North American Regional Reanalysis Research Articles

Meteorological factors contributing to the interannual variability of midsummer surface ozone in Colorado, Utah, and other western U.S. states

AbstractWe use daily maximum 8 h average surface O3 concentrations (MDA8) for July 1995–2013, meteorological variables from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis, the North American Regional Reanalysis, and output from regional chemistry‐climate simulations to assess relationships between O3 and weather in the western U.S. We also explore relationships among July O3, satellite‐derived NO2, and meteorology. A primary objective of this study is to identify an effective method for correcting the effects of meteorology on July MDA8. We find significant correlations between July MDA8 O3 and meteorological variables for sites in or near Denver, Colorado, and Salt Lake City, Utah. The highest correlations were for 500 hPa heights, surface temperatures, and 700 hPa temperatures and zonal winds. We conclude that increased 500 hPa heights lead to high July O3 in much of the western U.S., particularly in areas of elevated terrain near urban sources of NO2 and other O3 precursors. In addition to bringing warmer temperatures and fewer clouds, upper level ridges decrease winds and allow cyclic terrain‐driven circulations to reduce transport away from sources. Because of strong, nearly linear responses of July MDA8 to 500 hPa heights, it is not reasonable to use uncorrected trends in peak O3 for assessments of the effectiveness of emissions controls for much of the western U.S. Robust linear regressions for July MDA8 and tropospheric NO2 with 500 hPa heights can be used to assess and correct trends in July MDA8 in the Intermountain West.

Suitability of North American Regional Reanalysis (NARR) output for hydrologic modelling and analysis in mountainous terrain

AbstractMeteorological observations at high elevations in mountainous regions are often lacking. One opportunity to fill this data gap is through the use of downscaled output from weather reanalysis models. In this study, we tested the accuracy of downscaled output from the North American Regional Reanalysis (NARR) against high‐elevation surface observations at four ridgetop locations in the southern Coast Mountains of British Columbia, Canada. NARR model output was downscaled to the surface observation locations through three‐dimensional interpolation for air temperature, vapour pressure and wind speed and two‐dimensional interpolation for radiation variables. Accuracy was tested at both the 3‐hourly and daily time scales. Air temperature displayed a high level of agreement, especially at the daily scale, with root mean square error (RMSE) values ranging from 0.98 to 1.21 °C across all sites. Vapour pressure downscaling accuracy was also quite high (RMSE of 0.06 to 0.11 hPa) but displayed some site specific bias. Although NARR overestimated wind speed, there were moderate to strong linear relations (r2 from 0.38 to 0.84 for daily means), suggesting that the NARR output could be used as an index and bias‐corrected. NARR output reproduced the seasonal cycle for incoming short‐wave radiation, with Nash–Sutcliffe model efficiencies ranging from 0.78 to 0.87, but accuracy suffered on days with cloud cover, resulting in a positive bias and RMSE ranged from 42 to 46 Wm− 2. Although fewer data were available, incoming long‐wave radiation from NARR had an RMSE of 19 Wm− 2 and outperformed common methods for estimating incoming long‐wave radiation. NARR air temperature showed potential to assist in hydrologic analysis and modelling during an atmospheric river storm event, which are characterized by warm and wet air masses with atypical vertical temperature gradients. The incorporation of a synthetic NARR air temperature station to better represent the higher freezing levels resulted in increased predicted peak flows, which better match the observed run‐off during the event. Copyright © 2016 John Wiley & Sons, Ltd.

Estimating Daytime Planetary Boundary Layer Heights over a Valley from Rawinsonde Observations at a Nearby Airport: An Application to the Page Valley in Virginia, United States

AbstractThe planetary boundary layer (PBL) height is an essential parameter required for many applications, including weather forecasting and dispersion modeling for air quality. Estimates of PBL height are not easily available and often come from twice-daily rawinsonde observations at airports, typically at 0000 and 1200 UTC. Questions often arise regarding the applicability of PBL heights retrieved from these twice-daily observations to surrounding locations. Obtaining this information requires knowledge of the spatial variability of PBL heights. This knowledge is particularly limited in regions with mountainous terrain. The goal of this study is to develop a method for estimating daytime PBL heights in the Page Valley, located in the Blue Ridge Mountains of Virginia. The approach includes using 1) rawinsonde observations from the nearest sounding station [Dulles Airport (IAD)], which is located 90 km northeast of the Page Valley, 2) North American Regional Reanalysis (NARR) output, and 3) simulations with the Weather Research and Forecasting (WRF) Model. When selecting days on which PBL heights from NARR compare well to PBL heights determined from the IAD soundings, it is found that PBL heights are higher (on the order of 200–400 m) over the Page Valley than at IAD and that these differences are typically larger in summer than in winter. WRF simulations indicate that larger sensible heat fluxes and terrain-following characteristics of PBL height both contribute to PBL heights being higher over the Page Valley than at IAD.

A Climatology of Southern Appalachian Cold-Air Damming*

Abstract A 30-yr climatology (1981–2010) of cold-air damming (CAD) events in the southern Appalachians was conducted using hourly surface observations and North American Regional Reanalysis (NARR) data. Analysis of the spatial distribution and frequency of these events reveals that some part of the Southeast is affected by CAD on 50 days out of each year, and even the northern Florida panhandle and much of Alabama experience CAD conditions on about 30 days annually. Spatially, different CAD types tend to exhibit one of two patterns in the southernmost extent of the cold-air dome: a more southerly dome with a ridge axis oriented from north-northeast to south-southwest or a more westerly dome with a ridge axis in a northeast to west-southwest orientation. These patterns may be the result of both splitting around the region of higher terrain in east-central Alabama and Coriolis forcing in stronger CAD types with higher wind speeds. Analysis of the frequency of CAD by type on a month-by-month and year-by-year basis confirms previous work that CAD is much more frequent during the cold season versus the warm season, with CAD occurring on 6.8 days month−1 during December and only 1.3 days month−1 during July. Analysis was also stratified by CAD type, revealing that weak/dry events were the most common. Classical type events with stronger and more favorably positioned parent highs exhibited the longest average duration, nearly 45 h, while other CAD types averaged approximately half as long.

Climatology, Synoptic Conditions, and Misanalyses of Mississippi River Valley Drylines

Abstract The dryline is an important focal point for convection initiation. Although drylines most commonly occur on the southern Great Plains, dryline passages and subsequent severe weather outbreaks have been documented in the Mississippi River valley. This study presents a 15-yr (1999–2013) climatology of these Mississippi River valley drylines and associated severe weather. Additionally, synoptic patterns are identified that may result in drylines moving atypically far eastward into the Mississippi River valley. In total, 39 Mississippi River valley drylines (hereafter referred to as MRV drylines) were identified from the North American Regional Reanalysis (NARR) dataset through the study period. Mean and anomaly synoptic composites were created for these drylines. MRV dryline events typically occur under synoptically active conditions with an amplified upper-air pattern, a 500-hPa shortwave trough to the west or northwest of the dryline, and a strong surface cyclone to the north. These boundaries are often misanalyzed or inconsistently analyzed as cold fronts, stationary fronts, or trough axes on surface maps; of the 33 cases of identified MRV drylines for which the Weather Prediction Center archived analyses were available, only 6 were correctly analyzed as drylines. Drylines moving into the Mississippi River valley often result in severe weather outbreaks in the Mississippi River valley, the Midwest, and the southeastern United States.

Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

The weather research and forecast (WRF) model downscaling skill in extreme maximum daily temperature is evaluated by using the generalized extreme value (GEV) distribution. While the GEV distribution has been used extensively in climatology and meteorology for estimating probabilities of extreme events, accurately estimating GEV parameters based on data from a single pixel can be difficult, even with fairly long data records. This work proposes a simple method assuming that the shape parameter, the most difficult of the three parameters to estimate, does not vary over a relatively large region. This approach is applied to evaluate 31-year WRF-downscaled extreme maximum temperature through comparison with North American regional reanalysis (NARR) data. Uncertainty in GEV parameter estimates and the statistical significance in the differences of estimates between WRF and NARR are accounted for by conducting a novel bootstrap procedure that makes no assumption of temporal or spatial independence within a year, which is especially important for climate data. Despite certain biases over parts of the United States, overall, WRF shows good agreement with NARR in the spatial pattern and magnitudes of GEV parameter estimates. Both WRF and NARR show a significant increase in extreme maximum temperature over the southern Great Plains and southeastern United States in January and over the western United States in July. The GEV model shows clear benefits from the regionally constant shape parameter assumption, for example, leading to estimates of the location and scale parameters of the model that show coherent spatial patterns.

Land–Atmosphere Coupling at the Southern Great Plains Atmospheric Radiation Measurement (ARM) Field Site and Its Role in Anomalous Afternoon Peak Precipitation

Abstract The multimodel Global Land–Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land–atmosphere (LA) coupling and, consequently, land-derived temperature and precipitation predictability. The area including and surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied in the context of LA coupling. Observation-based studies suggest a coupling signal that is much weaker than modeled, if not elusive. Using North American Regional Reanalysis and North American Land Data Assimilation System data, this study provides a 36-yr (1979–2014) climatology of coupling for ARM-SGP that 1) unifies prior interdisciplinary efforts and 2) isolates the origin of the (weak) coupling signal. Specifically, the climatology of a prominent convective triggering potential–low-level humidity index (CTP–HIlow) coupling classification is linked to corresponding synoptic–mesoscale weather and atmospheric moisture budget analyses. The CTP–HIlow classification defines a dry-advantage regime for which convective triggering is preferentially favored over drier-than-average soils as well as a wet-advantage regime for which convective triggering is preferentially favored over wetter-than-average soils. This study shows that wet-advantage days are a result of horizontal moisture flux convergence over the region, and conversely, dry-advantage days are a result of zonal and vertical moisture flux divergence. In this context, the role of the land is nominal relative to that of atmospheric forcing. Surface flux partitioning, however, can play an important role in modulating diurnal precipitation cycle phase and amplitude and it is shown that soil moisture and sensible heat flux are significantly correlated with both occurrence and intensity of afternoon peak precipitation.

A Regional Land Use Drought Index for Florida

Drought index is a useful tool to assess and respond to drought. However, current drought indices could not fully reveal land use effects and they have limitations in applications. Besides, El Niño Southern Oscillation (ENSO), strongly influences the climate of Florida. Hence, understanding ENSO patterns on a regional scale and developing a new land use drought index suitable for Florida are critical in agriculture and water resources planning and management. This paper presents a 32 km high resolution land use adapted drought index, which relies on five types of land uses (lake, urban, forest, wetland, and agriculture) in Florida. The land uses were obtained from National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data from 1979 to 2002. The results showed that Bowen ratio responded to land use and could be used as an indicator to monitor drought events. Then, an innovative regional land use drought index was developed from the normalized Bowen ratio, which could reflect not only the level of severity during drought events resulting from land use effects, but also La Niña driven drought impacts. The proposed new index may help scientists answer the critical questions about drought effect on various land uses and potential feedbacks of changes in land use and land cover to climate.

An Observational, Spatially Explicit, Stability-Based Estimate of the Wind Resource off the Shore of North Carolina

AbstractAs part of ongoing studies of the feasibility of utility-scale wind energy off the shore of North Carolina, winds at 80-m elevation are estimated with a stability-based height-adjustment scheme. Data sources are level-3 daily Advanced Scatterometer (ASCAT) 10-m wind fields as measured by the MetOp-A satellite, North American Regional Reanalysis (NARR) estimates of near-surface atmospheric temperature and humidity, and the National Climatic Data Center’s optimally interpolated Advanced Very High Resolution Radiometer (AVHRR-OI) sea surface temperature (SST). A height-adjustment assuming neutral atmospheric stability provides reference conditions. The SST from AVHRR-OI was more accurate than SST from NARR and was used with NARR atmospheric data to represent atmospheric stability in the study region. The 5-yr average of the ASCAT 10-m winds is 6.5–9.0 m s−1 off the shore of North Carolina, with the strongest winds found over the Gulf Stream. Neutral-scheme 80-m wind speeds are 7.5–10.5 m s−1 and follow the same spatial pattern. The stability-based scheme produces an 80-m wind field with significantly different spatial wind patterns, with greater wind speeds than the neutral scheme in coastal regions where stable atmosphere conditions occur and lesser wind speeds than the neutral scheme farther offshore where unstable conditions are prevalent. The largest differences between the schemes occur in winter and spring when and where stable atmospheric conditions are most common. Estimated power inshore from the 100-m isobath with the neutral scheme yields average values of 400–800 W m−2, whereas the stability-based-scheme values are 600–800 W m−2. Capacity factors vary between 30% and 55%, with values in excess of 40% common in coastal areas off North Carolina.

Complementary‐relationship‐based 30 year normals (1981–2010) of monthly latent heat fluxes across the contiguous United States

AbstractThirty year normal (1981–2010) monthly latent heat fluxes (ET) over the conterminous United States were estimated by a modified Advection‐Aridity model from North American Regional Reanalysis (NARR) radiation and wind as well as Parameter‐Elevation Regressions on Independent Slopes Model (PRISM) air and dew‐point temperature data. Mean annual ET values were calibrated with PRISM precipitation (P) and validated against United States Geological Survey runoff (Q) data. At the six‐digit Hydrologic Unit Code level (sample size of 334) the estimated 30 year normal runoff (P – ET) had a bias of 18 mm yr−1, a root‐mean‐square error of 96 mm yr−1, and a linear correlation coefficient value of 0.95, making the estimates on par with the latest Land Surface Model results but without the need for soil and vegetation information or any soil moisture budgeting.

Observational investigation of relationships between moisture surges and mesoscale‐ to large‐scale convection during the North American monsoon

ABSTRACTThis article consists of a comprehensive climatological study of moisture surges (MSs) in the North American monsoon (NAM) core region using a multiyear (1990–2006) set of surges, surface and upper air data, satellite‐estimated mesoscale convective systems (MCSs), and North American Regional Reanalysis (NARR) products. Composites of surges are created with respect to MCSs occurrence in the NAM core region. MSs are further stratified based on co‐occurrence with tropical easterly waves and tropical storms/tropical cyclones. These results provide new insights into the nature of the Gulf of California (GoC) moisture flux variability and describe the influence of these multi‐scale processes on the occurrence and intensity of surges and the GoC diurnal circulations – especially the Gulf of California low‐level jet (GCLLJ). Results show that over the GoC Coastal Plain, MCSs modulate the diurnal cycle of the GoC low‐level circulation during ‘major surge’, ‘minor surge’, and ‘non‐surge’ environments. We found that MCS activity enhances the offshore flow along the eastern GoC coast, which then enhances the GCLLJ. On the other hand, immediately before major surges onset, the occurrence of MCSs over the southern GoC produces more intense surges. It is also shown that this relationship holds regardless of the intensity and type of tropical synoptic‐scale disturbance forcing the surge.

The Heated Condensation Framework. Part II: Climatological Behavior of Convective Initiation and Land–Atmosphere Coupling over the Conterminous United States

Abstract This is Part II of a two-part study introducing the heated condensation framework (HCF), which quantifies the potential convective state of the atmosphere in terms of land–atmosphere interactions. Part I introduced the full suite of HCF variables and applied them to case studies with observations and models over a single location in the southern Great Plains. It was shown in Part I that the HCF was capable of identifying locally initiated convection and quantifying energetically favorable pathways for initiation. Here, the HCF is applied to the entire conterminous United States and the climatology of convective initiation (CI) in relation to local land–atmosphere coupling (LoCo) is explored for 34 summers (June–August) using the North American Regional Reanalysis (NARR) and observations. NARR is found to be capable of capturing the convective threshold (buoyant mixing potential temperature θBM) and energy advantage transition (energy advantage potential temperature θadv) for most of the United States. However, there are compensating biases in the components of moisture qmix and temperature q*, resulting in low θBM biases for the wrong reason. The HCF has been used to show that local CI occurred over the Rocky Mountains and the southern Great Plains 35%–65% of the time. Finally, the LoCo process chain has been recast in light of the HCF. Both positive and negative soil moisture–convective feedbacks are possible, with negative feedbacks producing a stronger response in CI likelihood under weak convective inhibition. Positive feedbacks are present but weaker.

Estimation of Daily Surface Shortwave Net Radiation From the Combined MODIS Data

Surface shortwave net radiation (SSNR) is a key component of the surface radiation budget. In this paper, we refined a direct estimation approach to retrieve daily SSNR estimates from combined Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data. The retrieved MODIS SSNR estimates were validated against measurements at seven stations of the Surface Radiation Budget Network. We also compared the MODIS retrievals with three existing SSNR products: the Clouds and the Earth's Radiant Energy System (CERES) products, the North American Regional Reanalysis (NARR) data, and the ERA-Interim reanalysis data from the European Centre for Medium-Range Weather Forecasts. MODIS data at 1 km were upscaled to mitigate the mismatch between site measurements and satellite retrievals. Among the four data sets, the aggregated MODIS retrievals agreed best with in situ measurements, with a root-mean-square error (rmse) of 23.1 W/m2 and a negative bias of 6.7 W/m2. The CERES products have a slightly larger rmse of 24.2 W/m2 and a positive bias of 7.6 W/m2. Both reanalysis data (NARR and ERA-Interim) overestimate daily SSNR and have much larger uncertainties. Monthly satellite SSNR data are more accurate than daily values, and the scaling issue in validating monthly MODIS SSNR retrievals is also less prominent. Averaged with a window size of 23 km, the two MODIS sensors can estimate monthly SSNR with an rmse error of 11.6 W/m 2, representing an improvement of 2.4 W/m2 over the CERES products.

The Heated Condensation Framework. Part I: Description and Southern Great Plains Case Study

Abstract This study extends the heated condensation framework (HCF) presented in Tawfik and Dirmeyer to include variables for describing the convective background state of the atmosphere used to quantify the contribution of the atmosphere to convective initiation within the context of land–atmosphere coupling. In particular, the ability for the full suite of HCF variables to 1) quantify the amount of latent and sensible heat energy necessary for convective initiation, 2) identify the transition from moistening advantage to boundary layer growth advantage, 3) identify locally originating convection, and 4) compare models and observations, directly highlighting biases in the convective state, is demonstrated. These capabilities are illustrated for a clear-sky and convectively active day over the Atmospheric Radiation Measurement Program Southern Great Plains central station using observations, the Rapid Update Cycle (RUC) operational model, and the North American Regional Reanalysis (NARR). The clear-sky day had a higher and unattainable convective threshold, making convective initiation unlikely. The convectively active day had a lower threshold that was attained by midafternoon, reflecting local convective triggering. Compared to observations, RUC tended to have the most difficulty representing the convective state and captured the threshold for the clear-sky case only because of compensating biases in the moisture and temperature profiles. Despite capturing the observed moisture profile very well, a stronger surface inversion in NARR returned overestimates in the convective threshold. The companion paper applies the HCF variables introduced here across the continental United States to examine the climatological behavior of convective initiation and local land–atmosphere coupling.

Systematic assessment of atmospheric uncertainties for InSAR data at volcanic arcs using large-scale atmospheric models: Application to the Cascade volcanoes, United States

Satellite Radar Interferometry (InSAR) is suited to monitoring ground deformation on the scale of volcanic arcs, providing insight into the eruptive cycle over both long and short time periods. However, these measurements are often contaminated with atmospheric artefacts caused by changes in the refractivity of the atmosphere. Here, we test the use of two large-scale atmospheric models, ERA-Interim (ERA-I) and North American Regional Reanalysis (NARR), to correct atmospheric uncertainties in InSAR data from the Cascades Volcanic Arc, United States. At Lassen Volcanic Center, we find that NARR reduces interferogram standard deviation in 79 % of cases by an average of 22 %. Using NARR, we develop a strategy to produce a priori estimates of atmospheric uncertainties on an arc-wide basis. We show that in the Cascades, the RMS variation in range change is dependent upon volcano topography and increases by 0.7 cm per kilometre of relief. We use this to estimate detection thresholds for long-term monitoring of small magnitude (1 cm/year) deformation signals, and short-term monitoring of ground deformation associated with pre-eruptive unrest. This new approach of assessing atmospheric uncertainties a priori is widely applicable to other volcanic arcs, and provides realistic estimates of atmospheric uncertainties suitable for use in near-real-time analysis of InSAR data during periods of volcanic unrest.

Canadian icing envelopes near the surface and its impact on wind energy assessment

The present study aims at producing localized near-surface icing envelopes that contribute to optimal designs of near-surface structures under icing conditions. For this purpose, the 99th percentiles of liquid water content and wind speed that correspond to low-level supercooled clouds are used. Near-surface icing events and cloud microphysics are explored using North American Regional Reanalysis during winter months (D–J–F), over 32years. The investigation of the regional climatology of icing events involves 74 regional zones that cover Canada. For each zone, regional power loss of wind turbines under icing condition is estimated. The East and West coastal regions of the Hudson Bay demonstrate higher liquid cloud water of 0.4gm−3. The highest potential of wind is located in the West coast. The climatology of liquid water content around the Rocky Mountains manifests orographic condensation of the Pacific moisture transported toward the mountains. Within the range of temperatures [−15°C to 0°C], the near-surface results over Canada show that the monthly mean of wind speeds varies mostly between 4ms−1 and 10ms−1, and the mean supercooled cloud water content decreases linearly from 0.3gm−3 to 0.2gm−3, with decreasing temperature. The quantification of ice accumulation and the duration of icing events reveal that the West and the South of the Hudson Bay as well as the North of Manitoba and Ontario are exposed to extreme icing conditions, with a monthly accumulation that varies from 150mm to 225mm, and a monthly duration of icing events near 375h. Over the region encompassing the Gaspe Peninsula, St. Lawrence River and New Brunswick the higher limit of wind speed varies around 15ms−1. The cloud water upper limit of 0.45gm−3 occurs in December and January, and 0.3gm−3 in February. With decreasing temperature these upper limits reach 0.1gm−3 at −15°C. The highest wind energy is located in the Canadian East Coast regions. The Canadian arctic is characterized mostly by lower wind energy and larger power degradation under icing conditions. The average of wind turbine power loss during winter months (D–J–F) under icing conditions varies throughout Canada and reaches its maximum of about 15% over North-East of Manitoba, South of the Hudson Bay and the North coast of Ontario.

Assessment of NARCCAP model in simulating rainfall extremes using a spatially constrained regionalization method

ABSTRACTCapturing the intensity and return period of extreme rainfall events in the historic record and projecting them into the future are essential to managing, planning, and designing infrastructure. In this study, we assess the performance of the combination of four General Circulation Models (GCMs) and six Regional Climate Models (RCMs) that comprise the North American Regional Climate Change Assessment Program (NARCCAP) and evaluate their performance in simulating rainfall extremes in the continental United States. We adopt a regionalization method to objectively delineate 12 regions in the continental United States with relatively homogenous annual maximum 24‐h rainfall patterns from the North American Regional Reanalysis (NARR) data set. We then compare the Intensity–Duration–Frequency (IDF) curves generated from control simulations of NARCCAP models with those from NARR in each of these regions. We find significant spatial variability of model performance. The models perform reasonably well in many parts of the country, but poorly in the southeastern United States. The GCM providing boundary conditions strongly influences results – output from those RCMs driven by the Community Climate System Model (CCSM) and Canadian Global Climate Model version 3 (CGCM3) matched the NARR data best. Performance of individual RCMs also varied, often in response to nudging, wherein the regional model is constrained by the GCM fields. We also measure changes in bias‐corrected IDF curves generated from NARCCAP projections of the future. In most regions, most models project intensified 24‐h rainfall events in the future (exceptions include some model‐projected decreases in southern California, the extreme north‐central US, Florida, and the Texas Plains). This study provides a valuable means of assessing NARCCAP models' performance in simulating rainfall extremes at the regional scale and understanding how the GCMs, RCMs, and spatial variability affect model performance.

Tropical cyclones in the North American Regional Reanalysis: The impact of satellite‐derived precipitation over ocean

AbstractContinued advancement in the realm of tropical cyclone (TC) forecasting requires a more accurate depiction of these storms at model initialization. This study examines the impact of precipitation assimilation on the representation of TCs in the North American Regional Reanalysis before and after the 2004 introduction of precipitation assimilation over ocean in the vicinity of TCs. The probability distribution function of rainfall rates indicates that light (heavy) precipitation was overforecast (underforecast) in the early time period. Since the precipitation assimilation is applied through an adjustment to the latent heating distribution, the data assimilation system in the later time period initializes a low‐level moisture and heating profile that is more conducive to the initiation of deep convection and the generation of precipitation. Consequently, the deep convection and enhanced latent heat release lead to a more robust warm‐core temperature perturbation and a better developed secondary circulation, which supplies the TC with larger quantities of moisture from the large‐scale environment. Furthermore, the evolution of TC size, which was objectively estimated though the radius of outermost closed isobar, is significantly more skillful (p < 0.05) in post‐2003 storms. Based on this study, precipitation assimilation leads to a better analysis of temperature, winds, and moisture in the vicinity of TCs, resulting in improved representations of the water budget and storm life cycle. Therefore, we conclude that efforts toward the development of precipitation assimilation techniques from radar and satellite data sets will be valuable toward the construction of improved TC forecasting tools with more authentic TC representation.

The Low-Level Jet over the Southern Great Plains Determined from Observations and Reanalyses and Its Impact on Moisture Transport

Abstract This study utilizes six commonly used reanalysis products, including the NCEP–Department of Energy Reanalysis 2 (NCEP2), NCEP Climate Forecast System Reanalysis (CFSR), ECMWF interim reanalysis (ERA-Interim), Japanese 25-year Reanalysis Project (JRA-25), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and North American Regional Reanalysis (NARR), to evaluate features of the southern Great Plains low-level jet (LLJ) above the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) Southern Great Plains site. Two sets of radiosonde data are utilized: the six-week Midlatitude Continental Convective Clouds Experiment (MC3E) and a 10-yr period spanning 2001 through 2010. All six reanalyses are compared to MC3E data, while only the NARR, MERRA, and CFSR are compared to the 10-yr data. The reanalyses are able to represent most aspects of the composite LLJ profile, although there is a tendency for each reanalysis to overestimate the wind speed between the nose of the LLJ (at approximately 900 mb) and a pressure level of 700 mb. There are large discrepancies in the number of LLJs observed and derived from the reanalysis, particularly for strong LLJs, leading to an underestimate of the moisture transport associated with LLJs. When the 10-yr period is considered, the NARR and CFSR overestimate and MERRA underestimates the total moisture transport, but all three underestimate the transport associated with strong LLJs by factors of 1.4, 2.0, and 2.7 for CFSR, NARR, and MERRA, respectively. During MC3E there were differences in the patterns of moisture convergence and divergence, but the patterns are more consistent during the 10-yr period.

The Impacts of Wind Speed Trends and 30-Year Variability in Relation to Hydroelectric Reservoir Inflows on Wind Power in the Pacific Northwest.

In hydroelectric dominated systems, the value and benefits of energy are higher during extended dry periods and lower during extended or extreme wet periods. By accounting for regional and temporal differences in the relationship between wind speed and reservoir inflow behavior during wind farm site selection, the benefits of energy diversification can be maximized. The goal of this work was to help maximize the value of wind power by quantifying the long-term (30-year) relationships between wind speed and streamflow behavior, using British Columbia (BC) and the Pacific Northwest (PNW) as a case study. Clean energy and self-sufficiency policies in British BC make the benefits of increased generation during low streamflow periods particularly large. Wind density (WD) estimates from a height of 10m (North American Regional Reanalysis, NARR) were correlated with cumulative usable inflows (CUI) for BC (collected from BC Hydro) for 1979–2010. The strongest WD-CUI correlations were found along the US coast (r ~0.55), whereas generally weaker correlations were found in northern regions, with negative correlations (r ~ -0.25) along BC’s North Coast. Furthermore, during the lowest inflow years, WD anomalies increased by up to 40% above average values for the North Coast. Seasonally, high flows during the spring freshet were coincident with widespread negative WD anomalies, with a similar but opposite pattern for low inflow winter months. These poorly or negatively correlated sites could have a moderating influence on climate related variability in provincial electricity supply, by producing greater than average generation in low inflow years and reduced generation in wet years. Wind speed and WD trends were also analyzed for all NARR grid locations, which showed statistically significant positive trends for most of the PNW and the largest increases along the Pacific Coast.