Error covariance sensitivity and impact estimation with adjoint 4D‐Var: theoretical aspects and first applications to NAVDAS‐AR

Adjoint techniques are effective tools for the analysis and optimization of the observation performance on reducing the errors in the forecasts produced by atmospheric data assimilation systems (DASs). This chapter provides a detailed exposure of the equations that allow the extension of the adjoint-DAS applications from observation sensitivity and forecast impact assessment to diagnosis and tuning of parameters in the observation and background error covariance representation. The error covariance sensitivity analysis allows the identification of those parameters of potentially large impact on the forecast error reduction and provides a first-order diagnostic to parameter specification. A proof-of-concept is presented together with comparative results of observation impact assessment and sensitivity analysis obtained with the adjoint versions of the Naval Research Laboratory Atmospheric Variational Data Assimilation System – Accelerated Representer (NAVDAS-AR) and the Navy Operational Global Atmospheric Prediction System (NOGAPS).

In June 1990, the assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System (NOGAPS) was initiated at Fleet Numerical Oceanography Center (FNOC). These observations are derived directly from the information contained in the tropical cyclone warnings issued by the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center. This paper describes these synthetic observations, the evolution of their use at FNOC, and the details of their assimilation into NOGAPS. The results of a comprehensive evaluation of the 1991 NOGAPS tropical cyclone forecast performance in the western North Pacific are presented. NOGAPS analysis and forecast position errors were determined for all tropical circulations of tropical storm strength or greater. It was found that, after the assimilation of synthetic observations, the NOGAPS spectral forecast model consistently maintained the tropical circulations as evidenced by detection percentages of 96%, 90% ...

The paper evaluates the meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones. It is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The meterological characteristics of the NOGAPS tropical cyclone predictions are evaluated by examining the formation of low-level cyclone systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones.

The convective parameterization of Emanuel has been employed in the forecast model of the Navy Operational Global Atmospheric Prediction System (NOGAPS) since 2000, when it replaced a version of the relaxed Arakawa–Schubert scheme. Although in long-period data assimilation forecast tests the Emanuel scheme has been found to perform quite well in NOGAPS, particularly for tropical cyclones, some weaknesses have also become apparent. These weaknesses include underprediction of heavy-precipitation events, too much light precipitation, and unrealistic heating at upper levels. Recent research efforts have resulted in modifications of the scheme that are designed to reduce such problems. One change described here involves the partitioning of the cloud-base mass flux into mixing cloud mass flux at individual levels. The new treatment significantly reduces a heating anomaly near the tropopause that is associated with a large amount of mixing cloud mass flux ascribed to that region in the original Emanuel ...

A high-order accurate radiative transfer (RT) model developed by Fu and Liou has been implemented into the Navy Operational Global Atmospheric Prediction System (NOGAPS) to improve the energy budget and forecast skill. The Fu–Liou RT model is a four-stream algorithm (with a two-stream option) integrating over 6 shortwave bands and 12 longwave bands. The experimental 10-day forecasts and analyses from data assimilation cycles are compared with the operational output, which uses a two-stream RT model of three shortwave and five longwave bands, for both winter and summer periods. The verifications against observations of radiosonde and surface data show that the new RT model increases temperature accuracy in both forecasts and analyses by reducing mean bias and root-mean-square errors globally. In addition, the forecast errors also grow more slowly in time than those of the operational NOGAPS because of accumulated effects of more accurate cloud–radiation interactions. The impact of parameterized cloud effective radius in estimating liquid and ice water optical properties is also investigated through a sensitivity test by comparing with the cases using constant cloud effective radius to examine the temperature changes in response to cloud scattering and absorption. The parameterization approach is demonstrated to outperform that of constant radius by showing smaller errors and better matches to observations. This suggests the superiority of the new RT model relative to its operational counterpart, which does not use cloud effective radius. An effort has also been made to improve the computational efficiency of the new RT model for operational applications.

The Navy Operational Global Atmospheric Prediction System (NOGAPS) has proven itself to be competitive with any of the large forecast models run by the large operational forecast centers around the world. The navy depends on NOGAPS for an astonishingly wide range of applications, from ballistic winds in the stratosphere to air-sea fluxes to drive ocean general circulation models. Users of these applications will benefit from a better understanding of how a system such as NOGAPS is developed, what physical assumptions and compromises have been made, and what they can reasonably expect in the future as the system continues to evolve. The discussions will be equally relevant for users of products from other large forecast centers, e.g., National Meteorological Center, European Centre for Medium-Range Weather Forecasts. There is little difference in the scientific basis of the models and the development methodologies used for their development. However, the operational priorities of each center and t...

The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.

A set of criteria is developed to identify tropical cyclone (TC) formations in the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecast fields. Then the NOGAPS forecasts of TC formations from 1997 to 1999 are verified relative to a formation time defined to be the first warning issued by the Joint Typhoon Warning Center. During these three years, the spatial distributions of TC formations were strongly affected by an El Nino–Southern Oscillation event. The successful NOGAPS predictions of formation within a maximum separation threshold of 4° latitude are about 70%–80% for 24-h forecasts, and drop to about 20%–30% for 120-h forecasts. The success rate is higher for formations in the South China Sea and between 160°E and 180° but is generally lower between 120° and 160°E. The composite 850-hPa large-scale flow for the formations between 120° and 160°E is similar to a monsoon confluence region with marked cross-equatorial flow. Therefore, it is concluded that the skil...

This study is Part II of the effort to improve the forecasting of sudden stratospheric warming (SSW) events by using a version of the Navy Operational Global Atmospheric Prediction System (NOGAPS) that covers the full stratosphere. In Part I, extended-range (3 week) hindcast experiments (without data assimilation) for the January 2009 Arctic major SSW were performed using NOGAPS with a unified orographic drag parameterization that consists of the schemes employed by Webster et al., as well as Kim and Arakawa and Kim and Doyle. Part I demonstrated that the model with upgraded middle-atmospheric orographic drag physics better forecasts the magnitude and evolution of the SSW and better simulates the trend of the Arctic Oscillation (AO) index. In this study (Part II), a series of 5-day hindcast experiments is performed with cycling data assimilation using the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR), a four-dimensional variational data assimilation (4DVAR) system. Further efforts are made to improve the hindcasting of SSW by improving the satellite radiance bias correction process that strongly affects the data assimilation. The innovation (observation minus background) limit is optimally determined to reduce the rejection of useful radiance data. It is found that when the innovation limit is properly set, both the analysis and forecast of the SSW event can be improved, and that the orographic drag helps improve the SSW forecast.

The major weather services worldwide have concluded that longer-term tropospheric weather forecasting will require a more realistic treatment of the stratosphere. A major research effort is now underway at the Naval Research Laboratory (NRL) to extend the Navy Operational Global Atmospheric Prediction System (NOGAPS) into the stratosphere. The extended NOGAPS must assimilate and forecast ozone because absorption of UV radiation by ozone provides the primary energy input into the stratosphere. This energy input is a major driver of the stratospheric circulation, which, in turn, significantly affects the large-scale movement of surface weather systems. Operational ozone data for the extended NOGAPS will be obtained from the NPOESS Ozone Mapping and Profiler Suite (OMPS). OMPS consists of a nadir-viewing instrument that measures the ozone total column and profile (similar to TOMS & SBUV/2), and a limb-viewing instrument designed to measure the ozone profile between the tropopause and 60 km. OMPS-like ozone data are needed for developing and testing the extensions to NOGAPS. We have proposed an early flight of OMPS, OMPS-AE (OMPS-Assimilation Experiment), to provide such data. We are also exploring techniques for merging and extending data from existing satellite measurements of ozone profiles to produce 3D global ozone fields. In the future we will conduct experiments in which the global ozone fields from OMPS-AE or the data fusion experiments will be assimilated into the extended NOGAPS, with the aim of evaluating assimilation methodologies and increased forecasting skill.

A very strong Arctic major sudden stratospheric warming (SSW) event occurred in late January 2009. The stratospheric temperature climbed abruptly and the zonal winds reversed direction, completely splitting the polar stratospheric vortex. A hindcast of this event is attempted by using the Navy Operational Global Atmospheric Prediction System (NOGAPS), which includes the full stratosphere with its top at around 65 km. As Part I of this study, extended-range (3 week) forecast experiments are performed using NOGAPS without the aid of data assimilation. A unified parameterization of orographic drag is designed by combining two parameterization schemes; one by Webster et al., and the other by Kim and Arakawa and Kim and Doyle. With the new unified orographic drag scheme implemented, NOGAPS is able to reproduce the salient features of this Arctic SSW event owing to enhanced planetary wave activity induced by more comprehensive subgrid-scale orographic drag processes. The impact of the SSW on the tropospheric circulation is also investigated in view of the Arctic Oscillation (AO) index, which calculated using 1000-hPa geopotential height. The NOGAPS with upgraded orographic drag physics better simulates the trend of the AO index as verified by the Met Office analysis, demonstrating its improved stratosphere–troposphere coupling. It is argued that the new model is more suitable for forecasting SSW events in the future and can serve as a tool for studying various stratospheric phenomena.

Optimizing surface winds using QuikSCAT measurements in the Mediterranean Sea during 2000–2006

This paper examines the sensitivity of sea surface temperature (SST) to water turbidity in the Black Sea using the eddy-resolving (∼3.2-km resolution) Hybrid Coordinate Ocean Model (HYCOM), which includes a nonslab K-profile parameterization (KPP) mixed layer model. The KPP model uses a diffusive attenuation coefficient of photosynthetically active radiation (kPAR) processed from a remotely sensed dataset to take water turbidity into account. Six model experiments (expt) are performed with no assimilation of any ocean data and wind/thermal forcing from two sources: 1) European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA) and 2) Fleet Numerical Meteorology and Oceanography Center (FNMOC) Navy Operational Global Atmospheric Prediction System (NOGAPS). Forced with ECMWF, experiment 1 uses spatially and monthly varying kPAR values over the Black Sea, experiment 2 assumes all of the solar radiation is absorbed at the sea surface, and experiment 3 uses a constant kPAR value of 0.06 m−1, representing clear-water constant solar attenuation depth of 16.7 m. Experiments 4, 5, and 6 are twins of 1, 2, and 3 but forced with NOGAPS. The monthly averaged model SSTs resulting from all experiments are then compared with a fine-resolution (∼9 km) satellite-based monthly SST climatology (the Pathfinder climatology). Because of the high turbidity in the Black Sea, it is found that a clear-water constant attenuation depth (i.e., expts 3 and 6) results in SST bias as large as 3°C in comparison with standard simulations (expts 1 and 4) over most of the Black Sea in summer. In particular, when using the clear-water constant attenuation depth as opposed to using spatial and temporal kPAR, basin-averaged rms SST difference with respect to the Pathfinder SST climatology increases ∼46% (from 1.41°C in expt 1 to 2.06°C in expt 3) in the ECMWF forcing case. Similarly, basin-averaged rms SST difference increases ∼36% (from 1.39°C in expt 4 to 1.89°C in expt 6) in the NOGAPS forcing case. The standard HYCOM simulations (expts 1 and 4) have a very high basin-averaged skill score of 0.95, showing overall model success in predicting climatological SST, even with no assimilation of any SST data. In general, the use of spatially and temporally varying turbidity fields is necessary for the Black Sea OGCM studies because there is strong seasonal cycle and large spatial variation in the solar attenuation coefficient, and an additional simulation using a constant kPAR value of 0.19 m−1, the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) space–time mean for the Black Sea, did not yield as accurate SST results as experiments 1 and 4. Model–data comparisons also revealed that relatively large HYCOM SST errors close to the coastal boundaries can be attributed to the misrepresentation of land– sea mask in the ECMWF and NOGAPS products. With the relatively accurate mask used in NOGAPS, HYCOM demonstrated the ability to simulate accurate SSTs in shallow water over the broad northwest shelf in the Black Sea, a region of large errors using the inaccurate mask in ECMWF. A linear relationship is found between changes in SST and changes in heat flux below the mixed layer. Specifically, a change of ∼50 W m−2 in sub-mixed-layer heat flux results in a SST change of ∼3.0°C, a value that occurs when using clear-water constant attenuation depth rather than monthly varying kPAR in the model simulations, clearly demonstrating potential impact of penetrating solar radiation on SST simulations.

The purpose of this paper is to discuss the major systematic errors of the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS), version 3.2, and to describe several tuning experiments of NOGAPS parameterizations. It is found that despite its overall good performance, major systematic errors exist in the forecast model. These errors lead to a warmer atmosphere with less precipitation and eddy kinetic energy than is observed. Some of the errors may be attributed to the lack of horizontal and vertical resolution, but most of the errors are due to inadequacies and incorrect assumptions in the physical parameterizations. We present a list of the systematic errors of the operational 5-day forecasts and results of a 1-yr integration with climatological sea surface temperatures. One of the prominent features of NOGAPS integrations is a large diurnal oscillation in the global mean averages. This oscillation is traced to large differences in total albedo over the land and sea areas. We pres...

The second in a series of studies designed to identify systematic pressure, displacement, and directional errors in the 48-hour surface pressure forecast of extratropical cyclones by the Navy Operational Global Atmospheric Prediction System (NOGAPS) has been completed for the 1983 Northern Hemisphere winter season (5 January–31 March). All available NOGAPS 0000 and 1200 GMT forecast cycles are verified for the Western Pacific, Eastern Pacific, and Atlantic Oceans north of the equator. NOGAPS generally underforecasts the intensity of cyclones during their early stages, but overforecasts them during their mature and decaying phase. NOGAPS was slow in forward movement but showed improvement over the previous Navy forecast model. Case studies are presented which illustrate typical pressure and speed error patterns and the possible consequences of an inferior analysis on forecast quality. The results of this study correspond closely with the conclusions derived from the preliminary evaluation.