scholarly journals A Multiyear Ensemble Simulation of the U.S. Climate with a Stretched-Grid GCM

2005 ◽  
Vol 133 (9) ◽  
pp. 2505-2525 ◽  
Author(s):  
Michael S. Fox-Rabinovitz ◽  
Ernesto Hugo Berbery ◽  
Lawrence L. Takacs ◽  
Ravi C. Govindaraju
Keyword(s):  
Regional Climate ◽  
Warm Season ◽  
The United States ◽  
Rain Gauge ◽  
Climate Simulation ◽  
Uniform Grid ◽  
Low Level ◽  
Mountainous Regions ◽  
Ensemble Simulations ◽  
The Impact

Abstract Multiyear (1987–97) limited ensemble integrations using a stretched-grid GCM, previously developed and experimented with by the authors, are employed for U.S. regional climate simulations. The ensemble members (six in total) are produced at two different regional resolutions: three members with 60-km and the other three members with 10-km regional resolution. The use of these two finer and coarser regional resolution ensemble members allows one to examine the impact of resolution on the overall quality of the simulated regional fields. For the multiyear ensemble simulations, an efficient regional downscaling to realistic mesoscales has been obtained. The ensemble means of the midtroposphere prognostic variables (height and meridional wind) show an overall good resemblance to the global reanalysis, especially for summer. Low-level features like the warm season Great Plains low-level jet are well represented in the simulations. During winter the 100-km simulations develop a southward wind east of the Rockies that is present neither in the reanalyses nor in the 60-km simulations. The analysis of the annual mean precipitation and its variance reveals that the ensemble simulations reproduce many of the observed features of a high-resolution rain gauge dataset analyzed on a 0.5° × 0.5° grid. Signal-to-noise ratios are larger than 1.5 s over a major part of the United States, especially over the Midwest and also over the mountainous regions like the Rockies and the Appalachians, suggesting that the orographic forcing is contributing to a larger signal. The ratios are smaller toward the eastern and western U.S. coastlines. This result could be attributed, at least in part, to limits in the representation of the land–sea contrasts. For comparison purposes, an additional simulation has been performed using a global uniform 2° × 2.5° grid with the same number of global grid points as those of the above stretched grids. The stretched-grid GCM ensemble means show, overall, a better regional depiction of features than those of the uniform-grid GCM. The results of the study show that even using limited ensemble integrations with a state-of-the-art stretched-grid GCM is beneficial for reducing the uncertainty of the multiyear regional climate simulation, especially when using finer 60-km regional resolution.

scholarly journals Observations and  Modelling of Precipitation  in the Southern Alps of  New Zealand

2021 ◽  
Author(s):  
◽  
Stephen John Stuart
Keyword(s):  
New Zealand ◽  
Climate Model ◽  
Regional Climate ◽  
Rain Gauge ◽  
Southern Alps ◽  
Annual Rainfall ◽  
Mean Annual Precipitation ◽  
Mountain Range ◽  
Mountainous Regions ◽  
Orographic Rainfall

<p>Precipitation in the central Southern Alps affects glaciation, river flows and key economic activities, yet there is still uncertainty about its spatial distribution and primary influences. Long-term and future patterns of New Zealand precipitation can be estimated by the HadRM3P regional climate model (RCM) - developed by the United Kingdom Met Office - but orographic rainfall in the steep and rugged topography of the Southern Alps is difficult to simulate accurately at the 30-km resolution of the RCM. To quantify empirical relationships, observations of surface rainfall were gathered from rain gauges covering a broad region of the South Island. In four transects of the Hokitika, Franz Josef and Haast regions, the mean annual precipitation maxima of objectively interpolated profiles are consistently located 7-11 km southeast of the New Zealand Alpine Fault. The magnitude and shape of the rainfall profile across the Southern Alps are strongly influenced by the 850-hPa wind direction to the north of the mountain range, as determined by comparing rain-gauge observations to wind vectors from NCEP/NCAR Reanalysis 1. The observed profile of orographically enhanced rainfall was incorporated into a trivariate spline in order to interpolate precipitation simulated by the RCM. This downscaling method significantly improved the RCM's estimates of mean annual rainfall at stations in the Southern Alps region from 1971 to 2000, and RCM projections of future rainfall in mountainous regions may be similarly refined via this technique. The improved understanding of the observed rainfall distribution in the Southern Alps, as gained from this analysis, has a range of other hydrological applications and is already being used in 'downstream' modelling of glaciers.</p>

scholarly journals Convection Initiation Caused by Heterogeneous Low-Level Jets over the Great Plains

2018 ◽  
Vol 146 (8) ◽  
pp. 2615-2637 ◽  
Author(s):  
Joshua G. Gebauer ◽  
Alan Shapiro ◽  
Evgeni Fedorovich ◽  
Petra Klein
Keyword(s):  
Great Plains ◽  
Three Dimensional ◽  
Warm Season ◽  
The United States ◽  
Dimensional Structure ◽  
Nonuniform Heating ◽  
Low Level ◽  
Low Level Jets ◽  
Convection Initiation ◽  
Capping Inversion

AbstractObservations from three nights of the Plains Elevated Convection at Night (PECAN) field campaign were used in conjunction with Rapid Refresh model forecasts to find the cause of north–south lines of convection, which initiated away from obvious surface boundaries. Such pristine convection initiation (CI) is relatively common during the warm season over the Great Plains of the United States. The observations and model forecasts revealed that all three nights had horizontally heterogeneous and veering-with-height low-level jets (LLJs) of nonuniform depth. The veering and heterogeneity were associated with convergence at the top-eastern edge of the LLJ, where moisture advection was also occurring. As time progressed, this upper region became saturated and, due to its placement above the capping inversion, formed moist absolutely unstable layers, from which the convergence helped initiate elevated convection. The structure of the LLJs on the CI nights was likely influenced by nonuniform heating across the sloped terrain, which led to the uneven LLJ depth and contributed toward the wind veering with height through the creation of horizontal buoyancy gradients. These three CI events highlight the importance of assessing the full three-dimensional structure of the LLJ when forecasting nocturnal convection over the Great Plains.

Assessing the Impact of Remittances on Schooling: the Mexican Experience

2005 ◽  
Vol 5 (1) ◽  
pp. 1850033 ◽  
Author(s):  
Fernando Borraz
Keyword(s):  
United States ◽  
Human Capital ◽  
Census Data ◽  
The United States ◽  
Level Of Education ◽  
Low Level ◽  
Child Human Capital ◽  
The Impact

This paper analyzes the impact of remittances on child human capital in Mexico. During the 90’s and in particular after the “tequila crisis” Mexican workers increased the remittances that were sent to their homes from the United States. I will analyze the effect of such increasing source of income on child human capital decisions. Contrary to Hanson and Woodruff (2003) the results obtained from Census data indicate a positive and small effect of remittances on schooling only for children living in cities with fewer than 2,500 inhabitants and with mothers with a very low level of education. However its magnitude is not substantial.

scholarly journals “1D+4DVAR” Assimilation of NCEP Stage-IV Radar and Gauge Hourly Precipitation Data at ECMWF

2007 ◽  
Vol 135 (7) ◽  
pp. 2506-2524 ◽  
Author(s):  
Philippe Lopez ◽  
Peter Bauer
Keyword(s):  
Stage Iv ◽  
The United States ◽  
Rain Gauge ◽  
Precipitation Data ◽  
Surface Precipitation ◽  
Weather Radars ◽  
Potential Impact ◽  
Microwave Imager ◽  
The Impact

Abstract The one- plus four-dimensional variational data assimilation (“1D+4DVAR”) method currently run in operations at ECMWF with rain-affected radiances from the Special Sensor Microwave Imager is used to study the potential impact of assimilating NCEP stage-IV analyses of hourly accumulated surface precipitation over the U.S. mainland. These data are a combination of rain gauge measurements and observations from the high-resolution Doppler Next-Generation Weather Radars. Several 1D+4DVAR experiments have been run over a month in spring 2005. First, the quality of the precipitation forecasts in the control experiment is assessed. Then, it is shown that the impact of the assimilation of the additional rain observations on global scores of dynamical fields and temperature is rather neutral, while precipitation scores are improved for forecast ranges up to 12 h. Additional 1D+4DVAR experiments in which all moisture-affected observations are removed over the United States demonstrate that the NCEP stage-IV precipitation data on their own can clearly be beneficial to the analyses and subsequent forecasts of the moisture field. This result suggests that the potential impact of precipitation observations is overshadowed by the influence of other high-quality humidity observations, in particular, radiosondes. It also confirms that the assimilation of precipitation observations has the ability to improve the quality of moisture analyses and forecasts in data-sparse regions. Finally, the limitations inherent in the current assimilation of precipitation data, their implications for the future, and possible ways of improvement are discussed.

scholarly journals Convection-permitting regional climate simulation of warm-season precipitation over Eastern China

2019 ◽  
Vol 54 (3-4) ◽  
pp. 1469-1489 ◽  
Author(s):  
Yuxing Yun ◽  
Changhai Liu ◽  
Yali Luo ◽  
Xudong Liang ◽  
Ling Huang ◽  
...  
Keyword(s):  
East Asia ◽  
Regional Climate ◽  
Eastern China ◽  
Precipitation Amount ◽  
Wrf Model ◽  
Warm Season ◽  
Climate Simulation ◽  
The Tibetan Plateau ◽  
Model Skill ◽  
Geographical Regions

AbstractConvection-permitting regional climate models have been shown to improve precipitation simulation in many aspects, such as the diurnal cycle, precipitation frequency, intensity and extremes in many studies over several geographical regions of the world, but their skill in reproducing the warm-season precipitation characteristics over the East Asia has not been robustly tested yet. Motivated by recent advances in computing power, model physics and high-resolution reanalysis, we use the convection-permitting weather research and forecasting (WRF) model configured with 3 km grid spacing to simulate the warm-season precipitation in eastern China for 10 seasons (2008–2017). The hourly 31-km-resolution ERA5 reanalysis data are used to provide initial and boundary conditions for the simulations. The objectives are (1) to evaluate the model skill in simulating warm-season precipitation climatology in the East Asian monsoon region, (2) to identify the promises and problems of the convection-permitting simulation, and (3) to investigate solutions for the model deficiencies. Results demonstrate that the 3-km-resolution WRF model reasonably reproduces the spatial characteristics of seasonal and sub-seasonal precipitation, the seasonal meridional migration associated with the summer monsoon activity, the diurnal variation phase and amplitude, and the propagating convection east of the Tibetan Plateau. The major deficiency is that the model overestimates precipitation amount, especially in the afternoon. Analysis and sensitivity experiments suggest that improved treatment of sub-grid cloud fraction and the aerosol effects may help to suppress the oft-reported high precipitation bias. These results provide useful guidance for improving the model skill at simulating warm-season precipitation in East Asia.

scholarly journals Added Value of Atmosphere-Ocean Coupling in a Century-Long Regional Climate Simulation

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 537 ◽  
Author(s):  
Fanni Dóra Kelemen ◽  
Cristina Primo ◽  
Hendrik Feldmann ◽  
Bodo Ahrens
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Climate Simulation ◽  
Climatic Research Unit ◽  
Small Scale ◽  
Limited Area ◽  
Regional Climate Simulation ◽  
Marginal Seas ◽  
The Impact

A twentieth century-long coupled atmosphere-ocean regional climate simulation with COSMO-CLM (Consortium for Small-Scale Modeling, Climate Limited-area Model) and NEMO (Nucleus for European Modelling of the Ocean) is studied here to evaluate the added value of coupled marginal seas over continental regions. The interactive coupling of the marginal seas, namely the Mediterranean, the North and the Baltic Seas, to the atmosphere in the European region gives a comprehensive modelling system. It is expected to be able to describe the climatological features of this geographically complex area even more precisely than an atmosphere-only climate model. The investigated variables are precipitation and 2 m temperature. Sensitivity studies are used to assess the impact of SST (sea surface temperature) changes over land areas. The different SST values affect the continental precipitation more than the 2 m temperature. The simulated variables are compared to the CRU (Climatic Research Unit) observational data, and also to the HOAPS/GPCC (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, Global Precipitation Climatology Centre) data. In the coupled simulation, added skill is found primarily during winter over the eastern part of Europe. Our analysis shows that, over this region, the coupled system is dryer than the uncoupled system, both in terms of precipitation and soil moisture, which means a decrease in the bias of the system. Thus, the coupling improves the simulation of precipitation over the eastern part of Europe, due to cooler SST values and in consequence, drier soil.

scholarly journals Comparison of Methods Used to Generate Probabilistic Quantitative Precipitation Forecasts over South America

2009 ◽  
Vol 24 (1) ◽  
pp. 319-336 ◽  
Author(s):  
Juan Ruiz ◽  
Celeste Saulo ◽  
Eugenia Kalnay
Keyword(s):  
South America ◽  
Warm Season ◽  
Rain Gauge ◽  
Precipitation Forecast ◽  
Precipitation Regimes ◽  
Quantitative Precipitation Forecasts ◽  
Systematic Biases ◽  
Ensemble Systems ◽  
Calibration Techniques ◽  
The Impact

Abstract In this work, the quality of several probabilistic quantitative precipitation forecasts (PQPFs) is examined. The analysis is focused over South America during a 2-month period in the warm season. Several ways of generating and calibrating the PQPFs have been tested, using different ensemble systems and single-model runs. Two alternative calibration techniques (static and dynamic) have been tested. To take into account different precipitation regimes, PQPF performance has been evaluated over two regions: the northern part of South America, characterized by a tropical regime, and the southern part, where synoptic-scale forcing is stronger. The results support the adoption of such area separation, since differences in the precipitation regimes produce significant differences in PQPF performance. The more skillful PQPFs are the ones obtained after calibration. PQPFs derived from the ensemble mean also show higher skill and better reliability than those derived from the single ensemble members. The performance of the PQPFs derived from both ensemble systems is similar over the southern part of the region; however, over the northern part the superensemble approach seems to achieve better results in both reliability and skill. Finally, the impact of using Climate Prediction Center morphing technique (CMORPH) estimates to calibrate the precipitation forecast has been explored since the more extensive coverage of this dataset would allow its use over areas where the rain gauge coverage is insufficient. Results suggest that systematic biases present in the CMORPH estimates produce only a slight degradation of the resulting PQPF.

Objective Optimization of Weather Radar Networks for Low-Level Coverage Using a Genetic Algorithm

2012 ◽  
Vol 29 (6) ◽  
pp. 807-821 ◽  
Author(s):  
James M. Kurdzo ◽  
Robert D. Palmer
Keyword(s):  
Genetic Algorithm ◽  
Lifetime Cost ◽  
Optimization Technique ◽  
Weather Radar ◽  
The United States ◽  
Analysis Tool ◽  
Low Level ◽  
Mountainous Regions ◽  
Radar Network ◽  
Radar Networks

Abstract The current Weather Surveillance Radar-1988 Doppler (WSR-88D) radar network is approaching 20 years of age, leading researchers to begin exploring new opportunities for a next-generation network in the United States. With a vast list of requirements for a new weather radar network, research has provided various approaches to the design and fabrication of such a network. Additionally, new weather radar networks in other countries, as well as networks on smaller scales, must balance a large number of variables in order to operate in the most effective way possible. To offer network designers an objective analysis tool for such decisions, a coverage optimization technique, utilizing a genetic algorithm with a focus on low-level coverage, is presented. Optimization is achieved using a variety of variables and methods, including the use of climatology, population density, and attenuation due to average precipitation conditions. A method to account for terrain blockage in mountainous regions is also presented. Various combinations of multifrequency radar networks are explored, and results are presented in the form of a coverage-based cost–benefit analysis, with considerations for total network lifetime cost.

scholarly journals Low-Level Jets over the Mid-Atlantic States: Warm-Season Climatology and a Case Study

2006 ◽  
Vol 45 (1) ◽  
pp. 194-209 ◽  
Author(s):  
Da-Lin Zhang ◽  
Shunli Zhang ◽  
Scott J. Weaver
Keyword(s):  
Real Time ◽  
Great Plains ◽  
Thermal Gradient ◽  
Warm Season ◽  
Heat Fluxes ◽  
Time Model ◽  
Low Level ◽  
Mountainous Regions ◽  
Low Level Jets

Abstract Although considerable research has been conducted to study the characteristics of the low-level jets (LLJs) over the Great Plains states, little is known about the development of LLJs over the Mid-Atlantic states. In this study, the Mid-Atlantic LLJ and its associated characteristics during the warm seasons of 2001 and 2002 are documented with both the wind profiler data and the daily real-time model forecast products. A case study with three model sensitivity simulations is performed to gain insight into the three-dimensional structures and evolution of an LLJ and the mechanisms by which it developed. It is found that the Mid-Atlantic LLJ, ranging from 8 to 23 m s−1, appeared at an average altitude of 670 m and on 15–25 days of each month. About 90% of the 160 observed LLJ events occurred between 0000 and 0600 LST, and about 60% had southerly to westerly directions. Statistically, the real-time forecasts capture most of the LLJ events with nearly the right timing, intensity, and altitude, although individual forecasts may not correspond to those observed. For a selected southwesterly LLJ case, both the observations and the control simulation exhibit a pronounced diurnal cycle of horizontal winds in the lowest 1.5 km. The simulation shows that the Appalachian Mountains tend to produce a sloping mixed layer with northeasterly thermal winds during the daytime and reversed thermal winds after midnight. With additional thermal contrast effects associated with the Chesapeake Bay and the Atlantic Ocean, the daytime low-level winds vary significantly from the east coast to the mountainous regions. The LLJ after midnight tends to be peaked preferentially around 77.5°W near the middle portion of the sloping terrain, and it decreases eastward as a result of the opposite thermal gradient across the coastline from the mountain-generated thermal gradient. Although the Mid-Atlantic LLJ is much weaker and less extensive than that over the Great Plains states, it has a width of 300–400 km (to its half-peak value) and a length scale of more than 1500 km, following closely the orientation of the Appalachians. Sensitivity simulations show that eliminating the surface heat fluxes produces the most significant impact on the development of the LLJ, then topography and the land–sea contrast, with its area-averaged intensity reduced from 12 m s−1 to about 6, 9, and 10 m s−1, respectively.

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