[1] Regional evapotranspiration (ET) can be estimated using diagnostic remote sensing models, generally based on principles of energy balance closure, or with spatially distributed prognostic models that simultaneously balance both energy and water budgets over landscapes using predictive equations for land surface temperature and moisture states. Each modeling approach has complementary advantages and disadvantages, and in combination they can be used to obtain more accurate ET estimates over a variety of land and climate conditions, particularly for areas with limited ground truth data. In this study, energy and water flux estimates from diagnostic Atmosphere-Land Exchange (ALEXI) and prognostic Noah land surface models are compared over the Nile River basin between 2007 and 2011. A second remote sensing data set, generated with Penman-Monteith approach as implemented in the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 ET product, is also included as a comparative technique. In general, spatial and temporal distributions of flux estimates from ALEXI and Noah are similar in regions where the climate is temperate and local rainfall is the primary source of water available for ET. However, the diagnostic ALEXI model is better able to retrieve ET signals not directly coupled with the local precipitation rates, for example, over irrigated agricultural areas or regions influenced by shallow water tables. These hydrologic features are not well represented by either Noah or MOD16. Evaluation of consistency between diagnostic and prognostic model estimates can provide useful information about relative product skill, particularly over regions where ground data are limited or nonexistent as in the Nile basin.

BackgroundSignificant and persistent racial and income disparities in birth outcomes exist in the US. The analyses in this manuscript examine whether adverse birth outcome time trends and associations between area-level variables and adverse birth outcomes differ by urban–rural status.MethodsAlabama births records were merged with ZIP code-level census measures of race, poverty, and rurality. B-splines were used to determine long-term preterm birth (PTB) and low birth weight (LBW) trends by rurality. Logistic regression models were used to examine differences in the relationships between ZIP code-level percent poverty or percent African-American with either PTB or LBW. Interactions with rurality were examined.ResultsPopulation dense areas had higher adverse birth outcome rates compared to other regions. For LBW, the disparity between population dense and other regions increased during the 1991–2005 time period, and the magnitude of the disparity was maintained through 2010. Overall PTB and LBW rates have decreased since 2006, except within isolated rural regions. The addition of individual-level socioeconomic or race risk factors greatly attenuated these geographical disparities, but isolated rural regions maintained increased odds of adverse birth outcomes. ZIP code-level percent poverty and percent African American both had significant relationships with adverse birth outcomes. Poverty associations remained significant in the most population-dense regions when models were adjusted for individual-level risk factors.ConclusionsPopulation dense urban areas have heightened rates of adverse birth outcomes. High-poverty African American areas have higher odds of adverse birth outcomes in urban versus rural regions. These results suggest there are urban-specific social or environmental factors increasing risk for adverse birth outcomes in underserved communities. On the other hand, trends in PTBs and LBWs suggest interventions that have decreased adverse birth outcomes elsewhere may not be reaching isolated rural areas.

The Urban Heat Island (UHI), the tendency for urban areas to be hotter than rural regions, represents a significant health concern in summer as urban populations are exposed to elevated temperatures. A number of studies suggest that the UHI increases during warmer conditions, however there has been no investigation of this for a large ensemble of cities. Here we compare urban and rural temperatures in 54 US cities for 2000-2015 and show that the intensity of the urban heat island, measured here as the differences in daily-minimum or daily-maximum temperatures between urban and rural stations or Δ, in fact tends to decrease with increasing temperature in most cities (38/54). This holds when investigating daily variability, heat extremes, and variability across climate zones and is primarily driven by changes in rural areas. We relate this change to large-scale or synoptic weather conditions, and find that the lowest Δ nights occur during moist weather conditions. We also find that warming cities have not experienced an increasing urban heat island effect.

We analyse rainfall extreme events in Ethiopia from 1979 to 2014 using the standardized precipitation index (SPI) and the Palmer drought severity index (PDSI) derived from both station and satellite‐based observation data sets. Causal mechanisms of extreme events are also discussed. Trend principal component (TPC), regression, wavelet and composite analyses are used to investigate the trend, frequency and inter/intra‐annual variability of extreme events (dryness/wetness of rainfall) over Ethiopia. All methods of analysis, applied to monthly mean data, show that the north and northwest regions of Ethiopia experienced frequent and more severe drought conditions centred at the year 1983/1984, a recovery in the middle of the study period and a return to moderate dry events in recent years. For the southern and southwestern regions, drought conditions have become more frequent and intense during the study period, particularly since ∼1997. Analysis at the seasonal scale shows that the observed drying trend over the south and southwestern regions of the country is dominated by the spring season, which corresponds to the season of maximum precipitation. No observed long‐term trend is found in the north, northwestern and central mountainous regions of the country. This contrast reflects differing climate sensitivities of these different portions of the country: the observed periodicity of dryness/wetness over the northern regions corresponds largely to ENSO variability in both the spring and summer rainy seasons, while the drying trend in the south and southwest is associated with Atlantic Ocean warming and sea surface temperature gradients across the western Pacific Ocean.

Nairobi, Kenya exhibits a wide variety of micro-climates and heterogeneous surfaces. Paved roads and high-rise buildings interspersed with low vegetation typify the central business district, while large neighborhoods of informal settlements or “slums” are characterized by dense, tin housing, little vegetation, and limited access to public utilities and services. To investigate how heat varies within Nairobi, we deployed a high density observation network in 2015/2016 to examine summertime temperature and humidity. We show how temperature, humidity and heat index differ in several informal settlements, including in Kibera, the largest slum neighborhood in Africa, and find that temperature and a thermal comfort index known colloquially as the heat index regularly exceed measurements at the Dagoretti observation station by several degrees Celsius. These temperatures are within the range of temperatures previously associated with mortality increases of several percent in youth and elderly populations in informal settlements. We relate these changes to surface properties such as satellite-derived albedo, vegetation indices, and elevation.