ALBERT

Description: Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

Description: Having a common framework for early action to cope with complex disasters can make it easier for authorities and other stakeholders, including populations at risk, to understand the full spectrum of secondary and tertiary effects and thus where to focus preparedness efforts, and how best to provide more targeted warnings and response services. Meteorological and hydrological services world-wide have developed and implemented Multi-Hazard Early Warning Systems (MHEWS) for weather and climate related hazards that are now being expanded and transitioned towards Multi-Hazard Impact-based Early Warning Systems (MHIEWS). While it is still early days it is becoming clear that there are useful lessons from this approach in the COVID-19 global pandemic, and some valuable insight to be gained in risk communication, risk analysis and monitoring methodologies and approaches. The ability to understand and respond effectively to warnings through appropriate behaviours and actions is central to resilient societies and communities. By avoiding physical, societal and economic harm to the greatest extent possible, recovery from a hazard is likely to be faster, less costly and more complete. MHIEWS can be a common approach for all hazards and therefore more likely to become a trusted tool that everyone can understand and use as a basic element of their national disaster risk management system. The interconnectedness of hazards and their impacts is a strong motivator for a common approach. One of the lessons from the COVID-19 pandemic and extreme weather events is the need to understand the vulnerability of individuals, communities and societies so as to provide reliable, targeted guidance and warnings and the willingness and capacity to prepare for a reasonable worst-case scenario based on informed long-term planning. Meteorology and hydrology are making good progress in this direction and the process can be readily applied to health and other sectors.

Description: Biomass burning is a large source of uncontrolled air pollutants, including particulate matter (i.e., PM2.5), black carbon (BC), volatile organic compounds (VOCs), and carbon monoxide (CO), which have significant effects on air quality, human health, and climate. Measurements of PM2.5, BC, and CO made at the Yale Coastal Field Station in Guilford, CT, and five other sites in the metropolitan New York City (NYC) area indicate long-distance transport of pollutants from wildfires and other biomass burning to surface-level sites in the region. Here, we examine two such events occurring on 16–17 and 27–29 August 2018. In addition to regionally consistent enhancements in the surface concentrations of gases and particulates associated with biomass burning, satellite imagery confirms the presence of smoke plumes in the NYC–Connecticut region during these events. Back-trajectory modeling indicates that air masses arriving at surface-level sites in coastal Connecticut on 16–17 August passed over the western coast of Canada, near multiple large wildfires. In contrast, air parcels arriving on 27–29 August passed over active fires in the southeastern United States. The results of this study demonstrate that biomass burning events throughout the US and Canada (at times more than 4000 km away), which are increasing in frequency, impact surface-level air quality beyond regional scales, including in NYC and the northeastern US.

Description: Occupying about 14 % of the world's surface, the Southern Ocean plays a fundamental role in ocean and atmosphere circulation, carbon cycling and Antarctic ice-sheet dynamics. Unfortunately, high interannual variability and a dearth of instrumental observations before the 1950s limits our understanding of how marine–atmosphere–ice domains interact on multi-decadal timescales and the impact of anthropogenic forcing. Here we integrate climate-sensitive tree growth with ocean and atmospheric observations on southwest Pacific subantarctic islands that lie at the boundary of polar and subtropical climates (52–54° S). Our annually resolved temperature reconstruction captures regional change since the 1870s and demonstrates a significant increase in variability from the 1940s, a phenomenon predating the observational record. Climate reanalysis and modelling show a parallel change in tropical Pacific sea surface temperatures that generate an atmospheric Rossby wave train which propagates across a large part of the Southern Hemisphere during the austral spring and summer. Our results suggest that modern observed high interannual variability was established across the mid-twentieth century, and that the influence of contemporary equatorial Pacific temperatures may now be a permanent feature across the mid- to high latitudes.

Description: The International Submillimetre Airborne Radiometer (ISMAR) has been developed as an airborne demonstrator for the Ice Cloud Imager (ICI) that will be launched on board the next generation of European polar-orbiting weather satellites in the 2020s. It currently has 15 channels at frequencies between 118 and 664 GHz which are sensitive to scattering by cloud ice, and additional channels at 874 GHz are being developed. This paper presents an overview of ISMAR and describes the algorithms used for calibration. The main sources of bias in the measurements are evaluated, as well as the radiometric sensitivity in different measurement scenarios. It is shown that for downward views from high altitude, representative of a satellite viewing geometry, the bias in most channels is less than ±1 K and the NEΔT is less than 2 K, with many channels having an NEΔT less than 1 K. In-flight calibration accuracy is also evaluated by comparison of high-altitude zenith views with radiative-transfer simulations.

Description: Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere–biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index–rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian–Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño–Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

Description: Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the Level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP's other radiometric calibration procedures – i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime – depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30–34 km to the upper possible signal acquisition range of 36–39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. Additionally, an enhanced strategy for filtering the radiation-induced noise from high-energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), model. An aerosol scattering ratio of 1.01±0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2–3 % lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) are reduced from 3.6 %±2.2 % in the version 3 data set to 1.6 %±2.4 % in the version 4 release.

Description: The datasets described here bring together quality-controlled seawater temperature measurements, from over 130 years of Departmental government-funded marine science investigations in the UK (United Kingdom). Since before the foundation of a Marine Biological Association fisheries laboratory in 1902 and through subsequent evolutions as the Directorate of Fisheries Research and the current Centre for Environment Fisheries & Aquaculture Science, UK Government marine scientists and observers have been collecting seawater temperature data as part of oceanographic, chemical, biological, radiological, and other policy driven research and observation programmes in UK waters. These datasets start with a few tens of records per year, rise to hundreds from the early 1900s, thousands by 1959, hundreds of thousands by the 1980s, peaking with 〉 1 million for some years from 2000 onwards. The data source systems vary from time series at coastal monitoring stations or offshore platforms (buoys), through repeated research cruises or opportunistic sampling from ferry routes, to temperature extracts from CTD (Conductivity Temperature Depth) profiles, oceanographic, fishery and plankton tows, and data collected from recreational scuba divers or electronic devices attached to marine animals. The datasets described have not been included in previous seawater temperature collation exercises (e.g. International Comprehensive Ocean-Atmosphere Data Set, Met Office Hadley Centre Sea Surface Temperature data set, Centennial in situ Observation-Based Estimate Sea Surface Temperature data), although some summary data reside in the British Oceanographic Data Centre (BODC) archive, the Marine Environment Monitoring and Assessment National (MERMAN) database and the International Council for the Exploration of the Seas (ICES) Data Centre. We envisage the data primarily providing a biologically and ecosystem-relevant context for regional assessments of changing hydrological conditions around the British Isles, although cross matching with satellite derived data for surface temperatures at specific times and in specific areas is another area where the data could be of value (see e.g. Smit et al., 2013). Maps are provided indicating geographical coverage which is generally within and around UK Continental Shelf area, but occasionally extending north from Labrador and Greenland, to east of Svalbard, and southward to the Bay of Biscay. Example potential uses of the data are described using plots of data in four selected groups of 4 ICES Rectangles covering areas of particular fisheries interest. The full dataset enables extensive data synthesis, for example in the southern North Sea, where issues of spatial and numerical bias from a data source are explored. The full dataset also facilitates the construction of long-term temperature time series and an examination of changes in the phenology (seasonal timing) of ecosystem processes. This is done for a wide geographic area with an exploration of the limitations of data coverage over long periods. Throughout, we highlight and explore potential issues around the simple combination of data from the diverse and disparate sources collated here. The datasets are available on the Cefas Data Hub (https://www.cefas.co.uk/cefas-data-hub/).

Description: Advances in understanding and model representation of plant and ecosystem responses to rising temperature have typically required temperature manipulation of research plots, particularly when considering warming scenarios that exceed current climate envelopes. In remote or logistically challenging locations, passive warming using solar radiation is often the only viable approach for temperature manipulation. However, current passive warming approaches are only able to elevate the mean daily air temperature by  ∼  1.5 °C. Motivated by our need to understand temperature acclimation in the Arctic, where warming has been markedly greater than the global average and where future warming is projected to be  ∼  2–3 °C by the middle of the century; we have developed an alternative approach to passive warming. Our zero-power warming (ZPW) chamber requires no electrical power for fully autonomous operation. It uses a novel system of internal and external heat exchangers that allow differential actuation of pistons in coupled cylinders to control chamber venting. This enables the ZPW chamber venting to respond to the difference between the external and internal air temperatures, thereby increasing the potential for warming and eliminating the risk of overheating. During the thaw season on the coastal tundra of northern Alaska our ZPW chamber was able to elevate the mean daily air temperature 2.6 °C above ambient, double the warming achieved by an adjacent passively warmed control chamber that lacked our hydraulic system. We describe the construction, evaluation and performance of our ZPW chamber and discuss the impact of potential artefacts associated with the design and its operation on the Arctic tundra. The approach we describe is highly flexible and tunable, enabling customization for use in many different environments where significantly greater temperature manipulation than that possible with existing passive warming approaches is desired.

Description: Advances in understanding and model representation of plant and ecosystem responses to rising temperature have typically required temperature manipulation of research plots, particularly when considering warming scenarios that exceed current climate envelopes. In remote or logistically challenging locations, passive warming using solar radiation is often the only viable approach for temperature manipulation. However, current passive warming approaches are only able to elevate the mean daily air temperature by ~ 1.5 °C. Motivated by our need to understand temperature acclimation in the Arctic, where warming has been markedly greater than the global average and where future warming is projected to be ~ 2–3 °C by the middle of the century; we have developed an alternative approach to passive warming. Our Zero Power Warming (ZPW) chamber requires no electrical power for fully autonomous operation. It uses a novel system of internal and external heat exchangers that allow differential actuation of pistons in coupled cylinders to control chamber venting. This enables the ZPW chamber venting to respond to the difference between the external and internal air temperatures, thereby increasing the potential for warming and eliminating the risk of overheating. On the coastal tundra of northern Alaska our ZPW chamber was able to elevate the mean daily air temperature 2.6 °C above ambient, double the warming achieved by an adjacent passively warmed control chamber that lacked our hydraulic system. We describe the construction, evaluation and performance of our ZPW chamber and discuss the impact of potential artefacts associated with the design and its operation on the Arctic tundra. The approach we describe is highly flexible and tuneable enabling customization for use in many different environments where significantly greater temperature manipulation than that possible with existing passive warming approaches is desired.