Spuriously induced temperature trends in the Southeast United States

Summary This study uses correlation and multiple regression techniques to document differences in annual temperature trends between the National Climatic Data Center (NCDC) Climate Division Database (CDD) and the United States Historical Climate Network (USHCN) for the Southeast United States. Results indicate that an increase (decrease) in elevation and a northward (southward) shift in mean station location in the CDD correspond with decreases (increases) in temperature. Although the movement of station locations in the CDD showed only modest impacts on trends, the effects of the movements are statistically significant, and explain some of the variances in the temperature trends. Results therefore suggest that climate divisions with more rugged terrain and greater shifts in elevation are more susceptible to spuriously generated trends.     

Terrestrial carbon pools in southeast and south-central United States

Analyses of regional carbon sources and sinks are essential to assess the economical feasibility of various carbon sequestration technologies for mitigating atmospheric CO₂ accumulation and for preventing global warming. Such an inventory is a prerequisite for regional trading of CO₂ emissions. As a U.S. Department of Energy Southeast Regional Carbon Sequestration Partner, we have estimated the state-level terrestrial carbon pools in the southeast and south-central US. This region includes: Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia. We have also projected the potential for terrestrial carbon sequestration in the region. Texas is the largest contributor (34%) to greenhouse gas emission in the region. The total terrestrial carbon storage (forest biomass and soils) in the southeast and south-central US is estimated to be 130 Tg C/year. An annual forest carbon sink (estimated as 76 Tg C/year) could compensate for 13% of the regional total annual greenhouse gas emission (505 Tg C, 1990 estimate). Through proper policies and the best land management practices, 54 Tg C/year could be sequestered in soils. Thus, terrestrial sinks can capture 23% of the regional total greenhouse emission and hence are one of the most cost-effective options for mitigating greenhouse emission in the region.     

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...     

Heat waves in the United States: definitions, patterns and trends

High temperatures and heat waves are related but not synonymous concepts. Heat waves, generally understood to be acute periods of extreme warmth, are relevant to a wide range of stakeholders because of the impacts that these events have on human health and activities and on natural environments. Perhaps because of the diversity of communities engaged in heat wave monitoring and research, there is no single, standard definition of a heat wave. Experts differ in which threshold values (absolute versus relative), duration and ancillary variables to incorporate into heat wave definitions. While there is value in this diversity of perspectives, the lack of a unified index can cause confusion when discussing patterns, trends, and impacts. Here, we use data from the North American Land Data Assimilation System to examine patterns and trends in 15 previously published heat wave indices for the period 1979–2011 across the Continental United States. Over this period the Southeast region saw the highest number of heat wave days for the majority of indices considered. Positive trends (increases in number of heat wave days per year) were greatest in the Southeast and Great Plains regions, where more than 12 % of the land area experienced significant increases in the number of heat wave days per year for the majority of heat wave indices. Significant negative trends were relatively rare, but were found in portions of the Southwest, Northwest, and Great Plains.     

Multiseason evaluation of the MM5, COAMPS and WRF over southeast United States

Three models, MM5, COAMPS, and WRF, have been applied for the warm season in 2003 and the cool season in 2003?C2004 to evaluate their performances. All models run over the same domain area covering the north Gulf Mexico and southeastern United States (US) region with the same spatial resolution of 27?km. It was found that the temporal variations of the mean error distribution and strength at 24 and 36?h were rather weak for surface temperature, sea level pressure, and surface wind speed for all models. A warm bias in surface temperature forecasts dominated over land during the warm season, whereas a cool bias existed during the cool season. The MM5 and WRF produced negative biases of sea level pressure during the warm season and positive biases during the cool season while the COAMPS yielded a similar distribution of sea level pressure biases during both seasons. During both seasons, similar surface wind speed biases produced by each model included a high wind speed forecast over most areas by MM5 while the COAMPS and WRF yielded weak surface winds over the western Plains and stronger surface winds over the eastern Plains. Root-mean-squared errors revealed that the forecast of surface temperature, sea level pressure, and surface wind speed were degraded with the increase of forecast time. For rainfall evaluation, it was found that the MM5 underpredicted seasonal precipitation while the COAMPS and WRF overpredicted. The bias scores revealed that the MM5 yielded an underprediction of the coverage of precipitation areas, especially for heavier rainfall events. The MM5 presented the lower threat score at lighter rainfall events compared to the COAMPS and WRF. For moderate and heavier thresholds, all models lacked forecast accuracy. The WRF accuracy in predicting precipitation was heavily dependent upon the performance of the selected cumulus parameterization scheme. Use of the Grell?CDevenyi and Bette?CMiller?CJanjic schemes helps suppress precipitation overprediction.     

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.     

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。     

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.     

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.     

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.     

Effects of model resolution and subgrid-scale physics on the simulation of precipitation in the continental United States

We analyze simulations of the global climate performed at a range of spatial resolutions to assess the effects of horizontal spatial resolution on the ability to simulate precipitation in the continental United States. The model investigated is the CCM3 general circulation model. We also preliminarily assess the effect of replacing cloud and convective parameterizations in a coarse-resolution (T42) model with an embedded cloud-system resolving model (CSRM). We examine both spatial patterns of seasonal-mean precipitation and daily time scale temporal variability of precipitation in the continental United States. For DJF and SON, high-resolution simulations produce spatial patterns of seasonal-mean precipitation that agree more closely with observed precipitation patterns than do results from the same model (CCM3) at coarse resolution. However, in JJA and MAM, there is little improvement in spatial patterns of seasonal-mean precipitation with increasing resolution, particularly in the southeast USA. This is because of the dominance of convective (i.e., parameterized) precipitation in these two seasons. We further find that higher-resolution simulations have more realistic daily precipitation statistics. In particular, the well-known tendency at coarse resolution to have too many days with weak precipitation and not enough intense precipitation is partially eliminated in higher-resolution simulations. However, even at the highest resolution examined here (T239), the simulated intensity of the mean and of high-percentile daily precipitation amounts is too low. This is especially true in the southeast USA, where the most extreme events occur. A new GCM, in which a cloud-resolving model (CSRM) is embedded in each grid cell and replaces convective and stratiform cloud parameterizations, solves this problem, and actually produces too much precipitation in the form of extreme events. However, in contrast to high-resolution versions of CCM3, this model produces little improvement in spatial patterns of seasonal-mean precipitation compared to models at the same resolution using traditional parameterizations.     

Atmospheric moisture budget and its regulation of the summer precipitation variability over the Southeastern United States

Atmospheric moisture budget and its regulation of the summer (June–July–August) precipitation over the Southeastern United State (SE U.S.) were examined during 1948–2007 using PRECipitation REConstruction over Land and multiple reanalysis datasets. The analysis shows that the interannual variation of SE U.S. summer precipitation can be largely explained by the leading Empirical Orthogonal Function mode showing a spatially homogenous sub-continental scale pattern. Consequently, areal-averaged precipitation was investigated to focus on the large-scale rainfall changes over the SE U.S. The wavelet analysis identifies an increased 2–4 year power spectrum in recent 30 years (1978–2007), suggesting an intensification of the interannual variability. Analysis of the atmospheric moisture budget indicates that the increase in precipitation variability is mainly caused by moisture transport, which exhibits a similar increase in the 2–4 year power spectrum for the same period. Moisture transport, in turn, is largely controlled by the seasonal mean component rather than the subseasonal-scale eddies. Furthermore, our results indicate that dynamic processes (atmospheric circulation) are more important than thermodynamic processes (specific humidity) in regulating the interannual variation of moisture transport. Specifically, the North Atlantic Subtropical High western ridge position is found to be a primary regulator, with the ridge in the northwest (southwest) corresponding to anomalous moisture divergence (convergence) over the SE U.S. Changes in moisture transport consistent with the increased frequency of these two ridge types in recent 30 years favor the intensification of summer precipitation variability.     

最优化处理法估测黔西南地区降水

利用2004年多普勒雷达资料及自动站雨量资料,在黔西南地区进行降水估计。采用最优化处理法得到该区域的Z-I关系。选取2005年1~7月的部分资料进行检验对比,并对误差进行分析。结果表明,用此方法得出的Z-I适用性较好,准确率达80%以上。     

黔东南州近21a的降水气候特征分析

该文利用统计分析方法对黔东南州16个气象观测站1985-2005年共21a的各级降水量、四季降水,降水日数、降水强度进行分析;结果表明：黔东南州近21a平均降水量为1003．8—1366．7mm,年平均降水量≥1300mm的地区主要是丹寨、麻江、黎平、锦屏;年平均降水量在1100以下的有黄平、施秉、镇远、三穗;黔东南州各县日降水量≥0．1mm的降水日数年平均154～192d,其分布趋势由州西部分别向北部、南部递减,最多为麻江192d,最少为从江的154d;降水强度（单位时间内的降水量）的大小取决于降水量和降水时间,降水时间越短而降水量越大,则降水强度越大;州内各地降水以小雨为主。年平均为119～157d,占年总雨量的77％～82％,以麻江157d最多,从江119d为少,此研究结果可为农业生产和气象预报及气象公共服务提供参考。