Nudging Method Research Articles

A Spatially Dependent Nudging Method and Its Application to a Global Tide Assimilation

A Spatially Dependent Nudging Method and Its Application to a Global Tide Assimilation

A new high-resolution Coastal Ice-Ocean Prediction System for the East Coast of Canada

The Coastal Ice Ocean Prediction System for the East Coast of Canada (CIOPS-E) was developed and implemented operationally at Environment and Climate Change Canada (ECCC) to support a variety of critical marine applications. These include support for ice services, search and rescue, environmental emergency response and maritime safety. CIOPS-E uses a 1/36° horizontal grid (~ 2 km) to simulate sea ice and ocean conditions over the northwest Atlantic Ocean and the Gulf of St. Lawrence (GSL). Forcing at lateral open boundaries is taken from ECCC’s data assimilative Regional Ice-Ocean Prediction System (RIOPS). A spectral nudging method is applied offshore to keep mesoscale features consistent with RIOPS. Over the continental shelf and GSL, the CIOPS-E solution is free to evolve according to the model dynamics. Overall, CIOPS-E significantly improves the representation of tidal and sub-tidal water levels compared to ECCC’s lower resolution systems: RIOPS (~ 6 km) and the Regional Marine Prediction System – GSL (RMPS-GSL, 5 km). Improvements in the GSL are due to the higher resolution and a better representation of bathymetry, boundary forcing and dynamics in the upper St. Lawrence Estuary. Sea surface temperatures show persistent summertime cold bias, larger in CIOPS-E than in RIOPS, as the latter is constrained by observations. The seasonal cycle of sea ice extent and volume, unconstrained in CIOPS-E, compares well with observational estimates, RIOPS and RMPS-GSL. A greater number of fine-scale features are found in CIOPS-E with narrow leads and more intense ice convergence zones, compared to both RIOPS and RMPS-GSL.

Dynamical reconstruction of the upper-ocean state in the central Arctic during the winter period of the MOSAiC expedition

Abstract. This paper presents a methodological tool for dynamic reconstruction of the state of the ocean, based, as an example, on observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment. The data used in this study were collected in the Amundsen Basin between October 2019 and January 2020. Analysing observational data to assess tracer field and upper-ocean dynamics is highly challenging when measurement platforms drift with the ice pack due to continuous drift speed and direction changes. We have equipped the new version of the coastal branch of the global Finite-volumE sea ice–Ocean Model (FESOM-C) with a nudging method. Model nudging was carried out assuming a quasi-steady state. Overall, the model can reproduce the lateral and vertical structure of the temperature, salinity, and density fields, which allows for projecting dynamically consistent features of these fields onto a regular grid. We identify two separate depth ranges of enhanced eddy kinetic energy located around two maxima in buoyancy frequency: the depth of the upper halocline and the depth of the warm (modified) Atlantic Water. Simulations reveal a notable decrease in surface layer salinity and density in the Amundsen Basin towards the north but no significant gradient from east to west. However, we find a mixed-layer deepening from east to west, with a 0.084 m km−1 gradient at 0.6 m km−1 standard deviation, compared to a weak deepening from south to north. The model resolves several stationary eddies in the warm Atlantic Water and provides insights into the associated dynamics. The model output can be used to further analyse the thermohaline structure and related dynamics associated with mesoscale and submesoscale processes in the central Arctic, such as estimates of heat fluxes or mass transport. The developed nudging method can be utilized to incorporate observational data from a diverse set of instruments and for further analysis of data from the MOSAiC expedition.

Memory of HF radar surface-current assimilation on different forecasting variables of ocean circulation models

In this study, using nudging method, the current data from a pair of HF radar along Jiangsu coast was assimilated to unstructured grid models based on FVCOM. Several experiments were conducted to examine the effect of radar data on surface velocity, elevation and sea surface salinity forecast. The results show that the gain of assimilation on surface velocity and elevation forecasts disappeared fast within a few hours, while salinity forecasts can be influenced for more than 10 days. This fast diminishing of the gain of data assimilation on current and elevation can be attributed to the fast wave propagation from elsewhere to the radar coverage area.

Impacts of Nudged Sea Surface Temperature on Tropical Precipitation, Moisture, and Vertical Velocity in an Earth System Model

Abstract Understanding the effect of the nudged sea surface temperature (SST) on precipitation simulation is important in Earth system models. In this study, we analyzed the role of nudged SST and air–sea interaction in precipitation simulation by using the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2). CAS-ESM2 fully coupled runs with and without nudged tropical SST to observations, and the atmosphere-only runs (AMIP) are comprehensively evaluated against observations and reanalysis over the tropical ocean from 1982 to 2015. The precipitation is affected by the nudged SST and air–sea interaction by means of changes in both thermodynamic and dynamic processes. Simulation with the nudged SST dramatically improves the climatological precipitation fields over the tropics and four regional areas. As the simulated SSTs are nudged toward the observations, CAS-ESM2 well reproduces the mean annual values in column water vapor (CWV), vertical structure of specific humidity, and large-scale circulation. The nudged SST run also captures a wide range of the complex interactions between SST, precipitation, moisture, and large-scale circulations, as measured by the monthly relationships and bivariate probability distribution function. The biases in heavy precipitation associated with the CWV induced under moist conditions are decreased by applying the nudging technique. In particular, the nudging run performs better in reproducing the SST–precipitation covariability than the control and AMIP runs. However, CAS-ESM2 with nudged tropical SST simulates the degradation of strong ascending motions, which is similar to the AMIP runs and reflects the deviation of the atmospheric model. Our results confirm that the fully coupled run using the nudged SST is a method for improving the precipitation simulation across the tropical oceans. Significance Statement Understanding the sources of precipitation errors in Earth system models is challenging because of the complex error compensation and air–sea interaction. When the simulated SST is nudged toward observations, few studies have focused on the changes in both thermodynamic and dynamic processes via atmospheric large-scale circulation, moisture, and changes in the SST–precipitation relationship at the same time. Here, we carry out two CMIP6 historical experiments (a fully coupled control run and an SST-nudged run) and the atmosphere-only runs by using CAS-ESM2 from 1982 to 2015. Then, we validate and analyze the climatology of SST, precipitation, moisture, large-scale circulation, and their complex interactions over the tropical oceans and different regional areas. The fully coupled nudged-SST run outperforms the fully free coupled run in reproducing the climatology and complex interactions between SST, precipitation, moisture, and large-scale circulations across the tropics. Moreover, the biases in the SST–precipitation covariability are significantly alleviated in the nudging experiments. We confirmed that the SST nudging method is a potential way to improve precipitation simulation in CAS-ESM2.

Historical simulation of photovoltaic potential over China within the CORDEX-EA-II framework

This study evaluates historical simulation of solar photovoltaic potential (PVpot) during 1989–2008 over China against the ERA5 reanalysis, using the Weather Research and Forecasting (WRF) model and Regional Climate Model version 4 (RegCM4) within the framework of the Coordinated Regional Downscaling Experiment-East Asia second phase (CORDEX-EA-II). The impacts of spectral nudging technique and land surface model on the simulated PVpot are investigated as well. Results indicate that the observed PVpot is abundant over western China, which can reach up to 26% in summer particularly. The WRF simulations significantly overestimate the PVpot over most areas of China, with the bias about 9% over southeastern China, while the utilization of spectral nudging method and CLM4 land surface model can greatly reduce the deviation. The RegCM4 simulations generate underestimation of PVpot over Northwest China and overestimation over Southeast China. As for the interannual variation, the observed PVpot features an increase of 0.9%/decade over southeastern China. The WRF and RegCM4 simulations can reproduce the rising trend of PVpot, while the magnitude is much lower than ERA5. The WRF simulations can properly portray the characteristics of seasonal cycle of PVpot, with the peaks in May over entire China and most subregions, while RegCM4 exhibits poor skill in reproducing the intra-annual variation. Moreover, the simulated bias in the clear-sky solar radiation (RSDSCS), low-level cloud fraction, and light rain during the daylight may contribute to the deficiency of PVpot.

An assessment of the LICOM Forecast System under the IVTT class4 framework

This paper evaluates LFS (LICOM Forecast System) forecasts and compares them with other marine forecast systems under the IVTT (Intercomparison and Validation Task Team) Class 4 framework. LFS delivers real-time daily forecasts driven by the GFS (Global Forecast System) atmospheric analyses and surface forecasts. The nudging method in LFS provides the initial state for forecasting, with only the temperature and salinity restored towards the Mercator PSY4 daily analyses. Assessments show that LFS demonstrates a reasonably good capability in short-term marine environment forecast. For the leading 1-6 days forecasts, the root mean square error (RMSE) ranges between 0.53-0.63°C, 0.57-0.66°C and 0.12-0.13 psu for the sea surface temperature, temperature, and salinity profiles, respectively. The overall performance is comparable to other major marine forecast systems, with a slight advantage in forecasting the temperature and salinity profiles. Different nudging time scales are applied to the upper ocean and deep ocean to preserve the effects of mesoscale processes and correct the large-scale biases in temperature and salinity. However, the absence of other observational constraints, such as the sea level height, significantly affects the regional forecast features. Further analyses are required to improve the performance, and the integration of an assimilation system into LFS is urgently needed.

Back-and-forth nudging for the quasi-geostrophic ocean dynamics with altimetry: Theoretical convergence study and numerical experiments with the future SWOT observations

<p style='text-indent:20px;'>In data assimilation for geophysical problems, the increasing amount of satellite data to analyze makes it more and more challenging to guarantee near real time forecasting. Thus, low time and memory consuming data assimilation methods become very attractive. The back-and-forth nudging (BFN) method is a non-classical data assimilation method that can be seen as a deterministic and smoothing version of the Kalman filter. From a practical point of view, the BFN method is very valuable for its simplicity of implementation (no optimization, no differentiation, ...) and its rapidity of convergence. Under observability conditions, we prove the mathematical convergence of BFN at deep layers for a multi-layer quasi-geostrophic (MQG) ocean circulation model using an infinite dimensional variant of LaSalle's invariance principle. We also extend the BFN to the problem of joint state-parameter identification. The numerical experiments, performed on 120km large swath sea surface height (SSH) simulated data of the Surface Water Ocean Topography (SWOT) satellite, show the high robustness of the algorithm to uncertainties and the few iterations needed to reach convergence, whereas some problems remain due to non-reversibility properties in time. We also give a strategy to improve geophysical model accuracy, considering the large number of uncertain parameters inherent to models and their impacts on state estimation performance. We propose here a joint state-parameter estimation, tested on the baroclinic wavenumber as an unobserved parameter.</p>

Simple Hybrid Sea Ice Nudging Method for Improving Control Over Partitioning of Sea Ice Concentration and Thickness

AbstractTo assess the effect of ocean‐atmosphere coupling in the climate response to forced sea ice loss, the Polar Amplification Model Intercomparison Project protocol includes centennial coupled atmosphere‐ocean general circulation model simulations with imposed sea ice loss. The protocol, which specifies sea ice concentration and thickness distribution targets, does not prescribe a method for achieving them. Although different methods for imposing sea ice loss (or growth) in models have been documented, testing of the method‐dependence of the resulting climate responses has been limited. Achieving the targeted sea ice state has proven to be challenging using the so‐called ghost‐flux nudging method, which induces ice melt from below, as this method does not constrain the partitioning between thickness and concentration. We propose, describe and test a simple method that combines the advantages of direct sea ice nudging and ghost‐flux nudging. The hybrid nudging method better captures the partitioning between thickness and concentration while conserving total water content. We document how this novel sea ice constraining method reaches specific targets, enhances surface turbulent heat flux responses to sea ice loss, and induces tropospheric warming for both polar regions.

Nudging Observed Winds in the Arctic to Quantify Associated Sea Ice Loss from 1979 to 2020

Abstract Over the past decades, Arctic climate has exhibited significant changes characterized by strong pan-Arctic warming and a large-scale wind shift trending toward an anticyclonic anomaly centered over Greenland and the Arctic Ocean. Recent work has suggested that this wind change is able to warm the Arctic atmosphere and melt sea ice through dynamically driven warming, moistening, and ice drift effects. However, previous examination of this linkage lacks a capability to fully consider the complex nature of the sea ice response to the wind change. In this study, we perform a more rigorous test of this idea by using a coupled high-resolution modeling framework with observed winds nudged over the Arctic that allows for a comparison of these wind-induced effects with observations and simulated effects forced by anthropogenic forcing. Our nudging simulation can well capture observed variability of atmospheric temperature, sea ice, and the radiation balance during the Arctic summer and appears to simulate around 30% of Arctic warming and sea ice melting over the whole period (1979–2020) and more than 50% over the period 2000–12, which is the fastest Arctic warming decade in the satellite era. In particular, in the summer of 2020, a similar wind pattern reemerged to induce the second-lowest sea ice extent since 1979, suggesting that large-scale wind changes in the Arctic are essential in shaping Arctic climate on interannual and interdecadal time scales and may be critical to determine Arctic climate variability in the coming decades. Significance Statement This work conducts a set of new CESM1 nudging simulations to quantify the impact of the observed evolution of large-scale high-latitude atmospheric winds on Arctic climate variability over the past four decades. Variations in climate parameters, including sea ice, radiation, and atmospheric temperatures are well replicated in the model when observed winds are imposed in the Arctic. By investigating simulated sea ice melting processes in the simulation, we illustrate and estimate how large-scale winds in the Arctic help melt sea ice in summer. The nudging method has the potential to make Arctic climate attribution more tangible and to unravel the important physical processes underlying recent abrupt climate change in the Arctic.

Nudging effect of default options: A meta-analysis

<p id="p00005">In recent years, the nudging method of default options has been increasingly used to improve public behavior and increase the public approval of social policies. Default option setting is a tool of choice architecture. It involves setting a pre-selected option that takes advantage of people’s inertia, subtly increasing the likelihood that decision-makers choose this default option. Defaults are commonly framed in the opt-in system (without any default) and opt-out system (target option as a default). The frequencies at which the target option is of the target option is chosen are considerably higher in the latter, which is known as the default effect. Although a great number of studies have shown the default effect in various scenarios, the effectiveness of default nudge has been questioned by scholars and the public nowadays. For example, there are a series of studies that show that default option settings are ineffective or even counterproductive in promoting public behavior. <break/>Given the dispute on the effectiveness of the default nudge method, the current study aims to systematically examine how effective defaults are and whether their effectiveness varies across culture (Eastern culture vs. Western culture), domains (money-related domain, health-related domain, and environment-related domain), behavioral motives (benefits self vs. benefits others; whether there is real financial consequence of choice), and experiment characteristics (type of dependent variables, time of publication, sample size, and type of experiment). We conducted a literature search and meta-analysis of 56 articles, covering 92 default studies (pooled <italic>n</italic> = 112, 212, range = 16 ~ 19992) that fitted our inclusion criteria. The meta-analysis revealed that opt-out defaults lead to more pre-selected decisions than opt-in defaults do (<italic>d</italic> = 0.59, <italic>t </italic>= 10.12, 95% CI = [0.47, 0.71],<italic> p</italic> &lt; 0.001), indicating that default nudging has a considerable effect. Further analysis showed two factors that could partially explain when the defaults’ effectiveness varies. First, moderating analysis showed that cultural background moderated the effect of default nudging: the effect of opt-out system under Western culture performed better than that under Eastern culture (<italic>b</italic> = 0.44, 95% CI = [0.05, 0.84], <italic>p </italic>= 0.027). Second, the moderating analysis also revealed the moderating effect of consumer choice and health choice. The nudging effectiveness of the default option settings was relatively better in the field of consumer choice (<italic>b</italic> = 0.43, 95% CI = [0.15, 0.70], <italic>p </italic>= 0.002), also somewhat effective in the field of pro-environmental choice (<italic>b</italic> = -0.32, 95% CI = [-0.66, 0.02], <italic>p </italic>= 0.067), and weakest in the field of health domain (<italic>b</italic> = -0.32, 95% CI = [-0.42, 0.10], <italic>p </italic>= 0.233). Lately, the default effect was not influenced by motivational factors or experiment characteristics. <break/>In conclusion, the current work-integrated findings in previous default-related studies and answered the questions regarding how effective the defaults are and when their effectiveness varies. The present meta-analysis covered 21 more studies than previous analyses and 5 more studies based on the Asian samples. In the 92 studies included in this meta-analysis, most showed a positive effect of default nudge on people’s behavioral change, and only a few studies found no significant or negative effects. The total default effect in our analysis was slightly lower than the results reported by Jachimowicz et al. (2018), but it still showed a medium-sized effect, indicating that the default nudge is indeed effective in promoting behavioral changes. Our finding provides a new conclusion for the studies of the effectiveness of the default effect, and reveals the moderating effect of cultural background for the first time, which may help us to better understand whether the defaults are effective and when to use the defaults.

Seasonal Predictions of Summer Precipitation in the Middle-lower Reaches of the Yangtze River with Global and Regional Models Based on NUIST-CFS1.0.

Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River (MLYR) is of urgent demand for the local economic and societal development. This study assesses the seasonal forecast skill in predicting summer precipitation over the MLYR region based on the global Climate Forecast System of Nanjing University of Information Science and Technology (NUIST-CFS1.0, previously SINTEX-F). The results show that the model can provide moderate skill in predicting the interannual variations of the MLYR rainbands, initialized from 1 March. In addition, the nine-member ensemble mean can realistically reproduce the links between the MLYR precipitation and tropical sea surface temperature (SST) anomalies, but the individual members show great discrepancies, indicating large uncertainty in the forecasts. Furthermore, the NUIST-CFS1.0 can predict five of the seven extreme summer precipitation anomalies over the MLYR during 1982–2020, albeit with underestimated magnitudes. The Weather Forecast and Research (WRF) downscaling hindcast experiments with a finer resolution of 30 km, which are forced by the large-scale information of the NUIST-CFS1.0 predictions with a spectral nudging method, display improved predictions of the extreme summer precipitation anomalies to some extent. However, the performance of the downscaling predictions is highly dependent on the global model forecast skill, suggesting that further improvements on both the global and regional climate models are needed.Electronic supplementary materialSupplementary material is available in the online version of this article at 10.1007/s00376-022-1389-7.

Origins of the Intraseasonal Variability of East Asian Summer Precipitation

AbstractAccurate subseasonal prediction of East Asian summer precipitation (EASP) requires a deep understanding of the origins of its intraseasonal variability (ISV). However, the relative contributions to the EASP ISV from local processes, tropical intraseasonal oscillation (ISO), and extratropical influence remain unknown. We conducted a set of numerical experiments with a grid nudging method to confirm the roles of external forcing from mid‐to‐high latitude wave trains and tropical ISO and quantify their relative contributions. The Community Earth System Model can reproduce realistic EASP ISV and associated preceding signals. The tropical and mid‐to‐high latitude forcings account for, respectively, 53% and 40% of the total variance for the two leading ISV modes of EASP. The tropical forcing contributes more significantly to the two leading modes (31% and 40%, respectively) compared to the extratropical forcing (24% and 15%). These external forcings mainly affect EASP regional averages rather than the values of local (grid) scale.

Improving the Four-Dimensional Incremental Analysis Update (4DIAU) with the HWRF 4DEnVar Data Assimilation System for Rapidly Evolving Hurricane Prediction

AbstractShort-term spinup for strong storms is a known difficulty for the operational Hurricane Weather Research and Forecasting (HWRF) Model after assimilating high-resolution inner-core observations. Our previous study associated this short-term intensity prediction issue with the incompatibility between the HWRF Model and the data assimilation (DA) analysis. While improving physics and resolution of the model was found to be helpful, this study focuses on further improving the intensity predictions through the four-dimensional incremental analysis update (4DIAU). In the traditional 4DIAU, increments are predetermined by subtracting background forecasts from analyses. Such predetermined increments implicitly require linear evolution assumption during the update, which are hardly valid for rapidly evolving hurricanes. To confirm the hypothesis, a corresponding 4D analysis nudging (4DAN) method, which uses online increments is first compared with the 4DIAU in an oscillation model. Then, variants of 4DIAU are proposed to improve its application for nonlinear systems. Next, 4DIAU, 4DAN and their proposed improvements are implemented into the HWRF 4DEnVar DA system and are investigated with Hurricane Patricia (2015). Results from both the oscillation model and HWRF Model show that 1) the predetermined increments in 4DIAU can be detrimental when there are discrepancies between the updated and background forecasts during a nonlinear evolution; 2) 4DAN can improve the performance of incremental update upon 4DIAU, but its improvements are limited by the overfiltering; 3) relocating initial background before the incremental update can improve the corresponding traditional methods; and 4) the feature-relative 4DIAU method improves the incremental update the most and produces the best track and intensity predictions for Patricia among all experiments.

Effects of Suppressed Transient Eddies by the Tibetan Plateau on the East Asian Summer Monsoon

AbstractIt is known that the Tibetan Plateau (TP) can weaken the transient eddies (TEs) transported along the westerly jet stream. This study investigates the effects of the persistently suppressed TEs by the TP on the East Asian summer monsoon and the associated mechanisms using the NCAR Community Earth System Model. A nudging method is used to modify the suppression of the TEs without changing the steady dynamic and thermodynamic effects of the TP. The suppressed TEs by the TP weaken the East Asian westerly jet stream through the weakened poleward TE vorticity flux. On the one hand, the weakened jet stream leads to less (more) rainfall in northern (southern) East Asia by inducing anomalous moisture convergence, midtropospheric warm advection, and upper-level divergence, particularly in early summer when the eastward propagation of TE suppression by the TP is strong. On the other hand, the precipitation anomalies can shift the East Asian westerly jet stream southward and promote the moisture convergence in southern East Asia through latent heat release. Therefore, the persistent suppression of the TEs leads to a southward shift of the East Asian rain belt by a convective feedback, as it was previously found that the steady thermodynamic and dynamic forcings of the TP favored a northward shift of the rain belt. This study suggests that the anomalously weak TEs can lead to a rainfall change (more in the south, less in the north) over East Asia.

Development and evaluation of spectral nudging strategy for the simulation of summer precipitation over the Tibetan Plateau using WRF (v4.0)

Abstract. Precipitation is the key component determining the water budget and climate change of the Tibetan Plateau (TP) under a warming climate. This high-latitude region is regarded as “the Third Pole” of the Earth and the “Asian Water Tower” and influences the eco-economy of downstream regions. However, the intensity and diurnal cycle of precipitation are inadequately depicted by current reanalysis products and regional climate models (RCMs). Spectral nudging is an effective dynamical downscaling method used to improve precipitation simulations of RCMs by preventing simulated fields from drifting away from large-scale reference fields, but the most effective manner of applying spectral nudging over the TP is unclear. In this paper, the effects of spectral nudging parameters (e.g., nudging variables, strengths, and levels) on summer precipitation simulations and associated meteorological variables were evaluated over the TP. The results show that using a conventional continuous integration method with a single initialization is likely to result in the over-forecasting of precipitation events and the over-forecasting of horizontal wind speeds over the TP. In particular, model simulations show clear improvements in their representations of downscaled precipitation intensity and its diurnal variations, atmospheric temperature, and water vapor when spectral nudging is applied towards the horizontal wind and geopotential height rather than towards the potential temperature and water vapor mixing ratio. This altering of the spectral nudging method not only reduces the wet bias of water vapor in the lower troposphere of the ERA-Interim reanalysis (when it is used as the driving field) but also alleviates the cold bias of atmospheric temperatures in the upper troposphere, while maintaining the accuracy of horizontal wind features for the regional model field. The conclusions of this study imply how driving field errors affect model simulations, and these results may improve the reliability of RCM results used to study the long-term regional climate change.

Evaluation of Precipitation in the Chinese Regional Reanalysis Using Satellite Estimates, Gauge-Based Observations and Global Reanalysis

Two high-resolution Chinese regional reanalysis (CNRR) datasets at a resolution of 18 km during the period of 1998–2009 are generated by Gridpoint Statistical Interpolation (GSI) data assimilation system and spectral nudging (SN) method. The precipitation from CNRR is comprehensively evaluated against the observational datasets and global reanalysis ERA5 over East-Asia. The climatology mean, seasonal variability, extreme events, and summer diurnal cycle of precipitation are analyzed. Results show that CNRR reasonably reproduces the observed characteristics of rainfall, although some biases exist. The spatial distribution of climatology mean precipitation is well simulated by CNRR, while overestimation exists especially on the west side of Tibetan-Plateau (TP). CNRR reproduces the unimodal feature of the annual cycle with overestimations of summer precipitation, and well produces the probability of light and moderate rainfall but tend to overestimate heavy and extreme precipitation over most regions in China. The overall spatial distribution of extreme precipitation indices can be captured by CNRR. The diurnal cycle of summer precipitation, as well as the amplitude of diurnal cycle, are better reproduced by CNRR-GSI, capturing eastward propagation of diurnal phase from TP along the Yangtze River. CNRR-GSI generally outperforms CNRR-SN over most regions of China except in reproducing heavy and extreme rainfall in the Yangtze River Basin (YRB) and South China (SC) regions. CNRR-GSI shows comparable results with the latest ERA5 and outperforms it in simulating the diurnal cycle of precipitation. This dataset can be considered as a reliable source for precipitation related applications.

Representation of Arabian Peninsula summer climate in a regional atmospheric model using spectral nudging

This study assesses the performance of the Weather Research and Forecasting (WRF) model in simulating the Arabian Peninsula summer climate for the period 2001–2016. The European Centre for Medium range Weather Forecast (ECMWF) reanalysis is downscaled using WRF without (CTRL) and with the Spectral Nudging (SPN) method. Our results suggest that the noticeable cold biases in surface temperatures (mean, minimum, and maximum) over the Arabian Peninsula in CTRL are significantly reduced in SPN. The seasonal patterns of surface pressure, cloud cover, lower and upper tropospheric circulation, and mid-tropospheric anticyclone are also simulated more realistically with SPN. The evaluation of mean vertical profiles of dynamical and thermo-dynamical features over the Arabian Peninsula further confirms the enhanced simulations with SPN with respect to CTRL. Though SPN captures better the observed evolution of rainfall compared to that of CTRL, it produces a positive rainfall bias over the Southwestern Arabian Peninsula. Stronger vertical motions associated with the local topography enhance the higher water vapor loading, condenses in the upper layers, and results in excess amount of rainfall in SPN. Furthermore, with SPN, WRF is further able to better simulate the synoptic features of heat waves. Overall, SPN enhances WRF simulation skill of the horizontal structures and vertical profiles of the Arabian Peninsula summer climate by enforcing a better balance between the small and large scale features and associated feedbacks.

Evaluation of the soil moisture model with data assimilation by the triple collocation method

This paper deals with a nonlinear soil moisture transport problem, solved with addition of satellite observed soil moisture. The satellite data are assimilated into the model using Newtonian nudging method. Evaluation is done by the triple collocation method, which involves three independent data sources: model results, ground stations and ERA5 climatic data. The results testify that model results are nearly as accurate as the ground station measurements.

Development of a Data Assimilation Method Using Vibration Equation for Large‐Eddy Simulations of Turbulent Boundary Layer Flows

AbstractIn order to improve the simulation accuracy, it is effective to use a data assimilation technique which is capable of reproducing more realistic simulated states by incorporating observational data into simulation models. One of the simplest ones among data assimilation techniques is a Newtonian relaxation‐type nudging method which has been widely used in mesoscale meteorological models. In this study, we proposed a data assimilation method using a vibration equation which can incorporate turbulence winds toward target mean winds while maintaining small‐scale turbulent fluctuations as a different approach from the conventional nudging method. First, we conducted test simulations in which nudging is applied in a basic turbulent boundary layer (TBL) flow toward a target one. It is shown that the basic TBL flow can be reasonably nudged toward the target one while maintaining the turbulent fluctuations well when prescribing the natural frequency in the vibration equation smaller than the spectral peak frequency in the TBL flow. Then, we applied the proposed nudging method by incorporating data obtained from meteorological observations located in the actual city of Kyoto. The mean wind velocity profiles were reasonably nudged toward the target observed profile and the turbulence statistics were also favorably maintained. It is concluded that the data assimilation method using the vibration equation successfully nudges toward the target mean winds while maintaining small‐scale turbulent fluctuations well.