological stations (coastal) –3 Rawinsonde stations –1 Wind profiler –1 Radar for ocean current measuring 2. Communications –Data transmission, reception and distribution –Land stations to receive data –Use of GOES satellite Continued...

28. 3. Data Management –Data transmission, reception and distribution –Land stations to receive data –Use of GOES satellite 4. Modeling –Development, implementation, and operation of models –Weather, climate, oceanic, hydrologic, and biological models. 5. Training and Technical Assistance –Two courses –Hands-on training on modeling 6. Production and Dissemination –User tailored products TOTAL INVESTMENT ≈ US$5.7M (CIF)

31. La Plata Basin Total area: 3.1  10 6 km 2 Countries in basin (% of area): Argentina (30), Bolivia (7), Brazil (45), Paraguay (13), Uruguay (5) Principal river basins: Economic importance: Argentina, Bolivia, Brazil, Paraguay, and Uruguay produce about 70% of their combined GNP and house about 50% of their combined population in the basin. 1/12/00

32. A comparison between Mississippi and La Plata basins

35. MESA - Tier 2 Climatology and Hydrology of the Rio de la Plata Basin What are the dominant sources of precipitable moisture for the basin? What are the relative roles of variations on SST and land surface parameters in modulating the precipitation in the basin? What is the predictability of droughts and floods in the basin? What developments in models of the atmosphere-land- ocean system are required for successful simulation and prediction of the basin’s climatology and hydrology?

37. Near-cycles in river streamflows The Paraná, Paraguay, Uruguay, Negro River streamflow show significant near-cycles in ENSO-like and decadal time scales. There are also significant long-term trends. What causes these variations? The Uruguay and Negro appear to be affected by ENSO. The Paraguay and Paraná appear to be affected by decadal variations in SST in the tropical North Atlantic Ocean. Can these variations be used to obtain useful probabilistic predictions of monthly streamflow in those rivers? What are the current most limiting factors to adequately address these questions? 1/12/00

40. MESA - Tier 3 Integration Towards the end of CLIVAR, MESA will integrate LBA, VEPIC and PIRATA into a comprehensive program of empirical, modeling and predictability studies for South America. The program goal is to reduce uncertainties relating to climate change in the region. The objectives include the development of local competency and enhanced infrastructure.

42. Purpose Provide guidance to mitigate the adverse effects of climate change – Minimize loss of life –Enable economic adaption –Minimize property and infrastructure losses –Develop local competency to support national plans for sustainable development Reducing the uncertainties of relating to Climate Change in South America...

43. Implementation Establish an operational oceanographic observing system in support of ocean climate observations for Columbia, Ecuador, Peru, and Chile. –Implement a network of mooring (reference stations) to provide oceanographic and marine meteorological data in real time. –Implement participation in contribution to the international float program (Argo) to enable developing nation Parties to benefit from global data assimilation programs, which can provide climate change information for the region. Establish regional centers for the acquisition and dissemination of data –Implement a regional nodes in an international network to facilitate the global exchange of climate information. Establish an operation meteorological and atmospheric observing system in support of climate change observations for Argentina, Brazil, Chile, Peru, Bolivia, Paraguay, and Uruguay. –Implement a network of surface reference sites providing data in real-time and in accordance with World Weather Watch and Global Atmospheric Watch, which can benefit from international programs such as CLIVAR/VAMOS.

47. NAME - Tier 1 Mesoscale features in the core monsoon region How are low-level circulations along the Gulf of California related to the diurnal cycle of moisture and convection? What role does the Gulf of California low-level jet play in the summer precipitation and hydrology of southwestern North America? What are the dominant sources of precipitable moisture for monsoon precipitation over southwestern North America? What are the relative roles of local variations in SST and land- surface parameters (topography, soil moisture and vegetation cover) in modulating warm season precipitation in this region?

48. NAME - Tier 2 Regional-scale features over southwestern North America How important are interactions between Tropical Easterly Waves and Gulf of California moisture surges in the prediction of monsoon precipitation? What is the nature of the relationship between the Madden-Julian Oscillation (MJO), tropical cyclone activity and monsoon precipitation? What portion of the skill of summer precipitation forecasts, in addition to that already harvested from ENSO, will arise from an ability to forecast MJO activity over a season? What is the physical setting for the bimodal distribution (i.e. wet- dry-wet) in warm season precipitation over Mexico and Central America and what factors influence its interannual variability?

49. NAME - Tier 3 Continental-scale monsoon circulation How is the evolution of the warm season precipitation regime over North America related to the seasonal evolution of the boundary conditions? What are the interrelationships between year-to-year variations in the boundary conditions, the atmospheric circulation and the continental hydrologic regime? What are the links, if any, between the strength of the summer monsoon in southwestern North America and summertime precipitation over the central United States? Can coupled models reproduce the summer precipitation in average years and years with ENSO/PDO influence? What are the relationships between the incidence and intensity of extreme events (e.g. floods, droughts, hurricanes) and climate variability on intraseasonal-to-interannual time scales?

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