Monitoring absolute vertical land motions and absolute sea-level changes from GPS and tide gauges data over French Polynesia

In this study,we estimate the absolute vertical land motions at three tidal stations with collocated Global Navigation Satellite System(GNSS)receivers over French Polynesia during the period 2007-2020,and obtain,as ancillary results,estimates of the absolute changes in sea level at the same locations.To verify our processing approach to determining vertical motion,we first modeled vertical motion at the International GNSS Service(IGS)THTI station located in the capital island of Tahiti and compared our estimate with previous independent determinations,with a good agreement.We obtained the following estimates for the vertical land motions at the tide gauges:Tubuai island,Austral Archipelago-0.92±0.17 mm/yr,Vairao village,Tahiti Iti:-0.49±0.39 mm/yr,Rikitea,Gambier Archipelago-0.43±0.17 mm/yr.The absolute variations of the sea level are:Tubuai island,Austral Archipelago 5.25±0.60 mm/yr,Vairao village,Tahiti Iti:3.62±0.52 mm/yr,Rikitea,Gambier Archipelago 1.52±0.23 mm/yr.We discuss these absolute values in light of the values obtained from altimetric measurements and other means in French Polynesia.

Comprehensive Risk Assessment of Sea Level Rise and Tropical Cyclones in Dongzhaigang Mangroves,China

Mangroves play a pivotal role in tropical and subtropical coastal ecosystem,yet they are highly vulnerable to the effects of climate change,particularly the accelerated global sea level rise(SLR)and stronger tropical cyclones(TCs).However,there is a lack of research addressing future simultaneous combined impacts of the slow-onset of SLR and rapid-onset of TCs on China's mangroves.In order to develop a comprehensive risk assessment method considering the superimposed effects of these two factors and analyze risk for mangroves in Dongzhaigang,Hainan Island,China,we used observational and climate model data to assess the risks to mangroves under low,intermediate,and very high greenhouse gas(GHG)emission scenarios(such as SSP1-2.6,SSP2-4.5,and SSP5-8.5)in 2030,2050,and 2100,and compiled a risk assessment scheme for mangroves in Dongzhaigang,China.The results showed that the combined risks from SLR and TCs will continue to rise;however,SLRs will increase in intensity,and TCs will decrease.The comprehensive risk of the Dongzhaigang mangroves posed by climate change will remain low under SSP1-2.6 and SSP2-4.5 scenarios by 2030,but it will increase substantially by 2100.While under SSP5-8.5 scenario,the risks to mangroves in Dongzhaigang are projected to increase considerably by 2050,and approximately 68.8%of mangroves will be at very high risk by 2100.The risk to the Dongzhaigang mangroves is not only influenced by the hazards but also closely linked to their exposure and vulnerability.We therefore propose climate resilience developmental responses for mangroves to address the effects of climate change.This study for the combined impact of TCs and SLR on mangroves in Dongzhaigang,China can enrich the method system of mangrove risk assessment and provide references for scientific management.

Exploring Variability in Sea Level at a Tide Gauge Station through Control Charts

Monitoring temporal changes in sea level is important in assessing coastal risk.Sea level anomalies at a tide gauge station,if kinematically conceived,include systematic variations such as trend,acceleration,periodic oscillations,and random disturbances.Among them,the non-stationary nature of the random sea level variations of known or unknown origin at coastal regions has been long recognized by the sea level community.This study proposes the analyses of subgroups of random residual statistics of a rigorously formulated kinematic model solution of tide gauge variations using X-bar and S control charts.The approach is demonstrated using Key West,Florida tide gauge records.The mean and standard errors of 5-year-long subgroups of the residuals revealed that sea level changes at this location have been progressively intensifying from 1913 to the present.Increasing oscillations in sea level at this locality may be attributed partly to the thermal expansion of seawater with increasing temperatures causing larger buoyancy-related sea level fluctuations as well as the intensification of atmospheric events including wind patterns and the impact of changes in inverted barometer effects that will alter coastal risk assessments for the future.

Effects of Natural Processes on Sea Level Change along the West African Coastline

Coastal hazards induced by meteo-marine forcing are exacerbated by sea level change along the West African coastline. Changes in sea level are induced by ocean processes such as ocean heat content and river discharge. However, although these processes control largely change in sea level, they remain poorly understood. This study analyzes changes in ocean heat content, river discharge, and sea level and establishes an interconnection between these parameters using several statistical methods over the 1993-2021 period. Results showed a significant correlation between sea level and ocean heat content at 2000 m depth. The yearly minimum value appears in July from Cote d’Ivoire to Benin, whilst this value appears in June in Nigeria. The temporal variability of ocean heat content, river discharge and sea level along the West African coastline exhibits three or four periods interrupted by some breakpoints with unequal duration. The results indicate that the 1993-2000 period was dominated by an increasing ocean heat content along the coastline, while the period after the 2000s exhibits mostly a decreasing trend. Positive and negative trends characterized river discharge and sea level along this coastline. The result of multiple linear regression between sea level, river discharge and ocean heat content is a good approximation of sea level trend along the West African coastline. The results of this study could be used to predict future sea level trends along the coast.

The Impact of Sea Level Rise on Roadway Design and Evacuation Routes in Delaware

As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.

Performance of CMIP6 models in simulating the dynamic sea level:Mean and interannual variance

本研究采用卫星测高数据与第六次国际耦合模式比较计划(CMIP6)海平面动力进行对比,重点针对40S-40N地区的动力海平面(DSL),评估了模式对其平均态与年际变率的综合模拟能力,结果表明,对于DSL平均态的模拟,模式与观测结果非常吻合,模式之间的差异较小.其中,副热带北大西洋是模拟偏差和模式间差异较为显著的区域,对于DSL年际变率的模拟,模式之间保持较高的一致性,但是,模式与观测结果存在明显差异,模式普遍低估了DSL的年际方差;其中,误差大值区域出现在副热带西边界流附近,模式分辨率会影响CMIP6对中小尺度海洋过程的重现能力,这可能是导致CMIP6历史模拟出现误差的原因之一.

Can a global mean sea-level rise reduce the Last Interglacial model-data mismatch in East Asia?

末次间冰期有着丰富的重建和模拟资料,为研究未来温暖气候提供了一个理想的参考.然而,关于末次间冰期的东亚气候,模拟与重建的结果间长期存在着不匹配的情况,模拟结果普遍较重建结果更为冷干。本研究利用挪威地球系统模式(NorESM1-F),探讨了在末次间冰期模拟试验中纳入全球平均海平面上升能否减少模式-数据的不匹配.该试验结果表明,海平面上升情况下东亚地区会产生一定的增温增湿效应,但不足以消除模式-数据不匹配.基于这些结果,作者探讨了其它可能造成不匹配的因素以供进一步研究.

Numerical Simulation of the Influence of Mean Sea Level Rise on Typhoon Storm Surge in the East China Sea

In this paper, ECOMSED （Estuarine Coastal Ocean Model with sediment transport） model is employed to simulate storm surge process caused by typhoon passing across East China Sea in nearly years. Capability of ECOMSED to simulate storm surge is validated by comparing model result with observed data. Sensitivity experiments are designed to study the influence of sea level rise on typhoon storm surge. Numerical experiment shows that influence of mean sea level rise on typhoon storm surge is non-uniform spatially and changes as typhoon process differs. Maybe fixed boundary method would weaken the influence of mean sea level rise on storm surge, and free boundary method is suggested for the succeeding study.

Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence

Relationship between sea level change and a single climate indicator has been widely discussed.However,few studies focused on the relationship between monthly mean sea level(MMSL)and several key impact factors,including CO_(2) concentration,sea ice area,and sunspots,on various time scales.In addition,research on the independent relationship between climate factors and sea level on various time scales is lacking,especially when the dependence of climate factors on Nino 3.4 is excluded.Based on this,we use wavelet coherence(WC)and partial wavelet coherence(PWC)to establish a relationship between MMSL and its influencing factors.The WC results show that the influence of climate indices on MMSL has strong regional characteristics.The significant correlation between Southern Hemisphere sea ice area and MMSL is opposite to that between Northern Hemisphere sea ice area and MMSL.The PWC results show that after removing the influence of Nino 3.4,the significant coherent regions of the Pacific Decadal Oscillation(PDO),Dipole Mode Index(DMI),Atlantic Multidecadal Oscillation(AMO),and Southern Oscillation Index(SOI)decrease to varying degrees on different time scales in different regions,demonstrating the influence of Nino 3.4.Our work emphasizes the interrelationship and independent relationship between MMSL and its influencing factors on various time scales and the use of PWC and WC to describe this relationship.The study has an important reference significance for selecting the best predictors of sea level change or climate systems.

The impact of mean dynamic topography on a sea-level anomaly assimilation in the South China Sea based on an eddy-resolving model

The sea-level anomaly （SLA） from a satellite altimeter has a high accuracy and can be used to improve ocean state estimation by assimilation techniques. However, the lack of an accurate mean dynamic topography （MDT） is still a bothersome issue in an ocean data assimilation. The previous studies showed that the errors in MDT have significant impacts on assimilation results, especially on the time-mean components of ocean states and on the time variant parts of states via nonlinear ocean dynamics. The temporal-spatial differences of three MDTs and their impacts on the SLA analysis are focused on in the South China Sea （SCS）. The theoretical analysis shows that even for linear models, the errors in MDT have impacts on the SLA analysis using a sequential data assimilation scheme. Assimilation experiments, based on EnOI scheme and HYCOM, with three MDTs from July 2003 to June 2004 also show that the SLA assimilation is very sensitive to the choice of different MDTs in the SCS with obvious differences between the experimental results and observations in the centre of the SCS and in the vicinity of the Philippine Islands. A new MDT for assimilation of SLA data in the SCS was proposed. The results from the assimilation experiment with this new MDT show a marked reduction （increase） in the RMSEs （correlation coefficient） between the experimental and observed SLA. Furthermore, the subsurface temperature field is also improved with this new MDT in the SCS.

MEAN SEA LEVEL AND SEA SURFACE VARIABILITY OF NORTHWEST PACIFIC OCEAN AND EASTERN CHINA SEAS FROM GEOSAT ALTIMETRY

Collinear analysis technique is widely used for determining sea surface variability with Geosat altimeter data from its Exact Repeat Mission (ERM). But most of the researches have been only on global scale or in oceans deeper than 2000 m In shallow shelf waters this method is hampered by the inaccuracy of ocean tide data supplied with Geosat Geophysical Data Records (GDRs). This work uses a modified collinear analysis technique characterized by simultaneous separation of mean sea level and ocean tide with the least squares method, to compute sea surface variability in the Northwest Pacific Ocean and eastern China Seas. The mean sea level map obtained contains not only bathymetric but also dynamic features such as amphidromes, indicating considerable improvement over previous works. Our sea surface variability maps show dearly the main current system, the well-known Zhejiang coastal upwelling, and a northern East China Sea meso-scale eddy in good agreement with satellite sea surface temperature (SST) bservation and historical in situ measurement. These all suggest that meaningful and reliable oceanographic results can still be achieved in shallow shelf waters from Geosat altimetry as long as proper data processing techniques are applied.

Arctic Sea Level Variability from Oceanic Reanalysis and Observations

Quantifying the contributions to Arctic sea level(ASL)variability is critical to understand how the Arctic is responsing to ongoing climate change.Here,we use Ocean Reanalysis System 5(ORAS5)reanalysis data and tide gauge and satellite altimetry observations to quantify contributions from different physical processes on the ASL variability.The ORAS5 reanalysis shows that the ASL is rising with a trend of 2.5±0.3 mm yr−1(95%confidence level)over 1979-2018,which can be attributed to four components:(i)the dominant component from the global sea level increase of 1.9±0.5 mm yr−1,explaining 69.7%of the total variance of the ASL time series;(ii)the Arctic Oscillation-induced mass redistribution between the deep central basin and shallow shelves,with no significant trend and explaining 6.3%of the total variance;(iii)the steric sea level increase centering on the Beaufort Gyre region with a trend of 0.5±0.1 mm yr−1 and explaining 29.1%of the total variance of the ASL time series;and(iv)the intrusion of Pacific water into the Arctic Ocean,with no significant trend and contributing 14.2%of the total ASL variability.Furthermore,the dramatic sea ice melting and the larger area of open water changes the impact of the large-scale atmospheric forcing on the ASL variability after 1995,and the ocean dynamic circulation plays a more important role in the ASL variability.

Organic Carbon Deposition on the Inner Shelf of the East China Sea Constrained by Sea Level and Climatic Changes Since the Last Deglaciation

The East China Sea(ECS),which is located in the transitional zone between land and ocean,is the main site for the burial of sedimentary organic carbon.Despite good constraints of the modern source to the sinking process of organic carbon,its fate in response to changes in climate and sea level since the last deglaciation remains poorly understood.We aim to fill this gap by presenting a high-resolution sedimentary record of core EC2005 to derive a better understanding of the evolution of the depositional environment and its control on the organic deposition since 17.3 kyr.Our results suggest that sedimentary organic carbon was deposited in a terrestrial environment before the seawater reached the study area around 13.1 kyr.This significant transition from a terrestrial environment to a marine environment is reflected by the decrease in TOC/TN and TOC/TS ratios,which is attributed to deglacial sea level rise.The sea level continued to rise until it reached its highstand at approximately 7.3 kyr when the mud depocenter was developed.Our results further indicate that the deposition of the sedimentary organic carbon could respond quickly to abrupt cold events,including the Heinrich stadial 1 and the Younger Dryas during the last deglaciation,as well as‘Bond events'during the Holocene.We propose that the rapid response of the organic deposition to those cold events in the northern hemisphere is linked to the East Asian winter monsoon.These new findings demonstrate that organic carbon deposition and burial on the inner shelf could effectively document sea level and climatic changes.

A new decomposition model of sea level variability for the sea level anomaly time series prediction

Rising sea level is of great significance to coastal societies;predicting sea level extent in coastal regions is critical.When carrying out predictions,the subsequences obtained using decomposition methods may exhibit a certain regularity and therefore can provide multidimensional information that can be used to improve prediction models.Traditional decomposition methods such as seasonal and trend decomposition using Loess(STL)focus mostly on the fluctuating trend of time series and ignore its impact on prediction.Methods in the signal decomposition domain,such as variational mode decomposition(VMD),have no physical significance.In response to the above problems,a new decomposition method for sea level anomaly time series prediction(DMSLAP)is proposed.With this method,the trend term in a time series can be isolated and the effects of abnormal sea level change behaviors can be attenuated.We decompose multiperiod characteristics using this method while maintaining the smoothness of the analyzed series.Satellite altimetry data from 1993 to 2020 are used in experiments conducted in the study area.The results are then compared with predictions obtained using existing decomposition methods such as the STL and VMD methods and time varying filtering based on empirical mode decomposition(TVF-EMD).The performance of DMSLAP combined with a prediction method resulted in optimal sea level anomaly(SLA)predictions,with a minimum root mean square error(RMSE)of 1.40 cm and a maximum determination coefficient(R^(2))of 0.93 during 2020.The DMSLAP method was more accurate when predicting 1-year data and 3-year data.The TVF-EMD and DMSLAP methods had comparable accuracies,and the periodic term decomposed by the DMSLAP method was more in line with the actual law than that derived using the TVF-EMD method.Thus,DMSLAP can decompose SLA time series better than existing methods and is an effective tool for obtaining short-term SLA prediction.

Gravity anomalies determined from mean sea surface model data over the Gulf of Mexico

With the improvements in the density and quality of satellite altimetry data,a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data.Therefore,in this study,a method was proposed for determining marine gravity anomalies from a mean sea surface model.Taking the Gulf of Mexico(15°–32°N,80°–100°W)as the study area and using a removal-recovery method,the residual gridded deflections of the vertical(DOVs)are calculated by combining the mean sea surface,mean dynamic topography,and XGM2019e_2159 geoid,and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs.Finally,residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models.In this study,the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS,DTU21MSS,and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT.The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data.The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal.With an increase in the distance from the coast,the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases.The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km.The accuracy of the gravity anomalies derived by the mean sea surface model is high.

The effects of mean sea level rise and strengthened winds on extreme sea levels in the Baltic Sea

Mean sea level rise and climatological wind speed changes occur as part of the ongoing climate change and future projections of both variables are still highly uncertain. Here the Baltic Sea’s response in extreme sea levels to perturbations in mean sea level and wind speeds is investigated in a series of simulations with a newly developed storm surge model based on the nucleus for European modeling of the ocean(NEMO)-Nordic. A simple linear model with only two tunable parameters is found to capture the changes in the return levels extremely well. The response to mean sea level rise is linear and nearly spatially uniform, meaning that a mean sea level rise of 1 m increases the return levels by a equal amount everywhere. The response to wind speed perturbations is more complicated and return levels are found to increase more where they are already high. This behaviour is alarming as it suggests that already flooding prone regions like the Gulf of Finland will be disproportionally adversely affected in a future windier climate.

Prediction of the joint impacts of sea level rise and land development on distribution patterns of mangrove communities

Mangrove distribution along shorelines shows distinct zonation patterns;thus,different communities may face various influences from sea level rise(SLR)and land use.However,long-term change predictions are usually based only on the total extent of mangroves.Few studies have revealed how SLR and land development such as agriculture,aquaculture,and urbanization jointly affect different intertidal mangrove communities.This study proposed a novel framework combining SLAMM(Sea Level Affecting Marshes Model)and the CLUE-S(Conversion of Land Use and its Effect at Small regional extent)model to assess the potential impacts on upper and lower intertidal mangrove communities.Maoweihai in Guangxi,China,was selected as the study area and the potential impacts from the squeeze effect and mangrove expansion potential were evaluated.We established three scenarios combining SLR and land use patterns to predict mangrove coverage projections by 2070.The results showed that,under a single SLR driver,the upper intertidal mangroves would be more adaptive to rapid SLR than the lower intertidal mangroves.However,under the combined influence of the two drivers,the upper intertidal mangroves would experience larger squeeze effects than the lower intertidal mangroves,with up to 80.5%of suitable habitat lost.Moreover,the expansion potential of upper intertidal mangroves would be considerably more limited than that of lower intertidal mangroves.The length of the expandable habitat patch boundary of upper intertidal mangroves only reached 1.4–1.8 km,while that of the lower intertidal mangroves reached up to99.2–111.2 km.Further,we found that aquaculture ponds and cropland are the top two land development types that could occupy suitable habitat and restrict the mangrove expansion potential.Our results highlight that timely improvement of land use policies to create available landward accommodation space for mangrove migration is essential to maintain the coverage and diversity of mangrove communities under SLR.The proposed method can be a helpful tool for adaptive mangrove conservation and management under climate change.

Inferring the global mean sea level from a global tide gauge network

An attempt is made to infer the global mean sea level（GMSL） from a global tide gauge network and frame the problem in terms of the limitations of the network. The network,owing to its limited number of gauges and poor geographical distribution complicated further by unknown vertical land movements,is ill suited for measuring the GMSL. Yet it remains the only available source for deciphering the sea level rise over the last 100 a. The poor sampling characteristics of the tide gauge network have necessitated the usage of statistical inference. A linear optimal estimator based on the Gauss-Markov theorem seems well suited for the job. This still leaves a great deal of freedom in choosing the estimator. GMSL is poorly correlated with tide gauge measurements because the small uniform rise and fall of sea level are masked by the far larger regional signals. On the other hand,a regional mean sea level（RMSL） is much better correlated with the corresponding regional tide gauge measurements. Since the GMSL is simply the sum of RMSLs,the problem is transformed to one of estimating the RMSLs from regional tide gauge measurements. Specifically for the annual heating and cooling cycle,we separate the global ocean into 10-latitude bands and compute for each 10-latitude band the estimator that predicts its RMSL from tide gauges within. In the future,the statistical correlations are to be computed using satellite altimetry. However,as a first attempt,we have used numerical model outputs instead to isolate the problem so as not to get distracted by altimetry or tide gauge errors. That is,model outputs for sea level at tide gauge locations of the GLOSS network are taken as tide gauge measurements,and the RMSLs are computed from the model outputs. The results show an estimation error of approximately 2 mm versus an error of 2.7 cm if we simply average the tide gauge measurements to estimate the GMSL,caused by the much larger regional seasonal cycle and mesoscale variation plaguing the individual tide gauges. The numerical model,Los Alamos POP model Run 11 lasting 3 1/4 a,is one of the best eddy-resolving models and does a good job simulating the annual heating and cooling cycle,but it has no global or regional trend. Thus it has basically succeeded in estimating the seasonal cycle of the GMSL. This is still going to be the case even if we use the altimetry data because the RMSLs are dominated by the seasonal cycle in relatively short periods. For estimating the GMSL trend,longer records and low-pass filtering to isolate the statistical relations that are of interest. Here we have managed to avoid the much larger regional seasonal cycle plaguing individual tide gauges to get a fairly accurate estimate of the much smaller seasonal cycle in the GMSL so as to enhance the prospect of an accurate estimate of GMSL trend in short periods. One should reasonably expect to be able to do the same for longer periods during which tide gauges are plagued by much larger regional interannual（e. g.,ENSO events） and decadal sea level variations. In the future,with the availability of the satellite altimeter data,we could use the same approach adopted here to estimate the seasonal variations of GMSL and RMSL accurately and remove these seasonal variations accordingly so as to get a more accurate statistical inference between the tide gauge data and the RMSLs（therefore the GMSL） at periods longer than 1 a,i. e.,the long-term trend.

Potential effects of sea level rise on the soil-atmosphere green-house gas emissions in Kandelia obovata mangrove forests

Mangrove forests are under the stress of sea level rise(SLR)which would affect mangrove soil biogeochemistry.Mangrove soils are important sources of soil-atmosphere greenhouse gas(GHG)emissions,including carbon dioxide(CO_(2)),methane(CH_(4))and nitrous oxide(N_(2)O).Understanding how SLR influences GHG emissions is critical for evaluating mangrove blue carbon capability.In this study,potential effects of SLR on the GHG emissions were quantified through static closed chamber technique among three sites under different intertidal elevations,representing tidal flooding situation of SLR values of 0 cm,40 cm and 80 cm,respectively.Compared with Site SLR 0 cm,annual CO_(2) and N_(2)O fluxes decreased by approximately 75.0%and 27.3%due to higher soil water content,lower salinity and soil nutrient environments at Site SLR 80 cm.However,CH_(4) fluxes increased by approximately 13.7%at Site SLR 40 cm and 8.8%at Site SLR 80 cm because of lower salinity,higher soil water content and soil pH.CO_(2)-equivalent fluxes were 396.61 g/(m^(2)·a),1423.29 g/(m^(2)·a)and 1420.21 g/(m^(2)·a)at Sites SLR 80 cm,SLR 40 cm and SLR 0 cm,respectively.From Site SLR 0 cm to Site SLR 80 cm,contribution rate of N_(2)O and CH_(4) increased by approximately 7.42%and 3.02%,while contribution rate of CO_(2) decreased by approximately 10.44%.The results indicated that warming potential of trace CH_(4) and N_(2)O was non-negligible with SLR.Potential effects of SLR on the mangrove blue carbon capability should warrant attention due to changes of all three greenhouse gas fluxes with SLR.

Multi-mode Multi-frequency GNSS-IR Combination System for Sea Level Retrieval

With the development of Global Navigation Satellite Systems(GNSS),geodetic GNSS receivers have been utilized to monitor sea levels using GNSS-Interferometry Reflectometry(GNSS-IR)technology.The multi-mode,multi-frequency signals of GPS,GLONASS,Galileo,and Beidou can be used for GNSS-IR sea level retrieval,but combining these retrievals remains problematic.To address this issue,a GNSS-IR sea level retrieval combination system has been developed,which begins by analyzing error sources in GNSS-IR sea level retrieval and establishing and solving the GNSS-IR retrieval equation.This paper focuses on two key points:time window selection and equation stability.The stability of the retrieval combination equations is determined by the condition number of the coefficient matrix within the time window.The impact of ill-conditioned coefficient matrices on the retrieval results is demonstrated using an extreme case of SNR data with only ascending or descending trajectories.After determining the time window and removing ill-conditioned equations,the multi-mode,multi-frequency GNSS-IR retrieval is performed.Results from three International GNSS Service(IGS)stations show that the combination method produces high-precision,high-resolution,and high-reliability sea level retrieval combination sequences.