ALBERT

Description: Two theories for observed East Africa drying trends during March–May 1979–2013 are reconciled. Both hypothesize that variations in tropical sea surface temperatures (SSTs) caused East Africa drying. The first invokes a mainly human cause resulting from sensitivity to secular warming of Indo–western Pacific SSTs. The second invokes a mainly natural cause resulting from sensitivity to a strong articulation of ENSO-like Pacific decadal variability involving warming of the western Pacific and cooling of the central Pacific. Historical atmospheric model simulations indicate that observed SST variations contributed significantly to the East Africa drying trend during March–May 1979–2013. By contrast, historical coupled model simulations suggest that external radiative forcing alone, including the ocean’s response to that forcing, did not contribute significantly to East Africa drying. Recognizing that the observed SST variations involved a commingling of natural and anthropogenic effects, this study diagnosed how East African rainfall sensitivity was conditionally dependent on the interplay of those factors. East African rainfall trends in historical coupled models were intercompared between two composites of ENSO-like decadal variability, one operating in the early twentieth century before appreciable global warming and the other in the early twenty-first century of strong global warming. The authors find the coaction of global warming with ENSO-like decadal variability can significantly enhance 35-yr East Africa drying trends relative to when the natural mode of ocean variability acts alone. A human-induced change via its interplay with an extreme articulation of natural variability may thus have been key to Africa drying; however, these results are speculative owing to differences among two independent suites of coupled model ensembles.

Description: The 1981–2014 climatology and variability of the March–May eastern Horn of Africa boreal spring wet season are examined using precipitation, upper- and lower-level winds, low-level specific humidity, and convective available potential energy (CAPE), with the aim of better understanding the establishment of the wet season and the cause of the recent observed decline. At 850 mb, the development of the wet season is characterized by increasing specific humidity and winds that veer from northeasterly in February to southerly in June and advect moisture into the region, in agreement with an earlier study. Equally important, however, is a substantial weakening of the 200-mb climatological easterly winds in March. Likewise, the shutdown of the wet season coincides with the return of strong easterly winds in June. Similar changes are seen in the daily evolution of specific humidity and 200-mb wind when composited relative to the interannual wet season onset and end, with the easterlies decreasing (increasing) several days prior to the start (end) of the wet season. The 1981–2014 decrease in March–May precipitation has also coincided with an increase in 200-mb easterly winds, with no attendant change in specific humidity, leading to the conclusion that, while high values of specific humidity are an important ingredient of the wet season, the recent observed precipitation decline has resulted mostly from a strengthening of the 200-mb easterlies. This change in the easterly winds appears to be related to an increase in convection over the Indonesian region and in the associated outflow from that enhanced heat source.

Description: This study focuses on the impact of the Madden–Julian oscillation (MJO)—as monitored by a well-known multivariate index—on large daily precipitation events in West Africa for the period 1981–2014. Two seasons are considered: the near-equatorial wet season in March–May (MAM) and the peak of the West African monsoon during July–September (JAS), when the intertropical convergence zone (ITCZ) is at its most northerly position. Although the MJO-related interannual variation of seasonal mean rainfall is large, the focus here is on the impacts of the MJO on daily time scales because variations in the frequency of intense, short-term, flood-causing, rainfall events are more important for West African agriculture than variations in seasonal precipitation, particularly near the Guinean coast, where precipitation is abundant. Using composites based on thresholds of daily precipitation amounts, changes in mean precipitation and frequency of the heaviest daily events associated with the phase of the MJO are investigated. The expected modulation of mean rainfall by the MJO is much stronger during MAM than during JAS; yet the modulation of the largest events (i.e., daily rainfall rates above the 90th percentile) is comparable in both seasons. Conservative statistical tests of local and field significance indicate unambiguous impacts of the MJO of the expected sign during certain phases, but the nature of the impact depends on the local seasonal precipitation regime. For instance, in JAS, the early stages of the MJO increase the risk of flooding in the Sahel monsoon region while providing relief to the dry southern coast.

Description: Rainfall in South America as simulated by a 24-ensemble member of the ECHAM 4.5 atmospheric general circulation model is compared and contrasted with observations (in areas in which data are available) for the period 1976–2001. Emphasis is placed on determining the onset and end of the rainy season, from which its length and rain rate are determined. It is shown that over large parts of the domain the onset and ending dates are well simulated by the model, with biases of less than 10 days. There is a tendency for model onset to occur early and ending to occur late, resulting in a simulated rainy season that is on average too long in many areas. The model wet season rain rate also tends to be larger than observed. To estimate the relative importance of errors in wet season length and rain rate in determining biases in the annual total, adjusted totals are computed by substituting both the observed climatological wet season length and rate for those of the model. Problems in the rain rate generally are more important than problems in the length. The wet season length and rain rate also contribute substantially to interannual variations in the annual total. These quantities are almost independent, and it is argued that they are each associated with different mechanisms. The observed onset dates almost always lie within the range of onset of the ensemble members, even in the areas with a large model onset bias. In some areas, though, the model does not perform well. In southern Brazil the model ensemble average onset always occurs in summer, whereas the observations show that winter is often the wettest period. Individual members, however, do occasionally show a winter rainfall peak. In southern Northeast Brazil the model has a more distinct rainy season than is observed. In the northwest Amazon the model annual cycle is shifted relative to that observed, resulting in a model bias. No interannual relationship between model and observed onset dates is expected unless onset in the model and observations has a mutual relationship with SST anomalies. In part of the near-equatorial Amazon, there does exist an interannual relationship between onset dates. Previous studies have shown that in this area there is a relationship between SST anomalies and variations in seasonal total rainfall.

Description: Observations and sea surface temperature (SST)-forced ECHAM5 simulations are examined to study the seasonal cycle of eastern Africa rainfall and its SST sensitivity during 1979–2012, focusing on interannual variability and trends. The eastern Horn is drier than the rest of equatorial Africa, with two distinct wet seasons, and whereas the October–December wet season has become wetter, the March–May season has become drier. The climatological rainfall in simulations driven by observed SSTs captures this bimodal regime. The simulated trends also qualitatively reproduce the opposite-sign changes in the two rainy seasons, suggesting that SST forcing has played an important role in the observed changes. The consistency between the sign of 1979–2012 trends and interannual SST–precipitation correlations is exploited to identify the most likely locations of SST forcing of precipitation trends in the model, and conceivably also in nature. Results indicate that the observed March–May drying since 1979 is due to sensitivity to an increased zonal gradient in SST between Indonesia and the central Pacific. In contrast, the October–December precipitation increase is mostly due to western Indian Ocean warming. The recent upward trend in the October–December wet season is rather weak, however, and its statistical significance is compromised by strong year-to-year fluctuations. October–December eastern Horn rain variability is strongly associated with El Niño–Southern Oscillation and Indian Ocean dipole phenomena on interannual scales, in both model and observations. The interannual October–December correlation between the ensemble-average and observed Horn rainfall 0.87. By comparison, interannual March–May Horn precipitation is only weakly constrained by SST anomalies.

Description: The core region of the North American summer monsoon is examined using spatially averaged daily rainfall observations obtained from gauges, with the objective of improving understanding of its climatology and variability. At most grid points, composite and interannual variations of the onset and end of the wet season are well defined, although, among individual stations that make up a grid average, variability is large. The trigger for monsoon onset in southern and eastern Mexico appears to be related to a change in vertical velocity, while for northwestern Mexico, Arizona, and New Mexico it is related to a reduction in stability, as indicated by a decrease in the lifted index. The wet-season rain rate is a combination of the wet-day rain rate, which decreases with distance from the coast, and the wet-day frequency, which is largest over the Sierra Madre Occidental. Thus the maximum total rate lies slightly to the west of the highest orography. As has been previously noted, onset is not always well correlated with total seasonal precipitation, so in these areas, variations of wet-day frequency and wet-day rain rate must be important. Correlations are small between the wet-day frequency and the wet-day rate, and the former is better correlated than the latter with the seasonal rain rate. Summer rainfall in central to southern Mexico exhibits moderate negative correlations with the leading pattern of sea surface temperature (SST) anomalies in the equatorial Pacific, which projects strongly onto El Niño. The influence of equatorial SSTs on southern Mexico rainfall seems to operate mainly through variability of the wet-day frequency, rather than through variations of the wet-day rain rate.

Description: Intraseasonal and interannual variability of extreme wet and dry anomalies over southeastern Brazil and the western subtropical South Atlantic Ocean are investigated. Precipitation data are obtained from the Global Precipitation Climatology Project (GPCP) in pentads during 23 austral summers (December–February 1979/80–2001/02). Extreme wet (dry) events are defined according to 75th (25th) percentiles of precipitation anomaly distributions observed in two time scales: intraseasonal and interannual. The agreement between the 25th and 75th percentiles of the GPCP precipitation and gridded precipitation obtained from stations in Brazil is also examined. Variations of extreme wet and dry anomalies on interannual time scales are investigated along with variations of sea surface temperature (SST) and circulation anomalies. The South Atlantic SST dipole seems related to interannual variations of extreme precipitation events over southeastern Brazil. It is shown that extreme wet and dry events in the continental portion of the South Atlantic convergence zone (SACZ) are decoupled from extremes over the oceanic portion of the SACZ and there is no coherent dipole of extreme precipitation regimes between tropics and subtropics on interannual time scales. On intraseasonal time scales, the occurrence of extreme dry and wet events depends on the propagation phase of extratropical wave trains and consequent intensification (weakening) of 200-hPa zonal winds. Extreme wet and dry events over southeastern Brazil and subtropical Atlantic are in phase on intraseasonal time scales. Extreme wet events over southeastern Brazil and subtropical Atlantic are observed in association with low-level northerly winds above the 75th percentile of the seasonal climatology over central-eastern South America. Extreme wet events on intraseasonal time scales over southeastern Brazil are more frequent during seasons not classified as extreme wet or dry on interannual time scales.

Description: The South American monsoon system (SAMS) is the most important climatic feature in South America and is characterized by pronounced seasonality in precipitation during the austral summer. This study compares several statistical properties of daily gridded precipitation from different data (1998–2008): 1) Physical Sciences Division (PSD), Earth System Research Laboratory [1.0° and 2.5° latitude (lat)/longitude (lon)]; 2) Global Precipitation Climatology Project (GPCP; 1° lat/lon); 3) Climate Prediction Center (CPC) unified gauge (CPC-uni) (0.5° lat/lon); 4) NCEP Climate Forecast System Reanalysis (CFSR) (0.5° lat/lon); 5) NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis (0.5° lat/0.3° lon); and 6) Tropical Rainfall Measuring Mission (TRMM) 3B42 V6 data (0.25° lat/lon). The same statistical analyses are applied to data in 1) a common 2.5° lat/lon grid and 2) in the original resolutions of the datasets. All datasets consistently represent the large-scale patterns of the SAMS. The onset, demise, and duration of SAMS are consistent among PSD, GPCP, CPC-uni, and TRMM datasets, whereas CFSR and MERRA seem to have problems in capturing the correct timing of SAMS. Spectral analyses show that intraseasonal variance is somewhat similar in the six datasets. Moreover, differences in spatial patterns of mean precipitation are small among PSD, GPCP, CPC-uni, and TRMM data, while some discrepancies are found in CFSR and MERRA relative to the other datasets. Fitting of gamma frequency distributions to daily precipitation shows differences in the parameters that characterize the shape, scale, and tails of the frequency distributions. This suggests that significant uncertainties exist in the characterization of extreme precipitation, an issue that is highly important in the context of climate variability and change in South America.