Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of anomalous hydrometeorological events over East Africa
- 755 Downloads
The skill of North American multimodel ensemble (NMME) seasonal forecasts in East Africa (EA), which encompasses one of the most food and water insecure areas of the world, is evaluated using deterministic, categorical, and probabilistic evaluation methods. The skill is estimated for all three primary growing seasons: March–May (MAM), July–September (JAS), and October–December (OND). It is found that the precipitation forecast skill in this region is generally limited and statistically significant over only a small part of the domain. In the case of MAM (JAS) [OND] season it exceeds the skill of climatological forecasts in parts of equatorial EA (Northern Ethiopia) [equatorial EA] for up to 2 (5)  months lead. Temperature forecast skill is generally much higher than precipitation forecast skill (in terms of deterministic and probabilistic skill scores) and statistically significant over a majority of the region. Over the region as a whole, temperature forecasts also exhibit greater reliability than the precipitation forecasts. The NMME ensemble forecasts are found to be more skillful and reliable than the forecast from any individual model. The results also demonstrate that for some seasons (e.g. JAS), the predictability of precipitation signals varies and is higher during certain climate events (e.g. ENSO). Finally, potential room for improvement in forecast skill is identified in some models by comparing homogeneous predictability in individual NMME models with their respective forecast skill.
KeywordsForecast Skill Precipitation Forecast Temperature Forecast Equitable Threat Score Global Precipitation Climatology Center
The NMME forecasts and CPC-URD precipitation data were downloaded from the Institute of Research Institute (IRI) data library (http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/). The authors thank the CPC, IRI and NCAR personnel in creating, updating and maintaining the NMME archive. The NMME project and data dissemination is supported by NOAA, NSF, NASA and DOE. The GPCC Precipitation data was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at http://www.esrl.noaa.gov/psd/. The CHIRPS precipitation data was obtained from ftp://ftp.chg.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/global_monthly/ and the CRU temperature data set was obtained from Center of Environmental Data Archival via (https://services.ceda.ac.uk/dj_security/account/signin/?r=; http://browse.ceda.ac.uk/browse/badc/cru/data/cru_ts/cru_ts_3.22). Support for this study comes from the US Geological Survey (USGS) cooperative agreement #G09AC000001, NOAA Award NA11OAR4310151, the USGS Climate and Land Use Change program, NASA Grants NNX15AL46G, NNH12ZDA001 N-IDS and NNX14AD30G and through the SERVIR Applied Sciences Team as part of the NASA Earth Sciences Division Applied Sciences Program, Capacity Building Initiative (Dr. Nancy Searby Manager).
- Funk C, Senay G, Asfaw A, Verdin J, Rowland J, Michaelson J, Eilerts G, Korecha D, Choularton R (2005) Recent drought tendencies in Ethiopia and equatorial-subtropical eastern Africa. Famine Early Warning System Network, USAID, Washington, DC. Aug 2. http://pdf.usaid.gov/pdf_docs/Pnadh997.pdf. Accessed 27 July 2016
- López-Carr D, Pricope NG, Aukema JE et al (2014) A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide. Popul Environ 35:323–339. doi: 10.1007/s11111-014-0209-0 CrossRefGoogle Scholar
- Ogallo L, Oludhe C (2009) Climate information in decision-making in the Greater Horn of Africa: lessons and experiences. WMO Bull 58:185Google Scholar
- Wilks DS (2006) Statistical methods in the atmospheric sciences, 2nd edn. Academic Press, LondonGoogle Scholar