Scope for predicting seasonal variation of the SPCZ with ACCESS-S1

Regional seasonal forecasting requires accurate simulation of the variability of local climate drivers. The South Pacific Convergence Zone (SPCZ) is a large region of low-level convergence, clouds and precipitation in the South Pacific, whose effects extend as far as northeast Australia (NEA). The location of the SPCZ is modulated by the El Niño-Southern Oscillation (ENSO) which causes rainfall variability in the region. Correctly simulating the ENSO-SPCZ teleconnection and its interplay with local conditions is essential for improving seasonal rainfall forecasts. Here we analyse the ability of the ACCESS-S1 seasonal forecast system to predict the SPCZ’s relationship with ENSO including its latitudinal shifts, zonal slope and rainfall magnitude between 1990 and 2012 for the December–January–February (DJF) season. We found improvements in ACCESS-S1’s SPCZ prediction capability compared to its predecessor (POAMA), although prediction of the slope is still limited. The inability of ACCESS-S1 to replicate seasons with a strong anti-zonal SPCZ slope is attributed to its atmospheric model. This has implications for accurate seasonal rainfall forecasts for NEA and South Pacific Islands. Future challenges in seasonal prediction facing regional communities and developers of coupled ocean–atmosphere forecast models are discussed.

Evaluation of the NCEP Climate Forecast System and Its Downscaling for Seasonal Rainfall Prediction over Vietnam

This study investigates the ability to apply National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) products and their downscaling by using the Regional Climate Model version 4.2 (RegCM4.2) on seasonal rainfall forecasts over Vietnam. First, the CFS hindcasts (CFS_Rfc) from 1982 to 2009 are used to assess the ability of the CFS to predict the overall circulation and precipitation patterns at forecast lead times of up to 6 months. Second, the operational CFS forecasts (CFS_Ope) and its RegCM4.2 downscaling (RegCM_CFS) for the period 2012–14 are used to derive seasonal rainfall forecasts over Vietnam. The CFS_Rfc and CFS_Ope are validated against the ECMWF interim reanalysis, the Global Precipitation Climatology Centre (GPCC) analyzed rainfall, and observations from 150 meteorological stations across Vietnam. The results show that the CFS_Rfc can capture the seasonal variability of the Asian monsoon circulation and rainfall distribution. The higher-resolution RegCM_CFS product is advantageous over the raw CFS in specific climatic subregions during the transitional, dry, and rainy seasons, particularly in the northern part of Vietnam in January and in the country’s central highlands during July.

Should seasonal rainfall forecasts be used for flood preparedness?

In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.