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Chris Funk

Publications and source records attributed to Chris Funk.

64 records · Page 4Linked to original sources
USGS2011

The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

International Journal of Climatology↗
USGS2011

Effects of temperature changes on maize production in Mozambique

We examined intraseasonal changes in maize phenology and heat stress exposure over the 1979-2008 period, using Mozambique meteorological station data and maize growth requirements in a growing degree-day model. Identifying historical effects of warming on maize growth is particularly important in Mozambique because national food security is highly dependent on domestic food production, most of which is grown in already warm to hot environments. Warming temperatures speed plant development, shortening the length of growth periods necessary for optimum plant and grain size. This faster phenological development also alters the timing of maximum plant water demand. In hot growing environments, temperature increases during maize pollination threaten to make midseason crop failure the norm. In addition to creating a harsher thermal environment, we find that early season temperature increases have caused the maize reproductive period to start earlier, increasing the risk of heat and water stress. Declines in time to maize maturation suggest that, independent of effects to water availability, yield potential is becoming increasingly limited by warming itself. Regional variations in effects are a function of the timing and magnitude of temperature increases and growing season characteristics. Continuation of current climatic trends could induce substantial yield losses in some locations. Farmers could avoid some losses through simple changes to planting dates and maize varietal types.

Climate Research↗
USGS2010

Exploring the correlation between Southern Africa NDVI and Pacific sea surface temperatures: Results for the 1998 maize growing season

Several studies have identified statistically significant correlations between Pacific sea surface temperature anomalies and NDVI anomalies in Southern Africa. The potential predictive value of the relationship was explored for the 1998 maize growing season. Cross-validation techniques suggested a more useful relationship for regions of wet anomaly than for regions of dry anomaly. Observed 1998 NDVI anomaly patterns were consistent with this result. Wet anomalies were observed as expected, but wide areas of expected dry anomalies exhibited average or above-average greeness.

International Journal of Remote Sensing↗
USGS2009

Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe

For thirty years, simple crop water balance models have been used by the early warning community to monitor agricultural drought. These models estimate and accumulate actual crop evapotranspiration, evaluating environmental conditions based on crop water requirements. Unlike seasonal rainfall totals, these models take into account the phenology of the crop, emphasizing conditions during the peak grain filling phase of crop growth. In this paper we describe an analogous metric of crop performance based on time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) imagery. A special temporal filter is used to screen for cloud contamination. Regional NDVI time series are then composited for cultivated areas, and adjusted temporally according to the timing of the rainy season. This adjustment standardizes the NDVI response vis-??-vis the expected phenological response of maize. A national time series index is then created by taking the cropped-area weighted average of the regional series. This national time series provides an effective summary of vegetation response in agricultural areas, and allows for the identification of NDVI green-up during grain filling. Onset-adjusted NDVI values following the grain filling period are well correlated with U.S. Department of Agriculture production figures, possess desirable linear characteristics, and perform better than more common indices such as maximum seasonal NDVI or seasonally averaged NDVI. Thus, just as appropriately calibrated crop water balance models can provide more information than seasonal rainfall totals, the appropriate agro-phenological filtering of NDVI can improve the utility and accuracy of space-based agricultural monitoring.

Remote Sensing of Environment↗
USGS2009

New satellite observations and rainfall forecasts help provide earlier warning of African drought

The poor nations of sub-Saharan Africa face a constant struggle against weather and climate. The outcome of that struggle profoundly influences these nations’ economic growth, health, and social stability. Advances in climate monitoring and forecasting can help African nations and international aid organizations reduce the impact of these natural hazards. Satellites play a crucial role in this effort as they enable scientists to track climate conditions over data-sparse land and ocean areas. In this article, I discuss how a multi-organizational group of scientists use satellite data and statistical forecasts to provide earlier and more accurate early warning of potential drought conditions. We frame our discussion in a specific, timely context—that of probable dramatic food insecurity in Zimbabwe, Eastern Kenya, and Somalia. As this article was being prepared in mid-December, very warm conditions in the Indian Ocean appear likely to produce below normal December–January–February rainfall in both Eastern Kenya/Somalia and Zimbabwe.

Earth Observer↗
USGS2007

Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

Conference Paper↗
USGS2005

Climate science and famine early warning

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Philosophical Transactions of the Royal Society B:↗
USGS2005

Recent drought tendencies in Ethiopia and equatorial-subtropical eastern Africa

This report presents an analysis of Ethiopian rainfall from 1960 through 2004, based on 186 gauges in Ethiopia and 373 gauges from surrounding countriesi. Substantial post1997 declines in March-September rainfall have been observed in the northeast, southeast and southwestern portions of the country, a result corroborated by several independent data sourcesii. The observed rainfall reductions have been accompanied by an increase in millions needing food aid (Figure 1). The greatest percent decrease has occurred during the Belg (March-May) season, though Kiremt (June-September) rains have also diminished in many areas. This recent dryness may be linked to a warming tendency in the southern Indian Oceaniii, and is likely to impact densely populated and/or water-insecure regions of southern and eastern Ethiopia. These areas face declines in rainfall and increasing demands on land, water and agriculture. Recent dryness, dropping coffee prices, rising population and land degradation combine to create mounting destitution that must be countered with innovative planning and policiesiv. This report is organized as follows. Section 1 provides context for our results by summarizing recent trends in food aid, precipitation and the regional climate. Section 2 quantifies the water availability situation by analyzing potentially available runoff. Section 3 describes the results of our historical rainfall analysis. Section 4 relates the observed rainfall variations to circulation and sea surface temperature patterns in the Indian and Pacific Oceans. Section 5 briefly summarizes our results.

Equatorial-subtropical Africa↗
USGS2003

Estimating Meher crop production using rainfall in the 'Long Cycle' region of Ethiopia

Meher season crop production is well correlated with April-May rainfall in the Ethiopian 'long cycle' crop growing region. This relationship is used to estimate 2003 Meher small farmer gross production at 87 =B1 10 million quintals (8.7 million MT 2 =B1 1 million MT) of cereals, pulses and other crops, using data from the Central Statistical Authority (CSA). Assuming recent levels of commercial and food aid imports, Belg production and population growth, this estimate will produce a food deficit of about 23 million quintals (2.3 million MT) for 2003-04, smaller than the one experienced during 2002-03 (34 million Qt, or 3.4 million MT), but similar to the deficit experienced in 1997-98. A long-term negative rainfall trend in the southwestern highlands may be aggravating the situation. Increasing food requirements and decreasing precipitation point toward chronic food shortages in the near future.

FEWS NET Special Report↗