Browsing by Subject "SATELLITE"

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  • Keronen, Petri; Reissell, Anni; Chevallier, Frederic; Siivola, Erkki; Pohja, Toivo; Hiltunen, Veijo; Hatakka, Juha; Aalto, Tuula; Rivier, Leonard; Ciais, Philippe; Jordan, Armin; Hari, Pertti; Viisanen, Yrjo; Vesala, Timo (2014)
  • Sporre, Moa K.; O'Connor, Ewan J.; Håkansson, Nina; Thoss, Anke; Swietlicki, Erik; Petäjä, Tuukka (2016)
    Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiala, Finland, between February and September 2014 for the Biogenic Aerosols - Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). MODIS collection 6 overestimated LWP by on average 13 g m(-2) (11 %). Interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.
  • Wang, Qingkai; Lu, Peng; Zu, Yongheng; Li, Zhijun; Lepparanta, Matti; Zhang, Guiyong (2019)
    Arctic sea ice concentration (SIC) has been studied extensively using passive microwave (PM) remote sensing. This technology could be used to improve navigation along vessel cruise paths; however, investigations on this topic have been limited. In this study, shipborne photographic observation (P-OBS) of sea ice was conducted using oblique-oriented cameras during the Chinese National Arctic Research Expedition in the summer of 2016. SIC and the areal fractions of open water, melt ponds, and sea ice (A(w), A(p), and A(i), respectively) were determined along the cruise path. The distribution of SIC along the cruise path was U-shaped, and open water accounted for a large proportion of the path. The SIC derived from the commonly used PM algorithms was compared with the moving average (MA) P-OBS SIC, including Bootstrap and NASA Team (NT) algorithms based on Special Sensor Microwave Imager/Sounder (SSMIS) data; and ARTIST sea ice, Bootstrap, Sea Ice Climate Change Initiative, and NASA Team 2 (NT2) algorithms based on Advanced Microwave Scanning Radiometer 2 (AMSR2) data. P-OBS performed better than PM remote sensing at detecting low SIC (<10%). Our results indicate that PM SIC overestimates MA P-OBS SIC at low SIC, but underestimates it when SIC exceeds a turnover point (TP). The presence of melt ponds affected the accuracy of the PM SIC; the PM SIC shifted from an overestimate to an underestimate with increasing A(p), compared with MA P-OBS SIC below the TP, while the underestimation increased above the TP. The PM algorithms were then ranked; SSMIS-NT and AMSR2-NT2 are the best and worst choices for Arctic navigation, respectively.
  • Xiu, Yuanren; Li, Zhijun; Lei, Ruibo; Wang, Qingkai; Lu, Peng; Lepparanta, Matti (2020)
    In order to apply satellite data to guiding navigation in the Arctic more effectively, the sea ice concentrations (SIC) derived from passive microwave (PM) products were compared with ship-based visual observations (OBS) collected during the Chinese National Arctic Research Expeditions (CHINARE). A total of 3 667 observations were collected in the Arctic summers of 2010, 2012, 2014, 2016, and 2018. PM SIC were derived from the NASA-Team (NT), Bootstrap (BT) and Climate Data Record (CDR) algorithms based on the SSMIS sensor, as well as the BT, enhanced NASA-Team (NT2) and ARTIST Sea Ice (ASI) algorithms based on AMSR-E/AMSR-2 sensors. The daily arithmetic average of PM SIC values and the daily weighted average of OBS SIC values were used for the comparisons. The correlation coefficients (CC), biases and root mean square deviations (RMSD) between PM SIC and OBS SIC were compared in terms of the overall trend, and under mild/normal/severe ice conditions. Using the OBS data, the influences of floe size and ice thickness on the SIC retrieval of different PM products were evaluated by calculating the daily weighted average of floe size code and ice thickness. Our results show that CC values range from 0.89 (AMSR-E/AMSR-2 NT2) to 0.95 (SSMIS NT), biases range from -3.96% (SSMIS NT) to 12.05% (AMSR-E/AMSR-2 NT2), and RMSD values range from 10.81% (SSMIS NT) to 20.15% (AMSR-E/AMSR-2 NT2). Floe size has a significant influence on the SIC retrievals of the PM products, and most of the PM products tend to underestimate SIC under smaller floe size conditions and overestimate SIC under larger floe size conditions. Ice thickness thicker than 30 cm does not have a significant influence on the SIC retrieval of PM products. Overall, the best (worst) agreement occurs between OBS SIC and SSMIS NT (AMSR-E/AMSR-2 NT2) SIC in the Arctic summer.
  • Sarris, Theodoros E.; Talaat, Elsayed R.; Palmroth, Minna; Dandouras, Iannis; Armandillo, Errico; Kervalishvili, Guram; Buchert, Stephan; Tourgaidis, Stylianos; Malaspina, David M.; Jaynes, Allison N.; Paschalidis, Nikolaos; Sample, John; Halekas, Jasper; Doornbos, Eelco; Lappas, Vaios; Jorgensen, Therese Moretto; Stolle, Claudia; Clilverd, Mark; Wu, Qian; Sandberg, Ingmar; Pirnaris, Panagiotis; Aikio, Anita (2020)
    The Daedalus mission has been proposed to the European Space Agency (ESA) in response to the call for ideas for the Earth Observation program's 10th Earth Explorer. It was selected in 2018 as one of three candidates for a phase-0 feasibility study. The goal of the mission is to quantify the key electrodynamic processes that determine the structure and composition of the upper atmosphere, the gateway between the Earth's atmosphere and space. An innovative preliminary mission design allows Daedalus to access electrodynamics processes down to altitudes of 150 km and below. Daedalus will perform in situ measurements of plasma density and temperature, ion drift, neutral density and wind, ion and neutral composition, electric and magnetic fields, and precipitating particles. These measurements will unambiguously quantify the amount of energy deposited in the upper atmosphere during active and quiet geomagnetic times via Joule heating and energetic particle precipitation, estimates of which currently vary by orders of magnitude between models and observation methods. An innovation of the Daedalus preliminary mission concept is that it includes the release of subsatellites at low altitudes: combined with the main spacecraft, these subsatellites will provide multipoint measurements throughout the lower thermosphereionosphere (LTI) region, down to altitudes below 120 km, in the heart of the most under-explored region in the Earth's atmosphere. This paper describes Daedalus as originally proposed to the ESA.
  • Tuononen, Minttu; O'Connor, Ewan J.; Sinclair, Victoria A. (2019)
    The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar energy and UV radiation forecasts. Here we investigate how operational forecasts of low and mid-level clouds affect the accuracy of solar radiation forecasts. A total of 4 years of cloud and solar radiation observations from one site in Helsinki, Finland, are analysed. Cloud observations are obtained from a ceilometer and therefore we first develop algorithms to reliably detect cloud base, precipitation, and fog. These new algorithms are widely applicable for both operational use and research, such as in-cloud icing detection for the wind energy industry and for aviation. The cloud and radiation observations are compared to forecasts from the Integrated Forecast System (IFS) run operationally and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop methods to evaluate the skill of the cloud and radiation forecasts. These methods can potentially be extended to hundreds of sites globally. Over Helsinki, the measured global horizontal irradiance (GHI) is strongly influenced by its northerly location and the annual variation in cloudiness. Solar radiation forecast error is therefore larger in summer than in winter, but the relative error in the solar radiation forecast is more or less constant throughout the year. The mean overall bias in the GHI forecast is positive (8 W m(-2)). The observed and forecast distributions in cloud cover, at the spatial scales we are considering, are strongly skewed towards clear-sky and overcast situations. Cloud cover forecasts show more skill in winter when the cloud cover is predominantly overcast; in summer there are more clear-sky and broken cloud situations. A negative bias was found in forecast GHI for correctly forecast clear-sky cases and a positive bias in correctly forecast overcast cases. Temporal averaging improved the cloud cover forecast and hence decreased the solar radiation forecast error. The positive bias seen in overcast situations occurs when the model cloud has low values of liquid water path (LWP). We attribute this bias to the model having LWP values that are too low or the model optical properties for clouds with low LWP being incorrect.
  • Tripathi, Shankar; Subedi, Rajan; Adhikari, Hari (2020)
    An account of widespread degradation and deforestation in Nepal has been noticed in various literature sources. Although the contribution of community forests (CF) on the improvement of forest cover and condition in the Mid-hill of Nepal is positive, detailed study to understand the current situation seems important. The study area (Tanahun District) lies in the Gandaki Province of western Nepal. The objective of this study was to estimate the forest cover change over the specified period and to identify factors influencing the change. We used Landsat images from the years 1976, 1991, and 2015 to classify land use and land cover. We considered community perception in addition to the forest cover map to understand the different causes of forest cover change. Forest cover decreased from 1976 to 1991 annually at a rate of 0.96%. After 1991, the forest increased annually at a rate of 0.63%. The overall forest cover in the district regained its original status. Factors related to increasing forest cover were emigration, occupation shift, agroforestry practices, as well as particularly by plantation on barren lands, awareness among forest users, and conservation activities conducted by local inhabitants after the government forest was handed over to community members as a community forest management system.
  • Yan, Yu; Huang, Kaiyue; Shao, Dongdong; Xu, Yingjun; Gu, Wei (2019)
    Satellite remote sensing data, such as moderate resolution imaging spectroradiometers (MODIS) and advanced very high-resolution radiometers (AVHRR), are being widely used to monitor sea ice conditions and their variability in the Bohai Sea, the southernmost frozen sea in the Northern Hemisphere. Monitoring the characteristics of the Bohai Sea ice can provide crucial information for ice disaster prevention for marine transportation, oil field operation, and regional climate change studies. Although these satellite data cover the study area with fairly high spatial resolution, their typically limited cloudless images pose serious restrictions for continuous observation of short-term dynamics, such as sub-seasonal changes. In this study, high spatiotemporal resolution (500 m and eight images per day) geostationary ocean color imager (GOCI) data with a high proportion of cloud-free images were used to monitor the characteristics of the Bohai Sea ice, including area and thickness. An object-based feature extraction method and an albedo-based thickness inversion model were used for estimating sea ice area and thickness, respectively. To demonstrate the efficacy of the new dataset, a total of 68 GOCI images were selected to analyze the evolution of sea ice area and thickness during the winter of 2012-2013 with severe sea ice conditions. The extracted sea ice area was validated using Landsat Thematic Mapper (TM) data with higher spatial resolution, and the estimated sea ice thickness was found to be consistent with in situ observation results. The entire sea ice freezing-melting processes, including the key events such as the day with the maximum ice area and the first and last days of the frozen season, were better resolved by the high temporal-resolution GOCI data compared with MODIS or AVHRR data. Both characteristics were found to be closely correlated with cumulative freezing/melting degree days. Our study demonstrates the applicability of the GOCI data as an improved dataset for studying the Bohai Sea ice, particularly for purposes that require high temporal resolution data, such as sea ice disaster monitoring.
  • Pozza, Matteo; Rao, Ashwin; Flinck, Hannu; Tarkoma, Sasu (2018)
    One of the key features of next-generation mobile networks is the ability to satisfy the requirements coming from different verticals. For satisfying these requirements, 5G networks will need to dynamically reconfigure the deployment of the network functions. However, the current deployments of mobile networks are experiencing difficulties in exhibiting the required flexibility. At the same time, the research on connectivity provisioning in use cases such as after-disaster scenarios or battlefields has converged towards the idea of Network-In-a-Box. This idea revolves around fitting all software and hardware modules needed by a mobile network in a single or a handful of physical devices. A Network-In-a-Box inherently offers a high level of flexibility that makes it capable of providing connectivity services in a wide range of scenarios. Therefore, the Network-In-a-Box concept represents an alternative approach for satisfying the requirements of next-generation mobile networks. In this survey, we analyze the state-of-the-art of Network-In-a-Box solutions proposed by academia and industry in the time frame starting from 1998 up to early 2017. First, we present the main use cases around which the concept has been conceived. Then, we abstract the common features of the Network-In-a-Box implementations, and discuss how different proposals offer these features. We then draw our conclusions and discuss possible future research directions, including steps required to reach an even higher level of flexibility. The aim of our analysis is twofold. On one hand, we provide a comprehensive view of the idea of Network-In-a-Box. On the other hand, through the analysis we present the features that future mobile networks should exhibit to achieve their design goals. In particular, we show how the Network-In-a-Box fosters the transition towards the next-generation mobile networks.
  • Riuttanen, Laura; Bister, Marja; Kerminen, Veli-Matti; John, Viju O.; Sundstrom, Anu-Maija; Dal Maso, Miikka; Räisänen, Jouni; Sinclair, Victoria A.; Makkonen, Risto; Xausa, Filippo; De Leeuw, Gerrit; Kulmala, Markku (2016)
    Aerosol-cloud interactions are the largest source of uncertainty in the radiative forcing of the global climate. A phenomenon not included in the estimates of the total net forcing is the potential increase in upper tropospheric humidity (UTH) by anthropogenic aerosols via changes in the microphysics of deep convection. Using remote sensing data over the ocean east of China in summer, we show that increased aerosol loads are associated with an UTH increase of 2.2 +/- 1.5 in units of relative humidity. We show that humidification of aerosols or other meteorological covariation is very unlikely to be the cause of this result, indicating relevance for the global climate. In tropical moist air such an UTH increase leads to a regional radiative effect of 0.5 +/- 0.4 W m(-2). We conclude that the effect of aerosols on UTH should be included in future studies of anthropogenic climate change and climate sensitivity.
  • Sogacheva, Larisa; Kolmonen, Pekka; Virtanen, Timo H.; Rodriguez, Edith; Saponaro, Giulia; De Leeuw, Gerrit (2017)
    Cloud misclassification is a serious problem in the retrieval of aerosol optical depth (AOD), which might considerably bias the AOD results. On the one hand, residual cloud contamination leads to AOD overestimation, whereas the removal of high-AOD pixels (due to their misclassification as clouds) leads to underestimation. To remove cloudcontaminated areas in AOD retrieved from reflectances measured with the (Advanced) Along Track Scanning Radiometers (ATSR-2 and AATSR), using the ATSR dual-view algorithm (ADV) over land or the ATSR single-view algorithm (ASV) over ocean, a cloud post-processing (CPP) scheme has been developed at the Finnish Meteorological Institute (FMI) as described in Kolmonen et al. (2016). The application of this scheme results in the removal of cloudcontaminated areas, providing spatially smoother AOD maps and favourable comparison with AOD obtained from the ground-based reference measurements from the AERONET sun photometer network. However, closer inspection shows that the CPP also removes areas with elevated AOD not due to cloud contamination, as shown in this paper. We present an improved CPP scheme which better discriminates between cloud-free and cloud-contaminated areas. The CPP thresholds have been further evaluated and adjusted according to the findings. The thresholds for the detection of high-AOD regions (> 60% of the retrieved pixels should be high-AOD (> 0.6) pixels), and cloud contamination criteria for lowAOD regions have been accepted as the default for AOD global post-processing in the improved CPP. Retaining elevated AOD while effectively removing cloud-contaminated pixels affects the resulting global and regional mean AOD values as well as coverage. Effects of the CPP scheme on both spatial and temporal variation for the period 2002-2012 are discussed. With the improved CPP, the AOD coverage increases by 10-15% with respect to the existing scheme. The validation versus AERONET shows an improvement of the correlation coefficient from 0.84 to 0.86 for the global data set for the period 2002-2012. The global aggregated AOD over land for the period 2003-2011 is 0.163 with the improved CPP compared to 0.144 with the existing scheme. The aggregated AOD over ocean and globally (land and ocean together) is 0.164 with the improved CPP scheme (compared to 0.152 and 0.150 with the existing scheme, for ocean and globally respectively). Effects of the improved CPP scheme on the 10-year time series are illustrated and seasonal and temporal changes are discussed. The improved CPP method introduced here is applicable to other aerosol retrieval algorithms. However, the thresholds for detecting the high-AOD regions, which were developed for AATSR, might have to be adjusted to the actual features of the instruments.
  • Urraca, Ruben; Huld, Thomas; Lindfors, Anders V.; Riihelä, Aku; Javier Martinez-de-Pison, Francisco; Sanz-Garcia, Andres (2018)
    Solar radiation databases used for simulating PV systems are typically selected according to their annual bias in global horizontal irradiance (G(H)) because this bias propagates proportionally to plane-of-array irradiance (G(POA)) and module power (P-DC). However, the bias may get amplified through the simulations due to the impact of deviations in estimated irradiance on parts of the modeling chain depending on irradiance. This study quantifies these effects at 39 European locations by comparing simulations using satellite-based (SARAH) and reanalysis (COSMO-REA6 and ERAS) databases against simulations using station measurements. SARAH showed a stable bias through the simulations producing the best Pp c predictions in Central and South Europe, whereas the bias of reanalyses got substantially amplified because their deviations vary with atmospheric transmissivity due to an incorrect prediction of clouds. However, SARAH worsened at the northern locations covered by the product (55-65 degrees N) underestimating both G(POA) and P-DC. On the contrary, ERAS not only covers latitudes above 65 degrees but it also obtained the least biased P-DC estimations between 55 and 65 degrees N, which supports its use as a complement of satellite-based databases in high latitudes. The most significant amplifications occurred through the transposition model ranging from +/- 1% up to +/- 6%. Their magnitude increased linearly with the inclination angle, and they are related to the incorrect estimation of beam and diffuse irradiance. The bias increased around + 1% in the PV module model because the PV conversion efficiency depends on irradiance directly, and indirectly via module temperature. The amplification of the bias was similar and occasionally greater than the bias in annual G(H), so databases with the smallest bias in G(H) may not always provide the least biased PV simulations.
  • Sun, Linghui; Baker, Jessica; Gloor, Emanuel; Spracklen, Dominick; Boesch, Hartmut; Somkuti, Peter; Maeda, Eduardo Eiji; Buermann, Wolfgang (2019)
    We analyzed seasonal and spatial variations of evapotranspiration (ET) for five Amazon sub-basins and their response to the 2015/16 El Nino episode using a recently developed water-budget approach. ET varied typically between similar to 7 and 10 cm/month with exception of the Xingu basin for which it varied between 10 and 15 cm/month. Outstanding features of ET seasonality are (i) generally weak seasonality, (ii) two ET peaks for the two very wet catchments Solimoes and Negro, with one occurring during the wet season and one during the drier season, and (iii) a steady increase of ET during the second half of the dry season for the three drier catchments (Madeira, Tapajos, Xingu). Peak ET occurs during the first half of the wet season consistent with leaf flush occurring before the onset of the wet season. With regards to inter-annual variation, we found firstly that for the Solimoes and Madeira catchments the period with large positive wet season anomalies (2012-2015) is associated with negative ET anomalies, and negative SIF (solar induced fluorescence) anomalies. Furthermore, we found negative ET of several cm/months and SIF (up to 50%) anomalies for most of the Amazon basin during the 2015/16 El Nino event suggesting down-regulation of productivity as a main factor of positive carbon flux anomalies during anomalously hot and dry conditions. These results are of interest in view of predicted warmer and more erratic future climate conditions.
  • Urraca, Ruben; Huld, Thomas; Javier Martinez-de-Pison, Francisco; Sanz-Garcia, Andres (2018)
    The major sources of uncertainty in short-term assessment of global horizontal radiation (G) are the pyranometer type and their operation conditions for measurements, whereas the modeling approach and the geographic location are critical for estimations. The influence of all these factors in the uncertainty of the data has rarely been compared. Conversely, solar radiation data users are increasingly demanding more accurate uncertainty estimations. Here we compare the annual bias and uncertainty of all the mentioned factors using 732 weather stations located in Spain, two satellite-based products and three reanalyses. The largest uncertainties were associated to operational errors such as shading (bias = - 8.0%) or soiling (bias = - 9.4%), which occurred frequently in low-quality monitoring networks but are rarely detected because they pass conventional QC tests. Uncertainty in estimations greatly changed from reanalysis to satellite-based products, ranging from the gross accuracy of ERA-Interim (+ 6.1(-6.7)(+)(1)(8.)(8)%) to the high quality and spatial homogeneity of SARAH-1 (+ 1.4(-5.3)(+)(5.6)%). Finally, photodiodes from the Spanish agricultural network SIAR showed an uncertainty of (+6.)(9)(-5.4)%, which is far greater than that of secondary standards (+/- 1.5%) and similar to SARAH-1. This is probably caused by the presence of undetectable operational errors and the use of uncorrected photodiodes. Photodiode measurements from low-quality monitoring networks such as SIAR should be used with caution, because the chances of adding extra uncertainties due to poor maintenance or inadequate calibration considerably increase.
  • Kaki, Sebastian; Viljanen, Ari; Juusola, Liisa; Kauristie, Kirsti (2022)
    During auroral substorms, the electric currents flowing in the ionosphere change rapidly, and a large amount of energy is dissipated in the auroral ionosphere. An important part of the auroral current system is the auroral electrojets whose profiles can be estimated from magnetic field measurements from low-earth orbit satellites. In this paper, we combine electrojet data derived from the Swarm satellite mission of the European Space Agency with the substorm database derived from the SuperMAG ground magnetometer network data. We organize the electrojet data in relation to the location and time of the onset and obtain statistics for the development of the integrated current and latitudinal location for the auroral electrojets relative to the onset. The major features of the behaviour of the westward electrojet are found to be in accordance with earlier studies of field-aligned currents and ground magnetometer observations of substorm temporal statistics. In addition, we show that, after the onset, the latitudinal location of the maximum of the westward electrojet determined from Swarm satellite data is mostly located close to the SuperMAG onset latitude in the local time sector of the onset regardless of where the onset happens. We also show that the SuperMAG onset corresponds to a strengthening of the order of 100 kA in the amplitude of the median of the westward integrated current in the Swarm data from 15 min before to 15 min after the onset.
  • Liu, Yang; Tang, Zhipeng; Abera, Temesgen; Zhang, Xuezhen; Hakola, Hannele; Pellikka, Petri; Maeda, Eduardo (2020)
    Understanding the local sources of atmospheric formaldehyde (HCHO) is a key step in accurately determining the inversion of biogenic volatile organic compounds (BVOCs). This study aims to clarify the main sources and emission patterns of local total HCHO column densities over Ethiopia and Kenya. Between 2005 and 2015, the total monthly HCHO varied from 3.7 x 10(15) molecules/cm(2) to 7.7 x 10(15) molecules/cm(2). Monthly HCHO showed a strong seasonal pattern with annual peaks on March, July (small peak) and October, which well matched with the rainy seasons in Ethiopia and Kenya. Natural sources contributed 36% to the total HCHO in the study area. Grassland and savannas showed high column densities in the long rainy season starting from March, with the monthly average emission value of 5.6 x 10(15) molecules/cm(2). Multiple regression result showed that vegetation contributed 3.5 x 10(13) molecules/cm(2) to monthly HCHO, with grassland and forest in eastern Kenya and the boundary of Ethiopia and Kenya were the main contributors in these regions. Biomass burning and methane contributed to HCHO emission in the western and northern Ethiopia with a magnitude of 1.4 x 10(14) molecules/cm(2) and 6.2 x 10(16) molecules/cm(2) per month, respectively. Economic activities showed negative response to HCHO columns, except over the two small-scale regions of Addis Ababa City and Nairobi City. This study quantified the HCHO from various sources and suggested that natural sources produce more HCHO than anthropogenic sources over Ethiopia and Kenya.
  • Harrison, Sandy P.; Villegas-Diaz, Roberto; Cruz-Silva, Esmeralda; Gallagher, Daniel; Kesner, David; Lincoln, Paul; Shen, Yicheng; Sweeney, Luke; Colombaroli, Daniele; Ali, Adam; Barhoumi, Cheima; Bergeron, Yves; Blyakharchuk, Tatiana; Bobek, Premysl; Bradshaw, Richard; Clear, Jennifer L.; Czerwinski, Sambor; Daniau, Anne-Laure; Dodson, John; Edwards, Kevin J.; Edwards, Mary E.; Feurdean, Angelica; Foster, David; Gajewski, Konrad; Galka, Mariusz; Garneau, Michelle; Giesecke, Thomas; Gil Romera, Graciela; Girardin, Martin P.; Hoefer, Dana; Huang, Kangyou; Inoue, Jun; Jamrichova, Eva; Jasiunas, Nauris; Jiang, Wenying; Jimenez-Moreno, Gonzalo; Karpinska-Kolaczek, Monika; Kolaczek, Piotr; Kuosmanen, Niina; Lamentowicz, Mariusz; Lavoie, Martin; Li, Fang; Li, Jianyong; Lisitsyna, Olga; Lopez-Saez, Jose Antonio; Luelmo-Lautenschlaeger, Reyes; Magnan, Gabriel; Magyari, Eniko Katalin; Maksims, Alekss; Marcisz, Katarzyna; Marinova, Elena; Marlon, Jenn; Mensing, Scott; Miroslaw-Grabowska, Joanna; Oswald, Wyatt; Perez-Diaz, Sebastian; Perez-Obiol, Ramon; Piilo, Sanna; Poska, Anneli; Qin, Xiaoguang; Remy, Cecile C.; Richard, Pierre J. H.; Salonen, Sakari; Sasaki, Naoko; Schneider, Hieke; Shotyk, William; Stancikaite, Migle; Steinberga, Dace; Stivrins, Normunds; Takahara, Hikaru; Tan, Zhihai; Trasune, Liva; Umbanhowar, Charles E.; Väliranta, Minna; Vassiljev, Juri; Xiao, Xiayun; Xu, Qinghai; Xu, Xin; Zawisza, Edyta; Zhao, Yan; Zhou, Zheng; Paillard, Jordan (2022)
    Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b - Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345.
  • Castro-Morales, Karel; Schuermann, Gregor; Koestler, Christoph; Roedenbeck, Christian; Heimann, Martin; Zaehle, Soenke (2019)
    During the last decade, carbon cycle data assimilation systems (CCDAS) have focused on improving the simulation of seasonal and mean global carbon fluxes over a few years by simultaneous assimilation of multiple data streams. However, the ability of a CCDAS to predict longer-term trends and variability of the global carbon cycle and the constraint provided by the observations have not yet been assessed. Here, we evaluate two near-decade-long assimilation experiments of the Max Planck Institute-Carbon Cycle Data Assimilation System (MPI-CCDAS v1) using spaceborne estimates of the fraction of absorbed photosynthetic active radiation (FAPAR) and atmospheric CO2 concentrations from the global network of flask measurement sites from either 1982 to 1990 or 1990 to 2000. We contrast these simulations with independent observations from the period 1982-2010, as well as a third MPI-CCDAS assimilation run using data from the full 1982-2010 period, and an atmospheric inversion covering the same data and time. With 30 years of data, MPI-CCDAS is capable of representing land uptake to a sufficient degree to make it compatible with the atmospheric CO2 record. The long-term trend and seasonal amplitude of atmospheric CO2 concentrations at station level over the period 1982 to 2010 is considerably improved after assimilating only the first decade (1982-1990) of observations. After 15-19 years of prognostic simulation, the simulated CO2 mixing ratio in 2007-2010 diverges by only 2 +/- 1.3 ppm from the observations, the atmospheric inversion, and the MPI-CCDAS assimilation run using observations from the full period. The long-term trend, phenological seasonality, and interannual variability (IAV) of FAPAR in the Northern Hemisphere over the last 1 to 2 decades after the assimilation were also improved. Despite imperfections in the representation of the IAV in atmospheric CO2, model-data fusion for a decade of data can already contribute to the prognostic capacity of land carbon cycle models at relevant timescales.
  • Allahbakhshi, Hoda; Conrow, Lindsey; Naimi, Babak; Weibel, Robert (2020)
    This paper aims to examine the role of global positioning system (GPS) sensor data in real-life physical activity (PA) type detection. Thirty-three young participants wore devices including GPS and accelerometer sensors on five body positions and performed daily PAs in two protocols, namely semi-structured and real-life. One general random forest (RF) model integrating data from all sensors and five individual RF models using data from each sensor position were trained using semi-structured (Scenario 1) and combined (semi-structured + real-life) data (Scenario 2). The results showed that in general, adding GPS features (speed and elevation difference) to accelerometer data improves classification performance particularly for detecting non-level and level walking. Assessing the transferability of the models on real-life data showed that models from Scenario 2 are strongly transferable, particularly when adding GPS data to the training data. Comparing individual models indicated that knee-models provide comparable classification performance (above 80%) to general models in both scenarios. In conclusion, adding GPS data improves real-life PA type classification performance if combined data are used for training the model. Moreover, the knee-model provides the minimal device configuration with reliable accuracy for detecting real-life PA types.