AIM CIPS PMC tracking wind product retrieval approach and first assessment

This study presents the assessment and seasonal variation of wave energy along the southern coast of Java, Bali, and Nusa Tenggara Waters. For this purpose, the WAVEWATCH-III numerical model was used to simulate the Significant Wave Height in the study region over 25 years covering the time interval of 1991–2015. Wind field data input for the model was a combined dataset of Cross-Calibrated Multi-Platform, Navy Global Environmental Model, and Navy Operational Global Atmospheric Prediction System. In general, the simulation results showed that there was a good potential of wave energy along the southern coast of Java and Bali with the value of higher than 20 kW/m. Furthermore, it was found that there were 12 points which were considered to be the most promising high wave energy potential spots along the near-shore coastal waters of the Java and Bali southern coast. There was a noticeable seasonal variation of wave energy along the study area associated with tropical monsoon climates, which led to the highest value in the period of June to August for about 40 kW/m and the lowest value in the period of December to February for about 20 kW/m. All the selected points for wave energy exhibited dominant wave propagation between northward and northeastward. Moreover, there was an evident increasing trend of wave energy with the peak value appearing in 2005 for all stations.

Abstract A quasi 2‐day wave (QTDW) during the austral summer period usually coincides with a sudden stratospheric warming (SSW) event in the winter hemisphere, while the SSW influences on QTDWs are not totally understood. In this work, the hourly Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude reanalysis data sets during January/February 2006 are utilized to study the contribution of a major SSW on the anomalous QTDW activities during the same period. Our new findings are generalized as follows: (1) The summer easterly is enhanced during a SSW event due to the interhemispheric coupling, which is clearly indicated by the anomalous cross‐equator circulation from the winter to summer mesosphere. (2) The enhanced summer easterly could sustain critical layers for QTDWs with larger phase speeds (e.g., smaller zonal wave number or shortwave period) and strengthen the summer easterly barotropic/baroclinic instabilities, which are essential for the QTDW amplification through wave‐mean flow interactions. This is why a strong westward QTDW with zonal wave number 2 is identified besides the conventionally dominant wave mode of wave number 3, and their periods are only ~42–45 hr during January 2006. (3) The strong winter planetary waves during SSW periods facilitate the occurrence of the nonlinear interaction between QTDWs and stationary planetary waves, which is strongly suggested by the abnormal temporal variations of wave number 2 and wave number 3 QTDWs. We conclude that the anomalous QTDW behaviors in summer mesosphere during January 2006 are associated with the major SSW event in the winter stratosphere.

Indonesia is passed by an atmospheric phenomenon, called the Madden-Julian Oscillation (MJO), which has an impact on the wave height in the Indonesian Seas. The significant wave height is simulated using WAVEWATCH-III (WW3) numerical model in Indonesian region (90 °E-150 °E, 20 °N-20 °S) forced by surface winds from Cross-Calibrated Multi-Platform (CCMP), Navy Global Environmental Model (NAVGEM), and Navy Operational Global Atmospheric Prediction System (NOGAPS). This simulation is concentrated on MJO phase 3, 4, and 5 which passed through Indonesia and its adjacent waters that occurred in particular time between 1990-2015. In this study, the impact of MJO was analyzed during every monsoon season. In addition, wind speed analysis was carried out to further enrich the analysis of the MJO impact. The simulation result shows that MJO exerts the highest impact during phase 5 and DJF, which contributes to the increase of wind speed (WS) and significant wave height (SWH) in Indonesian inner seas by 6 m/s and 30 cm, respectively, and in southern Lesser Sunda Island by 8 m/s and 1.2 m, respectively. MJO can also contribute to decreasing of the WS and SWH, when it occurred during DJF and MAM phase 3, and JJA phase 4. There is no noticabe change of WS and SWH during SON.

Impact of non-migrating tides on the low latitude ionosphere during a sudden stratospheric warming event in January 2010

Abstract We present a combination of satellite observation and high‐resolution model output to understand monsoon convection as a source of high‐latitude mesospheric gravity waves (GWs). The GWs generated over the Northern Hemisphere (NH) monsoon region during the 2007 summer and the role of the winds in focusing these GWs toward the high‐latitude middle atmosphere are analyzed using the Sounding of the Atmosphere using Broadband Emission Radiometry/Thermosphere Ionosphere Mesosphere Energetics and Dynamics (SABER/TIMED) satellite temperature data and the high‐resolution Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude (NOGAPS/ALPHA) model results. In the NH, above the stratosphere, the monsoon GW Momentum Flux (GWMF) exhibits a poleward tilt that follows the slanted structure of the easterly jet. The correlation coefficients (>0.5) between the time series of NH tropical stratospheric GWMF and the global winds also have a slanted structure that coincide with the easterly jet, confirming the modeling theory that stratospheric monsoon GWs are refracted into the summer easterly jet and can reach the high‐latitude mesosphere. Since Polar Mesospheric Clouds (PMCs) are sensitive indicators of changes in the polar summer mesosphere, we compared the time series of tropical stratospheric GWMF to the PMC occurrence frequency (OF) obtained from the Cloud Imaging and Particle Size/Aeronomy of Ice in the Mesosphere satellite data to assess the influence of this wave focusing in the mesosphere. There is a significant positive correlation between the high‐latitude PMC OF and the tropical stratospheric GWMF suggesting a definite influence of monsoon GWs on the high‐latitude mesosphere. The disagreement in correlation at the end of the PMC season is attributed to the enhancement of the quasi 5 day planetary wave dominating over the influence of monsoon GWs on PMCs.

Abstract We compare D and lower E region ionospheric model calculations driven by the Whole Atmosphere Community Climate Model (WACCM) with a selection of electron density profiles made by sounding rockets over the past 50 years. The WACCM model, in turn, is nudged by winds and temperatures from the Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude (NOGAPS‐ALPHA). This nudging has been shown to greatly improve the representation of key neutral constituents, such as nitric oxide (NO), that are used as inputs to the ionospheric model. We show that with this improved representation, we greatly improve the comparison between calculated and observed electron densities relative to older studies. At midlatitudes, for both winter and equinoctal conditions, the model agrees well with the data. At tropical latitudes, our results confirm a previous suggestion that there is a model deficit in the calculated electron density in the lowermost D region. We then apply the calculated electron densities to examine the variation of HF absorption with altitude, latitude, and season and from 2008 to 2009. For low latitudes, our results agree with recent studies showing a primary peak absorption in the lower E region with a secondary peak below 75 km. For midlatitude to high latitude, the absorption contains a significant contribution from the middle D region where ionization of NO drives the ion chemistry. The difference in middle‐ to high‐latitude absorption from 2008 to 2009 is due to changes in the NO abundance near 80 km from changes in the wintertime mesospheric residual circulation.

Abstract This study presents the analysis of 14 months (January 2009 to February 2010) of continuous hourly Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude reanalysis data used for examining the quasi 2 day wave (QTDW). The global structure and seasonal variability of the eastward and westward traveling QTDWs in all meteorological fields (geopotential height, zonal and meridional wind, and temperature) have been studied. The use of hourly reanalysis data allows a comprehensive understanding of the global spatial‐temporal QTDW distribution by simultaneous separations of all tides and planetary waves. The wave characteristics (amplitudes and phases) are presented in latitude range ±80° and altitudes from 15 to 95 km. Two different types of eastward traveling waves are identified: (i) waves at middle and high latitudes with zonal wave numbers 2 and 3, which are observed in the local winters, and (ii) waves observed predominantly over the equator with zonal wave number 2, which do not have a well‐defined seasonal variability but show some enhancement between June and August. While the first type waves are seen in all meteorological fields, the second ones are not seen in the meridional wind and belong to the ultrafast Kelvin waves. Two different types of westward traveling waves have been identified as well: (i) waves at middle and high latitudes with zonal wave numbers 2, 3, and 4, which are observed mainly in summer hemisphere, and (ii) waves observed predominantly over the equator with zonal wave numbers 1, 2, and 3, enhanced predominantly at both solstices but are seen in other seasons as well. While the first type waves are seen in all meteorological fields, the second ones are observed in the meridional wind and are Rossby‐gravity normal modes.

Abstract We compare simulations of mesospheric tracer descent in the winter and spring of 2009 with two versions of the Whole Atmosphere Community Climate Model (WACCM), both with specified dynamics. One is constrained with data from the Modern‐Era Retrospective Analysis for Research and Applications which extends from 0 to 50 km; the other uses the Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude (NOGAPS‐ALPHA) which extends up to 92 km. By comparison with Solar Occultation for Ice Experiment data we show that constraining WACCM to NOGAPS‐ALPHA yields a dramatic improvement in the simulated descent of enhanced nitric oxide (NO) and very low methane (CH4). We suggest that constraining to NOGAPS‐ALPHA compensates for an underestimate of nonorographic gravity wave drag in WACCM. Other possibilities, such as missing energetic particle precipitation or underestimated eddy diffusion, are less likely for the Arctic winter and spring of 2009.

Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. This study outlines a methodology for combining multiple ocean satellite winds and winds from WRF simulations in order to acquire the accurate reconstructed offshore winds which can be used for offshore wind resource assessment. First, wind speeds retrieved from Synthetic Aperture Radar (SAR) and Scatterometer ASCAT images were validated against in situ measurements from seven coastal meteorological stations in South China Sea (SCS). The wind roses from the Navy Operational Global Atmospheric Prediction System (NOGAPS) and ASCAT agree well with these observations from the corresponding in situ measurements. The statistical results comparing in situ wind speed and SAR-based (ASCAT-based) wind speed for the whole co-located samples show a standard deviation (SD) of 2.09 m/s (1.83 m/s) and correlation coefficient of R 0.75 (0.80). When the offshore winds (i.e., winds directed from land to sea) are excluded, the comparison results for wind speeds show an improvement of SD and R, indicating that the satellite data are more credible over the open ocean. Meanwhile, the validation of satellite winds against the same co-located mast observations shows a satisfactory level of accuracy which was similar for SAR and ASCAT winds. These satellite winds are then assimilated into the Weather Research and Forecasting (WRF) Model by WRF Data Assimilation (WRFDA) system. Finally, the wind resource statistics at 100 m height based on the reconstructed winds have been achieved over the study area, which fully combines the offshore wind information from multiple satellite data and numerical model. The findings presented here may be useful in future wind resource assessment based on satellite data.

Abstract In October 2010, typhoon Megi induced a profound cold wake of size 800 km by 500 km with sea surface temperature cooling of 8°C in the South China Sea (SCS). More interestingly, the cold wake shifted from the often rightward bias to both sides of the typhoon track and moved to left in a few days. Using satellite data, in situ measurements and numerical modeling based on the East Asian Seas Nowcast/Forecast System (EASNFS), we performed detailed investigations. To obtain realistic typhoon‐strength atmospheric forcing, the EASNFS applied typhoon‐resolving Weather Research and Forecasting (WRF) model wind field blended with global weather forecast winds from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS). In addition to the already known impacts from the slow typhoon translation speed and shallow pre‐exiting ocean thermocline, we found the importance of the unique geographical setting of the SCS and the NE monsoon. As the event happened in late October, NE monsoon already started and contributed to the southwestward ambient surface current. Together with the topographicβ effect, the cold wake shifted westward to the left of Megi's track. It was also found that Megi expelled waters away from the SCS and manifested as a gush of internal Kelvin wave exporting waters through the Luzon Strait. The consequential sea level depression lasted and presented a favorable condition for cold dome development. Fission of the north‐south elongated cold dome resulted afterward and produced two cold eddies that dissipated slowly thereafter.

The high‐altitude analysis from the Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude (NOGAPS‐ALPHA) forecast/assimilation system is used to initialize a series of 10 day forecasts at different spatial resolutions without any assumed gravity wave drag parameterization. As the spatial resolution is increased from 2.25° (spectral truncation at 79 total wave numbers, T79) to 0.75° (T239) and finally, to 0.375°(T479), the model simulation progressively improves compared with the analysis. The model vertical momentum fluxes are significantly greater at T479 relative to T239, consistent with resolving a greater fraction of the gravity wave spectrum. However, even at 0.375° resolution, a residual cold bias at the winter stratopause and warm bias at the summer mesopause remain, suggesting a continuing need for parameterized gravity wave drag. In addition, the zonal mean temperature solution is sensitive to the assumed value of spectral hyperdiffusion, thus highlighting an additional parameter that must be properly tuned in high‐resolution middle atmosphere models.

Abstract Tropical cyclone (TC) forecasts rely heavily on output from global numerical models. While considerable research has investigated the skill of various models with respect to track and intensity, few studies have considered how well global models forecast TC genesis in the North Atlantic basin. This paper analyzes TC genesis forecasts from five global models [Environment Canada's Global Environment Multiscale Model (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF) global model, the Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Met Office global model (UKMET)] over several seasons in the North Atlantic basin. Identifying TCs in the model is based on a combination of methods used previously in the literature and newly defined objective criteria. All model-indicated TCs are classified as a hit, false alarm, early genesis, or late genesis event. Missed events also are considered. Results show that the models' ability to predict TC genesis varies in time and space. Conditional probabilities when a model predicts genesis and more traditional performance metrics (e.g., critical success index) are calculated. The models are ranked among each other, and results show that the best-performing model varies from year to year. A spatial analysis of each model identifies preferred regions for genesis, and a temporal analysis indicates that model performance expectedly decreases as forecast hour (lead time) increases. Consensus forecasts show that the probability of genesis noticeably increases when multiple models predict the same genesis event. Overall, this study provides a climatology of objectively identified TC genesis forecasts in global models. The resulting verification statistics can be used operationally to help refine deterministic and probabilistic TC genesis forecasts and potentially improve the models examined.

Abstract The effect on weather forecast performance of incorporating ensemble covariances into the initial covariance model of the four-dimensional variational data assimilation (4D-Var) Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR) is investigated. This NAVDAS-AR-hybrid scheme linearly combines the static NAVDAS-AR initial background error covariance with a covariance derived from an 80-member flow-dependent ensemble. The ensemble members are generated using the ensemble transform technique with a (three-dimensional variational data assimilation) 3D-Var-based estimate of analysis error variance. The ensemble covariances are localized using an efficient algorithm enabled via a separable formulation of the localization matrix. The authors describe the development and testing of this scheme, which allows for assimilation experiments using differing linear combinations of the static and flow-dependent background error covariances. The tests are performed for two months of summer and two months of winter using operational model resolution and the operational observational dataset, which is dominated by satellite observations. Results show that the hybrid mode data assimilation scheme significantly reduces the forecast error across a wide range of variables and regions. The improvements were particularly pronounced for tropical winds. The verification against radiosondes showed a greater than 0.5% reduction in vector wind RMS differences in areas of statistical significance. The verification against self-analysis showed a greater than 1% reduction from verifying against analyses between 2- and 5-day lead time at all eight vertical levels examined in areas of statistical significance. Using the Navy's summary of verification results, the Navy Operational Global Atmospheric Prediction System (NOGAPS) scorecard, the improvements resulted in a score (+1) that justifies a major system upgrade.

Case study of an ice void structure in polar mesospheric clouds

Abstract An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near–real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from numerical weather prediction model surface wind field forecasts, replaces the removed winds with interpolated values from surrounding grid points, and then adds a surface wind field generated from the official forecast into the background. The modified wind fields are then used as input into the WAVEWATCH III model to provide seas consistent with the official tropical cyclone forecasts. Although this product is appealing to forecasters because of its consistency and its superior tropical cyclone track forecast, there has been only anecdotal evaluation of resulting wave fields to date. This study evaluates this new algorithm for two years’ worth of Atlantic tropical cyclones and compares results with those of WAVEWATCH III run with U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) surface winds alone. Results show that the new algorithm has generally improved forecasts of maximum significant wave heights and 12-ft seas’ radii in proximity to tropical cyclones when compared with forecasts produced using only the NOGAPS surface winds.

ABSTRACTA multi-model archive of global deterministic forecasts and analyses from three operational systems is constructed to analyse recent Northern Hemisphere mid-latitude forecast skill from 2007 to 2012 and its relation to large-scale atmospheric flow anomalies defined by the Arctic Oscillation (AO) index. We find that the anomaly correlation coefficient (ACC) in 120-hr forecasts of 500 hPa geopotential height has similar variability on synoptic, monthly, and seasonal time scales in each of the three forecast systems examined here: the European Centre for Medium-Range Weather Forecasts, the National Centers for Environmental Prediction Global Forecast System, and the U.S. Navy Operational Global Atmospheric Prediction System. The results indicate that forecast skill as measured by the ACC is significantly correlated with the AO index and its transitions between negative and positive phase. Intervals of exceptionally high ACC skill during the 2009–2010 and 2010–2011 winters are associated with periods in which the AO remained in a persistent negative phase pattern. Episodes of low ACC, including so-called ‘forecast skill dropouts’ most frequently occur during transitions between negative and positive AO index and with positive AO index. The root mean square error (RMSE) of 120-hr forecast 500 hPa height is also modulated by the AO index, but to a lesser extent than the ACC. In two recent winters, the RMSE indicates lower 120-hr forecast accuracy during periods with negative AO index, which is opposite to ‘skill’ patterns provided by the ACC. These results suggest that the ACC is not in all situations an optimal metric with which to quantify model forecast skill, since the ACC can be higher when the large-scale atmospheric flow contains strong anomalies even if there is no actual improvement in model forecasts of that atmospheric state.

The local ensemble transform (ET) analysis perturbation scheme is adapted to generate perturbations to both atmospheric variables and sea‐surface temperature (SST). The adapted local ET scheme is used in conjunction with a prognostic model of SST diurnal variation and the Navy Operational Global Atmospheric Prediction System (NOGAPS) global spectral model to generate a medium‐range forecast ensemble. When compared to a control ensemble, the new forecast ensemble with SST variation exhibits notable differences in various physical properties including the spatial patterns of surface fluxes, outgoing longwave radiation (OLR), cloud radiative forcing, near‐surface air temperature and wind speed, and 24‐h accumulated precipitation. The structure of the daily cycle of precipitation also is substantially changed, generally exhibiting a more realistic midday peak of precipitation. Diagnostics of ensemble performance indicate that the inclusion of SST variation is very favorable to forecasts in the Tropics. The forecast ensemble with SST variation outscores the control ensemble in the Tropics across a broad set of metrics and variables. The SST variation has much less impact in the Midlatitudes. Further comparison shows that SST diurnal variation and the SST analysis perturbations are each individually beneficial to the forecast from an overall standpoint. The SST analysis perturbations have broader benefit in the Tropics than the SST diurnal variation, and inclusion of the SST analysis perturbations together with the SST diurnal variation is essential to realize the greatest gains in forecast performance.

The objective of this study is to i) investigate the effects of orography on the rainfall, wind, and cloud systems of the Typhoon Ketsana (2009) in Indochina, ii) determine rainfall distribution patterns and which parts of Indochina were most affected during Typhoon Ketsana, iii) identify trends in the cloud and rainfall distribution patterns and wind flow patterns in the synoptic scale on orographic effects during Typhoon Ketsana. Remote sensing techniques have been used to study the impacts of TCs. Using data from the remote sensing data such as Fengyun 2D (FY-2D) satellite, Global Digital Elevation Model (GDEM) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite, wind information from the Navy Operational Global Atmospheric Prediction System (NOGAPS), and radiosonde data were applied in this study to determine the relationship of the typhoon with the orographic effect. This study provides examples of how the orographic effect is important to weather forecasters, as high mountain ranges were able to influence the distribution of the cloud, rainfall and even wind flow patterns during the typhoon season. This remote sensing technique allows tropical cyclones to be forecasted and their impacts to be defined, and it allows disaster zones to be determined.

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.