scholarly journals Tree-Ring Based Reconstructions of Paleo-Precipitation Regimes in the Eastern Yellowstone Region

2000 ◽  
Vol 24 ◽  
pp. 144-148
Author(s):  
S. Gray ◽  
S. Jackson ◽  
K. Taylor ◽  
C. Palmer ◽  
C. Fastie
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Tree Ring ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Climate Variation ◽  
Climate System ◽  
Precipitation Regimes ◽  
Instrumental Records

There are few other regions where the influence of climate on basic ecosystem attributes has been as well documented as the Greater Yellowstone Ecosystem (GYE). Research has shown that elk, bison, and grizzly bear populations in the GYE are tightly linked to annual climate variation (Meagher 1976, Picton 1978). Authors have shown that the distribution of vegetation types in Grand Teton and Yellowstone National Parks is influenced by the seasonality of precipitation (Despain 1987, 1990). Natural disturbances, especially fires and insect outbreaks, are also known to coincide with specific climate scenarios in this region (Knight 1987, Balling et al. 1992). Therefore, understanding how climate can vary over time is essential for the proper management of these areas (Luckman 1996). Modem instrumental records have contributed greatly to our understanding of the current GYE climate system. In particular, work by Mock (1996) and Bartlein et al. (1997) has demonstrated how local manifestations of large-scale circulation patterns produce distinct climates within the GYE. In addition, studies using modem climate records and General Circulation Models by Balling et al. (1992) and Bartlein et al. (1997) have identified trends toward increasing aridity in the GYE and the potential for these trends to continue well into the future. Late Pleistocene and Holocene (18-1 kya) climate in the GYE is known mainly from lake­sediment cores. Work by Whitlock (1993), Whitlock and Bartlein (1993), and Thompson et al. (1993) indicates that after deglaciation, increased solar radiation during summer months led to a highly seasonal climate regime. As levels of solar radiation changed through the Holocene, GYE climate became increasingly more like today until the modem regime became established around 1500-1600 AD (Whitlock 1993, Elias 1997). While existing modem and paleoecological studies reveal important aspects of the GYE climate system, there is a distinct lack of high-resolution data for most of the last millennium. Lake sediments only record climate variation at a resolution of hundreds to thousands of years, and instrumental records do not exist before the 1890s. Dendroclimatology, the study of climate using patterns of tree-ring growth (Fritts 1976) is particularly well suited to fill this gap in our knowledge of GYE climate. Tree-rings have been used successfully for climate reconstructions worldwide, offer records spanning decades to millennia, and can provide annual resolution. Therefore, we are developing a network of tree-ring sites in the western Absaroka Mountains and eastern Bighorn Basin to fill important spatial (areas east of Yellowstone NP) and temporal (high resolution for the past 700-1,000+year) gaps in our knowledge of GYE climate.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

Global monthly sea surface temperature and sea ice reconstruction for historical simulations

2020 ◽  
Author(s):  
Eric Samakinwa ◽  
Stefan Brönnimann
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Sea Surface ◽  
Annual Variability ◽  
Instrumental Records

<p>Variability in Sea Surface Temperature (SST) is one of the prime sources of intra-annual variability, and also an important boundary condition for Atmospheric General Circulation Models (AGCMs). In many AGCM simulations, SST and Sea Ice Concentration (SIC) are prescribed. While SSTs are specified according to observations available in recent period of instrumental records (1850 – present), SIC depends on climatological averages with less variability prior to the inception of satellite measurements. This limits our understanding of large-scale climate variations in the past.</p><p>In this study, we augment multi-proxy reconstructed annual mean temperature of Neukom et al. (2019) with intra-annual variability from HadISST (v2.0), for 850 years (1000 – 1849). Intra-seasonal variability, such as the phase-locking of El-Nino Southern Oscillation, Indian Ocean Dipole and Tropical Atlantic SST indices to annual-cycle, are utilized. The intra-annual component of HadISST and SST indices estimated from the multi-proxy reconstructed annual mean, are used to develop grid-based multivariate linear regression models using the Frisch-Waugh-Lovell theorem, in a monthly stratified approach. Furthermore, we introduce a scaling technique to ensure homogeneous mean and variance, similar to that of the target. SST observations obtained from ship measurements by ICOADS before 1850, will be integrated in an off-line data assimilation approach.</p><p>Similarly, we reconstruct SIC via analogue resampling of HadISST SIC (1941 – 2000), for both hemispheres. We pool our analogues in four seasons, comprising of 3 months each, such that for each month within a season, there are 180 possible analogues. The best analogues are selected based on correlation coefficients between reconstructed SST and its target.</p>

scholarly journals Evaluation of WRF Mean and Extreme Precipitation over Spain: Present Climate (1970–99)

2012 ◽  
Vol 25 (14) ◽  
pp. 4883-4897 ◽  
Author(s):  
Daniel Argüeso ◽  
José Manuel Hidalgo-Muñoz ◽  
Sonia Raquel Gámiz-Fortis ◽  
María Jesús Esteban-Parra ◽  
Yolanda Castro-Díez
Keyword(s):  
Spatial Distribution ◽  
High Resolution ◽  
Iberian Peninsula ◽  
Extreme Events ◽  
General Circulation ◽  
Rainfall Variability ◽  
General Circulation Models ◽  
Monthly Precipitation ◽  
Climate System Model ◽  
Precipitation Regimes

Abstract The ability of the Weather Research and Forecasting model (WRF) to simulate precipitation over Spain is evaluated from a climatological point of view. The complex topography and the large rainfall variability make the Iberian Peninsula a particularly interesting region and permit assessment of model performance under very demanding conditions. Three high-resolution (10 km) simulations over the Iberian Peninsula have been completed spanning a 30-yr period (1970–99) and driven by different datasets: the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) as “perfect boundary conditions” and two general circulation models (GCMs), the Max Planck Institute ECHAM5 model (ECHAM5/MPI) and the NCAR Community Climate System Model, version 3 (CCSM3). The daily precipitation observational grid Spain02 is employed to evaluate the model at varying time scales. Not only are the long-term means (annual, seasonal, and monthly) examined but also the high-order statistics (extreme events). The WRF provides valuable information on precipitation at high resolution and enhances local spatial distribution due to orographic features. Although substantial errors are still observed in terms of monthly precipitation, especially during the spring, the model is largely able to capture the various precipitation regimes. The major benefits of using WRF are related to the spatial distribution of rainfall and the simulation of extreme events, two facets of climate that can be barely explored with GCMs. This study shows that WRF can be a useful tool for generating high-resolution climate information for Spanish precipitation at spatial and temporal scales that are crucial for both the environment and human life.

scholarly journals Quantification of Uncertainty in High-Resolution Temperature Scenarios for North America

2012 ◽  
Vol 25 (9) ◽  
pp. 3373-3389 ◽  
Author(s):  
Guilong Li ◽  
Xuebin Zhang ◽  
Francis Zwiers ◽  
Qiuzi H. Wen
Keyword(s):  
High Resolution ◽  
North America ◽  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Internal Variability ◽  
General Circulation Models ◽  
First Century ◽  
Small Scale ◽  
Twenty First Century

A framework for the construction of probabilistic projections of high-resolution monthly temperature over North America using available outputs of opportunity from ensembles of multiple general circulation models (GCMs) and multiple regional climate models (RCMs) is proposed. In this approach, a statistical relationship is first established between RCM output and that from the respective driving GCM and then this relationship is applied to downscale outputs from a larger number of GCM simulations. Those statistically downscaled projections were used to estimate empirical quantiles at high resolution. Uncertainty in the projected temperature was partitioned into four sources including differences in GCMs, internal variability simulated by GCMs, differences in RCMs, and statistical downscaling including internal variability at finer spatial scale. Large spatial variability in projected future temperature changes is found, with increasingly larger changes toward the north in winter temperature and larger changes in the central United States in summer temperature. Under a given emission scenario, downscaling from large scale to small scale is the most important source of uncertainty, though structural errors in GCMs become equally important by the end of the twenty-first century. Different emission scenarios yield different projections of temperature change. This difference increases with time. The difference between the IPCC’s Special Report on Emissions Scenarios (SRES) A2 and B1 in the median values of projected changes in 30-yr mean temperature is small for the coming 30 yr, but can become almost as large as the total variance due to internal variability and modeling errors in both GCM and RCM later in the twenty-first century.

scholarly journals Large-Scale Precipitation Variability over Northwest China Inferred from Tree Rings

2011 ◽  
Vol 24 (13) ◽  
pp. 3457-3468 ◽  
Author(s):  
Keyan Fang ◽  
Xiaohua Gou ◽  
Fahu Chen ◽  
Edward Cook ◽  
Jinbao Li ◽  
...  
Keyword(s):  
Tree Ring ◽  
Large Scale ◽  
Principal Component ◽  
Northwest China ◽  
Poor Quality ◽  
Contour Method ◽  
Precipitation Reconstruction ◽  
Nw China ◽  
Climate Station ◽  
Instrumental Records

Abstract A preliminary study of a point-by-point spatial precipitation reconstruction for northwestern (NW) China is explored, based on a tree-ring network of 132 chronologies. Precipitation variations during the past ~200–400 yr (the common reconstruction period is from 1802 to 1990) are reconstructed for 26 stations in NW China from a nationwide 160-station dataset. The authors introduce a “search spatial correlation contour” method to locate candidate tree-ring predictors for the reconstruction data of a given climate station. Calibration and verification results indicate that most precipitation reconstruction models are acceptable, except for a few reconstructions (stations Hetian, Hami, Jiuquan, and Wuwei) with degraded quality. Additionally, the authors compare four spatial precipitation factors in the instrumental records and reconstructions derived from a rotated principal component analysis (RPCA). The northern and southern Xinjiang factors from the instrumental and reconstructed data agree well with each other. However, differences in spatial patterns between the instrumentation and reconstruction data are also found for the other two factors, which probably result from the relatively poor quality of a few stations. Major drought events documented in previous studies—for example, from the 1920s through the 1930s for the eastern part of NW China—are reconstructed in this study.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

scholarly journals Cloud and Precipitation Parameterizations in Modeling and Variational Data Assimilation: A Review

2007 ◽  
Vol 64 (11) ◽  
pp. 3766-3784 ◽  
Author(s):  
Philippe Lopez
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Large Scale ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Variational Data Assimilation ◽  
Current Status ◽  
General Question ◽  
Observation Error ◽  
Moist Processes

Abstract This paper first reviews the current status, issues, and limitations of the parameterizations of atmospheric large-scale and convective moist processes that are used in numerical weather prediction and climate general circulation models. Both large-scale (resolved) and convective (subgrid scale) moist processes are dealt with. Then, the general question of the inclusion of diabatic processes in variational data assimilation systems is addressed. The focus is put on linearity and resolution issues, the specification of model and observation error statistics, the formulation of the control vector, and the problems specific to the assimilation of observations directly affected by clouds and precipitation.

Atmospheric response to Gulf Stream SST front shifting: impact of horizontal resolution in an ensemble of global climate models

2021 ◽  
Author(s):  
Luca Famooss Paolini ◽  
Alessio Bellucci ◽  
Paolo Ruggieri ◽  
Panos Athanasiadis ◽  
Silvio Gualdi
Keyword(s):  
High Resolution ◽  
Gulf Stream ◽  
General Circulation ◽  
Diabatic Heating ◽  
Storm Track ◽  
General Circulation Models ◽  
Horizontal Resolution ◽  
Atmospheric Response ◽  
Sst Front ◽  
Pressure Anomaly

<p>Western boundary currents transport a large amount of heat from the Tropics toward higher latitudes; furthermore they are characterized by a strong sea surface temperature (SST) gradient, which anchors zones of intense upward motion extending up to the upper-troposphere and shapes zones of intense baroclinic eddy activity (storm tracks). For such reasons they have been shown to be fundamental in influencing the climate of the Northern Hemisphere and its variability, and a potentially relevant source of atmospheric predictability. </p><p> </p><p>General circulation models show deficiencies in simulating the observed atmospheric response to SST front variability. The atmospheric horizontal resolution has been recently proposed as a key element in understanding such differences. However, the number of studies on this subject is still limited. Furthermore, a multi-model analysis to systematically investigate differences between low-resolution and high-resolution atmospheric response to oceanic forcing is still lacking. </p><p> </p><p>The present work has the objective to fill this gap, analysing the atmospheric response to Gulf Stream SST front shifting using data from recent High Resolution Model Intercomparison Project (HighResMIP). This project was designed with the specific objective of investigating the impact of increased model horizontal resolution on the representation of the observed climate. Ensembles of historical simulations performed with three atmospheric general circulation models (AGCMs) have been analysed, each conducted with a low-resolution (LR, about 1°) and a high-resolution (HR, about 0.25°) configuration. AGCMs have been forced with observed SSTs (HadISST2 dataset), available at daily frequency on a 0.25° grid, during 1950–2014. </p><p><br>Results show atmospheric responses to the SST-induced diabatic heating anomalies that are strongly resolution dependent. In LR simulations a low-pressure anomaly is present downstream of the SST anomaly, while the diabatic heating anomaly is mainly balanced by meridional advection of air coming from higher latitudes, as expected for an extra-tropical shallow heat source. In contrast, HR simulations generate a high-pressure anomaly downstream of the SST anomaly, thus driving positive temperature advection from lower latitudes (not balancing diabatic heating). Along the vertical direction, both in LR and HR simulation, the diabatic heating in the interior of the atmosphere is balanced by upward motion south of GS SST front and downward motion north and further south of the Gulf Stream. Finally, LR simulations show a reduction in storm-track activity over the North Atlantic, whereas HR simulations show a meridional displacement of the storm-track considerably larger (yet in the same direction) than that of the SST front. HR simulations reproduce the atmospheric response obtained from observations, albeit weaker. This is a hint for the existence of a positive feedback between ocean and atmosphere, as proposed in previous studies. These findings are qualitatively consistent with previous results in literature and, leveraging on recent coordinated modelling efforts, shed light on the effective role of atmospheric horizontal resolution in modelling the atmospheric response to extra-tropical oceanic forcing.</p>

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