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Relational values are values of desirable relationships between people and nature and amongpeople (through nature). We report on the approach to capture relational values of nature’scontributions to people in the regional assessment for Europe and Central Asia of theIntergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES).We present a framework considering indicators along four relational value dimensions aboutpeople’s relationships with nature: security and sovereignty; health; equity and justice; andheritage, social identity and stewardship. The framework has been operationalized for threenature’s contributions to people (NCP): regulation of freshwater quality and quantity, foodand feed, and physical and psychological experiences derived from nature. We identify waysto empirically assess relational values of nature’s contributions to people at regional andcontinental scales with social-ecological indicators and proxies, ranging from biophysicalindicators to indicators that intersect socio-economic with biophysical data. We concludethat many of the identified indicators can be considered as useful proxies of relational valuesin a quantitative way. The analysis shows that relational values are essential to consider at thescience-policy interface as they are an important set of values that people hold about natureand that go beyond instrumental relations.

The purpose of this research is to learn how city governments, human services departments, and community organizations can reduce the impact to human health from summer heat waves in U.S. cities. The city of Chicago developed its Extreme Weather Operations Plan to reduce the impact of heat waves after the tragedy experienced in 1995 when over 500 people died from excessive heat exposure (heat stroke). Another U.S. city, Philadelphia, developed a heat warning system, the Philadelphia Hot Weather Health Watch/Warning System, which used climate data and human mortality data to identify hazardous air masses (heat waves) that have the potential to elevate human mortality within the city. For this research, the case studies conducted on Chicago and Philadelphia will focus on the meteorological characteristics of a past heat wave such as length of time (days/weeks), high temperatures, low temperatures, heat index, and dew point temperatures. Then for each case study the impact on human health will be assessed. This study will be looking at heat wave mortality from exposure to excessive heat as well as mortality from other illnesses further complicated by exposure to excessive heat. Finally, this study will focus on how the heat warning systems used in Chicago and Philadelphia were able to reduce the impact to human health during heat waves and how these systems can be improved and used in other U.S. cities.

Simultaneous and precursory signals in sea surface temperature (SST) associated with anomalous precipitation over North, Central and South America are examined with seasonal mean data. The relationships are documented for SST variations in three regions: the equatorial Pacific (NIÑO3), the tropical North Atlantic (NATL), and the tropical South Atlantic (SATL). These area definitions are based on the distributions of variance explained by the leading modes of SST variability in each ocean basin. The analyses reveal that when SSTs are warmer than average in the NIÑO3 region, increased rainfall in the Caribbean Islands and southern Central America occurs. Precipitation also increases over the central US while it decreases over portions of Columbia, Venezuela, Guyana, Suriname, and French Guiana as well as the Nordeste region of South America. When NATL SSTs are warmer than average, large areas of the north central US as well as northeast Brazil experience decreased precipitation. When changes in SATL SSTs are considered, positive correlations with precipitation over the Nordeste and subtropical plains regions of South America are highly significant. Several long-lead relationships between SST and anomalous precipitation are identified. Changes in NINO3 SST during boreal summer are significantly correlated with rainfall anomalies over northern South America and southern North America six months later. Similarly, changes in both NATL and SATL SSTs are found to precede inter-American precipitation anomalies by six to nine months.

We analyzed CO measurements in the upper troposphere and lower stratosphere via infrared spectroscopy using a Fourier Transform Infrared (FTIR) spectrometer that was flown aboard two aircraft, a NASA DC8 and NCAR Sabreliner. Measurements were made between 1978-1992. Measurements of stratospheric CO can aid in understanding transport in the lower stratosphere. Calculated reference spectra were generated to analyze the observed spectra produced by the spectrometer using standard temperature and mixing ratio profiles and molecular line parameters. Nonlinear least squares fitting were used to match calculated reference spectra with observed spectra. The CO amount in the best-fit reference spectrum was assigned to the observed spectrum. CO column was corrected to be the amount above the 200mb pressure surface because column varies rapidly with aircraft altitude. CO column was plotted against latitude and then divided into seasons to observe any seasonal variations. Higher columns occurred near the equator while lower columns occurred near the poles. This characteristic was consistent in the seasonal plots, indicating little seasonal variations. Higher CO column near the equator is explained by presence of tropospheric air that has a higher density of CO and CO entering the stratosphere at the equator. Lower CO column near the poles is due to presence of only stratospheric air that has less CO. The observed column was similar in both hemispheres near the poles, where the observation is wholly stratospheric, but asymmetric about 20 because of the large interhemispheric gradient in tropospheric CO.

Aerosols modify climate directly by reflecting incoming solar and absorbing outgoing longwave radiation and indirectly by altering the microphysical properties of clouds, influencing how clouds reflect solar radiation. If aerosols also modify the larger scale physical properties of clouds, this could cause changes in their radiative properties at are not accounted for in present day climate models. Using measurements of aerosol concentration (A) collected onboard the NCAR C130 during the Indian Ocean Experiment (INDOEX), clouds were classified as pristine (A1500cm⁻³). Then using nadir airborne lidar data, measured cloud top heights in polluted air masses were found to be 897m±190m, and in pristine are masses 1223m± 405m, a difference of only 27%. Statistics assembled on the geometric properties of the aerosol layers show that multiple aerosol layers occur more frequently in polluted regions than in transition regions, with virtually no discernible aerosol layers in pristine regions. It was also determined that when multiple layers are present, their uppermost layers are lower in height than when only one thick aerosol layer is present.

Several previous studies have established statistical relationships between tornadic weather and environmental conditions by associating severe weather reports with rawinsonde observations. Here, we seek (1) to determine weather similar relationships hold when severe weather reports are associated with gridded short -term numerical forecasts, and (2) to develop and demonstrate a probabilistic model to forecast the likelihood a thunderstorm will be tornadic. Severe weather reports and lightning network data from 1 January 1999 through 29 June 1999 were used to classifY the weather at a set of Rapid-Update Cycle (RUC-2) grid points into the mutually exclusive and collectively exhaustive events representing increasing severity to the weather. The events were no significant weather, thunderstorms, severe thunderstorms, or tornadoes. RUC-2 forecast convectively available potential energy (CAPE), helicity, and 0-6 km wind shear from these same dates were associated with this gridded classification 0 the weather. We generally found similar relationships between environmental parameters and storm severity as others have previously documented. Our Bayesian probabilistic model forecasts the likelihood of that a thunderstorm will be tornadic given a certain value of CAPE and helicity (or CAPE and wind shear). This model is shown to do a reasonable job of locating high-threat areas many hours in advance ofthe severe weather and may be of use as a forecast tool.

Supplemental material, sj-pdf-1-pul-10.1177_2045894020922810 for Apoptosis signal-regulating kinase 1 inhibition in in vivo and in vitro models of pulmonary hypertension by Kathryn S. Wilson, Hanna Buist, Kornelija Suveizdyte, John T. Liles, Grant R. Budas, Colin Hughes, Margaret R. MacLean, Martin Johnson, Alistair C. Church, Andrew J. Peacock and David J. Welsh in Pulmonary Circulation