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The study uses numerical weather prediction models to predict the occurrence of heavy convective rainfall associated with the passage of the African Easterly Wave (AEW) during the period 23–26 August 2017 over Nigeria. Fraction skill score (FSS) and method for object‐based diagnostic evaluation (MODE) verification techniques were applied to verify how well the models predict the high‐impact event and to demonstrate how these tools can support operational forecasting. Ensemble model forecasts at a convective scale from UK Met Office Unified Model (MetUM) and a one‐way nested weather research and forecasting (WRF) model were compared with the integrated multisatellite retrievals for global precipitation measurement (IMERG GPM). The purpose is to examine skills of improved model resolution and ensemble in reproducing rainfall forecasts on useful scales and how the skill varies with spatial scale. WRF 2 and 6 km model forecasts show comparable skill at smaller grid scales. The skill of MetUM improves dramatically when the verification statistics are applied to the ensemble mean of the binary fields of the individual member forecast. The object‐based analysis reveals a similar structure as observed, although displaced eastwards. Most improvement occurred for heavier rainfall events associated with the passage of the AEW. WRF 6 km compares reasonably well with WRF 2 km in terms of shape and structure of rainfall underscoring the ability of the model to reasonably represent convection at 6 km horizontal resolution. The ensemble members in MetUM explicitly reproduce convection at 4 km resolution but are displaced at about 166 km behind observed rainfall. [ABSTRACT FROM AUTHOR]

The present study assesses the medium-range probabilistic forecast issued using an improved version of the Centre for Weather Forecasting and Climate Studies (CPTEC) Ensemble Prediction System (EPS). This version includes improvements made to the method used to select the fastest growing modes (the empirical orthogonal functions (EOF)-based method), and the bias correction. Results demonstrate that this improved CPTEC EPS surpasses the skills of the current operational version. An assessment was conducted using the framework of the THORPEX Interactive Grand Global Ensemble (TIGGE), comparing three configurations of the CPTEC EPS to the EPS from the National Centre for Environment Prediction (NCEP) and the Korean Meteorological Agency (KMA). The score adopted for metrics was the continuous ranked probability score (CRPS), calculated for absolute temperature at the 850 hPa level (T850), and sea level pressure (SLP). The best improvements were found for T850 over the Northern and Southern Hemispheres, with a general increase of 9 days in the useful forecast horizon. SLP augments are more modest, with useful performance extension of 2 days in the Northern Hemisphere and 3 days in the Southern Hemisphere. All the EPSs over the Southern Hemisphere showed a general decrease in performance when compared with their respective counterparts in the Northern Hemisphere, both for T850 and SLP. Over the Tropics, SLP is better predicted than T850 by most EPSs, but the NCEP EPS presents the best performance over this region with similar scores for the two variables. [ABSTRACT FROM AUTHOR]

Performance of all- India summer monsoon rainfall ( June to September) has been studied when June or July or June + July rainfall is reported as being in excess/deficit, using monthly and seasonal rainfall data for the period 1871-2010. The study shows that seasonal rainfall was above/below the long term mean in almost all the years when rainfall of June or July or June + July was in excess/deficit. The probabilities of occurrence of seasonal rainfall below the long term mean are 77, 83, and 92% respectively when June, July, and June + July rainfalls are in deficit. The years in which the rainfalls of June and July were deficit, were mostly El Niño years and their corresponding seasonal rainfalls were below the mean. The deficiencies in June/ July or June + July rainfall during El Niño years thus give an indication of seasonal rainfall being below the mean, and vice versa for La Niña years. The study has brought out an important result that rainfall during June gives a first signal of the performance of seasonal rainfall. In order to explain the relationship between June excess/deficit rainfall and seasonal above/below mean rainfall, an hypothesis is proposed which states that the circulation anomalies developed over the Indian region during an excess/deficit June persist throughout the season. The hypothesis has been proved by examining the composites of excess/deficit June wind anomalies at 850 and 200 hPa and observing their subsequent persistence from July to September. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Empirical conditional probabilities of extreme monthly precipitation averaged over three regions of the southern part of the La Plata basin were calculated as a function of three atmospheric indices: two of them represent low level moisture convergence and the third is related to the mid tropospheric circulation over southern South America. The first region includes southern Paraguay, northeastern Argentina, north of Uruguay and the western sector of southern Brazil, the second region stretches over part of southern Brazil, while the third region, surrounding the Plata Estuary extends over western Uruguay and eastern Argentina between 37 ° S and 32 ° S. Regional monthly precipitation was considered extreme when it exceeded its mean value plus one standard deviation. Conditional empirical probabilities of Months with Extreme Precipitation ( MEP) are more than twice and even four times higher than climatic probabilities when they are calculated under the restriction that the atmospheric indices were beyond certain extreme thresholds empirically defined. Combined conditional probability is even higher when the values of two or the three indices over their respective thresholds take place at the same time, but these cases are less frequent. The index that renders higher conditional probabilities is the one that accounts for the low level moisture convergence in a region that is basically to the west and outside of the three regions. This reflects the fact that most of the mesoconvective systems, which originate to the west of these regions and then move eastwards, produce heavy precipitation that lead to monthly accumulated extremes. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]