NWP Analyses Research Articles

Interactive 3D Visual Analysis of Weather Prediction Data Reveals Midlatitude Overshooting Convection during the CIRRUS-HL Field Experiment

Abstract In summer 2021, microphysical properties and climate impact of high- and midlatitude ice clouds over Europe and the North Atlantic were studied during the Cirrus High Latitude (CIRRUS-HL) airborne field campaign. The related forecasting and flight planning tasks provided a testbed for interactive 3D visual analysis. Operational analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) were visualized with the open-source software “Met.3D.” A combination of traditional 2D displays with innovative 3D views in the interactive visualization framework facilitated rapid and comprehensive exploration of the NWP data. By this means, the benefit of interactive 3D visual forecast products in the routine flight planning procedure was evaluated. Here, we describe the use of 3D tropopause and cloud visualizations during a convective event over the Alps, which became one of the CIRRUS-HL observation targets. For the planning of the research flight on 8 July 2021, our analysis revealed that simulated strong convective updrafts locally disturb the tropopause and inject ice water across the dynamical tropopause into the lower stratosphere. The presented example provides a novel 3D perspective of convective overshooting in a global NWP model and its impact on the tropopause and lower stratosphere. The case study shall encourage the atmospheric science community to further evaluate the use of modern 3D visualization capabilities for NWP analysis.

The Framework for Assimilating All-Sky GPM Microwave Imager Brightness Temperature Data in the NASA GEOS Data Assimilation System

Abstract Satellite radiance observations combine global coverage with high temporal and spatial resolution, and bring vital information to NWP analyses especially in areas where conventional data are sparse. However, most satellite observations that are actively assimilated have been limited to clear-sky conditions due to difficulties associated with accounting for non-Gaussian error characteristics, nonlinearity, and the development of appropriate observation operators for cloud- and precipitation-affected satellite radiance data. This article provides an overview of the development of the Gridpoint Statistical Interpolation (GSI) configurations to assimilate all-sky data from microwave imagers such as the GPM Microwave Imager (GMI) in the NASA Goddard Earth Observing System (GEOS). Electromagnetic characteristics associated with their wavelengths allow microwave imager data to be highly sensitive to precipitation. Therefore, all-sky data assimilation efforts described in this study are primarily focused on utilizing these data in precipitating regions. To utilize data in cloudy and precipitating regions, state and analysis variables have been added for ice cloud, liquid cloud, rain, and snow. This required enhancing the observation operator to simulate radiances in heavy precipitation, including frozen precipitation. Background error covariances in both the central analysis and EnKF analysis in the GEOS hybrid 4D-EnVar system have been expanded to include hydrometeors. In addition, the bias correction scheme was enhanced to reduce biases associated with thick clouds and precipitation. The results from single observation experiments demonstrate the capability of assimilating all-sky microwave brightness temperature data in GEOS both when the model forecast produces excessive precipitation and too little precipitation. Additional experiments show that hydrometeors and dynamic variables such as winds and pressure are adjusted in physically consistent ways in response to the assimilation.

Atmospheric Motion Vectors Derived from an Infrared Window Channel of a Geostationary Satellite Using Particle Image Velocimetry

AbstractAs the new-generation geostationary satellite Himawari-8 provides a greater frequency and more observation channels than its predecessor, the Multifunctional Transport Satellite series (e.g., MTSAT-2), an opportunity arises to generate atmospheric motion vectors (AMVs) with an increased accuracy and extensive distribution over eastern Asia. In this work AMVs were derived from consecutive images of an infrared-window channel (IR1) of the Himawari-8 satellite using particle image velocimetry (PIV) based on the theory of cross-correlation schemes. A multipass scheme and an adaptive interrogation scheme were also employed to increase spatial resolution and accuracy. For height assignment, an infrared-window method was applied for opaque cloud, while an H2O-intercept method was employed for semitransparent cloud. Validation was conducted by comparing the PIV-derived AMVs with wind fields obtained from NWP analysis, radiosonde observations, and the operational system from the Meteorological Satellite Center (MSC) of the Japan Meteorological Agency (JMA) or JMA/MSC. The comparison of wind velocity maps with the NWP data shows that the PIV-derived AMVs are capable of quantitatively depicting full-field wind field maps and strong jets in atmospheric circulation. Through comparisons with radiosonde observations, the root-mean-square error and wind speed bias (4.29 and −1.05 m s−1) of the PIV-derived AMVs are comparable to, although slightly greater than, that of the NWP data (3.88 and −0.26 m s−1). Based on comparison between the PIV-derived AMVs and wind fields obtained from the JMA/MSC operational system, the PIV-derived AMVs are again comparable, producing a slightly lower error but a larger wind speed bias (−1.05 vs 0.20 m s−1). This also implies that a better height assignment algorithm is necessary.

The Realization of Extreme Tornadic Storm Events under Future Anthropogenic Climate Change

Abstract This research seeks to answer the basic question of how current-day extreme tornadic storm events might be realized under future anthropogenic climate change. The pseudo global warming (PGW) methodology was adapted for this purpose. Three contributions to the CMIP5 archive were used to obtain the mean 3D atmospheric state simulated during May 1990–99 and May 2090–99. The climate change differences (or Δs) in temperature, relative humidity, pressure, and winds were added to NWP analyses of three high-end tornadic storm events, and this modified atmospheric state was then used for initial and boundary conditions for real-data WRF Model simulations of the events at high resolution. Comparison of an ensemble of these simulations with control simulations (CTRL) facilitated assessment of PGW effects. In contrast to the robust development of supercellular convection in each CTRL, the combined effects of increased convective inhibition (CIN) and decreased parcel lifting under PGW led to a failure of convection initiation in many of the experiments. Those experiments that had sufficient matching between the CIN and lifting tended to generate stronger convective updrafts than CTRL, although not in proportion to the projected higher levels of convective available potential energy (CAPE) under PGW. In addition, the experiments with enhanced updrafts also tended to have enhanced vertical rotation. In fact, such supercellular convection was even found in simulations that were driven with PGW-reduced environmental wind shear. Notably, the PGW modifications did not induce a change in the convective morphology in any of the PGW experiments with significant convective storminess.

A revised L-band radio-brightness sensitivity to extreme winds under Tropical Cyclones: the five year SMOS-storm database

Abstract Five years of SMOS L-band brightness temperature data intercepting a large number of tropical cyclones (TCs) are analyzed. The storm-induced half-power radio-brightness contrast (ΔI) is defined as the difference between the brightness observed at a specific wind force and that for a smooth water surface with the same physical parameters. ΔI can be related to surface wind speed and has been estimated for ~ 300 TCs that intercept with SMOS measurements. ΔI, expressed in a common storm-centric coordinate system, shows that mean brightness contrast monotonically increases with increased storm intensity ranging from ~ 5 K for strong storms to ~ 24 K for the most intense Category 5 TCs. A remarkable feature of the 2D mean ΔI fields and their variability is that maxima are systematically found on the right quadrants of the storms in the storm-centered coordinate frame, consistent with the reported asymmetric structure of the wind and wave fields in hurricanes. These results highlight the strong potential of SMOS measurements to improve monitoring of TC intensification and evolution. An improved empirical geophysical model function (GMF) was derived using a large ensemble of co-located SMOS ΔI, aircraft and H*WIND (a multi-measurement analysis) surface wind speed data. The GMF reveals a quadratic relationship between ΔI and the surface wind speed at a height of 10 m (U10). ECMWF and NCEP analysis products and SMOS derived wind speed estimates are compared to a large ensemble of H*WIND 2D fields. This analysis confirms that the surface wind speed in TCs can effectively be retrieved from SMOS data with an RMS error on the order of 10 kt up to 100 kt. SMOS wind speed products above hurricane force (64 kt) are found to be more accurate than those derived from NWP analyses products that systematically underestimate the surface wind speed in these extreme conditions. Using co-located estimates of rain rate, we show that the L-band radio-brightness contrasts could be weakly affected by rain or ice-phase clouds and further work is required to refine the GMF in this context.

A diagnostic method for aircraft turbulence based on high-resolution numerical weather prediction products

Forecasting aircraft turbulence accurately is of vital importance for route optimization and flight safety. The common methods including TI index and L-P are usually used to predict aircraft turbulence by diagnosing the strength of atmospheric turbulence, not taking into account the impact of aircraft itself and other elements, and can only be applied to the products with low horizontal resolutions. By considering factors that affect the aircraft lift, a new diagnostic index method, S Index (SI) method, is designed in this paper for aircraft turbulence, which can be applicable to high-resolution NWP products or analysis products. SI method mainly focuses on the factors that impact aircraft turbulence such as flight speed, wing loading, vertical velocity of air flow, horizontal wind speed, air density. The paper also provides a method of determining parameters based on the existing experience and mathematical techniques which are combined with aircraft reports and high-resolution NWP results. In addition, pointing to the level flight and takeoff/landing stages, SI analysis and calculation are carried out, respectively. To validate the application scope of the accuracy of SI method objectively, the physical quantity of turbulence area ratio (TAR), which is a statistical parameter to describe the ratio of turbulence area and the overall diagnostic region, is defined. In the case that the horizontal and vertical resolutions of weather research and forecasting (WRF) forecasts are 9 km and 300 m, respectively, the diagnostic results of SI show that for the stage of level flight, when the TAR ratio is 41 %, the overall forecast accuracy of aircraft turbulence can reach 74 %, of which the accuracy of moderate turbulence forecast is 60 % and the severe 27 %. For the stage with 20° elevation during the process of takeoff and landing, when the TAR ratio is 40 %, the overall forecast accuracy can get to 63 %, of which the accuracies of moderate and severe turbulence are 41 and 14 %, respectively.

An overview of the HIBISCUS campaign

Abstract. The EU HIBISCUS project consisted of a series of field campaigns during the intense convective summers in 2001, 2003 and 2004 in the State of São Paulo in Brazil. Its objective was to investigate the impact of deep convection on the Tropical Tropopause Layer (TTL) and the lower stratosphere by providing a new set of observational data on meteorology, tracers of horizontal and vertical transport, water vapour, clouds, and chemistry in the tropical Upper Troposphere/Lower Stratosphere (UT/LS). This was achieved using short duration research balloons to study local phenomena associated with convection over land, and long-duration balloons circumnavigating the globe to study the contrast between land and oceans. Analyses of observations of short-lived tracers, ozone and ice particles show strong episodic local updraughts of cold air across the lapse rate tropopause up to 18 or 19 km (420–440 K) in the lower stratosphere by overshooting towers. The long duration balloon and satellite measurements reveal a contrast between the composition of the lower stratosphere over land and oceanic areas, suggesting significant global impact of such events. The overshoots are shown to be well captured by non-hydrostatic meso-scale Cloud Resolving Models indicating vertical velocities of 50–60 m s−1 at the top of the Neutral Buoyancy Level (NBL) at around 14 km, but, in contrast, are poorly represented by global Chemistry-Transport Models (CTM) forced by Numerical Weather Forecast Models (NWP) underestimating the overshooting process. Finally, the data collected by the HIBISCUS balloons have allowed a thorough evaluation of temperature NWP analyses and reanalyses, as well as satellite ozone, nitrogen oxide, water vapour and bromine oxide measurements in the tropics.

Comparison of Snow Cover from Satellite and Numerical Weather Prediction Models in the Northern Hemisphere and Northern Europe

Abstract Snow cover has a strong effect on the surface and lower atmosphere in NWP models. Because the progress of in situ observations has stalled, satellite-based snow analyses are becoming increasingly important. Currently, there exist several products that operationally map global or continental snow cover. In this study, satellite-based snow cover analyses from NOAA, NASA, and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and NWP snow analyses from the High-Resolution Limited-Area Model (HIRLAM) and ECMWF, were compared using data from January to June 2006. Because no analyses were independent and since available in situ measurements were already used in the NWP analyses, no independent ground truth was available and only the consistency between analyses could be compared. Snow analyses from NOAA, NASA, and ECMWF were similar, but the analysis from NASA was greatly hampered by clouds. HIRLAM and EUMETSAT deviated most from other analyses. Even though the analysis schemes of HIRLAM and ECMWF were quite similar, the resulting snow analyses were quite dissimilar, because ECMWF used the satellite information of snow cover in the form of NOAA analyses, while HIRLAM used none. The differences are especially prominent in areas around the snow edge where few in situ observations are available. This suggests that NWP snow analyses based only on in situ measurements would greatly benefit from inclusion of satellite-based snow cover information.

Comparing ERA-40-Based L-Band Brightness Temperatures with Skylab Observations: A Calibration/Validation Study Using the Community Microwave Emission Model

Abstract The Community Microwave Emission Model (CMEM) has been used to compute global L-band brightness temperatures at the top of the atmosphere. The input data comprise surface fields from the 40-yr ECMWF Re-Analysis (ERA-40), vegetation data from the ECOCLIMAP dataset, and the Food and Agriculture Organization’s (FAO) soil database. Modeled brightness temperatures have been compared against (historic) observations from the S-194 passive microwave radiometer onboard the Skylab space station. Different parameterizations for surface roughness and the vegetation optical depth have been used to calibrate the model. The best results have been obtained for rather simple approaches proposed by Wigneron et al. and Kirdyashev et al. The rms errors after calibration are 10.7 and 9.8 K for North and South America, respectively. Comparing the ERA-40 soil moisture product against the corresponding in situ observations suggests that the uncertainty in the modeled soil moisture is the predominant contributor to these rms errors. Although the bias between model and observed brightness temperatures are reduced after the calibration, systematic differences in the dynamic range remain. For NWP analysis applications, bias correction schemes should be applied prior to data assimilation. The calibrated model has been used to compute a 10-yr brightness temperature climatology based on ERA-40 data.

Comparisons of Surface Meteorology and Turbulent Heat Fluxes over the Atlantic: NWP Model Analyses versus Moored Buoy Observations*

Surface meteorological variables and turbulent heat fluxes in the National Centers for Environmental Prediction‐National Center for Atmospheric Research reanalyses 1 and 2 (NCEP1 and NCEP2) and the analysis from the operational system of the European Centre for Medium-Range Weather Forecasts (ECMWF) are compared with high-quality moored buoy observations in regions of the Atlantic including the eastern North Atlantic, the coastal regions of the western North Atlantic, and the Tropics. The buoy latent and sensible heat fluxes are determined from buoy measurements using the recently improved Tropical Ocean Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment (TOGA COARE) flux algorithm. The time mean oceanic heat loss from the model analyses is systematically overestimated in all the regions. The overestimation in latent heat loss ranges from about 14 W m22 (13%) in the eastern subtropical North Atlantic to about 29 W m22 (30%) in the Tropics to about 30 W m22 (49%) in the midlatitude coastal areas, where the overestimation in sensible heat flux reaches about 20 W m 22 (60%). Depending upon the region and the NWP model, these systematic overestimations are either reduced, or change to underestimations, or remain unchanged when the TOGA COARE flux algorithm is used to recalculate the fluxes. The bias in surface meteorological variables, one of the major factors related to the biases in the revised NWP heat fluxes, varies with region and NWP analysis. Generally the temperature and humidity biases in the coastal regions are much larger than other regions. In the extratropical regions, NCEP1 and NCEP2 generally show a wet bias, which is mainly responsible for the underestimation in the revised NWP latent heat loss. In the Tropics a dry bias is found in the NWP analyses, particularly in ECMWF and NCEP2, which contributes to the overestimation in the revised NWP latent heat loss. Compared to NCEP1, NCEP2 shows less cold bias in 2-m air temperature and thus less biased sensible heat flux; NCEP2 also shows less humid bias in 2-m humidity in the extratropical regions but more dry bias in 2-m humidity in the Tropics, either of which leads to a more biased latent heat flux in NCEP2. Despite the significant biases in the NWP surface fields and the poor representation of short-time sea surface temperature variability, the NWP models are able to represent the dominant short-time variability in other basic variables and thus the variability in heat fluxes in the wintertime coastal regions of the western North Atlantic (on timescales of 3‐4 days and 1 week) and the northern and southern subtropical regions (on a timescale of about 2 weeks), but ECMWF and particularly the NCEP analyses do not represent well the 2‐3-week variability in the tropical Atlantic.

Impact of a New Cloud Motion Wind Product from Meteosat on NWP Analyses and Forecasts

Abstract Enhanced wind datasets of the European satellite Meteosat are now provided every 90 mins together with the quality indicator (QI) derived by the quality control of the Meteorological Product Extraction Facility (MPEF) at the European Organisation for the Exploitation of Meteorological Satellites. All three channel cloud motion winds and clear sky water vapor motion winds have been passively monitored by comparison with the European Centre for Medium-Range Weather Forecasts model background field. The evaluation of the relationship between the MPEF QI and the observation − background differences indicate possible benefits to be gained from the use of the QI within the observation screening of the assimilation system. The MPEF quality indicator is used as a selection criterion within the screening. The applied thresholds are restricted in the Tropics compared to the extratropical regions where the threshold for high-level winds has been relaxed below the automatic quality control at MPEF. The wind ...

Using low‐resolution winds to deduce fine structure in tracers

In a number of applications several numerical modellers have recently used low‐resolution GCM or NWP analysis winds to deduce very fine structure in the distribution of chemical species and of potential vorticity. This study aims to measure the error introduced by this mismatch of effective resolutions. By appealing to earlier theoretical work by Batchelor (1959), the approach has been organized around the steepness of the kinetic energy spectrum, E(k). It is found that when the spectrum is steeper than E(k) ∼ k–3 the root mean square error is proportional to the square of the wind truncation scale. By contrast, when E(k) approaches k–5/3 rms error is approximately proportional to the square root of the wind truncation scale. As a result coarse wind resolution produces remarkably accurate global scalar fields after a few advective timescales in the large spatial scales of the troposphere and in the stratosphere, but this result is not expected to hold at smaller scales or in the mesosphere where the spectrum is more shallow.

Aspects of the intraseasonal oscillation simulated by the Hadley Centre Atmosphere Model

The period and amplitude of the tropical intraseasonal oscillation in the Hadley Centre Global Climate Model have been examined by applying time filtering and spectral analysis techniques to time series of daily velocity potential. Results from an AMIP integration of the model, forced with observed sea surface temperatures for the decade 1979-88 show that the model has a reasonable degree of skill in simulating the main features of the oscillation, although the signal in the model is rather noisy compared to NWP analyses. The model also shows interannual variability of the oscillation similar in magnitude to that in the analyses. The impact on the oscillation of including a parametrization of momentum transport by cumulus convection is assessed. This parametrization significantly improves the mean circulation of the model, reducing systematic errors particularly in the tropics. However, the strength and coherence of the tropical intraseasonal oscillation are significantly reduced by this parametrization. It is speculated that this may be related to a reduction in westerly flow in the tropical central and east Pacific and a reduction in the strength of the SPCZ in DJF.

Some experiments to investigate the assimilation of SEASAT altimeter wave height data into a global wave model

AbstractA scheme for assimilating SEASAT altimeter wave heights into a global wave model, with the additional use of the collocated altimeter wind speeds, is reported. Control experiments are described in which the wave model was run with two sets of winds, one with SEASAT scatterometer wind data included in the NWP analysis and the other without, both for a period from 0000 GMT 15 September 1978 to 0000 GMT 20 September 1978. the results of forcing the wave model with these wind fields are compared with the altimeter wave heights. the differences are discussed in order to quantify errors in both the wave model and the altimetric data. Three experiments in which altimeter wave heights were assimilated are then described. the results of these are compared with the wave fields from the model runs without wave data assimilation. the assimilation experiments show that a significant improvement in model wave height is possible and that the impact of one day of assimilation is retained for at least five days.

Analysis methods for numerical weather prediction

Bayesian probabilistic arguments are used to derive idealized equations for finding the best analysis for numerical weather prediction. These equations are compared with those from other published methods in the light of the physical characteristics of the NWP analysis problem; namely the predetermined nature of the basis for the analysis, the need for approximation because of large-order systems, the underdeterminacy of the problem when using observations alone, and the availability of prior relationships to resolve the underdeterminacy. Prior relationships result from (1) knowledge of the time evolution of the model (which together with the use of a time distribution of observations constitutes four-dimensional data assimilation); (2) knowledge that the atmosphere varies slowly (leading to balance relationships); (3) other nonlinear relationships coupling parameters and scales in the atmosphere. Methods discussed include variational techniques, smoothing splines, Kriging, optimal interpolation, successive corrections, constrained initialization, the Kalman-Bucy filter, and adjoint model data assimilation. They are all shown to relate to the idealized analysis, and hence to each other. Opinions are given on when particular methods might be more appropriate. By comparison with the idealized method some insight is gained into appropriate choices of parameters in the practical methods.