Abstract
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) [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.
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References
Bahaga TK, Kucharski F, Tsidu GM, Yang H (2015) Assessment of prediction and predictability of short rains over equatorial East Africa using a multi-model ensemble. Theor Appl Climatol. doi:10.1007/s00704-014-1370-1
Barnston AG, van den Dool HM (1993) A degeneracy in cross-validated skill in regression-based forecasts. J Clim 6:963–977. doi:10.1175/1520-0442(1993)006<0963:ADICVS>2.0.CO;2
Barnston AG, Tippett MK, van den Dool HM, Unger DA (2015) Toward an improved multi-model ENSO prediction. J Appl Meteorol Climatol. doi:10.1175/JAMC-D-14-0188.1
Becker E, van den Dool H, Zhang Q (2014) Predictability and forecast skill in NMME. J Clim. doi:10.1175/JCLI-D-13-00597.1
Chaney NW, Sheffield J, Villarini G, Wood EF (2014) Development of a high-resolution gridded daily meteorological dataset over Sub-Saharan Africa: spatial analysis of trends in climate extremes. J Clim 27:5815–5835. doi:10.1175/JCLI-D-13-00423.1
Cheung WH, Senay GB, Singh A (2008) Trends and spatial distribution of annual and seasonal rainfall in Ethiopia. Int J Climatol 28:1723–1734. doi:10.1002/joc.1623
Dutra E, Magnusson L, Wetterhall F et al (2013) The 2010–2011 drought in the Horn of Africa in ECMWF reanalysis and seasonal forecast products. Int J Climatol 33:1720–1729. doi:10.1002/joc.3545
Feddersen H, Andersen U (2005) A method for statistical downscaling of seasonal ensemble predictions. Tellus A 57:398–408. doi:10.1111/j.1600-0870.2005.00102.x
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
Funk C, Dettinger MD, Michaelsen JC et al (2008) Warming of the Indian Ocean threatens eastern and southern African food security but could be mitigated by agricultural development. Proc Natl Acad Sci USA 105:11081–11086. doi:10.1073/pnas.0708196105
Funk C, Hoell A, Shukla S et al (2014) Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices. Hydrol Earth Syst Sci 18:4965–4978. doi:10.5194/hess-18-4965-2014
Funk C, Peterson P, Landsfeld M et al (2015) The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci Data 2:150066. doi:10.1038/sdata.2015.66
Goddard L, Barnston AG, Mason SJ (2003) Evaluation of the IRI’S “Net Assessment” seasonal climate forecasts: 1997–2001. Bull Am Meteorol Soc 84:1761–1781. doi:10.1175/BAMS-84-12-1761
Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 Dataset. Int J Climatol 34:623–642. doi:10.1002/joc.3711
Hawthorne S, Wang QJ, Schepen A, Robertson D (2013) Effective use of general circulation model outputs for forecasting monthly rainfalls to long lead times. Water Resour Res 49:5427–5436. doi:10.1002/wrcr.20453
Hillbruner C, Moloney G (2012) When early warning is not enough—Lessons learned from the 2011 Somalia Famine. Glob Food Sec 1:20–28. doi:10.1016/j.gfs.2012.08.001
Hoell A, Funk C (2013) Indo-Pacific sea surface temperature influences on failed consecutive rainy seasons over eastern Africa. Clim Dyn. doi:10.1007/s00382-013-1991-6
Infanti JM, Kirtman BP (2013) Southeastern U.S. Rainfall prediction in the North American multi-model ensemble. J Hydrometeorol 15:529–550. doi:10.1175/JHM-D-13-072.1
Johnson C, Bowler N (2009) On the reliability and calibration of ensemble forecasts. Mon Weather Rev 137:1717–1720. doi:10.1175/2009MWR2715.1
Kam J, Sheffield J, Yuan X, Wood EF (2014) Did a skillful prediction of sea surface temperatures help or hinder forecasting of the 2012 Midwestern US drought? Environ Res Lett 9:034005. doi:10.1088/1748-9326/9/3/034005
Kirtman BP, Min D, Infanti JM et al (2014) The North American multi-model ensemble (NMME): phase-1 seasonal to interannual prediction, phase-2 toward developing intra-seasonal prediction. Bull Am Meteorol Soc 95:585–601. doi:10.1175/BAMS-D-12-00050.1
Korecha D, Barnston AG (2007) Predictability of June–September rainfall in Ethiopia. Mon Weather Rev 135:628–650. doi:10.1175/MWR3304.1
Kumar A, Peng P, Chen M (2014) Is there a relationship between potential and actual skill? Mon Weather Rev 142:2220–2227. doi:10.1175/MWR-D-13-00287.1
Liebmann B, Hoerling MP, Funk C et al (2014) Understanding recent Eastern Horn of Africa rainfall variability and change. J Clim 27:8630–8645. doi:10.1175/JCLI-D-13-00714.1
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
Lyon B, DeWitt DG (2012) A recent and abrupt decline in the East African long rains. Geophys Res Lett. doi:10.1029/2011GL050337
Maxwell D, Fitzpatrick M (2012) The 2011 Somalia famine: context, causes, and complications. Glob Food Sec 1:5–12. doi:10.1016/j.gfs.2012.07.002
Mo KC, Lettenmaier DP (2014) Hydrologic prediction over the conterminous United States using the National multi-model ensemble. J Hydrometeorol 15:1457–1472. doi:10.1175/JHM-D-13-0197.1
Mo KC, Lyon B (2015) Global meteorological drought prediction using the North American multi-model ensemble. J Hydrometeorol. doi:10.1175/JHM-D-14-0192.1
Müller WA, Appenzeller C, Doblas-Reyes FJ, Liniger MA (2005) A debiased ranked probability skill score to evaluate probabilistic ensemble forecasts with small ensemble sizes. J Clim 18:1513–1523. doi:10.1175/JCLI3361.1
Mwangi E, Wetterhall F, Dutra E et al (2014) Forecasting droughts in East Africa. Hydrol Earth Syst Sci 18:611–620. doi:10.5194/hess-18-611-2014
Ogallo L, Oludhe C (2009) Climate information in decision-making in the Greater Horn of Africa: lessons and experiences. WMO Bull 58:185
Pricope NG, Husak G, Lopez-Carr D et al (2013) The climate-population nexus in the East African Horn: emerging degradation trends in rangeland and pastoral livelihood zones. Glob Environ Chang 23:1525–1541. doi:10.1016/j.gloenvcha.2013.10.002
Schepen A, Wang QJ (2014) Ensemble forecasts of monthly catchment rainfall out to long lead times by post-processing coupled general circulation model output. J Hydrol 519:2920–2931. doi:10.1016/j.jhydrol.2014.03.017
Schneider U, Becker A, Finger P et al (2013) GPCC’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor Appl Climatol 115:15–40. doi:10.1007/s00704-013-0860-x
Shukla S, Lettenmaier DP (2011) Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill. Hydrol Earth Syst Sci 15:3529–3538. doi:10.5194/hess-15-3529-2011
Shukla S, Sheffield J, Wood EF, Lettenmaier DP (2013) On the sources of global land surface hydrologic predictability. Hydrol Earth Syst Sci 17:2781–2796. doi:10.5194/hess-17-2781-2013
Shukla S, Funk C, Hoell A (2014a) Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa. Environ Res Lett 9:094009. doi:10.1088/1748-9326/9/9/094009
Shukla S, McNally A, Husak G, Funk C (2014b) A seasonal agricultural drought forecast system for food-insecure regions of East Africa. Hydrol Earth Syst Sci 18:3907–3921. doi:10.5194/hess-18-3907-2014
Steinemann A, Iacobellis SF, Cayan DR (2015) Developing and evaluating drought indicators for decision-making. J Hydrometeorol 16:1793–1803. doi:10.1175/JHM-D-14-0234.1
Stern DI, Gething PW, Kabaria CW et al (2011) Temperature and malaria trends in highland East Africa. PLoS ONE 6:e24524. doi:10.1371/journal.pone.0024524
Tierney JE, Smerdon JE, Anchukaitis KJ, Seager R (2013) Multidecadal variability in East African hydroclimate controlled by the Indian Ocean. Nature 493:389–392. doi:10.1038/nature11785
Tippett MK, Barnston AG, Robertson AW (2007) Estimation of seasonal precipitation tercile-based categorical probabilities from ensembles. J Clim 20:2210–2228. doi:10.1175/JCLI4108.1
Wang H (2014) Evaluation of monthly precipitation forecasting skill of the National Multi-model Ensemble in the summer season. Hydrol Process 28:4472–4486. doi:10.1002/hyp.9957
Williams AP, Funk C (2011) A westward extension of the warm pool leads to a westward extension of the Walker circulation, drying eastern Africa. Clim Dyn 37:2417–2435. doi:10.1007/s00382-010-0984-y
Weisheimer A, Palmer TN (2014) On the reliability of seasonal climate forecasts. J R Soc Interface 11:20131162. doi:10.1098/rsif.2013.1162
Wilks DS (2006) Statistical methods in the atmospheric sciences, 2nd edn. Academic Press, London
Acknowledgments
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).
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This paper is a contribution to the special collection on the North American Multi-Model Ensemble (NMME) seasonal prediction experiment. The special collection focuses on documenting the use of the NMME system database for research ranging from predictability studies, to multi-model prediction evaluation and diagnostics, to emerging applications of climate predictability for subseasonal to seasonal predictions. This special issue is coordinated by Annarita Mariotti (NOAA), Heather Archambault (NOAA), Jin Huang (NOAA), Ben Kirtman (University of Miami) and Gabriele Villarini (University of Iowa).
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Shukla, S., Roberts, J., Hoell, A. et al. Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of anomalous hydrometeorological events over East Africa. Clim Dyn 53, 7411–7427 (2019). https://doi.org/10.1007/s00382-016-3296-z
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DOI: https://doi.org/10.1007/s00382-016-3296-z