The summer North Atlantic Oscillation in CMIP3 models and related uncertainties in projected summer drying in Europe

This paper discusses uncertainties in model projections of summer drying in the Euro-Mediterranean region related to errors and uncertainties in the simulation of the summer NAO (SNAO). The SNAO is the leading mode of summer SLP variability in the North Atlantic/European sector and modulates precipitation not only in the vicinity of the SLP dipole (northwest Europe) but also in the Mediterranean region. An analysis of CMIP3 models is conducted to determine the extent to which models reproduce the signature of the SNAO and its impact on precipitation and to assess the role of the SNAO in the projected precipitation reductions. Most models correctly simulate the spatial pattern of the SNAO and the dry anomalies in northwest Europe that accompany the positive phase. The models also capture the concurrent wet conditions in the Mediterranean, but the amplitude of this signal is too weak, especially in the east. This error is related to the poor simulation of the upper-level circulation response to a positive SNAO, namely the observed trough over the Balkans that creates potential instability and favors precipitation. The SNAO is generally projected to trend upwards in CMIP3 models, leading to a consistent signal of precipitation reduction in NW Europe, but the intensity of the trend varies greatly across models, resulting in large uncertainties in the magnitude of the projected drying. In the Mediterranean, because the simulated influence of the SNAO is too weak, no precipitation increase occurs even in the presence of a strong SNAO trend, reducing confidence in these projections

Regional Climate Model–Simulated Timing and Character of Seasonal Rains in South America

The potential of an experimental nested prediction system to improve the simulation of subseasonal rainfall statistics including daily precipitation intensity, rainy season onset and withdrawal, and the frequency and duration of dry spells is evaluated by examining a four-member ensemble of regional climate model simulations performed for the period 1982–2002 over South America. The study employs the International Centre for Theoretical Physics (ICTP) regional climate model, version 3 (RegCM3), driven with the NCEP–NCAR reanalysis and the European Centre–Hamburg GCM, version 4.5. Statistics were examined for five regions: the northern Amazon, southern Amazon, the monsoon region, Northeast Brazil, and southeastern South America. RegCM3 and the GCM are able to replicate the distribution of daily rainfall intensity in most regions. The analysis of the rainy season timing shows the observed onset occurring first over the monsoon region and then spreading northward into the southern Amazon, in contrast to some previous studies. Correlations between the onset and withdrawal date and SSTs reveal a strong relationship between the withdrawal date in the monsoon region and SSTs in the equatorial Pacific, with above-average SSTs associated with late withdrawal. Over Northeast Brazil, the regional model errors are smaller than those shown by the GCM, and the strong interannual variability in the timing of the rainy season is better simulated by RegCM3. However, the regional model displays an early bias in onset and withdrawal over the southern Amazon and the monsoon regions. Both RegCM3 and the GCM tend to underestimate (overestimate) the frequency of shorter (longer) dry spells, although the differences in dry spell frequency during warm and cold ENSO events are well simulated. The results presented here show that there is potential for added value from the regional model in simulating subseasonal statistics; however, improvements in the physical parameterizations are needed for this tropical region

Seasonal cycle of precipitation variability in South America on intraseasonal timescales

The seasonal cycle of the intraseasonal (IS) variability of precipitation in South America is described through the analysis of bandpass filtered outgoing longwave radiation (OLR) anomalies. The analysis is discriminated between short (10--30 days) and long (30--90 days) intraseasonal timescales. The seasonal cycle of the 30--90-day IS variability can be well described by the activity of first leading pattern (EOF1) computed separately for the wet season (October--April) and the dry season (May--September). In agreement with previous works, the EOF1 spatial distribution during the wet season is that of a dipole with centers of actions in the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA), while during the dry season, only the last center is discernible. In both seasons, the pattern is highly influenced by the activity of the Madden--Julian Oscillation (MJO). Moreover, EOF1 is related with a tropical zonal-wavenumber-1 structure superposed with coherent wave trains extended along the South Pacific during the wet season, while during the dry season the wavenumber-1 structure is not observed. The 10--30-day IS variability of OLR in South America can be well represented by the activity of the EOF1 computed through considering all seasons together, a dipole but with the stronger center located over SESA. While the convection activity at the tropical band does not seem to influence its activity, there are evidences that the atmospheric variability at subtropical-extratropical regions might have a role. Subpolar wavetrains are observed in the Pacific throughout the year and less intense during DJF, while a path of wave energy dispersion along a subtropical wavetrain also characterizes the other seasons. Further work is needed to identify the sources of the 10--30-day-IS variability in South America

Climatology and interannual variability of boreal spring wet season precipitation in the eastern Horn of Africa and implications for its recent decline

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

Seasonality of African Precipitation from 1996 to 2009

Abstract A precipitation climatology of Africa is documented using 12 years of satellite-derived daily data from the Global Precipitation Climatology Project (GPCP). The focus is on examining spatial variations in the annual cycle and describing characteristics of the wet season(s) using a consistent, objective, and well-tested methodology. Onset is defined as occurring when daily precipitation consistently exceeds its local annual daily average and ends when precipitation systematically drops below that value. Wet season length, rate, and total are then determined. Much of Africa is characterized by a single summer wet season, with a well-defined onset and end, during which most precipitation falls. Exceptions to the single wet season regime occur mostly near the equator, where two wet periods are usually separated by a period of relatively modest precipitation. Another particularly interesting region is the semiarid to arid eastern Horn of Africa, where there are two short wet seasons separated by nearly dry periods. Chiefly, the summer monsoon spreads poleward from near the equator in both hemispheres, although in southern Africa the wet season progresses northwestward from the southeast coast. Composites relative to onset are constructed for selected points in West Africa and in the eastern Horn of Africa. In each case, onset is often preceded by the arrival of an eastward-propagating precipitation disturbance. Comparisons are made with the satellite-based Tropical Rainfall Measuring Mission (TRMM) and gauge-based Famine Early Warning System (FEWS NET) datasets. GPCP estimates are generally higher than TRMM in the wettest parts of Africa, but the timing of the annual cycle and average onset dates are largely consistent

An evaluation of CORDEX regional climate models in simulating precipitation over Southern Africa

This article evaluates the ability of the Coordinated Regional Downscaling Experiment (CORDEX) regional climate models (RCMs) in simulating monthly rainfall variation during the austral summer half year (October to March) over southern Africa, the timing of the rainy season and the relative frequencies of rainfall events of varying intensities. The phasing and amplitude of monthly rainfall evolution and the spatial progression of the wet season onset are well simulated by the models. Notwithstanding some systematic biases in a few models, the simulated onset and end of the rainy season and their interannual variability are highly correlated with those computed from the reference data. The strongest agreements between the reference and modelled precipitation patterns are found north of about 20∘S in the vicinity of the Inter Tropical Convergence Zone. A majority of the RCMs adequately capture the reference precipitation probability density functions, with a few showing a bias towards excessive light rainfall events.The CORDEX-Africa programme was supported by the Global Change System for Analysis, Research, and Training (START) through the Climate Systems Analysis Group of the University of Cape Town. Support from the World Climate Research Program (WCRP), the Climate and Development Knowledge Network (CDKN), the International Centre for Theoretical Physics (ICTP), the Swedish Meteorological and Hydrological Institute (SMHI) and the European Union Seventh Framework Programme.http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1530-261Xhb2016Geography, Geoinformatics and Meteorolog

Onset and End of the Rainy Season in South America in Observations and the ECHAM 4.5 Atmospheric General Circulation Model

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

Increased dry-season length over southern Amazonia in recent decades and its implication for future climate projection

RESUMEN: We have observed that the dry-season length (DSL) has increased over southern Amazonia since 1979, primarily owing to a delay of its ending dates (dry-season end, DSE), and is accompanied by a prolonged fire season. A poleward shift of the subtropical jet over South America and an increase of local convective inhibition energy in austral winter (June–August) seem to cause the delay of the DSE in austral spring (September–November). These changes cannot be simply linked to the variability of the tropical Pacific and Atlantic Oceans. Although they show some resemblance to the effects of anthropogenic forcings reported in the literature, we cannot attribute them to this cause because of inadequate representation of these processes in the global climate models that were presented in the Intergovernmental Panel on Climate Change’s Fifth Assessment Report. These models significantly underestimate the variability of the DSE and DSL and their controlling processes. Such biases imply that the future change of the DSE and DSL may be underestimated by the climate projections provided by the Intergovernmental Panel on Climate Change’s Fifth Assessment Report models. Although it is not clear whether the observed increase of the DSL will continue in the future, were it to continue at half the rate of that observed, the long DSL and fire season that contributed to the 2005 drought would become the new norm by the late 21st century. The large uncertainty shown in this study highlights the need for a focused effort to better understand and simulate these changes over southern Amazonia