scholarly journals Assessing the Coupled Influences of Clouds on the Atmospheric Energy and Water Cycles in Reanalyses with A-Train Observations

2018 ◽  
Vol 31 (20) ◽  
pp. 8241-8264 ◽  
Author(s):  
A. S. Daloz ◽  
E. Nelson ◽  
T. L’Ecuyer ◽  
A. D. Rapp ◽  
L. Sun
Keyword(s):  
Water Cycle ◽  
Weather Forecasts ◽  
Regional Energy ◽  
Complex Interactions ◽  
Absolute Strength ◽  
Medium Range ◽  
Greenhouse Effects ◽  
Earth’S Climate ◽  
Modern Era ◽  
Precipitating Clouds

The lack of complete knowledge concerning the complex interactions among clouds, circulation, and climate hinders our ability to simulate the Earth’s climate correctly. This study contributes to a broader understanding of the implications of cloud and precipitation biases on the representation of coupled energy and water exchanges by bringing together a suite of cloud impact parameters (CIPs). These parameters measure the coupled impact of cloud systems on regional energy balance and hydrology by simultaneously capturing the absolute strength of the cloud albedo and greenhouse effects, the relative importance of these two radiative effects, and the efficiency of precipitating clouds to radiatively heat the atmosphere and cool the surface per unit of heating through rain production. Global distribution of these CIPs is derived using satellite observations from CloudSat and used to evaluate energy and water cycle coupling in four reanalysis datasets [both versions of the Modern-Era Retrospective Analysis for Research and Applications (MERRA and MERRA-2); the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim); and the Japanese 55-year Reanalysis (JRA-55)]. The results show that the reanalyses provide a more accurate representation of the three radiation-centric parameters than the radiative efficiencies. Of the four reanalyses, MERRA and ERA-Interim provide the best overall representation of the different cloud processes but can still show significant biases. JRA-55 exhibits some clear deficiencies in many parameters, while MERRA-2 seems to introduce biases that were not evident in MERRA.

scholarly journals An update on global atmospheric ice estimates from satellite observations and reanalyses

2018 ◽  
Author(s):  
David Ian Duncan ◽  
Patrick Eriksson
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Principal Component ◽  
Diurnal Variability ◽  
Weather Forecasts ◽  
Earth Observing System ◽  
Current State ◽  
Medium Range ◽  
Ice Water ◽  
Modern Era

Abstract. This study assesses the global distribution of mean atmospheric ice mass from current state-of-the-art estimates and its variability on daily and seasonal timescales. Ice water path (IWP) retrievals from active and passive satellite platforms are compared and analysed against estimates from two reanalysis datasets, ERA5 (European Centre for Medium-range Weather Forecasts Reanalysis 5) and MERRA-2 (Modern-era Retrospective Reanalysis for Research and Applications 2). Large discrepancies in IWP exist between the satellite datasets themselves, making validation of the model results problematic and indicating that progress towards consensus on the distribution of atmospheric ice has been limited. Comparing the datasets, zonal means of IWP exhibit similar shapes but differing magnitudes. Diurnal analysis centred on A-Train overpasses shows homologous structures in some regions, but the degree and sign of the variability varies widely; the reanalyses exhibit noisier and higher amplitude diurnal variability than borne out by the satellite estimates. Spatial structures governed by the atmospheric general circulation are fairly consistent across the datasets, as principal component analysis shows that the patterns of seasonal variability line up well between the datasets but disagree in severity. These results underscore the limitations of the current Earth observing system with respect to atmospheric ice, as the level of consensus between observations is mixed. The large-scale variability of IWP is relatively consistent, whereas disagreements on diurnal variability and global means point to varying microphysical assumptions in retrievals and models alike that seem to underlie the biggest differences.

scholarly journals How much snow falls in the world's mountains? A first look at mountain snowfall estimates in A-train observations and reanalyses

2020 ◽  
Vol 14 (9) ◽  
pp. 3195-3207
Author(s):  
Anne Sophie Daloz ◽  
Marian Mateling ◽  
Tristan L'Ecuyer ◽  
Mark Kulie ◽  
Norm B. Wood ◽  
...  
Keyword(s):  
Large Scale ◽  
Critical Factor ◽  
Weather Forecasts ◽  
Cloud Radar ◽  
Regional Trends ◽  
Medium Range ◽  
America South ◽  
Alpine Environments ◽  
Modern Era ◽  
Factor Governing

Abstract. CloudSat estimates that 1773 km3 of snow falls, on average, each year over the world's mountains. This amounts to 5 % of the global snowfall accumulations. This study synthetizes mountain snowfall estimates over the four continents containing mountains (Eurasia, North America, South America and Africa), comparing snowfall estimates from a new satellite cloud-radar-based dataset to those from four widely used reanalyses: Modern-Era Retrospective analysis for Research and Applications (MERRA), MERRA-2, Japanese 55-year Reanalysis (JRA-55), and European Center for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim). Globally, the fraction of snow that falls in the world's mountains is very similar between all these independent datasets (4 %–5 %), providing confidence in this estimate. The fraction of snow that falls in the mountains compared to the continent as a whole is also very similar between the different datasets. However, the total of snow that falls globally and over each continent – the critical factor governing freshwater availability in these regions – varies widely between datasets. The consensus in fractions and the dissimilarities in magnitude could indicate that large-scale forcings may be similar in the five datasets, while local orographic enhancements at smaller scales may not be captured. This may have significant implications for our ability to diagnose regional trends in snowfall and its impacts on snowpack in rapidly evolving alpine environments.

scholarly journals An Examination of Tropical Cyclone Position, Intensity, and Intensity Life Cycle within Atmospheric Reanalysis Datasets

2012 ◽  
Vol 25 (10) ◽  
pp. 3453-3475 ◽  
Author(s):  
Benjamin A. Schenkel ◽  
Robert E. Hart
Keyword(s):  
Life Cycle ◽  
North Pacific ◽  
Strongly Correlated ◽  
Sea Level Pressure ◽  
Climate Forecast System Reanalysis ◽  
Weather Forecasts ◽  
The North ◽  
Medium Range ◽  
The Mean ◽  
Modern Era

Abstract The following study examines the position and intensity differences of tropical cyclones (TCs) among the Best-Track and five atmospheric reanalysis datasets to evaluate the degree to which reanalyses are appropriate for studying TCs. While significant differences are found in both reanalysis TC intensity and position, the representation of TC intensity within reanalyses is found to be most problematic owing to its underestimation beyond what can be attributed solely to the coarse grid resolution. Moreover, the mean life cycle of normalized TC intensity within reanalyses reveals an underestimation of both prepeak intensification rates as well as a delay in peak intensity relative to the Best-Track. These discrepancies between Best-Track and reanalysis TC intensity and position can further be described through correlations with such parameters as Best-Track TC age, Best-Track TC intensity, Best-Track TC location, and the extended Best-Track TC size. Specifically, TC position differences within the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), ECMWF Interim Re-Analysis (ERA-I), and Modern Era Retrospective-Analysis for Research and Applications (MERRA) exhibit statistically significant correlations (0.27 ≤ R ≤ 0.38) with the proximity of TCs to observation dense areas in the North Atlantic (NATL) and western North Pacific (WPAC). Reanalysis TC intensity is found to be most strongly correlated with Best-Track TC size (0.53 ≤ R ≤ 0.70 for maximum 10-m wind speed; −0.71 ≤ R ≤ −0.53 for minimum mean sea level pressure) while exhibiting smaller, yet significant, correlations with Best-Track TC age, Best-Track TC intensity, and Best-Track TC latitude. Of the three basins examined, the eastern North Pacific (EPAC) has the largest reanalysis TC position differences and weakest intensities possibly due to a relative dearth of observations, the strong nearby terrain gradient, and the movement of TCs away from the most observation dense portion of the basin over time. The smaller mean Best-Track size and shorter mean lifespan of Best-Track EPAC TCs may also yield weaker reanalysis TC intensities. Of the five reanalyses, the smaller position differences and stronger intensities found in the Climate Forecast System Reanalysis (CFSR) and Japanese 25-year Reanalysis (JRA-25) are attributed to the use of vortex relocation and TC wind profile retrievals, respectively. The discrepancies in TC position between the Best-Track and reanalyses combined with the muted magnitude of TC intensity and its partially nonphysical life cycle within reanalyses suggests that caution should be exercised when utilizing these datasets for studies that rely either on TC intensity (raw or normalized) or track. Finally, several cases of nonphysical TC structure also argue that further work is needed to improve TC representation while implying that studies focusing solely on TC intensity and track do not necessarily extend to other aspects of TC representation.

Evaluation of Reanalyses over British Columbia. Part II: Daily and Extreme Precipitation

2019 ◽  
Vol 58 (2) ◽  
pp. 291-315 ◽  
Author(s):  
Pedro Odon ◽  
Gregory West ◽  
Roland Stull
Keyword(s):  
British Columbia ◽  
Complex Terrain ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Weather Forecasts ◽  
Time Period ◽  
Medium Range ◽  
L Moments ◽  
Modern Era ◽  
Terrain Characteristics

AbstractThis study evaluates how well reanalyses represent daily and multiday accumulated precipitation (hereinafter daily PCP) over British Columbia, Canada (Part I evaluated 2-m temperature). Reanalyses are compared with observations from 66 meteorological stations distributed over the complex terrain of British Columbia, separated into climate regions by k-means clustering. Systematic error, two-sample χ2 statistic, and frequency of daily PCP occurrence are evaluated from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the latest Modern-Era Retrospective Analysis for Research and Applications (version 2; MERRA-2). The 2- and 30-yr return levels of daily PCP are estimated from a generalized extreme value (GEV) distribution fitted by the method of L moments, and their systematic errors are analyzed. JRA-55 and MERRA-2 generally outperform ERA-Interim and CFSR across all metrics. Biases are largely explained by poor reanalysis representation of terrain characteristics such as steepness, exposure, elevation, location of barriers, and wind speed and direction. Statistical stationarity of precipitation intensity and frequency over the 30-yr period is assessed by using confidence intervals and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of daily PCP for this region and time period.

scholarly journals Evaluation of Four Reanalysis Datasets against Radiosonde over Southwest Asia

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 402 ◽  
Author(s):  
Ali S. Alghamdi
Keyword(s):  
Air Temperature ◽  
Geopotential Height ◽  
Horizontal Wind ◽  
Complex Topography ◽  
Southwest Asia ◽  
Weather Forecasts ◽  
Fifth Generation ◽  
Medium Range ◽  
Consistent Performance ◽  
Modern Era

Upper-air observational networks in Southwest Asia (SWA) are geographically sparse and reanalysis datasets (RDs) are a typical alternative. However, RDs can perform with varying degrees of quality and accuracy due to differences in assimilation schemes and input observations, among other factors. Geopotential height (gph), air temperature (tmp) and horizontal wind (U and V) modelled by the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts Reanalysis Interim (ERA-I), the ERA fifth-generation (ERA-5), and the National Aeronautics and Space Administration (NASA) Modern Era Retrospective Analysis for Research and Applications version 2 (MERRA), are compared with radiosonde observations at three standard vertical levels (850, 500 and 300 hPa). Results showed that most RDs represent the general climatology, and ERA-5 tended to show the smallest agreements in most cases. RDs did not show consistent performance across seasons, variables, and pressure levels. RDs tended to conduct reasonable estimates over subregions with less complex topography. RDs showed better resampling performance at the upper and lower ends of sounding data distributions more frequently than around the means for most of the variables. This highlights the high potential usefulness of RDs in studying extremes over the region.

Impact of planetary waves on infrasound propagation uncertainties

2021 ◽  
Author(s):  
Elisabeth Blanc ◽  
Patrick Hupe ◽  
Bernd Kaifler ◽  
Natalie Kaifler ◽  
Alexis Le Pichon ◽  
...  
Keyword(s):  
Wave Activity ◽  
Atmospheric Dynamics ◽  
Planetary Waves ◽  
Data Sets ◽  
Atmospheric Models ◽  
Period Range ◽  
Weather Forecasts ◽  
Atmospheric Disturbances ◽  
Medium Range ◽  
Model Improvement

<p>The uncertainties in the infrasound technology arise from the middle atmospheric disturbances, which are partly underrepresented in the atmospheric models such as in the European Centre for Medium-Range Weather Forecasts (ECMWF) products used for infrasound propagation simulations. In the framework of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project, multi-instrument observations are performed to provide new data sets for model improvement and future assimilations. In an unexpected way, new observations using the autonomous CORAL lidar showed significant differences between ECMWF analysis fields and observations in Argentina in the period range between 0.1 and 10 days. The model underestimates the wave activity, especially in the summer. During the same season, the infrasound bulletins of the IS02 station in Argentina indicate the presence of two prevailing directions of the detections, which are not reflected by the simulations. Observations at the Haute Provence Observatory (OHP) are used for comparison in different geophysical conditions. The origin of the observed anomalies are discussed in term of planetary waves effect on the infrasound propagation.</p>

Hochaufgelöste Simulation von meteorologischen Feldern in urbanen Räumen mit dem Weather Research and Forecasting (WRF) Modell

2021 ◽  
Author(s):  
Lukas N. Pilz ◽  
Sanam N. Vardag ◽  
Joachim Fallmann ◽  
André Butz
Keyword(s):  
Greenhouse Gas ◽  
Monitoring System ◽  
Weather Research And Forecasting ◽  
Gas Monitoring ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range ◽  
Erste Ergebnisse ◽  
Weather Research

<p><span>Städte und Kommunen sind für mehr als 70% </span><span>der globalen, fossilen CO2-Emissionen</span><span> verantwortlich, sodass hier ein enormes Mitigationspotential besteht. Informationen über (inner-)städtische CO2-Emissionen stehen allerdings oft nicht </span><span>in hoher zeitlicher und räumlicher Auflösung</span><span> zur Verfügung und sind </span><span>meist</span><span> mit großen Unsicherheiten behaftet. Diese Umstände erschweren eine zielgerichtete und effiziente Mitigation im urbanen Raum. </span><span>Städtische Messnetzwerke können als unabhängige Informationsquelle einen Beitrag leisten, um CO2-Emissionen in Städten zu quantifizieren und Mitigation zu verifizieren</span><span>. </span><span>Verschiedene denkbare Beobachtungsstrategien sollten</span><span> im Vorfeld abgewägt werden, um urbane Emissionen bestmöglich, d.h. mit der erforderlichen Genauigkeit und </span><span>Kosteneffizienz</span><span> zu quantifizieren. So können Messnetzwerke die Basis für zielgerichtete und kosteneffiziente Mitigation legen.</span></p><p><span>Im Rahmen des Verbundvorhabens „Integrated Greenhouse Gas Monitoring System for Germany“ (ITMS) werden wir verschiedene Beobachtungsstrategien für urbane Räume entwerfen und mit Hilfe von Modellsimulation evaluieren und abwägen. Notwendige Voraussetzung für </span><span>die Evaluation der Strategien</span><span> ist eine akkurate Repräsentation des atmosphärischen Transports im Modell.</span></p><p><span>Diese Studie zeigt</span><span> erste Ergebnisse der hochauflösenden (1kmx1km) meteorologischen Simulationen für den Rhein-Neckar-Raum mit dem WRF Modell. </span><span>Die in WRF simulierten meteorologischen Größen werden für verschiedene Modellkonfigurationen mit </span><span>re-analysierten Daten des European Centre for Medium-Range Weather Forecasts (ECMWF) und ausgewählten Messstationen verglichen. Damit evaluieren wir </span><span>den Einfluss unterschiedlicher Nudging-Strategien, Parametrisierungen physikalischer Prozesse und urbaner Interaktionen</span><span> auf </span><span>die Modellperformance</span> <span>von</span><span> Lufttemperatur, Windrichtung, Windgeschwindigkeit und Grenzschichthöhe. Durch diese Analysen gewährleisten wir, dass die Simulation der Beobachtungsstrategien auf robuste</span><span>m</span><span> und realistische</span><span>m</span><span> atmosphärischen Transport basieren und schlussendlich repräsentative Empfehlungen für den Aufbau von Messnetzwerken liefern können. </span></p>

Aerosol Assimilation of lidar data from Satellite (AEOLUS) and Ground-based (EARLINET) instruments in COMPO-IFS.

2021 ◽  
Author(s):  
Julie Letertre-Danczak ◽  
Angela Benedetti ◽  
Drasko Vasiljevic ◽  
Alain Dabas ◽  
Thomas Flament ◽  
...  
Keyword(s):  
Quality Data ◽  
Lidar Data ◽  
Operational Model ◽  
Weather Forecasts ◽  
The Past ◽  
Medium Range ◽  
First Results ◽  
Monitoring Service ◽  
The Vertical Distribution ◽  
Good Quality Data

<p>Since several years, the number of aerosol data coming from lidar has grown and improved in quality. These new datasets are providing a valuable information on the vertical distribution of aerosols which is missing in the AOD (Aerosol Optical Depth), which has been used so far in aerosols analysis. The launch of AEOLUS in 2018 has increased the interest in the assimilation of the aerosol lidar information. In parallel, the ground-based network EARLINET (European Aerosol Research LIdar NETwork) has grown to cover the Europe with good quality data. Assimilation of these data in the ECMWF/CAMS (European Centre for Medium-range Weather Forecasts / Copernicus Atmosphere Monitoring Service) system is expected to provide improvements in the aerosol analyses and forecasts.<br><br>Three preliminary studies have been done in the past four years using AEOLUS data (A3S-ESA funded) and EARLINET data (ACTRIS-2 and EUNADIC-AV, EU-funded). These studies have allowed the full development of the tangent linear and adjoint code for lidar backscatter in the ECMWF's 4D-VAR system. These developments are now in the operational model version in research mode. The first results are promising and open the path to more intake of aerosol lidar data for assimilation purposes. The future launch of EARTHCARE (Earth-Cloud Aerosol and Radiation Explorer) and later ACCP (Aerosol Cloud, Convention and Precipitation) might even upgrade the use of aerosol lidar data in COMPO-IFS (Composition-Integrated Forecast system).<br><br>The most recent results using AEOLUS data (for October 2019 and April 2020) and using EARLINET data (October 2020) will be shown in this presentation. The output will be compared to the CAMS operational aerosol forecast as well as to independent data from AERONET (AErosol Robotic NETwork).</p>

Evaluierung des nichthydrostatischen mesoskaligen Modells GRAMM-SCI anhand der Richtlinie VDI 3783 Blatt 7/Evaluation of the nonhydrostatic mesoscale model GRAMM-SCI based on the guideline VDI 3783 Part 7

Gefahrstoffe ◽  
2020 ◽  
Vol 80 (07-08) ◽  
pp. 318-324
Author(s):  
D. Öttl
Keyword(s):  
Mesoscale Model ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range

Aufgrund der komplexen Orografie in den Alpen sind einfache, auf diagnostischen Ansätzen beruhende Windfeldmodelle in Österreich kaum anwendbar. Daher wird in den meisten österreichischen Bundesländern das mesoskalige Modell GRAMM im Rahmen von Luftschadstoffuntersuchungen eingesetzt. In diesem Beitrag werden Ergebnisse der Modellevaluierung anhand jener drei Datensätze der Richtlinie VDI 3783 Blatt 7 präsentiert, die auf teils umfangreichen Messkampagnen basieren. Das Modell GRAMM wurde mittlerweile erweitert (Version GRAMM-SCI) und kann nun auch mit den Reanalysedaten ERA5 des Europäischen Wetterdienstes (European Centre for Medium-Range Weather Forecasts, ECMWF) angetrieben werden. Um die Qualität der ERA5-Daten zu prüfen, wurden zusätzliche Simulationen für die drei Evaluierungsdatensätze aus VDI 3783 Blatt 7 durchgeführt. Es zeigt sich, dass Modellsimulationen mit GRAMM-SCI, die auf ERA5-Daten basieren, die Strömungs- und Temperaturverhältnisse grundsätzlich gut wiedergeben. Allerdings sind die Abweichungen zu den Messungen der Sondermesskampagnen teilweise etwas zu groß, um die hohen Anforderungen von VDI 3783 Blatt 7 an die Modellergebnisse vollständig zu erfüllen.

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