ALBERT

Description: Vertical profiles of aerosol extinction obtained with the CALIOP lidar onboard CALIPSO are used in conjunction with the GEOS-Chem chemical transport model and NOAA's HYSPLIT trajectory model to document three aerosol export events from East Asia to the Arctic in the year 2007. During each of these events CALIOP sampled the pollution plumes multiple times over periods of five to seven days. Midlatitude cyclones lifted the pollution to the free troposphere with net diabatic heating of ~5 °C day−1 and precipitation in this initial ascending stage. Rapid meridional transport to the Arctic took place at 3–7 km altitude, and was mediated by either a blocking high pressure system in the NW Pacific or a trough-ridge configuration. Once in the Arctic transport was nearly isentropic with slow subsidence and radiative cooling at a rate of 1–1.5 °C day−1. We find good agreement between modeled and observed plumes in terms of length, altitude, thickness and, within the measurement uncertainties, extinction coefficient. In one event the satellite algorithm misclassifies the aerosol layer as ice clouds as a result of the relatively high depolarization ratio (0.06), likely caused by a high dust component in the aerosol mixture. Using 500 hPa geopotential height anomalies for these three events along with eight other export events observed by CALIOP in 2007–2009, we develop a meteorological index that captures 40–60% of the variance of Asian transport events to the Arctic in winter and spring. Simulations with the GEOS-Chem model show that 6 major export events from Asia to the Arctic occur each year, on average. The maximum probability for such events is during March–June, with a secondary maximum in October–November. During these events, Asian pollution and dust aerosols account for 50–70% of the aerosol optical depth over the Siberian sector of the Arctic, compared to a mean background contribution of 33%.

Description: The largest uncertainty in the radiative forcing of climate change over the industrial era is that due to aerosols, a substantial fraction of which is the uncertainty associated with scattering and absorption of shortwave (solar) radiation by anthropogenic aerosols in cloud-free conditions (IPCC, 2001). Quantifying and reducing the uncertainty in aerosol influences on climate is critical to understanding climate change over the industrial period and to improving predictions of future climate change for assumed emission scenarios. Measurements of aerosol properties during major field campaigns in several regions of the globe during the past decade are contributing to an enhanced understanding of atmospheric aerosols and their effects on light scattering and climate. The present study, which focuses on three regions downwind of major urban/population centers (North Indian Ocean (NIO) during INDOEX, the Northwest Pacific Ocean (NWP) during ACE-Asia, and the Northwest Atlantic Ocean (NWA) during ICARTT), incorporates understanding gained from field observations of aerosol distributions and properties into calculations of perturbations in radiative fluxes due to these aerosols. This study evaluates the current state of observations and of two chemical transport models (STEM and MOZART). Measurements of burdens, extinction optical depth (AOD), and direct radiative effect of aerosols (DRE – change in radiative flux due to total aerosols) are used as measurement-model check points to assess uncertainties. In-situ measured and remotely sensed aerosol properties for each region (mixing state, mass scattering efficiency, single scattering albedo, and angular scattering properties and their dependences on relative humidity) are used as input parameters to two radiative transfer models (GFDL and University of Michigan) to constrain estimates of aerosol radiative effects, with uncertainties in each step propagated through the analysis. Constraining the radiative transfer calculations by observational inputs increases the clear-sky, 24-h averaged AOD (34±8%), top of atmosphere (TOA) DRE (32±12%), and TOA direct climate forcing of aerosols (DCF – change in radiative flux due to anthropogenic aerosols) (37±7%) relative to values obtained with "a priori" parameterizations of aerosol loadings and properties (GFDL RTM). The resulting constrained clear-sky TOA DCF is −3.3±0.47, −14±2.6, −6.4±2.1 Wm−2 for the NIO, NWP, and NWA, respectively. With the use of constrained quantities (extensive and intensive parameters) the calculated uncertainty in DCF was 25% less than the "structural uncertainties" used in the IPCC-2001 global estimates of direct aerosol climate forcing. Such comparisons with observations and resultant reductions in uncertainties are essential for improving and developing confidence in climate model calculations incorporating aerosol forcing.

Description: Aerosols affect the Earth's energy budget directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei and, thereby, affecting cloud properties. However, large uncertainties exist in current estimates of aerosol forcing because of incomplete knowledge concerning the distribution and the physical and chemical properties of aerosols as well as aerosol-cloud interactions. In recent years, a great deal of effort has gone into improving measurements and datasets. It is thus feasible to shift the estimates of aerosol forcing from largely model-based to increasingly measurement-based. Our goal is to assess current observational capabilities and identify uncertainties in the aerosol direct forcing through comparisons of different methods with independent sources of uncertainties. Here we assess the aerosol optical depth (τ), direct radiative effect (DRE) by natural and anthropogenic aerosols, and direct climate forcing (DCF) by anthropogenic aerosols, focusing on satellite and ground-based measurements supplemented by global chemical transport model (CTM) simulations. The multi-spectral MODIS measures global distributions of aerosol optical depth (τ) on a daily scale, with a high accuracy of ±0.03±0.05τ over ocean. The annual average τ is about 0.14 over global ocean, of which about 21%±7% is contributed by human activities, as estimated by MODIS fine-mode fraction. The multi-angle MISR derives an annual average AOD of 0.23 over global land with an uncertainty of ~20% or ±0.05. These high-accuracy aerosol products and broadband flux measurements from CERES make it feasible to obtain observational constraints for the aerosol direct effect, especially over global the ocean. A number of measurement-based approaches estimate the clear-sky DRE (on solar radiation) at the top-of-atmosphere (TOA) to be about -5.5±0.2 Wm-2 (median ± standard error from various methods) over the global ocean. Accounting for thin cirrus contamination of the satellite derived aerosol field will reduce the TOA DRE to -5.0 Wm-2. Because of a lack of measurements of aerosol absorption and difficulty in characterizing land surface reflection, estimates of DRE over land and at the ocean surface are currently realized through a combination of satellite retrievals, surface measurements, and model simulations, and are less constrained. Over the oceans the surface DRE is estimated to be -8.8±0.7 Wm-2. Over land, an integration of satellite retrievals and model simulations derives a DRE of -4.9±0.7 Wm-2 and -11.8±1.9 Wm-2 at the TOA and surface, respectively. CTM simulations derive a wide range of DRE estimates that on average are smaller than the measurement-based DRE by about 30-40%, even after accounting for thin cirrus and cloud contamination. A number of issues remain. Current estimates of the aerosol direct effect over land are poorly constrained. Uncertainties of DRE estimates are also larger on regional scales than on a global scale and large discrepancies exist between different approaches. The characterization of aerosol absorption and vertical distribution remains challenging. The aerosol direct effect in the thermal infrared range and in cloudy conditions remains relatively unexplored and quite uncertain, because of a lack of global systematic aerosol vertical profile measurements. A coordinated research strategy needs to be developed for integration and assimilation of satellite measurements into models to constrain model simulations. Enhanced measurement capabilities in the next few years and high-level scientific cooperation will further advance our knowledge.

Description: Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low resolution climate dynamics and high complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry–climate interactions.

Description: Most future projections forecast significant and ongoing climate change during the 21st century, but with the severity of impacts dependent on efforts to restrain or reorganise human activity to limit carbon dioxide (CO2) emissions. A major sink for atmospheric CO2, and a key source of biological resources, the World Ocean is widely anticipated to undergo profound physical and – via ocean acidification – chemical changes as direct and indirect results of these emissions. Given strong biophysical coupling, the marine biota is also expected to experience strong changes in response to this anthropogenic forcing. Here we examine the large-scale response of ocean biogeochemistry to climate and acidification impacts during the 21st century for Representative Concentration Pathways (RCPs) 2.6 and 8.5 using an intermediate complexity global ecosystem model, Medusa–2.0. The primary impact of future change lies in stratification-led declines in the availability of key nutrients in surface waters, which in turn leads to a global decrease (1990s vs. 2090s) in ocean productivity (−6.3%). This impact has knock-on consequences for the abundances of the low trophic level biogeochemical actors modelled by Medusa–2.0 (−5.8%), and these would be expected to similarly impact higher trophic level elements such as fisheries. Related impacts are found in the flux of organic material to seafloor communities (−40.7% at 1000 m), and in the volume of ocean suboxic zones (+12.5%). A sensitivity analysis removing an acidification feedback on calcification finds that change in this process significantly impacts benthic communities, suggesting that a better understanding of the OA-sensitivity of calcifying organisms, and their role in ballasting sinking organic carbon, may significantly improve forecasting of these ecosystems. For all processes, there is geographical variability in change, and changes are much more pronounced under RCP 8.5 than the RCP 2.6 scenario.

Description: Regime shifts have been reported in many marine ecosystems, and are often expressed as an abrupt change occurring in multiple physical and biological components of the system. In the Gulf of Alaska, a regime shift in the late 1970s was observed, indicated by an abrupt increase in sea surface temperature and major shifts in the catch of many fish species. This late 1970s regime shift in the Gulf of Alaska was followed by another shift in the late 1980s, not as pervasive as the 1977 shift, but which nevertheless did not return to the prior state. A thorough understanding of the extent and mechanisms leading to such regime shifts is challenged by data paucity in time and space. We investigate the ability of a suite of ocean biogeochemistry models of varying complexity to simulate regime shifts in the Gulf of Alaska by examining the presence of abrupt changes in time series of physical variables (sea surface temperature and mixed layer depth), nutrients and biological variables (chlorophyll, primary productivity and plankton biomass) using change-point analysis. Our study demonstrates that ocean biogeochemical models are capable of simulating the late 1970s shift, indicating an abrupt increase in sea surface temperature forcing followed by an abrupt decrease in nutrients and biological productivity. This predicted shift is consistent among all the models, although some of them exhibit an abrupt transition (i.e. a significant shift from one year to the next), whereas others simulate a smoother transition. Some models further suggest that the late 1980s shift was constrained by changes in mixed layer depth. Our study demonstrates that ocean biogeochemical can successfully simulate regime shifts in the Gulf of Alaska region, thereby providing better understanding of how changes in physical conditions are propagated from lower to upper trophic levels through bottom-up controls.

Description: A global general circulation model coupled to a simple six-compartment ecosystem model is used to study the extent to which global variability in primary and export production can be realistically predicted on the basis of advanced parameterizations of upper mixed layer physics, without recourse to introducing extra complexity in model biology. The ''K profile parameterization'' (KPP) scheme employed, combined with 6-hourly external forcing, is able to capture short-term periodic and episodic events such as diurnal cycling and storm-induced deepening. The model realistically reproduces various features of global ecosystem dynamics that have been problematic in previous global modelling studies, using a single generic parameter set. The realistic simulation of deep convection in the North Atlantic, and lack of it in the North Pacific and Southern Oceans, leads to good predictions of chlorophyll and primary production in these contrasting areas. Realistic levels of primary production are predicted in the oligotrophic gyres due to high frequency external forcing of the upper mixed layer (accompanying paper Popova et al., 2006) and novel parameterizations of zooplankton excretion. Good agreement is shown between model and observations at various JFOFS time series sites: BATS, KERFIX, Papa and station India. One exception is that the high zooplankton grazing rates required to maintain low chlorophyll in high-nutrient low-chlorophyll and oligotrophic systems lessened agreement between model and data in the northern North Atlantic, where mesozooplankton with lower grazing rates may be dominant. The model is therefore not globally robust in the sense that additional parameterizations were needed to realistically simulate ecosystem dynamics in the North Atlantic. Nevertheless, the work emphasises the need to pay particular attention to the parameterization of mixed layer physics in global ocean ecosystem modelling as a prerequisite to increasing the complexity of ecosystem models.

Description: The use of 6 h, daily, weekly and monthly atmospheric forcing resulted in dramatically different predictions of plankton productivity in a global 3-D coupled physical-biogeochemical model. Resolving the diurnal cycle of atmospheric variability by use of 6 h forcing, and hence also diurnal variability in UML depth, produced the largest difference, reducing predicted global primary and new production by 25% and 10% respectively relative to that predicted with daily and weekly forcing. This decrease varied regionally, being a 30% reduction in equatorial areas primarily because of increased light limitation resulting from deepening of the mixed layer overnight as well as enhanced storm activity, and 25% at moderate and high latitudes primarily due to increased grazing pressure resulting from late winter stratification events. Mini-blooms of phytoplankton and zooplankton occur in the model during these events, leading to zooplankton populations being sufficiently well developed to suppress the progress of phytoplankton blooms. A 10% increase in primary production was predicted in the peripheries of the oligotrophic gyres due to increased storm-induced nutrient supply end enhanced winter production during the short term stratification events that are resolved in the run forced by 6 h meteorological fields. By resolving the diurnal cycle, model performance was significantly improved with respect to several common problems: underestimated primary production in the oligotrophic gyres; overestimated primary production in the Southern Ocean; overestimated magnitude of the spring bloom in the subarctic Pacific Ocean, and overestimated primary production in equatorial areas. The result of using 6 h forcing on predicted ecosystem dynamics was profound, the effects persisting far beyond the hourly timescale, and having major consequences for predicted global and new production on an annual basis.

Description: A global general circulation model coupled to a simple six-compartment ecosystem model is used to study the extent to which global variability in primary and export production can be realistically predicted on the basis of advanced parameterizations of upper mixed layer physics, without recourse to introducing extra complexity in model biology. The "K profile parameterization" (KPP) scheme employed, combined with 6-hourly external forcing, is able to capture short-term periodic and episodic events such as diurnal cycling and storm-induced deepening. The model realistically reproduces various features of global ecosystem dynamics that have been problematic in previous global modelling studies, using a single generic parameter set. The realistic simulation of deep convection in the North Atlantic, and lack of it in the North Pacific and Southern Oceans, leads to good predictions of chlorophyll and primary production in these contrasting areas. Realistic levels of primary production are predicted in the oligotrophic gyres due to high frequency external forcing of the upper mixed layer (accompanying paper Popova et al., 2006) and novel parameterizations of zooplankton excretion. Good agreement is shown between model and observations at various JGOFS time series sites: BATS, KERFIX, Papa and HOT. One exception is the northern North Atlantic where lower grazing rates are needed, perhaps related to the dominance of mesozooplankton there. The model is therefore not globally robust in the sense that additional parameterizations are needed to realistically simulate ecosystem dynamics in the North Atlantic. Nevertheless, the work emphasises the need to pay particular attention to the parameterization of mixed layer physics in global ocean ecosystem modelling as a prerequisite to increasing the complexity of ecosystem models.

Description: The use of 6 h, daily, weekly and monthly atmospheric forcing resulted in dramatically different predictions of plankton productivity in a global 3-D coupled physical-biogeochemical model. Resolving the diurnal cycle of atmospheric variability by use of 6 h forcing, and hence also diurnal variability in UML depth, produced the largest difference, reducing predicted global primary and new production by 25% and 10% respectively relative to that predicted with daily and weekly forcing. This decrease varied regionally, being a 30% reduction in equatorial areas and 25% at moderate and high latitudes. A 10% increase in the primary production was seen in the peripheries of the oligotrophic gyres. By resolving the diurnal cycle, model performance was significantly improved with respect to several common problems: underestimated primary production in the oligotrophic gyres; overestimated primary production in the Southern Ocean; overestimated magnitude of the spring bloom in the subarctic Pacific Ocean, and overestimated primary production in equatorial areas. The result of using 6 h forcing on predicted ecosystem dynamics was profound, the effects persisting far beyond the hourly timescale, and having major consequences for predicted global and new production on an annual basis.