Based on Intergovernmental Panel on Climate Change (IPCC, 2007b), changes in climate patterns are projected to have a number of impacts including possible water shortages, decreased agricultural production, and food insecurity. With these considerations, a joint project undertaking was forged between the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA), the FAO-AMICAF (Food and Agriculture Organization of the United Nations), and University of Cantabria in Spain. The project aims to assess vulnerability of households to food insecurity through the use of a tool called MOSAICC (Modelling System for Agricultural Impacts of Climate Change). Ultimately, climate information generated from the project can be used to provide relevant and updated climate information for national socioeconomic policy making.
Based on Intergovernmental Panel on Climate Change (IPCC, 2007b), changes in climate patterns are projected to have a number of impacts including possible water shortages, decreased agricultural production, and food insecurity. With these considerations, a joint project undertaking was forged between the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA), the FAO-AMICAF (Food and Agriculture Organization of the United Nations), and University of Cantabria in Spain. The project aims to assess vulnerability of households to food insecurity through the use of a tool called MOSAICC (Modelling System for Agricultural Impacts of Climate Change). Ultimately, climate information generated from the project can be used to provide relevant and updated climate information for national socioeconomic policy making.
The work plan was implemented through a series of workflow wherein PAGASA undertook the first step of the work plan which is the climate scenario downscaling. Global climate models (GCMs) were statistically downscaled at station level under the Coupled Model Intercomparison Project Phase 3 (CMIP3). These GCMs are BCM2, CNCM3, and MPEH5.
Results of climate projections are provided in two time period: historical climate (1971-2000) and future climate (2011-2040) using two Special Report on Emission Scenarios (SRES): A1B (medium-range) and A2 (high-range). SRES are based on projected greenhouse gases emissions in future years.
There are three seasonal variables available for download : precipitation, minimum temperature, and maximum temperature. Season is defined as an average of three-month values: DJF (December-January-February), MAM (March, April, May), JJA (June, July, August), and SON (September-October-November).
A technical note to you understand our products is also available for download via this link.
NOTE: Kindly refer to this article for citation of methodology.
(2014). Assessments of Climate Change Impacts and Mapping of Vulnerability to Food Insecurity under Climate Change to Strengthen Household Food Security with Livelihoods’ Adaptation Approaches (AMICAF): Project Terminal Report. Submitted to Food and Agriculture Organization of the United Nations Country Office in the Philippines. Quezon City: DOST-PAGASA.
Basconcillo, J., A. Lucero, A. Solis, R. Sandoval, Jr., E. Bautista, T. Koizumi, and H. Kanamaru, 2016: Statistically downscaled projected changes in Seasonal Mean Temperature and Rainfall in Cagayan Valley, Philippines. J. Meteor. Soc. Japan, 94A, 151-164.
IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Lucero, A., Basconcillo, J., Solis, A., Kanamaru, H., Bautista, E., Sandoval, R., Hilario, S., Juanillo, E., (2014). Recent Projected Changes (2011-2040) in Seasonal Mean Temperature and Rainfall in the Philippines. Paper presented at the 3rd National Climate Conference. Manila, Philippines.
Manzanas, R., Brands, S., San-Martin, D., Lucero, A., Limbo, C., Gutierrez, J. (2015) Statistical Downscaling in the Tropics is Sensitive to Reanalysis Choice. Journal of Climate., Vol. 28, 4171-4184
Based on Intergovernmental Panel on Climate Change (IPCC, 2007b), changes in climate patterns are projected to have a number of impacts including possible water shortages, decreased agricultural production, and food insecurity. With these considerations, a joint project undertaking was forged between the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA), the FAO-AMICAF (Food and Agriculture Organization of the United Nations), and University of Cantabria in Spain. The project aims to assess vulnerability of households to food insecurity through the use of a tool called MOSAICC (Modelling System for Agricultural Impacts of Climate Change). Ultimately, climate information generated from the project can be used to provide relevant and updated climate information for national socioeconomic policy making.
The work plan was implemented through a series of workflow wherein PAGASA undertook the first step of the work plan which is the climate scenario downscaling. Global climate models (GCMs) were statistically downscaled at station level under the Coupled Model Intercomparison Project Phase 3 (CMIP3). These GCMs are BCM2, CNCM3, and MPEH5.
Results of climate projections are provided in two time period: historical climate (1971-2000) and future climate (2011-2040) using two Special Report on Emission Scenarios (SRES): A1B (medium-range) and A2 (high-range). SRES are based on projected greenhouse gases emissions in future years.
There are three seasonal variables available for download : precipitation, minimum temperature, and maximum temperature. Season is defined as an average of three-month values: DJF (December-January-February), MAM (March, April, May), JJA (June, July, August), and SON (September-October-November).
A technical note to you understand our products is also available for download via this link.
NOTE: Kindly refer to this article for citation of methodology.
(2014). Assessments of Climate Change Impacts and Mapping of Vulnerability to Food Insecurity under Climate Change to Strengthen Household Food Security with Livelihoods’ Adaptation Approaches (AMICAF): Project Terminal Report. Submitted to Food and Agriculture Organization of the United Nations Country Office in the Philippines. Quezon City: DOST-PAGASA.
Basconcillo, J., A. Lucero, A. Solis, R. Sandoval, Jr., E. Bautista, T. Koizumi, and H. Kanamaru, 2016: Statistically downscaled projected changes in Seasonal Mean Temperature and Rainfall in Cagayan Valley, Philippines. J. Meteor. Soc. Japan, 94A, 151-164.
IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Lucero, A., Basconcillo, J., Solis, A., Kanamaru, H., Bautista, E., Sandoval, R., Hilario, S., Juanillo, E., (2014). Recent Projected Changes (2011-2040) in Seasonal Mean Temperature and Rainfall in the Philippines. Paper presented at the 3rd National Climate Conference. Manila, Philippines.
Manzanas, R., Brands, S., San-Martin, D., Lucero, A., Limbo, C., Gutierrez, J. (2015) Statistical Downscaling in the Tropics is Sensitive to Reanalysis Choice. Journal of Climate., Vol. 28, 4171-4184