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- Author or Editor: Kingtse C. Mo x
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Abstract
The sensitivity of the systematic error of extended-range forecasts to sea surface temperature (SST) anomalies is investigated. General circulation model (GCM) experiments were performed to quantify error patterns for warm, normal, and cold SST anomalies in the equatorial central Pacific. The model underestimates the strength of tropical convection during warm El Niño-Southern Oscillation (ENSO) episodes and has large zonal mean errors in midlatitudes. The model captures the negative Pacific-North American teleconnection (PNA) pattern during the cold ENSO episodes, but the simulated amplitude is too weak. The time-mean errors during warm and cold ENSO events bear little resemblance to the errors estimated from a 10-yr integration, which includes both warm and cold episodes. The time-mean error of a 10-yr integration is a good estimate of the systematic model error only for those years when SSTs are close to climatology.
Abstract
The sensitivity of the systematic error of extended-range forecasts to sea surface temperature (SST) anomalies is investigated. General circulation model (GCM) experiments were performed to quantify error patterns for warm, normal, and cold SST anomalies in the equatorial central Pacific. The model underestimates the strength of tropical convection during warm El Niño-Southern Oscillation (ENSO) episodes and has large zonal mean errors in midlatitudes. The model captures the negative Pacific-North American teleconnection (PNA) pattern during the cold ENSO episodes, but the simulated amplitude is too weak. The time-mean errors during warm and cold ENSO events bear little resemblance to the errors estimated from a 10-yr integration, which includes both warm and cold episodes. The time-mean error of a 10-yr integration is a good estimate of the systematic model error only for those years when SSTs are close to climatology.
Abstract
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Abstract
Large-scale aspects of the atmospheric moisture transport and the overall moisture budget we studied using data from the National Centers for Environmental Prediction (NCEP) reanalysis. Our objective is to critically evaluate the usefulness of the reanalysis products for studies of the global hydrologic cycle. The study period is from January 1985 to December 1993. Monthly mean water vapor transport, evaporation, and precipitation are compared to the NASA Data Assimilation Office (DAO) reanalysis for roughly the same period and with satellite estimates and station observations.
Comparisons of the moisture flux fields form the NCEP and the DAO reanalyses show general agreement in most aspects, but there are regional differences. Discrepancies in tropical moisture transport are largely due to uncertainties in the divergent winds. The DAO reanalysis shows a weaker Hadley circulation and weaker cross-equatorial flow, particularly during the Northern Hemisphere winter.
Global patterns of evaporation from the two reanalyses are similar, but the NCEP values are higher over the oceans and lower over the landmasses. In the eastern Pacific, the DAO has less total precipitable water and less rainfall. While the large-scale features of precipitation from the reanalyses agree with each other and are within the envelope of the satellite rainfall estimates, regional differences are large. Both analyses show questionable features in the moisture flux divergence fields over North and South America that are to a large extent terrain related. Interannual variability related to the 1987–1989 ENSO cycle is well captured by both reanalyses. On intraseasonal timescales, the NCEP reanalysis has difficulty capturing the precipitation signal associated with the 30–60 day oscillation, but the moisture flux divergence from both reanalyses produces a more reasonable signal.
An examination of the overall moisture budget for rectangular regions over North and South America in both reanalyses reveals large differences in the moisture flux divergence. Both reanalyses overestimate rainfall in the southeastern United States. The largest uncertainties during the spring and summer months are directly related to differences in the topographically bound low-level jets.
Abstract
Large-scale aspects of the atmospheric moisture transport and the overall moisture budget we studied using data from the National Centers for Environmental Prediction (NCEP) reanalysis. Our objective is to critically evaluate the usefulness of the reanalysis products for studies of the global hydrologic cycle. The study period is from January 1985 to December 1993. Monthly mean water vapor transport, evaporation, and precipitation are compared to the NASA Data Assimilation Office (DAO) reanalysis for roughly the same period and with satellite estimates and station observations.
Comparisons of the moisture flux fields form the NCEP and the DAO reanalyses show general agreement in most aspects, but there are regional differences. Discrepancies in tropical moisture transport are largely due to uncertainties in the divergent winds. The DAO reanalysis shows a weaker Hadley circulation and weaker cross-equatorial flow, particularly during the Northern Hemisphere winter.
Global patterns of evaporation from the two reanalyses are similar, but the NCEP values are higher over the oceans and lower over the landmasses. In the eastern Pacific, the DAO has less total precipitable water and less rainfall. While the large-scale features of precipitation from the reanalyses agree with each other and are within the envelope of the satellite rainfall estimates, regional differences are large. Both analyses show questionable features in the moisture flux divergence fields over North and South America that are to a large extent terrain related. Interannual variability related to the 1987–1989 ENSO cycle is well captured by both reanalyses. On intraseasonal timescales, the NCEP reanalysis has difficulty capturing the precipitation signal associated with the 30–60 day oscillation, but the moisture flux divergence from both reanalyses produces a more reasonable signal.
An examination of the overall moisture budget for rectangular regions over North and South America in both reanalyses reveals large differences in the moisture flux divergence. Both reanalyses overestimate rainfall in the southeastern United States. The largest uncertainties during the spring and summer months are directly related to differences in the topographically bound low-level jets.
Abstract
The current generation of drought monitors uses physically based indices, such as the standardized precipitation index (SPI), total soil moisture (SM) percentiles, and the standardized runoff index (SRI) to monitor precipitation, soil moisture, and runoff deficits, respectively. Because long-term observations of soil moisture and, to a lesser extent, spatially distributed runoff are not generally available, SRI and SMP are more commonly derived from land surface model–derived variables, where the models are forced with observed quantities such as precipitation, surface air temperature, and winds. One example of such a system is the North American Land Data Assimilation System (NLDAS). While monitoring systems based on sources like NLDAS are able to detect droughts, they are challenged by classification of drought into, for instance, the D0–D4 categories used by the U.S. Drought Monitor (USDM), in part because of uncertainties among multiple drought indicators, models, and assimilation systems. An objective scheme for drawing boundaries between the D0–D4 classes used by the USDM is explored here. The approach is based on multiple SPI, SM, and SRI indices, from which an ensemble mean index is formed. The mean index is then remapped to a uniform distribution by using the climatology of the ensemble (percentile) averages. To assess uncertainties in the classification, a concurrence measure is used to show the extent to which the different indices agree. An approach to drought classification that uses both the mean of the ensembles and its concurrence measure is described. The classification scheme gives an idea of drought severity, as well as the representativeness of the ensemble mean index.
Abstract
The current generation of drought monitors uses physically based indices, such as the standardized precipitation index (SPI), total soil moisture (SM) percentiles, and the standardized runoff index (SRI) to monitor precipitation, soil moisture, and runoff deficits, respectively. Because long-term observations of soil moisture and, to a lesser extent, spatially distributed runoff are not generally available, SRI and SMP are more commonly derived from land surface model–derived variables, where the models are forced with observed quantities such as precipitation, surface air temperature, and winds. One example of such a system is the North American Land Data Assimilation System (NLDAS). While monitoring systems based on sources like NLDAS are able to detect droughts, they are challenged by classification of drought into, for instance, the D0–D4 categories used by the U.S. Drought Monitor (USDM), in part because of uncertainties among multiple drought indicators, models, and assimilation systems. An objective scheme for drawing boundaries between the D0–D4 classes used by the USDM is explored here. The approach is based on multiple SPI, SM, and SRI indices, from which an ensemble mean index is formed. The mean index is then remapped to a uniform distribution by using the climatology of the ensemble (percentile) averages. To assess uncertainties in the classification, a concurrence measure is used to show the extent to which the different indices agree. An approach to drought classification that uses both the mean of the ensembles and its concurrence measure is described. The classification scheme gives an idea of drought severity, as well as the representativeness of the ensemble mean index.
Abstract
The authors analyzed the skill of monthly and seasonal soil moisture (SM) and runoff (RO) forecasts over the United States performed by driving the Variable Infiltration Capacity (VIC) hydrologic model with forcings derived from the National Multi-Model Ensemble hindcasts (NMME_VIC). The grand ensemble mean NMME_VIC forecasts were compared to ensemble streamflow prediction (ESP) forecasts derived from the VIC model forced by resampling of historical observations during the forecast period (ESP_VIC), using the same initial conditions as NMME_VIC. The forecast period is from 1982 to 2010, with the forecast initialized on 1 January, 1 April, 5 July, and 3 October. Overall, forecast skill is seasonally and regionally dependent. The authors found that 1) the skill of the grand ensemble mean NMME_VIC forecasts is comparable with that of the individual model that has the highest skill; 2) for all forecast initiation dates, the initial conditions play a dominant role in forecast skill at 1-month lead, and at longer lead times, forcings derived from NMME forecasts start to contribute to forecast skill; and 3) the initial conditions dominate contributions to skill for a dry climate regime that covers the western interior states for all seasons and the north-central part of the country for January. In this regime, the forecast skill for both methods is high even at 3-month lead. This regime has low mean precipitation and precipitation variations, and the influence of precipitation on SM and RO is weak. In contrast, a wet regime covers the region from the Gulf states to the Tennessee and Ohio Valleys for forecasts initialized in January and April, the Southwest monsoon region, the Southeast, and the East Coast in summer. In these dynamically active regions, where rainfall depends on the path of the moisture transport and atmospheric forcing, forecast skill is low. For this regime, the climate forecasts contribute to skill. Skillful precipitation forecasts after lead 1 have the potential to improve SM and RO forecast skill, but it was found that this mostly was not the case for the NMME models.
Abstract
The authors analyzed the skill of monthly and seasonal soil moisture (SM) and runoff (RO) forecasts over the United States performed by driving the Variable Infiltration Capacity (VIC) hydrologic model with forcings derived from the National Multi-Model Ensemble hindcasts (NMME_VIC). The grand ensemble mean NMME_VIC forecasts were compared to ensemble streamflow prediction (ESP) forecasts derived from the VIC model forced by resampling of historical observations during the forecast period (ESP_VIC), using the same initial conditions as NMME_VIC. The forecast period is from 1982 to 2010, with the forecast initialized on 1 January, 1 April, 5 July, and 3 October. Overall, forecast skill is seasonally and regionally dependent. The authors found that 1) the skill of the grand ensemble mean NMME_VIC forecasts is comparable with that of the individual model that has the highest skill; 2) for all forecast initiation dates, the initial conditions play a dominant role in forecast skill at 1-month lead, and at longer lead times, forcings derived from NMME forecasts start to contribute to forecast skill; and 3) the initial conditions dominate contributions to skill for a dry climate regime that covers the western interior states for all seasons and the north-central part of the country for January. In this regime, the forecast skill for both methods is high even at 3-month lead. This regime has low mean precipitation and precipitation variations, and the influence of precipitation on SM and RO is weak. In contrast, a wet regime covers the region from the Gulf states to the Tennessee and Ohio Valleys for forecasts initialized in January and April, the Southwest monsoon region, the Southeast, and the East Coast in summer. In these dynamically active regions, where rainfall depends on the path of the moisture transport and atmospheric forcing, forecast skill is low. For this regime, the climate forecasts contribute to skill. Skillful precipitation forecasts after lead 1 have the potential to improve SM and RO forecast skill, but it was found that this mostly was not the case for the NMME models.
Abstract
The variability of sea surface temperature anomalies (SSTAs) in the tropical Atlantic is examined using data from 1900 to the present. SSTAs are filtered to focus on the interannual band with fluctuations less than 60 months. Both SSTAs over the northern tropical Atlantic (NTA) and the southern tropical Atlantic (STA) are associated with the El Niño–Southern Oscillation (ENSO) variability in the tropical Pacific. SSTAs over the STA are associated with the quasi-biennial component of ENSO with a timescale of 22–32 months, and SSTAs over the NTA are influenced by the low-frequency part of the ENSO signal with a timescale of 36–48 months. The ENSO influence is seasonally dependent. The strongest linkages occur in the spring of each hemisphere. In addition to ENSO, SSTAs in the north equatorial Atlantic are also modulated by the circulation and net heat flux anomalies associated with the North Atlantic oscillation (NAO).
The atmospheric impact on the ocean is different in the STA and NTA regions. When the quasi-biennial signal is strong in the central Pacific during September–November, warm SSTAs excite the Pacific South American wave train extending from the Pacific to the South Atlantic. The associated wind-driven dynamics initiates the changes in the STA. The local net heat flux anomalies and ocean wave dynamics influence the location and the strength of the SSTA maximum. The SSTAs over the NTA region are driven by the local heat flux anomalies related to the trade wind changes associated with the low-frequency component of ENSO in the Pacific. The magnitudes of SSTAs depend on the phase of the NAO. The net heat flux anomalies associated with the NAO may enhance or diminish the impact of ENSO over the NTA region and modulate SSTAs in the North Atlantic.
Abstract
The variability of sea surface temperature anomalies (SSTAs) in the tropical Atlantic is examined using data from 1900 to the present. SSTAs are filtered to focus on the interannual band with fluctuations less than 60 months. Both SSTAs over the northern tropical Atlantic (NTA) and the southern tropical Atlantic (STA) are associated with the El Niño–Southern Oscillation (ENSO) variability in the tropical Pacific. SSTAs over the STA are associated with the quasi-biennial component of ENSO with a timescale of 22–32 months, and SSTAs over the NTA are influenced by the low-frequency part of the ENSO signal with a timescale of 36–48 months. The ENSO influence is seasonally dependent. The strongest linkages occur in the spring of each hemisphere. In addition to ENSO, SSTAs in the north equatorial Atlantic are also modulated by the circulation and net heat flux anomalies associated with the North Atlantic oscillation (NAO).
The atmospheric impact on the ocean is different in the STA and NTA regions. When the quasi-biennial signal is strong in the central Pacific during September–November, warm SSTAs excite the Pacific South American wave train extending from the Pacific to the South Atlantic. The associated wind-driven dynamics initiates the changes in the STA. The local net heat flux anomalies and ocean wave dynamics influence the location and the strength of the SSTA maximum. The SSTAs over the NTA region are driven by the local heat flux anomalies related to the trade wind changes associated with the low-frequency component of ENSO in the Pacific. The magnitudes of SSTAs depend on the phase of the NAO. The net heat flux anomalies associated with the NAO may enhance or diminish the impact of ENSO over the NTA region and modulate SSTAs in the North Atlantic.
Abstract
The authors have documented the relationship between tropical convection and precipitation regimes in the western United States. Circulation patterns associated with precipitation regimes are described and physical mechanisms are proposed. Contributions from intraseasonal and interannual bands are examined.
When enhanced convection is located in the western Pacific, dry conditions in the Southwest (SW) and wet conditions in the Pacific Northwest (PNW) are observed. Fluctuations in both intraseasonal and interannual bands contribute to the rainfall variability. Enhanced convection in the western Pacific is accompanied by suppressed convection in the central Pacific. The associated Rossby wave vorticity source (S) anomalies keep the Pacific jet west of 150°W. A westward shift of the storm track to the North Pacific also contributes to dry conditions in the SW and wetness in the PNW. When enhanced tropical convection is located near 150°E, substantial contributions to outgoing longwave radiation anomalies are from fluctuations in the intraseasonal band. A wave train extends from the convective area in the Tropics to North America, where negative 200-hPa streamfunction anomalies are consistent with wetness in California and dry conditions in the PNW.
When tropical convection is enhanced in the central Pacific from the date line to 135°W, most contributions are from the interannual band. The positive S anomalies associated with an enhanced local Hadley cell extending from the North Pacific to California are responsible in part for the eastward shift of the subtropical jet. The storm track moves southeast and is consistent with wet conditions in the SW.
Abstract
The authors have documented the relationship between tropical convection and precipitation regimes in the western United States. Circulation patterns associated with precipitation regimes are described and physical mechanisms are proposed. Contributions from intraseasonal and interannual bands are examined.
When enhanced convection is located in the western Pacific, dry conditions in the Southwest (SW) and wet conditions in the Pacific Northwest (PNW) are observed. Fluctuations in both intraseasonal and interannual bands contribute to the rainfall variability. Enhanced convection in the western Pacific is accompanied by suppressed convection in the central Pacific. The associated Rossby wave vorticity source (S) anomalies keep the Pacific jet west of 150°W. A westward shift of the storm track to the North Pacific also contributes to dry conditions in the SW and wetness in the PNW. When enhanced tropical convection is located near 150°E, substantial contributions to outgoing longwave radiation anomalies are from fluctuations in the intraseasonal band. A wave train extends from the convective area in the Tropics to North America, where negative 200-hPa streamfunction anomalies are consistent with wetness in California and dry conditions in the PNW.
When tropical convection is enhanced in the central Pacific from the date line to 135°W, most contributions are from the interannual band. The positive S anomalies associated with an enhanced local Hadley cell extending from the North Pacific to California are responsible in part for the eastward shift of the subtropical jet. The storm track moves southeast and is consistent with wet conditions in the SW.
Abstract
We examine reforecasts of flash droughts over the United States for the late spring (April–May), midsummer (June–July), and late summer/early autumn (August–September) with lead times up to 3 pentads based on the NOAA second-generation Global Ensemble Forecast System reforecasts version 2 (GEFSv2). We consider forecasts of both heat wave and precipitation deficit (P deficit) flash droughts, where heat wave flash droughts are characterized by high temperature and depletion of soil moisture and P deficit flash droughts are caused by lack of precipitation that leads to (rather than being the cause of) high temperature. We find that the GEFSv2 reforecasts generally capture the frequency of occurrence (FOC) patterns. The equitable threat score (ETS) of heat wave flash drought forecasts for late spring in the regions where heat wave flash droughts are most likely to occur over the north-central and Pacific Northwest regions is statistically significant up to 2 pentads. The GEFSv2 reforecasts capture the basic pattern of the FOC of P-deficit flash droughts and also are skillful up to lead about 2 pentads. However, the reforecasts overestimate the P-deficit flash drought FOC over parts of the Southwest in late spring, leading to large false alarm rates. For autumn, the reforecasts underestimate P-deficit flash drought occurrence over California and Nevada. The GEFSv2 reforecasts are able to capture the approximately linear relationship between evaporation and soil moisture, but the lack of skill in precipitation forecasts limits the skill of P-deficit flash drought forecasts.
Abstract
We examine reforecasts of flash droughts over the United States for the late spring (April–May), midsummer (June–July), and late summer/early autumn (August–September) with lead times up to 3 pentads based on the NOAA second-generation Global Ensemble Forecast System reforecasts version 2 (GEFSv2). We consider forecasts of both heat wave and precipitation deficit (P deficit) flash droughts, where heat wave flash droughts are characterized by high temperature and depletion of soil moisture and P deficit flash droughts are caused by lack of precipitation that leads to (rather than being the cause of) high temperature. We find that the GEFSv2 reforecasts generally capture the frequency of occurrence (FOC) patterns. The equitable threat score (ETS) of heat wave flash drought forecasts for late spring in the regions where heat wave flash droughts are most likely to occur over the north-central and Pacific Northwest regions is statistically significant up to 2 pentads. The GEFSv2 reforecasts capture the basic pattern of the FOC of P-deficit flash droughts and also are skillful up to lead about 2 pentads. However, the reforecasts overestimate the P-deficit flash drought FOC over parts of the Southwest in late spring, leading to large false alarm rates. For autumn, the reforecasts underestimate P-deficit flash drought occurrence over California and Nevada. The GEFSv2 reforecasts are able to capture the approximately linear relationship between evaporation and soil moisture, but the lack of skill in precipitation forecasts limits the skill of P-deficit flash drought forecasts.
Abstract
We examined drought variability and trends over the last century (1916–2013) over the conterminous United States (CONUS) using observed precipitation P, temperature T, and reconstructed total moisture percentiles (TMP) and runoff from four land surface models. We used an integrated drought index (IDI), which we defined as the equally weighted mean of the 3-month standardized runoff index (SRI3) and TMP from four land surface models mapped onto a uniform probability distribution. Using a definition of drought as IDI less than 0.3 for 6 months or longer, we identified 16 drought events, which we termed great droughts that covered more than 50% of the CONUS during our study period. We examined the properties of great droughts and compared these with the 2012 event. The great droughts were located at least partially over the central United States (30°–42°N, 85°–110°W). We found that 12 of these great droughts occurred when cold sea surface temperature anomalies (SSTAs) were located in the tropical Pacific with warm SSTAs in the North Atlantic. We also found a predominance of decreasing trends in IDI; droughts occurred less often and events were less severe as time progressed. In particular, only 2 of the 16 great droughts (2012 and 1988) occurred in the second half of the record.
Abstract
We examined drought variability and trends over the last century (1916–2013) over the conterminous United States (CONUS) using observed precipitation P, temperature T, and reconstructed total moisture percentiles (TMP) and runoff from four land surface models. We used an integrated drought index (IDI), which we defined as the equally weighted mean of the 3-month standardized runoff index (SRI3) and TMP from four land surface models mapped onto a uniform probability distribution. Using a definition of drought as IDI less than 0.3 for 6 months or longer, we identified 16 drought events, which we termed great droughts that covered more than 50% of the CONUS during our study period. We examined the properties of great droughts and compared these with the 2012 event. The great droughts were located at least partially over the central United States (30°–42°N, 85°–110°W). We found that 12 of these great droughts occurred when cold sea surface temperature anomalies (SSTAs) were located in the tropical Pacific with warm SSTAs in the North Atlantic. We also found a predominance of decreasing trends in IDI; droughts occurred less often and events were less severe as time progressed. In particular, only 2 of the 16 great droughts (2012 and 1988) occurred in the second half of the record.
Abstract
Eighteen 30-day integrations with the NMC global atmospheric model (T40 resolution) were performed in order to test the impact of sea surface temperature anomalies (SSTAs) on 30-day forecasts for the Northern Hemisphere early summer. The years considered—1987, 1988, and 1989—correspond to a warm El Niño-Southern Oscillation (ENSO) event, a cold ENSO event, and a normal (non-ENSO year), respectively. For each year, 30-day forecasts were started on three successive days around 22 May, using climatological SSTs, and repeated using SSTAs fixed at their initial values.
The results indicate that SSTAs have a clear positive impact on the tropical forecasts and surface fluxes. The impacts on the extratropical forecasts, on the other hand, tend to be positive but small. Larger positive impacts in midlatitudes are obtained only in a case in which the atmospheric anomalous circulation is apparently driven by the ocean anomalies. A simple rule of thumb to distinguish whether quasi-stationary atmospheric anomalies are the cause or the result of SSTAs is discussed. It is also found that ensemble averaging results in a modest improvement in forecast skill. Moreover, in areas where the ensemble forecast anomalies are found to be significantly different from zero in a statistical sense, the anomalies tend to verify well, suggesting a method to estimate a priori regional skill. Overall, the Southern Hemisphere forecasts are more skillful than those in the Northern Hemisphere, perhaps because of a seasonal effect.
Abstract
Eighteen 30-day integrations with the NMC global atmospheric model (T40 resolution) were performed in order to test the impact of sea surface temperature anomalies (SSTAs) on 30-day forecasts for the Northern Hemisphere early summer. The years considered—1987, 1988, and 1989—correspond to a warm El Niño-Southern Oscillation (ENSO) event, a cold ENSO event, and a normal (non-ENSO year), respectively. For each year, 30-day forecasts were started on three successive days around 22 May, using climatological SSTs, and repeated using SSTAs fixed at their initial values.
The results indicate that SSTAs have a clear positive impact on the tropical forecasts and surface fluxes. The impacts on the extratropical forecasts, on the other hand, tend to be positive but small. Larger positive impacts in midlatitudes are obtained only in a case in which the atmospheric anomalous circulation is apparently driven by the ocean anomalies. A simple rule of thumb to distinguish whether quasi-stationary atmospheric anomalies are the cause or the result of SSTAs is discussed. It is also found that ensemble averaging results in a modest improvement in forecast skill. Moreover, in areas where the ensemble forecast anomalies are found to be significantly different from zero in a statistical sense, the anomalies tend to verify well, suggesting a method to estimate a priori regional skill. Overall, the Southern Hemisphere forecasts are more skillful than those in the Northern Hemisphere, perhaps because of a seasonal effect.
