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Abstract
The tangent linear and adjoint of an adiabatic version of the Weather Research and Forecasting (WRF) Model with its Advanced Research WRF (ARW) dynamic core have been developed. The source-to-source automatic differentiation tool [i.e., the Transformation of Algorithm (TAF) in FORTRAN] was used in the development. Tangent linear and adjoint checks of the developed adiabatic WRF adjoint modeling system (WAMS) were conducted, and all necessary correctness verification procedures were passed. As the first application, the adiabatic WAMS was used to study the adjoint sensitivity of a severe windstorm in Antarctica. Linearity tests indicated that an adjoint-based sensitivity study with the Antarctic Mesoscale Prediction System (AMPS) 90-km domain configuration for the windstorm is valid up to 24 h. The adjoint-based sensitivity calculation with adiabatic WAMS identified sensitive regions for the improvement of the 24-h forecast of the windstorm. It is indicated that the windstorm forecast largely relies on the model initial conditions in the area from the south part of the Trans-Antarctic Mountains to West Antarctica and between the Ross Ice Shelf and the South Pole. Based on the sensitivity analysis, the southerly or southeasterly wind at lower levels in the sensitivity region should be larger, the cyclone should be stronger, and the atmospheric stratification should be more stable over the north slope of the Trans-Antarctic Mountain to the Ross Ice Shelf, than the AMPS analyses. By constructing pseudo-observations in the sensitivity region using the gradient information of forecast windstorm intensity around McMurdo, the model initial conditions are revised with the WRF three-dimensional variational data assimilation, which leads to significant improvement in the prediction of the windstorm. An adjoint sensitivity study is an efficient way to identify sensitivity regions in order to collect more observations in the region for better forecasts in a specific aspect of interest.
Abstract
The tangent linear and adjoint of an adiabatic version of the Weather Research and Forecasting (WRF) Model with its Advanced Research WRF (ARW) dynamic core have been developed. The source-to-source automatic differentiation tool [i.e., the Transformation of Algorithm (TAF) in FORTRAN] was used in the development. Tangent linear and adjoint checks of the developed adiabatic WRF adjoint modeling system (WAMS) were conducted, and all necessary correctness verification procedures were passed. As the first application, the adiabatic WAMS was used to study the adjoint sensitivity of a severe windstorm in Antarctica. Linearity tests indicated that an adjoint-based sensitivity study with the Antarctic Mesoscale Prediction System (AMPS) 90-km domain configuration for the windstorm is valid up to 24 h. The adjoint-based sensitivity calculation with adiabatic WAMS identified sensitive regions for the improvement of the 24-h forecast of the windstorm. It is indicated that the windstorm forecast largely relies on the model initial conditions in the area from the south part of the Trans-Antarctic Mountains to West Antarctica and between the Ross Ice Shelf and the South Pole. Based on the sensitivity analysis, the southerly or southeasterly wind at lower levels in the sensitivity region should be larger, the cyclone should be stronger, and the atmospheric stratification should be more stable over the north slope of the Trans-Antarctic Mountain to the Ross Ice Shelf, than the AMPS analyses. By constructing pseudo-observations in the sensitivity region using the gradient information of forecast windstorm intensity around McMurdo, the model initial conditions are revised with the WRF three-dimensional variational data assimilation, which leads to significant improvement in the prediction of the windstorm. An adjoint sensitivity study is an efficient way to identify sensitivity regions in order to collect more observations in the region for better forecasts in a specific aspect of interest.
Abstract
The effect of eddy diffusion in an interactive two-dimensional model of the stratosphere is reexamined. The model consists of a primitive equation dynamics module, a simplified HO x ozone model and a full radiative transfer scheme. The diabatic/residual circulation in the model stratosphere is maintained by the following processes: 1) nonlocal forcing resulting from dissipation in the parameterized model troposphere and frictional drag at mesospheric levels, 2) mechanical damping within the stratosphere itself, and 3) potential vorticity flux due to large scale waves. The net effect of each process is discussed in terms of the efficiency of the induced circulation in transporting ozone from the equatorial lower stratosphere to high latitude regions. The same eddy diffusion coefficients are used to parameterize the flux of quasi-geostrophic potential vorticity and diffusion in the tracer transport equation. It is shown that the ozone distributions generated with the interactive two-dimensional model are very sensitive to the choice of values for the friction and the eddy diffusion coefficients. The strength of the circulation increases with the mechanical damping and Kyy . At the same time, larger diffusion in the tracer transport equation reduces the equator to pole transport (Holton 1986). Depending on the amount of friction assumed in the stratosphere, increasing eddy diffusion can lead to an increase as well as a decrease in the net transport. It is shown that reasonable latitudinal gradients of ozone can be obtained by using small values for the mechanical damping [≈1/(100 days)] and Kyy (order 104 m2 s−1) for the mid- and high-latitude stratosphere.
Abstract
The effect of eddy diffusion in an interactive two-dimensional model of the stratosphere is reexamined. The model consists of a primitive equation dynamics module, a simplified HO x ozone model and a full radiative transfer scheme. The diabatic/residual circulation in the model stratosphere is maintained by the following processes: 1) nonlocal forcing resulting from dissipation in the parameterized model troposphere and frictional drag at mesospheric levels, 2) mechanical damping within the stratosphere itself, and 3) potential vorticity flux due to large scale waves. The net effect of each process is discussed in terms of the efficiency of the induced circulation in transporting ozone from the equatorial lower stratosphere to high latitude regions. The same eddy diffusion coefficients are used to parameterize the flux of quasi-geostrophic potential vorticity and diffusion in the tracer transport equation. It is shown that the ozone distributions generated with the interactive two-dimensional model are very sensitive to the choice of values for the friction and the eddy diffusion coefficients. The strength of the circulation increases with the mechanical damping and Kyy . At the same time, larger diffusion in the tracer transport equation reduces the equator to pole transport (Holton 1986). Depending on the amount of friction assumed in the stratosphere, increasing eddy diffusion can lead to an increase as well as a decrease in the net transport. It is shown that reasonable latitudinal gradients of ozone can be obtained by using small values for the mechanical damping [≈1/(100 days)] and Kyy (order 104 m2 s−1) for the mid- and high-latitude stratosphere.
Abstract
The sea surface temperature (SST) contrast between the Northern Hemisphere (NH) and Southern Hemisphere (SH) influences the location of the intertropical convergence zone (ITCZ) and the intensity of the monsoon systems. This study examines the contributions of external forcing and unforced internal variability to the interhemispheric SST contrast in HadSST3 and ERSSTv5 observations, and 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 1881 to 2012. Using multimodel mean fingerprints, a significant influence of anthropogenic, but not natural, forcing is detected in the interhemispheric SST contrast, with the observed response larger than that of the model mean in ERSSTv5. The forced response consists of asymmetric NH–SH SST cooling from the mid-twentieth century to around 1980, followed by opposite NH–SH SST warming. The remaining best-estimate residual or unforced component is marked by NH–SH SST maxima in the 1930s and mid-1960s, and a rapid NH–SH SST decrease around 1970. Examination of decadal shifts in the observed interhemispheric SST contrast highlights the shift around 1970 as the most prominent from 1881 to 2012. Both NH and SH SST variability contributed to the shift, which appears not to be attributable to external forcings. Most models examined fail to capture such large-magnitude shifts in their control simulations, although some models with high interhemispheric SST variability are able to produce them. Large-magnitude shifts produced by the control simulations feature disparate spatial SST patterns, some of which are consistent with changes typically associated with the Atlantic meridional overturning circulation (AMOC).
Abstract
The sea surface temperature (SST) contrast between the Northern Hemisphere (NH) and Southern Hemisphere (SH) influences the location of the intertropical convergence zone (ITCZ) and the intensity of the monsoon systems. This study examines the contributions of external forcing and unforced internal variability to the interhemispheric SST contrast in HadSST3 and ERSSTv5 observations, and 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 1881 to 2012. Using multimodel mean fingerprints, a significant influence of anthropogenic, but not natural, forcing is detected in the interhemispheric SST contrast, with the observed response larger than that of the model mean in ERSSTv5. The forced response consists of asymmetric NH–SH SST cooling from the mid-twentieth century to around 1980, followed by opposite NH–SH SST warming. The remaining best-estimate residual or unforced component is marked by NH–SH SST maxima in the 1930s and mid-1960s, and a rapid NH–SH SST decrease around 1970. Examination of decadal shifts in the observed interhemispheric SST contrast highlights the shift around 1970 as the most prominent from 1881 to 2012. Both NH and SH SST variability contributed to the shift, which appears not to be attributable to external forcings. Most models examined fail to capture such large-magnitude shifts in their control simulations, although some models with high interhemispheric SST variability are able to produce them. Large-magnitude shifts produced by the control simulations feature disparate spatial SST patterns, some of which are consistent with changes typically associated with the Atlantic meridional overturning circulation (AMOC).
Abstract
Seasonal predictions of precipitation and surface air temperature from the Climate Forecast System, version 2 (CFSv2), are evaluated against gridded daily observations from 1982 to 2007 over 17 hydroclimatic regions in China. The seasonal predictive skill is quantified with skill scores including correlation coefficient, RMSE, and mean bias for spatially averaged seasonal precipitation and temperature forecasts for each region. The evaluation focuses on identifying regions and seasons where significant skill exists, thus potentially contributing to skill in hydrological prediction. The authors find that the predictive skill of CFSv2 precipitation and temperature forecasts has a stronger dependence on seasons and regions than on lead times. Both temperature and precipitation forecasts show higher skill from late summer [July–September (JAS)] to late autumn [October–December (OND)] and from winter [December–February (DJF)] to spring [March–May (MAM)]. The skill of CFSv2 precipitation forecasts is low during summer [June–August (JJA)] and winter (DJF) over all of China because of low potential predictability of the East Asian summer monsoon and the East Asian winter monsoon for China. As expected, temperature predictive skill is much higher than precipitation predictive skill in all regions. As observed precipitation shows significant correlation with the Oceanic Niño index over western, southwestern, and central China, the authors found that CFSv2 precipitation forecasts generally show similar correlation pattern, suggesting that CFSv2 precipitation forecasts can capture ENSO signals. This evaluation suggests that using CFSv2 forecasts for seasonal hydrological prediction over China is promising and challenging.
Abstract
Seasonal predictions of precipitation and surface air temperature from the Climate Forecast System, version 2 (CFSv2), are evaluated against gridded daily observations from 1982 to 2007 over 17 hydroclimatic regions in China. The seasonal predictive skill is quantified with skill scores including correlation coefficient, RMSE, and mean bias for spatially averaged seasonal precipitation and temperature forecasts for each region. The evaluation focuses on identifying regions and seasons where significant skill exists, thus potentially contributing to skill in hydrological prediction. The authors find that the predictive skill of CFSv2 precipitation and temperature forecasts has a stronger dependence on seasons and regions than on lead times. Both temperature and precipitation forecasts show higher skill from late summer [July–September (JAS)] to late autumn [October–December (OND)] and from winter [December–February (DJF)] to spring [March–May (MAM)]. The skill of CFSv2 precipitation forecasts is low during summer [June–August (JJA)] and winter (DJF) over all of China because of low potential predictability of the East Asian summer monsoon and the East Asian winter monsoon for China. As expected, temperature predictive skill is much higher than precipitation predictive skill in all regions. As observed precipitation shows significant correlation with the Oceanic Niño index over western, southwestern, and central China, the authors found that CFSv2 precipitation forecasts generally show similar correlation pattern, suggesting that CFSv2 precipitation forecasts can capture ENSO signals. This evaluation suggests that using CFSv2 forecasts for seasonal hydrological prediction over China is promising and challenging.
Abstract
The radar-retrieved refractivity fields provide detailed depictions of the near-surface moisture distribution at the meso-γ scale. This study represents a novel application of the refractivity fields by examining the spatiotemporal characteristics of moisture variability in a summertime coastal region in Taiwan over 4 weeks. The physiography in Taiwan lends itself to a variety of flow features and corresponding moisture behavior, which has not been well studied. High-resolution refractivity analyses demonstrate how a highly variable moisture field is related to the complex interaction between the synoptic-scale winds, diurnal local circulations, terrain, storms, and heterogeneous land use. On average, higher refractivity (water vapor) is observed along the coastline and refractivity decreases inland toward the foothills. Under weak synoptic forcing conditions, the daytime refractivity field develops differently under local surface wind directions determined by the synoptic-scale prevailing wind and the sea-breeze fronts. High moisture penetrates inland toward the foothills with southwesterly winds, but it stalls along the coastline with southerly and northwesterly winds. The moisture distribution may further affect the occurrence of the inland afternoon storms. During the nighttime, the dry downslope wind decreases the moisture from the foothills toward the coast and forms a refractivity gradient perpendicular to the meridionally oriented mountains. Furthermore, the refractivity fields illustrate higher-resolution moisture distribution over surface station point measurements by showing the lagged daytime sea-breeze front between the urban and rural areas and the detailed nighttime heterogeneous moisture distribution related to land-use and rivers.
Abstract
The radar-retrieved refractivity fields provide detailed depictions of the near-surface moisture distribution at the meso-γ scale. This study represents a novel application of the refractivity fields by examining the spatiotemporal characteristics of moisture variability in a summertime coastal region in Taiwan over 4 weeks. The physiography in Taiwan lends itself to a variety of flow features and corresponding moisture behavior, which has not been well studied. High-resolution refractivity analyses demonstrate how a highly variable moisture field is related to the complex interaction between the synoptic-scale winds, diurnal local circulations, terrain, storms, and heterogeneous land use. On average, higher refractivity (water vapor) is observed along the coastline and refractivity decreases inland toward the foothills. Under weak synoptic forcing conditions, the daytime refractivity field develops differently under local surface wind directions determined by the synoptic-scale prevailing wind and the sea-breeze fronts. High moisture penetrates inland toward the foothills with southwesterly winds, but it stalls along the coastline with southerly and northwesterly winds. The moisture distribution may further affect the occurrence of the inland afternoon storms. During the nighttime, the dry downslope wind decreases the moisture from the foothills toward the coast and forms a refractivity gradient perpendicular to the meridionally oriented mountains. Furthermore, the refractivity fields illustrate higher-resolution moisture distribution over surface station point measurements by showing the lagged daytime sea-breeze front between the urban and rural areas and the detailed nighttime heterogeneous moisture distribution related to land-use and rivers.
Abstract
Water masses are carriers of anthropogenic fingerprints in the ocean interior, with their property changes manifesting oceanic thermodynamic responses to climate change. Yet, delimiting ocean water masses remains challenging in either observational atlas or climate models. This study analyzes the distribution of Indian Ocean seawater in the density - spicity space and uses volumetric maxima and minima between σ = 27.1-27.4 kg m−3 to track the cores and boundaries of intermediate water masses, respectively. In addition to the well-known Antarctic Intermediate Water (AAIW) and Red Sea-Persian Gulf Intermediate Water (RS-PGIW), two other water masses are identified by the new approach. One is the Indian-AAIW (I-AAIW), as a mixture of the AAIW and the Indonesian throughflow water, existing in the South Equatorial Current and the Agulhas Current system. The other (EEIW) exits in the equatorial Indian Ocean and Bay of Bengal, sourced from the RS-PGIW and overlying fresh waters. These waters are corroborated by nutrient and dissolved oxygen data. Around half (26 out of 51) of the Coupled Model Intercomparison Project Phase-6 (CMIP6) models can reasonably simulate these intermediate water masses. Compared with the observed water masses, the intermediate water masses in models are of a smaller thickness, and the RS-PGIW is colder and fresher. The former arises from a warm bias in the thermocline, whereas the latter is likely linked to insufficient ventilation in the Red Sea and Persian Gulf in models owing to coarse grid resolution and a surface cold bias.
Abstract
Water masses are carriers of anthropogenic fingerprints in the ocean interior, with their property changes manifesting oceanic thermodynamic responses to climate change. Yet, delimiting ocean water masses remains challenging in either observational atlas or climate models. This study analyzes the distribution of Indian Ocean seawater in the density - spicity space and uses volumetric maxima and minima between σ = 27.1-27.4 kg m−3 to track the cores and boundaries of intermediate water masses, respectively. In addition to the well-known Antarctic Intermediate Water (AAIW) and Red Sea-Persian Gulf Intermediate Water (RS-PGIW), two other water masses are identified by the new approach. One is the Indian-AAIW (I-AAIW), as a mixture of the AAIW and the Indonesian throughflow water, existing in the South Equatorial Current and the Agulhas Current system. The other (EEIW) exits in the equatorial Indian Ocean and Bay of Bengal, sourced from the RS-PGIW and overlying fresh waters. These waters are corroborated by nutrient and dissolved oxygen data. Around half (26 out of 51) of the Coupled Model Intercomparison Project Phase-6 (CMIP6) models can reasonably simulate these intermediate water masses. Compared with the observed water masses, the intermediate water masses in models are of a smaller thickness, and the RS-PGIW is colder and fresher. The former arises from a warm bias in the thermocline, whereas the latter is likely linked to insufficient ventilation in the Red Sea and Persian Gulf in models owing to coarse grid resolution and a surface cold bias.
Abstract
Central Asia (CA; 35°–55°N, 55°–90°E) has been experiencing a significant warming trend during the past five decades, which has been accompanied by intensified local hydrological changes. Accurate identification of variations in hydroclimatic conditions and understanding the driving mechanisms are of great importance for water resource management. Here, we attempted to quantify dry/wet variations by using precipitation minus evapotranspiration (P − E) and attributed the variations based on the atmosphere and surface water balances. Our results indicated that the dry season became drier while the wet season became wetter in CA for 1982–2019. The land surface water budget revealed precipitation (96.84%) and vapor pressure deficit (2.26%) as the primary contributing factors for the wet season. For the dry season, precipitation (95.43%), net radiation (3.51%), and vapor pressure deficit (−2.64%) were dominant factors. From the perspective of the atmospheric water budget, net inflow moisture flux was enhanced by a rate of 72.85 kg m−1 s−1 in the wet season, which was mainly transported from midwestern Eurasia. The increase in precipitation induced by the external cycle was 11.93 mm (6 months)−1. In contrast, the drying trend during the dry season was measured by a decrease in the net inflow moisture flux (74.41 kg m−1 s−1) and reduced external moisture from midwestern Eurasia. An increase in precipitation during the dry season can be attributed to an enhancement in local evapotranspiration, accompanied by a 4.69% increase in the recycling ratio. The compounding enhancements between wet and dry seasons ultimately contribute to an increasing frequency of both droughts and floods.
Abstract
Central Asia (CA; 35°–55°N, 55°–90°E) has been experiencing a significant warming trend during the past five decades, which has been accompanied by intensified local hydrological changes. Accurate identification of variations in hydroclimatic conditions and understanding the driving mechanisms are of great importance for water resource management. Here, we attempted to quantify dry/wet variations by using precipitation minus evapotranspiration (P − E) and attributed the variations based on the atmosphere and surface water balances. Our results indicated that the dry season became drier while the wet season became wetter in CA for 1982–2019. The land surface water budget revealed precipitation (96.84%) and vapor pressure deficit (2.26%) as the primary contributing factors for the wet season. For the dry season, precipitation (95.43%), net radiation (3.51%), and vapor pressure deficit (−2.64%) were dominant factors. From the perspective of the atmospheric water budget, net inflow moisture flux was enhanced by a rate of 72.85 kg m−1 s−1 in the wet season, which was mainly transported from midwestern Eurasia. The increase in precipitation induced by the external cycle was 11.93 mm (6 months)−1. In contrast, the drying trend during the dry season was measured by a decrease in the net inflow moisture flux (74.41 kg m−1 s−1) and reduced external moisture from midwestern Eurasia. An increase in precipitation during the dry season can be attributed to an enhancement in local evapotranspiration, accompanied by a 4.69% increase in the recycling ratio. The compounding enhancements between wet and dry seasons ultimately contribute to an increasing frequency of both droughts and floods.
Abstract
Global warming and anthropogenic activities have imposed noticeable impacts on rainfall pattern changes at both spatial and temporal scales in recent decades. Systematic diagnosis of rainfall pattern changes is urgently needed at spatiotemporal scales for a deeper understanding of how climate change produces variations in rainfall patterns. The objective of this study was to identify rainfall pattern changes systematically under climate change at a subcontinental scale along a rainfall gradient ranging from 1800 to 200 mm yr−1 by analyzing centennial rainfall data covering 230 sites from 1910 to 2017 in the Northern Territory of Australia. Rainfall pattern changes were characterized by considering aspects of trends and periodicity of annual rainfall, abrupt changes, rainfall distribution, and extreme rainfall events. Our results illustrated that rainfall patterns in northern Australia have changed significantly compared with the early period of the twentieth century. Specifically, 1) a significant increasing trend in annual precipitation associated with greater variation in recent decades was observed over the entire study area, 2) temporal variations represented a mean rainfall periodicity of 27 years over wet to dry regions, 3) an abrupt change of annual rainfall amount occurred consistently in both humid and arid regions during the 1966–75 period, and 4) partitioned long-term time series of rainfall demonstrated a wetter rainfall distribution trend across coastal to inland areas that was associated with more frequent extreme rainfall events in recent decades. The findings of this study could facilitate further studies on the mechanisms of climate change that influence rainfall pattern changes.
Significance Statement
Characterizing long-term rainfall pattern changes under different rainfall conditions is important to understand the impacts of climate change. We conducted diagnosis of centennial rainfall pattern changes across wet to dry regions in northern Australia and found that rainfall patterns have noticeably changed in recent decades. The entire region has a consistent increasing trend of annual rainfall with higher variation. Meanwhile, the main shifting period of rainfall pattern was during 1966–75. Although annual rainfall seems to become wetter with an increasing trend, more frequent extreme rainfall events should also be noticed for assessing the impacts of climate changes. The findings support further study to understand long-term rainfall pattern changes under climate change.
Abstract
Global warming and anthropogenic activities have imposed noticeable impacts on rainfall pattern changes at both spatial and temporal scales in recent decades. Systematic diagnosis of rainfall pattern changes is urgently needed at spatiotemporal scales for a deeper understanding of how climate change produces variations in rainfall patterns. The objective of this study was to identify rainfall pattern changes systematically under climate change at a subcontinental scale along a rainfall gradient ranging from 1800 to 200 mm yr−1 by analyzing centennial rainfall data covering 230 sites from 1910 to 2017 in the Northern Territory of Australia. Rainfall pattern changes were characterized by considering aspects of trends and periodicity of annual rainfall, abrupt changes, rainfall distribution, and extreme rainfall events. Our results illustrated that rainfall patterns in northern Australia have changed significantly compared with the early period of the twentieth century. Specifically, 1) a significant increasing trend in annual precipitation associated with greater variation in recent decades was observed over the entire study area, 2) temporal variations represented a mean rainfall periodicity of 27 years over wet to dry regions, 3) an abrupt change of annual rainfall amount occurred consistently in both humid and arid regions during the 1966–75 period, and 4) partitioned long-term time series of rainfall demonstrated a wetter rainfall distribution trend across coastal to inland areas that was associated with more frequent extreme rainfall events in recent decades. The findings of this study could facilitate further studies on the mechanisms of climate change that influence rainfall pattern changes.
Significance Statement
Characterizing long-term rainfall pattern changes under different rainfall conditions is important to understand the impacts of climate change. We conducted diagnosis of centennial rainfall pattern changes across wet to dry regions in northern Australia and found that rainfall patterns have noticeably changed in recent decades. The entire region has a consistent increasing trend of annual rainfall with higher variation. Meanwhile, the main shifting period of rainfall pattern was during 1966–75. Although annual rainfall seems to become wetter with an increasing trend, more frequent extreme rainfall events should also be noticed for assessing the impacts of climate changes. The findings support further study to understand long-term rainfall pattern changes under climate change.
Abstract
Future changes in the frequency of extreme drought events are of vital importance for risk assessment and relevant policy making. But a reliable estimation of their probability is intrinsically challenging due to limited available observations or simulations. Here, we use two large ensemble simulations, 50 members from CanESM2 and 40 members from CESM1 under the future RCP8.5 scenario, to elaborate a reliable projection of the 100-yr drought events (once in a century) under different warming levels. It is however necessary to first remove systematic biases for the simulated temperature and precipitation through a bias-correction method based on quantile mapping. Droughts are diagnosed with the standardized precipitation evapotranspiration index (SPEI), which considers both precipitation and potential evapotranspiration (PET, involving temperature). The results show that the frequency of extreme droughts increases with the continued global warming. Some differences between the two ensembles are also observed, especially for high warming levels. The China-averaged probability of 100-yr droughts that occur once in a century in the current climate increase by a factor of 1.52 (1.44) and 1.90 (2.02) under 1.5°C and 2°C warming levels in CanESM2-LE (CESM1-LE), respectively. A simple statistical scheme shows that the increasing future risk of extreme droughts is mainly due to the increasing effect of PET on the occurrence of extreme drought events, while the effect of precipitation almost keeps constant with global warming.
Abstract
Future changes in the frequency of extreme drought events are of vital importance for risk assessment and relevant policy making. But a reliable estimation of their probability is intrinsically challenging due to limited available observations or simulations. Here, we use two large ensemble simulations, 50 members from CanESM2 and 40 members from CESM1 under the future RCP8.5 scenario, to elaborate a reliable projection of the 100-yr drought events (once in a century) under different warming levels. It is however necessary to first remove systematic biases for the simulated temperature and precipitation through a bias-correction method based on quantile mapping. Droughts are diagnosed with the standardized precipitation evapotranspiration index (SPEI), which considers both precipitation and potential evapotranspiration (PET, involving temperature). The results show that the frequency of extreme droughts increases with the continued global warming. Some differences between the two ensembles are also observed, especially for high warming levels. The China-averaged probability of 100-yr droughts that occur once in a century in the current climate increase by a factor of 1.52 (1.44) and 1.90 (2.02) under 1.5°C and 2°C warming levels in CanESM2-LE (CESM1-LE), respectively. A simple statistical scheme shows that the increasing future risk of extreme droughts is mainly due to the increasing effect of PET on the occurrence of extreme drought events, while the effect of precipitation almost keeps constant with global warming.
Abstract
Over the course of his career, Fuqing Zhang drew vital new insights into the dynamics of meteorologically significant mesoscale gravity waves (MGWs), including their generation by unbalanced jet streaks, their interaction with fronts and organized precipitation, and their importance in midlatitude weather and predictability. Zhang was the first to deeply examine “spontaneous balance adjustment”—the process by which MGWs are continuously emitted as baroclinic growth drives the upper-level flow out of balance. Through his pioneering numerical model investigation of the large-amplitude MGW event of 4 January 1994, he additionally demonstrated the critical role of MGW–moist convection interaction in wave amplification. Zhang’s curiosity-turned-passion in atmospheric science covered a vast range of topics and led to the birth of new branches of research in mesoscale meteorology and numerical weather prediction. Yet, it was his earliest studies into midlatitude MGWs and their significant impacts on hazardous weather that first inspired him. Such MGWs serve as the focus of this review, wherein we seek to pay tribute to his groundbreaking contributions, review our current understanding, and highlight critical open science issues. Chief among such issues is the nature of MGW amplification through feedback with moist convection, which continues to elude a complete understanding. The pressing nature of this subject is underscored by the continued failure of operational numerical forecast models to adequately predict most large-amplitude MGW events. Further research into such issues therefore presents a valuable opportunity to improve the understanding and forecasting of this high-impact weather phenomenon, and in turn, to preserve the spirit of Zhang’s dedication to this subject.
Abstract
Over the course of his career, Fuqing Zhang drew vital new insights into the dynamics of meteorologically significant mesoscale gravity waves (MGWs), including their generation by unbalanced jet streaks, their interaction with fronts and organized precipitation, and their importance in midlatitude weather and predictability. Zhang was the first to deeply examine “spontaneous balance adjustment”—the process by which MGWs are continuously emitted as baroclinic growth drives the upper-level flow out of balance. Through his pioneering numerical model investigation of the large-amplitude MGW event of 4 January 1994, he additionally demonstrated the critical role of MGW–moist convection interaction in wave amplification. Zhang’s curiosity-turned-passion in atmospheric science covered a vast range of topics and led to the birth of new branches of research in mesoscale meteorology and numerical weather prediction. Yet, it was his earliest studies into midlatitude MGWs and their significant impacts on hazardous weather that first inspired him. Such MGWs serve as the focus of this review, wherein we seek to pay tribute to his groundbreaking contributions, review our current understanding, and highlight critical open science issues. Chief among such issues is the nature of MGW amplification through feedback with moist convection, which continues to elude a complete understanding. The pressing nature of this subject is underscored by the continued failure of operational numerical forecast models to adequately predict most large-amplitude MGW events. Further research into such issues therefore presents a valuable opportunity to improve the understanding and forecasting of this high-impact weather phenomenon, and in turn, to preserve the spirit of Zhang’s dedication to this subject.
