Assessing Crop Water Requirement and Yield by Combining ERA5-Land Reanalysis Data with CM-SAF Satellite-Based Radiation Data and Sentinel-2 Satellite Imagery

Author(s):
Pelosi, Anna; Belfiore, Oscar Rosario; D’Urso, Guido; Chirico, Giovanni Battista
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 24
2022
DOI: 10.3390/rs14246233
Abstract:
The widespread development of Earth Observation (EO) systems and advances in numerical atmospheric modeling have made it possible to use the newest da… The widespread development of Earth Observation (EO) systems and advances in numerical atmospheric modeling have made it possible to use the newest data sources as input for crop–water balance models, thereby improving the crop water requirements (CWR) and yield estimates from the field to the regional scale. Satellite imagery and numerical weather prediction outputs offer high resolution (in time and space) gridded data that can compensate for the paucity of crop parameter field measurements and ground weather observations, as required for assessments of CWR and yield. In this study, the AquaCrop model was used to assess CWR and yield of tomato on a farm in Southern Italy by assimilating Sentinel-2 (S2) canopy cover imagery and using CM-SAF satellite-based radiation data and ERA5-Land reanalysis as forcing weather data. The prediction accuracy was evaluated with field data collected during the irrigation season (April–July) of 2021. Satellite estimates of canopy cover differed from ground observations, with a RMSE of about 11%. CWR and yield predictions were compared with actual data regarding irrigation volumes and harvested yield. The results showed that S2 estimates of crop parameters represent added value, since their assimilation into crop growth models improved CWR and yield estimates. Reliable CWR and yield estimates can be achieved by combining the ERA5-Land and CM-SAF weather databases with S2 imagery for assimilation into the AquaCrop model. more
Application Atmosphere CM-SAF Climate Data Records Land

Assessing sea ice microwave emissivity up to submillimeter waves from airborne and satellite observations

Author(s):
Risse, N.; Mech, M.; Prigent, C.; Spreen, G.; Crewell, S.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 9
2024
DOI: 10.5194/tc-18-4137-2024
Abstract:
Upcoming submillimeter wave satellite missions require an improved understanding of sea ice emissivity to separate atmospheric and surface microwave s… Upcoming submillimeter wave satellite missions require an improved understanding of sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale observations of airborne sea ice emissivity between 89 and 340 GHz, combined with high-resolution visual imagery from two Arctic airborne field campaigns that took place in summer 2017 and spring 2019 northwest of Svalbard, Norway. Using k-means clustering, we identify four distinct sea ice emissivity spectra that occur predominantly across multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest emissivity, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne measurements to kilometer-scale satellite footprints, we quantify the reduction in the variability of airborne emissivity as footprint size increases. At 340 GHz, the emissivity interquartile range decreases by almost half when moving from the hectometer scale to a footprint of 16 km, typical of satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral variations in emissivity at nadir on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz, which occurs for all hectometer-scale clusters except those predominantly composed of multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice in current and future satellite missions, such as the Ice Cloud Imager (ICI) and EUMETSAT Polar System - Sterna (EPS-Sterna). © 2024 Nils Risse et al. more
Application Atmosphere NWP-SAF Software for CDR development

Assessing prior emergent constraints on surface albedo feedback in CMIP6

Author(s):
Thackeray, C.W.; Hall, A.; Zelinka, M.D.; Fletcher, C.G.
Publication title: Journal of Climate
2021
 | Volume: 34 | Issue: 10
2021
DOI: 10.1175/JCLI-D-20-0703.1
Abstract:
An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of cli… An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAFsnow) and sea ice (SAFice). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAFsnow EC is equally strong in CMIP6 as it was in past generations, while the SAFice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 6 0.05 W m22 K21, or;61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. The NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAFsnow and SAFice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAFice, and to a lesser extent SAFsnow. Ó 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy more
Application CM-SAF Climate Data Records Cryosphere

Assessing the consistency of satellite derived upper tropospheric humidity measurements

Author(s):
Shi, Lei; Schreck III, Carl J.; John, Viju O.; Chung, Eui-Seok; Lang, Theresa; Buehler, Stefan A.; Soden, Brian J.
2022
2022
DOI: 10.5194/amt-15-6949-2022
Abstract:
Abstract. Four upper tropospheric humidity (UTH) datasets derived from satellite sounders are evaluated to assess their consistency as part of the act… Abstract. Four upper tropospheric humidity (UTH) datasets derived from satellite sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The datasets include UTH computed from brightness temperature measurements of the 183.31 ± 1 GHz channel of the Special Sensor Microwave – Humidity (SSM/T-2), Advanced Microwave Sounding Unit-B (AMSU-B), and Microwave Humidity Sounder (MHS), and from channel 12 of the High-Resolution Infrared Radiation Sounder (HIRS). The four datasets are consistent in the interannual temporal and spatial variability of the tropics. Large positive anomalies peaked over the central equatorial Pacific region during El Niño events in the same phase with the increase of sea surface temperature. Conversely, large negative anomalies were obtained during El Niño events when the tropical domain average is taken. The weakened ascending branch of the Pacific Walker circulation in the western Pacific and the enhanced descending branches of the local Hadley circulation along the Pacific subtropics largely contributed to widespread drying areas and thus negative anomalies in the upper troposphere during El Niño events as shown in all four datasets. Due to differences in retrieval definitions, calibration methods, and sensor limitations, there are differences in spatial anomalies and temporal change rates, where more significant anomaly values are usually found in the microwave UTH data. more
Application Atmosphere CM-SAF Climate Data Records EUM-Secr Validation

Assessing the Fitness of Satellite Albedo Products for Monitoring Snow Albedo Trends

Author(s):
Urraca, R; Lanconelli, C; Cappucci, F; Gobron, N
Publication title: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2023
 | Volume: 61
2023
DOI: 10.1109/TGRS.2023.3281188
Abstract:
Accurate monitoring of albedo trends over snow is essential to evaluate the consequences of the global snow cover retreat on Earth's energy budget. Sa… Accurate monitoring of albedo trends over snow is essential to evaluate the consequences of the global snow cover retreat on Earth's energy budget. Satellite observations provide the best way to monitor these trends globally, but their uncertainty increases over snow. Besides, different products sometimes show diverging trends. A better assessment of the fitness of satellite products for monitoring snow albedo trends is needed. We analyze the consistency of black-sky albedo estimates from global long-term products over snow: advanced very-high-resolution radiometer (AVHRR)-based (CLARA-A2.1, GLASS-v4.2), moderate resolution imaging spectroradiometer (MODIS)-based (MCD43C3-v6.1/v6, GLASS-v4.2), multiangle imaging spectro radiometer (MISR)-based (MIL3MLSN-v4), and multisensor (C3S-v1/v2). We use MCD43C3-6.1 as the reference based on a previous comparison against in situ measurements. CLARA-A2.1 is the one most consistent with MCD43C3, but has a low coverage in high latitudes and an artificial albedo decrease since 2015. The study shows the limitations of MIL3MLSN, Global Land Surface Satellite (GLASS), and Copernicus Climate Change Service (C3S) multisensor products over snow. MIL3MLSN has a too-low coverage of albedo over snow. GLASS-AVHRR overestimates albedo in regions with seasonal snow due to delayed snowmelt and underestimates it in permanently snow-covered regions. GLASS-MODIS is more consistent with MCD43C3 at mid-latitudes, and also underestimates albedo in regions with permanent snow and has an increase in missing values after 2011. Both the GLASS datasets are temporally inconsistent with the other products. Despite the improvements from v1 to v2, C3S-v2 has the largest negative bias over snow and discontinuities in the transitions between sensors. The study evidences the difficulties of AVHRR products to provide stable snow albedo estimates in polar regions, particularly before 2000. more
CM-SAF Climate Data Records Land Validation

Assessing the Influences of Cloud Top Height Information on Passive Microwave Retrieval of Cloud Liquid Water Path

Author(s):
Li, J.; Liu, C.; Yao, B.; Zhao, Y.; Dou, F.; Hu, X.; Weng, F.; Sohn, B.-J.
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2024
 | Volume: 62
2024
DOI: 10.1109/TGRS.2024.3493598
Abstract:
Cloud liquid water path (LWP) quantifies liquid water amount within the atmosphere and is closely related to water cycle, weather, and climate. Passiv… Cloud liquid water path (LWP) quantifies liquid water amount within the atmosphere and is closely related to water cycle, weather, and climate. Passive microwave (MW) observations are powerful tools for retrieving LWP. An empirical relationship between the LWPs and MW brightness temperatures (BTs) can be obtained for conventional retrievals, which consider only the influence of LWP on BTs. However, besides LWP, the cloud vertical extent [e.g., cloud top height (CTH)] can affect MW emission, absorption, and corresponding channel BTs, but it is ignored in conventional retrievals. This study investigates the influences of CTH on MW LWP retrievals, and a CTH-dependent algorithm is developed using CTHs from infrared retrievals. Synthetic radiative transfer simulations are performed to quantify CTH effects on MW channel BTs and to establish the CTH-dependent retrieval coefficients. We use the Advanced MW Scanning Radiometer 2 (AMSR2) observations. Cloud products from Moderate Resolution Imaging Spectroradiometer (MODIS) are collocated to provide the necessary CTH information. Thus, we develop an LWP retrieval algorithm by combining AMSR2 BTs with MODIS CTHs. The results indicate that incorporating CTH information into LWP retrievals enhances the consistency between MW and visible/infrared retrievals. Specifically, the CTH-dependent algorithm showed an improvement in the intraclass correlation coefficient (ICC) and a reduction in mean relative differences (MRDs) by approximately 4% (from 18% to 14%) compared to AMSR2 operational retrievals. The CTH-dependent results are slightly more consistent with the MODIS results than the CTH-independent ones, though it remains important to note that the CTH-dependent retrievals introduce less differences compared to their CTH-independent retrievals. © 2024 IEEE. more
Application Atmosphere NWP-SAF Software for CDR development

Assessing the potential for sea-based macroalgae cultivation and its application for nutrient removal in the Baltic Sea

Author(s):
Kotta, Jonne; Raudsepp, Urmas; Szava-Kovats, Robert; Aps, Robert; Armoskaite, Aurelija; Barda, Ieva; Bergstrom, Per; Futter, Martyn; Grondahl, Fredrik; Hargrave, Matthew; Jakubowska, Magdalena; Janes, Holger; Kaasik, Ants; Kraufvelin, Patrik; Kovaltchouk, Nikolai; Krost, Peter; Kulikowski, Tomasz; Koivupuu, Anneliis; Kotta, Ilmar; Lees, Liisi; Loite, Sander; Maljutenko, Ilja; Nylund, Goran; Paalme, Tiina; Pavia, Henrik; Purina, Ingrida; Rahikainen, Moona; Sandow, Verena; Visch, Wouter; Yang, Baoru; Barboza, Francisco R.
Publication title: SCIENCE OF THE TOTAL ENVIRONMENT
2022
 | Volume: 839
2022
DOI: 10.1016/j.scitotenv.2022.156230
Abstract:
Marine eutrophication is a pervasive and growing threat to global sustainability. Macroalgal cultivation is a promising circular economy solution to a… Marine eutrophication is a pervasive and growing threat to global sustainability. Macroalgal cultivation is a promising circular economy solution to achieve nutrient reduction and food security. However, the location of production hotspots is not well known. In this paper the production potential of macroalgae of high commercial value was predicted across the Baltic Sea region. In addition, the nutrient limitation within and adjacent to macroalgal farms was investigated to suggest optimal site-specific configuration of farms. The production potential of Saccharina latissima was largely driven by salinity and the highest production yields are expected in the westernmost Baltic Sea areas where salinity is > 23. The direct and interactive effects of light availability, temperature, salinity and nutrient concentrations regulated the predicted changes in the production of Ulva intestinalis and Fucus vesiculosus. The western and southern Baltic Sea exhibited the highest farming potential for these species, with promising areas also in the eastern Baltic Sea. Macroalgal farming did not induce significant nutrient limitation. The expected spatial propagation of nutrient limitation caused by macroalgal farming was less than 100-250 m. Higher propagation distances were found in areas of low nutrient and low water exchange (e.g. offshore areas in the Baltic Proper) and smaller distances in areas of high nutrient and high water exchange (e.g. western Baltic Sea and Gulf of Riga). The generated maps provide the most sought-after input to support blue growth initiatives that foster the sustainable development of macroalgal cultivation and reduction of in situ nutrient loads in the Baltic Sea. more
Application CM-SAF Climate Data Records Land

Assessing the representation of Arctic sea ice and the marginal ice zone in ocean–sea ice reanalyses

Author(s):
Cocetta, F.; Zampieri, L.; Selivanova, J.; Iovino, D.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 10
2024
DOI: 10.5194/tc-18-4687-2024
Abstract:
The recent development of data-assimilating reanalyses of the global ocean and sea ice enables a better understanding of the polar region dynamics and… The recent development of data-assimilating reanalyses of the global ocean and sea ice enables a better understanding of the polar region dynamics and provides gridded descriptions of sea ice variables without temporal and spatial gaps. Here, we study the spatiotemporal variability of the Arctic sea ice area and thickness using the Global ocean Reanalysis Ensemble Product (GREP) produced and disseminated by the Copernicus Marine Service (CMS). GREP is compared and validated against the state-of-the-art regional reanalyses PIOMAS and TOPAZ, as well as observational datasets of sea ice concentration and thickness for the period 1993–2020. Our analysis presents pan-Arctic metrics but also emphasizes the different responses of ice classes, the marginal ice zone (MIZ), and pack ice to climate changes. This aspect is of primary importance since the MIZ accounts for an increasing percentage of the summer sea ice as a consequence of the Arctic warming and sea ice extent retreat, among other processes. Our results show that GREP provides reliable estimates of present-day and recent-past Arctic sea ice states and that the seasonal to interannual variability and linear trends in the MIZ area are properly reproduced, with the ensemble spread often being as broad as the uncertainty of the observational dataset. The analysis is complemented by an assessment of the average MIZ latitude and its northward migration in recent years, a further indicator of the Arctic sea ice decline. There is substantial agreement between GREP and reference datasets in the summer. Overall, GREP is an adequate tool for gaining an improved understanding of the Arctic sea ice, also in light of the expected warming and the Arctic transition to ice-free summers. © Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License. more
Application Climate Data Records Cryosphere OSI-SAF Validation

Assessment of Atmospheric and Surface Energy Budgets Using Observation-Based Data Products

Author(s):
Mayer, Michael; Kato, Seiji; Bosilovich, Michael; Bechtold, Peter; Mayer, Johannes; Schröder, Marc; Behrangi, Ali; Wild, Martin; Kobayashi, Shinya; Li, Zhujun; L’Ecuyer, Tristan
Publication title: Surveys in Geophysics
2024
 | Volume: 45 | Issue: 6
2024
DOI: 10.1007/s10712-024-09827-x
Abstract:
Accurate diagnosis of regional atmospheric and surface energy budgets is critical for understanding the spatial distribution of heat uptake associated… Accurate diagnosis of regional atmospheric and surface energy budgets is critical for understanding the spatial distribution of heat uptake associated with the Earth’s energy imbalance (EEI). This contribution discusses frameworks and methods for consistent evaluation of key quantities of those budgets using observationally constrained data sets. It thereby touches upon assumptions made in data products which have implications for these evaluations. We evaluate 2001–2020 average regional total (TE) and dry static energy (DSE) budgets using satellite-based and reanalysis data. For the first time, a consistent framework is applied to the ensemble of the 5th generation European Reanalysis (ERA5), version 2 of modern-era retrospective analysis for research and applications (MERRA-2), and the Japanese 55-year Reanalysis (JRA55). Uncertainties of the computed budgets are assessed through inter-product spread and evaluation of physical constraints. Furthermore, we use the TE budget to infer fields of net surface energy flux. Results indicate biases  more
Application Atmosphere CM-SAF Climate Data Records Validation

Assessment of 24 soil moisture datasets using a new in situ network in the Shandian River Basin of China

Author(s):
Zheng, Jingyao; Zhao, Tianjie; Lü, Haishen; Shi, Jiancheng; Cosh, Michael H.; Ji, Dabin; Jiang, Lingmei; Cui, Qian; Lu, Hui; Yang, Kun; Wigneron, Jean-Pierre; Li, Xiaojun; Zhu, Yonghua; Hu, Lu; Peng, Zhiqing; Zeng, Yelong; Wang, Xiaoyi; Kang, Chuen Siang
Publication title: Remote Sensing of Environment
2022
 | Volume: 271
2022
DOI: 10.1016/j.rse.2022.112891
Climate Data Records H-SAF Land Validation
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