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- Author or Editor: Pavel Ya. Groisman x
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Abstract
A disproportionate increase in precipitation coming from intense rain events, in the situation of general warming (thus, an extension of the vegetation period with intensive transpiration), and an insignificant change in total precipitation could lead to an increase in the frequency of a potentially serious type of extreme events: prolonged periods without precipitation (even when the mean seasonal rainfall totals increase). This paper investigates whether this development is already occurring during the past several decades over the conterminous United States, for the same period when changes in frequency of intense precipitation events are being observed. Lengthy strings of “dry” days without sizeable (>1.0 mm) precipitation were assessed only during the warm season (defined as a period when mean daily temperature is above the 5°C threshold) when water is intensively used for transpiration and prolonged periods without sizable rainfall represent a hazard for terrestrial ecosystem’s health and agriculture. During the past four decades, the mean duration of prolonged dry episodes (1 month or longer in the eastern United States and 2 months or longer in the southwestern United States) has significantly increased. As a consequence the return period of 1-month-long dry episodes over the eastern United States has reduced more than twofold from 15 to 6–7 yr. The longer average duration of dry episodes has occurred during a relatively wet period across the country but is not observed over the northwestern United States.
Abstract
A disproportionate increase in precipitation coming from intense rain events, in the situation of general warming (thus, an extension of the vegetation period with intensive transpiration), and an insignificant change in total precipitation could lead to an increase in the frequency of a potentially serious type of extreme events: prolonged periods without precipitation (even when the mean seasonal rainfall totals increase). This paper investigates whether this development is already occurring during the past several decades over the conterminous United States, for the same period when changes in frequency of intense precipitation events are being observed. Lengthy strings of “dry” days without sizeable (>1.0 mm) precipitation were assessed only during the warm season (defined as a period when mean daily temperature is above the 5°C threshold) when water is intensively used for transpiration and prolonged periods without sizable rainfall represent a hazard for terrestrial ecosystem’s health and agriculture. During the past four decades, the mean duration of prolonged dry episodes (1 month or longer in the eastern United States and 2 months or longer in the southwestern United States) has significantly increased. As a consequence the return period of 1-month-long dry episodes over the eastern United States has reduced more than twofold from 15 to 6–7 yr. The longer average duration of dry episodes has occurred during a relatively wet period across the country but is not observed over the northwestern United States.
Abstract
Several changes in U.S. observational practice [in particular, the introduction of the Automated Surface Observing System (ASOS) in the early 1990s] have led to a challenging heterogeneity of time series of most ground-based cloud observations. In this article, an attempt is made to preserve/restore the time series of average low cloud cover (LCC) over the country up to the year 2001 using cloud sky condition and cloud-base height information collected in the national archive data and to describe its spatial and temporal variability. The switch from human observations to ASOS can be bridged through the use of frequency of overcast/broken cloudiness. During the past 52 yr, the nationwide LCC appears to exhibit a significant increase but all of this increase occurred prior to the early 1980s and thereafter tends to decrease. This finding is consistent with similar changes in the frequency of days with precipitation. When the cloud-type information was still available (i.e., during the pre-ASOS period), it was found that the overall LCC increase was due to the increase in stratiform and cumulonimbus cloud occurrences while cumulus cloud frequency decreased.
Abstract
Several changes in U.S. observational practice [in particular, the introduction of the Automated Surface Observing System (ASOS) in the early 1990s] have led to a challenging heterogeneity of time series of most ground-based cloud observations. In this article, an attempt is made to preserve/restore the time series of average low cloud cover (LCC) over the country up to the year 2001 using cloud sky condition and cloud-base height information collected in the national archive data and to describe its spatial and temporal variability. The switch from human observations to ASOS can be bridged through the use of frequency of overcast/broken cloudiness. During the past 52 yr, the nationwide LCC appears to exhibit a significant increase but all of this increase occurred prior to the early 1980s and thereafter tends to decrease. This finding is consistent with similar changes in the frequency of days with precipitation. When the cloud-type information was still available (i.e., during the pre-ASOS period), it was found that the overall LCC increase was due to the increase in stratiform and cumulonimbus cloud occurrences while cumulus cloud frequency decreased.
Abstract
The biases and large-scale inhomogeneities in the time series of measured precipitation and snowfall over the United States and Canada are discussed and analyzed. The spatial statistical characteristics of monthly and annual snowfall and total precipitation are investigated and parameterized. After adjustments and selection of the “best” network, reliable “first guess” estimates of North American snowfall and precipitation are obtained. Century-long time series of unbiased annual precipitation over the regions to the south of 55°N and 40-year time series of unbiased area-averaged annual precipitation and snowfall for all of North America are developed. The analysis of their trends shows the following.
1) During the last 100 years, annual precipitation has increased in southern Canada (south of 55°N) by 13% and in the contiguous United States by 4%; however, the main domain of this century-scale precipitation increase is eastern Canada and adjacent to it northern regions of the United States.
2) Up to a 20% increase has occurred in annual snowfall and rainfall during the last four decades in Canada north of 55°N.
The relationships between century-long precipitation time series over North America with Northern Hemisphere surface air temperature and the South Oscillation index (SOI) are investigated. It is shown that ENSO (negative anomaly of SOI) is usually accompanied by an increase of precipitation whenever it affects the United States (especially in the southwestern region of the country).
Abstract
The biases and large-scale inhomogeneities in the time series of measured precipitation and snowfall over the United States and Canada are discussed and analyzed. The spatial statistical characteristics of monthly and annual snowfall and total precipitation are investigated and parameterized. After adjustments and selection of the “best” network, reliable “first guess” estimates of North American snowfall and precipitation are obtained. Century-long time series of unbiased annual precipitation over the regions to the south of 55°N and 40-year time series of unbiased area-averaged annual precipitation and snowfall for all of North America are developed. The analysis of their trends shows the following.
1) During the last 100 years, annual precipitation has increased in southern Canada (south of 55°N) by 13% and in the contiguous United States by 4%; however, the main domain of this century-scale precipitation increase is eastern Canada and adjacent to it northern regions of the United States.
2) Up to a 20% increase has occurred in annual snowfall and rainfall during the last four decades in Canada north of 55°N.
The relationships between century-long precipitation time series over North America with Northern Hemisphere surface air temperature and the South Oscillation index (SOI) are investigated. It is shown that ENSO (negative anomaly of SOI) is usually accompanied by an increase of precipitation whenever it affects the United States (especially in the southwestern region of the country).
Precipitation measurements in the United States (as well as all other countries) are adversely affected by the gauge undercatch bias of point precipitation measurements. When these measurements are used to obtain areal averages, particularly in mountainous terrain, additional biases may be introduced because most stations are at lower elevations in exposed sites.
Gauge measurements tend to be underestimates of the true precipitation, largely because of wind-induced turbulence at the gauge orifice and wetting losses on the internal walls of the gauge. These are not trivial as monthly estimates of this bias often vary from 5% to 40%. Biases are larger in winter than in summer and increase to the north in the United States due largely to the deleterious effect of the wind on snowfall.
Simple spatial averaging of data from existing networks does not provide an accurate evaluation of the area-mean precipitation over mountainous terrain (e.g., over much of the western United States) since most stations are located at low elevations. This tends to underestimate area averages since, in mountainous terrain, precipitation generally increases with elevation.
Temporal precipitation trends for the United States, as well as seasonal and annual averages, are presented. Estimates of unbiased (or less biased) precipitation over the northern Great Plains provide a regional analysis.
Precipitation measurements in the United States (as well as all other countries) are adversely affected by the gauge undercatch bias of point precipitation measurements. When these measurements are used to obtain areal averages, particularly in mountainous terrain, additional biases may be introduced because most stations are at lower elevations in exposed sites.
Gauge measurements tend to be underestimates of the true precipitation, largely because of wind-induced turbulence at the gauge orifice and wetting losses on the internal walls of the gauge. These are not trivial as monthly estimates of this bias often vary from 5% to 40%. Biases are larger in winter than in summer and increase to the north in the United States due largely to the deleterious effect of the wind on snowfall.
Simple spatial averaging of data from existing networks does not provide an accurate evaluation of the area-mean precipitation over mountainous terrain (e.g., over much of the western United States) since most stations are located at low elevations. This tends to underestimate area averages since, in mountainous terrain, precipitation generally increases with elevation.
Temporal precipitation trends for the United States, as well as seasonal and annual averages, are presented. Estimates of unbiased (or less biased) precipitation over the northern Great Plains provide a regional analysis.
Abstract
The turbulent heat fluxes at the soil surface are not observed (or poorly observed) by existing observational systems. This affects the ability to reliably predict the consequences of climate changes on the hydrologic cycle. Therefore, an approach to estimating sensible surface heat fluxes based on combination of the K and similarity theories, and using routine meteorological observations available in Russia, was developed. This was possible for the former Soviet Union territory and some other countries, where the standard practice of hourly observations includes temperature measurements at the atmosphere–land surface boundary and codes of the surface conditions (wet, dry, snow covered, etc.). The approach is designed for use in climate change and/or climate feedback studies. A similar approach to estimating latent heat fluxes is developed, but only for saturated surfaces (wet and/or snow covered). The method has been tested on several observational datasets.
Abstract
The turbulent heat fluxes at the soil surface are not observed (or poorly observed) by existing observational systems. This affects the ability to reliably predict the consequences of climate changes on the hydrologic cycle. Therefore, an approach to estimating sensible surface heat fluxes based on combination of the K and similarity theories, and using routine meteorological observations available in Russia, was developed. This was possible for the former Soviet Union territory and some other countries, where the standard practice of hourly observations includes temperature measurements at the atmosphere–land surface boundary and codes of the surface conditions (wet, dry, snow covered, etc.). The approach is designed for use in climate change and/or climate feedback studies. A similar approach to estimating latent heat fluxes is developed, but only for saturated surfaces (wet and/or snow covered). The method has been tested on several observational datasets.
Abstract
The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (−49°C) to extreme heat (+52°C), in areas of heavy precipitation (4700 mm yr−1), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation.
Abstract
The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (−49°C) to extreme heat (+52°C), in areas of heavy precipitation (4700 mm yr−1), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation.
Abstract
A pronounced summer warming is observed in Europe since the 1980s that has been accompanied by an increase in the occurrence of heat waves. Water deficit that strongly reduces surface latent cooling is a widely accepted explanation for the causes of hot summers. The authors show that the variance of European summer temperature is partly explained by changes in summer cloudiness. Using observation-based products of climate variables, satellite-derived cloud cover, and radiation products, the authors show that, during the 1984–2007 period, Europe has become less cloudy (except northeastern Europe) and the regions east of Europe have become cloudier in summer daytime. In response, the summer temperatures increased in the areas of total cloud cover decrease and stalled or declined in the areas of cloud cover increase. Trends in the surface shortwave radiation are generally positive (negative) in the regions with summer warming (cooling or stalled warming), whereas the signs of trends in top-of-atmosphere (TOA) reflected shortwave radiation are reversed. The authors’ results suggest that total cloud cover is either the important local factor influencing the summer temperature changes in Europe or a major indicator of these changes.
Abstract
A pronounced summer warming is observed in Europe since the 1980s that has been accompanied by an increase in the occurrence of heat waves. Water deficit that strongly reduces surface latent cooling is a widely accepted explanation for the causes of hot summers. The authors show that the variance of European summer temperature is partly explained by changes in summer cloudiness. Using observation-based products of climate variables, satellite-derived cloud cover, and radiation products, the authors show that, during the 1984–2007 period, Europe has become less cloudy (except northeastern Europe) and the regions east of Europe have become cloudier in summer daytime. In response, the summer temperatures increased in the areas of total cloud cover decrease and stalled or declined in the areas of cloud cover increase. Trends in the surface shortwave radiation are generally positive (negative) in the regions with summer warming (cooling or stalled warming), whereas the signs of trends in top-of-atmosphere (TOA) reflected shortwave radiation are reversed. The authors’ results suggest that total cloud cover is either the important local factor influencing the summer temperature changes in Europe or a major indicator of these changes.
Abstract
A unique set of data from Valdai, Russia, (previously unreported in the United States) is used to evaluate the ubiquitous standard 8-in.-diameter raingage that has been used for over 100 years at tens of thousands of United States stations. The results of the Valdai analyses (where the 8-in. raingage measurements had been analyzed during 4 years of parallel observations with the etalon raingage) are consistent with other findings summarized in this paper. Rain undercatch (unshielded) is about 4%. Evaporation losses from the raingage and wetting losses (where part of the water stays on the funnel and bucket walls of the raingage and is not measured) have been estimated and were found to be fairly small. To put this in perspective, snow undercatch (as reported by others) can be several tens of percent for windy, unshielded sites.
Abstract
A unique set of data from Valdai, Russia, (previously unreported in the United States) is used to evaluate the ubiquitous standard 8-in.-diameter raingage that has been used for over 100 years at tens of thousands of United States stations. The results of the Valdai analyses (where the 8-in. raingage measurements had been analyzed during 4 years of parallel observations with the etalon raingage) are consistent with other findings summarized in this paper. Rain undercatch (unshielded) is about 4%. Evaporation losses from the raingage and wetting losses (where part of the water stays on the funnel and bucket walls of the raingage and is not measured) have been estimated and were found to be fairly small. To put this in perspective, snow undercatch (as reported by others) can be several tens of percent for windy, unshielded sites.
Abstract
Several essential aspects of weather observing and the management of weather data are discussed as related to improving knowledge of climate variations and change in the surface boundary layer and the resultant consequences for socioeconomic and biogeophysical systems. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems.
Although much has been learned from existing weather networks and methods of data management, the system is far from perfect. There are several vital areas that have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to the time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changed are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food.
Abstract
Several essential aspects of weather observing and the management of weather data are discussed as related to improving knowledge of climate variations and change in the surface boundary layer and the resultant consequences for socioeconomic and biogeophysical systems. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems.
Although much has been learned from existing weather networks and methods of data management, the system is far from perfect. There are several vital areas that have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to the time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changed are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food.
Abstract
In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested.
Abstract
In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested.
