Water Vapour content is decreasing. Sorry. That is the data. And it is not just arid regions. It is global. Just more pronounced in the Arid regions
The study exposes a major flaw in climate models. Their inability to correctly simulate humidity trends in dry regions. If models are
systematically overestimating atmospheric water vapor in arid regions, then they may also be
exaggerating the overall climate sensitivity to greenhouse gases. This contradicts alarmist narratives that assume strong, self-reinforcing warming due to rising humidity. Instead, the real-world data suggest a
more complex and less dramatic hydroclimate response to warming, highlighting the need for better modeling before making extreme climate projections.
The paper,
"Observed humidity trends in dry regions contradict climate models" by Isla R. Simpson et al., identifies a significant discrepancy between climate models and real-world observations concerning atmospheric humidity trends in arid and semi-arid regions.
The authors use accredited and widely recognized data sources for their analysis. Their study relies on multiple observational datasets, reanalysis products, and climate model simulations from reputable sources. Below are the key datasets they used:
1. Observational Datasets
These datasets are based on direct measurements and have undergone extensive quality control.
HadISDH (Hadley Centre Integrated Surface Database of Humidity)
- A homogenized dataset based on the Integrated Surface Database (ISD).
- Developed by the UK Met Office Hadley Centre.
- Used for assessing long-term humidity trends.
ISD (Integrated Surface Database)
- Maintained by the U.S. National Centers for Environmental Information (NCEI).
- Contains in-situ station-based humidity measurements from global meteorological stations.
Berkeley Earth Surface Temperature (BEST)
- A global temperature dataset developed by Berkeley Earth, known for its independent climate assessments.
GPCC (Global Precipitation Climatology Centre)
- A precipitation dataset managed by the German Weather Service (DWD).
- Based on rain gauge measurements worldwide.
GPCP (Global Precipitation Climatology Project)
- A dataset combining satellite and rain gauge data, produced by NASA.
CRUTS (Climatic Research Unit Time-Series)
- A historical precipitation dataset from the University of East Anglia’s Climatic Research Unit (CRU).
2. Reanalysis Products
These datasets assimilate various observational inputs into climate models for a globally consistent dataset.
ERA5 (ECMWF Reanalysis)
- Produced by the European Centre for Medium-Range Weather Forecasts (ECMWF).
- Assimilates in-situ humidity measurements from stations, radiosondes, aircraft, and satellites.
MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2)
- Developed by NASA.
- Unlike ERA5, it does not assimilate in-situ humidity measurements, which affects its reliability for humidity trends.
JRA-55 (Japanese 55-year Reanalysis)
- Produced by the Japan Meteorological Agency (JMA).
- Uses older ECMWF reanalysis procedures but still includes in-situ humidity measurements.
3. Climate Model Simulations
The authors also compare observations with climate model outputs from major international projects.
CMIP6 (Coupled Model Intercomparison Project Phase 6)
- A widely used climate model dataset coordinated by the World Climate Research Programme (WCRP).
- Includes simulations from over 40 global climate models.
LENS2 (Community Earth System Model Large Ensemble)
- A climate modeling project run by the National Center for Atmospheric Research (NCAR).
AMIP6 (Atmospheric Model Intercomparison Project Phase 6)
- Simulations using observed sea surface temperatures (SSTs) to test how climate models respond to historical conditions.
GOGA2 (Global Ocean-Global Atmosphere Model)
- A subset of the CESM2 (Community Earth System Model Version 2) experiments.
Implications:
- If vapor pressure deficit (VPD) continues increasing without an increase in actual vapor pressure, wildfires and ecosystem stress could become worse than models currently predict.
- Heat extremes may be more severe in reality due to limited humidity-driven cooling effects.
- Current climate models might be unreliable for projecting future hydroclimate in arid regions, necessitating urgent revisions.
