Abstract

In 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 most 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.

Abstract

In this study, the effect of assimilating Himawari-8 (HIMA-8) atmospheric motion vectors (AMVs) on forecast errors in East Asia is evaluated using observation system experiments based on the Weather Research and Forecasting Model and three-dimensional variational data assimilation system. The experimental period is from 1 August to 30 September 2015, during which both HIMA-8 and Multifunctional Transport Satellite-2 (MTSAT-2) AMVs exist. The energy-norm forecast error based on the analysis of each experiment as reference was reduced more by replacing MTSAT-2 AMVs with HIMA-8 AMVs than by adding HIMA-8 AMVs to the MTSAT-2 AMVs. When the HIMA-8 AMVs replaced or were added to MTSAT-2 AMVs, the observation impact was reduced, which implies the analysis–forecast system was improved by assimilating HIMA-8 AMVs. The root-mean-square error (RMSE) of the 500-hPa geopotential height forecasts based on the analysis of each experiment decreases more effectively when the region lacking in upper-air wind observations is reduced by assimilating both MTSAT-2 and HIMA-8 AMVs. When the upper-air radiosonde (SOUND) observations are used as reference, assimilating more HIMA-8 AMVs decreases the forecast error. Based on various measures, the assimilation of HIMA-8 AMVs has a positive effect on the reduction of forecast errors. The effects on the energy-norm forecast error and the RMSE based on SOUND observations are greater when HIMA-8 AMVs replaced MTSAT-2 AMVs. However, the effects on the RMSE of the 500-hPa geopotential height forecasts are greater when both HIMA-8 and MTSAT-2 AMVs were assimilated, which implies potential benefits of assimilating AMVs from several satellites for forecasts over East Asia depending on the choice of measurement.

Abstract

In this study, the structure and evolution of total energy singular vectors (SVs) of Typhoon Usagi (2007) are evaluated using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) and its tangent linear and adjoint models with a Lanczos algorithm. Horizontal structures of the initial SVs following the tropical cyclone (TC) evolution suggest that, relatively far from the region of TC recurvature, SVs near the TC center have larger magnitudes than those in the midlatitude trough. The SVs in the midlatitude trough region become dominant as the TC passes by the region of recurvature. Increasing magnitude of the SVs over the midlatitude trough regions is associated with the extratropical transition of the TC. While the SV sensitivities near the TC center are mostly associated with warming in the midtroposphere and inflow toward the TC along the edge of the subtropical high, the SV sensitivities in the midlatitude are located under the upper trough with upshear-tilted structures and associated with strong baroclinicity and frontogenesis in the lower troposphere. Given the results in this study, sensitive regions for adaptive observations of TCs may be different following the TC development stage. Far from the TC recurvature, sensitive regions near TC center may be important. Closer to the TC recurvature, effects of the midlatitude trough become dominant and the vertical structures of the SVs in the midlatitude are basically similar to those of extratropical cyclones.

Abstract

In this study, the structures and growth rates of singular vectors (SVs) for Typhoon Usagi were investigated using different moist physics and norms. The fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and its tangent linear and adjoint models with a Lanczos algorithm were used to calculate SVs over a 36-h period. The moist physics used for linear (i.e., tangent linear and adjoint model) integrations is large-scale precipitation, and the norms used are dry and moist total energy (TE) norms. Overall, moist physics in linear integrations and a moist TE norm increase the growth rates of SVs and cause smaller horizontal structures and vertical distributions closer to the lower boundary. With a dry TE norm, the SV energy distributions show similar (dissimilar) large- (small-) scale horizontal SV structures for experiments, regardless of physics. The SVs with moist linear physics and a moist TE norm have maximum horizontal energy structures near the typhoon center. With a small weighting on the moisture term in the moist TE norm, both the remote and nearby influences on the TC are indicated by the horizontal SV energy distributions. The kinetic energy shows the largest contributions to the vertical SV TE distributions in most of the experiments, except for the largest moisture (potential energy) contributions to the SV TE at the final (initial) time in the moist TE norm (dry and weighted moist TE norms at uppermost levels). In contrast, the SV vorticity distributions show more consistent structures among experiments with different linear physics and norms, implying that, in terms of the rotational component of the wind field, the SVs are not sensitive to the choice of moist physics and norms. Given large-scale precipitation as the linear moist physics, the SV energy structures and growth rate with a moist TE norm show the largest difference when compared with those with other norms.

Abstract

A diagnosis of singular vector (SV) evolution in the Eady model for the potential enstrophy and energy norms is performed using potential vorticity (PV) inversion and Eliassen–Palm (E–P) flux diagnostics, and compared with the SV evolution for the streamfunction variance norm. The diagnostics reveal that the mechanism for SV amplification depends on the initial relative magnitudes of the interior PV and boundary temperature anomalies (BTAs). In addition, the relative magnitudes of the initial PV and BTAs are dependent on the norm chosen, the length scale of the perturbation, and the length of the optimization interval.

If the initial contribution of the PV to a given norm is larger than the contribution of the BTAs to that norm, then the SV evolution in that norm is governed by the baroclinic superposition of the interior PV followed by an amplification of the BTAs by winds attributed to the interior PV. In the other case, the mutual interaction of BTAs governs the SV evolution. The initial interior PV is most important for the energy and streamfunction variance SVs, but is less important for the potential enstrophy SVs. Excluding the longwave (i.e., wavelengths longer than the Eady instability cutoff) enstrophy norm SVs, for the shortwave SVs and for long optimization times, the importance of the initial interior PV is most apparent.

In the view of targeted observations, the sensitive regions indicated by the SV analysis can be identified with particular mechanisms for SV development. The forecast measure may be considered sensitive in some regions in the sense that the forecast measure exhibits a large response to small changes in the initial conditions in those regions. The potential enstrophy norm is identified as being dynamically sensitive at the boundaries in contrast to the energy and streamfunction variance norm in the midtroposphere. It is suggested that subjective PV diagnosis of sensitivity may be viewed as being consistent with an objective diagnosis of sensitivity using potential enstrophy norm SVs.

Abstract

As the need for regional reanalyses emerged around the world, a short period of the East Asia Regional Reanalysis (EARR) system was recently developed based on the Unified Model (UM). In this study, the quality of the EARR is evaluated by comparing the short-range precipitation reforecasts against reforecasts of ERA-Interim (ERA-I) reanalysis and operational forecasts of the Korea Meteorological Administration (OPER). For the verification, two different periods are selected for 14 days in the summer (July 2013, denoted as 201307) and winter (February 2014, denoted as 201402). The equitable threat score (ETS) of EARR and OPER is generally greater than that of ERA-I. The frequency bias index (FBI) of EARR and OPER is overall closer to 1 than that of ERA-I for all thresholds, which indicates that EARR and OPER are much closer to the observation compared to ERA-I. For the period 201307, the ERA-I FBI is greater than 1 for lower thresholds and the probability of detection (POD) and false alarm ratio (FAR) of ERA-I are high, implying that ERA-I tends to overforecast light precipitation. In addition, using the same Weather Research and Forecasting (WRF) Model, the 6-h precipitation forecasts are integrated every 12 h (initialized from 0000/1200 UTC) for 4 months for the summer and winter season. Although the differences of ETS and FBI between EARR and ERA-I are not distinct for the summer season, overall EARR ETS is higher than ERA-I ETS, and EARR FBI is closer to 1 than ERA-I FBI. Based on several evaluations, the precipitation reforecasts of EARR are confirmed to be more accurate than those of OPER and ERA-I in East Asia.

Abstract

In this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

Abstract

In this study, the initial ensemble perturbation characteristics of the new Korea Meteorological Administration (KMA) ensemble prediction system (EPS), a version of the Met Office Global and Regional Ensemble Prediction System, were analyzed over two periods: from 1 June to 31 August 2011, and from 1 December 2011 to 29 February 2012. The KMA EPS generated the initial perturbations using the ensemble transform Kalman filter (ETKF). The observation effect was reflected in both the transform matrix and the inflation factor of the ETKF; it reduced (increased) uncertainties in the initial perturbations in regions with dense observations via the transform matrix (inflation factor). The reduction in uncertainties is generally governed by the transform matrix but locally modulated by the inflation factor. The sea ice significantly affects the initial perturbations near the lower boundary layer. The large perturbation energy in the lower stratosphere of the tropics was related to the dominant zonal wind, whereas the perturbation energy in the upper stratosphere of the winter hemispheres was related to the dominant polar night jet. In the early time-integration stage, the initial perturbations decayed in the lower troposphere but grew rapidly in the mid- to upper troposphere. In the meridional direction, the initial perturbations grew greatest in the northern polar region and smallest in the tropics. The initial perturbations maintained a hydrostatic balance, especially during the summer in both hemispheres and during both the summer and winter in the tropics, associated with the smallest growth rates of the initial perturbations. The initial perturbations in the KMA EPS appropriately describe the uncertainties associated with atmospheric features.

Abstract

In this study, the observation impacts on 24-h forecast error reduction (FER), based on the adjoint method in the four-dimensional variational (4DVAR) data assimilation (DA) and hybrid-4DVAR DA systems coupled with the Unified Model, were evaluated from 0000 UTC 5 August to 1800 UTC 26 August 2014. The nonlinear FER in hybrid-4DVAR was 12.2% greater than that in 4DVAR due to the use of flow-dependent background error covariance (BEC), which was a weighted combination of the static BEC and the ensemble BEC based on ensemble forecasts. In hybrid-4DVAR, the observation impacts (i.e., the approximated nonlinear FER) for most observation types increase compared to those in 4DVAR. The increased observation impact from using hybrid-4DVAR instead of 4DVAR changes depending on the analysis time and regions. To calculate the ensemble BEC in hybrid-4DVAR, analyses at 0600 and 1800 UTC (0000 and 1200 UTC) used 3-h (9-h) ensemble forecasts. Greater observation impact was obtained when 3-h ensemble forecasts were used for the ensemble BEC at 0600 and 1800 UTC, than with 9-h ensemble forecasts at 0000 and 1200 UTC. Different from other observations, the atmospheric motion vectors (AMVs) deduced from geostationary satellite are more frequently observed in the same area. When the ensemble forecasts with longer integration times were used for the ensemble BEC in hybrid-4DVAR, the observation impact of the AMVs decreased the most in East Asia. This implies that the observation impact of AMVs in East Asia shows the highest sensitivity to the integration time of the ensemble members used for deducing the flow-dependent BEC in hybrid-4DVAR.

Abstract

In this study, structures of real-time adaptive observation guidance provided by Yonsei University (YSU) in South Korea during The Observing System Research and Predictability Experiment (THORPEX)-Pacific Asian Regional Campaign (T-PARC) are presented and compared with those of no-lead-time adaptive observation guidance recalculated as well as other adaptive observation guidance for a tropical cyclone (Jangmi 200815). During the T-PARC period, real-time dry total energy (TE) singular vectors (SVs) based on the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the corresponding tangent linear and adjoint models with a Lanczos algorithm are provided by YSU to help determine sensitive regions for targeted observations. While YSU provided the real-time TESV guidance based on a mesoscale model, other institutes provided real-time TESV guidance based on global models. The overall features of the real-time MM5 TESVs were similar to those generated from global models, showing influences from tropical cyclones, midlatitude troughs, and subtropical ridges. TESV structures are very sensitive to verification region and forecast lead time. If a more accurate basic-state trajectory with no lead time is used, more accurate TESVs, which yield more accurate determinations of sensitive regions for targeted observations, may be calculated. The results of this study may imply that reducing forecast lead time is an important component to obtaining better sensitivity guidance for real-time targeted observation operations.