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Chris Funk and Joel Michaelsen

Abstract

An extension of Sinclair's diagnostic model of orographic precipitation (“VDEL”) is developed for use in data-poor regions to enhance rainfall estimates. This extension (VDELB) combines a 2D linearized internal gravity wave calculation with the dot product of the terrain gradient and surface wind to approximate terrain-induced vertical velocity profiles. Slope, wind speed, and stability determine the velocity profile, with either sinusoidal or vertically decaying (evanescent) solutions possible. These velocity profiles replace the parameterized functions in the original VDEL, creating VDELB, a diagnostic accounting for buoyancy effects. A further extension (VDELB*) uses an on/off constraint derived from reanalysis precipitation fields. A validation study over 365 days in the Pacific Northwest suggests that VDELB* can best capture seasonal and geographic variations. A new statistical data-fusion technique is presented and is used to combine VDELB*, reanalysis, and satellite rainfall estimates in southern Africa. The technique, matched filter regression (MFR), sets the variance of the predictors equal to their squared correlation with observed gauge data and predicts rainfall based on the first principal component of the combined data. In the test presented here, mean absolute errors from the MFR technique were 35% lower than the satellite estimates alone. VDELB assumes a linear solution to the wave equations and a Boussinesq atmosphere, and it may give unrealistic responses under extreme conditions. Nonetheless, the results presented here suggest that diagnostic models, driven by reanalysis data, can be used to improve satellite rainfall estimates in data-sparse regions.

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Andrew Hoell and Chris Funk

Abstract

El Niño–Southern Oscillation (ENSO) events are accompanied by an anomalous zonal sea surface temperature (SST) gradient over the west Pacific Ocean, defined here as the west Pacific SST gradient (WPG). The WPG is defined as the standardized difference between area-averaged SST over the central Pacific Ocean (Niño-4 region) and west Pacific Ocean (0°–10°N, 130°–150°E). While the direction of the WPG follows ENSO cycles, the magnitude of the gradient varies considerably between individual El Niño and La Niña events. In this study, El Niño and La Niña events are grouped according to the magnitude of the WPG, and tropical SST, circulations, and precipitation are examined for the period 1948–2011. Until the 1980s the WPG showed little trend as the west and central Pacific warmed at similar rates; however, the west Pacific has recently warmed faster than the central Pacific, which has resulted in an increased WPG during La Niña events.

The temporal evolution and distribution of tropical Pacific SST as well as the near-surface tropical Pacific zonal wind, divergence, and vertical velocity are considerably different during ENSO events partitioned according to the strength of the WPG. Modifications to the tropical circulation, resulting in changes to Indo west Pacific precipitation, are linked to strong and consistent circulation and precipitation modifications throughout the Northern Hemisphere during winter.

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Chris C. Funk and Andrew Hoell

Abstract

SSTs in the western Pacific Ocean have tracked closely with CMIP5 simulations despite recent hiatus cooling in the eastern Pacific. This paper quantifies these similarities and associated circulation and precipitation variations using the first global 1900–2012 ENSO-residual empirical orthogonal functions (EOFs) of 35 variables: observed SSTs; 28 CMIP5 SST simulations; Simple Ocean Data Assimilation (SODA) 25-, 70-, and 171-m ocean temperatures and sea surface heights (SSHs); and Twentieth Century Reanalysis, version 2 (20CRv2), surface winds and precipitation.

While estimated independently, these leading EOFs across all variables fit together in a meaningful way, and the authors refer to them jointly as the west Pacific warming mode (WPWM). WPWM SST EOFs correspond closely in space and time. Their spatial patterns form a “western V” extending from the Maritime Continent into the extratropical Pacific. Their temporal principal components (PCs) have increased rapidly since 1990; this increase has been primarily due to radiative forcing and not natural decadal variability.

WPWM circulation changes appear consistent with a Matsuno–Gill-like atmospheric response associated with an ocean–atmosphere dipole structure contrasting increased (decreased) western (eastern) Pacific precipitation, SSHs, and ocean temperatures. These changes have enhanced the Walker circulation and modulated weather on a global scale. An AGCM experiment and the WPWM of global boreal spring precipitation indicate significant drying across parts of East Africa, the Middle East, the southwestern United States, southern South America, and Asia. Changes in the WPWM have tracked closely with precipitation and the increase in drought frequency over the semiarid and water-insecure areas of East Africa, the Middle East, and southwest Asia.

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Andrew Hoell, Chris Funk, and Mathew Barlow

Abstract

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

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Chris Funk, Shraddhanand Shukla, Andy Hoell, and Ben Livneh
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Emily Williams, Chris Funk, Shraddhanand Shukla, and Daniel McEvoy
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Andrew Hoell, Shraddhanand Shukla, Mathew Barlow, Forest Cannon, Colin Kelley, and Chris Funk

Abstract

Southwest Asia, defined as the region containing the countries of Afghanistan, Iran, Iraq, and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during the boreal cold season of November–April. The forcing of southwest Asia precipitation has been previously examined for the entire boreal cold season from the perspective of climate variability originating over the Atlantic and tropical Indo-Pacific Oceans. This study examines the intermonthly differences in precipitation variability over southwest Asia and the atmospheric conditions directly responsible in forcing monthly November–April precipitation.

Seasonally averaged November–April precipitation over southwest Asia is significantly correlated with sea surface temperature (SST) patterns consistent with Pacific decadal variability (PDV), El Niño–Southern Oscillation (ENSO), and the long-term change of global SST (LT). In contrast, the precipitation variability during the individual months of November–April is unrelated and is correlated with SST signatures that include PDV, ENSO, and LT in different combinations.

Despite strong intermonthly differences in precipitation variability during November–April over southwest Asia, similar atmospheric circulations, highlighted by a stationary equivalent barotropic Rossby wave centered over Iraq, force the monthly spatial distributions of precipitation. Tropospheric flow on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean meridional temperature gradient, resulting in temperature advection that is balanced by vertical motions over southwest Asia. The forcing of monthly southwest Asia precipitation by equivalent barotropic Rossby waves is different from the forcing by baroclinic Rossby waves associated with tropically forced–only modes of climate variability.

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Shraddhanand Shukla, Daniel McEvoy, Mike Hobbins, Greg Husak, Justin Huntington, Chris Funk, Denis Macharia, and James Verdin

Abstract

The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, central Asia, and Central America. This study describes development of a new global reference evapotranspiration (ET0) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by FEWS NET to support food insecurity early warning. The ET0 reforecasts span the 1982–2009 period and are calculated following the American Society for Civil Engineers formulation of the Penman–Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from the National Centers for Environmental Prediction CFSv2 model and the National Aeronautics and Space Administration GEOS-5 model. The skill evaluation, using deterministic and probabilistic scores, focuses on the December–February (DJF), March–May (MAM), June–August (JJA), and September–November seasons. The results indicate that ET0 forecasts are a promising tool for early warning of drought and food insecurity. Globally, the regions where forecasts are most skillful (correlation > 0.35 at leads of 2 months) include the western United States, northern parts of South America, parts of the Sahel region, and southern Africa. The FEWS NET regions where forecasts are most skillful (correlation > 0.35 at lead 3) include northern sub-Saharan Africa (DJF; dry season), Central America (DJF; dry season), parts of East Africa (JJA; wet season), southern Africa (JJA; dry season), and central Asia (MAM; wet season). A case study over parts of East Africa for the JJA season shows that ET0 forecasts in combination with the precipitation forecasts would have provided early warning of recent severe drought events (e.g., in 2002, 2004, 2009) that contributed to substantial food insecurity in the region.

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Chris Funk, Laura Harrison, Shraddhanand Shukla, Diriba Korecha, Tamuka Magadzire, Gregory Husak, Gideon Galu, and Andrew Hoell
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William A. Turner, Greg Husak, Chris Funk, Dar A. Roberts, and Charles Jones

Abstract

A simple—yet powerful—indicator for monitoring agricultural drought is the Water Requirement Satisfaction Index (WRSI). In data-sparse, food-insecure areas, the WRSI is used to guide billions of dollars of aid every year. The WRSI uses precipitation (PPT) and reference evapotranspiration (RefET) data to estimate water availability relative to water demand experienced over the course of a growing season. If the season is in progress, to-date conditions can be combined with climatological averages to provide insight into potential end-of-season (EOS) crop performance. However, if the average is misrepresented, these forecasts can hinder early warning and delay precious humanitarian aid. While many agencies use arithmetic average climatologies as proxies for “average conditions,” little published research evaluates their effectiveness in crop-water balance models. Here, we use WRSI hindcasts of three African regions’ growing seasons, from 1981-2019, to assess the adequacy of the arithmetic mean climatological forecast—the Extended WRSI. We find the Extended WRSI is positively biased, overestimating the actual EOS WRSI by 2-23% in east, west, and southern Africa. The presented alternative combines to-date conditions with data from previous seasons to produce a series of historically realistic conclusions to the current season. The mean of these scenarios is the WRSI Outlook. Put in comparison to the Extended WRSI, which creates a single forecast scenario using average inputs that are not co-varying, the WRSI Outlook employs an ensemble of scenarios, which more adequately capture the historical distribution of distribution of rainfall events, as well as the covariability between climate variables. More specifically, the impact of dry spells in individual years is included in the WRSI Outlook, in a way that is smoothed over in the Extended WRSI. We find the WRSI Outlook has a near-zero bias score and generally has a lower RMSE. In total, this paper highlights the inadequacies of the arithmetic mean climatological forecast, and presents a less-biased, and more accurate, scenario-based approach. To this end, the WRSI Outlook can improve our ability to identify agricultural drought and the concomitant need for humanitarian aid.

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