Regional Climate Simulations and Decision Making: The Experience of Pesqueclima The Experience of Pesqueclima I Ibero-American Workshop on Climate Dynamics,

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Regional Climate Simulations and Decision Making: The Experience of Pesqueclima The Experience of Pesqueclima I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling São Paulo, SP, Brazil, August, Departamento de Geociências Fundação Universidade Federal de Rio Grande Nisia Krusche

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 2 Regional climate simulations may aid minimize the vulnerability of local populations. Regional climate simulations may aid minimize the vulnerability of local populations. Fishery communities Fishery communities Impact of climate variations Impact of climate variations Regional climate simulations Regional climate simulations

Pesqueclima Vulnerability of Fishery Communities to Climate Variability, in the Estuary of dos Patos Lagoon I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling São Paulo, SP, Brazil, August, 2007.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 4 Pesqueclima Evaluate the impact of climate variability in social and economical vulnerability of communities that fish shrimp in the estuarine region of dos Patos Lagoon; Provide climate forecasting design- ed to the needs of those communities, and contingency plans to climate situations that are not ade- quate to perform their economical activities.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 30 o S Location of dos Patos Lagoon Fonte: NASA 30 o S

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 6 Fishery Communities of dos Patos Lagoon

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 7 Fishery Artesian Systems of dos Patos Lagoon 1) Exclusive skilled fishers, living in small communities and specialize in fishing in interior waters; 2) Exclusive skilled fishers, living in communities near the entrance channel and specialize in fishing in interior waters and coastal sea waters;

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 8 Fishery Artesian Systems of dos Patos Lagoon 3) Sporadic fishers, living in urban communities and specialized in fishing in interior waters; 4) Exclusive skilled fishers, living in near urban centers and specialized in fishing in interior waters; 5) Fishers of São Lourenço do Sul, defeso period is in spring, while for the others it is in winter;

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 9 Fishery Artesian Systems of dos Patos Lagoon 6)Fisher-farmer, in the rural areas sur- rounding the estuary.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 10 Vulnerability of Fishery Communities Factors Fishery System Social Cohesion Low UsualLow OrganizationFair FineLow Change in arts Higher vulnerability, due to larger fishing effort and lower agreement among fishers. Uncertainties Higher vulnerability, due to uncertainties on the success of catches. Adaptation Low adaptation and learning in all systems, except 4.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 11 Fishers use weather forecasting: navigation, security, net setting and collecting, planning, identify best catch. radio and television; home- radio and cellular to other fishers, other communities, and Uruguayan fishers. Brazilian Navy. Obtained from

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 12 Vulnerability and resilience of those artisan fishery communities depend strongly on their degree of organization. Vulnerability and resilience of those artisan fishery communities depend strongly on their degree of organization. Strengthen of organization; Program to forecast shrimp catches; Plan of alternate options in case of negative results; Improvement on fish commerce; Better distribution of financial resources; Register again all fishers. ClimateForecast

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 13 Total Fishery Catch in dos Patos Lagoon, IBAMA, organized by Marcelo Vasconcellos, 2000.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 14 Artisan Shrimp Catch

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 15 Wavelet Transform

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 16 Energy Spectrum

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 17 Shrimp Life Cycle MESTUARY PLATAFORM SET Estuarine inflow and growing of shrimp fry Reproduction of shrimps in SC OCT NOV DEC Low concentration of shrimps JANGrowing FEB Growing FISHFISH MAR APRFemales go to the ocean MAYMales go to the ocean East winds and low precipitation

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 18 Drainage area of dos Patos Lagoon Organized by Allan de Oliveira, 2006.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 19 Catch and Precipitation Correlations

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 20 Catch and Precipitation Correlations

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 21 D’Incao (2007) observed periods with favorable climate conditions and low shrimp production. D’Incao (2007) observed periods with favorable climate conditions and low shrimp production. Official registers are of low confidence. Factors: biological, oceanographic, economical, and climate.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 22 RegCM3 Simulation Horizontal resolution of 40 km; Grell convective parameterization and Arakawa-Schubert closure.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 23 Topography in Extended Domain

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 24 Simulation Domain

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 25 Periods of simulation EXTREMEVENTINICIAL AND FINAL DATEM WET FEB a JFM JUL a JJA DEC a DJF JAN a JFM JUL a JJA DRY MAY a MJJ SEP a SON JAN a NDJ

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 26 Wet Simulation – Summer 1998

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 27 Wet Simulation – Summer 1998

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 28 Comparação entre simulação do RegCM3 e análise do NCDC, subdomínio SU1, preci- pitação média mensal M e desvio padrão , em mm dia -1, e erro médio relativo BR. Comparação entre simulação do RegCM3 e análise do NCDC, subdomínio SU1, preci- pitação média mensal M e desvio padrão , em mm dia -1, e erro médio relativo BR. M RCM3  RCM3 M NCDC  NCDC BR (%) NOV ,14,77,71,357,0 DEZ ,74,37,11,864,7 JAN ,83,97,21,577,8 FEV ,13,19,61,8 5,2 MAR ,72,26,91,3-2,9

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 29 Comparação entre simulação do RegCM3 e análise do NCDC, subdomínio SU2, precipitação média mensal M e desvio padrão , em mm dia -1, erro médio relativo BR e chuva em Rio Grande. Comparação entre simulação do RegCM3 e análise do NCDC, subdomínio SU2, precipitação média mensal M e desvio padrão , em mm dia -1, erro médio relativo BR e chuva em Rio Grande. M RCM3  RCM3 M NCDC  NCDC BR (%)RG NOV 19977,81,56,51,520,05,8 DEZ ,72,27,91,648,16,6 JAN ,54,26,40,964,06,3 FEV 19986,12,47,52,418,73,5 MAR 19986,01,55,20,915,34,9

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 30 Dry Simulation – Summer 2004 Dry Simulation – Summer 2004

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 31

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 32

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 33 Extreme Events of Precipitation in Rio Grande Observed precitation in Rio Grande is not always that of the drainage area in NCDC. Spatial and temporal patterns are simulated well by RegCM3 in most events; Mensal forecast errors often exceed ±5-30%. Errors decrease in seasonal (3months) average, especially in SU2 region;

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 34 Extreme Events of Precipitation in Rio Grande Error in region SU1 for seasonal average is high, due to boundary distance. Gas parameterization produces errors smaller or equal to Gfc ones. The analysis should be extend to establish a better representation of cumulus convention in the southern region of Brazil.

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 35 Researchers Nisia Krusche – DGEO-FURG Daniela C. Kalikoski – FAO, Roma Rosmeri P. da Rocha – DCA-IAG-USP Pedro Quevedo Neto – DGEO –FURG Team

I Ibero-American Workshop on Climate Dynamics, Climate Change, and Regional Climate Modeling 36 Acknowledgements Acknowledgements CNPq: Ed. 019/2004, n o /2004-6, e Ed. 057/2005, n o / FAPERGS : Ed. PROCOREDES II 001/2005, n o 05/1843.7