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Abstract
“Megafires” are of scientific interest and concern for fire management, public safety planning, and smoke-related public health management. There is a need to predict them on time scales from days to decades. Understanding is limited, however, of the role of daily weather in determining their extreme size. This study examines differences in the daily weather during these and other smaller fires, and in the two sets of fires’ responses to daily weather and antecedent atmospheric dryness. Twenty fires of unusual size (over 36 400 ha), were each paired with a nearby large fire (10 100–30 300 ha). Antecedent dryness and daily near-surface weather were compared for each set of fires. Growth response to daily weather was also examined for differences between the two sets of fires. Antecedent dryness measured as the evaporative demand drought index was greater for most of the fires of unusual size than it was for smaller fires. There were small differences in daily weather, with those differences indicating weather less conducive to fire growth for the unusually large fires than the smaller fires. Growth response was similar for the two sets of fires when weather properties were between 40th and 60th percentiles for each fire pair, but the unusually large fires’ growth was observably greater than the smaller fires’ growth for weather properties between the 80th to 100th percentiles. Response differences were greatest for wind speed, and for the Fosberg fire weather index and variants of the hot-dry-windy index, which combine wind speed with atmospheric moisture.
Abstract
“Megafires” are of scientific interest and concern for fire management, public safety planning, and smoke-related public health management. There is a need to predict them on time scales from days to decades. Understanding is limited, however, of the role of daily weather in determining their extreme size. This study examines differences in the daily weather during these and other smaller fires, and in the two sets of fires’ responses to daily weather and antecedent atmospheric dryness. Twenty fires of unusual size (over 36 400 ha), were each paired with a nearby large fire (10 100–30 300 ha). Antecedent dryness and daily near-surface weather were compared for each set of fires. Growth response to daily weather was also examined for differences between the two sets of fires. Antecedent dryness measured as the evaporative demand drought index was greater for most of the fires of unusual size than it was for smaller fires. There were small differences in daily weather, with those differences indicating weather less conducive to fire growth for the unusually large fires than the smaller fires. Growth response was similar for the two sets of fires when weather properties were between 40th and 60th percentiles for each fire pair, but the unusually large fires’ growth was observably greater than the smaller fires’ growth for weather properties between the 80th to 100th percentiles. Response differences were greatest for wind speed, and for the Fosberg fire weather index and variants of the hot-dry-windy index, which combine wind speed with atmospheric moisture.
Abstract
The concept of snow drought is gaining widespread interest as the climate of snow-dominated mountain watersheds continues to change. Warm snow drought is defined as above- or near-average accumulated precipitation coinciding with below-average snow water equivalent at a point in time. Dry snow drought is defined as below-average accumulated precipitation and snow water equivalent at a point in time. This study contends that such point-in-time definitions might miss important components of how snow droughts originate, persist, and terminate. Using these simple definitions and a variety of observations at monthly, daily, and hourly time scales, the authors explore the hydrometeorological origins of potential snow droughts in the northern Sierra Nevada from water years 1951 to 2017. This study finds that snow droughts can result from extreme early season precipitation, frequent rain-on-snow events, and low precipitation years. Late-season snow droughts can follow persistent warm and dry periods with effects that depend upon elevation. Many snow droughts were characterized by lower snow fractions and midwinter peak runoff events. These findings can guide improved evaluations of historical and potential future snow droughts, particularly with regards to how impacts on water resources and mountain ecosystems may vary depending on how snow droughts originate and evolve in time.
Abstract
The concept of snow drought is gaining widespread interest as the climate of snow-dominated mountain watersheds continues to change. Warm snow drought is defined as above- or near-average accumulated precipitation coinciding with below-average snow water equivalent at a point in time. Dry snow drought is defined as below-average accumulated precipitation and snow water equivalent at a point in time. This study contends that such point-in-time definitions might miss important components of how snow droughts originate, persist, and terminate. Using these simple definitions and a variety of observations at monthly, daily, and hourly time scales, the authors explore the hydrometeorological origins of potential snow droughts in the northern Sierra Nevada from water years 1951 to 2017. This study finds that snow droughts can result from extreme early season precipitation, frequent rain-on-snow events, and low precipitation years. Late-season snow droughts can follow persistent warm and dry periods with effects that depend upon elevation. Many snow droughts were characterized by lower snow fractions and midwinter peak runoff events. These findings can guide improved evaluations of historical and potential future snow droughts, particularly with regards to how impacts on water resources and mountain ecosystems may vary depending on how snow droughts originate and evolve in time.
Abstract
Predicting sharp hydroclimatic gradients in the complex terrain of the Great Basin can prove to be challenging because of the lack of climate observations that are gradient focused. Furthermore, evaluating gridded data products (GDPs) of climate in such environments for use in local hydroclimatic assessments is also challenging and typically ignored because of the lack of observations. In this study, independent Nevada Climate-Ecohydrological Assessment Network (NevCAN) observations of temperature, relative humidity, and precipitation collected along large altitudinal gradients of the Snake and Sheep mountain ranges from water-year 2012 (October–September) are utilized to evaluate four GDPs of different spatial resolutions: Parameter–Elevation Regressions on Independent Slopes Model (PRISM) 4 km, PRISM 800 m, Daymet 1 km, and a North American Land Data Assimilation System (NLDAS)–PRISM hybrid 4-km product. Inconsistencies and biases in precipitation measurements due to station siting and gauge type proved to be problematic with respect to comparisons to GDPs. This study highlights a weakness of GDPs in complex terrain: an underestimation of inversion strength and resulting minimum temperature in foothill regions, where cold air regularly drains into neighboring valleys. Results also clearly indicate that for semiarid regions, the assumption that daily average dewpoint temperature T dew equals daily minimum temperature does not hold true and should not be used to interpolate T dew spatially. Comparison statistics of GDPs to observations varied depending on the climate variable and grid spatial resolution, highlighting the importance of conducting local evaluations for hydroclimatic assessments.
Abstract
Predicting sharp hydroclimatic gradients in the complex terrain of the Great Basin can prove to be challenging because of the lack of climate observations that are gradient focused. Furthermore, evaluating gridded data products (GDPs) of climate in such environments for use in local hydroclimatic assessments is also challenging and typically ignored because of the lack of observations. In this study, independent Nevada Climate-Ecohydrological Assessment Network (NevCAN) observations of temperature, relative humidity, and precipitation collected along large altitudinal gradients of the Snake and Sheep mountain ranges from water-year 2012 (October–September) are utilized to evaluate four GDPs of different spatial resolutions: Parameter–Elevation Regressions on Independent Slopes Model (PRISM) 4 km, PRISM 800 m, Daymet 1 km, and a North American Land Data Assimilation System (NLDAS)–PRISM hybrid 4-km product. Inconsistencies and biases in precipitation measurements due to station siting and gauge type proved to be problematic with respect to comparisons to GDPs. This study highlights a weakness of GDPs in complex terrain: an underestimation of inversion strength and resulting minimum temperature in foothill regions, where cold air regularly drains into neighboring valleys. Results also clearly indicate that for semiarid regions, the assumption that daily average dewpoint temperature T dew equals daily minimum temperature does not hold true and should not be used to interpolate T dew spatially. Comparison statistics of GDPs to observations varied depending on the climate variable and grid spatial resolution, highlighting the importance of conducting local evaluations for hydroclimatic assessments.
Abstract
Drought is a recurrent natural phenomenon, but there is concern that climate change may increase the frequency or severity of drought in Alaska. Because most common drought indices were designed for lower latitudes, it is unclear how effectively they characterize drought in Alaska’s diverse, high-latitude climates. Here, we compare three commonly used meteorological drought indices [the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), and the self-calibrating Palmer drought severity index (scPDSI)] with each other and with streamflow across Alaska’s 13 climate divisions. All of the drought indices identify major droughts, but the severity of the drought varies depending on the index used. The SPI and the SPEI are more flexible and often better correlated with streamflow than the scPDSI, and we recommend using them. Although SPI and SPEI are very similar in energy-limited climates, the drought metrics do diverge in drier locations in recent years, and consideration of the impact of temperature on drought may grow more important in the coming decades. Hargreaves potential evapotranspiration (PET) estimates appeared more physically realistic than the more commonly used Thornthwaite equation and are equally easy to calculate, so we suggest using the Hargreaves equation when PET is estimated from temperature. This study, one of the first to evaluate drought indices for high-latitude regions, has the potential to improve drought monitoring and representation within the U.S. Drought Monitor, leading to more informed decision-making during drought in Alaska, and it improves our ability to track changes in drought driven by rising temperatures.
Significance Statement
Tracking drought at high latitudes is challenging because we have not adequately studied drought impacts in cold climates, and the primary meteorological drought indices were designed for lower latitudes and may not accurately estimate evaporative demand and the influence of snow. We investigate three common drought indices and recommend using the standardized precipitation index (SPI) or the standardized precipitation evapotranspiration index (SPEI) because they can track short and long droughts. The SPEI may be more useful because comparisons between the SPI and SPEI show that, in recent decades, temperature has made noticeable contributions to drought in drier parts of Alaska. If using the SPEI, we suggest the Hargreaves potential evapotranspiration rather than the Thornthwaite because it is more physically realistic.
Abstract
Drought is a recurrent natural phenomenon, but there is concern that climate change may increase the frequency or severity of drought in Alaska. Because most common drought indices were designed for lower latitudes, it is unclear how effectively they characterize drought in Alaska’s diverse, high-latitude climates. Here, we compare three commonly used meteorological drought indices [the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), and the self-calibrating Palmer drought severity index (scPDSI)] with each other and with streamflow across Alaska’s 13 climate divisions. All of the drought indices identify major droughts, but the severity of the drought varies depending on the index used. The SPI and the SPEI are more flexible and often better correlated with streamflow than the scPDSI, and we recommend using them. Although SPI and SPEI are very similar in energy-limited climates, the drought metrics do diverge in drier locations in recent years, and consideration of the impact of temperature on drought may grow more important in the coming decades. Hargreaves potential evapotranspiration (PET) estimates appeared more physically realistic than the more commonly used Thornthwaite equation and are equally easy to calculate, so we suggest using the Hargreaves equation when PET is estimated from temperature. This study, one of the first to evaluate drought indices for high-latitude regions, has the potential to improve drought monitoring and representation within the U.S. Drought Monitor, leading to more informed decision-making during drought in Alaska, and it improves our ability to track changes in drought driven by rising temperatures.
Significance Statement
Tracking drought at high latitudes is challenging because we have not adequately studied drought impacts in cold climates, and the primary meteorological drought indices were designed for lower latitudes and may not accurately estimate evaporative demand and the influence of snow. We investigate three common drought indices and recommend using the standardized precipitation index (SPI) or the standardized precipitation evapotranspiration index (SPEI) because they can track short and long droughts. The SPEI may be more useful because comparisons between the SPI and SPEI show that, in recent decades, temperature has made noticeable contributions to drought in drier parts of Alaska. If using the SPEI, we suggest the Hargreaves potential evapotranspiration rather than the Thornthwaite because it is more physically realistic.
Abstract
The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, central Asia, and Central America. This study describes development of a new global reference evapotranspiration (ET0) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by FEWS NET to support food insecurity early warning. The ET0 reforecasts span the 1982–2009 period and are calculated following the American Society for Civil Engineers formulation of the Penman–Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from the National Centers for Environmental Prediction CFSv2 model and the National Aeronautics and Space Administration GEOS-5 model. The skill evaluation, using deterministic and probabilistic scores, focuses on the December–February (DJF), March–May (MAM), June–August (JJA), and September–November seasons. The results indicate that ET0 forecasts are a promising tool for early warning of drought and food insecurity. Globally, the regions where forecasts are most skillful (correlation > 0.35 at leads of 2 months) include the western United States, northern parts of South America, parts of the Sahel region, and southern Africa. The FEWS NET regions where forecasts are most skillful (correlation > 0.35 at lead 3) include northern sub-Saharan Africa (DJF; dry season), Central America (DJF; dry season), parts of East Africa (JJA; wet season), southern Africa (JJA; dry season), and central Asia (MAM; wet season). A case study over parts of East Africa for the JJA season shows that ET0 forecasts in combination with the precipitation forecasts would have provided early warning of recent severe drought events (e.g., in 2002, 2004, 2009) that contributed to substantial food insecurity in the region.
Abstract
The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, central Asia, and Central America. This study describes development of a new global reference evapotranspiration (ET0) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by FEWS NET to support food insecurity early warning. The ET0 reforecasts span the 1982–2009 period and are calculated following the American Society for Civil Engineers formulation of the Penman–Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from the National Centers for Environmental Prediction CFSv2 model and the National Aeronautics and Space Administration GEOS-5 model. The skill evaluation, using deterministic and probabilistic scores, focuses on the December–February (DJF), March–May (MAM), June–August (JJA), and September–November seasons. The results indicate that ET0 forecasts are a promising tool for early warning of drought and food insecurity. Globally, the regions where forecasts are most skillful (correlation > 0.35 at leads of 2 months) include the western United States, northern parts of South America, parts of the Sahel region, and southern Africa. The FEWS NET regions where forecasts are most skillful (correlation > 0.35 at lead 3) include northern sub-Saharan Africa (DJF; dry season), Central America (DJF; dry season), parts of East Africa (JJA; wet season), southern Africa (JJA; dry season), and central Asia (MAM; wet season). A case study over parts of East Africa for the JJA season shows that ET0 forecasts in combination with the precipitation forecasts would have provided early warning of recent severe drought events (e.g., in 2002, 2004, 2009) that contributed to substantial food insecurity in the region.
Abstract
Nevada and eastern California are home to some of the driest and warmest climates, most mountainous regions, and fastest growing metropolitan areas of the United States. Throughout Nevada and eastern California, snow-dominated watersheds provide most of the water supply for both human and environmental demands. Increasing demands on finite water supplies have resulted in the need to better monitor drought and its associated hydrologic and agricultural impacts. Two multiscalar drought indices, the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI), are evaluated over Nevada and eastern California regions of the Great Basin using standardized streamflow, lake, and reservoir water surface stages to quantify wet and dry periods. Results show that both metrics are significantly correlated to surface water availability, with SPEI showing slightly higher correlations over SPI, suggesting that the inclusion of a simple term for atmospheric demand in SPEI is useful for characterizing hydrologic drought in arid regions. These results also highlight the utility of multiscalar drought indices as a proxy for summer groundwater discharge and baseflow periods.
Abstract
Nevada and eastern California are home to some of the driest and warmest climates, most mountainous regions, and fastest growing metropolitan areas of the United States. Throughout Nevada and eastern California, snow-dominated watersheds provide most of the water supply for both human and environmental demands. Increasing demands on finite water supplies have resulted in the need to better monitor drought and its associated hydrologic and agricultural impacts. Two multiscalar drought indices, the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI), are evaluated over Nevada and eastern California regions of the Great Basin using standardized streamflow, lake, and reservoir water surface stages to quantify wet and dry periods. Results show that both metrics are significantly correlated to surface water availability, with SPEI showing slightly higher correlations over SPI, suggesting that the inclusion of a simple term for atmospheric demand in SPEI is useful for characterizing hydrologic drought in arid regions. These results also highlight the utility of multiscalar drought indices as a proxy for summer groundwater discharge and baseflow periods.
Abstract
Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E 0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E 0—the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E 0 to surface drying anomalies that result from two distinct land surface–atmosphere interactions: 1) a complementary relationship between E 0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E 0, as in sustained droughts, and 2) parallel ET and E 0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E 0, a long-term, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E 0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in .
Abstract
Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E 0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E 0—the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E 0 to surface drying anomalies that result from two distinct land surface–atmosphere interactions: 1) a complementary relationship between E 0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E 0, as in sustained droughts, and 2) parallel ET and E 0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E 0, a long-term, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E 0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in .
Abstract
Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought; however, other climatic factors such as solar radiation, wind speed, and humidity can be important drivers in the depletion of soil moisture and evolution and persistence of drought. This work assesses the Evaporative Demand Drought Index (EDDI) at multiple time scales for several hydroclimates as the second part of a two-part study. EDDI and individual evaporative demand components were examined as they relate to the dynamic evolution of flash drought over the central United States, characterization of hydrologic drought over the western United States, and comparison to commonly used drought metrics of the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI), and the evaporative stress index (ESI). Two main advantages of EDDI over other drought indices are that it is independent of precipitation (similar to ESI) and it can be decomposed to identify the role individual evaporative drivers have on drought onset and persistence. At short time scales, spatial distributions and time series results illustrate that EDDI often indicates drought onset well in advance of the USDM, SPI, and SSI. Results illustrate the benefits of physically based evaporative demand estimates and demonstrate EDDI’s utility and effectiveness in an easy-to-implement agricultural early warning and long-term hydrologic drought–monitoring tool with potential applications in seasonal forecasting and fire-weather monitoring.
Abstract
Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought; however, other climatic factors such as solar radiation, wind speed, and humidity can be important drivers in the depletion of soil moisture and evolution and persistence of drought. This work assesses the Evaporative Demand Drought Index (EDDI) at multiple time scales for several hydroclimates as the second part of a two-part study. EDDI and individual evaporative demand components were examined as they relate to the dynamic evolution of flash drought over the central United States, characterization of hydrologic drought over the western United States, and comparison to commonly used drought metrics of the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI), and the evaporative stress index (ESI). Two main advantages of EDDI over other drought indices are that it is independent of precipitation (similar to ESI) and it can be decomposed to identify the role individual evaporative drivers have on drought onset and persistence. At short time scales, spatial distributions and time series results illustrate that EDDI often indicates drought onset well in advance of the USDM, SPI, and SSI. Results illustrate the benefits of physically based evaporative demand estimates and demonstrate EDDI’s utility and effectiveness in an easy-to-implement agricultural early warning and long-term hydrologic drought–monitoring tool with potential applications in seasonal forecasting and fire-weather monitoring.
