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Shraddhanand Shukla

Publications and source records attributed to Shraddhanand Shukla.

34 records · Page 2Linked to original sources
USGS2017

A land data assimilation system for sub-Saharan Africa food and water security applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Scientific Data↗
USGS2017

Child health outcomes in sub-Saharan Africa: A comparison of changes in climate and socio-economic factors

We compare changes in low birth weight and child malnutrition in 13 African countries under projected climate change versus socio-economic development scenarios. Climate scenarios are created by linking surface temperature gradients with declines in seasonal rainfall sea along with warming values of 1 °C and 2 °C. Socio-economic scenarios are developed by assigning regionally specific changes in access to household electricity and mother's education. Using these scenarios, in combination with established models of children's health, we investigate and compare the changes in predicted health outcomes. We find that the negative effects of warming and drying on child stunting could be mitigated by positive development trends associated with increasing mothers’ educational status and household access to electricity. We find less potential for these trends to mitigate how warming and drying trends impact birth weights. In short, under warming and drying, the risk of more malnourished children is greater than the risk of more children with low birth weights, but increases in child malnutrition could be averted in regions that increase access to educational resources and basic infrastructure.

Global Environmental Change↗
USGS2017

Examining the value of global seasonal reference evapotranspiration forecasts to support FEWS NET’s food insecurity outlooks

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 (ETo) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by the FEWS NET to support food insecurity early warning. The ETo reforecasts span the 1982-2009 period and are calculated following ASCE’s formulation of Penman-Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from NCEP’s CFSv2 and NASA’s GEOS-5 models. The skill evaluation using deterministic and probabilistic scores, focuses on the December-February (DJF), March-May (MAM), June-August (JJA) and September-November (SON) seasons. The results indicate that ETo 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 lead-2) include Western U.S., northern parts of South America, parts of 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 ETo forecasts in combination with the precipitation forecasts could have provided early warning of recent severe drought events (e.g., 2002, 2004, 2009) that contributed to substantial food insecurity in the region.

Journal of Applied Meteorology and Climatology↗
USGS2016

Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa

The skill of North American multimodel ensemble (NMME) seasonal forecasts in East Africa (EA), which encompasses one of the most food and water insecure areas of the world, is evaluated using deterministic, categorical, and probabilistic evaluation methods. The skill is estimated for all three primary growing seasons: March–May (MAM), July–September (JAS), and October–December (OND). It is found that the precipitation forecast skill in this region is generally limited and statistically significant over only a small part of the domain. In the case of MAM (JAS) [OND] season it exceeds the skill of climatological forecasts in parts of equatorial EA (Northern Ethiopia) [equatorial EA] for up to 2 (5) [5] months lead. Temperature forecast skill is generally much higher than precipitation forecast skill (in terms of deterministic and probabilistic skill scores) and statistically significant over a majority of the region. Over the region as a whole, temperature forecasts also exhibit greater reliability than the precipitation forecasts. The NMME ensemble forecasts are found to be more skillful and reliable than the forecast from any individual model. The results also demonstrate that for some seasons (e.g. JAS), the predictability of precipitation signals varies and is higher during certain climate events (e.g. ENSO). Finally, potential room for improvement in forecast skill is identified in some models by comparing homogeneous predictability in individual NMME models with their respective forecast skill.

Climate Dynamics↗
USGS2015

Recent and possible future variations in the North American Monsoon

The dynamics and recent and possible future changes of the June–September rainfall associated with the North American Monsoon (NAM) are reviewed in this chapter. Our analysis as well as previous analyses of the trend in June–September precipitation from 1948 until 2010 indicate significant precipitation increases over New Mexico and the core NAM region, and significant precipitation decreases over southwest Mexico. The trends in June–September precipitation have been forced by anomalous cyclonic circulation centered at 15°N latitude over the eastern Pacific Ocean. The anomalous cyclonic circulation is responsible for changes in the flux of moisture and the divergence of moisture flux within the core NAM region. Future climate projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, as part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), support the observed analyses of a later shift in the monsoon season in the presence of increased greenhouse gas concentrations in the atmosphere under the RCP8.5 scenario. The CMIP5 models under the RCP8.5 scenario predict significant NAM-related rainfall decreases during June and July and predict significant NAM-related rainfall increases during September and October.

Book chapter↗
USGS2015

The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10

This chapter briefly reviews the complex climatological cycle of the East African monsoon system, paying special attention to its connection to the larger Indo-Pacific-Asian monsoon cycle. We examine the seasonal monsoon cycle, and briefly explore recent circulation changes. The spatial footprint of our analysis corresponds with the “Greater Horn of Africa” (GHA) region, extending from Tanzania in the south to Yemen and Sudan in the north. During boreal winter, when northeast trade winds flow across the northwest Indian Ocean and the equatorial moisture transports over the Indian Ocean exhibit strong westerly mean flows over the equatorial Indian Ocean, East African precipitation is limited to a few highland areas. As the Indian monsoon circulation transitions during boreal spring, the trade winds over the northwest Indian Ocean reverse, and East African moisture convergence supports the “long” rains. In boreal summer, the southwesterly Somali Jet intensifies over eastern Africa. Subsidence forms along the westward flank of this jet, shutting down precipitation over eastern portions of East Africa. In boreal fall, the Jet subsides, but easterly moisture transports support rainfall in limited regions of the eastern Horn of Africa. We use regressions with the trend mode of global sea surface temperatures to explore potential changes in the seasonal monsoon circulations. Significant reductions in total precipitable water are indicated in Kenya, Tanzania, Rwanda, Burundi, Uganda, Ethiopia, South Sudan, Sudan, and Yemen, with moisture transports broadly responding in ways that reinforce the climatological moisture transports over the Indian Ocean. Over Kenya, southern Ethiopia and Somalia, regressions with velocity potential indicate increased convergence aloft. Near the surface, this convergence appears to manifest as a surface high pressure system that modifies moisture transports in these countries as well as Uganda, Tanzania, Rwanda, and Burundi. An analysis of rainfall changes indicates significant declines in parts of Tanzania, Rwanda, Burundi, Uganda, Kenya, Somalia, Ethiopia, and Yemen.

Book chapter↗
USGS2015

The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.

Scientific Data↗
USGS2015

The forcing of monthly precipitation variability over Southwest Asia during the Boreal cold season

Southwest Asia, deemed as the region containing the countries of Afghanistan, Iran, Iraq and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during8 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. Here, we examine the inter-monthly 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), the El Nino-Southern Oscillation (ENSO) and the warming trend of SST (Trend). On the contrary, the precipitation variability during individual months of November-April are unrelated and are correlated with SST signatures that include PDV, ENSO and Trend in different combinations. Despite strong inter-monthly 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 waves on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean 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 than the forcing by baroclinic Rossby waves associated with tropically-forced-only modes of climate variability.

Journal of Climate↗
USGS2015

Temperature impacts on the water year 2014 drought in California

California is experiencing one of the worst droughts on record. Here we use a hydrological model and risk assessment framework to understand the influence of temperature on the water year (WY) 2014 drought in California and examine the probability that this drought would have been less severe if temperatures resembled the historical climatology. Our results indicate that temperature played an important role in exacerbating the WY 2014 drought severity. We found that if WY 2014 temperatures resembled the 1916–2012 climatology, there would have been at least an 86% chance that winter snow water equivalent and spring-summer soil moisture and runoff deficits would have been less severe than the observed conditions. We also report that the temperature forecast skill in California for the important seasons of winter and spring is negligible, beyond a lead-time of one month, which we postulate might hinder skillful drought prediction in California.

California↗
USGS2015

Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa

This paper examined the relationship between birth weight, precipitation, and temperature in 19 African countries. We matched recorded birth weights from Demographic and Health Surveys covering 1986 through 2010 with gridded monthly precipitation and temperature data derived from satellite and ground-based weather stations. Observed weather patterns during various stages of pregnancy were also used to examine the effect of temperature and precipitation on birth weight outcomes. In our empirical model we allowed the effect of weather factors to vary by the dominant food production strategy (livelihood zone) in a given region as well as by household wealth, mother's education and birth season. This allowed us to determine if certain populations are more or less vulnerable to unexpected weather changes after adjusting for known covariates. Finally we measured effect size by observing differences in birth weight outcomes in women who have one low birth weight experience and at least one healthy birth weight baby. The results indicated that climate does indeed impact birth weight and at a level comparable, in some cases, to the impact of increasing women's education or household electricity status.

Global Environmental Change↗
USGS2014

Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa

In this study we implement and evaluate a simple 'hybrid' forecast approach that uses constructed analogs (CA) to improve the National Multi-Model Ensemble's (NMME) March–April–May (MAM) precipitation forecasts over equatorial eastern Africa (hereafter referred to as EA, 2°S to 8°N and 36°E to 46°E). Due to recent declines in MAM rainfall, increases in population, land degradation, and limited technological advances, this region has become a recent epicenter of food insecurity. Timely and skillful precipitation forecasts for EA could help decision makers better manage their limited resources, mitigate socio-economic losses, and potentially save human lives. The 'hybrid approach' described in this study uses the CA method to translate dynamical precipitation and sea surface temperature (SST) forecasts over the Indian and Pacific Oceans (specifically 30°S to 30°N and 30°E to 270°E) into terrestrial MAM precipitation forecasts over the EA region. In doing so, this approach benefits from the post-1999 teleconnection that exists between precipitation and SSTs over the Indian and tropical Pacific Oceans (Indo-Pacific) and EA MAM rainfall. The coupled atmosphere-ocean dynamical forecasts used in this study were drawn from the NMME. We demonstrate that while the MAM precipitation forecasts (initialized in February) skill of the NMME models over the EA region itself is negligible, the ranked probability skill score of hybrid CA forecasts based on Indo-Pacific NMME precipitation and SST forecasts reach up to 0.45.

Environmental Research Letters↗
USGS2014

A seasonal agricultural drought forecast system for food-insecure regions of East Africa

The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011. To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993–2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall is critical for end-of-season outcomes. Finally we show that, in terms of forecasting spatial patterns of SM anomalies, the skill of this agricultural drought forecast system is generally greater (> 0.8 correlation) during drought years. This means that this system might be particularity useful for identifying the events that present the greatest risk to the region.

Hydrology and Earth System Sciences↗
USGS2014

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

In southern Ethiopia, Eastern Kenya, and southern Somalia poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009 and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers support disaster risk reduction while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we explore the dominant modes of East African rainfall variability, links between these modes and sea surface temperatures, and a simple index-based monitoring-prediction system suitable for drought early warning.

Hydrology and Earth System Sciences↗