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

Author(s):  
David Ian Duncan ◽  
Patrick Eriksson

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.

2018 ◽  
Vol 18 (15) ◽  
pp. 11205-11219 ◽  
Author(s):  
David Ian Duncan ◽  
Patrick Eriksson

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 analysed and compared with estimates from two reanalysis data sets, ERA5 (European Centre for Medium-range Weather Forecasts Reanalysis 5, ECMWF) and MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications 2). Large discrepancies in IWP exist between the satellite data sets themselves, making validation of the model results problematic and indicating that progress towards a consensus on the distribution of atmospheric ice has been limited. Comparing the data sets, zonal means of IWP exhibit similar shapes but differing magnitudes, with large IWP values causing much of the difference in means. Diurnal analysis centred on A-Train overpasses shows similar 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 data sets, as principal component analysis shows that the patterns of seasonal variability line up well between the data sets 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.


2020 ◽  
Vol 14 (9) ◽  
pp. 3195-3207
Author(s):  
Anne Sophie Daloz ◽  
Marian Mateling ◽  
Tristan L'Ecuyer ◽  
Mark Kulie ◽  
Norm B. Wood ◽  
...  

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.


2014 ◽  
Vol 7 (2) ◽  
pp. 1001-1025
Author(s):  
L. L. Smith ◽  
J. C. Gille

Abstract. Global satellite observations from the EOS Aura spacecraft's High Resolution Dynamics Limb Sounder (HIRDLS) of temperature and geopotential height (GPH) are discussed. The accuracy, resolution and precision of the HIRDLS version 7 algorithms are assessed and data screening recommendations are made. Comparisons with GPH from observations, reanalyses and models including European Center for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis, Goddard Earth Observing System Model (GEOS) version 5, and EOS Aura Microwave Limb Sounder (MLS) illustrate the HIRDLS GPH have a precision ranging from 2 m to 30 m and an accuracy of ±100 m. Comparisons indicate HIRDLS GPH may have a slight low bias in the tropics and a slight high bias at high latitudes. Geostrophic winds computed with HIRDLS GPH qualitatively agree with winds from other data sources including ERA-Interim, NCEP and GEOS-5.


2014 ◽  
Vol 7 (8) ◽  
pp. 2775-2785 ◽  
Author(s):  
L. L. Smith ◽  
J. C. Gille

Abstract. The geopotential height (GPH) product created from global observations by the High Resolution Dynamics Limb Sounder (HIRDLS) instrument on NASA's Earth Observing System (EOS) Aura spacecraft is discussed. The accuracy, resolution and precision of the HIRDLS version 7 algorithms are assessed and data screening recommendations are made. Comparisons with GPH from observations, reanalyses and models including European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis illustrate the HIRDLS GPHs have a precision ranging from 2 to 30 m and an accuracy of ±100 m up to 1 hPa. Comparisons indicate HIRDLS GPH may have a slight low bias in the tropics and a slight high bias at high latitudes. Geostrophic winds computed with HIRDLS GPH qualitatively agree with winds from other data sources including ERA-Interim.


2008 ◽  
Vol 136 (11) ◽  
pp. 4301-4319 ◽  
Author(s):  
Brandon Kerns ◽  
Kantave Greene ◽  
Edward Zipser

Abstract Using the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40), vorticity maxima (VM) have been manually tracked and classified as developing and nondeveloping. The VM are identified on Hovmöller plots for June–October 1998–2001, within 0°–35°N, 140°–10°W. Over 600 low-level and midlevel VM are tracked. The ERA-40 VM track climatology compares favorably with previous knowledge about easterly waves. Some new results have also been found. The VM are not equivalent to easterly waves, so it is important to distinguish between the large-scale wave and the embedded VM. Unlike waves, individual VM leaving Africa generally do not survive to cross the entire Atlantic. Unlike waves, which can cross Central America, most individual east Pacific VM originate in the east Pacific. Genesis productivity is defined as the fraction of nontropical cyclone VM that eventually develop. It reaches 50% in the eastern North Pacific (EPAC) and 30% in the Atlantic, where there is geographical separation between the locations of maximum nondeveloping and pregenesis track density. There is a strong gradient in daily genesis potential (DGP) near 10°N, associated with weaker upper-level anticyclonic vorticity equatorward of 10°N. The maximum genesis productivity is obtained north of 10°N, where the upper-anticyclonic vorticity and DGP are higher. Finally, there is no obvious distinction in VM strength between developing VM prior to genesis and nondeveloping VM. A major factor is the minimum vorticity threshold for VM as opposed to cloud clusters.


2013 ◽  
Vol 141 (6) ◽  
pp. 1943-1962 ◽  
Author(s):  
Florian P. Pantillon ◽  
Jean-Pierre Chaboureau ◽  
Patrick J. Mascart ◽  
Christine Lac

Abstract The extratropical transition (ET) of a tropical cyclone is known as a source of forecast uncertainty that can propagate far downstream. The present study focuses on the predictability of a Mediterranean tropical-like storm (Medicane) on 26 September 2006 downstream of the ET of Hurricane Helene from 22 to 25 September. While the development of the Medicane was missed in the deterministic forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) initialized before and during ET, it was contained in the ECMWF ensemble forecasts in more than 10% of the 50 members up to 108-h lead time. The 200 ensemble members initialized at 0000 UTC from 20 to 23 September were clustered into two nearly equiprobable scenarios after the synoptic situation over the Mediterranean. In the first and verifying scenario, Helene was steered northeastward by an upstream trough during ET and contributed to the building of a downstream ridge. A trough elongated farther downstream toward Italy and enabled the development of the Medicane in 9 of 102 members. In the second and nonverifying scenario, Helene turned southeastward during ET and the downstream ridge building was reduced. A large-scale low over the British Isles dominated the circulation in Europe and only 1 of 98 members forecasted the Medicane. The two scenarios resulted from a different phasing between Helene and the upstream trough. Sensitivity experiments performed with the Méso-NH model further revealed that initial perturbations targeted on Helene and the upstream trough were sufficient in forecasting the warm-core Medicane at 84- and 108-h lead time.


2014 ◽  
Vol 27 (1) ◽  
pp. 312-324 ◽  
Author(s):  
Jonathan M. Eden ◽  
Martin Widmann

Abstract Producing reliable estimates of changes in precipitation at local and regional scales remains an important challenge in climate science. Statistical downscaling methods are often utilized to bridge the gap between the coarse resolution of general circulation models (GCMs) and the higher resolutions at which information is required by end users. As the skill of GCM precipitation, particularly in simulating temporal variability, is not fully understood, statistical downscaling typically adopts a perfect prognosis (PP) approach in which high-resolution precipitation projections are based on real-world statistical relationships between large-scale atmospheric predictors and local-scale precipitation. Using a nudged simulation of the ECHAM5 GCM, in which the large-scale weather states are forced toward observations of large-scale circulation and temperature for the period 1958–2001, previous work has shown ECHAM5 skill in simulating temporal variability of precipitation to be high in many parts of the world. Here, the same nudged simulation is used in an alternative downscaling approach, based on model output statistics (MOS), in which statistical corrections are derived for simulated precipitation. Cross-validated MOS corrections based on maximum covariance analysis (MCA) and principal component regression (PCR), in addition to a simple local scaling, are shown to perform strongly throughout much of the extratropics. Correlation between downscaled and observed monthly-mean precipitation is as high as 0.8–0.9 in many parts of Europe, North America, and Australia. For these regions, MOS clearly outperforms PP methods that use temperature and circulation as predictors. The strong performance of MOS makes such an approach to downscaling attractive and potentially applicable to climate change simulations.


2012 ◽  
Vol 15 (3) ◽  
pp. 1002-1021 ◽  
Author(s):  
Azadeh Ahmadi ◽  
Dawei Han

Downscaling methods are utilized to assess the effects of large scale atmospheric circulation on local hydrological variables such as precipitation and runoff. In this paper, a methodology of statistical downscaling using a support vector machine (SVM) approach is presented to simulate and predict the precipitation using general circulation model (GCM) data. Due to the complexity and issues related to finding a relationship between the large scale climatic parameters and local precipitation, the climate variables (predictors) affecting monthly precipitation variations over Wales are identified using a combination of the methods including the principal component analysis (PCA), fuzzy clustering, backward selection, forward selection, and Gamma test (GT). The effectiveness of those tools is illustrated through their implementations in the case study. It has been found that although the GT itself fails to identify the best input variable combination, it provides useful and narrowed-down options for further exploration. The best input variable combination is achieved by the GT and forward selection method. This approach can be a useful way for assessing the impacts of climate variables on precipitation forecasting.


2013 ◽  
Vol 6 (4) ◽  
pp. 995 ◽  
Author(s):  
Vanessa De Almeida Dantas ◽  
Ana Cleide Bezerra Amorim ◽  
Micejane Da Silva Costa ◽  
Cláudio Moisés Santos e Silva

Estudos utilizando modelos regionais na realização de downscaling dinâmico tem se mostrado adequado para reproduzir a escala local de uma região. Neste sentido, o presente estudo teve como objetivo analisar a sensibilidade de simulação da precipitação para o ano de 2009 na região do Nordeste Brasileiro (NEB) utilizando três esquemas de parametrização cumulus disponíveis no modelo RegCM4, a saber: Anthes Kuo (Kuo), Grell com fechamento Fristish Chappell (GFC) e MIT-Emmanuel (EM). Como condição inicial e de contorno de grande escala foram usadas informações do modelo European Centre for Medium-Range Weather Forecasts (ECMWF), especificamente o produto ERA_interim. Dados do projeto Tropical Rainfall Measuring Mission (TRMM) foram usados para a avaliação da precipitação simulada. Testes e parâmetros estatísticos foram usados como métrica na avaliação das simulações. Verificou-se que o modelo consegue representar de forma adequada a precipitação quando comparada aos dados do TRMM. Os experimentos que mais se aproximaram das observações foram GFC e EM. O RegCM4 subestimou a precipitação no NEB no início de março e superestimando em meados de julho. Entretanto, é possível afirmar que o modelo é capaz de reproduzir bem a variabilidade do clima, na região do NEB, após alguns ajustes utilizando diferentes tipos parametrizações para os trópicos. ABSTRACT Studies using regional models in performing dynamic downscaling have been adequate to reproduce the local scale of a region. In this sense, the present study aimed to analyze the sensitivity of rainfall simulation for the year 2009 in the Brazilian Northeast (NEB) using three cumulus parameterization schemes available in RegCM4 model, namely: Anthes Kuo (Kuo) Grell closure Fristish Chappell (GFC), and MIT-Emmanuel (EM). As a condition of initial and boundary large scale model information were used European Centre for Medium-Range Weather Forecasts (ECMWF), specifically the product ERA_interim. Project data Tropical Rainfall Measuring Mission (TRMM) were used for the evaluation of simulated rainfall. Testing and statistical parameters were used as a metric in evaluating simulations. It was found that the model can adequately represent the precipitation compared with data from TRMM. The experiments that came closer to the observations were GFC and EM. The RegCM4 underestimated precipitation in the NEB in early March and overestimating in mid-July. However, we can say that the model is able to reproduce well the climate variability in the region of the NEB, after some adjustments using different parameterizations for the tropics. Keywords: RegCM4, Kuo, Grell, Emanuel


2012 ◽  
Vol 25 (10) ◽  
pp. 3453-3475 ◽  
Author(s):  
Benjamin A. Schenkel ◽  
Robert E. Hart

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.


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