Global and regional ocean and sea ice reanalysis products (ORAs) are increasingly used in polar research, but their quality remains to be systematically assessed. To address this, the Polar ORA Intercomparison Project (Polar ORA-IP) has been established following on from the ORA-IP project. Several aspects of ten selected ORAs in the Arctic and Antarctic were addressed by concentrating on comparing their mean states in terms of snow, sea ice, ocean transports and hydrography. Most polar diagnostics were carried out for the first time in such an extensive set of ORAs. For the multi-ORA mean state, we found that deviations from observations were typically smaller than individual ORA anomalies, often attributed to offsetting biases of individual ORAs. The ORA ensemble mean therefore appears to be a useful product and while knowing its main deficiencies and recognising its restrictions, it can be used to gain useful information on the physical state of the polar marine environment.
The Three-North Shelter Forest Programme (TNSFP) covers 551 Chinese counties and an area of 4,069,000 km 2 mostly in arid and semi-arid regions. In this paper, we discuss the temporal and spatial changes in value of the normalized-difference vegetation index (NDVI) in this region, and the relationships between NDVI and climatic factors (temperature and precipitation) based on NOAA Advanced Very High Resolution Radiometer Global Inventory Modeling and Mapping Studies NDVI data with 8-km resolution from 1982 to 2006. During the past 25 years, the vegetation cover has generally increased in eastern regions of China and the oasis in the north piedmont of Tianshan Mountains, but has decreased northwest of Xinjiang and in the Hulunbeier Plateau. The multi-year monthly average NDVI distribution map showed that NDVI increased from April to August, but in the western and northern plateau areas, the lower temperatures and high altitude created a shorter growing season (1 or 2 months). The vegetation of the study area has generally increased in the regions covered by the TNSFP. Linear regression analysis of the vegetation cover showed an increasing trend over large areas. The largest annual growth rate per pixel (the slope of the regression) was 0.009; the largest negative annual change was -0.004. The correlation between NDVI and precipitation was higher than that between NDVI and temperature, suggesting that precipitation is the most important factor that affects NDVI changes in the study area, especially for temperate desert vegetation in northwestern China.
Abstract. Long dynamical atmospheric reanalyses are widely used for climate studies, but data-assimilative reanalyses of ocean and sea ice in the Arctic are less common. TOPAZ4 is a coupled ocean and sea ice data assimilation system for the North Atlantic and the Arctic that is based on the HYCOM ocean model and the ensemble Kalman filter data assimilation method using 100 dynamical members. A 23-year reanalysis has been completed for the period 1991-2013 and is the multi-year physical product in the Copernicus Marine Environment Monitoring Service (CMEMS) Arctic Marine Forecasting Center (ARC MFC). This study presents its quantitative quality assessment, compared to both assimilated and unassimilated observations available in the whole Arctic region, in order to document the strengths and weaknesses of the system for potential users. It is found that TOPAZ4 performs well with respect to near-surface ocean variables, but some limitations appear in the interior of the ocean and for ice thickness, where observations are sparse. In the course of the reanalysis, the skills of the system are improving as the observation network becomes denser, in particular during the International Polar Year. The online bias estimation successfully maintains a low bias in our system. In addition, statistics of the reduced centered random variables (RCRVs) confirm the reliability of the ensemble for most of the assimilated variables. Occasional discontinuities of these statistics are caused by the changes of the input data sets or the data assimilation settings, but the statistics remain otherwise stable throughout the reanalysis, regardless of the density of observations. Furthermore, no data type is severely less dispersed than the others, even though the lack of consistently reprocessed observation time series at the beginning of the reanalysis has proven challenging. IntroductionThe Arctic Ocean plays an important role in the global climate system, where the sea ice at the interface between atmosphere and ocean regulates the fluxes of heat, moisture and momentum. The recent warming of the Arctic and the change of its water cycle has been linked to the following manifestations: a significant reduction and thinning of the sea ice cover (Johannessen et al., 2004;Shimada et al., 2006;Rothrock et al., 2008;Kwok and Rothrock, 2009), more freshwater in the Arctic in the 2000s (Haine et al., 2015) and more mobility and faster deformations of the Arctic sea ice (Rampal et al., 2009;Spreen et al., 2011). The interpretation of such changes is severely hampered by the sparseness of the concerned observations, which should not be improved dramatically in the near future. It can be assisted by free-running model simulations, but those are usually hampered by mislocations of ice edge and certain water masses. One possibility is to study surrogate locations where similar processes are assumed to take place. Another solution is to correct the dynamical model by assimilating observations available over relevant timescales.The latter activities thu...
GEROS-ISS stands for GNSS REflectometry, radio occultation, and scatterometry onboard the International Space Station (ISS). It is a scientific experiment, successfully proposed to the European Space Agency in 2011. The experiment as the name indicates will be conducted on the ISS. The main focus of GEROS-ISS is the dedicated use of signals from the currently available Global Navigation Satellite Systems (GNSS) in L-band for remote sensing of the Earth with a focus to study climate change. Prime mission objectives are the determination of the altimetric sea surface height of the oceans and of the ocean surface mean square slope, which is related to sea roughness and wind speed. These geophysical parameters are derived using reflected GNSS signals (GNSS reflectometry, GNSS-R). Secondary mission goals include atmosphere/ionosphere sounding using refracted GNSS signals (radio occultation, GNSS-RO) and remote sensing of land surfaces using GNSS-R. The GEROS-ISS mission objectives and its design, the current status, and ongoing activities are reviewed and selected scientific and technical results of the GEROS-ISS preparation phase are described.
This paper summarizes recent efforts on Observing System Evaluation (OS-Eval) by the Ocean Data Assimilation and Prediction (ODAP) communities such as GODAE OceanView and CLIVAR-GSOP. It provides some examples of existing OS-Eval methodologies, and attempts to discuss the potential and limitation of the existing approaches. Observing System Experiment (OSE) studies illustrate the impacts of the severe decrease in the number of TAO buoys during 2012-2014 and TRITON buoys since 2013 on ODAP system performance. Multi-system evaluation of the impacts of assimilating satellite sea surface salinity data based on OSEs has been performed to demonstrate the need to continue and enhance satellite salinity missions. Impacts of underwater gliders have been assessed using Observing System Simulation Experiments (OSSEs) to provide guidance on the effective coordination of the western North Atlantic observing system elements. OSSEs are also being performed under H2020 AtlantOS Fujii et al.Observing System Evaluation project with the goal to enhance and optimize the Atlantic in-situ networks. Potential of future satellite missions of wide-swath altimetry and surface ocean currents monitoring is explored through OSSEs and evaluation of Degrees of Freedom for Signal (DFS). Forecast Sensitivity Observation Impacts (FSOI) are routinely evaluated for monitoring the ocean observation impacts in the US Navy's ODAP system. Perspectives on the extension of OS-Eval to coastal regions, the deep ocean, polar regions, coupled data assimilation, and biogeochemical applications are also presented. Based on the examples above, we identify the limitations of OS-Eval, indicating that the most significant limitation is reduction of robustness and reliability of the results due to their system-dependency. The difficulty of performing evaluation in near real time is also critical. A strategy to mitigate the limitation and to strengthen the impact of evaluations is discussed. In particular, we emphasize the importance of collaboration within the ODAP community for multi-system evaluation and of communication with ocean observational communities on the design of OS-Eval, required resources, and effective distribution of the results. Finally, we recommend further developing OS-Eval activities at international level with the support of the international ODAP (e.g., OceanPredict and CLIVAR-GSOP) and observational communities.
Abstract. An observation product for thin sea ice thickness (SMOS-Ice) is derived from the brightness temperature data of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. This product is available in near-real time, at daily frequency, during the cold season. In this study, we investigate the benefit of assimilating SMOS-Ice into the TOPAZ coupled ocean and sea ice forecasting system, which is the Arctic component of the Copernicus marine environment monitoring services. The TOPAZ system assimilates sea surface temperature (SST), altimetry data, temperature and salinity profiles, ice concentration, and ice drift with the ensemble Kalman filter (EnKF). The conditions for assimilation of sea ice thickness thinner than 0.4 m are favorable, as observations are reliable below this threshold and their probability distribution is comparable to that of the model. Two parallel Observing System Experiments (OSE) have been performed in March and November 2014, in which the thicknesses from SMOS-Ice (thinner than 0.4 m) are assimilated in addition to the standard observational data sets. It is found that the root mean square difference (RMSD) of thin sea ice thickness is reduced by 11 % in March and 22 % in November compared to the daily thin ice thicknesses of SMOS-Ice, which suggests that SMOS-Ice has a larger impact during the beginning of the cold season. Validation against independent observations of ice thickness from buoys and ice draft from moorings indicates that there are no degradations in the pack ice but there are some improvements near the ice edge close to where the SMOS-Ice has been assimilated. Assimilation of SMOS-Ice yields a slight improvement for ice concentration and degrades neither SST nor sea level anomaly. Analysis of the degrees of freedom for signal (DFS) indicates that the SMOS-Ice has a comparatively small impact but it has a significant contribution in constraining the system (> 20 % of the impact of all ice and ocean observations) near the ice edge. The areas of largest impact are the Kara Sea, Canadian Archipelago, Baffin Bay, Beaufort Sea and Greenland Sea. This study suggests that the SMOS-Ice is a good complementary data set that can be safely included in the TOPAZ system.
Abstract. We propose a satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40 km and more, with snapshots at least every day for latitudes 75 to 82°, and every few days for other latitudes. The use of incidence angles of 6 and 12° allows for measurement of the directional wave spectrum, which yields accurate corrections of the wave-induced bias in the current measurements. The instrument's design, an algorithm for current vector retrieval and the expected mission performance are presented here. The instrument proposed can reveal features of tropical ocean and marginal ice zone (MIZ) dynamics that are inaccessible to other measurement systems, and providing global monitoring of the ocean mesoscale that surpasses the capability of today's nadir altimeters. Measuring ocean wave properties has many applications, including examining wave–current interactions, air–sea fluxes, the transport and convergence of marine plastic debris and assessment of marine and coastal hazards.
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