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.

Evaluation of Reanalyses over British Columbia. Part I: Daily and Extreme 2-m Temperature

2018 ◽  
Vol 57 (9) ◽  
pp. 2091-2112 ◽  
Author(s):  
Pedro Odon ◽  
Gregory West ◽  
Roland Stull
Keyword(s):  
British Columbia ◽  
Daily Maximum ◽  
Climate Forecast System Reanalysis ◽  
Weather Forecasts ◽  
Time Period ◽  
Kolmogorov Smirnov ◽  
L Moments ◽  
Maximum Temperatures ◽  
Terrain Representation ◽  
Modern Era

AbstractWeather-station data coverage, quality, and completeness across British Columbia, Canada, degrade outside of population centers and as one goes back in time. This data paucity motivates the search for the best reanalysis to serve as a climatological reference dataset. This study focuses on how well reanalyses represent 2-m temperature (T2M). Systematic error, random error, and two-sample Kolmogorov–Smirnov statistics of daily maximum and minimum T2M are evaluated from the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Also evaluated are the 2- and 30-yr return levels of T2M, which are estimated by the method of L moments from a fitted generalized extreme value (GEV) distribution. Reanalyses are compared with observations from 57 meteorological stations distributed over the complex terrain of British Columbia from 1980 to 2010. Minimum temperatures are better captured than maximum temperatures by all four reanalyses. JRA-55 and ERA-Interim generally perform better across all metrics. Biases are largely explained by poor reanalysis terrain representation. Statistical stationarity over the 30-yr period is assessed by using Gaussian and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of T2M for this region and time period.

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.

Sea Surface Temperature–Precipitation Relationship in Different Reanalyses

2013 ◽  
Vol 141 (3) ◽  
pp. 1118-1123 ◽  
Author(s):  
Arun Kumar ◽  
Li Zhang ◽  
Wanqiu Wang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Department Of Energy ◽  
Sea Surface ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Temperature And Precipitation ◽  
The Relationship ◽  
Modern Era

Abstract The focus of this investigation is how the relationship at intraseasonal time scales between sea surface temperature and precipitation (SST–P) varies among different reanalyses. The motivation for this work was spurred by a recent report that documented that the SST–P relationship in Climate Forecast System Reanalysis (CFSR) was much closer to that in the observation than it was for the older generation of reanalyses [i.e., NCEP–NCAR reanalysis (R1) and NCEP–Department of Energy (DOE) reanalysis (R2)]. Further, the reason was attributed either to the fact that the CFSR is a partially coupled reanalysis, while R1 and R2 are atmospheric-alone reanalyses, or that R1 and R2 use the observed weekly-averaged SST. The authors repeated the comparison of the SST–P relationship among R1, R2, and CFSR, as well as two recent generations of atmosphere-alone reanalyses, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the ECMWF Re-Analysis Interim (ERA-Interim). The results clearly demonstrate that the differences in the SST–P relationship at intraseasonal time scales across different reanalyses are not due to whether the reanalysis system is coupled or atmosphere alone, but are due to the specification of different SSTs. The SST–P relationship in different reanalyses, when computed against a single SST for the benchmark, demonstrates a relationship that is common across all of the reanalyses and observations.

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.

A Comparison of Extratropical Cyclones in Recent Reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25

2011 ◽  
Vol 24 (18) ◽  
pp. 4888-4906 ◽  
Author(s):  
K. I. Hodges ◽  
R. W. Lee ◽  
L. Bengtsson
Keyword(s):  
The Other ◽  
Extratropical Cyclones ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Spatial Differences ◽  
The Mean ◽  
Using Data ◽  
Modern Era ◽  
Ncep Climate Forecast System

Abstract Extratropical cyclones are identified and compared using data from four recent reanalyses for the winter periods in both hemispheres. Results show the largest differences occur between the older lower resolution 25-yr Japanese Reanalysis (JRA-25) when compared with the newer high resolution reanalyses, particularly in the Southern Hemisphere (SH). Spatial differences between the newest reanalyses are small in both hemispheres and generally not significant except in some common regions associated with cyclogenesis close to orography. Differences in the cyclone maximum intensitites are generally related to spatial resolution except in the NASA Modern Era Retrospective-Analysis for Research and Applications (NASA MERRA), which has larger intensities for several different measures. Matching storms between reanalyses shows the number matched between the ECMWF Interim Re-Analysis (ERA-Interim) and the other reanalyses is similar in the Northern Hemisphere (NH). In the SH the number matched between JRA-25 and ERA-Interim is lower than in the NH; however, for NASA MERRA and the NCEP Climate Forecast System Reanalysis (NCEP CFSR), the number matched is similar to the NH. The mean separation of the identically same cyclones is typically less than 2° geodesic in both hemispheres for the latest reanalyses, whereas JRA-25 compared with the other reanalyses has a broader distribution in the SH, indicating greater uncertainty. The instantaneous intensity differences for matched storms shows narrow distributions for pressure, while for winds and vorticity the distributions are much broader, indicating larger uncertainty typical of smaller-scale fields. Composite cyclone diagnostics show that cyclones are very similar between the reanalyses, with differences being related to the intensities, consistent with the intensity results. Overall, results show NH cyclones correspond well between reanalyses, with a significant improvement in the SH for the latest reanalyses, indicating a convergence between reanalyses for cyclone properties.

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 Estudo do ciclo de vida do ciclone subtropical Arani ocorrido no Atlântico Sul em março de 2011 através das reanálises ERA-Interim e CFSR

2020 ◽  
Vol 15 (3) ◽  
pp. 235-249
Author(s):  
Ana Cristina Pinto de Almeida Palmeira ◽  
Rodrigo De Souza Barreto Mathias
Keyword(s):  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range

O ciclone Arani ocorreu em março de 2011 no oceano Atlântico Sul e foi classificado inicialmente como depressão subtropical. Ao atingir ventos superiores a 34 nós, passou à categoria de tempestade subtropical, sendo nomeado pela Marinha do Brasil como Arani, que significa tempo furioso em Tupi Guarani. O objetivo deste trabalho foi analisar o ciclone Arani através do Espaço de Fase de Ciclones, construído com dados da reanálise ERA-Interim do European Centre for Medium-Range Weather Forecasts (ECMWF), com 0,7º de resolução espacial, e, também, utilizando campos sinóticos e cortes verticais com os dados da reanálise do Climate Forecast System Reanalisys (CFSR), com 0,5º de resolução. Através dos diagramas de fase foi possível identificar a estrutura subtropical do ciclone Arani e o indício de uma transição de fase extratropical no final de seu ciclo de vida. Os resultados indicaram, também, que a qualidade dos diagramas de fase para ciclones com fraco núcleo quente e pequenas dimensões depende de modelos atmosféricos adequados e, por isso, os valores obtidos devem ser analisados com cautela quando se trata do uso de modelos globais. Neste caso, o estudo qualitativo dos diagramas se mostrou mais útil do que a análise puramente quantitativa. Apesar de discordar da informação de uma transição de fase extratropical no final do ciclo de vida do ciclone Arani, contida nos diagramas de fase empregados no estudo, a análise dos campos e dos perfis sinóticos contribuiu para o entendimento do desenvolvimento do ciclone e para a interpretação dos próprios diagramas de fase.

scholarly journals MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications

2011 ◽  
Vol 24 (14) ◽  
pp. 3624-3648 ◽  
Author(s):  
Michele M. Rienecker ◽  
Max J. Suarez ◽  
Ronald Gelaro ◽  
Ricardo Todling ◽  
Julio Bacmeister ◽  
...  
Keyword(s):  
Retrospective Analysis ◽  
Surface Fluxes ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Earth Observing System ◽  
Current Period ◽  
Climate Analysis ◽  
New Generation ◽  
Modern Era ◽  
Made In

Abstract The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).

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 Revisiting the Precipitous Terrain Classification from a Meteorological Perspective

2021 ◽  
Author(s):  
Domingo Muñoz-Esparza ◽  
Hyeyum Hailey Shin ◽  
Teddie L. Keller ◽  
Kyoko Ikeda ◽  
Robert D. Sharman ◽  
...  
Keyword(s):  
High Resolution ◽  
Complex Terrain ◽  
Weather Forecast ◽  
Federal Aviation Administration ◽  
Local Area ◽  
Terrain Classification ◽  
Weather Forecasts ◽  
Synoptic Weather ◽  
Aviation Hazards ◽  
Terrain Characteristics

AbstractTakeoff and landing maneuvers can be particularly hazardous at airports surrounded by complex terrain. To address this, the Federal Aviation Administration has developed a Precipitous Terrain classification, as a way to impose more restrictive terrain clearances in the vicinity of complex terrain and to mitigate possible altimeter errors and pilot control problems experienced while executing instrument approach procedures. The current Precipitous Point Value (PPV) algorithm relies on the terrain characteristics within a local area of 2 NM, and is therefore static in time. In this work, we investigate the role of meteorological effects leading to potential aviation hazards over complex terrain, namely turbulence, altimeter setting errors and density altitude deviations. To that end, we combine observations with high-resolution numerical weather forecasts within a 2° × 2° region over the Rocky Mountains in Colorado, containing three airports that are surrounded by Precipitous Terrain. Both available turbulence reports and model’s turbulence forecasts show little correlation with the PPV algorithm for the region analyzed, indicating that the static terrain characteristics cannot generally be used to reliably capture hazardous low-level turbulence events. Altimeter setting errors and density altitude effects are also found to be only very weakly correlated with the PPV algorithm. Altimeter setting errors contribute to hazardous conditions mainly during cold seasons, driven by synoptic weather systems, while density altitude effects are on the contrary predominantly present during the spring and summer months, and follow a very well-marked diurnal evolution modulated by surface radiative effects. These findings demonstrate the effectiveness of high-resolution weather forecast information in determining aviation-relevant hazardous conditions over complex terrain.

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