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Seasonal Forecasts

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In this homework assignment you will be considering seasonal forecasts for Kenya. Consider only
countrywide answers to the questions. Include maps and other graphics where appropriate.
A. ENSO influence
1. When is (are) the main rainy season(s) in Kenya
Suggested resource:
IRI Climatologies MapRoom: Seasonal Fraction of Annual Precipitation1
2. At what time(s) of the year is there an influence of the El Ni o Southern Oscillation (ENSO) on
rainfall over Kenya
Suggested resource:
IRI ENSO MapRoom: Historical Probability of Seasonal Gridded Precipitation Tercile Conditioned
on ENSO2
(Note that the information in this MapRoom is available only for three month seasons. In most
cases, when analyzing teleconnections, scientists typically look at three month periods. Three
months are usually long enough to eliminate the effects of weather noise that may dominate
shorter periods; and they are usually short enough for the background climatology to enable any
teleconnections to operate through a consistent process. Most of your answers to subsequent
sections should focus on the most appropriate three month period(s).)
3. Briefly explain how any ENSO influence(s) teleconnect to Kenya (100 words).
Suggested resources:
Black, E., J. Slingo, K. R. Sperber, 2003: An observational study on the relationship between
excessively strong short rains in coastal East Africa and Indian Ocean SST. Monthly Weather
Review, 131, 74 94.
B. Seasonal Predictability
1. Describe the skill level of IRI s seasonal rainfall forecasts for Kenya for the main rainy season(s).
How does the skill compare to that for other parts of the world
Suggested resource:
Verification of IRI s Seasonal Climate Forecasts3
2. The World Meteorological Organization has established a set of Global Producing Centres
that produce seasonal forecasts on at least a quarterly basis. The GPCs are required to

1 https://iridl.ldeo.columbia.edu/maproom/Global/Climatologies/Precip_Fraction.html 2 https://iridl.ldeo.columbia.edu/maproom/ENSO/Climate_Impacts/ENSO_PRCP_Prob_TS2p1.html 3 https://iri.columbia.edu/our expertise/climate/forecasts/verification/ 4 https://www.wmo.int/pages/prog/wcp/wcasp/gpc/gpc.php
provide measures of the skill of their models. These skill measures are collected and displayed
by the Lead Centre for Long Range Forecast Standardized Verification System .
Which of the models provides the best level of skill for Kenya during the rainy season(s) Use
the mean square skill score (MSSS)5
. Information about the MSSS can be found under the
Documentation link on the Lead Centre site.
3. The IRI continues to take more care than any other global forecasting centre to represent the
uncertainty in its forecasts reliably Briefly describe the various ways in which the IRI tries to
address the problem of estimating reliable probabilities for the forecasts (200 words).
Suggested resources:
Barnston, A. G., S. J. Mason, L. Goddard, L., D. G. DeWitt, and S. E. Zebiak, 2003: Multi model
ensembling in seasonal climate forecasting at IRI. Bulletin of the American Meteorological
Society, 84, 1783 1796.
Goddard, L., S. J. Mason, S. E. Zebiak, C. F. Ropelewski, R. Basher, and M. A. Cane, 2001: Current
approaches to seasonal to interannual climate predictions. International Journal of
Climatology, 21, 1111 1152.
Mason, S. J., L. Goddard, N. E. Graham, E. Yulaeva, L. Sun, and P. A. Arkin, 1999: The IRI seasonal
climate prediction system and the 1997/98 El Ni o event. Bulletin of the American
Meteorological Society, 80, 1853 1873.
C. Seasonal Forecasts
1. The IRI combines the information from the various models in question B.2 into a Net
Assessment . This forecast is in probabilistic format. What did the IRI s Net Assessment
forecast indicate for the rainy season(s) this year Explain how to interpret the probabilistic
forecast (200 words).
Suggested resources:
IRI s Seasonal Climate Forecasts6

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