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Abstract
The present study investigates different impacts of the East Asian winter monsoon (EAWM) on surface air temperature (Ts) in North America (NA) during ENSO and neutral ENSO episodes. In neutral ENSO years, the EAWM shows a direct impact on the Ts anomalies in NA on an interannual time scale. Two Rossby wave packets appear over the Eurasian–western Pacific (upstream) and North Pacific–NA (downstream) regions associated with a strong EAWM. Further analysis suggests that the downstream wave packet is caused by reflection of the upstream wave packet over the subtropical western Pacific and amplified over the North Pacific. Also, the East Asian subtropical westerly jet stream (EAJS) is intensified in the central and downstream region over the central North Pacific. Hence, increased barotropic kinetic energy conversion and the interaction between transient eddies and the EAJS tend to maintain the circulation anomaly over the North Pacific. Therefore, a strong EAWM tends to result in warm Ts anomalies in northwestern NA via the downstream wave packet emanating from the central North Pacific toward NA. A weak EAWM tends to induce cold Ts anomalies in western-central NA with a smaller magnitude. However, in ENSO years, an anomalous EAJS is mainly confined over East Asia and does not extend into the central North Pacific. The results confirm that the EAWM has an indirect impact on the Ts anomalies in NA via a modulation of the tropical convection anomalies associated with ENSO. Our results indicate that, for seasonal prediction of Ts anomalies in NA, the influence of the EAWM should be taken into account. It produces different responses in neutral ENSO and in ENSO years.
Abstract
The present study investigates different impacts of the East Asian winter monsoon (EAWM) on surface air temperature (Ts) in North America (NA) during ENSO and neutral ENSO episodes. In neutral ENSO years, the EAWM shows a direct impact on the Ts anomalies in NA on an interannual time scale. Two Rossby wave packets appear over the Eurasian–western Pacific (upstream) and North Pacific–NA (downstream) regions associated with a strong EAWM. Further analysis suggests that the downstream wave packet is caused by reflection of the upstream wave packet over the subtropical western Pacific and amplified over the North Pacific. Also, the East Asian subtropical westerly jet stream (EAJS) is intensified in the central and downstream region over the central North Pacific. Hence, increased barotropic kinetic energy conversion and the interaction between transient eddies and the EAJS tend to maintain the circulation anomaly over the North Pacific. Therefore, a strong EAWM tends to result in warm Ts anomalies in northwestern NA via the downstream wave packet emanating from the central North Pacific toward NA. A weak EAWM tends to induce cold Ts anomalies in western-central NA with a smaller magnitude. However, in ENSO years, an anomalous EAJS is mainly confined over East Asia and does not extend into the central North Pacific. The results confirm that the EAWM has an indirect impact on the Ts anomalies in NA via a modulation of the tropical convection anomalies associated with ENSO. Our results indicate that, for seasonal prediction of Ts anomalies in NA, the influence of the EAWM should be taken into account. It produces different responses in neutral ENSO and in ENSO years.
Abstract
Anthropogenic forcing is anticipated to increase the magnitude and frequency of precipitation-induced extremes such as the increase in drought risks. However, the model-projected future changes in global droughts remain largely uncertain, particularly in the context of the Paris Agreement targets. Here, by using the standardized precipitation index (SPI), we present a multiscale global assessment of the precipitation-driven meteorological drought characteristics at the 1.5° and 2°C warming levels based on 28 CMIP5 global climate models (GCMs) under three representative concentration pathways scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show large uncertainties in the timing reaching 1.5° and 2°C warming and the changes in drought characteristics among GCMs, especially at longer time scales and under higher RCP scenarios. The multi-GCM ensemble mean projects a general increase in drought frequency (Df) and area (Da) over North America, Europe, and northern Asia at both 1.5° and 2°C of global warming. The additional 0.5°C warming from 1.5° to 2°C is expected to result in a trend toward wetter climatic conditions for most global regions (e.g., North America, Europe, northern Asia, and northern Africa) due to the continuing increase in precipitation under the more intensified 2°C warming. In contrast, the increase in Df is projected only in some parts of southwest Asia, South America, southern Africa, and Australia. Our results highlight the need to consider multiple GCMs in drought projection studies under the context of the Paris Agreement targets to account for large model-dependent uncertainties.
Abstract
Anthropogenic forcing is anticipated to increase the magnitude and frequency of precipitation-induced extremes such as the increase in drought risks. However, the model-projected future changes in global droughts remain largely uncertain, particularly in the context of the Paris Agreement targets. Here, by using the standardized precipitation index (SPI), we present a multiscale global assessment of the precipitation-driven meteorological drought characteristics at the 1.5° and 2°C warming levels based on 28 CMIP5 global climate models (GCMs) under three representative concentration pathways scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show large uncertainties in the timing reaching 1.5° and 2°C warming and the changes in drought characteristics among GCMs, especially at longer time scales and under higher RCP scenarios. The multi-GCM ensemble mean projects a general increase in drought frequency (Df) and area (Da) over North America, Europe, and northern Asia at both 1.5° and 2°C of global warming. The additional 0.5°C warming from 1.5° to 2°C is expected to result in a trend toward wetter climatic conditions for most global regions (e.g., North America, Europe, northern Asia, and northern Africa) due to the continuing increase in precipitation under the more intensified 2°C warming. In contrast, the increase in Df is projected only in some parts of southwest Asia, South America, southern Africa, and Australia. Our results highlight the need to consider multiple GCMs in drought projection studies under the context of the Paris Agreement targets to account for large model-dependent uncertainties.
Abstract
In an effort to improve the tropical cyclone track forecast, two preprocessing procedures are applied to an operational baroclinic forecast system at the Central Weather Bureau (CWB) in Taipei. The first replaces the environmental wind field near the storm by the previous 6-h.movement vector of the storm. The second incorporates a wavenumber-1 asymmetry constructed by matching the flow at the center of the asymmetry with the previous 6-h storm movement. Applying both processes to the 32 typhoon casts archived at the CWB in 1990 reduces the averaged 48-h forecast distance error from 474 to 351 km.
Multiexisting typhoons may have interactions among themselves that depend on relative intensity. Proper representation of the intensities in the initial bogus is important for the track forecast. Experiments with different initial bogus intensities are conducted on a case of dual typhoons-Nat and Mireille in 1991. The forecast using different bogus vortices according to the estimated intensities of each typhoon gives substantially smaller errors than that using identical bogus vortices. The impact of initial bogus vortex intensity on the track forecast for single typhoon cases is also illustrated.
Abstract
In an effort to improve the tropical cyclone track forecast, two preprocessing procedures are applied to an operational baroclinic forecast system at the Central Weather Bureau (CWB) in Taipei. The first replaces the environmental wind field near the storm by the previous 6-h.movement vector of the storm. The second incorporates a wavenumber-1 asymmetry constructed by matching the flow at the center of the asymmetry with the previous 6-h storm movement. Applying both processes to the 32 typhoon casts archived at the CWB in 1990 reduces the averaged 48-h forecast distance error from 474 to 351 km.
Multiexisting typhoons may have interactions among themselves that depend on relative intensity. Proper representation of the intensities in the initial bogus is important for the track forecast. Experiments with different initial bogus intensities are conducted on a case of dual typhoons-Nat and Mireille in 1991. The forecast using different bogus vortices according to the estimated intensities of each typhoon gives substantially smaller errors than that using identical bogus vortices. The impact of initial bogus vortex intensity on the track forecast for single typhoon cases is also illustrated.
Abstract
The evolution of the daytime planetary boundary layer (PBL) and its association with warm-season precipitation is strongly impacted by land–atmosphere heat and moisture exchange (hereafter surface exchange). However, substantial uncertainty exists in the parameterization of the surface exchange in numerical weather prediction (NWP) models. In the current study, the authors examine 0–24-h convection-permitting forecasts with different surface exchange strengths for a 6-day period during the International H2O Project (IHOP_2002). Results indicate sensitivity in the timing of simulated afternoon convection initiation and subsequent precipitation amounts to variations in surface exchange strength. Convection initiation in simulations with weak surface exchange was delayed by 2–3 h compared to simulations with strong surface exchange, and area-averaged total precipitation amounts were less by up to a factor of 2. Over the western high plains (105°–100°W longitude), where deep convection is locally generated, simulations using a formulation for surface exchange that varied with the vegetation category (height) produced area-averaged diurnal cycles of forecasted precipitation amounts in better agreement with observations than simulations that used the current Advanced Research Weather Research and Forecasting Model (ARW-WRF) formulation. Parcel theory is used to diagnose mechanisms by which differences in surface exchange influence convection initiation in individual case studies. The more rapid initiation in simulations with strong surface exchange results from a more rapid removal of negative buoyancy beneath the level of free convection, which arises primarily from greater PBL warming.
Abstract
The evolution of the daytime planetary boundary layer (PBL) and its association with warm-season precipitation is strongly impacted by land–atmosphere heat and moisture exchange (hereafter surface exchange). However, substantial uncertainty exists in the parameterization of the surface exchange in numerical weather prediction (NWP) models. In the current study, the authors examine 0–24-h convection-permitting forecasts with different surface exchange strengths for a 6-day period during the International H2O Project (IHOP_2002). Results indicate sensitivity in the timing of simulated afternoon convection initiation and subsequent precipitation amounts to variations in surface exchange strength. Convection initiation in simulations with weak surface exchange was delayed by 2–3 h compared to simulations with strong surface exchange, and area-averaged total precipitation amounts were less by up to a factor of 2. Over the western high plains (105°–100°W longitude), where deep convection is locally generated, simulations using a formulation for surface exchange that varied with the vegetation category (height) produced area-averaged diurnal cycles of forecasted precipitation amounts in better agreement with observations than simulations that used the current Advanced Research Weather Research and Forecasting Model (ARW-WRF) formulation. Parcel theory is used to diagnose mechanisms by which differences in surface exchange influence convection initiation in individual case studies. The more rapid initiation in simulations with strong surface exchange results from a more rapid removal of negative buoyancy beneath the level of free convection, which arises primarily from greater PBL warming.
Abstract
This study evaluates, for the first time, the impact of airborne global positioning system radio occultation (ARO) observations on a hurricane forecast. A case study was conducted of Hurricane Karl during the Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field campaign in 2010. The assimilation of ARO data was developed for the three-dimensional variational (3DVAR) analysis system of the Weather Research and Forecasting (WRF) Model version 3.2. The impact of ARO data on Karl forecasts was evaluated through data assimilation (DA) experiments of local refractivity and nonlocal excess phase (EPH), in which the latter accounts for the integrated horizontal sampling along the signal ray path. The tangent point positions (closest point of an RO ray path to Earth’s surface) drift horizontally, and the drifting distance of ARO data is about 2 to 3 times that of spaceborne RO, which was taken into account in these simulations.
Results indicate that in the absence of other satellite observations, the assimilation of ARO EPH resulted in a larger impact on the analysis than local refractivity did. In particular, the assimilation of ARO observations at the actual tangent point locations resulted in more accurate forecasts of the rapid intensification of the storm. Among all experiments, the best forecast was obtained by assimilating ARO data with the most accurate geometric representation, that is, the use of nonlocal EPH operators with tangent point drift, which reduced the error in the storm’s predicted minimum sea level pressure (SLP) by 43% beyond that of the control experiment.
Abstract
This study evaluates, for the first time, the impact of airborne global positioning system radio occultation (ARO) observations on a hurricane forecast. A case study was conducted of Hurricane Karl during the Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field campaign in 2010. The assimilation of ARO data was developed for the three-dimensional variational (3DVAR) analysis system of the Weather Research and Forecasting (WRF) Model version 3.2. The impact of ARO data on Karl forecasts was evaluated through data assimilation (DA) experiments of local refractivity and nonlocal excess phase (EPH), in which the latter accounts for the integrated horizontal sampling along the signal ray path. The tangent point positions (closest point of an RO ray path to Earth’s surface) drift horizontally, and the drifting distance of ARO data is about 2 to 3 times that of spaceborne RO, which was taken into account in these simulations.
Results indicate that in the absence of other satellite observations, the assimilation of ARO EPH resulted in a larger impact on the analysis than local refractivity did. In particular, the assimilation of ARO observations at the actual tangent point locations resulted in more accurate forecasts of the rapid intensification of the storm. Among all experiments, the best forecast was obtained by assimilating ARO data with the most accurate geometric representation, that is, the use of nonlocal EPH operators with tangent point drift, which reduced the error in the storm’s predicted minimum sea level pressure (SLP) by 43% beyond that of the control experiment.
Abstract
This study highlights the distinct modulation of May–October tropical cyclones (TCs) in the western North Pacific (WNP), eastern North Pacific (ENP), and North Atlantic (NATL) Ocean basins by tropical transbasin variability (TBV) and ENSO. The pure TBV significantly modulates total TC counts in all three basins, with more TCs in the WNP and ENP and fewer TCs in the NATL during warm TBV years and fewer TCs in the WNP and ENP and more TCs in the NATL during cold TBV years. By contrast, the pure ENSO signal shows no impact on total TC count over any of the three basins. These results are consistent with changes in large-scale factors associated with TBV and ENSO. Low-level relative vorticity (VOR) is an important driver of WNP TC genesis frequency, with broad agreement between the observed spatial distribution of TC genesis and TBV/ENSO-associated VOR anomalies. TBV significantly affects ENP TC frequency as a result of changes in basinwide vertical wind shear and sea surface temperatures, whereas the modulation in TC frequency by ENSO is primarily caused by a north–south dipole modulation of large-scale atmospheric and oceanic factors. The pure TBV-related low-level VOR changes appear to be the most important factor modulating NATL TC frequency. Changes in large-scale factors compare well with the budget of synoptic-scale eddy kinetic energy. Possible physical processes associated with pure TBV and pure ENSO that modulate TC frequency are further discussed. This study contributes to the understanding of TC interannual variability and could thus be helpful for seasonal TC forecasting.
Abstract
This study highlights the distinct modulation of May–October tropical cyclones (TCs) in the western North Pacific (WNP), eastern North Pacific (ENP), and North Atlantic (NATL) Ocean basins by tropical transbasin variability (TBV) and ENSO. The pure TBV significantly modulates total TC counts in all three basins, with more TCs in the WNP and ENP and fewer TCs in the NATL during warm TBV years and fewer TCs in the WNP and ENP and more TCs in the NATL during cold TBV years. By contrast, the pure ENSO signal shows no impact on total TC count over any of the three basins. These results are consistent with changes in large-scale factors associated with TBV and ENSO. Low-level relative vorticity (VOR) is an important driver of WNP TC genesis frequency, with broad agreement between the observed spatial distribution of TC genesis and TBV/ENSO-associated VOR anomalies. TBV significantly affects ENP TC frequency as a result of changes in basinwide vertical wind shear and sea surface temperatures, whereas the modulation in TC frequency by ENSO is primarily caused by a north–south dipole modulation of large-scale atmospheric and oceanic factors. The pure TBV-related low-level VOR changes appear to be the most important factor modulating NATL TC frequency. Changes in large-scale factors compare well with the budget of synoptic-scale eddy kinetic energy. Possible physical processes associated with pure TBV and pure ENSO that modulate TC frequency are further discussed. This study contributes to the understanding of TC interannual variability and could thus be helpful for seasonal TC forecasting.
Abstract
Variability present at a satellite instrument sampling scale (small-scale variability) has been neglected in earlier simulations of atmospheric and cloud property change retrievals using spatially and temporally averaged spectral radiances. The effects of small-scale variability in the atmospheric change detection process are evaluated in this study. To simulate realistic atmospheric variability, top-of-the-atmosphere nadir-view longwave spectral radiances are computed at a high temporal (instantaneous) resolution with a 20-km field-of-view using cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, along with temperature humidity profiles obtained from reanalysis. Specifically, the effects of the variability on the necessary conditions for retrieving atmospheric changes by a linear regression are tested. The percentage error in the annual 10° zonal mean spectral radiance difference obtained by assuming linear combinations of individual perturbations expressed as a root-mean-square (RMS) difference computed over wavenumbers between 200 and 2000 cm−1 is 10%–15% for most of the 10° zones. However, if cloud fraction perturbation is excluded, the RMS difference decreases to less than 2%. Monthly and annual 10° zonal mean spectral radiances change linearly with atmospheric property perturbations, which occur when atmospheric properties are perturbed by an amount approximately equal to the variability of the10° zonal monthly deseasonalized anomalies or by a climate-model-predicted decadal change. Nonlinear changes in the spectral radiances of magnitudes similar to those obtained through linear estimation can arise when cloud heights and droplet radii in water cloud change. The spectral shapes computed by perturbing different atmospheric and cloud properties are different so that linear regression can separate individual spectral radiance changes from the sum of the spectral radiance change. When the effects of small-scale variability are treated as noise, however, the error in retrieved cloud properties is large. The results suggest the importance of considering small-scale variability in inferring atmospheric and cloud property changes from the satellite-observed zonally and annually averaged spectral radiance difference.
Abstract
Variability present at a satellite instrument sampling scale (small-scale variability) has been neglected in earlier simulations of atmospheric and cloud property change retrievals using spatially and temporally averaged spectral radiances. The effects of small-scale variability in the atmospheric change detection process are evaluated in this study. To simulate realistic atmospheric variability, top-of-the-atmosphere nadir-view longwave spectral radiances are computed at a high temporal (instantaneous) resolution with a 20-km field-of-view using cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, along with temperature humidity profiles obtained from reanalysis. Specifically, the effects of the variability on the necessary conditions for retrieving atmospheric changes by a linear regression are tested. The percentage error in the annual 10° zonal mean spectral radiance difference obtained by assuming linear combinations of individual perturbations expressed as a root-mean-square (RMS) difference computed over wavenumbers between 200 and 2000 cm−1 is 10%–15% for most of the 10° zones. However, if cloud fraction perturbation is excluded, the RMS difference decreases to less than 2%. Monthly and annual 10° zonal mean spectral radiances change linearly with atmospheric property perturbations, which occur when atmospheric properties are perturbed by an amount approximately equal to the variability of the10° zonal monthly deseasonalized anomalies or by a climate-model-predicted decadal change. Nonlinear changes in the spectral radiances of magnitudes similar to those obtained through linear estimation can arise when cloud heights and droplet radii in water cloud change. The spectral shapes computed by perturbing different atmospheric and cloud properties are different so that linear regression can separate individual spectral radiance changes from the sum of the spectral radiance change. When the effects of small-scale variability are treated as noise, however, the error in retrieved cloud properties is large. The results suggest the importance of considering small-scale variability in inferring atmospheric and cloud property changes from the satellite-observed zonally and annually averaged spectral radiance difference.
Abstract
Sensible heat flux (H), latent heat flux (LE), and net radiation (NR) are important surface energy components that directly influence climate systems. In this study, the changes in the surface energy and their contributions from global climate change and/or land-cover change over eastern China during the past nearly 30 years were investigated and assessed using a process-based land surface model [the Ecosystem–Atmosphere Simulation Scheme (EASS)]. The modeled results show that climate change contributed more to the changes of land surface energy fluxes than land-cover change, with their contribution ratio reaching 4:1 or even higher. Annual average temperature increased before 2000 and reversed thereafter; annual total precipitation continually decreased, and incident solar radiation continually increased over the past nearly 30 years. These climatic changes could lead to increased NR, H, and LE, assuming land cover remained unchanged during the past nearly 30 years. Among these meteorological variables, at spatial distribution, the incident solar radiation has the greatest effect on land surface energy exchange. The impacts of land-cover change on the seasonal variations in land surface heat fluxes between the four periods were large, especially for H. The changes in the regional energy fluxes resulting from different land-cover type conversions varied greatly. The conversion from farmland to evergreen coniferous forests had the greatest influence on land surface energy exchange, leading to a decrease in H by 19.39% and an increase in LE and NR by 7.44% and 2.74%, respectively. The results of this study can provide a basis and reference for climate change adaptation.
Abstract
Sensible heat flux (H), latent heat flux (LE), and net radiation (NR) are important surface energy components that directly influence climate systems. In this study, the changes in the surface energy and their contributions from global climate change and/or land-cover change over eastern China during the past nearly 30 years were investigated and assessed using a process-based land surface model [the Ecosystem–Atmosphere Simulation Scheme (EASS)]. The modeled results show that climate change contributed more to the changes of land surface energy fluxes than land-cover change, with their contribution ratio reaching 4:1 or even higher. Annual average temperature increased before 2000 and reversed thereafter; annual total precipitation continually decreased, and incident solar radiation continually increased over the past nearly 30 years. These climatic changes could lead to increased NR, H, and LE, assuming land cover remained unchanged during the past nearly 30 years. Among these meteorological variables, at spatial distribution, the incident solar radiation has the greatest effect on land surface energy exchange. The impacts of land-cover change on the seasonal variations in land surface heat fluxes between the four periods were large, especially for H. The changes in the regional energy fluxes resulting from different land-cover type conversions varied greatly. The conversion from farmland to evergreen coniferous forests had the greatest influence on land surface energy exchange, leading to a decrease in H by 19.39% and an increase in LE and NR by 7.44% and 2.74%, respectively. The results of this study can provide a basis and reference for climate change adaptation.
