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Amandeep Vashisht and Benjamin Zaitchik

Abstract

Climate variabilities can have significant impacts on rainfall in East Africa, leading to disruption in natural and human systems and affecting the lives of tens of millions of people. Subseasonal and interannual variabilities are critical components of total rainfall variability in the region. The goal of this study is to examine the combined effects of the Madden Julian Oscillation (MJO), operating at subseasonal timescale, and the El Niño Southern Oscillation (ENSO), operating at an interannual scale, on the modulation of East African boreal fall (October-November-December; OND) rainfall, commonly called the short rains. Composite analysis shows that daily rainfall responses depend on MJO phase and its interaction with ENSO state. In particular, MJO modulation of rainfall is generally stronger under El Niño conditions relative to ENSO neutral and La Niña conditions, leading to increased potential for daily precipitation excesses during wet MJO phases under El Niño. There is evidence for both dynamic and thermodynamic mechanisms associated with these impacts, including an increase in westerly moisture transport and easterly advection of temperature and moist static energy. Seasonal analysis shows that the frequency and intensity of wet MJO phases during an El Niño contribute notably to the seasonal total precipitation anomaly. This suggests that MJO can mediate El Niño’s impact on OND rainfall in East Africa.

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Fisseha Berhane and Benjamin Zaitchik

Abstract

Spatiotemporal variability in East African precipitation affects the livelihood of tens of millions of people. From the perspective of floods, flash droughts, and agriculture, variability on intraseasonal time scales is a critical component of total variability. The principal objective of this study is to explore subseasonal impacts of the Madden–Julian oscillation (MJO) on tropospheric circulations affecting East Africa (EA) during the long (March–May) and short (October–December) rains and associated variability in precipitation. Analyses are performed for 1979–2012 for dynamics and 1998–2012 for precipitation. Consistent with previous studies, significant MJO influence is found on wet and dry spells during the long and short rains. This influence, however, is found to vary within each season. Specifically, indices of MJO convection at 70°–80°E and 120°W are strongly associated with precipitation variability across much of EA in the early (March) and late (May) long rainy season and in the middle and late (November–December) short rainy season. In the early short rains (October) a different pattern emerges, in which MJO strength at 120°E (10°W) is associated with dry (wet) spells in coastal EA but not the interior. In April the MJO influence on precipitation is obscured but can be diagnosed in lead time associations. This diversity of influences reflects a diversity of mechanisms of MJO influence, including dynamic and thermodynamic mechanisms tied to large-scale atmospheric circulations and localized dynamics associated with MJO modulation of the Somali low-level jet. These differences are relevant to problems of subseasonal weather forecasts and climate projections for EA.

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Benjamin F. Zaitchik and Matthew Rodell

Abstract

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow-covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation—SCA indicates only the presence or absence of snow, not snow water equivalent—and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to nonphysical artifacts in the local water balance. In this paper, a novel assimilation algorithm is presented that introduces Moderate Resolution Imaging Spectroradiometer (MODIS) SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm uses observations from up to 72 h ahead of the model simulation to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes during the snow season and, in some regions, on into the following spring.

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Justin Schulte, Frederick Policelli, and Benjamin Zaitchik

Abstract

It is well documented that the relationship between the El Niño–Southern Oscillation (ENSO) and the Indian summer monsoon changes on interdecadal time scales, yet an explanation for the variations is still a subject of debate. Here, using a continuum framework based on one-point partial correlation maps, we show that the ENSO–Indian rainfall relationship is influenced by the gradient of sea surface temperature anomalies (SSTA) across the Niño-3 region. Based on this identified SSTA pattern, a simple trans-Niño-3 (TN3) index is created that explains up to 50% of all-India rainfall variability during the mid- to late monsoon season after the 1960s. It is also shown that the influence of the TN3 pattern on the relationship between common ENSO metrics and all-India rainfall is strongest during the August–September (AS) monsoon subseason and weakest during the June–July subseason. The TN3 pattern accounts for up to 80% of the change and sign reversal in the AS Niño-1+2–all-India rainfall relationship in recent decades. The 1940s coincides with the intensification of the TN3 pattern and its influence. As the TN3 index is nearly orthogonal to the Niño-3 index, and both are strongly correlated with all-India rainfall, the strengthening TN3 influence must be systematically associated with the weakening Niño-3–all-India relationship in recent decades. This work supports arguments that recent changes in the ENSO–Indian rainfall relationship are not solely related to noise.

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Alexandria M. Russell, Anand Gnanadesikan, and Benjamin Zaitchik

Abstract

Global climate model simulations project that the tropical Andes Mountains of South America, which are particularly vulnerable to climate change because of a reliance on snow and glacial melt for freshwater resources, will experience enhanced warming in the near future, with both higher rates of warming at higher elevations within the mountain range itself and localized enhancement of warming exceeding surrounding areas of the globe. Yet recent surface temperature changes in the tropical Andes do not show evidence for either elevation-dependent warming or regional enhancement of warming on average. However, it remains a possibility that the expected warming trends in this region have begun to manifest in other ways (e.g., in the free atmosphere or at intermediate mountain elevations). This paper proposes evidence from several reanalysis products that there has indeed been a regional enhancement of midtropospheric warming around the central Andes over the past few decades that makes this region stand out as a hot spot within the broader pantropics. This trend is generally not reproduced by historical AMIP climate model simulations, which suggests that the mechanisms through which the atmosphere is warming over the central Andes are not adequately captured by climate models. Possible explanations for localized enhancement of warming in this region are considered. On the other hand, reanalysis products do not consistently exhibit enhanced warming at intermediate mountain elevations in the central Andes as evidenced by the generally moderate rates of change in the freezing-level height, except perhaps in the highest-resolution reanalysis product.

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Fisseha Berhane, Benjamin Zaitchik, and Hamada S. Badr

Abstract

This paper characterizes the influence of the Madden–Julian oscillation (MJO) on spring rainy season (March–June) convection variability over equatorial West Africa (EWA) and investigates mechanisms of association. It is found that the MJO has a significant impact on convection and precipitation anomalies over the region. Over large portions of EWA, MJO impacts on rainfall constitute a difference on the order of 20%–50% from average daily rain rates for the season. This impact is primarily due to the direct influence of the eastward movement of the MJO convective core into EWA, which is associated with westerly low-level wind anomalies that advect moisture from the Atlantic Ocean to the region. In addition, equatorial Rossby and Kelvin waves triggered by MJO convection anomalies over the Indian Ocean have a significant and systematic influence on EWA spring rainy season precipitation. The Kelvin wave contribution and the relative strength of the direct MJO convective influence compared to that of equatorial wave activity differs from findings of studies that have examined MJO influence on EWA during boreal summer. In addition, MJO is found to influence precipitation extremes during spring rains in a manner that is not observed in summer. Importantly, in this analysis the influences of MJO convection and each of the MJO-associated convectively coupled equatorial waves frequently coincide, reaching EWA approximately 20 days after MJO convection initiates in the Indian Ocean. This coincident timing enhances the total MJO impact on the region, and it also implies that MJO events have potential for prediction of regional-scale convection and rainfall anomalies over EWA in this season.

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Asha K. Jordan, Anand Gnanadesikan, and Benjamin Zaitchik

Abstract

North Africa is the world’s largest source of mineral dust, and this dust has potentially significant impacts on precipitation. Yet there is no consensus in published studies regarding the sign or magnitude of dust impacts on rainfall in either the highly climate-sensitive Sahel region of North Africa or the neighboring tropical Atlantic Ocean. Here the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model 2 (GFDL CM2.0) with Modular Ocean Model, version 4.1 (MOM4.1), run at coarse resolution (CM2Mc) is applied to investigate one poorly characterized aspect of dust–precipitation dynamics: the importance of sea surface temperature (SST) changes in mediating the atmospheric response to dust. Two model experiments were performed: one comparing Dust-On to Dust-Off simulations in the absence of ocean–atmosphere coupling, and the second comparing Dust-On to Dust-Off with the ocean fully coupled. Results indicate that SST changes in the coupled experiment reduce the magnitude of dust impacts on Sahel rainfall and flip the sign of the precipitation response over the nearby ocean. Over the Sahel, CM2Mc simulates a net positive impact of dust on monsoon season rainfall, but ocean–atmosphere coupling in the presence of dust decreases the inflow of water vapor, reducing the amount by which dust enhances rainfall. Over the tropical Atlantic Ocean, dust leads to SST cooling in the coupled experiment, resulting in increased static stability that overrides the warming-induced increase in convection observed in the uncoupled experiment and yields a net negative impact of dust on precipitation. These model results highlight the potential importance of SST changes in dust–precipitation dynamics in North Africa and neighboring regions.

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Fisseha Berhane, Benjamin Zaitchik, and Amin Dezfuli

Abstract

The Ethiopian portion of the Blue Nile River basin is subject to significant interannual variability in precipitation. As this variability has implications for local food security and transboundary water resources, numerous studies have been directed at improved understanding and, potentially, predictability of the Blue Nile rainy season (June–September) precipitation. Taken collectively, these studies present a wide range of large-scale drivers associated with precipitation variability in the Blue Nile: El Niño–Southern Oscillation (ENSO), the Indian summer monsoon, sea level pressure (SLP) anomalies over the Arabian Peninsula and Gulf of Guinea, the quasi-biennial oscillation (QBO), and dynamics of the tropical easterly jet (TEJ) and African easterly jet (AEJ) have all been emphasized to varying degrees. This study aims to reconcile these diverse analyses by evaluating teleconnection patterns and potential mechanisms of association on the subseasonal scale. It is found that associations with the TEJ, Pacific modes of variability, and the Indian monsoon are strongest in the late rainy season. Mid–rainy season precipitation (July and August) shows mixed associations with Pacific/Indian Ocean variability and Atlantic Ocean indices, along with connections to regional pressure patterns and the AEJ. June precipitation is negatively correlated with SLP over the equatorial Atlantic and upper-tropospheric geopotential height. June and July precipitation show little significant correlation with the sea surface temperature over the equatorial Pacific Ocean. The observed intraseasonal evolution of teleconnections across the rainy season indicates that subseasonal analysis is required to advance understanding and prediction of Blue Nile precipitation variability.

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Amandeep Vashisht, Benjamin Zaitchik, and Anand Gnanadesikan

Abstract

Global 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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Wanshu Nie, Benjamin F. Zaitchik, Guangheng Ni, and Ting Sun

Abstract

Anthropogenic heat is an important component of the urban energy budgets that can affect land surface and atmospheric boundary layer processes. Representation of anthropogenic heat in numerical climate modeling systems is therefore important when simulating urban meteorology and climate and has the potential to improve weather forecasts, climate process studies, and energy demand analysis. Here, spatiotemporally dynamic anthropogenic heat data estimated by the Building Effects Parameterization and Building Energy Model (BEP-BEM) are incorporated into the Weather Research and Forecasting (WRF) Model system to investigate its impact on simulation of summertime rainfall in Beijing, China. Simulations of four local rainfall events with and without anthropogenic heat indicate that anthropogenic heat leads to increased rainfall over the urban area. For all four events, anthropogenic heat emission increases sensible heat flux, enhances mixing and turbulent energy transport, lifts PBL height, increases dry static energy, and destabilizes the atmosphere in urban areas through thermal perturbation and strong upward motion during the prestorm period, resulting in enhanced convergence during the major rainfall period. Intensified rainfall leads to greater atmospheric dry-down during the storm and a higher poststorm LCL.

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