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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
Free access
Vimal Mishra
,
Keith A. Cherkauer
, and
Shraddhanand Shukla

Abstract

Understanding the occurrence and variability of drought events in historic and projected future climate is essential to managing natural resources and setting policy. The Midwest region is a key contributor in corn and soybean production, and the occurrence of droughts may affect both quantity and quality of these crops. Soil moisture observations play an essential role in understanding the severity and persistence of drought. Considering the scarcity of the long-term soil moisture datasets, soil moisture observations in Illinois have been one of the best datasets for studies of soil moisture. In the present study, the authors use the existing observational dataset and then reconstruct long-term historic time series (1916–2007) of soil moisture data using a land surface model to study the effects of historic climate variability and projected future climate change on regional-scale (Illinois and Indiana) drought. The objectives of this study are to (i) estimate changes and trends associated with climate variables in historic climate variability (1916–2007) and in projected future climate change (2009–99) and (ii) identify regional-scale droughts and associated severity, areal extent, and temporal extent under historic and projected future climate using reconstructed soil moisture data and gridded climatology for the period 1916–2007 using the Variable Infiltration Capacity (VIC) model. The authors reconstructed the soil moisture for a long-term (1916–2007) historic time series using the VIC model, which was calibrated for monthly streamflow and soil moisture at eight U.S. Geological Survey (USGS) gauge stations and Illinois Climate Network’s (ICN) soil moisture stations, respectively, and then it was evaluated for soil moisture, persistence of soil moisture, and soil temperature and heat fluxes. After calibration and evaluation, the VIC model was implemented for historic (1916–2007) and projected future climate (2009–99) periods across the study domain. The nonparametric Mann–Kendall test was used to estimate trends using the gridded climatology of precipitation and air temperature variables. Trends were also estimated for annual anomalies of soil moisture variables, snow water equivalent, and total runoff using a long-term time series of the historic period. Results indicate that precipitation, minimum air temperature, total column soil moisture, and runoff have experienced upward trends, whereas maximum air temperature, frozen soil moisture, and snow water equivalent experienced downward trends. Furthermore, the decreasing trends were significant for the frozen soil moisture in the study domain. The results demonstrate that retrospective drought periods and their severity were reconstructed using model-simulated data. Results also indicate that the study region is experiencing reduced extreme and exceptional droughts with lesser areal extent in recent decades.

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Andrew Hoell
,
Andrea E. Gaughan
,
Shraddhanand Shukla
, and
Tamuka Magadzire

Abstract

Southern Africa precipitation during December–March (DJFM), the height of the rainy season, is closely related with two modes of climate variability, El Niño–Southern Oscillation (ENSO) and the subtropical Indian Ocean dipole (SIOD). Recent research has found that the combined effects of ENSO and SIOD phasing are linked with changes to the regional southern Africa atmospheric circulation beyond the individual effects of either ENSO or SIOD alone. Here, the authors extend the recent research and examine the southern Africa land surface hydrology associated with the synchronous effects of ENSO and SIOD events using a macroscale hydrologic model, with particular emphasis on the evolution of the hydrologic conditions over three critical Transfrontier Conservation Areas: the Kavango–Zambezi Conservation Area, the Greater Limpopo Transfrontier Park, and the Kgalagadi Transfrontier Park. A better understanding of the climatic effects of ENSO and SIOD phase combinations is important for regional-scale transboundary conservation planning, especially for southern Africa, where both humans and wildlife are dependent on the timing and amount of precipitation. Opposing ENSO and SIOD phase combinations (e.g., El Niño and a negative SIOD or La Niña and a positive SIOD) result in strong southern Africa climate impacts during DJFM. The strong instantaneous regional precipitation and near-surface air temperature anomalies during opposing ENSO and SIOD phase combinations lead to significant soil moisture and evapotranspiration anomalies in the year following the ENSO event. By contrast, when ENSO and SIOD are in the same phase (e.g., El Niño and a positive SIOD or La Niña and a negative SIOD), the southern Africa climate impacts during DJFM are minimal.

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Shraddhanand Shukla
,
Anne Steinemann
,
Sam F. Iacobellis
, and
Daniel R. Cayan

Abstract

Annual precipitation in California is more variable than in any other state and is highly influenced by precipitation in winter months. A primary question among stakeholders is whether low precipitation in certain months is a harbinger of annual drought in California. Historical precipitation data from 1895 to 2013 are investigated to identify leading monthly indicators of annual drought in each of the seven climate divisions (CDs) as well as statewide. For this study, drought conditions are defined as monthly/annual (October–September) precipitation below the 20th/30th percentile, and a leading indicator is defined as a monthly drought preceding or during an annual drought that has the strongest association (i.e., joint probability of occurrence) with a statewide annual drought. Monthly precipitation variability and contributions to annual precipitation, along with joint probabilities of drought among the winter months, are first analyzed. Then the probabilities of annual drought and the variability in leading indicators are analyzed according to different climate phases and CDs. This study identified December within a water year as being the leading indicator that is most frequently associated with annual drought statewide (56%) and in most of the CDs (the highest was CD2 at 65%). Associated with its leading-indicator status, December drought was most frequently associated with drought in other winter months (joint probability > 30%). Results from this study can help stakeholders to understand and assess the likelihood of annual drought events given monthly precipitation preceding or early in the water year.

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Lu Su
,
Qian Cao
,
Shraddhanand Shukla
,
Ming Pan
, and
Dennis P. Lettenmaier

Abstract

Predictions of drought onset and termination at subseasonal (from 2 weeks to 1 month) lead times could provide a foundation for more effective and proactive drought management. We used reforecasts archived in NOAA’s Subseasonal Experiment (SubX) to force the Noah Multiparameterization (Noah-MP), which produced forecasts of soil moisture from which we identified drought levels D0–D4. We evaluated forecast skill of major and more modest droughts, with leads from 1 to 4 weeks, and with particular attention to drought termination and onset. We find usable drought termination and onset forecast skill at leads 1 and 2 weeks for major D0–D2 droughts and limited skill at week 3 for major D0–D1 droughts, with essentially no skill at week 4 regardless of drought severity. Furthermore, for both major and more modest droughts, we find limited skill or no skill for D3–D4 droughts. We find that skill is generally higher for drought termination than for onset for all drought events. We also find that drought prediction skill generally decreases from north to south for all drought events.

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Shraddhanand Shukla
,
Anne C. Steinemann
, and
Dennis P. Lettenmaier

Abstract

A drought monitoring system (DMS) can help to detect and characterize drought conditions and reduce adverse drought impacts. The authors evaluate how a DMS for Washington State, based on a land surface model (LSM), would perform. The LSM represents current soil moisture (SM), snow water equivalent (SWE), and runoff over the state. The DMS incorporates the standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture percentile (SMP) taken from the LSM. Four historical drought events (1976–77, 1987–89, 2000–01, and 2004–05) are constructed using DMS indicators of SPI/SRI-3, SPI/SRI-6, SPI/SRI-12, SPI/SRI-24, SPI/SRI-36, and SMP, with monthly updates, in each of the state’s 62 Water Resource Inventory Areas (WRIAs). The authors also compare drought triggers based on DMS indicators with the evolution of drought conditions and management decisions during the four droughts. The results show that the DMS would have detected the onset and recovery of drought conditions, in many cases, up to four months before state declarations.

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Benjamin I. Cook
,
Weston Anderson
,
Kimberly Slinski
,
Shraddhanand Shukla
, and
Amy McNally

Abstract

The state of the El Niño–Southern Oscillation (ENSO) is critical for seasonal climate forecasts, but recent events diverged substantially from expectations in many regions, including sub-Saharan Africa where seasonal forecasts are critical tools for addressing food security. Here, we evaluate 39 years (1982–2020) of data on hydroclimate, leaf area index, and maize yields to investigate the strength of ENSO teleconnections in southern and East Africa. Teleconnections to precipitation, soil moisture, and leaf area index are generally stronger during ENSO phases that cause drought conditions (El Niño in southern Africa and La Niña in East Africa), with seasonality that aligns well with the maize growing seasons. Within maize growing areas, however, ENSO teleconnections to hydroclimate and vegetation are generally weaker compared to the broader geographic regions, especially in East Africa. There is also little evidence that the magnitude of the ENSO event affects the hydroclimate or vegetation response in these maize regions. Maize yields in Kenya, Malawi, South Africa, and Zimbabwe all correlate significantly with hydroclimate and leaf area index, with South Africa and Zimbabwe showing the strongest and most consistent yield responses to ENSO events. Our results highlight the chain of causality from El Niño and La Niña forcing of regional anomalies in hydroclimate to vegetation health and maize yields in southern and East Africa. The large spread across individual ENSO events, however, underscores the limitations of this climate mode for seasonal climate prediction in the region, and the importance of finding additional sources of skill for improving climate and yield forecasts.

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Chris Funk
,
Laura Harrison
,
Shraddhanand Shukla
,
Diriba Korecha
,
Tamuka Magadzire
,
Gregory Husak
,
Gideon Galu
, and
Andrew Hoell
Full access
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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