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This paper analyzes the relationships between the circulation regimes of the 500-hPa height (z500) and 250-hPa zonal winds (u250) in the Pacific–North America region during boreal winter, and the 45-day Northern Hemisphere oscillation in z500. The regimes were calculated using a k-means clustering applied to the leading 12 principal components of the combined z500–u250 anomaly fields. We divided the oscillation into eight arbitrary phases. The oscillation phase z500 composite maps are spatially well correlated with regime z500 composites: phases 1–2 are best correlated with the Arctic Low, phases 3–5 are best correlated with the Pacific Trough, phase 6 is best correlated with the Arctic High, and phases 7–8 are best correlated with the Alaskan Ridge. We found that these correlations are generally consistent with the regimes that tend to occur during the individual oscillation phases: the Arctic Low occurs above significance in phases 1–2, the Pacific Trough occurs above significance in phase 3, and Alaskan Ridge occurs above significance in phases 7–8. Therefore, the oscillation has a preferred order with respect to the regimes. The regime transitions indicate a pattern that moves through the Pacific Wavetrain, a regime that appears for k = 5 as a mean state. Transitions out of this regime into different regimes are preferred in different phases of the oscillation. These results imply a possible enhancement to regime prediction using the low-frequency oscillations in combination with regimes. Significance Statement: Subseasonal prediction, weather forecasting in the 2–4-week range, is important for many parts of society, e.g., water managers, emergency response units, and farmers. However, current prediction skill in this time range is low. This paper performs an initial analysis of a possible method to increase weather statistic prediction skill beyond 10 days in the winter for the Pacific–North America region. This is done by combining two ways of looking at large, long-lasting patterns of pressure systems in the atmosphere, which are associated with various weather statistics like precipitation extremes and storminess. The results indicate this method holds potential skill for enhancing subseasonal prediction. Further investigation might yield forecasting improvements in this important time range. [ABSTRACT FROM AUTHOR]

A 2020 metastudy by Knutson et al. gave distributions for possible changes in the frequency and intensity of tropical cyclones under climate change. The results form a great resource for those who model the impacts of tropical cyclones. However, a number of steps of processing may be required to use the results in practice. These include interpolation in time, distribution fitting, and reverse engineering of correlations. In this paper we study another processing step that may be required, which is adjusting the frequency change results so that they apply to landfalling frequencies. An adjustment is required because the metastudy results give frequency adjustments as a function of storm lifetime maximum intensity rather than landfall intensity. Increases in the frequency of category-4 and category-5 storms, by lifetime maximum intensity, then contribute to increases in the frequencies of storms of all intensities at landfall. We consider North Atlantic Ocean storms and use historical storm information to quantify this effect as a function of landfall intensity and region. Whereas the original metastudy results suggest that the mean frequency of category-3 storms will decrease, our analysis suggests that the mean frequency of landfalling category-3 storms will increase. Our results are highly uncertain, particularly because we assume that tracks and genesis locations of storms will not change, even though some recent climate model results suggest otherwise. However, making the adjustments we describe is likely to be a better way to model future landfall risk than applying the original metastudy frequency changes directly at landfall. Significance Statement: A recent metastudy gave distributions for possible changes in the frequency and intensity of tropical cyclones under climate change. For the North Atlantic Ocean, we show how to convert these results to changes at landfall. This conversion increases the changes in the frequencies of storms in intensity categories 0–3, and, in particular, the mean frequency change of storms in category 3 flips from decreasing to increasing in most regions. [ABSTRACT FROM AUTHOR]

The term "tornado outbreak" appeared in the meteorological literature in the 1950s and was used to highlight severe weather events with multiple tornadoes. The exact meaning of "tornado outbreak," however, evolved over the years. Depending on the availability of scientific data, technological advancements, and the intended purpose of these definitions, authors offered a diverse set of approaches to shape the perception and applications of the term "tornado outbreak." This paper reviews over 200 peer-reviewed publications--by decade--to outline the evolving nature of the "tornado outbreak" definition and to examine the changes in the "tornado outbreak" definition or its perception. A final discussion highlights the importance, limitations, and potential future evolution of what defines a "tornado outbreak.". [ABSTRACT FROM AUTHOR]

This paper provides an updated analysis of observed changes in extreme precipitation using high-quality station data up to 2018. We examine changes in extreme precipitation represented by annual maxima of 1-day (Rx1day) and 5-day (Rx5day) precipitation accumulations at different spatial scales and attempt to address whether the signal in extreme precipitation has strengthened with several years of additional observations. Extreme precipitation has increased at about two-thirds of stations and the percentage of stations with significantly increasing trends is significantly larger than that can be expected by chance for the globe, continents including Asia, Europe, and North America, and regions including central North America, eastern North America, northern Central America, northern Europe, the Russian Far East, eastern central Asia, and East Asia. The percentage of stations with significantly decreasing trends is not different from that expected by chance. Fitting extreme precipitation to generalized extreme value distributions with global mean surface temperature (GMST) as a covariate reaffirms the statistically significant connections between extreme precipitation and temperature. The global median sensitivity, percentage change in extreme precipitation per 1 K increase in GMST is 6.6% (5.1% to 8.2%; 5%–95% confidence interval) for Rx1day and is slightly smaller at 5.7% (5.0% to 8.0%) for Rx5day. The comparison of results based on observations ending in 2018 with those from data ending in 2000–09 shows a consistent median rate of increase, but a larger percentage of stations with statistically significant increasing trends, indicating an increase in the detectability of extreme precipitation intensification, likely due to the use of longer records. [ABSTRACT FROM AUTHOR]

This paper describes the development and analysis of an objective climatology of warm and cold fronts over North America from 1979 to 2018. Fronts are detected by a convolutional neural network (CNN), trained to emulate fronts drawn by human meteorologists. Predictors for the CNN are surface and 850-hPa fields of temperature, specific humidity, and vector wind from the ERA5 reanalysis. Gridded probabilities from the CNN are converted to 2D frontal regions, which are used to create the climatology. Overall, warm and cold fronts are most common in the Pacific and Atlantic cyclone tracks and the lee of the Rockies. In contrast with prior research, we find that the activity of warm and cold fronts is significantly modulated by the phase and intensity of El Niño–Southern Oscillation. The influence of El Niño is significant for winter warm fronts, winter cold fronts, and spring cold fronts, with activity decreasing over the continental United States and shifting northward with the Pacific and Atlantic cyclone tracks. Long-term trends are generally not significant, although we find a poleward shift in frontal activity during the winter and spring, consistent with prior research. We also identify a number of regional patterns, such as a significant long-term increase in warm fronts in the eastern tropical Pacific Ocean, which are characterized almost entirely by moisture gradients rather than temperature gradients. [ABSTRACT FROM AUTHOR]

The assumption of a stationary global signal linked to El Niño–Southern Oscillation (ENSO) events is often used in paleo-ENSO proxy data interpretation. This paper attempts to investigate whether the assumption is valid during the last glacial maximum (LGM) over the region 60°S–90°N, 60°E−60°W. Using four models within phase 3 of the Paleoclimate Modeling Intercomparison Project framework that well reproduce ENSO-induced variabilities, differences from the preindustrial period to LGM in the ENSO-related sea surface temperature pattern and its impacts are investigated. Compared to the preindustrial period, the ENSO impacts are revealed to weaken and shift eastward during the LGM. According to multimodel medians, ENSO impacts on precipitation and near-surface air temperature are attenuated over most regions of concern, with percentage changes in both parameters averaging −21% for the whole region; the ENSO-induced Pacific–North America (PNA) teleconnection pattern is weakened, manifested by the 41% diminished center over the North Pacific and the almost vanished activity centers over the continent. Spatially, there is a zonal contraction of 13° for the sea surface warming of ENSO, as well as eastward migration over 10° for the ENSO-induced positive precipitation anomaly center over the tropical Pacific and the PNA teleconnection pattern outside the tropics. The aforementioned changes are linked to the altered climatic background during the LGM, which features a 16° eastward shift for the Pacific Walker circulation rising branch and a weakened waveguide in the midlatitudes. The results suggest that the hypothesis of stationary ENSO impacts should be applied cautiously to the past. [ABSTRACT FROM AUTHOR]

A quality control (QC) process has been developed and implemented on an observational database of surface wind speed and direction in northeastern North America. The database combines data from 526 land stations and buoys spread across eastern Canada and five adjacent northeastern U.S. states. It combines the observations of three different institutions spanning from 1953 to 2010. The quality of these initial data varies among source institutions. The current QC process is divided into two parts. Part I, described herein, is focused on issues related to data management: issues stemming from data transcription and collection; differences in measurement units and recording times; detection of sequences of duplicated data; unification of calm and true north criteria for wind direction; and detection of physically unrealistic data measurements. As a result, around ~0.1% of wind speed and wind direction records have been identified as erroneous and deleted. The most widespread error type is related to duplications within the same station, but the error type that entails more erroneous data belongs to duplications among different sites. Additionally, the process of data compilation and standardization has had an impact on more than 90% of the records. A companion paper (Part II) deals with a group of errors that are conceptually different, and is focused on detecting measurement errors that relate to temporal consistency and biases in wind speed and direction. [ABSTRACT FROM AUTHOR]

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T B at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T B based on their correlations with the prior T B (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171 m RMSE), the overall snow depth estimates are improved by 1.6% (0.168 m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177 m RMSE). Significant improvement of the snow depth estimates in the rule-based RA is observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant ( p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions. [ABSTRACT FROM AUTHOR]

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge. [ABSTRACT FROM AUTHOR]

Two questions are addressed in this paper: whether ENSO can be adequately characterized by simple, seasonally invariant indices and whether the time series of a single component-SST or OLR-provides a sufficiently complete representation of ENSO for the purpose of quantifying U.S. climate impacts. Here, ENSO is defined as the leading mode of seasonally varying canonical correlation analysis (CCA) between anomalies of tropical Pacific SST and outgoing longwave radiation (OLR). The CCA reveals that the strongest regions of coupling are mostly invariant as a function of season and correspond to an OLR region located in the central Pacific Ocean (CP-OLR) and an SST region in the eastern Pacific that coincides with the Niño-3 region. In a linear context, the authors explore whether the use of a combined index of these SST and OLR regions explains additional variance of North American temperature and precipitation anomalies beyond that described by using a single index alone. Certain seasons and regions benefit from the use of a combined index. In particular, a combined index describes more variability in winter/spring precipitation and summer temperature. [ABSTRACT FROM AUTHOR]

Northwestern Canada is a genesis region of arctic air masses often considered to be formed primarily through radiative processes. However, the details of their life cycle are poorly understood. This paper examines the formation, maintenance, and dissipation of an intense and long-lived arctic air mass, using a thermodynamic budget analysis. The airmass formation is characterized by a deep-layer, multistage process that begins with snow falling into a nascent air mass. Radiative cooling from cloud tops begins the process. After the snow abates and clear skies are observed, the surface temperature drops rapidly, aided by the high emissivity of fresh snow cover, falling 17°C in two days, creating an intense but shallow temperature inversion. Once the surface temperature falls below the frost point, ice crystals form. Afterward, although the surface temperature remains constant, the height of the inversion rises, as radiative cooling at the top of the ice fog layer decreases temperatures. During the maintenance phase, a cold-air damming structure is present with an anticyclone in the lee of the Canadian Rockies, low pressure in the Gulf of Alaska, and an intense baroclinic zone parallel to the mountains, separating warmer maritime air from colder continental air. The air mass persists for 12 days, undergoing several cycles of deep-layer weakening and intensification. [ABSTRACT FROM AUTHOR]

The paper presents the incremental improvement of the prediction of the Great Lakes net basin supply (NBS) with the hydrometeorological model Modélisation Environmentale-Surface et Hydrologie (MESH) by increasing the accuracy of the simulated NBS components (overlake precipitation, lake evaporation, and runoff into the lake). This was achieved through a series of experiments with MESH and its parent numerical weather prediction model [the Canadian Global Environmental Multiscale model in its regional configuration (GEM Regional)]. With forcing extracted from operational GEM Regional forecasts, MESH underestimated the NBS in fall and winter. The underestimation increased when the GEM precipitation was replaced with its corrected version provided by the Canadian Precipitation Analysis. This pointed to overestimated lake evaporation and prompted the revision of the parameterization of the surface turbulent fluxes over water used both in MESH and GEM. The revised parameterization was validated against turbulent fluxes measured at a point on Lake Superior. Its use in MESH reduced the lake evaporation and largely corrected the NBS underestimation. However, the Lake Superior NBS became overestimated, signaling an inconsistency between the reduced lake evaporation and the prescribed precipitation. To remove the inconsistency, a new forcing dataset (including precipitation) was generated with the GEM model using the revised flux parameterization. A major NBS simulation improvement was obtained with the new atmospheric forcing reflecting the atmospheric response to the modified surface fluxes over the lakes. Additional improvements resulted by correcting the runoff with a modified snowmelt rate and by insertion of observed streamflows. The study shows that accurate lake evaporation simulation is crucial for accurate NBS prediction. [ABSTRACT FROM AUTHOR]

The North American Regional Climate Change Assessment Program (NARCCAP) is an international effort designed to investigate the uncertainties in regional-scale projections of future climate and produce high-resolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere-ocean general circulation models (AOGCMs) forced with the Special Report on Emission Scenarios (SRES) A2 scenario, with a common domain covering the conterminous United States, northern Mexico, and most of Canada. The program also includes an evaluation component (phase I) wherein the participating RCMs, with a grid spacing of 50 km, are nested within 25 years of National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) Reanalysis II. This paper provides an overview of evaluations of the phase I domain-wide simulations focusing on monthly and seasonal temperature and precipitation, as well as more detailed investigation of four subregions. The overall quality of the simulations is determined, comparing the model performances with each other as well as with other regional model evaluations over North America. The metrics used herein do differentiate among the models but, as found in previous studies, it is not possible to determine a "best" model among them. The ensemble average of the six models does not perform best for all measures, as has been reported in a number of global climate model studies. The subset ensemble of the two models using spectral nudging is more often successful for domain-wide root-mean-square error (RMSE), especially for temperature. This evaluation phase of NARCCAP will inform later program elements concerning differentially weighting the models for use in producing robust regional probabilities of future climate change. [ABSTRACT FROM AUTHOR]

The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (−49°C) to extreme heat (++52°C), in areas of heavy precipitation (4700 mm yr−1), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation. [ABSTRACT FROM AUTHOR]

Key mechanisms important for the simulation and better understanding of the precipitation of the North American monsoon (NAM) were analyzed in this paper. Three experiments with the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model, the Hadley Centre Regional Model version 3P (HadRM3P), driven by different boundary conditions were carried out. After a detailed analysis of the moisture and low-level winds derived from the models, the authors conclude that the Gulf of Mexico (GoM) moisture and the Great Plains low-level jet (GPLLJ) play an important role in the northern portion of the NAM. Moreover, the realistic simulation of these features is necessary for a better simulation of precipitation in the NAM. Previous works suggest that the influence of moisture from the GoM in Arizona--New Mexico (AZNM) takes place primarily via the middle- and upper-tropospheric flow (above 700 mb). However, it is shown here that if the GoM does not supply enough moisture and the GPLLJ at lower levels (below 700 mb) does not reach the AZNM region, then a dry westerly flow dominates that area and the summer precipitation is below normal. The implications of these findings for studies of climate change are demonstrated with the analysis of two general circulation models (GCMs) commonly used for climate change prediction, which are shown not to reproduce correctly the GPLLJ intensity nor the moisture in the GoM. This implies that the precipitation in AZNM would not be correctly represented by a regional model driven by these GCMs. [ABSTRACT FROM AUTHOR]

Heavy precipitation and the resulting flooding are the most serious weather-related hazards over the west coast of North America. This paper analyzes the trends in heavy precipitation for the period 1950--2009 by examining the decadal distributions of the top 60, 40, and 20 two-day precipitation events for a collection of stations along the coastal zone of the United States and British Columbia, as well as the decadal distribution of maximum daily discharge for unregulated rivers from northern California to Washington State. During the past 60 years there has been a modest increase in heavy precipitation events over southern and central coastal California, a decline in heavy events from northern California through the central Oregon coast, a substantial increase in major events over Washington, and a modest increase over coastal British Columbia. Most of these trends are not significantly different from zero at the 95%% level. The trends in maximum daily discharge of unregulated rivers are consistent with the above pattern, with increasing discharges over the past three decades over Washington and northern Oregon and declines over the remainder of Oregon and northern California. Finally, the above trends in heavy rainfall and daily discharge are compared to the future patterns indicated by general circulation models under various global warming scenarios. [ABSTRACT FROM AUTHOR]

In northwestern North America, which is a large area with complex physiography, Climatic Research Unit (CRU) Time Series, version 2.1, (TS 2.1) gridded monthly mean 2-m temperatures are systematically lower than interpolated monthly averaged North American Regional Reanalysis (NARR) pressure-level temperatures----in particular, in the winter. Quantification of these differences based on CRU gridded observations can be used to estimate pressure-level temperatures from CRU 2-m temperatures (1901--2002) that predate the NARR period (since 1979). Such twentieth-century pressure-level temperature fields can be used in glacier mass-balance modeling and as an alternative to calibrating general circulation model control runs, avoiding the need for accurate boundary layer parameterization. In this paper, an approach is presented that is transferable to moisture, wind, and other 3D fields with potential applications in wind power generation, ecology, and air quality. At each CRU grid point, the difference between CRU and NARR is regressed against seven predictors in CRU (mean temperature, daily temperature range, precipitation, vapor pressure, cloud cover, and number of wet and frost days) for the period of overlap between CRU and NARR (1979--2002). Bayesian model averaging (BMA) is used to avoid overfitting the CRU--NARR differences and underestimating uncertainties. In cross validations, BMA provides reliable posterior predictions of the CRU--NARR differences and outperforms predictions from three alternative models: the constant model (24-yr mean), the regression model of highest Bayesian model probability, and the full model retaining all seven predictors in CRU. [ABSTRACT FROM AUTHOR]

There is growing concern about the effects of large-scale oceanic atmospheric climate variability, such as the Pacific decadal oscillation (PDO), on regional hydrology and water resources. In this paper, the effects of PDO on temporal patterns of winter (January–March) flow in northwestern North America (NWNA), which is believed to be a PDO-sensitive region, is studied for the period 1943–2007 using daily streamflow data from a much larger set of 179 stations, compared to previous studies in which only smaller subsets of these stations were analyzed. Time series of winter flows were divided into two nonoverlapping blocks corresponding to change points detected in time series of December–March mean monthly PDO indices. Both parametric and nonparametric measures of correlation and average percentage differences and average standardized differences from the period-of-record mean were explored. Like some of the previous studies, it is found that, on average, winter flows tend to be higher (lower) during the warm (cold) phase of the PDO and that establishes the physical link between large-scale climate variability and basin response. It is shown that the serial structure of time series of PDO indices conforms to that of a stochastic process with long-term persistence (LTP). Based on this finding and the climate–streamflow physical link, it is plausible to investigate temporal variations in winter flows with the LTP hypothesis, in addition to assuming merely independence (IND) or short-term persistence (STP). The results of the analysis demonstrate that the LTP mechanism, in combination with the STP, is able to explain more than half of the significant trends noted, with the IND assumption suggesting that the significance of trends reported in previous studies in NWNA may have been overstated. This result has important implications for future planning of regional water resources. [ABSTRACT FROM AUTHOR]

A morphometric analysis of a southern European city and the derivation of relevant fluid dynamical parameters for use in urban flow and dispersion models are explained in this paper. Calculated parameters are compared with building statistics that have already been computed for parts of three northern European and two North American cities. The aim of this comparison is to identify similarities and differences between several building configurations and city types, such as building packing density, compact versus sprawling neighborhoods, regular versus irregular street orientation, etc. A novel aspect of this work is the derivation and use of digital elevation models (DEMs) for parts of a southern European city. Another novel aspect is the DEMs’ construction methodology, which is low cost, low tech, and of simple implementation. Several building morphological parameters are calculated from the urban DEMs using image processing techniques. The correctness and robustness of these techniques have been verified through a series of sensitivity tests performed on both idealized building configurations, as well as on real case DEMs, which were derived using the methodology here. In addition, the planar and frontal area indices were calculated as a function of elevation. It is argued that those indices, estimated for neighborhoods of real cities, may be used instead of the detailed building geometry within urban canopy models as those indices together synthesize the geometric features of a city. The direct application of these results will facilitate the development of fast urban flow and dispersion models. [ABSTRACT FROM AUTHOR]

A large number of water- and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the normalized difference vegetation index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables, as identified in site- and time-specific studies. The current paper investigates the generality of the LST–NDVI relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60°N) during the summer growing season (April–September). Information on LST and NDVI was obtained from long-term (21 years) datasets acquired with the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (the typical situation for low latitudes of the study area and during the midseason), the LST–NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth (in higher latitudes and elevations, especially at the beginning of the growing season), a positive correlation exists between LST and NDVI. Multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, whereas other biophysical variables play a lesser role. Air temperature is the primary factor in midsummer. It is concluded that there is a need to use empirical LST–NDVI relationships with caution and to restrict their application to drought monitoring to areas and periods where negative correlations are observed, namely, to conditions when water—not energy—is the primary factor limiting vegetation growth. [ABSTRACT FROM AUTHOR]

This paper verifies the strengths and positions of extratropical cyclones around North America and the adjacent oceans within the Short Range Ensemble Forecast (SREF) system at the National Centers for Environmental Prediction (NCEP) during the 2004–07 cool seasons (October–March). The SREF mean for cyclone position and central pressure has a smaller error than the various subgroups within SREF and the operational North American Mesoscale (NAM) model in many regions on average, but not the operational Global Forecast System (GFS) for many forecast times. Inclusion of six additional Weather Research and Forecasting (WRF) model members into SREF during the 2006–07 cool season did not improve the SREF mean predictions. The SREF has slightly more probabilistic skill over the eastern United States and western Atlantic than the western portions of the domain for cyclone central pressure. The SREF also has slightly greater probabilistic skill than the combined GFS and NAM for central pressure, which is significant at the 90% level for many regions and thresholds. The SREF probabilities are fairly reliable, although the SREF is overconfident at higher probabilities in all regions. The inclusion of WRF did not improve the SREF probabilistic skill. Over the eastern Pacific, eastern Canada, and western Atlantic, the SREF is overdispersed on average, especially early in the forecast, while across the central and eastern United States the SREF is underdispersed later in the forecast. There are relatively large biases in cyclone central pressure within each SREF subgroup. As a result, the best-member diagrams reveal that the SREF members are not equally accurate for the cyclone central pressure and displacement. Two cases are presented to illustrate examples of SREF developing large errors early in the forecast for cyclones over the eastern United States. [ABSTRACT FROM AUTHOR]

This paper verifies extratropical cyclones around North America and the adjacent oceans within the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and North American Mesoscale (NAM) models during the 2002–07 cool seasons (October–March). The analyzed cyclones in the Global Forecast System (GFS) model, North American Mesoscale (NAM) model, and the North American Regional Reanalysis (NARR) were also compared against sea level pressure (SLP) observations around extratropical cyclones. The GFS analysis of SLP was clearly superior to the NAM and NARR analyses. The analyzed cyclone pressures in the NAM improved in 2006–07 when its data assimilation was switched to the Gridpoint Statistical Interpolation (GSI). The NCEP GFS has more skillful cyclone intensity and position forecasts than the NAM over the continental United States and adjacent oceans, especially over the eastern Pacific, where the NAM has a large positive (underdeepening) bias in cyclone central pressure. For the short-term (0–60 h) forecasts, the GFS and NAM cyclone errors over the eastern Pacific are larger than the other regions to the east. There are relatively large biases in cyclone position for both models, which vary spatially around North America. The eastern Pacific has four to eight cyclone events per year on average, with errors >10 mb at hour 48 in the GFS; this number has not decreased in recent years. There has been little improvement in the 0–2-day cyclone forecasts during the past 5 yr over the eastern United States, while there has been a relatively large improvement in the cyclone pressure predictions over the eastern Pacific in the NAM. [ABSTRACT FROM AUTHOR]

The wintertime Pacific–North American (PNA) teleconnection pattern has previously been shown to influence springtime snow conditions over portions of North America. This paper develops a more complete physical understanding of this linkage across the continent, using a recently released long-term, continental-scale gridded North American snow depth dataset and the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis data. An empirical orthogonal function–based filtering process is used to identify and isolate the interannual snow depth variations associated with PNA. Then linear and partial correlations are employed to investigate the physical mechanisms that link winter PNA with spring snow depth. In the positive phase of PNA, the enhanced PNA pressure centers lead to warmer temperatures over northwestern North America and less precipitation at midlatitudes. The temperature and precipitation pathways act independently and in distinct geographical regions, and together they serve to reduce winter snow depth across much of North America. Winter anomalies in the snow depth field then tend to persist into spring. Dynamic mechanisms responsible for the PNA-influenced North American precipitation and temperature anomalies, involving moisture transport and cold air intrusions, are confirmed in this study and also extended to continental snow depth anomalies. [ABSTRACT FROM AUTHOR]

The seasonal rainfall over the U.S. central plains features a late-spring maximum. A spring–fall annual mode revealed from the empirical orthogonal function analysis on rainfall delineates a maximum center over the central plains that coincides with the large late-spring rainfall. This paper examines the large-scale dynamical and hydrological processes in forming the rainfall center. The NCEP–Department of Energy (DOE) reanalysis 2 data reveal that the baroclinic structure of the continental-scale circulation during late spring (May and June) induces a vertically out-of-phase divergent circulation forming strong convergence of water vapor flux over the central plains. Such circulation features generate concentrated convective activity in this region. The upper-level anticyclone development with the North American monsoon in July replaces the late-spring baroclinic structure and, in turn, reduces the convective activity. The Great Plains low-level jet (LLJ) plays a role in the downscaling process that connects the continental-scale circulation to rainfall. The LLJ coupled with approaching baroclinic waves leads to stronger moisture convergence in the central plains than that occurring under the upper-level anticyclone. The former type of the LLJ occurs most frequently in late spring and contributes to more than 60% of the rainfall. During midsummer (July and August), such a coupling is hindered by the well-developed upper-level anticyclone, subsequently decreasing the rainfall. [ABSTRACT FROM AUTHOR]

In this paper, a diagnostic metric—termed the local-convergence ratio—is used to analyze the contribution of evaporation and atmospheric moisture-flux convergence to model-based estimates of climatological precipitation over the North American continent. Generally, the fractional evaporative contribution is largest during spring and summer when evaporation is largest and decreases as evaporation decreases. However, there appears to be at least three regions with distinct spatiotemporal seasonal evolutions of this ratio. Over both the northern and western portions of the continent, the fractional evaporative contribution peaks in spring and early summer and decreases during fall and into winter. Over the northern portion, this fall decrease is related to an increase in atmospheric moisture-flux convergence associated with enhanced meridional moisture fluxes into the region; over the western coastal regions, the fall decrease in evaporative contribution is associated with a decrease in evaporation and an increase in total moisture-flux convergence, most likely associated with increased storm activity. In contrast, over the central portions of the continent, the fractional evaporative contribution to precipitation remains relatively low in spring—when enhanced low-level jet activity increases the low-level atmospheric moisture flux convergence into the region—and instead peaks in summer and fall—when the moisture-flux convergence associated with the low-level jet decreases and precipitation is balanced predominantly by local evaporation. Finally, over the southwestern United States and northwestern Mexico, the fractional evaporative contribution to precipitation is found to contain a wintertime minimum as well as a secondary minimum during summer. This latter feature is due to a substantial increase in low-level atmospheric moisture-flux convergence associated with the large-scale monsoon circulation that influences this region during this time. [ABSTRACT FROM AUTHOR]

This paper outlines the development of a continuous, daily time series of potential evapotranspiration (PET) using Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data from the Terra satellite platform. The approach is based on the Priestley–Taylor equation, incorporating a daily net radiation model during cloudless days. A simple algorithm using “theoretical clear-sky” net radiation (incorporating daily cloud fraction and cloud optical thickness) and PET is then used to estimate net radiation and PET under cloudy conditions. The method requires minimal ground-based observations for initial calibration of regional radiation algorithm coefficients. Point-scale comparisons are undertaken at four flux-tower sites in North America covering a range of hydroclimatic conditions and biomes. Preliminary results at the daily time step for a 4-yr period (2001–04) show good correlation (R2 = 0.89) and low bias (0.34 mm day-1) for three of the more humid sites. Results are further improved when aggregated to the monthly time scale (R2 = 0.95, bias = 0.31 mm day-1). Performance at the semiarid site is less satisfactory (R2 = 0.95, bias = 2.05 mm day-1 at the daily time step). In general, the MODIS-based daily PET estimates derived in this study are promising and show the potential for use in theoretical and operational water resource studies in both gauged and ungauged basins. [ABSTRACT FROM AUTHOR]

Upper-air observations with kites, aircraft, and radiosondes were performed in the United States operationally since the 1890s. In this paper, the authors present a reevaluation of newly digitized monthly mean values from the Monthly Weather Review back to 1922. Data from 46 U.S. weather stations are presented with a focus on early kite and aircraft observations during the 1922–38 period. A quality assessment of the data, based on reconstructed reference series, is carried out and the quality of the monthly mean data is found to be sufficient for analysis of variability in upper-level circulation. Anomalies of upper-level temperatures from the reevaluated station data, together with surface fields, are shown for selected periods. [ABSTRACT FROM AUTHOR]

The pre-cold-frontal low-level jet within oceanic extratropical cyclones represents the lower-tropospheric component of a deeper corridor of concentrated water vapor transport in the cyclone warm sector. These corridors are referred to as atmospheric rivers (ARs) because they are narrow relative to their length scale and are responsible for most of the poleward water vapor transport at midlatitudes. This paper investigates landfalling ARs along adjacent north- and south-coast regions of western North America. Special Sensor Microwave Imager (SSM/I) satellite observations of long, narrow plumes of enhanced integrated water vapor (IWV) were used to detect ARs just offshore over the eastern Pacific from 1997 to 2005. The north coast experienced 301 AR days, while the south coast had only 115. Most ARs occurred during the warm season in the north and cool season in the south, despite the fact that the cool season is climatologically wettest for both regions. Composite SSM/I IWV analyses showed landfalling wintertime ARs extending northeastward from the tropical eastern Pacific, whereas the summertime composites were zonally oriented and, thus, did not originate from this region of the tropics. Companion SSM/I composites of daily rainfall showed significant orographic enhancement during the landfall of winter (but not summer) ARs. The NCEP–NCAR global reanalysis dataset and regional precipitation networks were used to assess composite synoptic characteristics and overland impacts of landfalling ARs. The ARs possess strong vertically integrated horizontal water vapor fluxes that, on average, impinge on the West Coast in the pre-cold-frontal environment in winter and post-cold-frontal environment in summer. Even though the IWV in the ARs is greater in summer, the vapor flux is stronger in winter due to much stronger flows associated with more intense storms. The landfall of ARs in winter and north-coast summer coincides with anomalous warmth, a trough offshore, and ridging over the Intermountain West, whereas the south-coast summer ARs coincide with relatively cold conditions and a near-coast trough. ARs have a much more profound impact on near-coast precipitation in winter than summer, because the terrain-normal vapor flux is stronger and the air more nearly saturated in winter. During winter, ARs produce roughly twice as much precipitation as all storms. In addition, wintertime ARs with the largest SSM/I IWV are tied to more intense storms with stronger flows and vapor fluxes, and more precipitation. ARs generally increase snow water equivalent (SWE) in autumn/winter and decrease SWE in spring. On average, wintertime SWE exhibits normal gains during north-coast AR storms and above-normal gains during the south-coast AR storms. The north-coast sites are mostly lower in altitude, where warmer-than-normal conditions more frequently yield rain. During those events when heavy rain from a warm AR storm falls on a preexisting snowpack, flooding is more likely to occur. [ABSTRACT FROM AUTHOR]

This paper presents a diagnostic study of the evolution of initial corrections obtained from the key analysis error algorithm that minimizes the short-range (24 h) forecast errors for four specific events poorly forecasted over the eastern part of North America. A potential vorticity (PV) perspective is employed. It is shown that the modification to the low-level structure at the initial time is mainly attributed to the modification of the low-level PV distribution, while changes in the upper-level structure are attributed to the modification of the upper-level PV distribution. The low-level corrections grow mainly through background surface potential temperature advection by the wind corrections attributable to the interior PV corrections. Changes in the diabatic processes and the vertical alignment of low-level PV corrections by differential PV advection also increase the magnitude of the low-level corrections with time. The upper-level corrections grow by advection of background PV from wind corrections. However, the cause of these latter wind corrections responsible for upper-level background PV advection varies from case to case. An investigation of the relative importance of the low-level and of the upper-level initial corrections to produce the final-time corrections also reveals strong variability between cases. Finally, comparison of two cases in which the key analysis errors propagate vertically with two others without significant vertical propagation shows how the relative position of the key analysis errors with respect to the structure of the background flow can influence the evolution of the initial corrections. [ABSTRACT FROM AUTHOR]

In support of the 2004 North American Monsoon Experiment (NAME) field campaign, NOAA established and maintained a field site about 100 km north of Mazatlán, Mexico, consisting of wind profilers, precipitation profilers, surface upward–downward-looking radiometers, and a 10-m meteorological tower to observe the environment within the North American monsoon. Three objectives of this NOAA project are discussed in this paper: 1) to observe the vertical structure of precipitating cloud systems as they passed over the NOAA profiler site, 2) to estimate the vertical air motion and the raindrop size distribution from near the surface to just below the melting layer, and 3) to better understand the microphysical processes associated with stratiform rain containing well-defined radar bright bands. To provide a climatological context for the profiler observations at the field site, the profiler reflectivity distributions were compared with Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity distributions from the 2004 season over the NAME domain as well as from the 1998–2005 seasons. This analysis places the NAME 2004 observations into the context of other monsoon seasons. It also provides a basis for evaluating the representativeness of the structure of the precipitation systems sampled at this location. The number of rain events observed by the TRMM PR is dependent on geography; the land region, which includes portions of the Sierra Madre Occidental, has more events than the coast and gulf regions. Conversely, from this study it is found that the frequencies of occurrence of stratiform rain and reflectivity profiles with radar bright bands are mostly independent of region. The analysis also revealed that the reflectivity distribution at each height has more year-to-year variability than region-to-region variability. These findings suggest that in cases with a well-defined bright band, the vertical profile of the reflectivity relative to the height of the bright band is similar over the gulf, coast, and land regions. [ABSTRACT FROM AUTHOR]

The identification of clear-sky and cloudy pixels is a key step in the processing of satellite observations. This is equally important for surface and cloud–atmosphere applications. In this paper, the Separation of Pixels Using Aggregated Rating over Canada (SPARC) algorithm is presented, a new method of pixel identification for image data from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA satellites. The SPARC algorithm separates image pixels into clear-sky and cloudy categories based on a specially designed rating scheme. A mask depicting snow/ice and cloud shadows is also generated. The SPARC algorithm has been designed to work year-round (day and night) over the temperate and polar regions of North America, for current and historical AVHRR/NOAA High-Resolution Picture Transmission (HRPT) and Local Area Coverage (LAC) data with original 1-km spatial resolution. The algorithm was tested and applied to data from the AVHRR sensors flown on board NOAA-6 to NOAA-18. The method was employed in generating historical clear-sky composites for the 1982–2005 period at daily, 10-day, and monthly time scales at 1-km resolution for an area of 5700 km × 4800 km centered over Canada. This region also covers the northern part of the United States, including Alaska, as well as Greenland and the surrounding oceans. The SPARC algorithm is designed to produce an aggregated rating that accumulates the results of several tests. The magnitude of the rating serves as an indicator of the probability for a pixel to belong to the clear-sky, partly cloudy, or overcast categories. The individual tests employ the spectral properties of five AVHRR channels, as well as surface skin temperature maps from the North American Regional Reanalysis (NARR) dataset. These temperature fields are available at 32 km × 32 km spatial resolution and at 3-h time intervals. Combining all test results into one final rating for each pixel is beneficial for the generation of multiscene clear-sky composites. The selection of the best pixel to be used in the final clear-sky product is based on the magnitude of the rating. This provides much-improved results relative to other approaches or “yes/no” decision methods. The SPARC method has been compared to the results of supervised classification for a number of AVHRR scenes representing various seasons (snow-free summer, winter with snow/ice coverage, and transition seasons). The results show an overall agreement between the automated (SPARC) and the supervised classification at the level of 80% to 91%. [ABSTRACT FROM AUTHOR]

The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP–NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub)tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere–ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using “trends” (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years’ averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in “explaining” variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century. [ABSTRACT FROM AUTHOR]

The extent to which wintertime North American surface temperature can be specified based on simultaneous sea surface temperature (SST) is quantified for the period 1982–98. The term specification indicates that the predictor and predictands are not lagged in time, as would be the case for true prediction. Four state-of-the-art general circulation models (GCMs) and linear empirical models with predictors derived from observations and dynamical models are considered. Predictors are derived from model hindcasts using principal component analysis (PCA), canonical correlation analysis (CCA), and discriminant analysis. The last technique has appeared in the climate literature, but its use in the present context appears new. A distinguishing feature of this paper is that several methods and models are compared in a common framework. The specification skill of GCMs for the period 1982–98 is statistically significant in the northwestern region near Washington State, British Columbia, and central Canada, with some local correlations exceeding 0.6. The specification skill of GCMs is comparable to, or better than, the skill of the best empirical model for the particular 17-yr period examined. No single specification strategy was found to improve the model hindcast skill in all cases. Predictors derived from discriminant analysis generally lead to larger skill than predictors based on PCA or CCA. The signal-to-noise ratio varies greatly among models and appears to be, if anything, inversely related to the specification skill when discriminants are used as predictors. Predictors based on 500-hPa geopotential height can lead to specification skill at least as good as predictors based on land surface temperature. Evidence is presented for the existence of at least two distinct dynamically predictable components of land surface temperature arising from two distinct “flavors” of SST anomalies associated with El Niño and La Niña. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the influence of tropical sea surface temperature (SST) on the midlatitude circulation regime behavior in the Pacific–North American region. Toward this end, a cluster analysis has been applied to 55-member ensembles of winter seasonal simulations of the Center for Ocean–Land–Atmosphere Studies general circulation model for 18 winters. The ensemble members for each winter utilize the same prescribed, observed weekly varying SST for that winter. The cluster analysis includes all fluctuations with time scales longer than 10 days except for the ensemble mean seasonal cycle. Using a partitioning algorithm separately applied to each winter's ensemble, clusters are found in the 200-hPa height field that are signicant (vis-à-vis a suitable Gaussian background), reproducible (in half-length datasets), and consistent (with clusters obtained from the 200-hPa u wind) for all winters except the strong El Niño events of 1982/83, 1986/87, and 1997/98. One cluster found consistently in many winters, consisting of a strong ridge over the Alaskan region and a trough over central North America, is quite similar to the Alaskan pattern identified from observations as being particularly difficult to predict and that occurs preferentially during La Niña events. Two other clusters found in many winters have no observational counterparts. A regime that is very similar to the seasonal mean response to cold tropical Pacific SSTs is seen during several La Niña winters. A strong negative correlation between a measure of the strength of the clustering and the Niño-3 SST index is found. That this correlation is as strong as the correlation between the seasonal mean response and the same SST index indicates that the El Niño–Southern Oscillation–related SSTs affect the regime structure of intraseasonal flow as strongly as they do the mean state. [ABSTRACT FROM AUTHOR]

This paper documents the sensitivity of the modeled evolution of the North American monsoon system (NAMS) to convective parameterization in terms of thermodynamic and circulation characteristics, stability profiles, and precipitation. The convective parameterization schemes (CPSs) of Betts–Miller–Janjic, Kain–Fritsch, and Grell were tested using version 3.4 of the PSU–NCAR fifth-generation Mesoscale Model (MM5) running in a pseudoclimate mode. Model results for the initial phase of the 1999 NAM are compared with surface climate station observations and seven radiosonde sites in Mexico and the southwestern United States. The results show substantial differences in modeled precipitation, surface climate, and atmospheric stability occuring between the different model simulations, which are attributable to the representation of convection in the model. Moreover, large intersimulation differences in the low-level circulation fields are found. While none of the CPSs tested gave perfect simulation of observations everywhere in the model domain, the Kain–Fritsch scheme generally gave significantly superior estimates of surface and upper air verification error statistics. [ABSTRACT FROM AUTHOR]

This paper describes the results of an analysis of trends in short duration (1--7 days) extreme precipitation events that have a recurrence interval of 1 yr or longer for stations in the United States and Canada. This definition of extreme precipitation was chosen because such events are highly correlated with hydrologic flooding in some U.S. regions. The dominant temporal characteristic of a national event composite index is significant low-frequency variability. There were lengthy periods of a below-average number of events in the 1930s and 1950s and an above-average number of events in the early 1940s, early 1980s, and 1990s. Regional variations often differ substantially from the national composite. A simple linear analysis indicates that the overall trend covering the period 1931--96 has been upward at a highly statistically significant rate over the southwest United States and in a broad region from the central Great Plains across the middle Mississippi River and southern Great Lakes basins. The national trend for the United States is upward at a rate of 3% decade 21 for the period 1931--96. While the annual trend for Canada is upward for the period 1951--93, it is not statistically significant. Although the high statistical significance of the results is partially a consequence of the low frequency during the 1930s and 1950s located in the first half of the record, the latter half of the record exhibits an upward trend nearly identical to the entire record. However, an analysis of a 101-yr record of midwestern stations shows that heavy precipitation event frequencies around the turn of the twentieth century (1896--1906) were higher than for other periods of comparable length, except for 1986--96. Although data were not available in digital form to extend the analysis back to 1896 for the entire United States, the midwestern analysis shows that interpretation of the recent upward trends must account for the possibility of significant... [ABSTRACT FROM AUTHOR]

In a companion paper, Y. Liu and R. Avissar analyzed the features of persistence in the land--atmosphere system simulated with the National Center for Atmospheric Research Community Climate Model Version 2 coupled with the Biosphere--Atmosphere Transfer Scheme (CCM2--BATS). To interpret the results obtained in that study, a fourth-order land--atmosphere analytical model is developed and used to investigate the timescales of disturbances in the land--atmosphere system, and the major parameters and processes affecting them. This analytical model has four damping timescales, namely seasonal, monthly, weekly, and daily. It is found that the seasonal scale is caused by self-feedback of soil moisture, and its length increases significantly due to the interactions between soil moisture and the other system variables. A sensitivity analysis performed with the Fourier amplitude sensitivity test indicates that the seasonal timescale is mostly affected by the physical param-eters related to hydrological processes (namely, evaporation, runoff, and soil moisture diffusion), while the thermal characteristics of the land--atmosphere system mostly affect the monthly timescale. Thus, the results of this analytical study indicate that the persistence obtained in the CCM2--BATS simulation is an inherent property of the land--atmosphere system. They also emphasize the importance of soil moisture disturbances on persistence in the climatic system. [ABSTRACT FROM AUTHOR]

The transport of water vapor through the Mackenzie River basin, a typical high-latitude river basin, is examined for the period from August to October 1994. The spatial and temporal variability in the transport is considered with both objectively analyzed fields and radiosonde data. Previous studies of the high-latitude water vapor have made use of radiosonde data and have been able to document some features of annual cycle of water vapor transport. These studies have left unresolved many important aspects of moisture transport processes. In particular, detailed information as to the spatial and temporal variation of the transport has not been fully documented or understood. In order to address these important issues, the authors make use of the objectively analyzed fields from the European Centre for Medium-Range Weather Forecasts to study the high-latitude transport of water vapor. This paper presents findings regarding the transport of water vapor over northern parts of North America. It is shown that the transport is highly variable in time with transient synoptic-scale disturbances being responsible for much of the transport. The prospect of using the objectively analyzed fields to determine the spatial structure of humidity fluxes and the evaporation-- precipitation field in data-sparse high-latitude regions is discussed. The results obtained with the objectively analyzed fields are compared with those obtained directly from radiosonde data for stations in and around the basin. The influence that the local land topography has on the regional water vapor balance is also discussed. [ABSTRACT FROM AUTHOR]