The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known…The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known seasonality of sea-ice protist and meiofauna community composition, abundance and biomass in the bottom 30 cm of sea ice in relation to ice properties and ice drift trajectories in the northwestern Barents Sea. We expected low abundances during the polar night and highest values during spring prior to ice melt. Sea ice conditions and Chlorophyll a concentrations varied strongly seasonally, while particulate organic carbon concentrations were fairly stable throughout the seasons. In December to May we sampled growing first-year ice, while in July and August melting older sea ice dominated. Low sea-ice biota abundances in March could be related to the late onset of ice formation and short time period for ice algae and uni- and multicellular grazers to establish themselves. Pennate diatoms, such as Navicula spp. and Nitzschia spp., dominated the bottom ice algal communities and were present during all seasons. Except for May, ciliates, dinoflagellates, particularly of the order Gymnodiales, and small-sized flagellates were co-dominant. Ice meiofauna (here including large ciliates and foraminifers) was comprised mainly of harpacticoid copepods, copepod nauplii, rotifers, large ciliates and occasionally acoels and foraminifers, with dominance of omnivore species throughout the seasons. Large ciliates comprised the most abundant meiofauna taxon at all ice stations and seasons (50–90 %) but did not necessarily dominate the biomass. While ice melt might have released and reduced ice algal biomass in July, meiofauna abundance remained high, indicating different annual cycles of protist versus meiofauna taxa. In May highest Chlorophyll a concentrations (29.4 mg m−2) and protist biomass (107 mg C m−2) occurred, while highest meiofauna abundance was found in August (23.9 × 103 Ind. m−2) and biomass in December (0.6 mg C m−2). The abundant December ice biota community further strengthens the emerging notion of an active biota during the dark Arctic winter. The data demonstrated a strong and partially unexpected seasonality in the Barents Sea ice biota, indicating that changes in ice formation, drift and decay will significantly impact the functioning of the ice-associated ecosystem.more
The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant bias…The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant biases for the simulation of extreme precipitation. To understand the causes of these biases, we used five different cumulus parameterization schemes in the regional Climate-Weather Research and Forecasting (CWRF) model to investigate its performance and biases in the simulation of extreme precipi-tation events in China. In general, the ensemble cumulus parameterization (ECP) scheme was the most skillful in reproducing the spatial distribution of the 95th percentile daily precipitation (P95) and the other four schemes either overestimated (the Kain-Fritsch Eta and Tiedtke schemes) or underestimated (the Betts-Miller-Janjic and New Simplified Arakawa-Schubert schemes) P95. Compared with the observational data, ECP scheme signifi-cantly improved the simulation of extreme precipitation in China and had the highest correlation and the smallest root-mean-square error in most areas and seasons. To clarify the underlying physical processes of P95 simulation biases, we established a regression model of extreme precipitation based on ECP scheme. This showed that P95 in North China is mainly affected by moisture convergence, planetary boundary layer height and lifting condensation level (relative importance 18-32%). In Central China, the vertical upward motion of water vapor, sensible heat flux and planetary boundary layer height (relative importance 18-30%) are main factors associated with P95. In South China, the vertical upward motion and horizontal transport of water vapor are predominant (relative importance 26-37%). In addition, the net surface energy, surface and atmospheric radiation flux, total precipitable water, convective available potential energy and cloud water path also have a high correlation with P95 (the second most important factor; relative importance 14-31%). The influence of each factor on the simulation of P95 is different when using different cumulus parameterization schemes and the interaction among the different factors determines the ability of CWRF model to simulate extreme precipitation. These results provide important references for future model evaluations and improvements.more
The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strong…The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strongly depend on their partitioning between the liquid and ice phases. In this study, we investigated the sensitivities of the cloud phase to the ice-nucleating particle (INP) concentration and thermodynamics. Moreover, passive satellite retrieval algorithms and cloud products were evaluated to identify whether they could detect cloud microphysical and thermodynamical perturbations. Experiments were conducted using the ICOsahedral Nonhydrostatic (ICON) model at the convection-permitting resolution of about 1.2 km on a domain covering significant parts of central Europe, and they were compared to two different retrieval products based on Spinning Enhanced Visible and InfraRed Imager (SEVIRI) measurements. We selected a day with multiple isolated deep convective clouds, reaching a homogeneous freezing temperature at the cloud top. The simulated cloud liquid pixel fractions were found to decrease with increasing INP concentration, both within clouds and at the cloud top. The decrease in the cloud liquid pixel fraction was not monotonic and was stronger in high-INP cases. Cloud-top glaciation temperatures shifted toward warmer temperatures with an increasing INP concentration by as much as 8 ∘C. Moreover, the impact of the INP concentration on cloud-phase partitioning was more pronounced at the cloud top than within the cloud. Furthermore, initial and lateral boundary temperature fields were perturbed with increasing and decreasing temperature increments from 0 to ±3 and ±5 K between 3 and 12 km, respectively. Perturbing the initial thermodynamic state was also found to systematically affect the cloud-phase distribution. However, the simulated cloud-top liquid pixel fraction, diagnosed using radiative transfer simulations as input to a satellite forward operator and two different satellite remote-sensing retrieval algorithms, deviated from one of the satellite products regardless of perturbations in the INP concentration or the initial thermodynamic state for warmer subzero temperatures while agreeing with the other retrieval scheme much better, in particular for the high-INP and high-CAPE (convective available potential energy) scenarios. Perturbing the initial thermodynamic state, which artificially increases the instability of the mid- and upper-troposphere, brought the simulated cloud-top liquid pixel fraction closer to the satellite observations, especially in the warmer mixed-phase temperature range.more
Regional hydrological cycle responding to rising temperatures can have significant influences on society and human activities. We suggest a new perspe…Regional hydrological cycle responding to rising temperatures can have significant influences on society and human activities. We suggest a new perspective on East Asia’s enhanced precipitation amount that emphasizes the role of Siberian surface warming. Increased vegetation greenness in late spring and early summer in eastern Siberia, which may be a response to global warming, acts to warm the surface by reducing the surface albedo with an increase in net absorbed shortwave radiation. Subsequently, eastern Siberia warming leads to the strengthening of anti-cyclonic atmospheric circulation over inner East Asia as well as the subtropical western North Pacific high via thermal forcing and the enhanced land-sea thermal contrast, respectively. Consequently, the anticyclonic circulation over inner East Asia transports much drier and cooler air to southern East Asia. This leads to favorable conditions for increased precipitation in combination with an increased tropical moisture flux from the subtropical western North Pacific high. Therefore, continuous Siberian vegetation growth has a potential influence on the future precipitation amount in the subtropics through vegetation–atmosphere coupled processes.more
Abstract. Long-term gridded precipitation products are crucial for several
applications in hydrology, agriculture and climate sciences. Currently
avai…Abstract. Long-term gridded precipitation products are crucial for several
applications in hydrology, agriculture and climate sciences. Currently
available precipitation products suffer from space and time inconsistency
due to the non-uniform density of ground networks and the difficulties in
merging multiple satellite sensors. The recent “bottom-up” approach that
exploits satellite soil moisture observations for estimating rainfall
through the SM2RAIN (Soil Moisture to Rain) algorithm is suited to build a consistent rainfall data
record as a single polar orbiting satellite sensor is used. Here we exploit the Advanced SCATterometer (ASCAT) on board three Meteorological Operational (MetOp)
satellites, launched in 2006, 2012, and 2018, as part of the European Organisation for the Exploitation of
Meteorological Satellites (EUMETSAT) Polar
System programme. The continuity of the scatterometer sensor is ensured
until the mid-2040s through the MetOp Second Generation Programme. Therefore, by
applying the SM2RAIN algorithm to ASCAT soil moisture observations, a long-term
rainfall data record will be obtained, starting in 2007 and lasting until the mid-2040s. The
paper describes the recent improvements in data pre-processing, SM2RAIN
algorithm formulation, and data post-processing for obtaining the
SM2RAIN–ASCAT quasi-global (only over land) daily rainfall data record at a
12.5 km spatial sampling from 2007 to 2018. The quality of the SM2RAIN–ASCAT data record
is assessed on a regional scale through comparison with high-quality
ground networks in Europe, the United States, India, and Australia. Moreover, an
assessment on a global scale is provided by using the triple-collocation (TC)
technique allowing us also to compare these data with the latest, fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis
(ERA5), the Early Run version of the Integrated Multi-Satellite Retrievals
for Global Precipitation Measurement (IMERG), and the gauge-based Global
Precipitation Climatology Centre (GPCC) products. Results show that the SM2RAIN–ASCAT rainfall data record performs relatively
well at both a regional and global scale, mainly in terms of root mean square
error (RMSE) when compared to other products. Specifically, the SM2RAIN–ASCAT data
record provides performance better than IMERG and GPCC in data-scarce
regions of the world, such as Africa and South America. In these areas, we
expect larger benefits in using SM2RAIN–ASCAT for hydrological and
agricultural applications. The limitations of the SM2RAIN–ASCAT data record consist
of the underestimation of peak rainfall events and the presence of
spurious rainfall events due to high-frequency soil moisture fluctuations
that might be corrected in the future with more advanced bias correction
techniques. The SM2RAIN–ASCAT data record is freely available at
https://doi.org/10.5281/zenodo.3405563 (Brocca et al., 2019) (recently extended to the end of
August 2019).more
Photosynthetically active radiation (PAR) is the 400–700 nm portion of the solar radiation spectrum that photoautotrophic organisms including plants, …Photosynthetically active radiation (PAR) is the 400–700 nm portion of the solar radiation spectrum that photoautotrophic organisms including plants, algae, and cyanobacteria use for photosynthesis. PAR is a key variable in global ecosystem and Earth system modeling, playing a prominent role in carbon and water cycling. Alongside air temperature, water availability, and atmospheric CO2 concentration, PAR controls photosynthesis and consequently biomass productivity in general. The management of agricultural and horticultural crops, forests, grasslands, and even grasses at sports venues is a non-exhaustive list of applications for which an accurate knowledge of the PAR resource is desirable. Modern agrivoltaic systems also require a good knowledge of PAR in conjunction with the variables needed to monitor the co-located photovoltaic system. In situ quality-controlled PAR sensors provide high-quality information for specific locations. However, due to associated installation and maintenance costs, such high-quality data are relatively scarce and generally extend over a restricted and sometimes non-continuous period. Numerous studies have already demonstrated the potential offered by surface radiation estimates based on satellite information as reliable alternatives to in situ measurements. The accuracy of these estimations is site-dependent and is related, for example, to the local climate, landscape, and viewing angle of the satellite. To assess the accuracy of PAR satellite models, we inter-compared 11 methods for estimating 30 min surface PAR based on satellite-derived estimations at 33 ground-based station locations over several climate regions in Europe, Africa, and South America. Averaged across stations, the results showed average relative biases (relative to the measurement mean) across methods of 1 to 20%, an average relative standard deviation of 25 to 30%, an average relative root mean square error of 25% to 35% and a correlation coefficient always above 0.95 for all methods. Improved performance was seen for all methods at relatively cloud-free sites, and quality degraded towards the edge of the Meteosat Second Generation viewing area. A good compromise between computational time, memory allocation, and performance was achieved for most locations using the Jacovides coefficient applied to the global horizontal irradiance from HelioClim-3 or the CAMS Radiation Service. In conclusion, satellite estimations can provide a reliable alternative estimation of ground-based PAR for most applications.more
The present work investigated the performance of an isotropic (Liu–Jordan, L–J) and an anisotropic (Hay) model in assessing the solar energy potential…The present work investigated the performance of an isotropic (Liu–Jordan, L–J) and an anisotropic (Hay) model in assessing the solar energy potential of Saudi Arabia. Three types of solar collectors were considered: with southward fixed-tilt (mode (i)), with fixed-tilt tracking the Sun (mode (ii)), and with varying-tilt tracking the Sun (mode (iii)). This was the first time such a study was conducted for Saudi Arabia. The average annual difference between anisotropic (Hay) and isotropic (L–J) estimates is least ≈38 kWhm−2 year−1 over Saudi Arabia for mode (i), and therefore, the L–J model can be used effectively. In modes (ii) and (iii), the difference is greater (≈197 and ≈226 kWhm−2 year−1, respectively). It is, then, up to the solar energy engineer to decide which model is to be used, but it is recommended that the Hay model be utilised for mode-(iii) solar collectors. These results fill a research gap about the suitability of models in practice. An interesting feature for the ratio of the annual mean solar energy yield of Hay over L–J as function of the latitude, φ, and the ground albedo, ρr, is the formation of a “well” for 29° ≤ φ ≤ 31° and 1.15 ≤ ρr ≤ 1.more