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- Author or Editor: Richard R. Heim Jr. x
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The monitoring and analysis of drought have long suffered from the lack of an adequate definition of the phenomenon. As a result, drought indices have slowly evolved during the last two centuries from simplistic approaches based on some measure of rainfall deficiency, to more complex problem-specific models. Indices developed in the late nineteenth and early twentieth century included such measures as percent of normal precipitation over some interval, consecutive days with rain below a given threshold, formulae involving a combination of temperature and precipitation, and models factoring in precipitation deficits over consecutive days. The incorporation of evapotranspiration as a measure of water demand by Thornthwaite led to the landmark development in 1965 by Palmer of a water budget-based drought index that is still widely used. Drought indices developed since the 1960s include the Surface Water Supply Index, which supplements the Palmer Index by integrating snowpack, reservoir storage, streamflow, and precipitation at high elevations; the Keetch–Byram Drought Index, which is used by fire control managers; the Standardized Precipitation Index; and the Vegetation Condition Index, which utilizes global satellite observations of vegetation condition. These models continue to evolve as new data sources become available. The twentieth century concluded with the development of the Drought Monitor tool, which incorporates Palmer's index and several other (post Palmer) indices to provide a universal assessment of drought conditions across the entire United States. By putting the development of these drought indices into a historical perspective, this paper provides a better understanding of the complex Palmer Index and of the nature of measuring drought in general.
The monitoring and analysis of drought have long suffered from the lack of an adequate definition of the phenomenon. As a result, drought indices have slowly evolved during the last two centuries from simplistic approaches based on some measure of rainfall deficiency, to more complex problem-specific models. Indices developed in the late nineteenth and early twentieth century included such measures as percent of normal precipitation over some interval, consecutive days with rain below a given threshold, formulae involving a combination of temperature and precipitation, and models factoring in precipitation deficits over consecutive days. The incorporation of evapotranspiration as a measure of water demand by Thornthwaite led to the landmark development in 1965 by Palmer of a water budget-based drought index that is still widely used. Drought indices developed since the 1960s include the Surface Water Supply Index, which supplements the Palmer Index by integrating snowpack, reservoir storage, streamflow, and precipitation at high elevations; the Keetch–Byram Drought Index, which is used by fire control managers; the Standardized Precipitation Index; and the Vegetation Condition Index, which utilizes global satellite observations of vegetation condition. These models continue to evolve as new data sources become available. The twentieth century concluded with the development of the Drought Monitor tool, which incorporates Palmer's index and several other (post Palmer) indices to provide a universal assessment of drought conditions across the entire United States. By putting the development of these drought indices into a historical perspective, this paper provides a better understanding of the complex Palmer Index and of the nature of measuring drought in general.
Abstract
The United States experienced a severe drought that peaked in 2012 and was characterized by near-record extent, record warmth, and record dryness in several areas. For some regions, the 2012 drought was a continuation of drought that began in earlier years and continued through 2014. The 1998–2014 drought episode is compared to the two other major drought episodes of the twentieth century in terms of duration, areal extent, intensity, and spatial pattern using operational datasets produced by the National Oceanic and Atmospheric Administration/National Centers for Environmental Information. It is characterized by more short-term dryness, more concurrent (regional) wetness, and warmer temperatures than the other two drought episodes. The implications of these differences for water resource managers and decision-makers are discussed.
Abstract
The United States experienced a severe drought that peaked in 2012 and was characterized by near-record extent, record warmth, and record dryness in several areas. For some regions, the 2012 drought was a continuation of drought that began in earlier years and continued through 2014. The 1998–2014 drought episode is compared to the two other major drought episodes of the twentieth century in terms of duration, areal extent, intensity, and spatial pattern using operational datasets produced by the National Oceanic and Atmospheric Administration/National Centers for Environmental Information. It is characterized by more short-term dryness, more concurrent (regional) wetness, and warmer temperatures than the other two drought episodes. The implications of these differences for water resource managers and decision-makers are discussed.
Abstract
The international scientific community has long recognized the need for coordinated drought monitoring and response, but many factors have prevented progress in the development of a Global Drought Early Warning System (GDEWS): some of which involve administrative issues (coordinated international action and policy) while others involve scientific, technological, and logistical issues. The creation of the National Integrated Drought Information System (NIDIS) Portal within the United States provided an opportunity to take the first steps toward building the informational foundation for a GDEWS: that is, a Global Drought Information System (GDIS). At a series of workshops sponsored by the World Meteorological Organization (WMO) and Group on Earth Observations (GEO) held in Asheville, North Carolina, in April 2010, it was recommended that a modular approach be taken in the creation of a GDIS and that the NIDIS Portal serve as the foundation for the GDIS structure. Once a NIDIS-based Global Drought Monitor (GDM) Portal (GDMP) established an international drought clearinghouse, the various components of a GDIS (drought monitoring, forecasting, impacts, history, research, and education) and later a GDEWS (drought relief, recovery, and planning) could be constructed atop it. The NIDIS Portal is a web-based information system created to address drought services and early warning in the United States, including drought monitoring, forecasting, impacts, mitigation, research, and education. This portal utilizes Open Geospatial Consortium (OGC) web mapping services (WMS) to incorporate continental drought monitors into the GDMP. As of early 2012, the GDM has incorporated continental drought information for North America (North American Drought Monitor), Europe (European Drought Observatory), and Africa (African Drought Monitor developed by Princeton University); interest has been expressed by groups representing Australia and South America; and coordination with appropriate parties in Asia is also expected. Because of the range of climates across the world and the diverse nature of drought and the sectors it impacts, the construction and functioning of each continental drought monitor needs to be appropriate for the continent in question. The GDMP includes a suite of global drought indicators identified by experts and adopted by the WMO as the necessary measures to examine drought from a meteorological standpoint; these global drought indicators provide a base to assist the global integration and interpretation of the continental drought monitors. The GDMP has been included in recent updates to the GEO Work Plan and has benefited from substantial coordination with WMO on both their Global Framework for Climate Services and the National Drought Policy efforts. The GDMP is recognized as having the potential to be a major contributor to both of these activities.
Abstract
The international scientific community has long recognized the need for coordinated drought monitoring and response, but many factors have prevented progress in the development of a Global Drought Early Warning System (GDEWS): some of which involve administrative issues (coordinated international action and policy) while others involve scientific, technological, and logistical issues. The creation of the National Integrated Drought Information System (NIDIS) Portal within the United States provided an opportunity to take the first steps toward building the informational foundation for a GDEWS: that is, a Global Drought Information System (GDIS). At a series of workshops sponsored by the World Meteorological Organization (WMO) and Group on Earth Observations (GEO) held in Asheville, North Carolina, in April 2010, it was recommended that a modular approach be taken in the creation of a GDIS and that the NIDIS Portal serve as the foundation for the GDIS structure. Once a NIDIS-based Global Drought Monitor (GDM) Portal (GDMP) established an international drought clearinghouse, the various components of a GDIS (drought monitoring, forecasting, impacts, history, research, and education) and later a GDEWS (drought relief, recovery, and planning) could be constructed atop it. The NIDIS Portal is a web-based information system created to address drought services and early warning in the United States, including drought monitoring, forecasting, impacts, mitigation, research, and education. This portal utilizes Open Geospatial Consortium (OGC) web mapping services (WMS) to incorporate continental drought monitors into the GDMP. As of early 2012, the GDM has incorporated continental drought information for North America (North American Drought Monitor), Europe (European Drought Observatory), and Africa (African Drought Monitor developed by Princeton University); interest has been expressed by groups representing Australia and South America; and coordination with appropriate parties in Asia is also expected. Because of the range of climates across the world and the diverse nature of drought and the sectors it impacts, the construction and functioning of each continental drought monitor needs to be appropriate for the continent in question. The GDMP includes a suite of global drought indicators identified by experts and adopted by the WMO as the necessary measures to examine drought from a meteorological standpoint; these global drought indicators provide a base to assist the global integration and interpretation of the continental drought monitors. The GDMP has been included in recent updates to the GEO Work Plan and has benefited from substantial coordination with WMO on both their Global Framework for Climate Services and the National Drought Policy efforts. The GDMP is recognized as having the potential to be a major contributor to both of these activities.
No Abstract available.
No Abstract available.
Accurate monitoring of the large-scale dimensions of global snow cover is essential for understanding details of climate dynamics and climate change. Presently, such information is gathered individually from ground station networks and satellite platforms. Efforts are in progress to consolidate and analyze long-term station records from a number of countries. To gain truly global coverage, however, satellite-based monitoring techniques must be employed. A 27-year record of Northern Hemisphere continental snow cover produced by the National Oceanic and Atmospheric Administration (NOAA) is the longest such environmental record available. Records of Southern Hemisphere continental cover and snow on top of Arctic sea ice have been produced by similar means for a portion of this interval. The visible imagery charting technique used to generate these data provides information on snow extent but not on snow volume. Satellite microwave analyses over Northern Hemisphere lands show some promise in this regard, however, large-scale monitoring of snow extent with microwave data remains less accurate than visible charting.
This paper updates the status of global snow cover monitoring, concentrating on the weekly snow charts prepared by NOAA and discussing a new and consistent record of monthly snow cover generated from these weekly charts. The NOAA charts show a reduction of hemispheric snow cover over the past five years, particularly in spring. Snow areas from the NOAA product are then compared with values derived using passive microwave data. The latter consistently reports less snow cover than the more accurate visible product. Finally, future snow monitoring initiatives are recommended. These include continuing the consistent NOAA product until an all-weather all-surface product is developed. The latter would use multiple data sources and geographic information systems techniques. Such an integrative product would need extensive comparisons with the NOAA product to ensure the continued utility of the lengthy NOAA observations in studies of climate change. In a retrospective sense, satellite charts from the middle 1960s to early 1970s need reevaluation and techniques to merge satellite products with historic station time series must be developed.
Accurate monitoring of the large-scale dimensions of global snow cover is essential for understanding details of climate dynamics and climate change. Presently, such information is gathered individually from ground station networks and satellite platforms. Efforts are in progress to consolidate and analyze long-term station records from a number of countries. To gain truly global coverage, however, satellite-based monitoring techniques must be employed. A 27-year record of Northern Hemisphere continental snow cover produced by the National Oceanic and Atmospheric Administration (NOAA) is the longest such environmental record available. Records of Southern Hemisphere continental cover and snow on top of Arctic sea ice have been produced by similar means for a portion of this interval. The visible imagery charting technique used to generate these data provides information on snow extent but not on snow volume. Satellite microwave analyses over Northern Hemisphere lands show some promise in this regard, however, large-scale monitoring of snow extent with microwave data remains less accurate than visible charting.
This paper updates the status of global snow cover monitoring, concentrating on the weekly snow charts prepared by NOAA and discussing a new and consistent record of monthly snow cover generated from these weekly charts. The NOAA charts show a reduction of hemispheric snow cover over the past five years, particularly in spring. Snow areas from the NOAA product are then compared with values derived using passive microwave data. The latter consistently reports less snow cover than the more accurate visible product. Finally, future snow monitoring initiatives are recommended. These include continuing the consistent NOAA product until an all-weather all-surface product is developed. The latter would use multiple data sources and geographic information systems techniques. Such an integrative product would need extensive comparisons with the NOAA product to ensure the continued utility of the lengthy NOAA observations in studies of climate change. In a retrospective sense, satellite charts from the middle 1960s to early 1970s need reevaluation and techniques to merge satellite products with historic station time series must be developed.
Abstract
Contemporary large-scale changes in solid and total precipitation and satellite-derived snow cover were examined over the North American continent. Annual snow cover extent over the last 19 years decreased up to 6×105 km2 relative to a 0.93°C (0.33°C) increase in North American (Northern Hemisphere) temperature.
A strong correlation exists between snow cover and temperature where up to 78% of the variance in regional snow cover and snowfall is explained by the anomalies of monthly mean maximum temperature. Over the last two decades the decrease in snow cover during winter (December-March) has largely occurred through reduced frequency of snow cover in areas that typically have a high probability of snow on the ground with little change in the frequency of snow cover in other areas. Similar characteristics were observed during spring (April-May) in areas with high snow cover probability except for an expansion of the snow-free regions. Anomalies in these two seasons dominate the interannual variability (nearly three-fourths of the variance) of snow cover.
The apparent unprecedented global warmth of the 1980s was accompanied by a retreat of the mean annual North American snow cover, a 10% increase in annual Alaskan precipitation, a significant decrease (−7% ) in annual snowfall over southern Canada (while the total precipitation remained above normal), and a more than twofold increase in the variance of the ratio of frozen to total precipitation over the contiguous United States. An increase (4% –5% per decade) of both solid and total precipitation over northern Canada (zone 55°–70°N) occurred during the last four decades. A century-scale increase (1% per decade) of precipitation was found over southern Canada, but the proportion of the precipitation that falls in frozen form over this area decreased over the last four decades. Precipitation over the contiguous United States has significantly (2% –3% per decade) increased during the last four decades, but on a century time scale the increasing trend is not yet statistically significant.
Abstract
Contemporary large-scale changes in solid and total precipitation and satellite-derived snow cover were examined over the North American continent. Annual snow cover extent over the last 19 years decreased up to 6×105 km2 relative to a 0.93°C (0.33°C) increase in North American (Northern Hemisphere) temperature.
A strong correlation exists between snow cover and temperature where up to 78% of the variance in regional snow cover and snowfall is explained by the anomalies of monthly mean maximum temperature. Over the last two decades the decrease in snow cover during winter (December-March) has largely occurred through reduced frequency of snow cover in areas that typically have a high probability of snow on the ground with little change in the frequency of snow cover in other areas. Similar characteristics were observed during spring (April-May) in areas with high snow cover probability except for an expansion of the snow-free regions. Anomalies in these two seasons dominate the interannual variability (nearly three-fourths of the variance) of snow cover.
The apparent unprecedented global warmth of the 1980s was accompanied by a retreat of the mean annual North American snow cover, a 10% increase in annual Alaskan precipitation, a significant decrease (−7% ) in annual snowfall over southern Canada (while the total precipitation remained above normal), and a more than twofold increase in the variance of the ratio of frozen to total precipitation over the contiguous United States. An increase (4% –5% per decade) of both solid and total precipitation over northern Canada (zone 55°–70°N) occurred during the last four decades. A century-scale increase (1% per decade) of precipitation was found over southern Canada, but the proportion of the precipitation that falls in frozen form over this area decreased over the last four decades. Precipitation over the contiguous United States has significantly (2% –3% per decade) increased during the last four decades, but on a century time scale the increasing trend is not yet statistically significant.
Abstract
Two climate indices that are useful for monitoring the impact of weather and climate on energy usage and crop yields in the United States have been developed at the National Climatic Data Center. The residential energy-demand temperature index (REDTI), which is based on total population-weighted heating and cooling degree days in the contiguous United States, provides quantitative information on the impact of seasonal temperatures on residential energy demand. The moisture stress index (MSI) is based on the effect of severe to catastrophic drought (Palmer Z index values ≤−2) or catastrophic wetness (Z ≥ +5) on crop productivity within two crop-growing regions (corn and soybeans). Using climate data that extends into the late nineteenth century and operational updates of near-real-time data, the indices provide information that places the impact of weather and climate on energy-supply and crop-production sectors of the economy during the most recent season into historical perspective.
Abstract
Two climate indices that are useful for monitoring the impact of weather and climate on energy usage and crop yields in the United States have been developed at the National Climatic Data Center. The residential energy-demand temperature index (REDTI), which is based on total population-weighted heating and cooling degree days in the contiguous United States, provides quantitative information on the impact of seasonal temperatures on residential energy demand. The moisture stress index (MSI) is based on the effect of severe to catastrophic drought (Palmer Z index values ≤−2) or catastrophic wetness (Z ≥ +5) on crop productivity within two crop-growing regions (corn and soybeans). Using climate data that extends into the late nineteenth century and operational updates of near-real-time data, the indices provide information that places the impact of weather and climate on energy-supply and crop-production sectors of the economy during the most recent season into historical perspective.
This paper describes a new snowfall index that quantifies the impact of snowstorms within six climate regions in the United States. The regional snowfall index (RSI) is based on the spatial extent of snowfall accumulation, the amount of snowfall, and the juxtaposition of these elements with population. Including population information provides a measure of the societal susceptibility for each region. The RSI is an evolution of the Northeast snowfall impact scale (NESIS), which NOAA's National Climatic Data Center began producing operationally in 2006. While NESIS was developed for storms that had a major impact in the Northeast, it includes all snowfall during the lifetime of a storm across the United States and as such can be thought of as a quasi-national index that is calibrated to Northeast snowstorms. By contrast, the RSI is a regional index calibrated to specific regions using only the snow that falls within that region. This paper describes the methodology used to compute the RSI, which requires region-specific parameters and thresholds, and its application within six climate regions in the eastern two-thirds of the nation. The process used to select the region-specific parameters and thresholds is explained. The new index has been calculated for over 580 snowstorms that occurred between 1900 and 2013 providing a century-scale historical perspective for these snowstorms. The RSI is computed for category 1 or greater storms in near–real time, usually a day after the storm has ended.
This paper describes a new snowfall index that quantifies the impact of snowstorms within six climate regions in the United States. The regional snowfall index (RSI) is based on the spatial extent of snowfall accumulation, the amount of snowfall, and the juxtaposition of these elements with population. Including population information provides a measure of the societal susceptibility for each region. The RSI is an evolution of the Northeast snowfall impact scale (NESIS), which NOAA's National Climatic Data Center began producing operationally in 2006. While NESIS was developed for storms that had a major impact in the Northeast, it includes all snowfall during the lifetime of a storm across the United States and as such can be thought of as a quasi-national index that is calibrated to Northeast snowstorms. By contrast, the RSI is a regional index calibrated to specific regions using only the snow that falls within that region. This paper describes the methodology used to compute the RSI, which requires region-specific parameters and thresholds, and its application within six climate regions in the eastern two-thirds of the nation. The process used to select the region-specific parameters and thresholds is explained. The new index has been calculated for over 580 snowstorms that occurred between 1900 and 2013 providing a century-scale historical perspective for these snowstorms. The RSI is computed for category 1 or greater storms in near–real time, usually a day after the storm has ended.
Abstract
Using the Palmer drought severity index, the ability of 19 state-of-the-art climate models to reproduce observed statistics of drought over North America is examined. It is found that correction of substantial biases in the models’ surface air temperature and precipitation fields is necessary. However, even after a bias correction, there are significant differences in the models’ ability to reproduce observations. Using metrics based on the ability to reproduce observed temporal and spatial patterns of drought, the relationship between model performance in simulating present-day drought characteristics and their differences in projections of future drought changes is investigated. It is found that all models project increases in future drought frequency and severity. However, using the metrics presented here to increase confidence in the multimodel projection is complicated by a correlation between models’ drought metric skill and climate sensitivity. The effect of this sampling error can be removed by changing how the projection is presented, from a projection based on a specific time interval to a projection based on a specified temperature change. This modified class of projections has reduced intermodel uncertainty and could be suitable for a wide range of climate change impacts projections.
Abstract
Using the Palmer drought severity index, the ability of 19 state-of-the-art climate models to reproduce observed statistics of drought over North America is examined. It is found that correction of substantial biases in the models’ surface air temperature and precipitation fields is necessary. However, even after a bias correction, there are significant differences in the models’ ability to reproduce observations. Using metrics based on the ability to reproduce observed temporal and spatial patterns of drought, the relationship between model performance in simulating present-day drought characteristics and their differences in projections of future drought changes is investigated. It is found that all models project increases in future drought frequency and severity. However, using the metrics presented here to increase confidence in the multimodel projection is complicated by a correlation between models’ drought metric skill and climate sensitivity. The effect of this sampling error can be removed by changing how the projection is presented, from a projection based on a specific time interval to a projection based on a specified temperature change. This modified class of projections has reduced intermodel uncertainty and could be suitable for a wide range of climate change impacts projections.
