Earth System Research Laboratory: Climate Analysis Branch

2007 ◽  
Vol 44 (12) ◽  
pp. 44-6901-44-6901
Keyword(s):  
Research Laboratory ◽  
Earth System ◽  
System Research ◽  
Climate Analysis

scholarly journals Estudo da Temperatura da Superfície do Mar para os Oceanos Atlântico e Pacífico Utilizando a Técnica de Análises de Componente Principal e de Agrupamento (Study of Sea Surface Temperature for the Atlantic and Pacific Oceans Using the Technique of...)

2011 ◽  
Vol 4 (2) ◽  
pp. 264
Author(s):  
Madson Tavares Silva ◽  
Stephany C. F. Do Egito Costa ◽  
Manoel Francisco Gomes Filho ◽  
Daisy B. Lucena
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Research Laboratory ◽  
Principal Component ◽  
Component Analysis ◽  
Sea Surface ◽  
Earth System ◽  
System Research

Apresenta-se neste estudo a avaliação da metodologia de Análises Multivariadas: Análises em Componente Principal (ACP) e de Agrupamento (AA), aos dados de Temperatura da Superfície do Mar (TSM) para os Oceanos Atlântico (Norte (NATL), Tropical (TROP) e Sul (SATL)) e Pacifico (NIÑO1+2, NIÑO3.4, NIÑO3 e NIÑO4). Foram utilizados dados mensais de janeiro de 1950 a dezembro de 2010 de TSM obtidos na NOAA (National Oceanic and Atmospheric Administration/Earth System Research Laboratory). As regiões TROP e NIÑO4 apresentam as maiores TSM para os meses entre dezembro-julho. A região NATL apresenta no período de agosto-outubro seu maiores valores de TSM. A região NIÑo1+2 apresentou os menores valores de TSM. Os resultados da Análise em Componente Principal (ACP) identificaram maiores pesos na variação total explicada pelas duas primeiras componentes, que representam cerca de 100% da variância total dos dados de TSM. A Análise de Agrupamento (AA), pelo método Ward, permitiu o agrupamento das estações em três grupos homogêneos. Palavras - chave: Análises Multivariadas, Mudanças climáticas, Aquecimento Global.   Study of Sea Surface Temperature for the Atlantic and Pacific Oceans Using the Technique of Principal Component Analysis and Cluster   ABSTRACT Presented in this study was to evaluate the methodology of Multivariate Analysis: Principal Component Analysis (PCA) and cluster analysis (CA), the data of sea surface temperature (SST) for the Atlantic (North (NATL), Tropical (TROP) and South (Satler)) and Pacific (+2 NIÑO1, NIÑO3.4, and NIÑO3 NIÑO4). We used monthly data from January 1950 to December 2010 SST obtained from NOAA (National Oceanic and Atmospheric Administration / Earth System Research Laboratory). TROP and NIÑO4 regions have the highest SST for the months from December to July. NATL The region has in the period August-October SST your highest values +2 NIÑo1 The region had the lowest values of TSM. Results on Principal Component Analysis (PCA) identified higher weights in the total variation explained by the first two components, which represent about 100% of the total variance of SST. The Cluster Analysis (AA), the Ward method, allowed the grouping of stations into three homogeneous groups. Keywords: Multivariate Analysis, Climate Change, Global Warming.

scholarly journals Platform-Motion Correction of Velocity Measured by Doppler Lidar

2008 ◽  
Vol 25 (8) ◽  
pp. 1369-1382 ◽  
Author(s):  
Reginald J. Hill ◽  
W. Alan Brewer ◽  
Sara C. Tucker
Keyword(s):  
Motion Correction ◽  
Research Laboratory ◽  
Doppler Velocity ◽  
Doppler Lidar ◽  
Earth System ◽  
System Research ◽  
Velocity Data ◽  
Velocity Measurements ◽  
Platform Motion ◽  
Coherent Doppler Lidar

Abstract The NOAA/Earth System Research Laboratory (ESRL) has two coherent Doppler lidar systems that have been deployed on board research vessels to obtain data during several experiments. The instruments measure the wind velocity relative to the motion of the lidar; therefore, correction for the motion of the platform is required. This article gives a thorough analysis of the correction for lidar velocity measurements. The analysis is general enough to be applied to Doppler velocity measurements from all monostatic ship- and aircraftborne lidars and radars, and generalization to bistatic systems is achievable. The correction is demonstrated using miniature master-oscillator power-amplifier (mini-MOPA) Doppler velocity data obtained during the Rain in Cumulus over the Ocean (RICO) experiment.

A influência da temperatura da superfície do mar do oceano Pacífico na precipitação pluvial de Penedo-AL

2018 ◽  
Vol 2 (2) ◽  
pp. 8
Author(s):  
Eliane Barbosa Santos ◽  
Gildo Rafael De Almeida SANTANA
Keyword(s):  
Research Laboratory ◽  
Earth System ◽  
System Research

Estudos climáticos da ocorrência de precipitações extremas têm importante papel socioeconômico, pois longos períodos secos e chuvosos acarretam prejuízos para a infraestrutura das cidades. Com isso, o objetivo desse estudo é analisar as tendências dos índices dependentes da precipitação pluvial diária para o Município de Penedo, assim como, analisar suas relações com as Temperaturas da Superfície do Mar (TSM) das regiões dos Niños (1+2, 3, 3.4 e 4), no período de 1948 a 2007. Os dados de precipitação foram obtidos através da Agência Nacional de Águas (ANA) e os dados referentes às TSM das regiões dos Niños foram obtidos no site do Earth System Research Laboratory. O software utilizado no processamento e controle de qualidade dos dados de precipitação diária foi o RClimdex 1.9.0. Com base nos resultados encontrados, foram observadas tendências de aumento do número de dias secos consecutivos e uma diminuição do número de dias úmidos consecutivos, assim como, uma diminuição em dias com precipitação igual ou acima de 50 mm. As correlações estatisticamente significativas entre os índices de precipitação e as TSM foram negativas, indicando que um aumento nas TSM das regiões dos Niños leva a uma diminuição dos eventos extremos de chuva e do número de dias úmidos consecutivos na região em estudo. Das regiões dos Niños, as TSM dos Niños 1+2 e 3 foram as que apresentaram melhores relações com os índices de precipitação do Município de Penedo.

scholarly journals Convection and Rapid Filamentation in Typhoon Sinlaku during TCS-08/T-PARC

2012 ◽  
Vol 140 (9) ◽  
pp. 2806-2817 ◽  
Author(s):  
Hung-Chi Kuo ◽  
Chih-Pei Chang ◽  
Ching-Hwang Liu
Keyword(s):  
Research Laboratory ◽  
Field Experiments ◽  
Deep Convection ◽  
Naval Research ◽  
Upward Motion ◽  
System Research ◽  
Spiral Rainband ◽  
Spiral Bands ◽  
Aircraft Data ◽  
Development And Evolution

Abstract This study examines the convection and rapid filamentation in Typhoon Sinlaku (2008) using the Naval Research Laboratory (NRL) P-3 aircraft data collected during the Tropical Cyclone Structure 2008 (TCS-08) and The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) field experiments. The high-resolution aircraft radar and wind data are used to directly compute the filamentation time, to allow an investigation into the effect of filamentation on convection. During the reintensification stage, some regions of deep convection near the eyewall are found in the vorticity-dominated area where there is little filamentation. In some other parts of the eyewall and the outer spiral rainband region, including areas of upward motion, the filamentation process appears to suppress deep convection. However, the magnitude of the suppression differs greatly in the two regions. In the outer spiral band region, which is about 200 km from the center, the suppression is much more effective, such that the ratio of the deep convective regime occurrence over the stratiform regime varies from around 50% (200%) for filamentation time shorter (longer) than 24 min. In the eyewall cloud region where the conditions are conducive to deep convection, the filamentation effect may be quite limited. While effect of filamentation suppression is only about 10%, it is still systematic and conspicuous for filamentation times shorter than 19 min. The results suggest the possible importance of vortex-scale filamentation dynamics in suppressing deep convection and organizing spiral bands, which may affect the development and evolution of tropical cyclones.

scholarly journals How Should a Global Carbon Budget be Estimated?

2021 ◽  
Author(s):  
Paul Clements
Keyword(s):  
Global Warming ◽  
Co2 Emissions ◽  
Carbon Budget ◽  
Arctic Sea Ice ◽  
Atmospheric Co2 ◽  
Earth System ◽  
Intergovernmental Panel ◽  
System Models ◽  
Climate Analysis ◽  
Earth System Models

Abstract The Intergovernmental Panel on Climate Change (IPCC), the authority for estimating a carbon budget for keeping to the Paris Agreement’s 1.5—2°C target for limiting global warming, has indicated a budget of 580—1170 gigatons (Gt) of carbon dioxide (CO2) from 2018. This budget is based largely on Earth system models using data from the instrumental record over the industrial period. During the prior 800,000 years, however, a range of 120 parts per million (ppm) in atmospheric CO2 was associated with about a 6°C change in temperature, while temperature has only risen about 1°C with the 130 ppm increase in atmospheric CO2 in the industrial period. The paleoclimate record indicates that the anthropogenic increase in CO2 up to the present commits Earth to significant additional warming, such as from reduced albedo as Arctic sea ice melts and further CO2 release from vegetative stores. Instrumental data and model updates also indicate greater warming from these sources than IPCC models predict. Additionally, reductions in CO2 emissions to meet the Paris warming target will also reduce cooling from aerosols, which the IPCC may also have underestimated. Together, these factors indicate that CO2 emissions consistent with the IPCC’s carbon budget are likely to lead to at least 2—2.5°C global warming. I draw on the sustained critique of IPCC findings by Hansen and his colleagues, who have argued that the paleoclimate should be considered on par with Earth system models in climate analysis, and for more ambitious targets for reducing CO2 emissions.

Common evaluation/evolution of cloud-radiation processes from 25km S2S to 3km NWP

2020 ◽  
Author(s):  
Stan Benjamin ◽  
Joseph Joseph Olson ◽  
Shan Sun ◽  
Georg Georg Grell ◽  
Curtis Curtis Alexander
Keyword(s):  
Solar Radiation ◽  
Turbulent Mixing ◽  
Earth System ◽  
Subgrid Scale ◽  
System Research ◽  
Shallow Convection ◽  
Near Surface ◽  
Land System ◽  
Scale Models ◽  
Physical Parameterizations

<p>Subgrid-scale cloud representation and the closely related surface-energy balance continue to be a central challenge from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours. Previously, NOAA/ESRL confirmed this issue from 3-km model (HRRR using WRF-ARW) for short-range forecasting including sub-grid-scale cloud representation up to a 25-km subseasonal model (FV3-GFS) testing a common suite of scale-aware physical parameterizations.  </p><p>In a major physics suite component -- modified representation of subgrid cloud water resulted in much improved agreement with radiation measurements as shown with 2018-2020 testing of the 3km HRRR model. Latest results will be shown using SURFRAD radiation and METAR ceiling observations, indicating much improved bias in downward solar radiation and in cloud location (via mean absolute error metric), as well as with 2m temperature and precipitation.</p><p>In addition, new evaluations with the same convection-allowing suite (“mesoscale” suite) of physical parameterizations revised further for subseasonal 30-day tests over summer and winter periods with the 25km NOAA FV3-GFS model. These results are compared with CERES-estimated cloud and downward solar radiation fields. The radiation results from this very preliminary subseasonal test with the ESRL-HRRR physics suite will be compared with previous subseasonal tests using the GFS physics suite and at different horizontal resolution.  This global application now confirms much better downward solar-radiation results over oceans for both January and June from a Nov-2019 version over a 2018 of the “mesoscale” suite.</p><p>Background: NOAA Earth System Research Laboratory, together with NCAR, has developed this parameterization suite (turbulent mixing, deep/shallow convection, 9-layer land/snow/vegetation/lake model) to improve PBL biases (temperature and moisture) including better representation of clouds and precipitation. This parameterization suite development has been accompanied by an effort for improved data assimilation of clouds, near-surface observations and radar for the atmosphere-land system.</p><p>Subgrid-scale cloud representation continues to be a central challenge from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours.   Previously, NOAA/ESRL confirmed this issue from 3-km model (HRRR) for short-range forecasting including sub-grid-scale cloud representation up to a 60-km subseasonal model testing a common suite of scale-aware physical parameterizations.   Some progress has been made in 2018-2019 to substantially reduce cloud deficiency and excessive downward solar radiation at least over land areas.</p><p>Recent development and refinements to this common suite of physical parameterizations for scale-aware deep/shallow convection and boundary-layer mixing over this wide range of time and spatial scales will be reported in this presentation showing some progress. Evaluation of components of this suite is being evaluated for cloud/radiation (using SURFRAD, CERES, METAR ceiling) and near-surface (METAR, mesonet, aircraft, rawinsonde).</p><p>NOAA Earth System Research Laboratory, together with NCAR, has developed this parameterization suite (turbulent mixing, deep/shallow convection, 9-layer land/snow/vegetation model) to improve PBL biases (temperature and moisture) including better representation of clouds and precipitation. This parameterization suite development has been accompanied by an effort for improved data assimilation of clouds, near-surface observations and radar for the atmosphere-land system.  </p><p>The MYNN boundary-layer EDMF scheme (Olson, et al 2019), RUC land-surface model (Smirnova et al. 2016 MWR), Grell-Freitas scheme (2014, Atmos. Chem. Phys.), and aerosol-aware cloud microphysics (Thompson and Eidhammer 2015) have been applied and tested extensively for the NOAA hourly updated 3-km High-Resolution Rapid Refresh (HRRR) and 13-km Rapid Refresh model/assimilation systems over the United States and North America.   This mesoscale but also scale-aware suite is being tested,</p>

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