Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones

The NASA CYGNSS satellite constellation measures ocean surface winds using the existing network of the Global Navigation Satellite System (GNSS) and was designed for measurements in tropical cyclones (TCs). Here, we focus on using a consistent methodology to validate multiple CYGNSS wind data records currently available to the public, some focusing on low to moderate wind speeds, others for high winds, a storm-centric product for TC analyses, and a wind dataset from NOAA that applies a track-wise bias correction. Our goal is to document their differences and provide guidance to users. The assessment of CYGNSS winds (2017–2020) is performed here at global scales and for all wind regimes, with particular focus on TCs, using measurements from radiometers that are specifically developed for high winds: SMAP, WindSat, and AMSR2 TC-winds. The CYGNSS high-wind products display significant biases in TCs and very large uncertainties. Similar biases and large uncertainties were found with the storm-centric wind product. On the other hand, the NOAA winds show promising skill in TCs, approaching a level suitable for tropical meteorology studies. At the global level, the NOAA winds are overall unbiased at wind regimes from 0–30 m/s and were selected for a test assimilation into a global wind analysis, CCMP, also presented here.

Energy balance at the land-surface interface

A small scale field experiment was conducted at the Indian Institute of Tropical Meteorology (IITM). Pashan Pune and the energy budget at the land surface interface was studied for clear and cloudy days over bare soil. Using instrumented towers, a net radiometer and soil temperature probe all the components of the energy budget. i.e. the sensible heat flux, latent heat flux, soil heat flux and net radiation were measured directly and the energy balance was computed. It is observed that when considered over the whole day, the energy budget is fairly balanced. As a part of energy budget, the Bowen's ratio is also discussed.

PREFACE

The seasonal atmospheric condition over the Maritime Continent is mainly driven by the Asian-Australian Monsoon. Precipitation over the Maritime Continent is highly influenced by the intra-seasonal Madden-Julian Oscillation (MJO), also highly affected by the El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole Mode (IOD). At an interannual time scale the Maritime Continent is also crossed by Indonesia Through Flow (ITF), as the artery connecting Tropical Pacific and Indian Oceans, and acting as a crucial link of the ocean general circulation that affects not only properties of these two oceans but also global climate. This complex mixture of land and sea interaction, with various atmospheric and oceanic phenomena within, makes the Maritime Continent as a unique, enigmatic and challenging area for scientific endeavor on tropical meteorology and atmospheric sciences. Various observations and research have been coordinated, campaigned, and conducted to better understand the atmospheric and oceanic condition over the tropics, especially the Maritime Continent. Many scientific discoveries have been found to enrich the knowledge of atmospheric science on the tropics, from the International Winter Monsoon Experiment in 1978, TOGA COARE in 1993, HARIMAU that ended in 2010, to CINDY/DYNAMO in 2011. The recent Year of Maritime Continent (YMC) during 2017 - 2020 aimed to improve understanding and prediction local multi-scale variability of the Maritime Continent weather-climate system and its global impact through observations and modelling exercises, was the state-of-art for such coordinated research on the tropics. As a part of YMC program, BMKG will also be involved in Measurements and Modelling of the Indonesian Throughflow International Experiment (MINTIE) which is collaborative research among countries including Indonesia BMKG and being led by Columbia University during 2019 – 2024. LIST OF Committee, Steering Committee, Organizing Committee Leader, Leader, Secretariat & Public Relations, Treasure, Event are available in this pdf.

Changing Spatio-Temporal Rainfall Fluctuation over North East India

This study is analysis of changes in rainfall fluctuation in North East India. Using the longest instrumental monthly rainfall data of well spread 316 stations across India available from Indian Institute of Tropical Meteorology (IITM), the fluctuation characteristics as well as the spatial-temporal variability of the seasonal, monsoon monthly and annual rainfall pattern over the north eastern region of India (NER) have been examined. On an average, NER receives about 2450 mm of rainfall with 1093.0 mm as its annual evapo transpiration. The winter (JF) rainfall contributes 2.1% to the annual rainfall; summer (MAM) rainfall 24.3%; summer monsoon (JJAS) rainfall 65.1% and the post-monsoon (OND) rainfall contributes 8.5% to the annual rainfall. The region shows great variation in surface temperature regime (15oC to 32oC in summer and 0 to 26oC in winter). The spatial-temporal rainfall variability shows random fluctuating characteristics of expansion / contraction of desert area but overall it is showing a slight decreasing over the NER as well as whole India.

Probabilistic Streamflow forecast for Narmada River Basin

<p>Ensemble Streamflow Prediction (ESP) is a widely used method in forecasting streamflow, particularly for extremely low or high flows. However, the incorporation of reservoir operations in using ensemble streamflow prediction has not been investigated till yet. We calibrated Variable Infiltration Capacity (VIC) model for daily streamflow for Narmada river basin at four stations (Sandia, Handia, Mandleshwar and Garudeshwar) considering the effect of four reservoirs (Bargi, Tawa, Indira Sagar and Sardar Sarovar). The model is well-calibrated for the selected river basin (R2>0.55) at all locations. Further, routing of streamflow is done considering the reservoir storage dynamics and operating rules. Input data for ensemble prediction is taken from all 16 members of the Extended Range Forecast System (ERFS) developed by Indian Institute of Tropical Meteorology (IITM) and implemented by India Meteorological Department (IMD). Post-processing of the results gave us probabilities of uncertainties associated with streamflow prediction using ERFS members. This study provides key information in predictions of streamflow by incorporating the reservoirs based on the ERFS ensemble members, which can be used to effectively mitigate life and property losses associated with extreme flows in rivers.</p>

Value Addition to Forecasting: Towards Kharif Rice Crop Predictability Through Local Climate Variations Associated With Indo-Pacific Climate Drivers.

The Indian Institute of Tropical Meteorology (IITM) has generated seasonal and extended range hindcast products for 1981-2008 and 2003-2016 respectively using the IITM-Climate Forecast System (IITM-CFS) coupled model at various resolutions and configurations. Notably, our observational analysis suggests that for the 1981-2008 period, the tropical Indo-Pacific drivers, namely, the canonical El Niño-Southern Oscillation (ENSO), ENSO Modoki, and Indian Ocean Dipole (IOD) are significantly associated with the observed Kharif rice production (KRP) of various rice-growing Indian states. In this paper, using the available hindcasts, we evaluate whether these state-of-the-art retrospective forecasts capture the relationship of the KRP of multiple states with the local rainfall as well as the tropical Indo-Pacific drivers, namely, the canonical ENSO, ENSO Modoki and the IOD. Using techniques of anomaly correlation, partial correlation, and pattern correlation, we surmise that the IITM-CFS successfully simulate the observed association of the tropical Indo-Pacific drivers with the local rainfall of many states during the summer monsoon. Significantly, the observed relationship of the local KRP with various climate drivers is predicted well for several Indian states such as United Andhra Pradesh, Karnataka, Odisha, and Bihar. The basis seems to be the model's ability to capture the teleconnections from the tropical Indo-Pacific drivers such as the IOD, canonical and Modoki ENSOs to the local climate, and consequently, the Kharif rice production.

Atmospheric Chemistry Signatures of an Equatorially Symmetric Matsuno–Gill Circulation Pattern

Matsuno–Gill circulations have been widely studied in tropical meteorology, but their impact on stratospheric chemistry has seldom been explicitly evaluated. This study demonstrates that, in a model nudged to reanalysis, anticyclonic Rossby wave gyres that form near the tropopause as a result of equatorially symmetric heating in the troposphere provide a dynamical mechanism to influence tropical and subtropical atmospheric chemistry during near-equinox months. The anticyclonic flow entrains extratropical air from higher latitudes into the deep tropics of both hemispheres and induces cooling in the already cold upper-troposphere/lower-stratosphere (UTLS) region. Both of these aspects of the circulation allow heterogeneous chlorine activation on sulfuric acid aerosols to proceed rapidly, primarily via the HCl + ClONO2 reaction. Precipitation rates and heating rates from reanalysis are shown to be consistent with these heating and circulation response patterns in the months of interest. This study analyzes specified dynamics simulations from the Whole Atmosphere Community Climate Model (SD-WACCM) with and without tropical heterogeneous chemistry to demonstrate that these circulations influence substantially the distributions of, for example, NO2 and ClO in the UTLS tropics and subtropics of both hemispheres. This provides a previously unrecognized dynamical influence on the spatial structures of atmospheric composition changes in the UTLS during near-equinox months.

NASA Global Satellite and Model Data Products and Services for Tropical Meteorology and Climatology

Satellite remote sensing and model data play an important role in research and applications of tropical meteorology and climatology over vast, data-sparse oceans and remote continents. Since the first weather satellite was launched by NASA in 1960, a large collection of NASA’s Earth science data is freely available to the research and application communities around the world, significantly improving our overall understanding of the Earth system and environment. Established in the mid-1980s, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), located in Maryland, USA, is a data archive center for multidisciplinary, satellite and model assimilation data products. As one of the 12 NASA data centers in Earth sciences, GES DISC hosts several important NASA satellite missions for tropical meteorology and climatology such as the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) Mission and the Modern-Era Retrospective analysis for Research and Applications (MERRA). Over the years, GES DISC has developed data services to facilitate data discovery, access, distribution, analysis and visualization, including Giovanni, an online analysis and visualization tool without the need to download data and software. Despite many efforts for improving data access, a significant number of challenges remain, such as finding datasets and services for a specific research topic or project, especially for inexperienced users or users outside the remote sensing community. In this article, we list and describe major NASA satellite remote sensing and model datasets and services for tropical meteorology and climatology along with examples of using the data and services, so this may help users better utilize the information in their research and applications.

First Woman

This book, based on the life and work of Joanne (Gerould) Simpson (1923–2010), charts the history of women in meteorology and the history of tropical meteorology in the context of her long and productive career as pioneer scientist, project leader, and mentor. In 1943 women had no status in meteorology, tropical weather was largely aer incognita, and Joanne Gerould, a new graduate student at the University of Chicago, had just set her sights on understanding the behavior of clouds. Establishing her career in an era of overwhelming marginalization of women in science was no easy matter, and Joanne (who published under three married names and raised three children) had to fight every step of the way. Under the mentorship of Herbert Riehl, she received a PhD degree from Chicago in 1949. Later, while working at Woods Hole, she collaborated with Riehl on their revolutionary and controversial “hot tower” hypothesis that cumulonimbus clouds were the driving force in the tropical atmosphere, providing energy to power the Hadley circulation, the trade winds, and by implication, the global circulation. The mechanism of hot towers alludes to the incessant battle between buoyancy and entrainment in tropical convection, valorizing those clouds that successfully break through the trade wind inversion to soar to the top of the troposphere. The metaphor of hot towers points to the incessant battles Joanne waged between her sky-high aspirations and the dark psychological and institutional forces dragging her down. Yet she prevailed, reaching the pinnacle of personal and professional accomplishment, especially in her years at NASA, as she conditioned the atmosphere for further breakthroughs for women in science. She is best remembered as a pioneer woman scientist, the best tropical scientist of her generation.

Real-Time Forecast of Dense Fog Events over Delhi: The Performance of the WRF Model during the WiFEX Field Campaign

A Winter Fog Experiment (WiFEX) was conducted to study the genesis of fog formation between winters 2016–17 and 2017–18 at Indira Gandhi International Airport (IGIA), Delhi, India. To support the WiFEX field campaign, the Weather Research and Forecasting (WRF) Model was used to produce real-time forecasts at 2-km horizontal grid spacing. This paper summarizes the performance of the model forecasts for 43 very dense fog episodes (visibility < 200 m) and preliminary evaluation of the model against the observations. Similarly, near-surface liquid water content (LWC) from models and continuous visibility observations are used as a metric for model evaluation. Results show that the skill score is relatively promising for the hit rate with a value of 0.78, whereas the false alarm rate (0.19) and missing rate (0.32) are quite low. This indicates that the model has reasonable predictive accuracy, and the performance of the real-time forecast is better for both dense fog events and no-fog events. For success cases, the model accurately captured the near-surface meteorological conditions, particularly the low-level moisture, wind fields, and temperature inversion. In contrast, for failed cases, the WRF Model shows large error in near-surface relative humidity and temperature compared to the observations, although it captures temperature inversions reasonably well. Our results also suggest that the model is able to capture the variability in fog onset for consecutive fog events. Errors in near-surface variables during failed cases are found to be affected by the errors in the initial conditions taken from the Indian Institute of Tropical Meteorology Global Forecasting System (IITM-GFS) spectral model forecast. Further evaluation of the operational forecasts for dense fog cases indicates that the error in predicting fog onset stage is relatively large (mean error of 4 h) compared to the dissipation stage.