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Chris Funk

Publications and source records attributed to Chris Funk.

At least 37 records · Page 2Linked to original sources
USGS2020

Drought early warning and forecasting

Drought risk management involves three pillars: drought early warning, drought vulnerability and risk assessment, and drought preparedness, mitigation, and response. This book collects in one place a description of all the key components of the first pillar, and describes strategies for fitting these pieces together. The best modern drought early warning systems incorporate and integrate a broad array of environmental information sources: weather station observations, satellite imagery, land surface and crop model simulations, and weather and climate model forecasts, and analyze this information in context-relevant ways that take into account exposure and vulnerability. Drought Early Warning and Forecasting: Theory and Practice assembles a comprehensive overview of these components, providing examples drawn from the Famine Early Warning Systems Network and the United States Drought Monitor. This book simultaneously addresses the physical, social, and information management aspects of drought early warning, and informs readers about the tools, techniques, and conceptual models required to effectively identify, predict, and communicate potential drought-related disasters. This book is a key text for postgraduate scientists and graduate and advanced undergraduate students in hydrology, geography, earth sciences, meteorology, climatology, and environmental sciences programs. Professionals dealing with disaster management and drought forecasting will also find this book beneficial to their work.

Book↗
USGS2019

Using out-of-sample yield forecast experiments to evaluate which earth observation products best indicate end of season maize yields

In East Africa, accurate grain yield predictions can help save lives and protect livelihoods. Regional grain yield forecasts can inform decisions regarding the availability and prices of key staples, food aid, and large humanitarian responses. Here, we use earth observation (EO) products to develop and evaluate subnational grain yield forecasts for 56 regions located in two severely food insecure countries: Kenya and Somalia. We identify, for a given region and time of year, which, if any, product is the best indicator for end-of-season maize yields. Our analysis seeks to inform a real-world situation in which analysts have access to multiple regularly updated EO data products, but predictive skill corresponding to each may vary across these regions and throughout the season. We find that the most accurate predictions can be made for high-producing areas, but that the relationship between production and forecast accuracy diminishes in areas with yields averaging greater than one metric ton per hectare. However, while forecast accuracy is highest in high production areas, in many of these regions, the forecast accuracy of models using EO products is not better than a set of baseline models that do not use EO products. Overall, we find that rainfall is the best indicator in low-producing regions and that other EO products work best in areas where yields are relatively consistent, but production is still limited by environmental factors.

Environmental Research Letters↗
USGS2019

On the use of indices to study extreme precipitation on sub-daily and daily timescales

While there are obstacles to the exchange of long-term high temporal resolution precipitation data, there have been few barriers to the exchange of so-called ‘indices’ which are derived from daily and sub-daily data and measure aspects of precipitation frequency, duration and intensity that could be used for the study of extremes. This paper outlines the history of the rationale and use of these indices, the types of indices that are frequently used and the advantages and pitfalls in analysing them. Moving forward, satellite precipitation products are now showing the potential to provide global climate indices to supplement existing products using longer-term in situ gauge records but we suggest that to advance this area differences between data products, limitations in satellite-based estimation processes, and inherent challenges of scale need to be better understood.

Environmental Research Letters↗
USGS2019

Exploring trends in wet-season precipitation and drought indices in wet, humid and dry regions

This study examines wet season droughts using eight products from the FROGS database. The study begins by evaluating wet season precipitation totals and wet day counts at seasonal and decadal time scales. While we find a high level of agreement among the products at a seasonal timescale, evaluations of 10-year variability indicate substantial non-stationary inter-product differences that make the assessment of low-frequency changes difficult, especially in data-sparse regions. Some products, however, appear more reliable than others on decadal time scales. Global time series of dry, middle, and wet region standardized precipitation index (SPI) time series indicate little coherent change. There is substantial coherence in year-to-year variations in these time series, for the better performing products, likely indicative of skill for monitoring variations at large spatial scales. During the wet season, the data do not appear to indicate wide spread global increases in precipitation, RefET or Standardized Precipitation Evapotranspiration Index (SPEI) values. Neither the precipitation, RefET or SPEI indicate a wide-spread regional shift towards more arid conditions. Focusing on SPEI values for dry regions during droughts, however, indicate substantial increases in dry region aridity when wet season precipitation is below normal. Dry region SPEI values during droughts have decreased by -0.2 since the 1990s. More detailed analysis in further studies will be needed to confirm this result. For wet regions, however, the majority of products appear to indicate increases in wet season precipitation, although many products perform poorly in these regions due to limited observation networks, and estimated increases vary substantially.

Environmental Research Letters↗
USGS2019

Identifying changing precipitation extremes in Sub-Saharan Africa with gauge and satellite products

Sparse gauge networks in Sub-Saharan Africa limit our ability to identify changing precipitation extremes with in situ observations. Given the potential for satellite and satellite-gauge precipitation products to help, we investigate how daily gridded gauge and satellite products compare for seven core climate change precipitation indices. According to a new gauge-only product, the Rainfall estimates on a Gridded Network (REGEN), there were notable changes in Sub-Saharan Africa precipitation characteristics between 1950 and 2013 in well-gauged areas. We examine these trends and how these vary for wet, intermediate, and dry areas. For a 31 year period of overlap we compare REGEN data, other gridded products, and three satellite products. Then for 1998-2013 we compare a set of twelve satellite products. Finally, we compare spatial patterns of 1983-2013 trends across all of Sub-Saharan Africa. Robust 1950-2013 trends indicate that in well-gauged areas extreme events became wetter, particularly in wet areas. Annual totals decreased due to fewer rain days. Since the 1980s were increases in average precipitation intensity and annual maximum 1-day totals. These trends only represent 15% of Sub-Saharan Africa, however, and only one tenth of the main wet areas. Unfortunately, gauge and satellite products do not provide consensus for wet area trends. A promising result for identifying regional changes is that numerous satellite products do well at interannual variations in precipitation totals and number of rain days- as well as some gauge-only products. Products perform less well for dry spell length and average intensity and worst for annual maximum 1-day totals. TRMM 3B42 and CHIRPS ranked highest for multiple indices. Several products have seemingly unrealistic trends outside of the well-gauged areas that may be due to influence of non-stationary systematic biases.

Environmental Research Letters↗
USGS2019

Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends

Droughts in Tanzania pose challenges to agriculture, water resources, and hydropower production, all of which impact livelihoods. Tanzania experienced below average precipitation during 1999-2014 during two important seasons: December to February (DJF) in the south and during March to June (MAMJ) in the northeast. We explore DJF and MAMJ precipitation in the areas with drying trends and examine their relationships with anomalous sea surface temperatures (SST) in the Indo-Pacific and corresponding circulation patterns. It is found that at seasonal time scales, precipitation in DJF and MAMJ trend areas appears inversely related to diabatic forcing in the equatorial Pacific. The dominant influence for droughts in DJF is from eastern Pacific SST while for droughts in MAMJ it is from West Pacific SST. A bivariate regression model with West Pacific and Niño3.4 region SST as predictors is found to recreate multidecadal DJF variability after the 1950s and the extreme drying in MAMJ during the 2000s. The regression model coefficients also indicate differential eastern vs. western Pacific forcing for DJF vs. MAMJ. Thus we suggest that recent La Niña-like conditions, characterized by an enhanced Pacific SST gradient due to cooling in the eastern Pacific and warming in the western Pacific, played a substantial role in Tanzania’s recent multi-season drying trends. SST change scenarios (difference between 2023-2037 and 2000-2014 means) based on CMIP5 projections and observed trends illustrate the uncertainty about future precipitation outcomes and also the potential implications of contrasting linkages to eastern vs. western Pacific SSTs. These scenarios are mainly optimistic for the DJF southern Tanzania trend area, because it appears dominated by Niño3.4 cooling at both seasonal and decadal time scales. Conversely, our scenarios are quite pessimistic for the MAMJ northeastern Tanzania trend area, because we find a dominant negative influence of warming West Pacific SST.

International Journal of Climate Change: Impacts a↗
USGS2019

Financing agricultural drought risk through ex-ante cash transfers

Despite advances in drought early warning systems, forecast information is rarely used for triggering and financing early actions, such as cash transfer. Scaling up cash transfer pay-outs , and overcoming the barriers to actions based on forecasts, requires an understanding of costs resulting from False Alarms, and the potential benefits associated with appropriate early interventions. On this study, we evaluate the potential cost-effectiveness of cash transfer responses, comparing the relative costs of ex-ante cash transfers during the maize growing season to ex-post cash transfers after harvesting in Kenya. For that, we developed a forecast model using Fast-and Frugal Trees that unravels early warning relationships between climate variability, vegetation coverage, and maize yields at multiple lead times. Results indicate that our models correctly forecast low maize yield events 85% of the time across the districts studied, some already six months before harvesting. The models’ performance improves towards the end of the growing season driven by a decrease of 39% in the probability of False Alarms. Overall, we show that timely cash transfers ex-ante to a disaster can often be more cost-effective than investing in ex-post expenditures. Our findings suggest that early response can yield significant cost savings, and can potentially increase the effectiveness of existing cash transfer systems.

Science of the Total Environment↗
USGS2019

Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security

On a planet with more than 7 billion people, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the US Agency for International Development's Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model and predict food insecurity. Here we provide an overview of FEWS NET's DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET's monitoring system, it draws from many disciplines - remote sensing, climate prediction, agro-climatic monitoring, and hydrologic modeling. Here we describe FEWS NET's multi-agency multi-disciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Mid-season droughts are monitored using multiple cutting-edge earth observing systems. Crop and hydrologic models can translate these observations into impacts. This information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

Bulletin of the American Meteorological Society↗
USGS2019

A high-resolution 1983-2016 Tmax climate data record based on InfraRed Temperatures and Stations by the Climate Hazard Center

Understanding the dynamics and physics of climate extremes will be a critical challenge for 21st century climate science. Increasing temperatures and saturation vapor pressures may exacerbate heat waves, droughts and precipitation extremes. Yet our ability to monitor temperature variations is limited and declining. Between 1983 and 2016 the number of observations in the CRU Tmax product declined precipitously (5,900→1,000); 1,000 poorly distributed measurements are not enough to resolve regional Tmax variations. Here we show that long (1983-near present) high resolution (0.05°), cloud-screened archives of geostationary satellite Thermal Infrared Red (TIR) observations, when combined with a dense set of ~15,000 station observations, can explain 23, 40, 30, 11% more variance than the CRU over the globe, South America, Africa, India and areas north of 50°N, with even greater levels of improvement over the 2011-2016 period (28, 45, 39, 52, 28%). Described here for the first time, the TIR Tmax algorithm uses sub-daily TIR distributions to screen out cloud contaminated observations, providing accurate (correlation≈0.8) gridded emission Tmax estimates. Blending these gridded fields with ~15,000 station observations provides a seamless, high-resolution source of accurate Tmax estimates that performs well in areas lacking dense in situ observations and even better where in situ observations are available. Cross-validation results indicates that the satellite-only, station-only and combined products all perform accurately (R≈0.8-0.9, mean absolute errors ≈0.8-1.0). Hence, the Climate Hazards center InfraRed Temperature with Stations (CHIRTSmax) data set should provide a valuable resource for climate change studies, climate extreme analyses, and early warning applications.

Journal of Climate↗
USGS2018

Validation of the CHIRPS satellite rainfall estimates over eastern Africa

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time-scales. The evaluation was done by comparing the satellite products with rain-gauge data from about 1,200 stations. The CHIRP and CHIRPS products were also compared with two similar operational satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product at dekadal and monthly time-scales, while TAMSAT performed better at the daily time-scale. The performance of the different satellite products exhibits high spatial variability with weak performances over coastal and mountainous regions.

Africa↗
USGS2018

Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts

Southern Africa (SA) and eastern Africa (EA) experienced a sequence of severe droughts in December–February (SA DJF) 2015–2016, October–December (EA OND) 2016 and March–April–May 2017 (EA MAM). This sequence contributed to severe food insecurity. While climate variability in these regions is very complex, the goal of this study is to analyse the role played by unusually warm Indo–Pacific SSTs, where unusual is defined as a 1‐in‐6 year event. We use observed sea‐surface temperatures (SST) and satellite–gauge rainfall observations, a 20‐member ensemble of Community Atmospheric Model version 5.1 simulations (CAM5), and a 40‐member ensemble of climate change simulations from the Community Earth Systems Model version 1 (CESM1) Large Ensemble Community Project (LENS) to explore climate conditions associated with warm events identified based on eastern and western Pacific SSTs. Our analysis suggests that strong El Niño's may be followed by warm western Pacific SST conditions, which can lead to conditions conducive to successive and potentially predictable droughts in SA DJF, EA OND and EA MAM. We show that different regions of warm SST are related to recent droughts—SA DJF: Niño 3.4; EA OND: western equatorial Pacific (WEP); and EA MAM: western North Pacific (WNP). For DJF and MAM, respectively, the CAM5 model driven with observed SST and the same model driven within a climate change experiment indicate that warmer El Niño's and WNP events produce more intense atmospheric responses, potentially associated with more severe droughts. OND climate seems to be strongly influenced by the Indian Ocean Dipole, which corresponds with some WEP events. Given global warming, we suggest that the extreme Niño 3.4 and west Pacific SST events responsible for 2015–2017 droughts are likely to reoccur, thus humanitarian agencies should prepare to predict and respond to multi‐year drought and substantial food insecurity in SA and EA.

Journal of the Royal Meteorological Society↗
USGS2018

Distinguishing Southern Africa precipitation response by strength of El Niño events and implications for decision-making

December–February precipitation in southern Africa during recent El Niño events is studied by distinguishing circulation and precipitation responses during strong and moderate-to-weak events. We find that while both strong and moderate-to-weak El Niño events tend to dry southern Africa, the pattern and magnitude of precipitation anomalies in the region are different, with strong El Niño events resulting in rainfall deficits often less than −0.88 standardized units and deficits of only about half that for the moderate-to-weak case. Additionally, the likelihood of southern Africa receiving less than climatologic precipitation is approximately 80% for strong El Niño events compared to just over 60% for moderate-to-weak El Niño. Strong El Niño events are found to substantially disrupt onshore moisture transports from the Indian Ocean and increase geopotential heights within the Angola Low. Since El Niño is the most predictable component of the climate system that influences southern Africa precipitation, the information provided by this assessment of the likelihood of dry conditions can serve to benefit early warning systems.

Environmental Research Letters↗
USGS2018

Assessing recovery and change in West Africa's rainfall regime from a 161-year record

The Sahel region is known for the multi-decadal occurrence of severe drought that commenced in the late 1960s. A still open question is whether or not the region's rainfall has returned to “normal.” This paper provides a compelling answer to that question by examining the longest and most comprehensive gauge series for the region ever published. It extends from 1854 to 2014 and is based on 602 gauge records. A comparative series for the Guinea Coast region to the south is also presented, as the two regions collectively provide insight into the long-term variability of the West African monsoon. In contrast to many previous studies, here the question of recovery and regime change is not restricted to the core of the Sahelian rainy season (July–September), but is separately discussed also for the coastal phase (April–May), transition phase (June), Sahelian phase (July–September) and the second transition phase (October–November) of the West African monsoon. These analyses suggest that full recovery from the droughts of the 1970s and 1980s has not occurred that a major change in the rainfall regime occurred around 1968 and that since that time large-scale teleconnections have also changed markedly. The shift post-1968 is evident in all phases of the monsoon except the coastal phase, in which a change to drier conditions occurred a decade later. Overall, recovery has been greater in the east than in the west, creating a change in the climatological east–west rainfall gradient. The drier post-1968 conditions appear to be associated with a general weakening of the intensity of the West African monsoon and only a small southwards displacement of the rainfall maximum. These changes have strong implications for the future of this region and for seasonal prediction.

International Journal of Climatology↗
USGS2018

Anthropogenic enhancement of moderate-to-strong El Niño events likely contributed to drought and poor harvests in southern Africa during 2016

In December–February (DJF) of 2015/16, a strong El Niño (Niño‑3.4 SST >29°C) contributed to a severe drought over southern Africa (SA; Funk et al. 2016). A 9-million ton cereal deficit resulted in 26 mil‑ lion people in need of humanitarian assistance (SADC 2016). While SA rainfall has a well-documented nega‑ tive teleconnection with Niño‑3.4 SSTs (Hoell et al. 2015, 2017; Jury et al. 1994; Lindesay 1988; Misra 2003; Nicholson and Entekhabi 1987; Nicholson and Kim 1997; Reason et al. 2000; Rocha and Simmonds 1997), the link between climate change and El Niño remains unclear (Christensen et al. 2013) due to the large natural variability of ENSO SSTs (Wittenberg 2009), uncertainties surrounding measurements and trends (Solomon and Newman 2012), intermodel differences in ENSO representation and feedbacks (Guilyardi et al. 2012; Kim et al. 2014), and difficulties associated with quantifying ENSO strength (Cai et al. 2015).

Bulletin of the American Meteorological Society↗
USGS2018

How will East African maize yields respond to climate change and can agricultural development mitigate this response?

We analyze the response of Kenyan maize yields to near-term climate change and explore potential mitigation options. We model county level yields as a function of rainfall and temperature during a period of increased regional warming and drying (1989–2008). We then do a counter factual analysis by comparing existing maize yields from 2000 to 2008 to what yields might have been if observed warming and drying trends had not occurred. We also examine maize yields based on projected 2026–2040 climate trends. Without the observed warming and drying trends, Eastern Kenya would have had an 8% increase in maize yields, which in turn would have led to a net production increase of 500,000 metric tons. In Western Kenya, the magnitude of change is higher but the relative changes in predicted values are smaller. If warming and drying trends continue, we expect future maize yields to decline by 11% in Eastern Kenya (vs. 7% in Western Kenya). We also examine whether these future losses might be offset through agricultural development. For that analysis, we use a household panel dataset (2000, 2005) with measurements of individual farm plot yields, inputs, and outputs. We find that under a scenario of aggressive adoption of hybrid seeds and fertilizer usage coupled with warming and drying trends, yields in Western Kenya might increase by 6% while those in Eastern Kenya could increase by 14%. This increase in yields might be larger if there is a corresponding increase in usage of drought-tolerant hybrids. However, wide prediction intervals across models highlight the uncertainty in these outcomes and scenarios.

Climatic Change↗
USGS2018

Rainfall over the African continent from the 19th through the 21st century

Most of the African continent is semi-arid and hence prone to extreme variations in rainfall from year to year. The extreme droughts that have plagued the Sahel and eastern Africa are particularly well known. This article uses a markedly expanded and updated rainfall data set to examine rainfall variability in 13 sectors that cover most of the continent. Annual rainfall is presented for each sector; the March-to-May and October–November seasons are also examined for equatorial sectors. In each case, the article includes the longest and most comprehensive precipitation gauge series ever published. All time series cover at least a century and most cover roughly one and one-half centuries or more. Although towards the end of the 20th century there was a widespread trend towards more arid conditions, few significant trends are evident over the entire period of record. The largest were downward trends in the Sahel and western sectors of North Africa. In those regions, an abrupt reduction in rainfall occurred around 1968, but a synchronous change occurred many other parts of Africa. A recovery did occur in the Sahel, but to varying degrees across the east-west expanse of the region. Noteworthy is that the west-to-east rainfall gradient across the region appears to have weakened in recent decades. For the continent as a whole, another change began in the 1980s decade, with more arid conditions persisting at the continental scale until early in the twenty-first century. No other such period of dry conditions occurred within the roughly one and one-half centuries evaluated here. A notable change also occurred at the seasonal level. During the period 1980 to 1998 rainfall during March-to-May was well below the long-term mean throughout most of the area from 20° N to 35° S. At the same time rainfall was above the long-term mean in most of eastern sectors within this latitude span, indicating a change in the seasonality of rainfall of a large part of Africa.

Global and Planetary Change↗
USGS2018

Attribution analysis of the Ethiopian drought of 2015

In northern and central Ethiopia, 2015 was a very dry year. Rainfall was only from one-half to three-quarters of the usual amount, with both the “belg” (February–May) and “kiremt” rains (June–September) affected. The timing of the rains that did fall was also erratic. Many crops failed, causing food shortages for many millions of people. The role of climate change in the probability of a drought like this is investigated, focusing on the large-scale precipitation deficit in February–September 2015 in northern and central Ethiopia. Using a gridded analysis that combines station data with satellite observations, it is estimated that the return period of this drought was more than 60 years (lower bound 95% confidence interval), with a most likely value of several hundred years. No trend is detected in the observations, but the large natural variability and short time series means large trends could go undetected in the observations. Two out of three large climate model ensembles that simulated rainfall reasonably well show no trend while the third shows an increased probability of drought. Taking the model spread into account the drought still cannot be clearly attributed to anthropogenic climate change, with the 95% confidence interval ranging from a probability decrease between preindustrial and today of a factor of 0.3 and an increase of a factor of 5 for a drought like this one or worse. A soil moisture dataset also shows a nonsignificant drying trend. According to ENSO correlations in the observations, the strong 2015 El Niño did increase the severity of the drought.

Journal of Climate↗