James J. O’Brien

Objectively Derived Daily “Winds” from Satellite Scatterometer Data

Abstract An objective technique is used to create regularly gridded daily “wind” fields from NASA scatterometer (NSCAT) observations for the Pacific Ocean north of 40°S. The objective technique is a combination of direct minimization, and cross validation with multigridding. The fields are created from the minimization of a cost function. The cost function is developed to maximize information from the observational data and minimize smoothing. Three constraints are in the cost function: a misfit to observations, a smoothing term, and a misfit of the curl. The second and third terms are relative to a background field. The influence of the background field is controlled by weights on the smoothing constraints. Weights are objectively derived by the method of cross validation. Cross validation is a process that removes observations from the input to the cost function and determines tuning parameters (weights) by the insensitivity of the removed observations to the output field. This method is computationally...

Role of Multiple-Level Tropospheric Circulations in Forcing ENSO Winter Precipitation Anomalies

Abstract Regionally organized winter (DJF) precipitation anomalies over North America are presented in association with cold and warm phases of the El Nino–Southern Oscillation. Variations in low-level flow from moisture sources and in upper-level dynamic properties are diagnosed for each anomalous precipitation region using DJF composites of upper- and lower-tropospheric winds, sea level pressure, divergence, and vorticity advection. Variance analysis determines which precipitation and circulation patterns are robust and evaluates the predictability of the extreme phase composites with respect to the climatology. In cold phases, the Pacific Northwest and the lower Mississippi Valley regions have above-normal precipitation totals. The heavier precipitation over the Pacific Northwest is the result of a multilevel onshore flow forced by an amplified Pacific high off the California coast and a single zonal upper-tropospheric jet. In the Lower Mississippi and Tennessee Valleys, the equatorward entrance region...

A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses

We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS Land–Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability. Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their “parent” reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the “parent” reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis.

ENSO’s Impact on Regional U.S. Hurricane Activity

Abstract Regional variations in North Atlantic hurricane landfall frequency along the U.S. coastline are examined in relation to the phase of El Nino–Southern Oscillation (ENSO). ENSO warm (cold) phases are known to reduce (increase) hurricane activity in the North Atlantic basin as a whole. Using best-track data from the U.S. National Hurricane Center, regional analysis reveals that ENSO cold-phase landfall frequencies are only slightly larger than neutral-phase landfall frequencies along the Florida and Gulf coasts. However, for the East Coast, from Georgia to Maine, a significant decrease in landfall frequency occurs during the neutral ENSO phase as compared to the cold phase. Along the East Coast, two or more major (category 3 or above) hurricanes never made landfall in the observational record (1900–2004) during a single hurricane season classified as an ENSO neutral or warm phase.

Assessing Predictability of Cotton Yields in the Southeastern United States Based on Regional Atmospheric Circulation and Surface Temperatures

Abstract The potential to predict cotton yields up to one month before planting in the southeastern United States is assessed in this research. To do this, regional atmospheric variables that are related to historic summer rainfall and cotton yields were identified. The use of simulations of those variables from a global circulation model (GCM) for estimating cotton yields was evaluated. The authors analyzed detrended cotton yields (1970–2004) from 48 counties in Alabama and Georgia, monthly rainfall from 53 weather stations, monthly reanalysis data of 850- and 200-hPa winds and surface temperatures over the southeast U.S. region, and monthly predictions of the same variables from the ECHAM 4.5 GCM. Using the reanalysis climate data, it was found that meridional wind fields and surface temperatures around the Southeast were significantly correlated with county cotton yields (explaining up to 52% of the interannual variability of observed yields), and with rainfall over most of the region, especially durin...

Reconciling the Spatial Distribution of the Surface Temperature Trends in the Southeastern United States

AbstractThis study attempts to explain the considerable spatial heterogeneity in the observed linear trends of monthly mean maximum and minimum temperatures (Tmax and Tmin) from station observations in the southeastern (SE) United States (specifically Florida, Alabama, Georgia, South Carolina, and North Carolina). In a majority of these station sites, the warming trends in Tmin are stronger in urban areas relative to rural areas. The linear trends of Tmin in urban areas of the SE United States are approximately 7°F century−1 compared to about 5.5°F century−1 in rural areas. The trends in Tmax show weaker warming (or stronger cooling) trends with irrigation, while trends in Tmin show stronger warming trends. This functionality of the temperature trends with land features also shows seasonality, with the boreal summer season showing the most consistent relationship in the trends of both Tmax and Tmin. This study reveals that linear trends in Tmax in the boreal summer season show a cooling trend of about 0.5...

Model estimates hurricane wind speed probabilities

In the United States, intense hurricanes (category 3, 4, and 5 on the Saffir/Simpson scale) with winds greater than 50 m s −1 have caused more damage than any other natural disaster [Pielke and Pielke, 1997]. Accurate estimates of wind speed exceedance probabilities (WSEP) due to intense hurricanes are therefore of great interest to (re)insurers, emergency planners, government officials, and populations in vulnerable coastal areas. The historical record of U.S. hurricane landfall is relatively complete only from about 1900, and most model estimates of WSEP are derived from this record. During the 1899–1998 period, only two category-5 and 16 category-4 hurricanes made landfall in the United States. The historical record therefore provides only a limited sample of the most intense hurricanes.

A New FSU Winds Climatology

Abstract A new objective time series of in situ–based monthly surface winds has been developed as a replacement for the subjective tropical Pacific Florida State University (FSU) winds. The new time series begins in January 1978, and it is ongoing. The objective method distinguishes between observations from volunteer observing ships (VOSs) and buoys, allowing different weights for these different types of observations. An objective method is used to determine these weights and accounts for the differences in error characteristics and in spatial/temporal sampling. A comparison is made between the objective and subjective products, as well as scatterometer winds averaged monthly on the same grid. The scatterometer fields are a good proxy for truth. These three sets of fields have similar magnitudes, directions, and derivative fields. Both in situ wind products underestimate convergence about the intertropical convergence zone; however, the objective FSU product is a much better match to the scatterometer o...

Interannual Variability of Synthesized FSU and NCEP-NCAR Reanalysis Pseudostress Products over the Pacific Ocean

Abstract A technique is applied to seamlessly blend height-adjusted Florida State University (FSU) surface wind pseudostress with National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis-based pseudostress over the Pacific Ocean. The FSU pseudostress is shown to be of higher quality in the equatorial Pacific and thus dominates the analysis in that region, while the NCEP–NCAR reanalysis-based pseudostress is used outside the equatorial region. The blending technique is based on a direct minimization approach. The functional to minimize consists of five constraints; each constraint is given a weight that determines its influence on the solution. The first two constraints are misfits for the FSU and NCEP–NCAR reanalysis datasets. A spatially dependent weighting that highlights the regional strengths of each dataset is designed for these misfit constraints. Climatological structure information is used as a weak smoothing constraint on the solution through L...

Seasonal Surface Air Temperature and Precipitation in the FSU Climate Model Coupled to the CLM2

The current Florida State University (FSU) climate model is upgraded by coupling the National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) as its land component in order to make a better simulation of surface air temperature and precipitation on the seasonal time scale, which is important for crop model application. Climatological and seasonal simulations with the FSU climate model coupled to the CLM2 (hereafter FSUCLM) are compared to those of the control (the FSU model with the original simple land surface treatment). The current version of the FSU model is known to have a cold bias in the temperature field and a wet bias in precipitation. The implementation of FSUCLM has reduced or eliminated this bias due to reduced latent heat flux and increased sensible heat flux. The role of the land model in seasonal simulations is shown to be more important during summertime than wintertime. An additional experiment that assimilates atmospheric forcings produces improved land-model initial conditions, which in turn reduces the biases further. The impact of various deep convective parameterizations is examined as well to further assess model performance. The land scheme plays a more important role than the convective scheme in simulations of surface air temperature. However, each convective scheme shows its own advantage over different geophysical locations in precipitation simulations.