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Abstract
Computer simulations of satellite-derived Earth radiation parameters are examined to determine the source and size of errors arising from averaging parameters over 1 month on a 2.5°×2.5° longitude-latitude grid. November 1978 data from the Geostationary Operational Environmental Satellite (GOES) have been used as a source of radiation parameter fields within each region. The regions are sampled according to various combinations of satellite orbits which have been chosen on the basis of their applicability to the Earth Radiation Budget Experiment. A mathematical model is given for the data-processing algorithms that are used to produce daily, monthly and monthly hourly estimates of shortwave, longwave and net radiant exitance. Because satellite sampling of each region is sparse during any day, and because the meteorological behavior between measurements is unknown, the retrieved diurnal cycle in shortwave radiant exitance is especially sensitive to the temporal distribution of measurements. The resulting retrieval errors are seen to be due to insufficient knowledge of the temporal distribution of both cloud fraction and albedo. These errors, in combination with similar sampling errors resulting from diurnal variations in longwave radiant exitance (especially over land), produce biases in monthly net radiant exitance which are complex, regionally-dependent functions of the local time of the measurements. The regions studied have shown standard errors of estimate for monthly net radiant exitance ranging from about 20 W m−2 for the worst single-satellite sample to ∼2 W m−2 for the three-satellite sampling assumed to be available.
Abstract
Computer simulations of satellite-derived Earth radiation parameters are examined to determine the source and size of errors arising from averaging parameters over 1 month on a 2.5°×2.5° longitude-latitude grid. November 1978 data from the Geostationary Operational Environmental Satellite (GOES) have been used as a source of radiation parameter fields within each region. The regions are sampled according to various combinations of satellite orbits which have been chosen on the basis of their applicability to the Earth Radiation Budget Experiment. A mathematical model is given for the data-processing algorithms that are used to produce daily, monthly and monthly hourly estimates of shortwave, longwave and net radiant exitance. Because satellite sampling of each region is sparse during any day, and because the meteorological behavior between measurements is unknown, the retrieved diurnal cycle in shortwave radiant exitance is especially sensitive to the temporal distribution of measurements. The resulting retrieval errors are seen to be due to insufficient knowledge of the temporal distribution of both cloud fraction and albedo. These errors, in combination with similar sampling errors resulting from diurnal variations in longwave radiant exitance (especially over land), produce biases in monthly net radiant exitance which are complex, regionally-dependent functions of the local time of the measurements. The regions studied have shown standard errors of estimate for monthly net radiant exitance ranging from about 20 W m−2 for the worst single-satellite sample to ∼2 W m−2 for the three-satellite sampling assumed to be available.
Abstract
Simulations of the Earth Radiation Budget Experiment with several satellite sampling schemes have been used to compare three different approaches to modeling longwave diurnal behavior observed over certain kinds of land regions. November 1978 data from the GOES satellite have been used to produce a reference set of radiation parameters over the regions of interest. The monthly average longwave radiant exitance has been estimated first with linear interpolation between satellite measurements, then with a method that replaces linear interpolations across day-night boundaries with piecewise constant extrapolations to the boundaries, and finally with a trigonometric model which replaces some of the linear interpolations that go through daytime measurements over land. This third model consists of constant extrapolation of nighttime measurements to sunrise or sunset, with a half-sine curve fitted through existing daytime measurements and constrained at sunrise and sunset to an average of the surrounding nighttime measurements. It applies only when the daytime and surrounding nighttime measurements meet certain restrictive criteria, including tests that tend to limit the trigonometric model to cloud-free regions. For all satellite sampling strategies considered, the trigonometric model gave the best overall monthly estimate of longwave radiant exitance. For non-land regions, the linear interpolation model generally gave better results than the piecewise constant model.
Abstract
Simulations of the Earth Radiation Budget Experiment with several satellite sampling schemes have been used to compare three different approaches to modeling longwave diurnal behavior observed over certain kinds of land regions. November 1978 data from the GOES satellite have been used to produce a reference set of radiation parameters over the regions of interest. The monthly average longwave radiant exitance has been estimated first with linear interpolation between satellite measurements, then with a method that replaces linear interpolations across day-night boundaries with piecewise constant extrapolations to the boundaries, and finally with a trigonometric model which replaces some of the linear interpolations that go through daytime measurements over land. This third model consists of constant extrapolation of nighttime measurements to sunrise or sunset, with a half-sine curve fitted through existing daytime measurements and constrained at sunrise and sunset to an average of the surrounding nighttime measurements. It applies only when the daytime and surrounding nighttime measurements meet certain restrictive criteria, including tests that tend to limit the trigonometric model to cloud-free regions. For all satellite sampling strategies considered, the trigonometric model gave the best overall monthly estimate of longwave radiant exitance. For non-land regions, the linear interpolation model generally gave better results than the piecewise constant model.
A 2-yr study affirms that the temperature indicated by an inexpensive ($20–$60) IR thermometer pointed at the cloud-free zenith sky (Tz) is a proxy for total column water vapor [precipitable water (PW)]. From 8 September 2008 to 18 October 2010 Tz was measured either at or near solar noon, and occasionally at night, at a field in south-central Texas. PW was measured by a MICROTOPS II sun photometer. The coefficient of correlation (r 2) of PW and Tz was 0.90, and the rms difference was 3.2 mm. A comparison of Tz with PW from a GPS site 31 km northnortheast yielded an r 2 of 0.79 and an rms difference of 5.8 mm. An expanded study compared Tz from eight IR thermometers with PW at various times during the day and night from 17 May to 18 October 2010, mainly at the Texas site, with an additional 10 days at Hawaii's Mauna Loa Observatory. The best results were provided by two IR thermometers that yielded an r 2 of 0.96 and an rms difference with PW of 2.7 mm. The results of both the ongoing 2-yr study and the 5-month comparison show that IR thermometers can measure PW with an accuracy (rms difference/mean PW) approaching 10%, which is the accuracy typically ascribed to sun photometers. The simpler IR method, which works during both day and night, can be easily mastered by students, amateur scientists, and cooperative weather observers.
A 2-yr study affirms that the temperature indicated by an inexpensive ($20–$60) IR thermometer pointed at the cloud-free zenith sky (Tz) is a proxy for total column water vapor [precipitable water (PW)]. From 8 September 2008 to 18 October 2010 Tz was measured either at or near solar noon, and occasionally at night, at a field in south-central Texas. PW was measured by a MICROTOPS II sun photometer. The coefficient of correlation (r 2) of PW and Tz was 0.90, and the rms difference was 3.2 mm. A comparison of Tz with PW from a GPS site 31 km northnortheast yielded an r 2 of 0.79 and an rms difference of 5.8 mm. An expanded study compared Tz from eight IR thermometers with PW at various times during the day and night from 17 May to 18 October 2010, mainly at the Texas site, with an additional 10 days at Hawaii's Mauna Loa Observatory. The best results were provided by two IR thermometers that yielded an r 2 of 0.96 and an rms difference with PW of 2.7 mm. The results of both the ongoing 2-yr study and the 5-month comparison show that IR thermometers can measure PW with an accuracy (rms difference/mean PW) approaching 10%, which is the accuracy typically ascribed to sun photometers. The simpler IR method, which works during both day and night, can be easily mastered by students, amateur scientists, and cooperative weather observers.
Abstract
An inexpensive two-channel near-IR sun photometer for measuring total atmospheric column water vapor (precipitable water) has been developed for use by the Global Learning and Observations to Benefit the Environment (GLOBE) environmental science and education program and other nonspecialists. This instrument detects sunlight in the 940-nm water vapor absorption band with a filtered photodiode and at 825 nm with a near-IR light-emitting diode (LED). The ratio of outputs of these two detectors is related to total column water vapor in the atmosphere. Reference instruments can be calibrated against column atmospheric water vapor data derived from delays in radio signals received at global positioning satellite (GPS) receiver sites and other independent sources. For additional instruments that are optically and physically identical to reference instruments, a single-parameter calibration can be determined by making simultaneous measurements with a reference instrument and forcing the derived precipitable water values to agree. Although the concept of near-IR detection of precipitable water is not new, this paper describes a first attempt at developing a protocol for calibrating large numbers of inexpensive instruments suitable for use by teachers, students, and other nonspecialists.
Abstract
An inexpensive two-channel near-IR sun photometer for measuring total atmospheric column water vapor (precipitable water) has been developed for use by the Global Learning and Observations to Benefit the Environment (GLOBE) environmental science and education program and other nonspecialists. This instrument detects sunlight in the 940-nm water vapor absorption band with a filtered photodiode and at 825 nm with a near-IR light-emitting diode (LED). The ratio of outputs of these two detectors is related to total column water vapor in the atmosphere. Reference instruments can be calibrated against column atmospheric water vapor data derived from delays in radio signals received at global positioning satellite (GPS) receiver sites and other independent sources. For additional instruments that are optically and physically identical to reference instruments, a single-parameter calibration can be determined by making simultaneous measurements with a reference instrument and forcing the derived precipitable water values to agree. Although the concept of near-IR detection of precipitable water is not new, this paper describes a first attempt at developing a protocol for calibrating large numbers of inexpensive instruments suitable for use by teachers, students, and other nonspecialists.
Abstract
An intercomparison between radiative parameters determined from visible and infrared channels of the METEOSAT-1 and GOES-2 geosynchronous satellites has been carried out using data obtained over the central Atlantic Ocean for 5 November 1978. Hourly visible-infrared measurement pairs at a nominal resolution of 5 km (METEOSAT) or 8 km (GOES) have been stored in 1° × 1° longitude-latitude regions. For the infrared intercomparisons, the GOES 11.5 μm radiance has been compared to METEOSAT infrared counts. The scatter in partly cloudy regions is interpreted as being caused by meteorological differences arising from differences in measurement time between the two data sets. For the visible intercomparison, the GOES measurements for clear and cloudy scenes have first been converted with the aid of scene-dependent angular reflectance and albedo models to estimates of the filtered shortwave radiance that GOES would have measured had it been in the METEOSAT position. This value has then been compared to METEOSAT counts for the shortwave channel. The results indicate that earlier METEOSAT calibrations made from airplane overflights of a limited variety of surfaces are applicable to much larger areas of cloud and ocean.
Abstract
An intercomparison between radiative parameters determined from visible and infrared channels of the METEOSAT-1 and GOES-2 geosynchronous satellites has been carried out using data obtained over the central Atlantic Ocean for 5 November 1978. Hourly visible-infrared measurement pairs at a nominal resolution of 5 km (METEOSAT) or 8 km (GOES) have been stored in 1° × 1° longitude-latitude regions. For the infrared intercomparisons, the GOES 11.5 μm radiance has been compared to METEOSAT infrared counts. The scatter in partly cloudy regions is interpreted as being caused by meteorological differences arising from differences in measurement time between the two data sets. For the visible intercomparison, the GOES measurements for clear and cloudy scenes have first been converted with the aid of scene-dependent angular reflectance and albedo models to estimates of the filtered shortwave radiance that GOES would have measured had it been in the METEOSAT position. This value has then been compared to METEOSAT counts for the shortwave channel. The results indicate that earlier METEOSAT calibrations made from airplane overflights of a limited variety of surfaces are applicable to much larger areas of cloud and ocean.
First results for diurnal cycles derived from the Earth Radiation Budget Experiment (ERBE) are presented for the combined Earth Radiation Budget Satellite (ERBS) and NOAA-9 spacecraft for April 1985. Regional scale longwave (LW) radiation data are analyzed to determine diurnal variations for the total scene (including clouds) and for clear-sky conditions. The LW diurnal range was found to be greatest for clear desert regions (up to about 70 W · m−2) and smallest for clear oceans (less than 5 W · m−2). Local time of maximum longwave radiation occurs at a wide range of times throughout the day and night over oceans, but generally occurs from noon to early afternoon over land and desert regions.
First results for diurnal cycles derived from the Earth Radiation Budget Experiment (ERBE) are presented for the combined Earth Radiation Budget Satellite (ERBS) and NOAA-9 spacecraft for April 1985. Regional scale longwave (LW) radiation data are analyzed to determine diurnal variations for the total scene (including clouds) and for clear-sky conditions. The LW diurnal range was found to be greatest for clear desert regions (up to about 70 W · m−2) and smallest for clear oceans (less than 5 W · m−2). Local time of maximum longwave radiation occurs at a wide range of times throughout the day and night over oceans, but generally occurs from noon to early afternoon over land and desert regions.
The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hailstorms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make using the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical link- ages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multidecadal trends in the areal percentage of the contiguous United States impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the United States as a whole since 1950.
The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hailstorms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make using the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical link- ages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multidecadal trends in the areal percentage of the contiguous United States impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the United States as a whole since 1950.
This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.
This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.
Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale “memory” in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood.
Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale “memory” in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood.
Abstract
The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.
Abstract
The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.
