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The Southwestern U.S. has been in a megadrought for the past two decades, stressing vegetation across the region and leading to poor forage conditions on rangelands. How has human‐induced climate change affected air temperatures and atmospheric evaporative demand in the greater Four Corners region of the Southwest, and what have the corresponding impacts been to vegetative productivity? We address this question via a multi‐step climate change detection and attribution analysis. We first relate evaporative demand (quantified by Vapor Pressure Deficit, or VPD) and precipitation to the Normalized Difference Vegetation Index (NDVI) in six unique plant‐precipitation zones. VPD is strongly negatively related to NDVI, and the strength of this relation is similar in magnitude to precipitation. We then use a large ensemble of climate change simulations to estimate the magnitude of VPD increases attributable to human‐induced climate change. We find that modest increases in air temperatures have led to large increases in VPD, with the influence of climate change about twice the inter‐annual standard deviation by 2020. Finally, we estimate the reductions in NDVI due to increased VPD and present the reductions in terms of total annual Aboveground Net Primary Productivity. We conclude that human‐induced warming has roughly doubled the magnitude of recent vegetation deficits, especially in mid‐precipitation areas (receiving 250–500 mm of precipitation annually), concentrated in New Mexico. These results indicate that increased temperatures from human‐caused climate change are having persistent and damaging impacts on vegetation productivity, with significant implications for ranchers and other land users in the region. Plain Language Summary: Numerous communities in the Southwestern U.S. depend on rangelands to support their livelihoods. As air temperatures rise in this semi‐arid environment, increased atmospheric evaporative demand stresses grasses and shrubs, which are important forage sources for livestock and other animals. Here, we show that human‐induced temperature increases have already driven substantial increases in atmospheric evaporative demand, especially in the hottest and driest areas of the region. We also show that these increases in evaporative demand have contributed to large and rapidly increasing reductions in rangeland productivity, with the greatest sensitivity in areas receiving moderate amounts of precipitation. While precipitation deficits are a major driver of recent vegetation deficits, climate change‐induced warming has also magnified the impact of droughts, often doubling the magnitude of productivity deficits. Our findings indicate that increased temperatures from human‐caused climate change have had and will have an increasingly damaging effect on rangeland vegetation, with large implications for both local ecosystems and communities that depend on southwestern rangeland resources. Key Points: Climate change‐enhanced Vapor Pressure Deficits (VPD) are negatively impacting vegetation productivity on Southwestern U.S. rangelandsRelatively modest temperature increases have roughly doubled the magnitude of vegetation productivity deficits in recent yearsThe largest impacts are concentrated in New Mexico [ABSTRACT FROM AUTHOR]

During 1999–2014, Tanzania experienced below average precipitation in 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 (SSTs) in the Indo‐Pacific and corresponding circulation patterns. At seasonal time scales, precipitation in DJF and MAMJ trend areas appears inversely related to diabatic forcing in the equatorial Pacific. Dominant influence for droughts in DJF is eastern Pacific SST while for droughts in MAMJ it is 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 versus western Pacific forcing for DJF versus 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 of future precipitation outcomes, as well as the potential implications of contrasting linkages to eastern versus 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. [ABSTRACT FROM AUTHOR]

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. Southern and eastern Africa experienced a sequence of severe droughts and food insecurity in 2015–2017. This study analyses how unusually warm eastern Pacific (Niño 3.4) and western Pacific (Western V) sea‐surface temperatures contributed to large‐scale modulations of the Walker Circulation, increases in diabatic forcing, and potential opportunities for prediction. El Niño events and South African droughts tend to be followed by western Pacific warming and East African drought. Climate change may be increasing the frequency of these warm events. [ABSTRACT FROM AUTHOR]

• Women face unique risks associated with food insecurity and climate change. • Changing childbearing may be an explicit livelihood strategy. • Women respond to growing season conditions by adjusting fertility behaviors. • Ensuring availability of diverse family planning services is a priority. Agricultural production and household food security are hypothesized to play a critical role connecting climate change to downstream effects on women's health, especially in communities dependent on rainfed agriculture. Seasonal variability in agriculture strains food and income resources and makes it a challenging time for households to manage a pregnancy or afford a new child. Yet, there are few direct assessments of the role locally varying agricultural quality plays on women's health, especially reproductive health. In this paper we build on and integrate ideas from past studies focused on climate change and growing season quality in low-income countries with those on reproductive health to examine how variation in local seasonal agricultural quality relates to childbearing goals and family planning use in three countries in sub-Saharan Africa: Burkina Faso, Kenya, and Uganda. We use rich, spatially referenced data from the Performance Monitoring for Action (PMA) individual surveys with detailed information on childbearing preferences and family planning decisions. Building on recent advances in remote monitoring of seasonal agriculture, we construct multiple vegetation measures capturing different dimensions of growing season conditions across varying time frames. Results for the Kenya sample indicate that if the recent growing season is better a woman is more likely to want a child in the future. In Uganda, when the growing season conditions are better, women prefer to shorten the time until their next birth and are also more likely to discontinue using family planning. Additional analyses reveal the importance of education and birth spacing in moderating these findings. Overall, our findings suggest that, in some settings, women strategically respond to growing season conditions by adjusting fertility aspirations or family planning use. This study also highlights the importance of operationalizing agriculture in nuanced ways that align with women's lives to better understand how women are impacted by and respond to seasonal climate conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA), Soil Moisture and Ocean Salinity (SMOS) and NASA’s Soil Moisture Active Passive (SMAP); however, these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we evaluate the quality of a 30+ year time series of merged active–passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM) over East Africa. Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we find substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies are well correlated ( R > 0.5) with modeled soil moisture, and in some regions, NDVI. We use pixel-wise correlation analysis and qualitative comparisons of seasonal maps and time series to show that remotely sensed soil moisture can inform remote drought monitoring that has traditionally relied on rainfall and NDVI in moderately vegetated regions. [ABSTRACT FROM AUTHOR]