North American Regional Reanalysis Research Articles

Hydroclimatological impact of century‐long drainage in midwestern United States: CCSM sensitivity experiments

Community Climate System Model (CCSM3) sensitivity experiments are performed to investigate the impact of past wetland drainage on the hydroclimatology of midwestern United States (MW USA). Coupled land surface and atmospheric components of CCSM3 are used at T85 (∼140 km) horizontal grid mesh size to create four control model experiments. These include: (1) 355 ppm CO2 for year 1990 excluding wetland (present condition), (2) 355 ppm CO2 for 1990 including wetland, (3) 289 ppm CO2 for year 1870 excluding wetland, and (4) 289 ppm CO2 for year 1870 including wetland. The CCSM3 control run for the present condition is validated with high‐resolution North American Regional Reanalysis (NARR) data for the Midwest region. Validation results show that CCSM3 is reasonable in simulating at‐surface incoming solar radiation, net short‐wave radiation, and 2 m air temperature. However, partitioning of net radiation into sensible and latent heat fluxes is imprecise, and summer precipitation is largely underestimated in CCSM3. To remove any biases in CCSM3 output, results from sensitivity experiments are analyzed in terms of difference in monthly climatology. Sensitivity experiment results show significant changes in summer sensible and latent heat fluxes due to wetland drainage. Near‐surface (2 m) air temperature has significantly increased, and convective precipitation has decreased by a small amount (∼50 mm) during the summer. Except for 2 m air temperature which is affected by both greenhouse gas emission–based climate change and wetland drainage over the last century, all other climatic variables are primarily affected by wetland drainage in the region.

On the Dependence of Winter Precipitation Types on Temperature, Precipitation Rate, and Associated Features

Abstract The phase of precipitation formed within the atmosphere is highly dependent on the vertical temperature profile through which it falls. In particular, several precipitation types can form in an environment with a melting layer aloft and a refreezing layer below. These precipitation types include freezing rain, ice pellets, wet snow, and slush. To examine the formation of such precipitation, a bulk microphysics scheme was used to compare the characteristics of the hydrometeors produced by the model and observed by a research aircraft flight during the 1998 ice storm near Montreal, Canada. The model reproduced several of the observed key precipitation characteristics. Sensitivity tests on the precipitation types formed during the ice storm were also performed. These tests utilized temperature profiles produced by the North American Regional Reanalysis. The results show that small variations (±0.5°C) in the temperature profiles as well as in the precipitation rate can have major impacts on the types of precipitation formed at the surface. These results impose strong requirements on the accuracy needed by prediction models.

Hydroclimate and variability in the Great Lakes region as derived from the North American Regional Reanalysis

We investigated the seasonal and interannual variability of the moisture budget in the Great Lakes region of the United States using the North American Regional Reanalysis (NARR) data set from 1979 through 2007. The much higher spatial and temporal resolution and improved precipitation and land surface data assimilation of the NARR data set compared with its global counterparts enable more accurate depictions of the moisture budget and hydrological cycle in the Great Lakes region. The analyses reveal that in the past three decades except for two drought years, the evaporation over the region is insufficient to account for the total precipitation. Transport mechanisms supply additional moisture, with a net gain in moisture associated with meridional transport by southerly winds overcoming a net loss in moisture due to zonal transport by westerly winds. The interannual variability of the moisture deficit (the difference between evaporation and precipitation) is associated mainly with the interannual variability in the moisture flux convergence. These results highlight the critical importance of remote moisture sources and large‐scale moisture transport to the hydrological cycle in the Great Lakes region. The trend analyses show an upward trend for evaporation that is consistent with warming over the region in all seasons during the NARR data period. Precipitation exhibits an increasing trend in spring and winter, with the largest increase in winter, but no clear trends in summer and autumn.

Concurrent variations of water vapor and temperature corresponding to the interannual variation of precipitation in the North American Regional Reanalysis

The concurrent variation patterns of water vapor and temperature corresponding to the interannual variation of winter precipitation and the roles of change in atmospheric circulation are studied with the North American Regional Reanalysis. A very tight positive relationship between precipitation and relative humidity at interannual time scale is found from the large spatially sampled data set. On the basis of this relationship, the concurrent variations of water vapor and temperature between the wettest and the driest years are categorized into three patterns. The distribution of the patterns shows that more winter precipitation of wetter years corresponds to more water vapor but not lower temperature (moistening pattern) in high latitudes, lower temperature but not more water vapor (cooling pattern) in midlatitudes, and both more water vapor and lower temperature (moistening‐cooling pattern) in low latitudes. The characteristics and roles of change in atmospheric circulation from the driest years to the wettest years are analyzed for two selected areas. It is found that, around the selected cooling pattern (moistening pattern) area, the field of wind difference between the wettest years and the driest years is divergent (convergent). Dominated by this, the fields of differences in both heat flux and water vapor flux are divergent (convergent). This leads to the decreases (increases) of the heating and moistening rates and, thus, the characteristics of the cooling pattern (moistening pattern) area with cooling and drying (warming and moistening) from the driest years to the wettest years. This study suggests that, for interannual prediction of precipitation, temperature, in addition to water vapor, should also be considered.

Evolution of Mesoscale Precipitation Band Environments within the Comma Head of Northeast U.S. Cyclones

Abstract This paper explores the mesoscale forcing and stability evolution of intense precipitation bands in the comma head sector of extratropical cyclones using the 32-km North American Regional Reanalysis, hourly 20-km Rapid Update Cycle analyses, and 2-km composite radar reflectivity data. A statistical and composite analysis of 36 banded events occurring during the 2002–08 cool seasons reveals a common cyclone evolution and associated band life cycle. A majority (61%) of banded events develop along the northern portion of a hook-shaped upper-level potential vorticity (PV) anomaly. During the 6 h leading up to band formation, lower-tropospheric frontogenesis nearly doubles and the conditional stability above the frontal zone is reduced. The frontogenesis increase is primarily due to changes in the kinematic flow associated with the development of a mesoscale geopotential height trough. This trough extends poleward of the 700-hPa low, and is the vertical extension of the surface warm front (and surface warm occlusion when present). The conditional stability near 500 hPa is reduced by differential horizontal potential temperature advection. During band formation, layers of conditional instability above the frontal zone are present nearly 3 times as often as layers of conditional symmetric instability. The frontogenetical forcing peaks during band maturity and is offset by an increase in conditional stability. Band dissipation occurs as the conditional stability continues to increase, and the frontogenesis weakens in response to changes in the kinematic flow. A set of 22 null events, in which band formation was absent in the comma head, were also examined. Although exhibiting similar synoptic patterns as the banded events, the null events were characterized by weaker frontogenesis. However, statistically significant differences between the midlevel frontogenesis maximum of the banded and null events only appear ~2 h prior to band formation, illustrating the challenge of predicting band formation.

Downscaling and Bias Correcting a Cold Season Precipitation Climatology over Coastal Southern British Columbia Using the Regional Atmospheric Modeling System (RAMS)

Abstract Thirty years of the North American Regional Reanalysis (NARR) are dynamically downscaled to an 8-km grid spacing using the Regional Atmospheric Modeling System (RAMS) to generate a climatology of glacier winter accumulation over the southern Coast Mountains in British Columbia (BC), Canada. RAMS precipitation fields are bias corrected using observations from Environment Canada (EC) synoptic and climate stations and BC provincial snow pillow stations. Raw and bias-corrected model output is compared with observations from EC Reference Climate Network stations, BC provincial Ministry of Transportation and Highways stations, BC Hydro stations, snow course data, and glacier mass balance studies. A water balance is also applied to 12 drainage basins located within the modeling domain to test the consistency of both the raw and bias-corrected precipitation fields with observed streamflow. Model output is compared with the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) and bias-corrected NARR. Isotropic spectral power densities are examined to compare the effective spatial resolution of the various precipitation fields. The spatial distribution of the bias-correction field suggests that RAMS underpredicts precipitation on the western edge of Vancouver Island, Canada, and overpredicts along the southern Coast Mountains. The bias correction helps close the water balance budgets in all basins except the Somass on Vancouver Island. The bias correction generally improves the agreement between RAMS and observed snow water equivalent amounts at the glacier and snow course sites, and observed precipitation amounts at the synoptic, climate, and snow pillow stations. The RAMS and NARR isotropic spectral power densities show a loss of variability at approximately 45 and 63 km, while PRISM shows little falloff down to 16 km.

Surface temperature spatial and temporal variations in North America from homogenized satellite SMMR‐SSM/I microwave measurements and reanalysis for 1979–2008

We have developed procedures for deriving land surface temperature and homogenizing 30 years of daily microwave brightness temperatures from the NOAA/NASA Nimbus 7 scanning multichannel microwave radiometer (SMMR) and Defense Meteorological Satellite Program Special Sensor Microwave/Imager (DMSP SSM/I) Pathfinder EASE‐Grid database. Processing includes normalization of variable acquisition overpass time, removing the effects of changing satellite orbits, intercalibration of sensors, and filling gaps between missing data. The derived new database over North America (above 45°N), limited to snow‐free periods, provides the first estimate of the trends of consistent mean daily summer land surface temperature over the last three decades. By comparison with near‐surface air temperatures derived from the European Centre for Medium‐Range Weather Forecasts 40 year Reanalysis (ERA‐40), the National Centers for Environmental Prediction North American Regional Reanalysis (NARR), and the exhaustive ground‐based meteorological measurements across Canada, we highlighted significant systematic biases in the satellite‐derived surface temperatures for the 1983–1991 period, spanning from the second half of Nimbus 7 SMMR lifetime (1983–1987; mean bias of −0.87°C compared to ERA‐40) and the entire period of DMSP‐F8 SSM/I lifetime (1987–1991; mean bias of −1.56°C compared to ERA‐40). The biased data were corrected with use of a relative offset derived from ERA‐40 and DMSP‐F11/F13 mean difference over the 1992–2002 period. The comparison of corrected data from the 9 day overlap between SMMR and DMSP‐F8 SSM/I and from ground‐based meteorological measurements over the 1983–1991 biased period shows the usefulness of the correction method. The mean difference between corrected satellite‐derived surface temperature and in situ meteorological air temperature is +0.05°C ± 1.85°C for the entire period (1979–2008). The NARR data appear, in general, to be too warm by about 1°C. The satellite‐derived homogenized database gives new observational evidence for global warming over North American regions (mean summer temperature trend of +0.018°C/a throughout the studied period) with regional variable trends, in agreement with reanalysis and in situ measurement trends. However, over the Canadian Arctic tundra, the increase in observed land surface temperatures appears slightly less than the estimates based on near‐surface air temperature.

Long-Term Regional Estimates of Evapotranspiration for Mexico Based on Downscaled ISCCP Data

Abstract The development and evaluation of a long-term high-resolution dataset of potential and actual evapotranspiration for Mexico based on remote sensing data are described. Evapotranspiration is calculated using a modified version of the Penman–Monteith algorithm, with input radiation and meteorological data from the International Satellite Cloud Climatology Project (ISCCP) and vegetation distribution derived from Advanced Very High Resolution Radiometer (AVHRR) products. The ISCCP data are downscaled to ⅛° resolution using statistical relationships with data from the North American Regional Reanalysis (NARR). The final product is available at ⅛°, daily, for 1984–2006 for all Mexico. Comparisons are made with the NARR offline land surface model and measurements from approximately 1800 pan stations. The remote sensing estimate follows well the seasonal cycle and spatial pattern of the comparison datasets, with a peak in late summer at the height of the North American monsoon and highest values in low-lying and coastal regions. The spatial average over Mexico is biased low by about 0.3 mm day−1, with a monthly rmse of about 0.5 mm day−1. The underestimation may be related to the lack of a model for canopy evaporation, which is estimated to be up to 30% of total evapotranspiration. Uncertainties in both the remote sensing–based estimates (because of input data uncertainties) and the true value of evapotranspiration (represented by the spread in the comparison datasets) are up to 0.5 and 1.2 mm day−1, respectively. This study is a first step in quantifying the long-term variation in global land evapotranspiration from remote sensing data.

National Centers for Environmental Prediction – National Center for Atmospheric Research (NCEP–NCAR) reanalyses data for hydrologic modelling on a basin scale

This paper evaluates the National Centers for Environmental Prediction – National Center for Atmospheric Research (NCEP–NCAR) reanalyses hydroclimatic data as an initial check for assessment of hydrologic impacts of climate change at the basin scale. A reanalysis dataset for daily precipitation, maximum temperature, and minimum temperature from the NCEP–NCAR global (NNGR) and regional (North American Regional Reanalysis or NARR) reanalysis project has been used as input into the semidistributed hydrologic model (Hydrologic Engineering Center Hydraulic Modeling System or HEC–HMS) for the period 1980–2005. An extensive analysis has been performed for assessing the performance of the reanalysis data generated flows compared with the observed inputs during May–November. The stream flows generated from the NARR dataset show encouraging results in simulating summertime low flows with less variability and fewer errors. The results indicate that NNGR results are less accurate and highly variable. This study suggests that NARR can be adequately used as an alternative in data-scarce regions.

A Seven-Year Wind Profiler–Based Climatology of the Windward Barrier Jet along California’s Northern Sierra Nevada

Abstract This wind profiler–based study highlights key characteristics of the barrier jet along the windward slope of California’s Sierra Nevada. Between 2000 and 2007 roughly 10% of 100 000 hourly wind profiles, recorded at two sites, satisfied the sierra barrier jet (SBJ) threshold criteria described in the text. The mean magnitude of the terrain-parallel flow in the SBJ core (i.e., Vmax) was similar at both sites (∼17.5 m s−1) and at a comparable altitude, 500–1000 m above the surface. The cross-mountain wind speed was weak at the altitude of Vmax, consistent with blocked conditions. The seasonal cycle of SBJ occurrences showed a maximum during the cooler months and a minimum in summer. Additionally, the SBJ was stronger in winter than in summer. Because the warm-season (May–September) SBJs were different than their cool-season (October–April) counterparts and occurred during California’s dry season, they were not discussed in detail. An inventory of ∼250 cool-season SBJ cases from the two sites was generated (a case contains ≥8 consecutive SBJ profiles). Up to 60% of the nearby cool-season precipitation fell during SBJ cases, and these cases shifted the precipitation down the sierra’s windward slope and enhanced precipitation at the north end of the Central Valley (relative to non-SBJ conditions). The large number of cool-season SBJ cases was stratified by the mean strength and altitude of Vmax and by the case duration. Composite profiles of the along-barrier component for the top- and bottom-20 ranked cases in each of these three SBJ classes reveal stark differences in the magnitude and vertical positioning of the barrier jet. The three SBJ classes yielded uniquely different local precipitation characteristics in proximity to the wind profilers, with the strongest and longest-lived SBJs yielding the greatest precipitation. North American Regional Reanalysis plan-view composites were generated to explore the synoptic conditions responsible for, and to showcase the precipitation distributions associated with, the top- and bottom-20 ranked cases in each of the three classes of SBJs. The composite analyses yielded large contrasts between the SBJ classes that could prove useful in forecasting SBJs and their precipitation impacts. All SBJ classes occurred, on average, in the pre-cold-frontal environment of landfalling winter storms.

The Synergistic Relationship between Soil Moisture and the Low-Level Jet and Its Role on the Prestorm Environment in the Southern Great Plains

Abstract Changes in low-level moisture alter the convective parameters [e.g., convective available potential energy (CAPE), lifted index (LI), and convective inhibition (CIN)] as a result of alterations in the latent and sensible heat energy exchange. Two sources for low-level moisture exist in the southern Great Plains: 1) moisture advection by the low-level jet (LLJ) from the Gulf of Mexico and 2) evaporation and transpiration from the soils and vegetation in the region. The primary focus of this study is to examine the spatial distribution of soil moisture on a daily basis and to determine the effect it has on the convective parameters. The secondary objective is to investigate how the relationship between soil moisture and convective parameters is altered by the presence of an LLJ. The soil moisture data were obtained through newly developed procedures and advances in technology aboard the Tropical Rainfall Measuring Mission Microwave Imager. The convective parameter data were obtained through the North American Regional Reanalysis dataset. The study examined seven warm seasons (April–September) from 1998 to 2004 and found that the convective environment is more unstable (CAPE > 900 J kg−1, LI < −2°C) but more strongly capped (CIN > 70 J kg−1) on days with an LLJ present. Spearman’s rank correlation analysis showed a less stable atmosphere with increased soil moisture, after soil moisture reached 5%, on most days. Additional analysis determined that on all synoptic-type days the probability of reaching various thresholds of convective intensity increased as soil moisture values increased. The probabilities were even greater on days with an LLJ present than on the days without an LLJ present. An examination of four days representing each synoptic-type day indicates that on the daily scale the intensity of the convective environment is closely related to the high soil moisture and the presence of an LLJ.

Spatial variabilities and their relationships of the trends of temperature, water vapor, and precipitation in the North American Regional Reanalysis

Spatial variabilities and their relationships of the trends of temperature, water vapor, and precipitation in the North American Regional Reanalysis are examined for each season from March 1979 to February 2007. Results show that warming dominates the domain in the troposphere from the surface to 300 hPa. Water vapor increases at lower levels but does not change much at mid‐upper levels. Because of the large increase of water vapor holding capacity of the air at all levels due to the warming, relative humidity has a decreasing trend at all levels. The decrease is small at the surface and largest at midlevels. Precipitation, which corresponds well to ascending motion in trends, both increases and decreases in about half of the domain. Statistical analysis from the very large spatial samples indicates that the precipitation trend positively relates to both specific humidity trend and relative humidity trend. However, temperature trend positively relates to specific humidity trend but negatively relates to relative humidity trend. So, in strong warming places, whether precipitation increases or not depends on whether the decrease of relative humidity becomes a limiting factor; small decrease of relative humidity may still allow precipitation to increase, but large decrease of relative humidity may make precipitation decrease. The uncertain relationship between the trends of precipitation and temperature can also be understood from the nonlinear characteristics of the atmospheric processes.

Hydrodynamics of the Caribbean Low-Level Jet and Its Relationship to Precipitation

Abstract The easterly Caribbean low-level jet (CLLJ) is a prominent climate feature over the Intra-America Seas, and it is associated with much of the water vapor transport from the tropical Atlantic into the Caribbean Basin. In this study, the North American Regional Reanalysis (NARR) is analyzed to improve the understanding of the dynamics of the CLLJ and its relationship to regional rainfall variations. Horizontal momentum balances are examined to understand how jet variations on both diurnal and seasonal time scales are controlled. The jet is geostrophic to the first order. Its previously documented semidiurnal cycle (with minima at about 0400 and 1600 LT) is caused by semidiurnal cycling of the meridional geopotential height gradient in association with changes in the westward extension of the North Atlantic subtropical high (NASH). A diurnal cycle is superimposed, associated with a meridional land–sea breeze (solenoidal circulation) onto the north coast of South America, so that the weakest jet velocities occur at 1600 LT. The CLLJ is present throughout the year, and it is known to vary in strength semiannually. Peak magnitudes in July are related to the seasonal cycle of the NASH, and a second maximum in February is caused by heating over northern South America. From May through September, zonal geopotential gradients associated with summer heating over Central America and Mexico induce meridional flow. The CLLJ splits into two branches, including a southerly branch that connects with the Great Plains low-level jet (GPLLJ) bringing moisture into the central United States. During the rest of the year, the flow remains essentially zonal across the Caribbean Basin and into the Pacific. A strong (weak) CLLJ is associated with reduced (enhanced) rainfall over the Caribbean Sea throughout the year in the NARR. The relationship with precipitation over land depends on the season. Despite the fact that the southerly branch of the CLLJ feeds into the meridional GPLLJ in May through September, variations in the CLLJ strength during these months do not impact U.S. precipitation, because the CLLJ strength is varying in response to regional-scale forcing and not to changes in the large-scale circulation. During the cool season, there are statistically significant correlations between the CLLJ index and rainfall over the United States. When the CLLJ is strong, there is anomalous northward moisture transport across the Gulf of Mexico into the central United States and pronounced rainfall increases over Louisiana and Texas. A weak jet is associated with anomalous westerly flow across the southern Caribbean region and significantly reduced rainfall over the south-central United States. No connection between the intensity of the CLLJ and drought over the central United States is found. There are only three drought summers in the NARR period (1980, 1988, and 2006), and the CLLJ was extremely weak in 1988 but not in 1980 or 2006.

Temperature and equivalent temperature over the United States (1979–2005)

AbstractTemperature (T) and equivalent temperature (TE) trends over the United States from 1979 to 2005 and their correlation to land cover types are investigated using National Centers for Environmental Prediction North American Regional Reanalysis data, the Advanced Very High Resolution Radiometer (AVHRR) land use/cover classification, the National Land Cover Database (NLCD) 1992–2001 Retrofit Land Cover Change and the Normalised Difference Vegetation Index (NDVI) derived from AVHRR. Even though most of the magnitude of TE is explained by T, the moisture component induces larger trends and variability of TE relative to T. The contrast between pronounced temporal and spatial differences between T and TE at the near‐surface level (2 m) and minor‐to‐no differences at 300–200 mb is a consistent pattern. This study therefore demonstrates that in addition to temperature, atmospheric heat content may help to quantify the differences between surface and tropospheric heating trends, and hence the impact of land cover types on the surface temperature changes. Correlations of T and TE with NDVI reveal that TE shows a stronger relationship to vegetation cover than T, especially during the growing season, with values that are significantly different and of opposite signs (−0.31 for T vs NDVI; 0.49 for TE vs NDVI). Our results suggest that land cover types influence both moisture availability and temperature in the lower atmosphere and that TE is larger in areas with higher physical evaporation and transpiration rates. As a result, TE can be used as an additional metric for analysing near‐surface heating trends with respect to land cover types. Moreover, TE can be tested as a complementary variable for assessing the impact of land surface and boundary layer processes in re‐analysis and weather/climate model studies. Copyright © 2010 Royal Meteorological Society

Snow-to-Liquid Ratio Variability and Prediction at a High-Elevation Site in Utah’s Wasatch Mountains

Abstract Contemporary snowfall forecasting is a three-step process involving a quantitative precipitation forecast (QPF), determination of precipitation type, and application of a snow-to-liquid ratio (SLR). The final step is often performed using climatology or algorithms based primarily on temperature. Based on a record of consistent and professional daily snowfall measurements, this study 1) presents general characteristics of SLR at Alta, Utah, a high-elevation site in interior North America with frequent winter storms; 2) diagnoses relationships between SLR and atmospheric conditions using reanalysis data; and 3) develops a statistical method for predicting SLR at the study location. The mean SLR at Alta is similar to that observed at lower elevations in the surrounding region, with substantial variability throughout the winter season. Using data from the North American Regional Reanalysis, temperature, wind speed, and midlevel relative humidity are shown to be related to SLR, with the strongest correlation occurring between SLR and near-crest-level (650 hPa) temperature. A stepwise multiple linear regression (SMLR) equation is constructed that explains 68% of the SLR variance for all events, and 88% for a high snow-water equivalent (>25 mm) subset. To test predictive ability, the straightforward SMLR approach is applied to archived 12–36-h forecasts from the National Centers for Environmental Prediction Eta/North American Mesoscale (Eta/NAM) model, yielding an improvement over existing operational SLR prediction techniques. Errors in QPF over complex terrain, however, ultimately limit skill in forecasting snowfall amount.

Analysis of simulated and spaceborne passive microwave brightness temperatures using in situ measurements of snow and vegetation properties

Variations in snow cover and vegetation in the Province of Quebec, Canada, were characterized for a transect spanning from 50°N to 60°N during the International Polar Year field campaign of February 2008. The main objective of this study was to compare measured (AMSR-E) and modeled (MEMLS) brightness temperature (Tb) and to analyze differences in the in situ measurement of snow water equivalent (SWE) and vegetation. Sampling involved detailed snow measurements on the ground in four different ecological environments. Measured and modeled SWE were compared using a thermodynamic multilayered snow model (SNOWPACK) driven with North American Regional Reanalysis (NARR) data. The root mean square error (RMSE) of modeled data compared with measurements was 63 mm (30%). The simulated SWE was generally underestimated throughout the transect but stayed within the large standard deviation observed for measured SWE. In situ snow measurements were used as input to a microwave emission model (MEMLS) to simulate Tb. An innovative approach using calibrated near-infrared reflectance photographs was used to characterize the effective snow grain-size parameter needed for the radiative transfer model. Although some results provided Tb predictions similar to AMSR-E data for certain areas, large differences remained for the majority of sampling sites. The derived RMSE of 16 K and 32 K, respectively, for 18.7 and 36.5 GHz (vertical polarization) throughout the transect cannot be explained solely in terms of grain-size variations introduced into the simulations. Local variability in snow structure and thickness produced large variability (up to 60 K within one AMSR-E pixel) compared with AMSR-E Tb throughout the transect (15 K for 18.7 GHz and 35 K for 36.5 GHz).

Contribution of tropical cyclones to extreme rainfall events in the southeastern United States

Extreme precipitation has been increasing in the United States over the past century. In light of the associated impacts and possible linkages to climate change, this topic has garnered a great deal of attention from the scientific community and general public. Because tropical cyclones are a common source of heavy rainfall in the southeastern United States, we examined the contribution of tropical cyclone precipitation relative to overall extreme precipitation from all weather systems combined. We used a surface observation network over the period 1972–2007, consisting of first‐order and Cooperative Observer Program weather stations. Furthermore, to account for precipitation that may be unmeasured by rain gauges because of windy conditions during tropical cyclones, we employed a wind‐corrected data set and the North American Regional Reanalysis. According to several metrics of extreme precipitation, we found that extreme precipitation from tropical cyclones has been increasing over the past few decades. Additionally, the contribution of tropical cyclone precipitation to overall extreme precipitation has been significantly increasing by approximately 5%–10% per decade in the southeastern Atlantic coastal states. We attribute this rise in tropical cyclone contribution to an increase in both the storm wetness (precipitation per storm) and storm frequency over the period of record. There is little evidence that changes in storm duration are responsible for the increase. As such, we believe that an important factor in accurately projecting changes in extreme precipitation rests on whether tropical cyclone activity is driven more by natural decadal oscillations or by large‐scale warming of the environment.

Validation of Solar Radiation Surfaces from MODIS and Reanalysis Data over Topographically Complex Terrain

Abstract The magnitude and distribution of incoming shortwave solar radiation (SW↓) has significant influence on the productive capacity of forest vegetation. Models that estimate forest productivity require accurate and spatially explicit radiation surfaces that resolve both long- and short-term temporal climatic patterns and that account for topographic variability of the land surface. This paper presents a validation of monthly average total (SW↓t) and diffuse ( SW↓df ) incoming solar radiation surfaces taken from North American Regional Reanalysis (NARR) data and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery for a mountainous region of the Pacific northwestern United States and Canada. A topographic solar radiation model based on a regionally defined clearness index was used to downscale the 32-km NARR SW↓t surfaces to 1 km, resulting in surfaces that better matched the spatial resolution of MODIS, as well as accounted for elevation and terrain effects including shadowing. Validation was carried out using a series of ground station measurements (n = 304) collected in 2003. The results indicated that annually, the NARR and MODIS SW↓t surfaces were both in strong agreement with ground measurements (r = 0.98 and 0.97), although the strength and bias of the relationships varied considerably by month. Correlations were highest in winter, early summer, and fall and lowest in spring. The NARR and MODIS SW↓df surfaces displayed poorer agreement with ground measurements (r = 0.89 and 0.79), the result of some months having negative correlations. The correlation and spatial structure between NARR and MODIS SW↓t surfaces was enhanced by topographic correction, resulting in more consistent input radiation surfaces for use in broad-scale forest productivity modeling.

Understanding the Characteristics of Daily Precipitation over the United States Using the North American Regional Reanalysis

Abstract This study examines the seasonal characteristics of daily precipitation over the United States using the North American Regional Reanalysis (NARR). To help understand the physical mechanisms that contribute to changes in the characteristics of daily precipitation, vertically integrated moisture flux convergence (MFC) and precipitable water were included in the study. First, an analysis of the NARR precipitation was carried out because while observed precipitation is indirectly assimilated in the system, differences exist. The NARR mean seasonal amount is very close to that of observations throughout the year, although NARR exhibits a slight systematic bias toward more-frequent, lighter precipitation. Particularly during summer, the precipitation intensity and the probability distribution function (PDF) indicate that NARR somewhat underestimates extremes and overestimates lighter events in the eastern half of the United States. The intensity and PDF of moisture flux convergence exhibit a strong similarity to those of precipitation, suggesting a link between strong MFC and precipitation extremes. On the other hand, the relationship between the precipitable water and precipitation PDFs is weaker, based on the lack of agreement of their gamma distribution parameters. The dependence of the precipitation PDF on the lower-frequency modulation of ENSO was examined. During El Niño winters, the Southwest and central United States, Gulf of Mexico region, and southeastern coast have greater precipitation intensity and extremes than during La Niña, and the Ohio River and Red River basins have lower intensity and fewer extreme events. During summer, the northern Rocky Mountains receive higher intensity precipitation with more extreme events. Most areas where the change in the daily mean precipitation between ENSO phases is large have greater shifts in the extreme tail of the PDF. The ENSO-related response of moisture flux convergence is similar to that of precipitation. ENSO-related shifts in the precipitation PDF do not appear to have a strong relationship to the shifts in precipitable water.

Simulation of Snow Water Equivalent (SWE) Using Thermodynamic Snow Models in Québec, Canada

Abstract Snow cover plays a key role in the climate system by influencing the transfer of energy and mass between the soil and the atmosphere. In particular, snow water equivalent (SWE) is of primary importance for climatological and hydrological processes and is a good indicator of climate variability and change. Efforts to quantify SWE over land from spaceborne passive microwave measurements have been conducted since the 1980s, but a more suitable method has yet to be developed for hemispheric-scale studies. Tools such as snow thermodynamic models allow for a better understanding of the snow cover and can potentially significantly improve existing snow products at the regional scale. In this study, the use of three snow models [SNOWPACK, CROCUS, and Snow Thermal Model (SNTHERM)] driven by local and reanalysis meteorological data for the simulation of SWE is investigated temporally through three winter seasons and spatially over intensively sampled sites across northern Québec. Results show that the SWE simulations are in agreement with ground measurements through three complete winter seasons (2004/05, 2005/06, and 2007/08) in southern Québec, with higher error for 2007/08. The correlation coefficients between measured and predicted SWE values ranged between 0.72 and 0.99 for the three models and three seasons evaluated in southern Québec. In subarctic regions, predicted SWE driven with the North American Regional Reanalysis (NARR) data fall within the range of measured regional variability. NARR data allow snow models to be used regionally, and this paper represents a first step for the regionalization of thermodynamic multilayered snow models driven by reanalysis data for improved global SWE evolution retrievals.