scholarly journals Seasonal Predictability of Summer Rainfall over South America

2018 ◽  
Vol 31 (20) ◽  
pp. 8181-8195 ◽  
Author(s):  
Rodrigo J. Bombardi ◽  
Laurie Trenary ◽  
Kathy Pegion ◽  
Benjamin Cash ◽  
Timothy DelSole ◽  
...  

The seasonal predictability of austral summer rainfall is evaluated in a set of retrospective forecasts (hindcasts) performed as part of the Minerva and Metis projects. Both projects use the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) coupled to the Nucleus for European Modelling of the Ocean (NEMO). The Minerva runs consist of three sets of hindcasts where the spatial resolution of the model’s atmospheric component is progressively increased while keeping the spatial resolution of its oceanic component constant. In the Metis runs, the spatial resolution of both the atmospheric and oceanic components are progressively increased. We find that raw model predictions show seasonal forecast skill for rainfall over northern and southeastern South America. However, predictability is difficult to detect on a local basis, but it can be detected on a large-scale pattern basis. In addition, increasing horizontal resolution does not lead to improvements in the forecast skill of rainfall over South America. A predictable component analysis shows that only the first predictable component of austral summer precipitation has forecast skill, and the source of forecast skill is El Niño–Southern Oscillation. Seasonal prediction of precipitation remains a challenge for state-of-the-art climate models. Positive benefits of increasing model resolution might be more evident in other atmospheric fields (i.e., temperature or geopotential height) and/or temporal scales (i.e., subseasonal temporal scales).

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 758
Author(s):  
Wayne Yuan-Huai Tsai ◽  
Mong-Ming Lu ◽  
Chung-Hsiung Sui ◽  
Yin-Min Cho

During the austral summer 2018/19, devastating floods occurred over northeast Australia that killed approximately 625,000 head of cattle and inundated over 3000 homes in Townsville. In this paper, the disastrous event was identified as a record-breaking subseasonal peak rainfall event (SPRE). The SPRE was mainly induced by an anomalously strong monsoon depression that was modulated by the convective phases of an MJO and an equatorial Rossby (ER) wave. The ER wave originated from an active equatorial deep convection associated with the El Niño warm sea surface temperatures near the dateline over the central Pacific. Based on the S2S Project Database, we analyzed the extended-range forecast skill of the SPRE from two different perspectives, the monsoon depression represented by an 850-hPa wind shear index and the 15-day accumulated precipitation characterized by the percentile rank (PR) and the ratio to the three-month seasonal (DJF) totals. The results of four S2S models of this study suggest that the monsoon depression can maintain the same level of skill as the short-range (3 days) forecast up to 8–10 days. For precipitation parameters, the conclusions are similar to the monsoon depression. For the 2019 northern Queensland SPRE, the model forecast was, in general, worse than the expectation derived from the hindcast analysis. The clear modulation of the ER wave that enhanced the SPRE monsoon depression circulation and precipitation is suspected as the main cause for the lower forecast skill. The analysis procedure proposed in this study can be applied to analyze the SPREs and their associated large-scale drivers in other regions.


2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.


2021 ◽  
Author(s):  
Juan Sierra ◽  
Jhan Carlo Espinoza ◽  
Clementine Junquas ◽  
Jan Polcher ◽  
Miguel Saavedra ◽  
...  

<p>The Amazon rainforest is a key component of the climate system and one of the main planetary evapotranspiration sources. Over the entire Amazon basin, strong land-atmosphere feedbacks cause almost one third of the regional rainfall to be transpired by the local rainforest. Maximum precipitation recycling ratio takes place on the southwestern edge of the Amazon basin (a.k.a. Amazon-Andes transition region), an area recognized as the rainiest and biologically richest of the whole watershed. Here, high precipitation rates lead to large values of runoff per unit area providing most of the sediment load to Amazon rivers. As a consequence, the transition region can potentially be very sensitive to Amazonian forest loss. In fact, recent acceleration in deforestation rates has been reported over tropical South America. These sustained land-cover changes can alter the regional water and energy balances, as well as the regional circulation and rainfall patterns. In this sense, the use of regional climate models can help to understand the possible impacts of deforestation on the Amazon-Andes zone.</p><p>This work aims to assess the projected Amazonian deforestation effects on the moisture transport and rainfall behavior over tropical South America and the Amazon-Andes transition region. We perform 10-year austral summer simulations with the Weather Research and Forecasting model (WRF) using 3 one-way nested domains. Our finest domain is located over the south-western part of the basin, comprising two instrumented Andean Valleys (Zongo and Coroico river Valleys). Convective permitting high horizontal resolution (1km) is used over this domain. The outcomes presented here enhance the understanding of biosphere-atmosphere coupling and its deforestation induced disturbances.</p>


2019 ◽  
Vol 15 (5) ◽  
pp. 1845-1859 ◽  
Author(s):  
Ignacio A. Jara ◽  
Antonio Maldonado ◽  
Leticia González ◽  
Armand Hernández ◽  
Alberto Sáez ◽  
...  

Abstract. Modern precipitation anomalies in the Altiplano, South America, are closely linked to the strength of the South American summer monsoon (SASM), which is influenced by large-scale climate features sourced in the tropics such as the Intertropical Convergence Zone (ITCZ) and El Niño–Southern Oscillation (ENSO). However, the timing, direction, and spatial extent of precipitation changes prior to the instrumental period are still largely unknown, preventing a better understanding of the long-term drivers of the SASM and their effects over the Altiplano. Here we present a detailed pollen reconstruction from a sedimentary sequence covering the period between 4500 and 1000 cal yr BP in Lago Chungará (18∘ S; 4570 m a.s.l.), a high-elevation lake on the southwestern margin of the Altiplano where precipitation is delivered almost exclusively during the mature phase of the SASM over the austral summer. We distinguish three well-defined centennial-scale anomalies, with dry conditions between 4100–3300 and 1600–1000 cal yr BP and a conspicuous humid interval between 2400 and 1600 cal yr BP, which resulted from the weakening and strengthening of the SASM, respectively. Comparisons with other climate reconstructions from the Altiplano, the Atacama Desert, the tropical Andes, and the southwestern Atlantic coast reveal that – unlike modern climatological controls – past precipitation anomalies at Lago Chungará were largely decoupled from north–south shifts in the ITCZ and ENSO. A regionally coherent pattern of centennial-scale SASM variations and a significant latitudinal gradient in precipitation responses suggest the contribution of an extratropical moisture source for the SASM, with significant effects on precipitation variability in the southern Altiplano.


2019 ◽  
Vol 19 (5) ◽  
pp. 1067-1086 ◽  
Author(s):  
Frank Colberg ◽  
Kathleen L. McInnes ◽  
Julian O'Grady ◽  
Ron Hoeke

Abstract. Projections of sea level rise (SLR) will lead to increasing coastal impacts during extreme sea level events globally; however, there is significant uncertainty around short-term coastal sea level variability and the attendant frequency and severity of extreme sea level events. In this study, we investigate drivers of coastal sea level variability (including extremes) around Australia by means of historical conditions as well as future changes under a high greenhouse gas emissions scenario (RCP 8.5). To do this, a multi-decade hindcast simulation is validated against tide gauge data. The role of tide–surge interaction is assessed and found to have negligible effects on storm surge characteristic heights over most of the coastline. For future projections, 20-year-long simulations are carried out over the time periods 1981–1999 and 2081–2099 using atmospheric forcing from four CMIP5 climate models. Changes in extreme sea levels are apparent, but there are large inter-model differences. On the southern mainland coast all models simulated a southward movement of the subtropical ridge which led to a small reduction in sea level extremes in the hydrodynamic simulations. Sea level changes over the Gulf of Carpentaria in the north are largest and positive during austral summer in two out of the four models. In these models, changes to the northwest monsoon appear to be the cause of the sea level response. These simulations highlight a sensitivity of this semi-enclosed gulf to changes in large-scale dynamics in this region and indicate that further assessment of the potential changes to the northwest monsoon in a larger multi-model ensemble should be investigated, together with the northwest monsoon's effect on extreme sea levels.


Author(s):  
Juan Sulca ◽  
Mathias Vuille ◽  
Oliver Elison Timm ◽  
Bo Dong ◽  
Ricardo Zubieta

AbstractPrecipitation is one of the most difficult variables to estimate using large-scale predictors. Over South America (SA), this task is even more challenging, given the complex topography of the Andes. Empirical-Statistical Downscaling (ESD) models can be used for this purpose, but such models, applicable for all of SA, have not yet been developed. To address this issue, we construct an ESD model based on multiple linear regression techniques for the period 1982-2016 that is based on large-scale circulation indices representing tropical Pacific, Atlantic, and South American climate variability, to estimate austral summer (DJF) precipitation over SA.Statistical analyses show that the ESD model can reproduce observed precipitation anomalies over the tropical Andes (Ecuador, Colombia, Peru, and Bolivia), the eastern equatorial Amazon basin, and the central part of the western Argentinian Andes. On a smaller scale, the ESD model also shows good results over the western Cordillera of the Peruvian Andes.The ESD model reproduces anomalously dry conditions over the eastern equatorial Amazon and the wet conditions over Southeastern South America (SESA) during the three extreme El Niño’s 1982/83, 1997/98, and 2015/16. However, it overestimates the observed intensities over SESA. For the central Peruvian Andes as a case study, results further show that the ESD model can correctly reproduce DJF precipitation anomalies over the entire Mantaro basin during the three extreme El ñ episodes.Moreover, multiple experiments with varying predictor combinations of the ESD model corroborate the hypothesis that the interaction between the South Atlantic Convergence Zone (SACZ) and the equatorial Atlantic Ocean provoked the Amazon drought in 2015/16.


2015 ◽  
Vol 28 (24) ◽  
pp. 9583-9605 ◽  
Author(s):  
Xiangwen Liu ◽  
Song Yang ◽  
Jianglong Li ◽  
Weihua Jie ◽  
Liang Huang ◽  
...  

Abstract Subseasonal predictions of the regional summer rainfall over several tropical Asian ocean and land domains are examined using hindcasts by the NCEP CFSv2. Higher actual and potential forecast skill are found over oceans than over land. The forecast for Arabian Sea (AS) rainfall is most skillful, while that for Indo-China (ICP) rainfall is most unskillful. The rainfall–surface temperature (ST) relationship over AS is characterized by strong and fast ST forcing but a weak and slow ST response, while the relationships over the Bay of Bengal, the South China Sea (SCS), and the India subcontinent (IP) show weak and slow ST forcing, but apparently strong and rapid ST response. Land–air interactions are often less noticeable over ICP and southern China (SC) than over IP. The CFSv2 forecasts reasonably reproduce these observed features, but the local rainfall–ST relationships often suffer from different degrees of unrealistic estimation. Also, the observed local rainfall is often related to the circulation over limited regions, which gradually become more extensive in forecasts as lead time increases. The prominent interannual differences in forecast skill of regional rainfall are sometimes associated with apparent disparities in forecasts of local rainfall–ST relationships. Besides, interannual variations of boreal summer intraseasonal oscillation, featured by obvious changes in frequency and amplitude of certain phases, significantly modulate the forecasts of rainfall over certain regions, especially the SCS and SC. It is further discussed that the regional characteristics of rainfall and model’s deficiencies in capturing the influences of local and large-scale features are responsible for the regional discrepancies of actual predictability of rainfall.


2021 ◽  
Vol 14 (1) ◽  
pp. 73-90
Author(s):  
Hsi-Yen Ma ◽  
Chen Zhou ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Mark D. Zelinka ◽  
...  

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.


2021 ◽  
Vol 34 (1) ◽  
pp. 293-312
Author(s):  
Amandeep Vashisht ◽  
Benjamin Zaitchik ◽  
Anand Gnanadesikan

AbstractGlobal climate models (GCMs) are critical tools for understanding and projecting climate variability and change, yet the performance of these models is notoriously weak over much of tropical Africa. To improve this situation, process-based studies of African climate dynamics and their representation in GCMs are required. Here, we focus on summer rainfall of eastern Africa (SREA), which is crucial to the Ethiopian Highlands and feeds the flow of the Blue Nile River. The SREA region is highly vulnerable to droughts, with El Niño–Southern Oscillation (ENSO) being a leading cause of interannual rainfall variability. Adequate understanding and accurate representation of climate features that influence regional variability is an important but often neglected issue when evaluating models. We perform a process-based evaluation of GCMs, focusing on the upper-troposphere tropical easterly jet (TEJ), which has been hypothesized to link ENSO to SREA. We find that most models have an ENSO–TEJ coupling similar to observed, but the models diverge in their representation of TEJ–SREA coupling. Differences in the latter explain the majority (80%) of variability in ENSO teleconnection simulation across the models. This is higher than the variance explained by rainfall coupling with the Somali jet (44%) and African easterly jet (55%). However, our diagnostics of the leading hypothesized mechanism in the models—variability in divergence in the TEJ exit region—are not consistent across models and suggest that a deeper understanding of the mechanisms of TEJ–precipitation coupling should be a priority for studies of climate variability and change in the region.


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