Explicit and parameterized episodes of warm-season precipitation over the continental United States

This paper describes explicit and parameterized simulations of midsummer precipitation over the continental United States for two distinct episodes： moderate large-scale forcing and weak forcing. The objective is to demonstrate the capability of explicit convection at currently affordable grid-resolution and compare it with parameterized realizations. Under moderate forcing, 3-kin grid-resolution explicit simulations represent rainfall coherence remarkably well. The observed daily convective generation near the Continental Divide and the subsequent organization and propagation are reproduced qualitatively. The propagation speed, zonal extent and duration of the rainfall streaks compare favorably with their observed counterparts, although the streak frequency is underestimated. The simulations at -10-km grid-resolution applying conventional convective parameterization schemes also replicate reasonably well the diurnal convective regeneration in moderate forcing. The performance of the 3-km grid-resolution model demonstrates the potential of -1-km-resolution explicit cloud-resolving models for the prediction of warm season precipitation for moderately forced environments. In weak forcing conditions, however, predictions of precipitation coherence and diurnal variability are much poorer. This suggests that an even finer resolution explicit model is required to adequately treat convective initiation and upscale organization typical of the warm season over the continental U.S.     

Characterizing the distribution of observed precipitation and runoff over the continental United States

This paper describes the development of a comprehensive geographic database of historical precipitation and runoff measurements for the conterminous U.S. The database is used in a spatial analysis to characterize large scale precipitation and runoff patterns and to assess the utility and limitations of using historical hydro-meteorological data for providing spatially distributed precipitation estimates at regional and continental scales. Long-term annual average precipitation (P) and runoff (Q) surfaces (geographically referenced, digital representations of a continuous spatial distribution) generated from interpolation of point measurements are used in a distributed water balance calculation to check the reliability of precipitation estimates. The resulting input-output values (P- Q) illustrate the deficiency (sparse distribution and low elevation bias) of historical precipitation measurements in the mountainous western U.S. where snowmelt is an important component of the annual runoff. The incorporation of high elevation snow measurements into the precipitation record significantly improves the water balance estimates in some areas and enhances the utility of historical data for providing spatially distributed precipitation estimates in topographically diverse regions. Regions where the use of historical precipitation data may be most limited for precipitation estimation are identified and alternatives to the use of interpolated historical data for precipitation estimation across large heterogenous regions are suggested. The research establishes a database for continental scale studies and provides direction for the successful development of spatially distributed regional scale water balance models.     

Spuriously induced precipitation trends in the southeast United States

This study uses correlation and multiple regression techniques to document differences in annual and seasonal precipitation trends between the NCDC Climate Division database and the United States Historical Climate Network (USHCN) in the southeast United States. Findings indicate that the majority of climate divisions have different temporal patterns than those depicted by the USHCN. They did not, however, consistently possess statistically significant relationships between the ratio (CDD/USHCN) and changes in mean station location as noted in other studies. It appears that other influences cause the majority of the variance between the two datasets. The fact that the two datasets do not consistently agree, however, suggests that spuriously induced trends may be present in the NCDC Climate Division database.     

A subgrid-scale model for large-eddy simulation of planetary boundary-layer flows

A long-standing problem in large-eddy simulations (LES) of the planetary boundary layer (PBL) is that the mean wind and temperature profiles differ from the Monin-Obukhov similarity forms in the surface layer. This shortcoming of LES has been attributed to poor grid resolution and inadequate sub-grid-scale (SGS) modeling. We study this deficiency in PBL LES solutions calculated over a range of shear and buoyancy forcing conditions. The discrepancy from similarity forms becomes larger with increasing shear and smaller buoyancy forcing, and persists even with substantial horizontal grid refinement. With strong buoyancy forcing, however, the error is negligible.In order to achieve better agreement between LES and similarity forms in the surface layer, a two-part SGS eddy-viscosity model is proposed. The model preserves the usual SGS turbulent kinetic energy formulation for the SGS eddy viscosity, but it explicitly includes a contribution from the mean flow and a reduction of the contributions from the turbulent fluctuations near the surface. Solutions with the new model yield increased fluctuation amplitudes near the surface and better correspondence with similarity forms out to a distance of 0.1–0.2 times the PBL depth, i.e., a typical surface-layer depth. These results are also found to be independent of grid anisotropy. The new model is simple to implement and computationally inexpensive.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Out-phased decadal precipitation regime shift in China and the United States

Theoretical and Applied Climatology - In order to understand the changes in precipitation variability associated with the climate shift around mid-1970s, the precipitation regime changes have been...     

Improvements in WRF simulation skills of southeastern United States summer rainfall: physical parameterization and horizontal resolution

Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang–McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang–McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang–McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang–McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution.     

Synoptic and mesoscale controls on the isotopic composition of precipitation in the western United States

We present a new event-scale catalog of stable isotopic measurements from 5?years of storm events at 4 sites in southern California, which is used to understand the storm to storm controls on the isotopic composition of precipitation and validate the event-scale performance of an isotope-enabled GCM simulation (IsoGSM) (Yoshimura et?al. 2008). These analyses are motivated to improve the interpretation of proxy records from this region and provide guidance in testing the skill of GCMs in reproducing the hydrological variability in the western US. We find that approximately 40% of event-scale isotopic variability arises from the percentage of precipitation that is convective and the near surface relative humidity in the days prior to the storms landfall. The additional isotopic variability arises from the fact that storms arriving from different source regions advect moisture of distinct isotopic compositions. We show using both field correlation and Lagrangian trajectory analysis that the advection of subtropical and tropical moisture is important in producing the most isotopically enriched precipitation. The isotopic catalog is then used along with satellite-derived δD retrievals of atmospheric moisture to benchmark the performance of the IsoGSM model for the western US. The model is able to successfully replicate the observed isotopic variability suggesting that it is closely reproducing the moisture transport and storm track dynamics that drive the large storm-to-storm isotopic range. Notably, we find that an increase in moisture flux from the central tropical Pacific leads to a convergence of isotopically enriched water vapor in the subtropics and consequently an increase in δ¹⁸O of precipitation at sites along the entire west coast. Changes in poleward moisture flux from the central Tropical Pacific have important implications for both the global hydrological cycle and regional precipitation amounts and we suggest such changes can be captured through instrumental and proxy-reconstruction of the spatiotemporal isotopic patterns in the precipitation along the west coast of the US.     

The effect of horizontal resolution on simulation of very extreme US precipitation events in a global atmosphere model

We investigate the ability of a global atmospheric general circulation model (AGCM) to reproduce observed 20 year return values of the annual maximum daily precipitation totals over the continental United States as a function of horizontal resolution. We find that at the high resolutions enabled by contemporary supercomputers, the AGCM can produce values of comparable magnitude to high quality observations. However, at the resolutions typical of the coupled general circulation models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, the precipitation return values are severely underestimated.     

On the role of resolution and topography in the simulation of East Asia precipitation

Summary In this paper, we investigate the role that horizontal resolution plays in the simulation of East Asia precipitation. Two sets of numerical experiments are performed using the Regional Climate Model (RegCM2) nested in one-way mode within the CSIRO global coupled atmosphere-ocean model. In the first set we use the actual RegCM2 topography at the selected model resolutions, which are 45, 60, 90, 120, 180, 240 and 360 km. In the second set of the experiments, the same coarse CSIRO model topography is used in all simulations using the different resolutions of the first set. The results demonstrate that the simulation of East Asian precipitation improves as the horizontal resolution is increased. Moreover, it is shown that the simulations using a higher resolution along with the coarse CSIRO topography perform better than the simulations using a coarser model resolution with corresponding model topography. This suggests that over East Asia adequate spatial resolution to resolve the physical and dynamical processes is more important than topography. Lastly, the results indicate that model resolutions of 60 km or higher are needed to accurately simulate the distribution of precipitation over China and East Asia.     

Climate change and the demand for recreational ecosystem services on public lands in the continental United States

Cultural ecosystem services represent nonmaterial benefits people derive from the environment; these benefits include outdoor recreation opportunities. Changes in climatic conditions are likely to shift the spatial and temporal demand for recreational ecosystem services. To date, little is known about the magnitude and spatial variability in these shifts across large geographic extents. We use 14 years of geotagged social media data to explore how the climatological mean of maximum temperature affects the demand for recreational ecosystem services by season across public lands in the continental United States. We also investigate how the demand for recreational ecosystem services on public lands may change by 2050 under two climate change scenarios, RCP 4.5 and RCP 8.5. Across all public lands in the continental U.S., demand for recreational ecosystem services is expected to decrease 18% by 2050 under RCP 4.5 in the summer, but increase 12% in the winter and 5% in the spring, with no significant changes in the fall. There is substantial variation in the magnitude of projected changes by region. In the spring and fall, some regions are likely to see an increase in the demand for recreational ecosystem services (e.g., Arkansas-Rio Grande-Texas-Gulf), while others will see declines (e.g., South Atlantic Gulf, California Great Basin). Our findings suggest the total demand for recreational ecosystem services across the continental U.S. is expected to decline under warming temperatures. However, there is a large amount of variation in where, when, and by how much, demand will change. The peak season for visiting public lands is likely to lengthen in the continental U.S. as the climate continues to warm, with demand declining in the summer and growing in the off-season.     

Sub-regional seasonal precipitation linkages to SOI and PDO in the Southwest United States

This paper highlights the relationship between precipitation variability at the sub-regional level in the Southwest United States and the SOI and PDO climate teleconnection indices during the period 1950–2000. Statistical correlations at α = 0.05 and 0.01 levels are calculated for fall, winter, and spring precipitation in the Southwest, and contemporaneous and antecedent seasonal SOI and PDO index values. A strong SOI-winter precipitation signal is seen to progress across Arizona and New Mexico from southwest to northeast over a three-season lagged period. The PDO also exhibits a strong relationship with winter and spring precipitation in New Mexico; however, the PDO is not well correlated with precipitation in Arizona. The results underscore the non-uniform spatio-temporal relationships of the SOI and PDO indices as they relate to the precipitation regime of the Southwest, and provide a framework for future diagnostic analyses of these relationships.     

Spatial and temporal characteristics of intraseasonal oscillations of precipitation over the United States

Summary  This study shows that precipitation over the United States has two time scales of intraseasonal variation at about 37 days and 24 days. The results are derived from the application of a combination of statistical methods including principal component analysis (PCA), singular spectrum analysis (SSA), and multi-channel singular spectrum analysis (MSSA) to over 10 years of gridded daily precipitation records. Both oscillations have largest amplitude during the cold season. The 37-day oscillation has larger interannual variability. Intraseasonal oscillations are most significant in the Pacific Northwest. The 37-day oscillation has opposite phases between the western and eastern United States, while the 24-day oscillation has the same phases. These intraseasonal time scale precipitation variations may be associated with previously revealed mid-tropospheric circulation anomalies that oscillate at similar time scales. Received February 7, 2000 Revised October 20, 2000     

Evaluation of high-resolution simulations of daily-scale temperature and precipitation over the United States

Extreme climate events have been increasing over much of the world, and dynamical models predict further increases in response to enhanced greenhouse forcing. We examine the ability of a high-resolution nested climate model, RegCM3, to capture the statistics of daily-scale temperature and precipitation events over the conterminous United States, using observational and reanalysis data for comparison. Our analyses reveal that RegCM3 captures the pattern of mean, interannual variability, and trend in the tails of the daily temperature and precipitation distributions. However, consistent biases do exist, including wet biases in the topographically-complex regions of the western United States and hot biases in the southern and central United States. The biases in heavy precipitation in the western United States are associated with excessively strong surface and low-level winds. The biases in daily-scale temperature and precipitation in the southcentral United States are at least partially driven by biases in circulation and moisture fields. Further, the areas of agreement and disagreement with the observational data are not intuitive from analyzing the simulated mean seasonal temperature and precipitation fields alone. Our evaluation should enable more informed application and improvement of high-resolution climate models for the study of future changes in socially- and economically-relevant temperature and precipitation events.     

Evaluation of climate change over the continental United States using a moisture index

This paper uses a modified form of Thornthwaite’s moisture index to better quantify climate variability by integrating the effects of temperature and precipitation. Using the moisture index, trends were evaluated over the last 112 years (1895–2006), when unique changes in temperature and precipitation have been documented to have occurred. In addition, data on potential evapotranspiration and the moisture index were used to investigate changing climate and vegetation regions. The results show that the eastern half of the country has been getting wetter, even as temperatures have continued to increase in many areas. In particular, conditions have become wetter in the South, Northeast, and East North Central regions. The changing climate is illustrated by computing climate and vegetation regions for three 30-year periods (1910–1939, 1940–1969, and 1970–1999). Climate regions based on the moisture index show an expansion of the Humid region (where precipitation vastly exceeds climatic demands for water) across the East as well as a westward shift in the zero moisture index line. In terms of vegetation zones, the most dramatic change occurs across the Midwestern prairie peninsula where the wetter conditions lead to a westward expansion of conditions favorable for oak–hickory–pine vegetation.     

利用深度学习预报美国东北部日降水分布

现阶段降水预报主要依靠数值天气预报模式。但受物理参数化、计算资源等因素的影响,基于数值模式的降水预报还存在非常大的不确定性。近年来,深度学习在天气预报领域显示出巨大优势和潜力。本文通过构建神经网络预报美国东北部日降水分布,探讨神经网络模型基于低分辨率气象场(ERA-Interim, 0.7°)预报高分辨率降水(CPC,0.25°)的能力,并比较3种主流网络框架(VGG,ResNet, GoogleNet)在该任务中的表现。结果表明,3种网络框架都对美国东北部日降水分布具有一定的预报能力(VGG框架表现最优),但三者的均方根误差(RMSE)均高于ERA-Interim 24-h(ERA24)的降水预报。3种神经网络的集合预报结果优于ERA24预报,且这三者与ERA24预报结果的集合平均能够显著提高ERA24对不同季节、不同强度降水的预报。     

Effects of Land Use on the Climate of the United States

Land use practices have replaced much of the natural needleleaf evergreen, broadleaf deciduous, and mixed forests of the Eastern United States with crops. To a lesser extent, the natural grasslands in the Central United States have also been replaced with crops. Simulations with a land surface process model coupled to an atmospheric general circulation model show that the climate of the United States with modern vegetation is significantly different from that with natural vegetation. Three important climate signals caused by modern vegetation are: (1) 1 °C cooling over the Eastern United States and 1 °C warming over the Western United States in spring; (2) summer cooling of up to 2 °C over a wide region of the Central United States; and (3) moistening of the near-surface atmosphere by 0.5 to 1.5 g kg^-1over much of the United States in spring and summer. Although individual months show large, statistically significant differences in precipitation due to land-use practices, these differences average out over the course of the 3-month seasons. These changes in surface temperature and moisture extend well into the atmosphere, up to 500 mb, and affect the boundary layer and atmospheric circulation. The altered climate is due to reduced surface roughness, reduced leaf and stem area index, reduced stomatal resistance, and increased surface albedo with modern vegetation compared to natural vegetation. The climate change caused by land use practices is comparable to other well known anthropogenic climate forcings. For example, it would take 100 to 175 years at the current, observed rate of summer warming over the United States to offset the cooling from deforestation. The summer sulfate aerosol forcing completely offsets the greenhouse forcing over the Eastern United States. Similarly, the climatic effect of North American deforestation, with extensive summer cooling, further offsets the greenhouse forcing.