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At least 55 records · Page 3

Modeled Seasonal Variations of Firn Density Induced by Steady State Surface Air Temperature Cycle

Seasonal variations of firn density in ice-sheet firn layers have been attributed to variations in deposition processes or other processes within the upper firn. A recent high-resolution (mm scale) density profile, measured along a 181 m core from Antarctica, showed small-scale density variations with a clear seasonal cycle that apparently was not-related to seasonal variations in deposition or known near-surface processes (Gerland and others 1999). A recent model of surface elevation changes (Zwally and Li, submitted) produced a seasonal variation in firn densification, and explained the seasonal surface elevation changes observed by satellite radar altimeters. In this study, we apply our 1-D time-dependent numerical model of firn densification that includes a temperature-dependent formulation of firn densification based on laboratory measurements of grain growth. The model is driven by a steady-state seasonal surface temperature and a constant accumulation rate appropriate for the measured Antarctic ice core. The modeled seasonal variations in firn density show that the layers of snow deposited during spring to mid-summer with the highest temperature history compress to the highest density, and the layers deposited during later summer to autumn with the lowest temperature history compress to the lowest density. The initial amplitude of the seasonal difference of about 0.13 reduces to about 0.09 in five years and asymptotically to 0.92 at depth, which is consistent with the core measurements.

Jun, Li↗

Variation of Surface Air Temperature in Relation to El Nino and Cataclysmic Volcanic Eruptions, 1796-1882

During the contemporaneous interval of 1796-1882 a number of significant decreases in temperature are found in the records of Central England and Northern Ireland. These decreases appear to be related to the occurrences of El Nino and/or cataclysmic volcanic eruptions. For example, a composite of residual temperatures of the Central England dataset, centering temperatures on the yearly onsets of 20 El Nino of moderate to stronger strength, shows that, on average, the change in temperature varied by about +/- 0.3 C from normal being warmer during the boreal fall-winter leading up to the El Nino year and cooler during the spring-summer of the El Nino year. Also, the influence of El Nino on Central England temperatures appears to last about 1-2 years. Similarly, a composite of residual temperatures of the Central England dataset, centering temperatures on the month of eruption for 26 cataclysmic volcanic eruptions, shows that, on average, the change in temperature decreased by about 0.1 - 0.2 C, typically, 1-2 years after the eruption, although for specific events, like Tambora, the decrease was considerably greater. Additionally, tropical eruptions appear to produce greater changes in temperature than extratropical eruptions, and eruptions occurring in boreal spring-summer appear to produce greater changes in temperature than those occurring in fall-winter.

Wilson, Robert M.↗

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water.

Lakshmi, Venkataraman↗

Heat Capacity Mapping Mission (HCMM): Interpretation of imagery over Canada

Visual analysis of HCMM images acquired over two sites in Canada and supporting aircraft and ground data obtained at a smaller subsite in Alberta show that nightime surface temperature distribution is primarily related to the near-surface air temperature; the effects of topography, wind, and land cover were low or indirect through air temperature. Surface cover and large altitudinal differences were important parameters influencing daytime apparent temperature values. A quantitative analysis of the relationship between the antecedent precipitation index and the satellite thermal IR measurements did not yield statistically significant correlation coefficients, but the correlations had a definite temporal trend which could be related to the increasing uniformity of vegetation cover. The large pixel size (resulting in a mixture of cover types and soil/canopy temperatures measured by the satellite) and high cloud cover frequency found in images covering both Canadian sites and northern U.S. were considered the main deficiencies of the thermal satellite data.

Cihlar, J.↗

Development of an Unbiased Future Solar Dataset for Solar Resource Adequacy Research Over CONUS

A high-resolution, long-term solar dataset is essential for capturing the variability of solar energy resources and informing strategies to ensure grid reliability and resilience in systems with high levels of solar energy integration. This study focuses on generating unbiased, high-resolution projections of solar irradiance through a statistical downscaling framework, using Earth system model (ESM) simulations obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). The National Solar Radiation Database (NSRDB) is used to calibrate statistical downscaling models. The newly developed dataset provides solar irradiance, surface air temperature, and surface wind speed at 4-km and hourly resolutions across the contiguous United States (CONUS), based on two future scenarios (RCP4.5 and RCP8.5). This study outlines key steps in developing the high-resolution future solar dataset, including (1) regridding ESM data to a common 20-km resolution grid, (2) correcting ESM biases using the NSRDB, and (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar projections. Preliminary results indicate that downscaled projections (4-km) captured reasonable spatial patterns when compared to observations across CONUS for four variables. On average across all pixels, 4-km daily-total GHI and DNI projections showed normalized bias (nBias) less than 1% and 6% for GHI and DNI against NSRDB, respectively (nBias less than 1% and 5% for daily-average surface air temperature and surface wind speed). In terms of long-term trend for GHI and DNI, there was no strong increasing or decreasing trend (when compared to surface air temperature), but it showed a very weak decreasing trend.

14 SOLAR ENERGY↗

Application of Satellite-Derived Land Surface Temperature to Minimum Temperature Forecasting

Satellite-derived land surface temperature (LST) is studied for the purpose of understanding regional skin temperature dependency and variability, and its relationship to corresponding, site-specific air temperature. Skin temperature is highly correlated with surface-air temperature although it differs depending on land surface characteristics, terrain, and atmospheric conditions on a diurnal and seasonal scale. The high temporal resolution of the Geostationary Operational Environmental Satellite (GOES) -12 sounder is used to compare the diurnal cycles of LST and surface-air temperature. The minimum for both temperatures occurs near sunrise and LST is found to agree closely with surface-air temperatures a period of hours before sunrise on clear sky nights. The Moderate Resolution Imaging Spectroradiometer (MODIS)-derived LST renders more horizontal temperature structure - with its high spatial resolution (1 km at nadir) compared to the GOES-12 sounder (10 km). Nighttime MODIS-derived LST is extrapolated to the time of minimum temperature for a number of case study days and these are grouped by season and atmospheric conditions. These composites show that the variation in LST mirror the variation in minimum surface-air temperature under similar conditions.

Jones, P. R.↗

LiG Metrology, Correlated Error, and the Integrity of the Global Surface Air-Temperature Record

The published 95% uncertainty of the global surface air-temperature anomaly (GSATA) record through 1980 is impossibly less than the 2σ = ±0.25 °C lower limit of laboratory resolution of 1 °C/division liquid-in-glass (LiG) thermometers. The ~0.7 °C/century Joule-drift of lead- and soft-glass thermometer bulbs renders unreliable the entire historical air-temperature record through the 19th century. A circa 1900 Baudin meteorological spirit thermometer bulb exhibited intense Pb X-ray emission lines (10.55, 12.66, and 14.76 keV). Uncorrected LiG thermometer non-linearity leaves 1σ = ±0.27 °C uncertainty in land-surface air temperatures prior to 1981. The 2σ = ±0.43 °C from LiG resolution and non-linearity obscures most of the 20th century GSATA trend. Systematic sensor-measurement errors are highly pair-wise correlated, possibly across hundreds of km. Non-normal distributions of bucket and engine-intake difference SSTs disconfirm the assumption of random measurement error. Semivariogram analysis of ship SST measurements yields half the error difference mean, ±½Δε 1,2, not the error mean. Transfer-function adjustment following a change of land station air-temperature sensor eliminates measurement independence and forward-propagates the antecedent uncertainty. LiG resolution limits, non-linearity, and sensor field calibrations yield GSATA mean ±2σ RMS uncertainties of, 1900–1945, ±1.7 °C; 1946–1980, ±2.1 °C; 1981–2004, ±2.0 °C; and 2005–2010, ±1.6 °C. Finally, the 20th century (1900–1999) GSATA, 0.74 ± 1.94 °C, does not convey any information about rate or magnitude of temperature change.

54 ENVIRONMENTAL SCIENCES↗

An upper bound for extreme temperatures over midlatitude land

Heatwaves damage societies worldwide and are intensifying with global warming. Several mechanistic drivers of heatwaves, such as atmospheric blocking and soil moisture-atmosphere feedback, are well-known for their ability to raise surface air temperature. However, what limits the maximum surface air temperature in heatwaves remains unclear; this became evident during recent Northern Hemisphere heatwaves which achieved temperatures far beyond the upper tail of the observed statistical distribution. Here, we present evidence for the hypothesis that convective instability limits annual maximum surface air temperatures (TXx) over midlatitude land. We provide a theory for the corresponding upper bound of midlatitude temperatures, which accurately describes the observed relationship between temperatures at the surface and in the midtroposphere. We show that known heatwave drivers shift the position of the atmospheric state in the phase space described by the theory, changing its proximity to the upper bound. This theory suggests that the upper bound for midlatitude TXx should increase 1.9 times as fast as 500-hPa temperatures at the time and location of TXx occurrences. Using empirical 500-hPa warming, we project that the upper bound of TXx over Northern Hemisphere midlatitude land (40°N to 65°N) will increase about twice as fast as global mean surface air temperature, and TXx will increase faster than this bound over regions that dry on the hottest days.

54 ENVIRONMENTAL SCIENCES↗