scholarly journals Soil Field Model Interoperability: Challenges and Impact on Screen Temperature Forecast Skill during the Nordic Winter

2012 ◽  
Vol 13 (4) ◽  
pp. 1215-1232 ◽  
Author(s):  
Jørn Kristiansen ◽  
Dag Bjørge ◽  
John M. Edwards ◽  
Gabriel G. Rooney
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Boundary Conditions ◽  
Limited Area ◽  
Lateral Boundary ◽  
Error Source ◽  
Main Error ◽  
Lateral Boundary Conditions ◽  
The Impact ◽  
Grid Length

Abstract The high-resolution (4-km grid length) Met Office (UKMO) Unified Model forecasts driven by the coarser-resolution (8-km grid length) High-Resolution Limited-Area Model (HIRLAM), UM4, often produce significantly colder screen-level (2 m) temperatures in winter over Norway than forecast with HIRLAM itself. To diagnose the main error source of this cold bias this study focuses on the forecast initial and lateral boundary conditions, particularly the initialization of soil moisture and temperature. The soil variables may be used differently by land surface schemes of varying complexity, representing a challenge to model interoperability. In a set of five experiments, daily UM4 forecasts are driven by alternating initial and lateral boundary conditions from two different parent models: HIRLAM and Met Office North Atlantic and Europe (NAE). The experiment period is November 2007. Points for scientific examination into the topics of model interoperability and sensitivity to soil initial conditions are identified. The soil moisture is the main error source and is therefore important also in winter, rather than being a challenge only in summer. The day-to-day variability in the forecast error is large with the larger errors on days with strong longwave heat loss at the surface (i.e., the forecast sensitivity to soil moisture content is significant but variable). The much drier soil in HIRLAM compared to NAE reduces the heat capacity of the soil layers and affects the heat flux from the surface soil layer to the surface. Normalizing the respective soil moisture fields reduces these differences. The impact of ground snow is quite limited.

scholarly journals Soil Initialization Strategy for Use in Limited-Area Weather Prediction Systems

2011 ◽  
Vol 139 (6) ◽  
pp. 1844-1860 ◽  
Author(s):  
Francesca Di Giuseppe ◽  
Davide Cesari ◽  
Giovanni Bonafé
Keyword(s):  
Soil Moisture ◽  
Boundary Conditions ◽  
Weather Prediction ◽  
Global Model ◽  
Limited Area ◽  
Lateral Boundary ◽  
Prognostic Variables ◽  
Lateral Boundary Conditions ◽  
Local Soil ◽  
Analysis System

Abstract Three diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model’s soil field cannot evolve far from the host model. The second method uses the soil properties generated by a previous limited-area model forecast, allowing the soil moisture to evolve over time to a new equilibrium consistent with the regional model’s hydrological cycle. The third method implements a new local soil moisture variational analysis system that uses screen-level temperature to adjust the soil water content, allowing the use of high-resolution station data that may be available to a regional meteorological service. The methods are tested in a suite of short-term weather forecasts performed with the Consortium for Small Scale Modeling (COSMO) model over the period September–November 2008, using the ECMWF Integrated Forecast System (IFS) model to provide the lateral boundary conditions. Extensive comparisons to observations show that substantial improvements in forecast skills are achievable with improved soil temperature initialization while a smaller additional benefit in the prediction of surface fluxes is possible with the soil moisture analysis. The analysis suggests that keeping the model prognostic variables close to equilibrium with the soil state, especially for temperature, is more relevant than correcting the soil moisture initial values. In particular, if a local soil analysis system is not available, it seems preferable to adopt an “open loop” strategy rather than the interpolation from the host global model analysis. This appears to be especially true for the COSMO model in its current operational configuration since the soil–vegetation–atmosphere transfer (SVAT) scheme of the ECMWF global host model and that of COSMO are radically diverse.

scholarly journals Limited-Area Atmospheric Modeling Using an Unstructured Mesh

2018 ◽  
Vol 146 (10) ◽  
pp. 3445-3460 ◽  
Author(s):  
William C. Skamarock ◽  
Michael G. Duda ◽  
Soyoung Ha ◽  
Sang-Hun Park
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Atmospheric Modeling ◽  
Limited Area ◽  
Lateral Boundary ◽  
Test Results ◽  
Variable Resolution ◽  
Lateral Boundary Conditions ◽  
Perfect Model ◽  
Global Variable

Abstract A regional configuration of the atmospheric component of the Model for Prediction Across Scales (MPAS-A) is described and evaluated. It employs horizontally unstructured spherical centroidal Voronoi meshes (nominally hexagonal), and lateral boundary conditions used in rectangular grid regional models are adapted to the MPAS-A Voronoi mesh discretization. Test results using a perfect-model assumption show that the lateral boundary conditions are stable and robust. As found in other regional modeling studies, configurations using larger regional domains generally have smaller solution errors compared to configurations employing smaller regional domains. MPAS-A supports variable-resolution meshes, and when regional domains are expanded to include a coarser outer mesh, the variable-resolution configurations recover most of the error reduction compared to a configuration using uniform high resolution, and at much-reduced cost. The wider relaxation-zone region of the variable-resolution mesh also helps reconcile differences near the lateral boundary that evolve between the regional model solution and the driving solution, and the configuration is more stable than one using a uniform high-resolution regional mesh. At convection-permitting resolution, solutions produced using global variable-resolution MPAS-A configurations have smaller solution errors than the regional configurations after about 48 h.

Evaluation of the new high resolution unstructured grid Marmara Sea model

2021 ◽  
Author(s):  
Mehmet Ilicak ◽  
Ivan Federico ◽  
Ivano Barletta ◽  
Nadia Pinardi ◽  
Stefania Angela Ciliberti ◽  
...  
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Black Sea ◽  
Mixed Layer ◽  
Unstructured Grid ◽  
The Black Sea ◽  
Marmara Sea ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
Forecasting System

<p>Marmara Sea including Bosphorus and Dardanelles Straits (i.e. Turkish Strait Systems, TSS) is the connection between the Black Sea and the Mediterranean. The exchange flow that occurs in the Straits is crucial to set the deep water properties in the Black Sea and the surface water conditions in the Northern Aegean Sea. We have developed a new high-resolution unstructured grid model (U-TSS) for the Marmara Sea including the Bosporus and Dardanelles Straits using the System of HydrodYnamic Finite Element Modules (SHYFEM). Using an unstructured grid in the horizontal better resolves geometry of the Turkish Straits. The new model has a resolution between 500 meter in the deep to 50 meter in the shallow areas, and 93 geopotential coordinate levels in the vertical. We conducted a 4 year hindcast simulation between 2016 and 2019 using lateral boundary conditions from CMEMS (https://marine.copernicus.eu/) analysis, in particular Black Sea Forecasting System (BS-FS) for the northern boundary and Mediterranean Sea Forecasting System (MS-FS) for the southern boundary. Atmospheric boundary conditions fare from the ECMWF dataset.</p><p>Mean averaged surface circulation shows that there is a cyclonic gyre in the middle of the basin due to Bosphorus jet flowing to the south and turning to west after reaching the southern Marmara coast. The U-TSS model has been validated against the seasonal in situ observations obtained from four different cruises between 2017 and 2018. The maximum bias occurs at around halocline depth between 20 to 30 meters.  We also found that root mean square error field is higher in the mixed layer interface. We conclude that capturing shallow mixed layer depth is very in the Marmara Sea due to the interplay of air-sea fluxes and mixing parametrizations uncertainties. Maximum salinity bias and rms in the new U-TSS model are around 3 psu which is a significant improvement with respect to previous studies. This new model will be used as an operational forecasting system and will provide lateral boundary conditions for the BS-FS and MS-FS models in the future.</p>

scholarly journals Synoptic-scale conditions and convection-resolving hindcast experiments of a cold-season derecho on 3 January 2014 in western Europe

2019 ◽  
Vol 19 (5) ◽  
pp. 1023-1040 ◽  
Author(s):  
Luca Mathias ◽  
Patrick Ludwig ◽  
Joaquim G. Pinto
Keyword(s):  
Boundary Conditions ◽  
Surface Pressure ◽  
Large Scale ◽  
Vertical Wind Shear ◽  
Mesoscale Convective System ◽  
Cold Season ◽  
Limited Area ◽  
Convective System ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions

Abstract. A major linear mesoscale convective system caused severe weather over northern France, Belgium, the Netherlands and northwestern Germany on 3 January 2014. The storm was classified as a cold-season derecho with widespread wind gusts exceeding 25 m s−1. While such derechos occasionally develop along cold fronts of extratropical cyclones, this system formed in a postfrontal air mass along a baroclinic surface pressure trough and was favoured by a strong large-scale air ascent induced by an intense mid-level jet. The lower-tropospheric environment was characterised by weak latent instability and strong vertical wind shear. Given the poor operational forecast of the storm, we analyse the role of initial and lateral boundary conditions to the storm's development by performing convection-resolving limited-area simulations with operational analysis and reanalysis datasets. The storm is best represented in simulations with high temporally and spatially resolved initial and lateral boundary conditions derived from ERA5, which provide the most realistic development of the essential surface pressure trough. Moreover, simulations at convection-resolving resolution enable a better representation of the observed derecho intensity. This case study is testimony to the usefulness of ensembles of convection-resolving simulations in overcoming the current shortcomings of forecasting cold-season convective storms, particularly for cases not associated with a cold front.

scholarly journals Regional data assimilation of multi-spectral MOPITT observations of CO over North America

2015 ◽  
Vol 15 (12) ◽  
pp. 6801-6814 ◽  
Author(s):  
Z. Jiang ◽  
D. B. A. Jones ◽  
J. Worden ◽  
H. M. Worden ◽  
D. K. Henze ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Boundary Conditions ◽  
North American ◽  
A Priori ◽  
Sensitivity Analyses ◽  
Small Scale ◽  
Lateral Boundary ◽  
Free Troposphere ◽  
Lateral Boundary Conditions

Abstract. Chemical transport models (CTMs) driven with high-resolution meteorological fields can better resolve small-scale processes, such as frontal lifting or deep convection, and thus improve the simulation and emission estimates of tropospheric trace gases. In this work, we explore the use of the GEOS-Chem four-dimensional variational (4D-Var) data assimilation system with the nested high-resolution version of the model (0.5° × 0.67°) to quantify North American CO emissions during the period of June 2004–May 2005. With optimized lateral boundary conditions, regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), the main sink for CO. To further limit the potential impact of discrepancies in chemical aging of air in the free troposphere, associated with errors in OH, we use surface-level multispectral MOPITT (Measurement of Pollution in The Troposphere) CO retrievals, which have greater sensitivity to CO near the surface and reduced sensitivity in the free troposphere, compared to previous versions of the retrievals. We estimate that the annual total anthropogenic CO emission from the contiguous US 48 states was 97 Tg CO, a 14 % increase from the 85 Tg CO in the a priori. This increase is mainly due to enhanced emissions around the Great Lakes region and along the west coast, relative to the a priori. Sensitivity analyses using different OH fields and lateral boundary conditions suggest a possible error, associated with local North American OH distribution, in these emission estimates of 20 % during summer 2004, when the CO lifetime is short. This 20 % OH-related error is 50 % smaller than the OH-related error previously estimated for North American CO emissions using a global inversion analysis. We believe that reducing this OH-related error further will require integrating additional observations to provide a strong constraint on the CO distribution across the domain. Despite these limitations, our results show the potential advantages of combining high-resolution regional inversion analyses with global analyses to better quantify regional CO source estimates.

scholarly journals Estimating the Uncertainty in a Regional Climate Model Related to Initial and Lateral Boundary Conditions

2005 ◽  
Vol 18 (7) ◽  
pp. 917-933 ◽  
Author(s):  
Wanli Wu ◽  
Amanda H. Lynch ◽  
Aaron Rivers
Keyword(s):  
Boundary Conditions ◽  
Climate Model ◽  
Initial Conditions ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Regional Model ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
The Impact

Abstract There is a growing demand for regional-scale climate predictions and assessments. Quantifying the impacts of uncertainty in initial conditions and lateral boundary forcing data on regional model simulations can potentially add value to the usefulness of regional climate modeling. Results from a regional model depend on the realism of the driving data from either global model outputs or global analyses; therefore, any biases in the driving data will be carried through to the regional model. This study used four popular global analyses and achieved 16 driving datasets by using different interpolation procedures. The spread of the 16 datasets represents a possible range of driving data based on analyses to the regional model. This spread is smaller than typically associated with global climate model realizations of the Arctic climate. Three groups of 16 realizations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) in an Arctic domain, varying both initial and lateral boundary conditions, varying lateral boundary forcing only, and varying initial conditions only. The response of monthly mean atmospheric states to the variations in initial and lateral driving data was investigated. Uncertainty in the regional model is induced by the interaction between biases from different sources. Because of the nonlinearity of the problem, contributions from initial and lateral boundary conditions are not additive. For monthly mean atmospheric states, biases in lateral boundary conditions generally contribute more to the overall uncertainty than biases in the initial conditions. The impact of initial condition variations decreases with the simulation length while the impact of variations in lateral boundary forcing shows no clear trend. This suggests that the representativeness of the lateral boundary forcing plays a critical role in long-term regional climate modeling. The extent of impact of the driving data uncertainties on regional climate modeling is variable dependent. For some sensitive variables (e.g., precipitation, boundary layer height), even the interior of the model may be significantly affected.

scholarly journals Cloud-Resolving Ensemble Simulations of Mediterranean Heavy Precipitating Events: Uncertainty on Initial Conditions and Lateral Boundary Conditions

2011 ◽  
Vol 139 (2) ◽  
pp. 403-423 ◽  
Author(s):  
Benoît Vié ◽  
Olivier Nuissier ◽  
Véronique Ducrocq
Keyword(s):  
Boundary Conditions ◽  
Case Studies ◽  
Short Range ◽  
Initial Conditions ◽  
Ensemble Prediction ◽  
Lateral Boundary ◽  
Synoptic Scale ◽  
Lateral Boundary Conditions ◽  
Convective Scale ◽  
The Impact

Abstract This study assesses the impact of uncertainty on convective-scale initial conditions (ICs) and the uncertainty on lateral boundary conditions (LBCs) in cloud-resolving simulations with the Application of Research to Operations at Mesoscale (AROME) model. Special attention is paid to Mediterranean heavy precipitating events (HPEs). The goal is achieved by comparing high-resolution ensembles generated by different methods. First, an ensemble data assimilation technique has been used for assimilation of perturbed observations to generate different convective-scale ICs. Second, three ensembles used LBCs prescribed by the members of a global short-range ensemble prediction system (EPS). All ensembles obtained were then evaluated over 31- and/or 18-day periods, and on 2 specific case studies of HPEs. The ensembles are underdispersive, but both the probabilistic evaluation of their overall performance and the two case studies confirm that they can provide useful probabilistic information for the HPEs considered. The uncertainty on convective-scale ICs is shown to have an impact at short range (under 12 h), and it is strongly dependent on the synoptic-scale context. Specifically, given a marked circulation near the area of interest, the imposed LBCs rapidly overwhelm the initial differences, greatly reducing the spread of the ensemble. The uncertainty on LBCs shows an impact at longer range, as the spread in the coupling global ensemble increases, but it also depends on the synoptic-scale conditions and their predictability.

The impact of chemical lateral boundary conditions on CMAQ predictions of tropospheric ozone over the continental United States

2008 ◽  
Vol 9 (1) ◽  
pp. 43-58 ◽  
Author(s):  
Youhua Tang ◽  
Pius Lee ◽  
Marina Tsidulko ◽  
Ho-Chun Huang ◽  
Jeffery T. McQueen ◽  
...  
Keyword(s):  
United States ◽  
Boundary Conditions ◽  
Tropospheric Ozone ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
The Impact

scholarly journals Effect of boundary conditions on adjoint-based forecast sensitivity observation impact in a regional model

2021 ◽  
Author(s):  
Hyun Mee Kim ◽  
Dae-Hui Kim
Keyword(s):  
Boundary Conditions ◽  
Forecast Error ◽  
Error Reduction ◽  
Regional Model ◽  
Buffer Size ◽  
Lateral Boundary ◽  
Modeling Framework ◽  
Lateral Boundary Conditions ◽  
Observation Impact ◽  
The Impact

AbstractIn this study, the effect of boundary condition configurations in the regional Weather Research and Forecasting (WRF) model on the adjoint-based forecast sensitivity observation impact (FSOI) for 24 h forecast error reduction was evaluated. The FSOI has been used to diagnose the impact of observations on the forecast performance in several global and regional models. Different from the global model, in the regional model, the lateral boundaries affect forecasts and FSOI results. Several experiments with different lateral boundary conditions were conducted. The experimental period was from 1 to 14 June 2015. With or without data assimilation, the larger the buffer size in lateral boundary conditions, the smaller the forecast error. The nonlinear and linear forecast error reduction (i.e., observation impact) decreased as the buffer size increased, implying larger impact of lateral boundaries and smaller observation impact on the forecast error. In all experiments, in terms of observation types (variables), upper-air radiosonde observations (brightness temperature) exhibited the greatest observation impact. The ranking of observation impacts was consistent for observation types and variables among experiments with a constraint in the response function at the upper boundary. The fractions of beneficial observations were approximately 60%, and did not considerably vary depending on the boundary conditions specified when calculating the FSOI in the regional modeling framework.

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