Journal of Applied Meteorology and Climatology

Wind measurement offers an essential data source for a wide range of practices in the fields of meteorology and wind engineering. However, records of surface winds are usually influenced by terrain/topographic effects, and direct usage of raw data may bring in nonignorable errors for follow-up applications. A data-driven standardization scheme was recently proposed by the authors to convert the surface wind measurements over rugged terrain into their potential values corresponding to reference conditions, that is, for neutral winds at a height of 10 m above open flat terrain (z₀ = 0.03 m). As a complementary part of the preceding work, this study focuses on the standardization of surface wind speeds with marine exposures. The effect of wind strength on the roughness of the sea surface is further taken into account, with emphasis on the difference between deep-ocean and shallow-water cases. As an application example, wind measurements at a buoy site near the coastal line (water depth is 14 m) are adjusted to their potential values, which are then compared with those at a nearby station. The good agreement between the two sets of results demonstrates the accuracy and effectiveness of the standardization method. It is also found that the behavior of roughness length scale over shallow water may differ noticeably from that over deep ocean, especially under strong wind conditions, and an inappropriate usage of marine roughness predictors may result in significant estimation errors.

Land surface temperature and emissivity spectra are essential variables for improving models of the earth surface–atmosphere interaction or retrievals of atmospheric variables such as thermodynamic profiles, chemical composition, cloud and aerosol characteristics, and so on. In most cases, emissivity spectral variations are not correctly taken into account in climate models, leading to potentially significant errors in the estimation of surface energy fluxes and temperature. Satellite infrared observations offer the dual opportunity of accurately estimating these properties of land surfaces as well as allowing a global coverage in space and time. Here, high-spectral-resolution observations from the Infrared Atmospheric Sounder Interferometer (IASI) over the tropics (30°N–30°S), covering the period July 2007–March 2011, are interpreted in terms of 1° × 1° monthly mean surface skin temperature and emissivity spectra from 3.7 to 14 μm at a resolution of 0.05 μm. The standard deviation estimated for the surface temperature is about 1.3 K. For the surface emissivity, it varies from about 1%–1.5% for the 10.5–14- and 5.5–8-μm windows to about 4% around 4 μm. Results from comparisons with products such as Moderate Resolution Imaging Spectroradiometer (MODIS) low-resolution emissivity and surface temperature or ECMWF forecast data (temperature only) are presented and discussed. Comparisons with emissivity derived from the Airborne Research Interferometer Evaluation System (ARIES) radiances collected during an aircraft campaign over Oman and made at the scale of the IASI field of view offer valuable data for the validation of the IASI retrievals.

Since the launch of the first Advanced Very High Resolution Radiometer (AVHRR) instrument aboard the Television and Infrared Observational Satellite (TIROS-N), measurements in the 3.7-μm atmospheric window have been exploited for use in cloud detection and screening, cloud thermodynamic phase and surface snow/ice discrimination, and quantitative cloud particle size retrievals. The utility of the band has led to the incorporation of similar channels on a number of existing satellite imagers and future operational imagers. Daytime observations in the band include both reflected solar and thermal emission energy. Since 3.7-μm channels are calibrated to a radiance scale (via onboard blackbodies), knowledge of the top-of-atmosphere solar irradiance in the spectral region is required to infer reflectance. Despite the ubiquity of 3.7-μm channels, absolute solar spectral irradiance data come from either a single measurement campaign (Thekaekara et al.) or synthetic spectra. In the current study, the historical 3.7-μm band spectral irradiance datasets are compared with the recent semiempirical solar model of the quiet sun by Fontenla et al. The model has expected uncertainties of about 2% in the 3.7-μm spectral region. The channel-averaged spectral irradiances using the observations reported by Thekaekara et al. are found to be 3.2%–4.1% greater than those derived from the Fontenla et al. model for Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR instrument bandpasses; the Kurucz spectrum, as included in the Moderate Spectral Resolution Atmospheric Transmittance (MODTRAN4) distribution, gives channel-averaged irradiances 1.2%–1.5% smaller than the Fontenla model. For the MODIS instrument, these solar irradiance uncertainties result in cloud microphysical retrieval uncertainties that are comparable to other fundamental reflectance error sources.

A 34% reduction in 10-m wind speeds at Sudbury Airport in Ontario, Canada, over the period 1975–95 appears to be a result of significant changes in the surface roughness of the surrounding area that are due to land restoration and reforestation following historical environmental damage caused by high sulfur dioxide and other industrial emissions. Neither 850-hPa winds extracted from the NCEP–NCAR reanalysis database nor wind measurements at meteorological stations 200 km to the north and 120 km to the east of Sudbury show the same decrease. To assess these changes in observed wind speed quantitatively, geostrophic drag laws were employed to illustrate potential changes in near-surface wind speeds in areas surrounding the airport. A model of the internal boundary layer flow adjustment associated with changes in the surface roughness length between the surroundings and the grass or snow surface of the airport was then applied to compute expected annual average wind speeds at the airport site itself. The estimates obtained with this relatively simple procedure match the observations and confirm that reforestation is likely the major cause of the reduced wind speeds. This finding bears economic, social, and ecological importance, because it will influence wind energy potential, wind loads on structures, wind chill, and home heating costs through to the biology of small- to medium-sized lakes.

U.S. hourly surface observations are examined at 145 stations to identify annual and seasonal changes in temperature, dewpoint, relative humidity, and specific humidity since 1930. Because of numerous systematic instrument changes that have occurred, a homogeneity assessment was performed on temperatures and dewpoints. Dewpoints contained higher breakpoint detection rates associated with instrumentation changes than did temperatures. Temperature trends were tempered by adjusting the data, whereas dewpoints were unaffected. The effects were the same whether the adjustments were based on statistically detected or fixed-year breakpoints. Average long-term trends (1930–2010) indicate that temperature has warmed but that little change has occurred in dewpoint and specific humidity. Warming is strongest in spring. There is evidence of inhomogeneity in the relative humidity record that primarily affects data from prior to 1950. Therefore, long-term decreases in relative humidity, which are strongest in winter, need to be viewed with caution. Trends since 1947 indicate that the warming of temperatures has coincided with increases in dewpoints and a moistening of specific humidity. This moistening is especially pronounced during the summer in the Midwest. For the nation, trends in relative humidity show little change for the period 1947–2010, during which these data are more homogeneous. Moistening has occurred throughout the central United States while other regions have experienced drying. Urban-related warming and drying trends are present in the data, but their effect is minimal. Regional changes in land use and moisture availability are likely influencing trends in atmospheric moisture.

The impact of climate change on wind power generation potentials over Europe is investigated by considering ensemble projections from two regional climate models (RCMs) driven by a global climate model (GCM). Wind energy density and its interannual variability are estimated based on hourly near-surface wind speeds. Additionally, the possible impact of climatic changes on the energy output of a sample 2.5-MW turbine is discussed. GCM-driven RCM simulations capture the behavior and variability of current wind energy indices, even though some differences exist when compared with reanalysis-driven RCM simulations. Toward the end of the twenty-first century, projections show significant changes of energy density on annual average across Europe that are substantially stronger in seasonal terms. The emergence time of these changes varies from region to region and season to season, but some long-term trends are already statistically significant in the middle of the twenty-first century. Over northern and central Europe, the wind energy potential is projected to increase, particularly in winter and autumn. In contrast, energy potential over southern Europe may experience a decrease in all seasons except for the Aegean Sea. Changes for wind energy output follow the same patterns but are of smaller magnitude. The GCM/RCM model chains project a significant intensification of both interannual and intra-annual variability of energy density over parts of western and central Europe, thus imposing new challenges to a reliable pan-European energy supply in future decades.

Despite tremendous efforts to improve weather and climate predictions and to inform farmers about the use of such weather products, farmers’ attitudes toward forecast use remain poor and farmer use of forecasts has not increased. This paper describes features of a new conceptual model for facilitating farmers’ use of weather products and offers preliminary evidence for its effectiveness based on a test-of-concept prototype. The prototype system provides farmers with contextualized information, the opportunity to use that information in relevant farming contexts, and collaborative interaction with other users. In addition, scaffolding and feedback are incorporated in the model to enhance learning and motivation. Surveys before and after use of the prototype system, and focus-group discussion after system use, were conducted to obtain evaluations from 15 farmers in southeastern Nebraska. Farmers’ evaluations of the system were moderately positive and indicated greater intentions to use the products in the future than they had in the past. However, farmers only slightly increased their positive expectancies of various general categories of weather and climate products, supporting the difficulties associated with changing overall attitudes when attempting to transfer scientific improvements into practical uses. It is suggested that multiple exposures to such a system and more individualized and personally relevant use opportunities may further enhance the power of the proposed model.

Future projections of near-surface ozone concentrations depend on the climate/emissions scenario used to drive future simulations, the direct effects of the changing climate on the atmosphere, and the indirect effects of changing temperatures and CO2 levels on biogenic ozone precursor emissions. The authors investigate the influence of these factors on potential future changes in summertime daily 8-h maximum ozone over the United States and China by comparing Model for Ozone and Related Chemical Tracers, version 2.4, (MOZART-2.4) simulations for the period 1996–2000 with 2095–99, using climate projections from NCAR–Department of Energy Parallel Climate Model simulations driven by the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios A1fi (higher) and B1 (lower) emission scenarios, with corresponding changes in biogenic emissions. The effect of projected climate changes alone on surface ozone is generally less than 3 ppb over most regions. Regional ozone increases and decreases are driven mainly by local warming and marine air dilution enhancement, respectively. Changes are approximately the same magnitude under both scenarios, although spatial patterns of responses differ. Projected increases in isoprene emissions (32%–94% over both countries), however, result in significantly greater changes in surface ozone. Increases of 1–15 ppb are found under A1fi and of 0–7 ppb are found under B1. These increases not only raise the frequency of “high ozone days,” but are also projected to occur nearly uniformly across the distribution of daily ozone maxima. Thus, projected future ozone changes appear to be more sensitive to changes in biogenic emissions than to direct climate changes, and the spatial patterns and magnitude of future ozone changes depend strongly on the future emissions scenarios used.

The impacts of air pollution on the environment and human health could increase as a result of potential climate change. To assess such possible changes, model simulations of pollutant concentrations need to be performed at climatic (seasonal) rather than episodic (days) time scales, using future climate projections from a general circulation model. Such a modeling system was employed here, consisting of a regional climate model (RCM), an emissions model, and an air quality model. To assess overall model performance with one-way coupling, this system was used to simulate tropospheric ozone concentrations in the midwestern and northeastern United States for summer seasons between 1995 and 2000. The RCM meteorological conditions were driven by the National Centers for Environmental Prediction/Department of Energy global reanalysis (R-2) using the same procedure that integrates future climate model projections. Based on analyses for several urban and rural areas and regional domains, fairly good agreement with observations was found for the diurnal cycle and for several multiday periods of high ozone episodes. Even better agreement occurred between monthly and seasonal mean quantities of observed and model-simulated values. This is consistent with an RCM designed primarily to produce good simulations of monthly and seasonal mean statistics of weather systems.

The Pearl River delta (PRD) region has undergone rapid urbanization since the 1980s, which has had significant effects on the sea-breeze circulation in this region. Because the sea breeze plays an important role in pollutant transportation and convective initiation in the PRD region, it is meaningful to study the effects of urbanization on the sea breeze. In this study, three numerical experiments were conducted from 2 June to 31 August 2010 with land-use data from 1988, 1999, and 2010. For each simulation, characteristics of the sea breeze such as the start time, end time, intensity, height, pumping ability, and inland penetration distance were quantified. By comparing the characteristics of the sea breeze in these simulations, its response to urbanization was quantified. The results show that urbanization enhances the duration, height, and intensity of the sea breeze but blocks its inland penetration. One physical mechanism is proposed to dynamically elucidate the response of the sea breeze to urbanization. Because the urban area in the PRD region is concentrated near the coast, urbanization imposes a positive heating gradient on the coastal region and a negative heating gradient on the region farther inland. The positive heating gradient may intensify the sea breeze, and the negative heating gradient may prevent the sea breeze from propagating farther inland.