Spurious Grid-Scale Precipitation in the North American Regional Reanalysis

2007 ◽  
Vol 135 (6) ◽  
pp. 2168-2184 ◽  
Author(s):  
Gregory L. West ◽  
W. James Steenburgh ◽  
William Y. Y. Cheng

Abstract Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.

2019 ◽  
Vol 58 (1) ◽  
pp. 71-92 ◽  
Author(s):  
Austin T. King ◽  
Aaron D. Kennedy

AbstractA suite of modern atmospheric reanalyses is analyzed to determine how they represent North American supercell environments. This analysis is performed by comparing a database of Rapid Update Cycle (RUC-2) proximity soundings with profiles derived from the nearest grid point in each reanalysis. Parameters are calculated using the Sounding and Hodograph Analysis and Research Program in Python (SHARPpy), an open-source Python sounding-analysis package. Representation of supercell environments varies across the reanalyses, and the results have ramifications for climatological studies that use these datasets. In particular, thermodynamic parameters such as the convective available potential energy (CAPE) show the widest range in biases, with reanalyses falling into two camps. The North American Regional Reanalysis (NARR) and the Japanese 55-year Reanalysis (JRA-55) are similar to RUC-2, but other reanalyses have a substantial negative bias. The reasons for these biases vary and range from thermodynamic biases at the surface to evidence of convective contamination. Overall, it is found that thermodynamic biases feed back to other convective parameters that incorporate CAPE directly or indirectly via the effective layer. As a result, significant negative biases are found for indices such as the supercell composite parameter. These biases are smallest for NARR and JRA-55. Kinematic parameters are more consistent across the reanalyses. Given the issues with thermodynamic properties, better segregation of soundings by storm type is found for fixed-layer parameters than for effective-layer shear parameters. Although no reanalysis can exactly reproduce the results of earlier RUC-2 studies, many of the reanalyses can broadly distinguish between environments that are significantly tornadic versus nontornadic.


2014 ◽  
Vol 53 (9) ◽  
pp. 2093-2113 ◽  
Author(s):  
Claudia K. Walters ◽  
Julie A. Winkler ◽  
Sara Husseini ◽  
Ryan Keeling ◽  
Jovanka Nikolic ◽  
...  

AbstractClimatological analyses of low-level jets (LLJs) can be negatively influenced by the coarse spatial and temporal resolution and frequent changes in observing and archiving protocols of rawinsonde observations (raobs). The introduction of reanalysis datasets, such as the North American Regional Reanalysis (NARR), provides new resources for climatological research with finer spatial and temporal resolution and potentially fewer inhomogeneities. To assess the compatibility of LLJ characteristics identified from NARR wind profiles with those obtained from raob profiles, LLJs were extracted using standard jet definitions from NARR and raobs at 12 locations in the central United States for four representative years that reflect different rawinsonde protocols. LLJ characteristics (e.g., between-station differences in relative frequency, diurnal fluctuations, and mean speed and elevation) are generally consistent, although absolute frequencies are smaller for NARR relative to raobs at most stations. LLJs are concurrently identified in the NARR and raob wind profiles on less than 60% of the observation times with LLJ activity. Variations are seen between analysis years and locations. Of particular note is the substantial increase in LLJ frequency seen in raobs since the introduction of the Radiosonde Replacement System, which has led to a greater discrepancy in jet frequency between the NARR and raob datasets. The analyses suggest that NARR is a viable additional resource for climatological analyses of LLJs. Many of the findings are likely applicable for other fine-resolution reanalysis datasets, although differences between reanalyses require that each be carefully evaluated before its use in climatological analyses of wind maxima.


2019 ◽  
Vol 5 (4) ◽  
pp. 218-239 ◽  
Author(s):  
Richard Bello ◽  
Kaz Higuchi

Monthly and annual component fluxes of the surface radiation and energy budgets for the two-decade period from 1997 to 2016 are compared with the climate normal period (1981–2010) for the marine system consisting of James Bay, Hudson Bay, Hudson Strait and Foxe Basin using estimates from the North American regional reanalysis model. Reflected solar radiation has declined unevenly, primarily offshore of major rivers, in polynyas and along shore leads, both during earlier melt and later freeze up. Annually, net radiation increases are driven by albedo decreases during the summer. Over 94% of the increases in ocean heat gain during the melt season are due to increases in absorbed sunlight. Large enhanced oceanic heat losses in the late fall are almost entirely consumed by intensified convective losses of both sensible and latent heat. All the seas within the Hudson Bay Complex show a reduced rate of ocean warming over the past two decades. This outcome can be partially reconciled with the observation that all water bodies are experiencing enhanced losses of energy during extended ice-free winters that exceed enhanced gains of energy during the extended ice-free summers. The implications of seasonal changes in ice cover for future climate are discussed.


2015 ◽  
Vol 7 (2) ◽  
pp. 159-168 ◽  
Author(s):  
Claire Steinweg ◽  
William J. Gutowski

Abstract A matrix of four GCM–RCM combinations from the NARCCAP project is examined for changes in heat stress between contemporary and future scenario climates in the greater St. Louis region in Missouri. The analysis also compares the contemporary simulations with observation-based results from the North American Regional Reanalysis. The character of heat-stress days in one of the RCMs, the CRCM, tends to be like that of heat-stress days in the North American Regional Reanalysis, with high temperatures accompanied by high humidity. In contrast, heat-stress days in the other RCM, the Weather Research and Forecasting Model with Grell-Devenyi Cumulus Scheme (WRFG), have high temperature, but typically the humidity is similar to or even slightly drier than climatological values. Although specific magnitudes of change differ between the simulations, all show a marked increase in projected heat stress, from a variety of perspectives. Increases in temperature contribute more to these increases than do increases in humidity, though both are relevant. All simulations agree that the frequency of excessive heat advisories and excessive heat warnings as defined by the National Weather Service could increase by midcentury, with multiple excessive heat advisories occurring every year. The day of first heat stress each summer could occur 3–4 weeks earlier as part of a more prolonged period when the region might experience heat stress each year. Although St. Louis has adopted measures to reduce health threats during heat-stress events, the measures consume human and economic resources; much more frequent and longer-lasting heat-stress events in the future have the potential to impose substantial costs on the region.


2017 ◽  
Vol 18 (2) ◽  
pp. 515-527 ◽  
Author(s):  
Ronald D. Leeper ◽  
Jesse E. Bell ◽  
Chanté Vines ◽  
Michael Palecki

Abstract Accurate and timely information on soil moisture conditions is an important component to effectively prepare for the damaging aspects of hydrological extremes. The combination of sparsely dense in situ networks and shallow observation depths of remotely sensed soil moisture conditions often force local and regional decision-makers to rely on numerical methods when assessing the current soil state. In this study, soil moisture from a commonly used, high-resolution reanalysis dataset is compared to observations from the U.S. Climate Reference Network (USCRN). The purpose of this study is to evaluate how well the North American Regional Reanalysis (NARR) captured the evolution, intensity, and spatial extent of the 2012 drought using both raw volumetric values and standardized anomalies of soil moisture. Comparisons revealed that despite a dry precipitation bias of 22% nationally, NARR had predominantly wetter 5-cm volumetric soil conditions over the growing season (April–September) than observed at USCRN sites across the contiguous United States, with differences more pronounced in drier regions. These biases were partially attributed to differences between the dominant soil characteristics assigned to the modeled grid cells and localized soil characteristics at the USCRN stations. However, NARR was able to successfully capture many aspects of the 2012 drought, including the timing, intensity, and spatial extent when using standardized soil moisture anomalies. Standardizing soil moisture conditions reduced the magnitude of systematic biases between NARR and USCRN in many regions and provided a more robust basis for utilizing modeled soil conditions in assessments of hydrological extremes.


2012 ◽  
Vol 13 (3) ◽  
pp. 856-876 ◽  
Author(s):  
Justin Sheffield ◽  
Ben Livneh ◽  
Eric F. Wood

Abstract The North American Regional Reanalysis (NARR) is a state-of-the-art land–atmosphere reanalysis product that provides improved representation of the terrestrial hydrologic cycle compared to previous global reanalyses, having the potential to provide an enhanced picture of hydrologic extremes such as floods and droughts and their driving mechanisms. This is partly because of the novel assimilation of observed precipitation, state-of-the-art land surface scheme, and higher spatial resolution. NARR is evaluated in terms of the terrestrial water budget and its depiction of drought at monthly to annual time scales against two offline land surface model [Noah v2.7.1 and Variable Infiltration Capacity (VIC)] simulations and observation-based runoff estimates over the continental United States for 1979–2003. An earlier version of the Noah model forms the land component of NARR and so the offline simulation provides an opportunity to diagnose NARR land surface variables independently of atmospheric feedbacks. The VIC model has been calibrated against measured streamflow and so provides a reasonable estimate of large-scale evapotranspiration. Despite similar precipitation, there are large differences in the partitioning of precipitation into evapotranspiration and runoff. Relative to VIC, NARR and Noah annual evapotranspiration is biased high by 28% and 24%, respectively, and the runoff ratios are 50% and 40% lower. This is confirmed by comparison with observation-based runoff estimates from 1130 small, relatively unmanaged basins across the continental United States. The overestimation of evapotranspiration by NARR is largely attributed to the evapotranspiration component of the Noah model, whereas other factors such as atmospheric forcings or biases induced by precipitation assimilation into NARR play only a minor role. A combination of differences in the parameterization of evapotranspiration and in particular low stomatal resistance values in NARR, the seasonality of vegetation characteristics, the near-surface radiation and meteorology, and the representation of soil moisture dynamics, including high infiltration rates and the relative coupling of soil moisture with baseflow in NARR, are responsible for the differences in the water budgets. Large-scale drought as quantified by soil moisture percentiles covaries closely over the continental United States between the three datasets, despite large differences in the seasonal water budgets. However, there are large regional differences, especially in the eastern United States where the VIC model shows higher variability in drought dynamics. This is mostly due to increased frequency of completely dry conditions in NARR that result from differences in soil depth, higher evapotranspiration, early snowmelt, and early peak runoff. In the western United States, differences in the precipitation forcing contribute to large discrepancies between NARR and Noah/VIC simulations in the representation of the early 2000s drought.


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