Larger Root Mean Square Research Articles

A novel watermarking algorithm for three-dimensional point-cloud models based on vertex curvature

A new blind watermarking scheme for three-dimensional point-cloud models is proposed based on vertex curvature to achieve an appropriate trade-off between transparency and robustness. The root mean square curvature of local set of every vertex is first calculated for the three-dimensional point-cloud model and then the vertices with larger root mean square curvature are used to carry the watermarking information; the vertices with smaller root mean square curvature are exploited to establish the synchronization relation between the watermark embedding and extraction. The three-dimensional point-cloud model is divided into ball rings, and the watermarking information is inserted by modifying the radial radii of vertices within ball rings. Those vertices taking part in establishing the synchronization relation do not carry the watermarking information; therefore, the synchronization relation is not affected by the embedded watermark. Experimental results show the proposed method outperforms other well-known three-dimensional point-cloud model watermarking methods in terms of imperceptibility and robustness, especially for against geometric attack.

Effects of Dummy Thermal Vias on Interconnect Delay and Power Dissipation of Very Large Scale Integration Circuits

The interconnect temperature of very large scale integration (VLSI) circuits keeps rising due to self-heating and substrate temperature, which can increase the delay and power dissipation of interconnect wires. The thermal vias are regarded as a promising method to improve the temperature performance of VLSI circuits. In this paper, the extra thermal vias were used to decrease the delay and power dissipation of interconnect wires of VLSI circuits. Two analytical models were presented for interconnect temperature, delay and power dissipation with adding extra dummy thermal vias. The influence of the number of thermal vias on the delay and power dissipation of interconnect wires was analyzed and the optimal via separation distance was investigated. The experimental results show that the adding extra dummy thermal vias can reduce the interconnect average temperature, maximum temperature, delay and power dissipation. Moreover, this method is also suitable for clock signal wires with a large root mean square current.

Evaluating the Potential of ALS Data to Increase the Efficiency of Aboveground Biomass Estimates in Tropical Peat–Swamp Forests

Estimates of aboveground biomass (AGB) in forests are critically required by many actors including forest managers, forest services and policy makers. Because the AGB of a forest cannot be observed directly, models need to be employed. Allometric models that predict the AGB of a single tree as a function of diameter at breast height (DBH) are commonly used in forest inventories that use a probability selection scheme to estimate total AGB. However, for forest areas with limited accessibility, implementing such a field-based survey can be challenging. In such cases, models that use remotely sensed information may support the biomass assessment if useful predictor variables are available and statistically sound estimators can be derived. Airborne laser scanning (ALS) has become a prominent auxiliary data source for forest biomass assessments and is even considered to be one of the most promising technologies for AGB assessments in forests. In this study, we combined ALS and forest inventory data from a logged-over tropical peat swamp forest in Central Kalimantan, Indonesia to estimate total AGB. Our objective was to compare the precision of AGB estimates from two approaches: (i) from a field-based inventory only and, (ii) from an ALS-assisted approach where ALS and field inventory data were combined. We were particularly interested in analyzing whether the precision of AGB estimates can be improved by integrating ALS data under the particular conditions. For the inventory, we used a standard approach based on a systematic square sample grid. For building a biomass-link model that relates the field based AGB estimates to ALS derived metrics, we used a parametric nonlinear model. From the field-based approach, the estimated mean AGB was 241.38 Mgha − 1 with a standard error of 11.17 Mgha − 1 (SE% = 4.63%). Using the ALS-assisted approach, we estimated a similar mean AGB of 245.08 Mgha − 1 with a slightly smaller standard error of 10.57 Mgha − 1 (SE% = 4.30%). Altogether, this is an improvement of precision of estimation, even though the biomass-link model we found showed a large Root Mean Square Error (RMSE) of 47.43 Mgha − 1 . We conclude that ALS data can support the estimation of AGB in logged-over tropical peat swamp forests even if the model quality is relatively low. A modest increase in precision of estimation (from 4.6% to 4.3%), as we found it in our study area, will be welcomed by all forest inventory planners as long as ALS data and analysis expertise are available at low or no cost. Otherwise, it gives rise to a challenging economic question, namely whether the cost of the acquisition of ALS data is reasonable in light of the actual increase in precision.

Image recognition method using Local Binary Pattern and the Random forest classifier to count post larvae shrimp

Thailand is one of the world's largest shrimp producers. However, Thailand's fishery industry, which includes the shrimp industry, is still using human labor intensively. The culture process starts with getting shrimp that are at the early “post-larvae” stage from a supplier and growing them in a closed environment. One of the most basic tasks, counting the number of larvae, is tedious labor-intensive work. To increase the effectiveness of this traditional task, the use of image recognition techniques for larvae counting was investigated through the evaluation of two feature extraction methods: Local Binary Pattern (LBP) and Red, Green, Blue (RGB) feature extraction, with an ensemble tree classifier, Random Forest (RF). Assessing the results with K-fold cross validation (k = 5) showed the LBP method was 98.50% accurate. This research had a relatively large root mean square error (RMSE) of 14.43 due to the overlapping of shrimp. This method has the potential to help with this basic and essential task and increase the efficiency of the shrimp farming process.

A bioinspired structure modification of piezoelectric wind energy harvester based on the prototype of leaf veins

This paper describes a novel leaf-like piezoelectric wind energy harvester based on the venation growth algorithm, which are derived from the prototype of dicotyledonous plant leaves that have the netted distributions of veins. Some triangle polyvinylidene fluoride (PVDF) leaves are designed and fabricated to be the energy harvesting element that is driven by the vortex induced vibration in the wind flow behind a bluff body. Wind tunnel experiments were carried out to investigate and compare the performances of energy harvesting capacity of different elements. Experimental results show that the output powers of the veined structures are 4–6 times higher than that of the structure without veins. The largest root mean square of open circuit output voltage reaches 1.094 V under the wind velocity of 11 m/s for the 110 μm thickness PVDF leaf with veins. The dynamic analysis indicates that the veins can greatly influence the mechanical coupling properties between the harvesters and the wind flow although the system has not reached a typical state of instability. It is confirmed that the presence of veins has an important effect on the efficiency of the energy harvesting system.

Gait alterations on irregular surface in people with Parkinson's disease

BackgroundPersons with Parkinson's disease are at high risk for fall-related injuries with a large proportion of falls occurring while walking, especially when the walking environments are complex. The aim of this study was to characterize gait parameters on irregular surface for persons with Parkinson's disease. MethodsThree-dimensional gait analysis was conducted for nine persons with Parkinson's disease and nine healthy age-matched adults on both regular and irregular surfaces. Repeated ANOVA and paired t-test were performed to determine the effect of surface and group for spatiotemporal, kinematic and stability variables. FindingsIndividuals with Parkinson's disease showed a larger ratio of reduction for speed, cadence and step length than controls when the surface changed from regular to irregular. The ankle transverse range of motion and root mean square of trunk acceleration increased on irregular surface for both groups. Additionally, individuals with Parkinson's disease demonstrated a decreased knee sagittal range of motion and trunk frontal and transverse range of motion compared with controls, especially on the irregular surface. InterpretationThe irregular surface posed a greater challenge to maintain balance and stability for individuals with Parkinson's disease. A relatively small knee range of motion in the sagittal plane and large root mean square of trunk acceleration increased the potential fall risk for individuals with Parkinson's disease. This information improves the understanding of parkinsonian gait adaptations on irregular surfaces and may guide gait training and rehabilitation interventions for this high fall-risk population.

Real‐time PPP based on the Quasi‐Zenith Satellite System MADOCA‐LEX signal

This study assessed the satellite orbit and clock corrections of the L-band experiment (LEX) signal correction messages broadcasted by the Japan Quasi-Zenith Satellite System (QZSS) by comparing them with those of the international global navigation satellite system (GNSS) service real-time (IGS-RT) products. Using datasets collected at a fixed static station and a kinematic vehicle experiment, the authors evaluated the application of multi-GNSS advanced demonstration of orbit and clock analysis (MADOCA) products in precise point positioning (PPP) through static and kinematic data processing modes. The results show that the MADOCA-LEX products bring slightly larger root mean square and standard deviation of three-dimensional positions than the IGS-RT products. For kinematic PPP positioning, the convergence time was longer than IGS-RT products. However, from the global scope, the positioning accuracy of the MADOCA-LEX products, at a level of 20 cm, is comparable with that of the IGS-RT products, which satisfies the need of global PPP.

Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts

On-farm nutrition and management interventions to reduce enteric CH4 (eCH4) emission, the most abundant greenhouse gas from cattle, may also affect volatile solids and N excretion. The objective was to jointly quantify eCH4 emissions, digestible volatile solids (dVS) excretion and N excretion from dairy cattle, based on dietary variables and animal characteristics, and to evaluate relationships between these emissions and excreta. Univariate and Bayesian multivariate mixed-effects models fitted to 520 individual North American dairy cow records indicated dry matter (DM) intake and dietary ADF and CP to be the main predictors for production of eCH4 emissions and dVS and N excreta (g/day). Yields (g/kg DM intake) of eCH4 emissions and dVS and N excreta were best predicted by dietary ADF, dietary CP, milk yield and milk fat content. Intensities (g/kg fat- and protein-corrected milk) of eCH4, dVS and N excreta were best predicted by dietary ADF, dietary CP, days in milk and BW. A K-fold cross-validation indicated that eCH4 and urinary N variables had larger root mean square prediction error (RMSPE; % of observed mean) than dVS, fecal N and total N production (on average 24.3% and 26.5% v. 16.7%, 15.5% and 16.2%, respectively), whereas intensity variables had larger RMSPE than production and yields (29.4%, 14.7% and 14.6%, respectively). Univariate and multivariate equations performed relatively similar (18.8% v. 19.3% RMSPE). Mutual correlations indicated a trade-off for eCH4v. dVS yield. The multivariate model indicated a trade-off between eCH4 and dVS v. total N production, yield and intensity induced by dietary CP content.

Evaluation of the Runoff and River Routing Schemes in the Community Land Model of the Yellow River Basin

AbstractRunoff and river routing schemes play important roles in land surface models (LSMs) because they regulate the soil moisture, heat flux, and vegetation dynamics of land surface processes and account for the carbon and nutrient transport in river channels. However, these schemes are often simplistic and conceptual. Hence, in this study, we focused on (1) evaluating these schemes in the Community Land Model (CLM) and (2) altering the model representations using physically based schemes based on a study of the Yellow River basin. For runoff simulation, CLM exhibits limitations in water‐limited areas, especially areas with aridity index values greater than 2. Additionally, CLM greatly overestimates runoff, and produces negative Nash‐Sutcliffe efficiency (NSE) coefficients, few quick flow variations, high quick flow index values, and large root mean square errors of total water storage. These issues were greatly improved by implementing schemes of physically based overland flow, lateral soil water flow, and interchange between groundwater and river water. Furthermore, for the river routing scheme, the use of 1‐D kinematic wave routing improved previously unrealistic aspects of the flood hydrographs (e.g., incorrect flood peak values and times) of the original CLM. Moreover, compared with using the grid element‐based river routing approach in CLM, the computational costs were reduced by up to 45% by implementing the flow interval element method. Finally, our results indicate that parameter calibration in CLM minimally improved the simulation performance in water‐limited areas, while physically based schemes generated better results.

Comparison of shipborne GNSS-derived precipitable water vapor with radiosonde in the western North Pacific and in the seas adjacent to Japan

We installed two global navigation satellite system (GNSS) antennas on a research vessel, the RYOFU MARU of the Japan Meteorological Agency, and conducted experimental observations to assess the GNSS-derived precipitable water vapor (PWV) from October 19, 2016, to August 6, 2017. One antenna was set on the mast (MAST), while another antenna was set on the upper deck (DECK). The GNSS analysis was conducted using the precise point positioning procedure with a real-time GNSS orbit. A quality control (QC) procedure based on the amount of zenith tropospheric delay (ZTD) time variation was proposed. After the QC was applied, the retrieved PWVs were compared to 77 radiosonde observations. The PWVs of MAST agreed with the radiosonde observations with a 1.7 mm root mean square (RMS) difference, a − 0.7-mm bias, and 3.6% rejection rate, while that of DECK showed a 3.2, − 0.8 mm, and 15.7%. The larger RMS and higher rejection rate of DECK imply a stronger multi-path effect on the deck. The differences in the GNSS PWV versus radiosonde observations were compared to the atmospheric delay, the estimated altitude of the GNSS antenna, the vessel’s moving speed, the wind speed, and the wave height. The atmospheric delay and GNSS antenna altitude showed moderate correlation with the differences. The results suggest the kinematic PPP’s potential for practical water vapor monitoring over oceans worldwide. At the same time, from the growing negative biases with the PWV value and with estimated antenna altitude, it could be inferred that the difficulty grows in separating the signal delay from the vertical coordinate under high-humidity conditions.

Process monitoring in precision cylindrical traverse grinding of slender bar using acoustic emission technology

The precision cylindrical traverse grinding process of slender bar is very complex for the strongly time dependent properties of the wheel. Therefore, it is very difficult for operators to properly judge the grinding state using naked eyes and ears. This calls for automatic monitoring technology that can monitor the process in precision cylindrical traverse grinding to guarantee machining quality and productivity as well as reduction in cost. This study developed an automatic monitoring system for precision cylindrical traverse grinding of slender bar using Acoustic emission (AE) technology. Grinding tests on molybdenum were conducted under traverse conditions in a conventional cylindrical grinder. It was found that larger radial material removal depth results in larger root mean square value of Acoustic emission signals (AERMS). Based on this, the AERMS was analyzed and used to determine the finishing of spark-out process and the pre-processing of tool alignment. The variation tendency of AERMS in one spark-out process was applied to determine when a wheel wears out and has to be dressed. The experimental results showed that the AE system was effective to monitor the pre-processing of tool alignment, spark-out and wheel wear in precision cylindrical traverse grinding of slender bar.

Change in the natural head-neck orientation momentarily altered sensorimotor control during sensory transition

Achilles tendon vibration generates proprioceptive information that is incongruent with the actual body position; it alters the perception of body orientation leading to a vibration-induced postural response. When a person is standing freely, vibration of the Achilles tendon shifts the internal representation of the verticality backward thus the vibration-induced postural response realigned the whole body orientation with the shifted subjective vertical. Because utricular otoliths information participates in the creation of the internal representation of the verticality, changing the natural orientation of the head-neck system during Achilles tendon vibration could alter the internal representation of the earth vertical to a greater extent. Consequently, it was hypothesized that compared to neutral head-neck orientation, alteration in the head-neck orientation should impair balance control immediately after Achilles tendon vibration onset or offset (i.e., sensory transition) as accurate perception of the earth vertical is required. Results revealed that balance control impairment was observed only immediately following Achilles tendon vibration offset; both groups with the head-neck either extended or flexed showed larger body sway (i.e., larger root mean square scalar distance between the center of pressure and center of gravity) compared to the group with the neutral head-neck orientation. The fact that balance control was uninfluenced by head-neck orientation immediately following vibration onset suggests the error signal needs to accumulate to a certain threshold before the internal representation of the earth vertical becomes incorrect.

Initial Results of the Precise Orbit Determination for the New-Generation BeiDou Satellites (BeiDou-3) Based on the iGMAS Network

By August 2016, 5 new-generation BeiDou satellites (BeiDou-3) have successfully been launched. The observations of a very limited number of 9 International GNSS (Global Navigation Satellite System) Monitoring and Assessment Service (iGMAS) stations and 52 Multi-GNSS Experiment (MGEX) stations from 16 July to 14 August 2016 are processed to determine the orbits of BeiDou-3 and BeiDou-2 satellites, respectively. The internal consistency and satellite laser ranging (SLR) validations are conducted for the orbit validation. BeiDou-3 MEO (Medium Earth Orbit) (C33 and C34) have larger root mean square (RMS) values than those BeiDou-3 IGSO (C31 and C32), whereas BeiDou-2 MEO satellites have smaller RMS values than the BeiDou-2 IGSO satellites. Furthermore, BeiDou-3 IGSO and BeiDou-2 satellites have RMS values at identical levels, whereas BeiDou-3 MEO satellites have larger RMS values than the BeiDou-2 MEO satellites. The RMS residuals are approximately 10 cm in the radial component and approximately 25 cm in the along component for BeiDou-3 IGSO satellites. For BeiDou-3 MEO satellites, the RMS residuals are approximately 40 cm in the radial component and approximately 60 cm in the along component. The SLR validation reports that the orbit radial component can reach an accuracy on the level of 1 decimeter and 4 decimeters for BeiDou-3 IGSO and MEO, respectively.

Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification

In this study, reliable water levels for four lakes are estimated based on an innovative processing strategy using a semi-automatic CryoSat-2 Synthetic Aperture Radar (SAR) multi-looked waveform classification. The selection of valid water returns is an essential step in inland altimetry applications. In order to identify reliable observations allowing for an accurate retracking, an unsupervised classification method for CryoSat-2 SAR multi-looked waveforms has been developed based on the k-mean algorithm. With this approach, changes in the water surface extent or surrounding inundation areas can be taken into account. In addition, a modified version of the Improved Threshold Retracker is developed in order to obtain optimal results for the lake heights. The used method is based on the identification of the optimal sub-waveform by employing height thresholds. The validation of the derived CryoSat-2 SAR time series with in-situ gauging data yields root mean square (RMS) differences between 3 and 90 cm for the different lakes. Compared to modeled CryoSat-2 water heights derived according to the approach used in the AltWater database our water level time series are slightly improved in terms of RMS accuracy but they contain more gaps due to the lack of reliable observations. In comparison with classical radar altimeter missions such as Envisat or Jason-2, the SAR-based time series show smaller RMS differences for the small lakes but larger RMS differences for the large lakes covered by multiple repeat missions. The presented innovative processing strategy can be easily adopted to other satellite altimetry SAR data such as from the new Sentinel-3 mission.

Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins.

Predicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging, in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable, and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2–9 ± 1 Å2 for Cα and 7.3 ± 0.9–9.6 ± 0.2 Å2 for Cγ, when the sampling was done for each of these proteins over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations with AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive to a priori prediction of crystallographic B-factors of a folded globular protein.

Pathways of intraseasonal Kelvin waves in the Indonesian Throughflow regions derived from satellite altimeter observation

AbstractThe gridded sea level anomaly (SLA) data-set provided by AVISO is used to track the propagation of intraseasonal Kelvin waves in the Indonesian Throughflow (ITF) region. The large root mean square of intraseasonal SLA along the Sumatra and Java coast is closely related to the propagation of intraseasonal Kelvin waves that derive from the equatorial Indian Ocean. These Kelvin waves are further found to propagate following different pathways at the Lombok Strait. Pathway A propagates eastward throughout the Sumba Strait and Savu Sea to reach the Ombai Strait. Pathway B penetrates into Lombok and propagates northward to reach the Makassar Strait. Pathway C propagates southeastward along the southwest coast of the Sumba Island. The equatorial Kelvin waves take around 15 days to travel from the equatorial Indian Ocean to Lombok Strait, and around 5 days to penetrate into the Makassar and Ombai straits. The Kelvin wave-induced SLA persists in the ITF region for an additional 5 days and then diminishes s...

Evaluating the potential of rainfall product from Indian geostationary satellite for operational agromet advisory services in India

Satellite remote sensing technology is increasingly gaining recognition as an important source of operational agro meteorological services. Spatial daily rainfall product from geostationary satellite is one of the important data source for quick evaluation of suitability of sowing conditions and other economically relevant agricultural operations (irrigation, fertilizer applications, spraying etc.) by farmers as well as disaster (drought, flood) warning causing crop loss and also to derive weather derivatives for crop insurance. In view of that a study was taken up to explore the use of satellite based rainfall data at different temporal scales. Under the present study, comparison has been made between Kalpana-1 high resolution (0.25° x 0.25°) rainfall estimates for four south-west monsoon months (June-September) in two contrasting monsoon periods of 2008 (normal) and 2009 (drought) with in situ measurements andforecast (1° x 1°) at nine AMFUs (Agro-Meteorological Field Units) in different agro climatic zones.Initial analysis show less correlation and large root mean square error (RMSE) of Kalpana-1 daily rainfall estimates with measurements and forecast. However, correlation was found to increase significantly from 60 to 80% over weekly to fortnightly scale with concomitant decrease in RMSE.

Surface-electromyographic analysis of the upper extremity muscles can aid in the rehabilitation of hemiparetic stroke survivors

Objective To explore any changes in the surface electromyography (sEMG) signals measured from the biceps brachii, flexor pollicis brevis and the first dorsal interosseous muscles of stroke survivors with hemiparesis during maximum isometric voluntary contractions. To correlate them with motor function recovery so as to provide a reference in making up individualized rehabilitation programs. Methods Twenty stroke survivors with hemiparesis were selected as the experimental group, and 10 healthy counterparts were recruited as the control group. For all of them, sEMG signals were recorded bilaterally from the biceps brachii, flexor pollicis brevis and the first dorsal interosseous muscles during maximum isometric voluntary contractions involving elbow flexion, thumb flexion and index finger abduction. For the stroke patients, such recording was performed repeatedly on the paretic side during the course of convalescence. Both root-mean-square (RMS) amplitude and median frequency (MDF) were calculated for the recorded surface EMG signals. The upper-extremity component of the Fugl-Meyer assessment scale (FMA-UE) and manual testing (MMT) of each muscle examined were performed with each stroke patient to assess motor function and upper extremity muscle strength. Results There were no significant differences in either RMS amplitude or MDF between the left and right sides of the healthy control subjects. Significant differences in both RMS amplitude and MDF were observed for the stroke survivors and between their values and those of the controls. The patients' unaffected side had significantly larger RMS amplitude and MDF than either side of the healthy control group. For the affected side of the stroke patients, both RMS amplitude and MDF tended to increase during the course of rehabilitation, with significant differences between the values obtained at the first and the last sessions. The FMA-UE scores and MMT results on the affected side were positively correlated with the RMS amplitudes and MDF results for the upper extremity muscles. Conclusions Surface electromyography is able to reflect the rehabilitation process and the recovery of muscle strength and motor function. It can be considered as a quantitative index for evaluating rehabilitation and a useful reference for designing targeted functional training programs. Key words: Stroke; Upper extremities; Surface electromyography; Rehabilitation

The influence of geometrical and rheological non-linearity on the calculation of rubber friction

We discuss the influence of geometrical and rheological non-linearities on the prediction of rubber friction and true contact area for rough sliding interactions. In particular, we compare the results of a linearly-viscoelastic linear-contact model, formulated in the Fourier space, with those obtained from non-linear finite element calculations. A sinusoidal rigid profile indenting a rubber block is here considered for simplicity, whereas the effects of non-linearity are evaluated by varying the aspect ratio, loading conditions and sliding speed of the contact interface. It is found that accurate friction predictions can be obtained through the linear viscoelastic model, provided that the roughness under investigation features moderate values of root mean square slopes, whereas non-linear finite element computations should be adopted for large root mean square slopes.

Impacts of AMSU-A, MHS and IASI data assimilation on temperature and humidity forecasts with GSI–WRF over the western United States

Abstract. Using NOAA's Gridpoint Statistical Interpolation (GSI) data assimilation system and NCAR's Advanced Research WRF (Weather Research and Forecasting) (ARW-WRF) regional model, six experiments are designed by (1) a control experiment (CTRL) and five data assimilation (DA) experiments with different data sets, including (2) conventional data only (CON); (3) microwave data (AMSU-A + MHS) only (MW); (4) infrared data (IASI) only (IR); (5) a combination of microwave and infrared data (MWIR); and (6) a combination of conventional, microwave and infrared observation data (ALL). One-month experiments in July 2012 and the impacts of the DA on temperature and moisture forecasts at the surface and four vertical layers over the western United States have been investigated. The four layers include lower troposphere (LT) from 800 to 1000 hPa, middle troposphere (MT) from 400 to 800 hPa, upper troposphere (UT) from 200 to 400 hPa, and lower stratosphere (LS) from 50 to 200 hPa. The results show that the regional GSI–WRF system is underestimating the observed temperature in the LT and overestimating in the UT and LS. The MW DA reduced the forecast bias from the MT to the LS within 30 h forecasts, and the CON DA kept a smaller forecast bias in the LT for 2-day forecasts. The largest root mean square error (RMSE) is observed in the LT and at the surface (SFC). Compared to the CTRL, the MW DA produced the most positive contribution in the UT and LS, and the CON DA mainly improved the temperature forecasts at the SFC. However, the IR DA gave a negative contribution in the LT. Most of the observed humidity in the different vertical layers is overestimated in the humidity forecasts except in the UT. The smallest bias in the humidity forecast occurred at the SFC and in the UT. The DA experiments apparently reduced the bias from the LT to UT, especially for the IR DA experiment, but the RMSEs are not reduced in the humidity forecasts. Compared to the CTRL, the IR DA experiment has a larger RMSE in the moisture forecast, although the smallest bias is found in the LT and MT.