Christopher L. Castro

The relationship of the North American Monsoon to tropical and North Pacific Sea surface temperatures as revealed by observational analyses

The North American monsoon is a seasonal shift of upper- and low-level pressure and wind patterns that brings summertime moisture into the southwest United States and ends the late spring wet period in the Great Plains. The interannual variability of the North American monsoon is examined using the NCEP-NCAR reanalysis (1948-98). The diurnal and seasonal evolution of 500-mb geopotential height, integrated moisture flux, and integrated moisture flux convergence are constructed using a 5-day running mean for the months May through September. All of the years are used to calculate an average daily Z score that removes the diurnal, seasonal, and intraseasonal variability. The 30-day average Z score centered about the date is correlated with Pacific sea surface temperature anomaly (SSTA) indices associated with the El Nino-Southern Oscillation (ENSO) and the North Pacific oscillation (NPO). These indices are Nino-3, a North Pacific index, and a Pacific index that combines the previous two. Regional time-evolving precipitation indices for the Southwest and Great Plains, which consider the total number of wet or dry stations in a region, are also correlated with the SSTA indices. The use of nonnormally distributed point source precipitation data is avoided. Teleconnections are computed relative to the climatological evolution of the North American monsoon, rather than to calendar months, thus more accurately accounting for the climatological changes in the large-scale circulation. Tropical and North Pacific SSTs are related to the occurrence of the Pacific Transition and East Pacific teleconnection patterns, respectively, in June and July. A high (low) NPO phase and El Nino (La Nina) conditions favor a weaker (stronger) and southward (northward) displaced monsoon ridge. These teleconnection patterns affect the timing and large-scale distribution of monsoon moisture. In the Great Plains, the spring wet season is lengthened (shortened) and early summer rainfall and integrated moisture flux convergence are above (below) average. In the Southwest, monsoon onset is late (early) and early summer rainfall and integrated moisture flux convergence are below (above) average. Relationships with Pacific SSTA indices decay in the later part of the monsoon coincident with weakening of the jet stream across the Pacific and strengthening of the monsoon ridge over North America. The most coherent summer climate patterns occur over the entire western United States when the Pacific index is substantially high or low, such as during the Midwest flood of 1993 and drought of 1988. The Pacific index in spring is a good predictor of early summer height anomalies over the western United States when the time evolution of the North Pacific SST dipole is considered.

Distinguishing Pronounced Droughts in the Southwestern United States: Seasonality and Effects of Warmer Temperatures

Abstract Higher temperatures increase the moisture-holding capacity of the atmosphere and can lead to greater atmospheric demand for evapotranspiration, especially during warmer seasons of the year. Increases in precipitation or atmospheric humidity ameliorate this enhanced demand, whereas decreases exacerbate it. In the southwestern United States (Southwest), this means the greatest changes in evapotranspirational demand resulting from higher temperatures could occur during the hot–dry foresummer and hot–wet monsoon. Here seasonal differences in surface climate observations are examined to determine how temperature and moisture conditions affected evapotranspirational demand during the pronounced Southwest droughts of the 1950s and 2000s, the latter likely influenced by warmer temperatures now attributed mostly to the buildup of greenhouse gases. In the hot–dry foresummer during the 2000s drought, much of the Southwest experienced significantly warmer temperatures that largely drove greater evapotranspir...

Investigation of the Summer Climate of the Contiguous United States and Mexico Using the Regional Atmospheric Modeling System (RAMS). Part I: Model Climatology (1950–2002)

Abstract Fifty-three years of the NCEP–NCAR Reanalysis I are dynamically downscaled using the Regional Atmospheric Modeling System (RAMS) to generate a regional climate model (RCM) climatology of the contiguous United States and Mexico. Data from the RAMS simulations are compared to the recently released North American Regional Reanalysis (NARR), as well as observed precipitation and temperature data. The RAMS simulations show the value added by using a RCM in a process study framework to represent North American summer climate beyond the driving global atmospheric reanalysis. Because of its enhanced representation of the land surface topography, the diurnal cycle of convective rainfall is present. This diurnal cycle largely governs the transitions associated with the evolution of the North American monsoon with regards to rainfall, the surface energy budget, and surface temperature. The lower frequency modes of convective rainfall, though weaker, account for rainfall variability at a remote distance from...

Can a regional climate model improve the ability to forecast the North American monsoon

AbstractGlobal climate models are challenged to represent the North American monsoon, in terms of its climatology and interannual variability. To investigate whether a regional atmospheric model can improve warm season forecasts in North America, a retrospective Climate Forecast System (CFS) model reforecast (1982–2000) and the corresponding NCEP–NCAR reanalysis are dynamically downscaled with the Weather Research and Forecasting model (WRF), with similar parameterization options as used for high-resolution numerical weather prediction and a new spectral nudging capability. The regional model improves the climatological representation of monsoon precipitation because of its more realistic representation of the diurnal cycle of convection. However, it is challenged to capture organized, propagating convection at a distance from terrain, regardless of the boundary forcing data used. Dynamical downscaling of CFS generally yields modest improvement in surface temperature and precipitation anomaly correlations...

Comparison of land-precipitation coupling strength using observations and models.

Abstract Numerous studies have attempted to address the land–precipitation coupling, but scientists’ understanding remains limited and discrepancies still exist from different studies. A new parameter Γ is proposed here to estimate the land–precipitation coupling strength based on the ratio of the covariance between monthly or seasonal precipitation and evaporation anomalies (from their climatological means) over the variance of precipitation anomalies. The Γ value is easy to compute and insensitive to the horizontal scales used; however, it does not provide causality. A relatively high Γ is a necessary—but not sufficient—condition for a relatively strong land–precipitation coupling. A computation of Γ values using two global reanalyses (ECMWF and NCEP), one regional reanalysis [North American Regional Reanalysis (NARR)], and observed precipitation along with Variable Infiltration Capacity (VIC)-derived evaporation data indicates that the land–precipitation coupling is stronger in summer and weaker in win...

The Relationship of Transient Upper-Level Troughs to Variability of the North American Monsoon System

Relationships between transient upper-tropospheric troughs and warm season convective activity over the southwest United States and northern Mexico are explored. Analysis of geopotential height and vorticity fields from the North American Regional Reanalysis and cloud-to-ground lightning data indicates that the passage of mobile inverted troughs (IVs) significantly enhances convection when it coincides with the peak diurnal cycle (1800‐0900 UTC) over the North American monsoon (NAM) region. The preferred tracks of IVs during early summer are related to the dominant modes of Pacific sea surface temperature (SST) var

Atmospheric Rivers and Cool Season Extreme Precipitation Events in the Verde River Basin of Arizona

AbstractInland-penetrating atmospheric rivers (ARs) can affect the southwestern United States and significantly contribute to cool season (November–March) precipitation. In this work, a climatological characterization of AR events that have led to cool season extreme precipitation in the Verde River basin (VRB) in Arizona for the period 1979/80–2010/11 is presented. A “bottom up” approach is used by first evaluating extreme daily precipitation in the basin associated with AR occurrence, then identifying the two dominant AR patterns (referred to as Type 1 and Type 2, respectively) using a combined EOF statistical analysis. The results suggest that AR events in the Southwest do not form and develop in the same regions. Water vapor content in Type 1 ARs is obtained from the tropics near Hawaii (central Pacific) and enhanced in the midlatitudes, with maximum moisture transport over the ocean at low levels of the troposphere. On the other hand, moisture in Type 2 ARs has a more direct tropical origin and merid...

Coupling terrestrial and atmospheric water dynamics to improve prediction in a changing environment

Humans have profoundly influenced their environment. It has been estimated that nearly one-third of the global land cover has been modified while approximately 40% of the photosynthesis has been appropriated. As the interface between the subsurface and the atmosphere is altered, it is imperative that we understand the influence this alteration has in terms of changing regional and global climates. Land surface heterogeneity is sometimes a principal modulator of local and regional climates and, as such, there are potential aggregation and teleconnection effects ranging in scales from soil pores to the general atmospheric circulation when the land surface is altered across a range of scales. The human fingerprint on land surface processes is critical and must also be accounted for in the discourse on land-atmosphere coupling as it pertains to climate and global change as well as local processes such as evapotranspiration and streamflow. It is at this pivotal interface where hydrologists, atmospheric scientists and ecologists must understand how their disciplines interact and influence each other.Fluxes across the land-surface directly influence predictions of ecological processes, atmospheric dynamics, and terrestrial hydrology. However, many simplifications are made in numerical models when considering terrestrial hydrology from the view point of the atmosphere and visa-versa. While this may be a necessity in the current generation of operational models used for forecasting, it can create obstacles to the advancement of process understanding. These simplifications can limit the numerical prediction capabilities on how water partitions itself throughout all phases of the water cycle. The feedbacks between terrestrial and atmospheric water dynamics are not well understood or represented by the current generation of operational land-surface and atmospheric models. This can lead to erroneous spatial patterns and anomalous temporal persistence in land-atmosphere exchanges and atmospheric water cycle predictions. Cross-disciplinary efforts are needed not only to identify but also to quantify feedbacks between terrestrial and atmospheric water at appropriate spatiotemporal scales. This is especially true as today’s young scientists set their sights on improving process understanding and prediction skill from both research and operational models used to describe such linked systems.In recognition of these challenges, a junior faculty and early career scientist forum was recently held at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado with the intent of identifying and characterizing feedback interactions, and their attendant spatial and temporal scales, important for coupling terrestrial and atmospheric water dynamics. The primary focus of this forum is on improved process understanding, rather than operational products, as the possibility of incorporating more realistic physics into operational models is computationally prohibitive. We approached the subject of improved predictability through better process understanding by focusing on the following three framework questions described and discussed below.

Spatiotemporal Variability of Precipitation, Modeled Soil Moisture, and Vegetation Greenness in North America within the Recent Observational Record

Abstract Dominant spatiotemporal patterns of precipitation, modeled soil moisture, and vegetation are determined in North America within the recent observational record (late twentieth century onward). These data are from a gridded U.S.–Mexico precipitation product, retrospective long-term integrations of two land surface models, and satellite-derived vegetation greenness. The analysis procedure uses three statistical techniques. First, all the variables are normalized according to the standardized precipitation index procedure. Second, dominant patterns of spatiotemporal variability are determined using multitaper method–singular value decomposition for interannual and longer time scales. The dominant spatiotemporal patterns of precipitation generally conform to known and distinct Pacific SST forcing in the cool and warm seasons. Two specific time scales in precipitation at 9 and 6–7 yr correspond to significant variability in soil moisture and vegetation, respectively. The 9-yr signal is related to prec...

Future climate: projected average

Global climate models (GCMs) are the fundamental drivers of regional climate-change projections (IPCC 2007). GCMs allow us to characterize changes in atmospheric circulation associated with human causes at global and continental scales. However, because of the planetary scope of the GCMs, their resolution, or level of detail, is somewhat coarse. A typical GCM grid spacing is about 62 miles (100 km) or greater, which is inadequate for creating projections and evaluating impacts of climate change at a regional scale. Thus, a “downscaling” procedure is needed to provide finer spatial detail of the model results.