Coastal Precipitation Research Articles

Control of Low-Level Wind on the Diurnal Cycle of Tropical Coastal Precipitation

Abstract To understand how coastal precipitation is controlled by the low-level background wind, we performed comprehensive analysis using the 17-yr observations of the TRMM PR over the entire region of the tropics. We classified the data according to the direction (onshore or offshore) and strength of the cross-shore wind. Under weak winds, the contribution of the diurnal cycle to total precipitation is large, indicating that thermally forced precipitation with a symmetrical propagation pattern with opposite sign across the coastline is dominant. As the background wind strengthens, the contribution of the diurnal cycle reduces owing to the predominance of mechanical forcing; however, the effect of the diurnal cycle remains nonnegligible with an asymmetrical propagation pattern across the coastline. Using the linear theory of the sea–land-breeze circulation, we demonstrated that the difference in propagation is attributable to gravity waves excited by the land–ocean surface heating difference. Under weak winds, symmetrical diurnal phase propagation is caused by the two symmetrical modes of landward and seaward gravity waves. Under stronger background winds, in addition to the Doppler-shifted landward and seaward modes, waves propagating toward the upwind side in the flow-relative frame but with slow group velocity are advected to the downwind near the coastline, forming another mode that moves slowly in the downwind direction. The superposition of the three modes leads to asymmetrical propagation of precipitation with varying phase speed depending on the distance from the coastline.

Impact of the Guinea coast upwelling on atmospheric dynamics, precipitation and pollutant transport over southern West Africa

Abstract. In West Africa, the zonal band of precipitation is generally located around the southern coast in June before migrating northward towards the Sahel in late June/early July. This gives way to a relative dry season for coastal regions from Côte d'Ivoire to Benin called “little dry season”, which lasts until September–October. Previous studies have noted that the coastal rainfall cessation in early July seems to coincide with the emergence of an upwelling along the Guinea coast. The aim of this study is to investigate the mechanisms by which this upwelling impacts precipitation, using a set of numerical simulations performed with the Weather Research and Forecasting regional atmospheric model (WRF v 3.7.1). Sensitivity experiments highlight the response of the atmospheric circulation to an intensification or reduction of the strength of the coastal upwelling. They clearly show that the coastal upwelling emergence is responsible for the cessation of coastal precipitation by weakening the northward humidity transport, thus decreasing the coastal convergence of the humidity transport and inhibiting the deep atmospheric convection. In addition, the diurnal cycle of the low-level circulation plays a critical role: the land breeze controls the seaward convergence of diurnal anomaly of humidity transport, explaining the late night–early morning peak observed in coastal precipitation. The emergence of the coastal upwelling strongly attenuates this peak because of a reduced land–sea temperature gradient in the night and a weaker land breeze. The impact on the inland transport of anthropogenic pollution is also shown with numerical simulations of aerosols using the CHIMERE chemistry-transport model: warmer (colder) sea surface temperature (SST) increases (decreases) the inland transport of pollutants, especially during the night, suggesting an influence of the upwelling intensity on the coastal low-level jet. The mechanisms described have important consequences for inland humidity transport and the predictability of the West African monsoon precipitation in summer.

The relationship between the large-scale relative vorticity fields and precipitation over Iran

Abstract This study examines the relationship between relative vorticity, a key variable in mid-latitude synoptic motions, and precipitation in Iran. Using the S-mode PCA, activity centers of relative vorticity and precipitation were identified. Canonical correlation analysis (CCA) was applied to the factor scores of these centers to reveal coupled patterns of relative vorticity and precipitation. The analysis is based on 500- and 850-hPa relative vorticity fields at 2.5° grid points (10°–70° E and 10°–70° N) and uses monthly relative vorticity values from NCEP-DOE reanalysis databases (1981–2020) along with standardized rainfall data from 97 Iranian synoptic stations. Three main CCA patterns reveal connections: 500-hPa relative vorticity changes in the eastern Mediterranean, Middle East, and Iran relate to eastern Iran's precipitation. Relative vorticity over Eastern Europe inversely correlates with southern Caspian Sea coast precipitation. Changes over Turkey and Cyprus can affect northwestern Iran's rainfall. The changes in 850-hPa relative vorticity over the Arabian Sea inversely link to eastern Iran's precipitation, while those over the eastern Mediterranean directly connect to western Iran's precipitation. Relative vorticity changes in Eastern Europe negatively correlate with southwestern Caspian Sea coast precipitation.

IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model

This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting.

The Impact of Dropsonde Data on the Performance of the NCEP Global Forecast System during the 2020 Atmospheric Rivers Observing Campaign. Part II: Dynamic Variables and Humidity

Abstract The impact of assimilating dropsonde data from the 2020 Atmospheric River (AR) Reconnaissance (ARR) field campaign on operational numerical weather forecasts was assessed. Two experiments were executed for the period from 24 January to 18 March 2020 using the National Centers for Environmental Prediction (NCEP) Global Forecast System version 15 (GFSv15) with a four-dimensional hybrid ensemble–variational (4DEnVar) data assimilation system. The control run (CTRL) used all of the routinely assimilated data and included data from 628 ARR dropsondes, whereas the denial run (DENY) excluded the dropsonde data. Results from 17 intensive observing periods (IOPs) indicate a mixed impact for mean sea level pressure and geopotential height over the Pacific–North American (PNA) region in CTRL compared to DENY. The overall local impact over the U.S. West Coast and Gulf of Alaska for the 17 IOPs is neutral (−0.45%) for integrated vapor transport (IVT), but positive for wind and moisture profiles (0.5%–1.0%), with a spectrum of statistically significant positive and negative impacts for various IOPs. The positive dropsonde data impact on precipitation forecasts over U.S. West Coast domains appears driven, in part, by improved low-level moisture and wind fields at short-forecast lead times. Indeed, data gaps, especially for accurate and unbiased moisture profiles and wind fields, can be at least partially mitigated to improve U.S. West Coast precipitation forecasts.

Using Deep Learning for an Analysis of Atmospheric Rivers in a High‐Resolution Large Ensemble Climate Data Set

AbstractThere is currently large uncertainty over the impacts of climate change on precipitation trends over the US west coast. Atmospheric rivers (ARs) are a significant source of US west coast precipitation and trends in ARs can provide insight into future precipitation trends. There are already a variety of different methods used to identify ARs, but many are used in contexts that are often difficult to apply to large climate datasets due to their computational cost and requirement of integrated vapor transport as an input variable, which can be expensive to compute in climate models at high temporal frequencies. Using deep learning (DL) to track ARs is a unique approach that can alleviate some of the computational challenges that exist in more traditional methods. However, some questions still remain regarding its flexibility and robustness. This research investigates the consistency of a DL methodology of tracking ARs with more established algorithms to demonstrate its high‐level performance for future studies.

Impact of Extratropical Northeast Pacific SST on U.S. West Coast Precipitation

AbstractThe rainfall over the U.S. West Coast is known to be highly influenced by large‐scale atmospheric circulation and tropical climate teleconnections. However, the role of North Pacific oceanic variability is less understood. Using high‐resolution regional atmospheric model simulations forced by sustained positive and negative phases of the extratropical Pacific Decadal Oscillation sea surface temperature anomalies (SSTa), we diagnose the precipitation changes over the U.S. West Coast during 2010–2020. We find that precipitation anomalies are up to 60% stronger (weaker) for the warm (cold) cases, especially over Northern and Central California during wintertime, and Baja California in the summertime. In both seasons, precipitation is predominantly modulated through changes in the water vapor flux, which are directed toward the coast in wintertime and away from the coast during summertime. These flux anomalies are primarily driven by large‐scale changes in the wind associated with the atmospheric adjustment to the strong ocean SSTa.

Improving Precipitation Forecasts with Convolutional Neural Networks

Abstract A machine learning method based on spatial convolution to capture complex spatial precipitation patterns is proposed to identify and reduce biases affecting predictions of a dynamical model. The method is based on a combination of a classification and dual regression model approach using modified U-Net convolutional neural networks (CNN) to post-process daily accumulated precipitation over the US west coast. In this study, we leverage 34 years of high resolution deterministic Western Weather Research and Forecasting (West-WRF) precipitation reforecasts as training data for the U-Net CNN. The data is split such that the test set contains 4 water years of data that encompass characteristic west coast precipitation regimes: El Niño, La Niña, and dry and wet El Niño/Southern Oscillation (ENSO-neutral) water years. On the unseen 4-year data set, the trained CNN yields a 12.9-15.9% reduction in root mean square error (RMSE) and 2.7-3.4% improvement in Pearson correlation (PC) over West-WRF for lead times of 1-4 days. Compared to an adapted model output statistics correction, the CNN reduces RMSE by 7.4-8.9% and improves PC by 3.3-4.2% across all events. Effectively, the CNN adds more than a day of predictive skill when compared to West-WRF. The CNN outperforms the other methods also for the prediction of extreme events, which we define as the top 10% of events with the greatest average daily accumulated precipitation. The improvement over West-WRF’s RMSE/PC for these events is 19.8-21.0%/4.9-5.5% and MOS’s RMSE/PC is 8.8-9.7%/4.2-4.7%. Hence, the proposed U-Net CNN shows significantly improved forecast skill over existing methods, highlighting a promising path forward for improving precipitation forecasts.

Sensitivity of boundary layer parameterization schemes in a marine boundary layer jet and associated precipitation during a coastal warm-sector heavy rainfall event

The sensitivity of planetary boundary layer (PBL) parameterization schemes in a marine boundary layer jet and associated precipitation is investigated in this study. Six PBL parameterization schemes in the Weather Research and Forecasting Model, including YSU, MYJ, MYNN, ACM2, BouLac, and UW schemes, are examined in simulating a marine boundary layer jet (BLJ) over South China Sea and associated coastal precipitation during a warm-sector heavy rainfall event (19–20 May 2015) near the coast of South China. The results show that YSU, MYJ, MYNN, and BouLac schemes can generally reproduce the coastal warm-sector heavy rainfall with 6-h accumulated precipitation exceeding 50 mm, but not for the ACMs and UW schemes. No convection initiation occurs in the ACM2 run, while rainfall is located to further north with weaker intensity in the UW run. Meanwhile, weakest and strongest BLJs are simulated in the ACM2 and UW runs, respectively. In the ACM2 run, the weaker BLJ with the maximum wind speed less than 17 m s−1 induces weaker convergence and lifting in the upwind side of the coastal terrain as well as less water vapor transport to the coastal area, which thus inhibit convection initiation. On the contrary, the too strong BLJ in the UW run with large area of wind speed greater than 18 m s−1 causes the northward movement of convection along with cold pools, and rainfall moves further north accordingly. The differences in BLJs’ strength among PBL schemes are attributed to varying simulated low-level vortex on the northern side of the BLJ through veering ageostrophic winds. The intensity of the simulated low-level vortex is affected by variations in boundary layer mixing over land and associated vertical temperature stratification under different PBL schemes.

The Impact of Dropsonde Data on the Performance of the NCEP Global Forecast System during the 2020 Atmospheric Rivers Observing Campaign. Part I: Precipitation

Abstract The impact of assimilating dropsonde data from the 2020 Atmospheric River (AR) Reconnaissance (ARR) field campaign on operational numerical precipitation forecasts was assessed. Two experiments were executed for the period from 24 January to 18 March 2020 using the NCEP Global Forecast System, version 15 (GFSv15), with a four-dimensional hybrid ensemble–variational (4DEnVar) data assimilation system. The control run (CTRL) used all the routinely assimilated data and included ARR dropsonde data, whereas the denial run (DENY) excluded the dropsonde data. There were 17 intensive observing periods (IOPs) totaling 46 Air Force C-130 and 16 NOAA G-IV missions to deploy dropsondes over targeted regions with potential for downstream high-impact weather associated with the ARs. Data from a total of 628 dropsondes were assimilated in the CTRL. The dropsonde data impact on precipitation forecasts over U.S. West Coast domains is largely positive, especially for day-5 lead time, and appears driven by different model variables on a case-by-case basis. These results suggest that data gaps associated with ARs can be addressed with targeted ARR field campaigns providing vital observations needed for improving U.S. West Coast precipitation forecasts.

A global survey of diurnal offshore propagation of rainfall

Diurnal rainfall offshore propagation (OP) shapes the timing and intensity of coastal rainfall and thus impacts both nature and society. Previous OP studies have rarely compared various coasts, and a consensus regarding physical mechanisms has not been reached on a global scale. Here, we provide the global climatology of observed OP, which propagates across ~78% of all coasts and accounts for ~59% of the coastal precipitation. Generally, OP is facilitated by low latitudes, high moisture conditions and offshore background winds. OP at low latitudes in a high-moisture environment is mainly caused by inertia–gravity waves due to the land–sea thermal contrast, whereas OP at higher latitudes is significantly influenced by background winds under trapped land–sea breeze circulation conditions. Slower near-shore OP might be modulated by density currents. Our results provide a guide for global OP hotspots and suggest relative contributions of mechanisms from a statistical perspective.

Cost-effective management measures for coastal aquifers affected by saltwater intrusion and climate change.

Sustainable management of natural water resources and food security in the face of changing climate conditions is critical to the livelihood of coastal communities. Increasing inundation and saltwater intrusion (SWI) will likely adversely affect agricultural production and the associated beach access for tourism. This study uses an integrated surface-ground water model to introduce a new approach for retardation of SWI that consists of placing aquifer fill materials along the existing shoreline using Coastal Land Reclamation (CLR). The modeling results suggest that the artificial aquifer materials could be designed to decrease SWI by increasing the infiltration area of coastal precipitation, collecting runoffs from the catchment area, and applying treated wastewater or desalinated brackish water-using coastal wave energy to reduce water treatment costs. The SEAWAT model was applied to verify that it correctly addressed Henry's problem and then applied to the Biscayne aquifer, Florida, USA. In this study, to better inform Coastal Aquifer Management (CAM), we developed four modeling scenarios, namely, Physical Surface Barriers (PSB), including the artificial aquifer widths, permeability, and side slopes and recharge. In the base case scenario without artificial aquifer placement, results show that seawater levels would increase aquifer salinity and displace large amounts of presently available fresh groundwater. More specifically, for the Biscayne aquifer, approximately 0.50% of available fresh groundwater will be lost (that is, 41,192 m3) per km of the width of the aquifer considering the increasing seawater level. Furthermore, the results suggest that placing the PSB aquifer with a smaller permeability of <100 m per day at a width of approximately 615 m increases the available fresh groundwater by approximately 45.20 and 43.90% per km of shoreline, respectively. Similarly, decreasing the slope on the aquifer-ocean side and increasing the aquifer recharge will increase freshwater availability by about 43.90 and 44.50% per km of the aquifer. Finally, placing an aquifer fill along the shallow shoreline increases net revenues to the coastal community through increased agricultural production and possibly tourism that offset fill placement and water treatment costs. This study is useful for integrated management of coastal zones by delaying aquifer salinity, protecting fresh groundwater bodies, increasing agricultural lands, supporting surface water supplies by harvesting rainfall and flash flooding, and desalinating saline water using wave energy. Also, the feasibility of freshwater storage and costs for CAM is achieved in this study.

Anthropogenic aerosol impacts on Pacific Coast precipitation in CMIP6 models

Studies show anthropogenic aerosols (AAs) can perturb regional precipitation, including the tropical rain belt and monsoons of the Northern Hemisphere (NH). In the NH mid-latitudes, however, the impact of AAs on regional climate and precipitation remains uncertain. This work investigates the influence of AAs on wintertime precipitation along the North American Pacific Coast using models from the Coupled Model Intercomparison Project phase 6 (CMIP6). Over the early to mid-20th century, when U.S. and European AA and precursor gas emissions rapidly increased, a robust wintertime precipitation dipole pattern exists in CMIP6 all-forcing and AA-only forcing simulations, with wetting of the southern Pacific Coast (southward of ∼40∘ N) and drying to the north. A corresponding dynamical dipole pattern also occurs—including strengthening of the east Pacific jet southward of ∼40∘ N and weakening to the north—which is related to a Rossby wave teleconnection that emanates out of the tropical Pacific. Over the 21st century, when AAs are projected to decrease, an opposite hydro-dynamic dipole pattern occurs, including drying southward of 40∘ N (including California) and wetting to the north. Although Pacific Coast precipitation is dominated by natural variability, good multi-model agreement in the forced component of Pacific Coast precipitation change exists, with the AA pattern (north south dipole) dominating the greenhouse gas (uniform) pattern in the historical all-forcing simulations. A high level of agreement in individual model-realization trends also exists, particularly for the early part of the 20th century, suggesting a robustness to the human signature on Pacific Coast precipitation changes. Thus, historical precipitation responses along the Pacific Coast are likely to have been driven by a mixture of natural variability and forced changes. Natural variations appear to drive a large fraction of this change, but human influences (i.e. aerosols) are likely to have preconditioned the variability of the climate in this region.

Behavior of the ITCZ second band near the Peruvian coast during the 2017 coastal El Niño

The behavior of the second band of the Intertropical Convergence Zone (ITCZ) near the Peruvian coast during early 2017 is studied, using precipitation, surface winds, sea surface temperature (SST) and atmospheric variables in different isobaric levels. The proposal of a daily index (Ia) to identify opportunely the formation of this band and the Lorenz energy terms in the region is also considered. This band was present from late January to early April 2017, associated with an anomalous dipole of sea level pressure between the east and west eastern Equatorial Pacific that configured anomalously northerly surface winds and the release of southeasterly trade winds near Peru. In medium levels, a zonally oriented positive mixing ratio anomaly was observed in early March over the ITCZ second band, associated with heavy rain systems over the northern Peruvian coastal region. In the same period, positive anomalies of divergence in high tropospheric levels were observed. The daily Ia index allowed an effective detection of the ITCZ second band 11 days before the maximum coastal precipitation, and the Lorenz energy terms showed eddy kinetic energy (KE) peaks in January and February and a contribution of barotropic instability in equatorial regions.

Atmospheric River Reconnaissance 2021: A Review

Abstract Atmospheric River Reconnaissance (AR Recon) is a targeted campaign that complements other sources of observational data, forming part of a diverse observing system. AR Recon 2021 operated for ten weeks from January 13 to March 22, with 29.5 Intensive Observation Periods (IOPs), 45 flights and 1142 successful dropsondes deployed in the northeast Pacific. With the availability of two WC-130J aircraft operated by the 53rd Weather Reconnaissance Squadron (53 WRS), Air Force Reserve Command (AFRC) and one National Oceanic and Atmospheric Administration (NOAA) Aircraft Operations Center (AOC) G-IVSP aircraft, six sequences were accomplished, in which the same synoptic system was sampled over several days. The principal aim was to gather observations to improve forecasts of landfalling atmospheric rivers on the U.S. West Coast. Sampling of other meteorological phenomena forecast to have downstream impacts over the U.S. was also considered. Alongside forecast improvement, observations were also gathered to address important scientific research questions, as part of a Research and Operations Partnership. Targeted dropsonde observations were focused on essential atmospheric structures, primarily atmospheric rivers. Adjoint and ensemble sensitivities, mainly focusing on predictions of U.S. West Coast precipitation, provided complementary information on locations where additional observations may help to reduce the forecast uncertainty. Additionally, Airborne Radio Occultation (ARO) and tail radar were active during some flights, 30 drifting buoys were distributed, and 111 radiosondes were launched from four locations in California. Dropsonde, radiosonde and buoy data were available for assimilation in real-time into operational forecast models. Future work is planned to examine the impact of AR Recon 2021 data on model forecasts.

Role of the Tropics in State‐Dependent Improvements of US West Coast NOAA Unified Forecast System Precipitation Forecasts

AbstractBoreal‐wintertime hindcasts in the Unified Forecast System with the tropics nudged toward reanalysis improve United States (US) West Coast precipitation forecasts at Weeks 3–4 lead times when compared to those without nudging. To diagnose the origin of these improvements, a multivariate k‐means clustering method is used to group hindcasts into subsets by their initial conditions. One cluster characterized by an initially strong Aleutian Low demonstrates larger improvements at Weeks 3–4 with nudging compared to the others. The greater improvements with nudging for this cluster are related to model errors in simulating the interaction between the Aleutian Low and the teleconnection patterns associated with the Madden‐Julian oscillation (MJO) and El Niño‐Southern Oscillation (ENSO). Improving forecasts of tropical intraseasonal precipitation, especially during early MJO phases under non‐cold ENSO, may be important for producing better Weeks 3–4 precipitation forecasts for the US West Coast.

Obliquity Influence on Low‐Latitude Coastal Precipitation in Eastern Brazil During the Past ∼850 kyr

AbstractPaleoclimate records from tropical South America typically show precession‐paced variability in rainfall, caused by insolation‐driven changes in the South American Monsoon System, however this mechanism may not be responsible for hydroclimate change outside of the core monsoon domain, such as in the coastal zone of tropical eastern Brazil. Our findings are based on a ∼850 kyr‐long multiproxy record from a marine sediment core collected from the eastern Brazilian margin that represents the longest continuous record of South American hydroclimate to date. Utilizing the ln (K/Al) chemical weathering proxy from the core, we determine that past hydroclimate change in the coastal zone was primarily modulated by obliquity forcing. We demonstrate that high obliquity is associated with an increase in the boreal summer interhemispheric insolation contrast which decreases the zonality of the southern trade winds and reduces moisture advection to the coastal zone. Based on the long‐term coherence between the ln (K/Al) record and benthic δ13C records from the Atlantic during Marine Isotope Stages 16–13, we infer that an increase in the strength of the overturning circulation, caused by Northern Hemisphere high‐latitude forcing, may have produced surface cooling in the western tropical South Atlantic which led to reduced moisture advection to the coastal zone. We suggest that this mechanism may have also caused the amplification in millennial‐scale variability in the coastal hydroclimate system, which began after the decoupling of the coastal hydroclimate system from obliquity forcing.

Air-sea coupling shapes North American hydroclimate response to ice sheets during the Last Glacial Maximum

The Western U.S. is vulnerable to hydrological stress, and insights from past climate periods are helpful for providing historical benchmarks for future climate projections. Myriad evidence from coupled models and paleoclimatic proxies suggests a major reorganization of west coast hydroclimate during the Last Glacial Maximum (LGM, ∼17–25 ka), such that the Southwest U.S. was wetter than modern day and the Pacific Northwest was drier. Yet the fundamental mechanisms underlying these hydroclimatic shifts remain unclear. Here, we employ a suite of targeted model simulations to probe the influence of LGM Northern Hemisphere ice sheets on west coast atmospheric dynamics. Whereas previous modeling studies have suggested that the southward shift of LGM west coast precipitation was driven only by the mechanical steering of atmospheric circulation by elevated ice sheet topography, we find this to be an artifact of earlier simulations that neglected realistic air-sea interaction. Instead, our simulations indicate that ice sheet albedo induced a pattern of North Pacific sea surface temperatures, reinforced by ocean-atmosphere feedbacks, that shifted the large-scale atmospheric circulation as well as the latitudinal distribution of west coast precipitation southward during the LGM. Crucially, we find that atmosphere-ocean feedbacks that sustained this ice sheet albedo-induced temperature pattern in the LGM could drive similar hydroclimatic changes today.

Responses of the atmospheric boundary layer to a low‐latitude mesoscale SST front

AbstractThe responses of the atmospheric boundary layer at low latitudes (20°N) to forcing by an ocean‐mesoscale sea surface temperature (SST) front are investigated under the conditions that the background wind intersects with the SST front (i.e., there are cross‐frontal and along‐frontal wind components) through ideal numerical experiments. The simulation results show that the responses of the atmospheric boundary layer are sensitive to the background wind speed and its direction relative to the SST front. The type of convergence and divergence of Ekman transport and that of the background wind can be constructive or destructive, depending on the relative orientation of the background wind and the SST front. When the two kinds of convergence and divergence are constructive, they can cause strong convergence and divergence in the boundary layer near the SST front; further, the unbalanced state forced over the SST front will excite inertial gravity waves propagating into the free atmosphere. The vertical velocity excited in this case is much greater than that when there is only a cross‐frontal background wind component with an equivalent magnitude. On the contrary, when the two kinds of convergence and divergence are destructive, the resultants of convergence and divergence are reduced significantly, and the interaction between the boundary layer and the aloft atmosphere decays rapidly with height. The significance of the results obtained for the analysis of coastal precipitation are discussed.

Impact of High Temporal Resolution FY‐4A Geostationary Interferometric Infrared Sounder (GIIRS) Radiance Measurements on Typhoon Forecasts: Maria (2018) Case With GRAPES Global 4D‐Var Assimilation System

AbstractTargeted observations for Typhoon Maria (2018) using the Geostationary Interferometric Infrared Sounder (GIIRS) at a temporal resolution of 15 min provide unprecedented information for impact studies of high‐temporal‐resolution from geostationary hyperspectral IR sounders. This study investigates the impacts of different temporal resolutions for GIIRS assimilation on Maria analyses and forecasts. Results reveal that assimilating higher resolution data captures more detailed temporal and spatial structures and stronger warm anomalies. Additionally, the track forecast for Maria from assimilating higher temporal resolution GIIRS radiances is better than those from assimilating radiances with lower temporal resolution, and both are better than the control experiment. The accuracy of the different temporal resolutions GIIRS experiments (from 3 h to 15 min) is improved (from 18% to 43%), and the intensity forecast errors are also reduced (from 12% to 18%). Meanwhile, high‐temporal GIIRS assimilation also improves the coastal precipitation forecasts during typhoon landfall.