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Intraseasonal precipitation, wind, and vertically integrated moisture flux variability were assessed from June to August between 1998 and 2009. To that end, we used daily precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim reanalysis. The composites of precipitation anomalies showed that during the intraseasonal enhancement of convective activity over the area assessed, increased precipitation occurs over the northern coast of South America; the opposite is true during the decrease in intraseasonal convective activity. The convective activity over the region of maximum precipitation variance is intraseasonally enhanced during 210 days, whereas the decrease occurs during 194 days. During the days on which the convective activity over the region of maximum precipitation variance was enhanced (decreased) by the Madden–Julian oscillation, the frequency of African easterly waves (AEWs) cases was greater (lower). The most significant average characteristics observed during this period were the displacement of positive precipitation anomalies toward the north and the intensification of the flux toward the tropical North Atlantic Ocean. This pattern disfavours precipitation over the northern coast of South America. On the other hand, during the dry period of Madden–Julian oscillation, there was a decrease in AEWs cases which, although there was negative precipitation anomalies over the northern coast of South America, there were positive anomalies over northwest South America. Therefore, the increase (decrease) in convective activity over the region of maximum precipitation variance favours (disfavours) the frequency of AEWs over this region and, consequently, the precipitation over the northern coast of South America decreases (increases) during the dry season (June to August).

Precipitation measurements in the Mekong River Basin (MRB) are full of variability due to this domain's varied weather systems, climate conditions, elevation, and specific land–atmosphere interactions. This study provides an in-depth evaluation of the differences between four gridded precipitation products [i.e. Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Tropical Rainfall Measuring Mission (TRMM), CPC MORPHing technique (CMORPH), and Climatic Research Unit (CRU)] over the Greater Mekong Subregion. Precipitation data from a total of 242 stations in this domain are used to investigate the quality of the gridded products. Our analysis verifies that gauge-based APHRODITE exhibits the highest correlations with the station data as well as the highest probability of detection of daily precipitation. The false alarm ratio, on the other hand, is slightly in favour of TRMM and CMORPH. Subtracting APHRODITE (as baseline) from TRMM and CMORPH reveals the spatial and frequency distribution of potential biases. The results indicate that TRMM appears to have a wet bias in most areas, while CMORPH shows no similar or consistent bias over APHRODITE. To utilize the higher accuracy of APHRODITE and the finer spatial and temporal footprints of CMORPH, a new restructuring algorithm is introduced in this study. The algorithm is capable of eliminating biases and possible artefacts associated with CMORPH while resolving the resolution discrepancies between the two data sets.

This study evaluates the capability of regional climate models (RCMs) in simulating extreme rainfall events over Southern Africa, and in reproducing the characteristics of widespread extreme rainfall events (WERE) in the Western Cape (South Africa). We obtained simulation datasets of nine RCMs from the Co-ordinated Regional Downscaling Experiment (CORDEX) and compared them with observation datasets from the Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) as well as with the reanalysis dataset (ERAINT) that forced the simulations. A self-organising map was used to classify the WEREs into 12 nodes. The contribution of each RCM to each node was compared with the contributions of GPCP, TRMM and ERAINT. Using ERAINT dataset, we analysed the synoptic-scale atmospheric condition associated with each node. The results show that, in simulating the spatial distribution of the extreme rainfall event over Southern Africa, only four RCMs perform better than the forcing reanalysis (ERAINT) while two RCMs perform worse than the reanalysis. All the RCMs underestimate the threshold of extreme rainfall over Western Cape, poorly simulate the inter-annual variability of the WEREs (r ≤ 0.3), but correctly reproduce the maximum frequency of the WEREs in Autumn (March–May). The WEREs in the Western Cape may be broadly grouped into four synoptic rainfall patterns. The first pattern links WEREs with tropical rainfall activities (tropical-temperate troughs); the second pattern shows isolated WEREs; the third and fourth patterns link WEREs with rainfall activities in the mid-latitudes (frontal systems) and over the Agulhas Current, respectively. While most RCMs overestimate the frequency of the first pattern, they all underestimate the frequency of the second pattern but simulate the frequencies of the third and fourth patterns well. The results of this study should help in improving the RCM simulations over Southern Africa and in downscaling impacts of climate change on extreme rainfall events over the region.

A new method to determine the onset dates of the rainy season (ONR) in the Central Amazon area using the antisymmetric in relation to the equator outgoing longwave radiation (OLR) data was developed in a previous paper. This method is adjusted and used here to determine the ONR in Western-Central Brazil (WCB). The adjustment is needed because of the northwest-southeast (NW-SE) orientation of the American monsoon-related convection displacement. The area averages of the OLR (AOLR) are used to identify the ONR dates. The ONR dates in WCB based on the precipitation index determined in a previous work are used as reference for comparisons. The differences between the results with the AOLR method and those shown in previous papers, as well as the advantages of this method are discussed, using composite maps of OLR and maps of the Tropical Rainfall Measuring Mission (TRMM) precipitation data for individual years. The results obtained here for the WCB indicate a potential of the new method for monitoring purposes because the OLR data can easily be obtained and the AOLR calculation is very simple. Copyright © 2011 Royal Meteorological Society

This study examines the differences in diurnal variations of summer (June–August) rainfall recorded in the station rain gauge data (Gdata) and Tropical Rainfall Measuring Mission 3B42 product (Tdata) over central eastern China during 1998–2006. For the diurnal variations, rainfall amount and frequency in Tdata get the maximum in the afternoon, against the double diurnal peaks in the morning and afternoon of Gdata. For the intensity, the principal morning peak in Tdata contrasts with the dominated afternoon peak in Gdata. It is found that the massive morning light rainfall, which is missed by Tdata, greatly contributes to the weakened morning diurnal peaks of amount and frequency and the stronger morning intensity in Tdata. The overestimated afternoon rainfall in Tdata, including the light rainfall detected only by Tdata and the enhanced rainfall in Tdata when both datasets measure the rainfall, strengthens the afternoon peak of rainfall amount and frequency. In addition, the light rainfall in the morning missed by Tdata is more prevalent in plains than in mountains, whereas the overestimation of afternoon rainfall is more significant in mountain regions. For the diurnal rainfall amount, the afternoon peak in Tdata differs from the morning peak in Gdata in plains and the afternoon peak of Tdata is enhanced in mountain regions. Copyright © 2011 Royal Meteorological Society

Variability in sea-surface temperature (SST) and winds in the Angola Benguela frontal zone (ABFZ) in the tropical south-east Atlantic Ocean has previously been shown to be important for regional fisheries and for seasonal rainfall anomalies over Angola/Namibia in austral summer and coastal West Africa in boreal summer. This study investigates intraseasonal variability in winds and SST over this region using QuikSCAT and tropical rainfall measuring mission (TRMM) satellite data for 1999–2004. Wavelet analyses reveal periods of relatively strong power in the 20–30 or 30–64 day frequency bands throughout the record but that there is substantial interannual variability in the occurrence of these intraseasonal oscillations. The implications of this variability for seasonal rainfall anomalies during the main rainy seasons in southern Africa (austral summer) and coastal West Africa (boreal summer) are discussed. Copyright © 2008 Royal Meteorological Society

Satellite observations of clouds and precipitation have a history stretching back over 40 years. The observations of clouds initially led to the inference of precipitation from cloud top features and subsequently more direct methods derived from passive microwave observations. More recently, the Tropical Rainfall Measuring Mission (TRMM) has provided unprecedented information from the first active microwave instrument specifically designed to measure rainfall, the precipitation radar (PR). This paper utilises data from the TRMM PR for the period December 1997 to November 2005 to investigate rainfall over Hawaii and the surrounding ocean. The PR instrument not only provides spatial information on rainfall, but also vertical profiles of precipitation. Data from the PR instrument is used to map rainfall at a spatial resolution of 5 km and, utilising the information from the vertical profiles, map the distribution of trade-wind and non-trade-wind precipitation. This paper provides quantitative estimates of rainfall over Hawaii and the surrounding ocean that generally match those of surface observations and models. It is found that the islands exert a significant influence on the distribution of the amount and occurrence of precipitation over this region. Copyright © 2006 Royal Meteorological Society

From analyses of blended space-based and ground-based global rainfall data, we found increasing trends in the occurrence of extreme heavy and light rain events, coupled to a decreasing trend in moderate rain events in the tropics during 1979-2003. The trends are consistent with a shift in the large-scale circulation associated with a) a relatively uniform increase in warm rain over the tropical oceans, b) enhanced ice-phase rain over the near-equatorial oceans, and c) reduced mixed-phase rain over the tropical ocean and land regions. Due to the large compensation among different rain categories, the total tropical rainfall trend remained undetectable.

Tropical rainfall measuring mission (TRMM) TRMM microwave imager (TMI) retrieved total precipitable water (TPW) has been shown in previous studies to be useful for characterizing energy transport and rainfall variability over water bodies. In this study, 3-day composite TPW values during the monsoon months of June–September in 1999 and 2003 were evaluated against radiosonde derived TPW over the coastal regions of Indian Ocean. The radiosonde measurements were from coastal locations, island stations and ship-based observations made during the 1999 Bay of Bengal Monsoon Experiment (BOBMEX). Our study is one of the first attempts to compare TMI-derived TPW with the BOBMEX data. Root mean square (RMS) error of 8.1 mm and a bias of −0.76 mm were obtained for TMI 3-day composite TPW data with respect to the radiosonde data over the Indian coastal regions. TMI overestimated (underestimated) radiosonde measurements under dry (wet) atmospheric conditions. Daily TMI-derived TPW was also validated with radiosonde measurements from the BOBMEX data for the period 21 July–28 August 1999. Diurnal signals of TPW over Bay of Bengal were found to be comparable to the in situ measurements during the same period. Copyright © 2006 Royal Meteorological Society

Following an earlier paper, which classified tropical rainfall stations using 34 variables and a single clustering approach, this paper compares the results with those utilizing three other methods. A variety of measures were used to assess ‘performance’ of the methods. Three of the methods (Ward, Average Linkage, and Lance-Williams) produced very similar results, and even the other one (Centroid) showed a reasonably similar pattern. The similarity in results from the different methods suggests that the station groups obtained are meaningful. However, minor differences are worthy of consideration when climatological interpretation is undertaken at a later stage of the project.