ALBERT

Description: Two feature-based verification methods, thus far only used for the diagnostic evaluation of atmospheric models, have been applied to compare ∼7 km resolution pre-operational analyses of chlorophyll-a (Chl-a) concentrations to a 1 km gridded satellite-derived Chl-a concentration product. The aim of this study was to assess the value of applying such methods to ocean models. Chl-a bloom objects were identified in both data sets for the 2019 bloom season (1 March to 31 July). These bloom objects were analysed as discrete (2-D) spatial features, but also as space–time (3-D) features, providing the means of defining the onset, duration and demise of distinct bloom episodes and the season as a whole. The new feature-based verification methods help reveal that the model analyses are not able to represent small coastal bloom objects, given the coarser definition of the coastline, also wrongly producing more bloom objects in deeper Atlantic waters. Model analyses' concentrations are somewhat higher overall. The bias manifests itself in the size of the model analysis bloom objects, which tend to be larger than the satellite-derived bloom objects. The onset of the bloom season is delayed by 26 d in the model analyses, but the season also persists for another month beyond the diagnosed end. The season was diagnosed to be 119 d long in the model analyses, compared to 117 d from the satellite product. Geographically, the model analyses and satellite-derived bloom objects do not necessarily exist in a specific location at the same time and only overlap occasionally.

Description: Non-Gaussian forecast error is a challenge for ensemble-based data assimilation (DA), particularly for more nonlinear convective dynamics. In this study, we investigate the degree of the non-Gaussianity of forecast error distributions at 1 km resolution using a 1000-member ensemble Kalman filter, and how it is affected by the DA update frequency and observation number. Regional numerical weather prediction experiments are performed with the SCALE (Scalable Computing for Advanced Library and Environment) model and the LETKF (local ensemble transform Kalman filter) assimilating phased array radar observations every 30 s. The results show that non-Gaussianity develops rapidly within convective clouds and is sensitive to the DA frequency and the number of assimilated observations. The non-Gaussianity is reduced by up to 40 % when the assimilation window is shortened from 5 min to 30 s, particularly for vertical velocity and radar reflectivity.

Description: The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation–environmental response function (NS–ERF) approach to observing system simulation experiments that aids surface–atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS–ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72 h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2 h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS–ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS–ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases.

Description: This paper presents a new technique to derive thermospheric temperature from space-based disk observations of far ultraviolet airglow. The technique, guided by findings from principal component analysis of synthetic daytime Lyman–Birge–Hopfield (LBH) disk emissions, uses a ratio of the emissions in two spectral channels that together span the LBH (2,0) band to determine the change in band shape with respect to a change in the rotational temperature of N2. The two-channel-ratio approach limits representativeness and measurement error by only requiring measurement of the relative magnitudes between two spectral channels and not radiometrically calibrated intensities, simplifying the forward model from a full radiative transfer model to a vibrational–rotational band model. It is shown that the derived temperature should be interpreted as a column-integrated property as opposed to a temperature at a specified altitude without utilization of a priori information of the thermospheric temperature profile. The two-channel-ratio approach is demonstrated using NASA GOLD Level 1C disk emission data for the period of 2–8 November 2018 during which a moderate geomagnetic storm has occurred. Due to the lack of independent thermospheric temperature observations, the efficacy of the approach is validated through comparisons of the column-integrated temperature derived from GOLD Level 1C data with the GOLD Level 2 temperature product as well as temperatures from first principle and empirical models. The storm-time thermospheric response manifested in the column-integrated temperature is also shown to corroborate well with hemispherically integrated Joule heating rates, ESA SWARM mass density at 460 km, and GOLD Level 2 column O/N2 ratio.

Description: Icequakes are the result of processes occurring within the ice mass or between the ice and its environment. Studying icequakes provides a unique view on ice dynamics, specifically on the basal conditions. Changes in conditions due to environmental or climate changes are reflected in icequakes. Counting and characterizing icequakes is thus essential to monitor them. Most of the icequakes recorded by the seismic station at the Belgian Princess Elisabeth Antarctica Station (PE) have small amplitudes corresponding to maximal displacements of a few nanometres. Their detection threshold is highly variable because of the rapid and strong changes in the local seismic noise level. Therefore, we evaluated the influence of katabatic winds on the noise measured by the well-protected PE surface seismometer. Our purpose is to identify whether the lack of icequake detection during some periods could be associated with variations in the processes generating them or simply with a stronger seismic noise linked to stronger wind conditions. We observed that the wind mainly influences seismic noise at frequencies greater than 1 Hz. The seismic noise power exhibits a bilinear correlation with the wind velocity, with two different slopes at a wind velocity lower and greater than 6 m s−1 and with, for example at a period of 0.26 s, a respective variation of 0.4 dB (m −1 s) and 1.4 dB (m −1 s). These results allowed a synthetic frequency and wind-speed-dependent noise model to be presented that explains the behaviour of the wind-induced seismic noise at PE, which shows that seismic noise amplitude increases exponentially with increasing wind speed. This model enables us to study the influence of the wind on the original seismic dataset, which improves the observation of cryoseismic activity near the PE station.

Description: In this paper, we present a new version of the chemistry–climate model SOCOL-AERv2 supplemented by an iodine chemistry module. We perform three 20-year ensemble experiments to assess the validity of the modeled iodine and to quantify the effects of iodine on ozone. The iodine distributions obtained with SOCOL-AERv2-I agree well with AMAX-DOAS observations and with CAM-chem model simulations. For the present-day atmosphere, the model suggests that the iodine-induced chemistry leads to a 3 %–4 % reduction in the ozone column, which is greatest at high latitudes. The model indicates the strongest influence of iodine in the lower stratosphere with 30 ppbv less ozone at low latitudes and up to 100 ppbv less at high latitudes. In the troposphere, the account of the iodine chemistry reduces the tropospheric ozone concentration by 5 %–10 % depending on geographical location. In the lower troposphere, 75 % of the modeled ozone reduction originates from inorganic sources of iodine, 25 % from organic sources of iodine. At 50 hPa, the results show that the impacts of iodine from both sources are comparable. Finally, we determine the sensitivity of ozone to iodine by applying a 2-fold increase in iodine emissions, as it might be representative for iodine by the end of this century. This reduces the ozone column globally by an additional 1.5 %–2.5 %. Our results demonstrate the sensitivity of atmospheric ozone to iodine chemistry for present and future conditions, but uncertainties remain high due to the paucity of observational data of iodine species.

Description: Frequently occurring mega-droughts under current global climate change have attracted broad social attention. A paleoclimatic perspective is needed to increase our understanding of the causes and effects of droughts. South-western (SW) China has been threatened by severe seasonal droughts. Our current knowledge of millennial-scale dry and wet phases in this region is primarily based on the variability of the Indian summer monsoon. However, water availability over land does not always follow patterns of monsoonal precipitation but also depends on water loss from evaporation and transpiration. Here, we reconstructed precipitation intensity, lake hydrological balance and the soil water stress index (SWSI) for the last 27 000 years. Grain size, geochemical and pollen records from Yilong Lake reveal the long-term relationships and inconsistencies of dry–wet patterns in meteorological, hydrological and soil systems in the central Yunnan region, SW China. Our results show that the long-term trends among precipitation, hydrological balance and soil moisture varied through time. The hydrological balance and soil moisture were primarily controlled by temperature-induced evaporation change during periods of low precipitation such as the Last Glacial Maximum and Younger Dryas. During periods of high precipitation (the early to late Holocene), intensified evaporation from the lake surface offset the effects of increased precipitation on the hydrological balance. However, abundant rainfall and the dense vegetation canopy circumvented a soil moisture deficit that might have resulted from rising temperature. In conclusion, the hydrological balance in the central Yunnan region was more sensitive to temperature change while soil moisture could be further regulated by vegetation changes over millennial timescales. Therefore, under future climate warming, the surface water shortage in the central Yunnan region may become even more serious. Our study suggests that reforestation efforts may provide some relief to soil moisture deficits in this region.

Description: McMurdo Sound sea ice can generally be partitioned into two regimes: (1) a stable fast-ice cover, forming south of approximately 77.6∘ S around March–April and then breaking out the following January–February, and (2) a more dynamic region north of 77.6∘ S that the McMurdo Sound and Ross Sea polynyas regularly impact. In 2019, a stable fast-ice cover formed unusually late due to repeated break-out events. We analyse the 2019 sea-ice conditions and relate them to a modified storm index (MSI), a proxy for southerly wind events. We find there is a strong correlation between the timing of break-out events and several unusually large MSI events.

Description: The importance of Antarctic sea ice and Southern Ocean warming has come into the focus of polar research during the last couple of decades. Especially around West Antarctica, where warm water masses approach the continent and where sea ice has declined, the distribution and evolution of sea ice play a critical role in the stability of nearby ice shelves. Organic geochemical analyses of marine seafloor surface sediments from the Antarctic continental margin allow an evaluation of the applicability of biomarker-based sea-ice and ocean temperature reconstructions in these climate-sensitive areas. We analysed highly branched isoprenoids (HBIs), such as the sea-ice proxy IPSO25 and phytoplankton-derived HBI-trienes, as well as phytosterols and isoprenoidal glycerol dialkyl glycerol tetraethers (GDGTs), which are established tools for the assessment of primary productivity and ocean temperatures respectively. The combination of IPSO25 with a phytoplankton marker (i.e. the PIPSO25 index) permits semi-quantitative sea-ice reconstructions and avoids misleading over- or underestimations of sea-ice cover. Comparisons of the PIPSO25-based sea-ice distribution patterns and TEX86L- and RI-OH′-derived ocean temperatures with (1) sea-ice concentrations obtained from satellite observations and (2) instrument measurements of sea surface and subsurface temperatures corroborate the general capability of these proxies to determine oceanic key variables properly. This is further supported by model data. We also highlight specific aspects and limitations that need to be taken into account for the interpretation of such biomarker data and discuss the potential of IPSO25 as an indicator for the former occurrence of platelet ice and/or the export of ice-shelf water.

Description: Aeromagnetic exploration is an important method of geophysical exploration. We study the compensation method of the towed bird system and establish the towed bird interference model. Due to the geomagnetic gradient changing greatly, the geomagnetic gradient is considered in the towed bird interference model. In this paper, we model the geomagnetic field gradient and analyze the influence of the towed bird system on the aeromagnetic compensation results. Finally, we apply the ridge regression method to solve the problem. We verify the feasibility of this compensation method through actual flight tests and further improve the data quality of the towed bird interference.