Spectral model with a regional focus

Abstract. Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ∼ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales < 10 km, the development of global nonhydrostatic models with high accuracy is urgently required. The Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7) is designed to understand and statistically quantify the advantages of high-resolution nonhydrostatic global atmospheric models to improve tropical cyclone (TC) prediction. A total of 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolutions of 7 km and a conventional hydrostatic global model with a horizontal resolution of 20 km were run on the Earth Simulator. The three 7 km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Double Fourier Series Model (DFSM), the Multi-Scale Simulator for the Geoenvironment (MSSG) and the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The 20 km mesh hydrostatic model is the operational Global Spectral Model (GSM) of the Japan Meteorological Agency. Compared with the 20 km mesh GSM, the 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7 km mesh nonhydrostatic global models. While the three 7 km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20 km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.

Does a regional climate model provide a more useful regional climatology than can be obtained from larger‐scale global analyses or a better regional forecast than can be obtained by a large‐scale seasonal prediction model? To examine these questions, U.S. regional spectral model (RSM) climate simulations forced by 1‐day global spectral model (GSM) forecasts initialized from the National Centers for Environmental Prediction (NCEP) operational analysis are compared with regional RSM simulations forced by the NASA Seasonal to Interannual Prediction Project general circulation model (GCM). The GCM was continuously forced by observed sea surface temperature variations, but since sea surface temperatures (SSTs) are so persistent, these forced GCM simulations were equivalent to seasonal GCM predictions, which are mainly based upon persistent SSTs anyhow. RSM simulations forced by these two global modes were compared at the same spatial resolution as the global models (200 km) and at higher resolution (50 km). Resolution was important for producing better geographic pictures but does not currently produce significantly more skillful regional climate simulations or forecasts of the temporal variability, which already have significant skill from the global models. However, regional climate simulations and forecasts better depict the precipitation intensity, especially over the U.S. West. Finally, re‐initialized (from the large‐scale analysis) 1‐day RSM forecasts were compared with continuous RSM simulations, and this increased the overall regional skill back to the original GSM skill, which was somewhat degraded in continuous RSM simulations.

In this chapter we provide an introduction to the topic of spherical harmonics as basis functions for a global spectral model. The spherical harmonics are made up of trigonometric functions along the zonal direction and associated Legendre functions in the meridional direction. A number of properties of these functions need to be understood for the formulation of a spectral model. This chapter describes some useful properties that will be used to illustrate the procedure for the representation of data sets over a sphere with spherical harmonics as basis functions. The calculations of Fourier and Legendre transforms and their inverse transforms are an important part of global spectral modeling, and these are covered in some detail in this chapter. Finally, this chapter addresses the formulation of two simple spectral models. One of these is a single-level barotropic model, and the other is a shallow-water model.

Inaccuracies in the data at the boundaries of a limited area may be a major source of forecast errors in that area. With a global spectral shallow water model we show that the major part of these local errors propagate from the boundaries at a speed equal to the local wind speed with a maximum speed of propagation along the jet stream. Thus, taking into account the forecast length and the accuracy of the data at the boundaries in limited‐area models, one needs to adjust the extent of the buffer region where errors propagate and contaminate the forecast.

The mainstream data assimilation system in operation will still employ four-dimensional variational data assimilation(4DVAR) method in a long time of future. We develop a new 4DVAR system, i.e., YH4DVAR, using global spectral model as a constraint to impose a dynamic balance on the assimilation. The cost function of YH4DVAR consists of four terms: background, observations, digital filter, and bias correction, respectively. YH4DVAR employs the wavelet background error convariance, the multi-resolution incremental formulation, the tangent linear and adjoint models for dynamics core and physical processes, and ATOVS radiance data assimilation. Simultaneous spatial and spectral variations of horizontal and vertical covariance are achieved by dividing the control vector into several parts, each of which corresponds to a band of total spherical wavenumbers. Using NWP consisting of YH4DVAR and global spectral model, the anomaly correlation with the verifying analysis for geopotential height 8-day forecast on the 500 hPa isobaric surface at 12-month mean is above 60%. The formulation and implementation of YH4VAR are described in detail in this paper.

¶This paper deals with the systematic evolution of the North American monsoon system by analyzing the evolution of tropospheric circulation, precipitation, moisture fluxes and the adjoining sea surface temperatures from observations and the Florida State University Nested Regional Spectral Model embedded within a coupled atmosphere–ocean coupled model. The atmospheric part is a global spectral model with triangular truncation T63 and a nested regional spectral model. The global atmospheric model is coupled with the Hamburg’s Global Ocean Model. This model was integrated for six-months with 50 km resolution in the North American monsoon domain. The NCEP/NCAR reanalysis were used as the observed state for comparison. The analyzed model results shows that the above model has the capability of capturing some of the features of the North American monsoon system. Besides the evolution of the monsoon system, the out-of-phase relationship between the Mexican monsoon with south-central United States precipitation and the largest moisture supply from the Gulf of Mexico are the principal findings of this study. It is also noted that during the mature phase of the monsoon, the Gulf of California and the Pacific Ocean dominates the Gulf of Mexico in order of moisture supply but immediately after the mature phase, the Gulf of Mexico dominates.

Using a global spectral model with wave-CISK formulation we have generated an eastward de which. Resembles the observed 30-50 day mode. This has a scale of global wave number one and two years structure in the vertical. It has the structure of a composite of Kelvin and Rossby waves. This composite system moves eastwards.
 We have also studied a linear two-level analytical model to understand the nonlinear spectral model response. In the linear as well as in the nonlinear spectral model, as we Increase the moisture availability factor the speeds of the waves decrease. In the linear model this speed is found to be independent of drag for all types of waves. In the nonlinear spectral model for a given drag there is a critical value of the moisture availability factor for which the wave becomes stationary and beyond which even shows westward propagation. Thus both moisture availability and nonlinearity appear to contribute to the slow eastward speed of the equatorial 30-50 day mode.

Compute and data intensive scientific applications demand compilers to allocate more temporaries on the stack. For example, the change resolution component of a global spectral model changes the resolution of the input files using Nearest Neighbour Interpolation which requires large temporaries on the stack. Temporaries include sub-arrays, automatic arrays and, sub-sections corresponding to actual arguments of a subroutine. If the infrastructure cannot provide adequate stack space at runtime relative to the total size of the temporaries, then the application program runs out of stack and aborts. Allocating the heap memory to store the large temporaries introduced around 25% additional runtime because of allocation and deallocation of the memory. This is observed in various components of a global spectral model. We propose an automatic dynamic stack management framework which uses application profile information and the information related to the required stack memory. It does not mandate any hardware configuration changes. This technique manages stack frames on RAM by the compiler-inserted code into the application binary. Our experiments with a global spectral model show that we are able to obtain an average runtime savings of 21% along with a compile time overhead of 4%. The actual gain depends on the size of the temporaries in an application and the size of the RAM. Currently, it supports sequential and OpenMP applications. We further enhance our framework to deal with the complex MPI and GPU programming paradigms.

The diffraction of the field of dipole radiation by two spheres

The moisture advection component of the National Meteorological Center global spectral model is replaced with a semi-Lagrangian transport scheme. Several interpolation schemes, both monotonic and nonmonotonic, which were not eliminated from contention in earlier studies with simple test systems, are compared for moisture transport in five-day forecasts. The observed conservation properties of the schemes are considered first. Many of the schemes are found to be unsatisfactory with respect to conservation although several are very good. The best nonmonotonic interpolants are Hermite cubic and a rational cubic both coupled with a cubic derivative estimate. The best monotonic interpolants are these same two with the cubic derivative estimate modified to satisfy the appropriate C° monotonicity condition. The conservation aspects of these four schemes are better than the original spectral scheme if their computational sources are compared to the negative mixing ratios introduced by the spectral method. The skill of the semi-Lagrangian forecasts as measured by the traditional global skill scores (anomaly correlation and rms) is the same as that of the original spectral model. The characteristics of the precipitation in the semi-Lagrangian forecasts are very different from those of the spectral forecast. While the major precipitation events are similar in the two in both magnitude and location, the patterns of light precipitation are very different. The spectral model produces regions of light precipitation which are attributable to spectral truncation. The semi-Lagrangian method shows no similar spurious precipitation.

In this article, we describe an implementation of two‐way coupling between the Yin–He Global Spectral Model (YHGSM) and the Wave Model (WAM). The YHGSM atmosphere model gives the surface air water density and 10‐m wind for the WAM model, while the WAM model provides the Charnock coefficient as a response. The effects on the meteorological aptitude of the two‐way coupled system are assessed statistically. The coupled model exhibits a 75% significant positive impact on both the northern (NthH) and the southern hemisphere (SthH) for all metrics at almost all pressure levels. Typhoon track assessments of the coupled model will be implemented later. The results show that the coupling of the WAM model benefits typhoon landfall prediction. Finally, we make a comprehensive comparison of the significant wave height (SWH) between the YHGSM–WAM coupled model and the European Centre for Medium‐Range Weather Forecasts (ECMWF) model with buoy data from the Chinese Ocean Monitoring Network. The comparison shows that the YHGSM–WAM coupled model exhibits more accuracy and predictive stability of SWH forecasts against buoy observations than the ECMWF forecasts. The above results indicate that the YHGSM–WAM coupled model possesses superior performance to uncoupled models.

A hybrid coupled model (HCM) consisting of a tropical Pacific Ocean and global atmosphere is presented. The ocean component is a linear reduced gravity model of the upper ocean in the tropical Pacific. The atmospheric component is a triangular 30 horizontal resolution global spectral general circulation model with 18 unevenly spaced levels in the vertical. In coupling these component models, an anomaly coupling strategy is employed. A 40-yr simulation was made with HCM and the variability in the tropical Pacific was compared to the observed variability. The HCM produces irregular ENSO events with a broad spectrum of periods between 12 and 48 months. On longer timescales, approximately 48 months, the simulated variability was weaker than the observed and on shorter timescales (approximately 24 months) the simulated variability was too strong. The simulated variability is asymmetric in the sense that the amplitude of the warm events is realistic, but there are no significant cold events. An ensemble of 60 hindcast predictions was made with the HCM and the skill was compared to other prediction systems. In forecasting sea surface temperature anomalies in the eastern Pacific, the HCM is comparable to the other prediction systems for lead times up to 10 months. The anomaly correlation coefficient for the eastern Pacific SSTA remains above 0.6 for lead times of up to 11 months. Consistent with the 40-yr simulation, hindcasts of cold events have little skill, particularly when compared to hindcasts of warm events. Specific hindcasts also demonstrate that the HCM also has difficulty predicting the transition from warm conditions to normal or cold conditions.

Abstract. The IGCM4 (Intermediate Global Circulation Model version 4) is a global spectral primitive equation climate model whose predecessors have extensively been used in areas such as climate research, process modelling and atmospheric dynamics. The IGCM4's niche and utility lies in its speed and flexibility allied with the complexity of a primitive equation climate model. Moist processes such as clouds, evaporation, atmospheric radiation and soil moisture are simulated in the model, though in a simplified manner compared to state-of-the-art global circulation models (GCMs). IGCM4 is a parallelised model, enabling both very long integrations to be conducted and the effects of higher resolutions to be explored. It has also undergone changes such as alterations to the cloud and surface processes and the addition of gravity wave drag. These changes have resulted in a significant improvement to the IGCM's representation of the mean climate as well as its representation of stratospheric processes such as sudden stratospheric warmings. The IGCM4's physical changes and climatology are described in this paper.

Directional ocean wave spectra derived from Shuttle Imaging Radar-B (SIR-B) L-band imagery collected off the coast of southern Chile on 11 and 12 October 1984 were compared with independent spectral estimates from two airborne scanning radars. In sea states with significant wave heights ranging from 3 to 5 meters, the SIR-B-derived spectra at 18 degrees and 25 degrees off nadir yielded reasonable estimates of wavelengths, directions, and spectral shapes for all wave systems encountered, including a purely azimuth-traveling system. A SIR-B image intensity variance spectrum containing predominantly range-traveling waves closely resembles an independent aircraft estimate of the slope variance spectrum. The prediction of a U.S. Navy global spectral ocean wave model on 11 October 1984 exhibited no significant bias in dominant wave number but contained a directional bias of about 30 degrees espect to the mean of the aircraft and spacecraft estimates.

Global data analysis procedures were developed to perform data assimilation for observed geopotential heights wind components, and relative humidity. These procedures were implemented in conjunction with a global spectral forecast model (GSM) and normal mode initialization procedure to produce global analyses at six-hour intervals. A set of five-day experiments were conducted to assess the impact of several alternative sources of humidity analysis procedure. Satellite moisture retrievals, surface weather observations, and Air Force Global Weather Central 3-D nephanalysis cloud amounts were used as sources of upper-air relative humidity as to permit their use in data assimilation. The 3-D nephanalysis-inferred humidities, and to a lesser extent the surface weather observation-inferred humidities, were found to have a beneficial impact on the analyses. When used in a manner to maximize their impact, their inclusion in the analysis resulted in an analysis that agreed better with withheld radiosonde relative humidity than did the uncorrected first guess.