1) How does the new version compare?
v4.6.0.2023f is virtually identical to v4.5.1.2022f over the 1973-2022 period for specific humidity (
q) and relative humidity (RH). Each year there is usually a small change to the source station dataset as a few stations or subperiods of stations are added or lost from processing within the source dataset (
NOAA NCEI's ISD). A new wet-bulb temperature algorithm means that there are small changes to the
Tw fields only. A bug fix in the HadISD parent dataset (
initial post,
HadISD update post) has also resulted in a greater removal of flagged errors. In terms of gridboxes with sufficient presence over the climatology period, the new version v4.6.0.2023f results in 15 (for
q) and 11 (for RH) lost gridboxes, mostly over higher latitudes. There are 14 (for
q) and 11 (for RH) additional gridboxes mostly over the tropics and extratropics (Figs. 1 and 2 panel a). but clearly these have made negligible difference to the regional mean timeseries.
The overall story of increasing specific humidity is concurrent in both versions with no change to long-term trends in v4.6.0.2023f that have an extra year of data other than the moistening in the tropics being 0.01 g kg -1 decade -1 larger and the negligible decreasing trend in the Southern Hemisphere becoming 0.00 g kg -1 decade -1, compared to v4.5.1.2022f. (Figure 1 panels d to g). Across the globe (Figure 1 panel a) the vast majority of gridboxes show trends in the same direction (95% of gridboxes - Figure 1 panel b), with 84.8% of these both showing increasing q (Figure 1 panel b). Trends in opposite directions occur in 5 % of gridboxes and are mostly in the Southern Hemisphere, across South America and northern Australia.
The overall story of decreasing relative humidity (except over the tropics) is also still valid in both versions, with long-term negative RH trends in v4.6.0.2023f being 0.01 %rh decade -1 less negative for the globe and tropics (still not significant), -0.01 %rh decade -1 more negative over the Northern Hemisphere, and -0.04 %rh decade -1 less negative over the Southern Hemisphere, compared to v4.5.1.2022f (Figure 2 panels d to g). Across the globe (Figure 2 panel a), 88.4% of gridboxes have trends in the same direction in both versions which is a slightly smaller proportion compared to q (Figure 1 panel b). Overall, 57.7% of gridboxes agree on negative trends and 30.7% agree on positive RH trends.
Figure 1. Difference in regional timeseries and decadal trends between HadISDH.landq v4.6.0.2023f and v4.5.1.2022f. a) Ratio of v4.6.0.2023f to v4.5.1.2022f decadal trends (1973-2023 and 2022 respectively) with change in number of gridboxes annotated and identified by red (gained) and pink (lost). b) Scatter plot of gridbox trends with percentage in each quadrant of positive/positive, positive/negative, negative/negative and negative/positive annotated. c) Distribution of gridbox decadal trends for each version with mean and standard deviation annotated. d) Total gridbox coverage by 5 degree latitude band for each year for v4.6.0.2023f. e) Difference in total gridbox coverage by 5 degree latitude band for each year between v4.6.0.2023f and v4.5.1.2022f. f to i) regional mean monthly time series and decadal trends with 90th percentile confidence range annotated.
Figure 2. Difference in regional timeseries and decadal trends between HadISDH.landRH v4.6.0.2023f and v4.5.1.2022f. a) Ratio of v4.6.0.2023f to v4.5.1.2022f decadal trends (1973-2023 and 2022 respectively) with change in number of gridboxes annotated and identified by red (gained) and pink (lost). b) Scatter plot of gridbox trends with percentage in each quadrant of positive/positive, positive/negative, negative/negative and negative/positive annotated. c) Distribution of gridbox decadal trends for each version with mean and standard deviation annotated. d) Total gridbox coverage by 5 degree latitude band for each year for v4.6.0.2023f. e) Difference in total gridbox coverage by 5 degree latitude band for each year between v4.6.0.2023f and v4.5.1.2022f. f to i) regional mean monthly time series and decadal trends with 90th percentile confidence range annotated.
2) What's New?
We use HadISD.3.4.0.2023f as the basis for HadISDH.land.4.6.0.2023f which includes an additional 12 months of data and any ISD level processing changes during the previous 12 months. There has been a bug fix applied to this dataset (initial post,
HadISD update post) after detecting that the buddy check test hadn't been implemented correctly since 2017f versions. The buddy check allows flagged errors to be reinstated if they are supported by neighbouring stations but the bug meant that too many flagged errors were being reinstated. The correction has increased the number of flagged errors removed and therefore changed the observational coverage slightly.
Although only last year we implemented a new
algorithm (Stull, 2011) to remove the large errors at high temperature/low
humidity in the previous Jensen et al., (1990) method, a new method is now available
which reduces moist bias errors at high temperature/low humidity (reaching +1.3
°C) and dry bias errors at low temperature/high humidity (approaching -1 °C). The
new Non-iterative Evaluation of Wet-bulb Temperature (NEWT) method has been developed
by Rob Warren at the Bureau of Meteorology and coded in python. Its errors are far
smaller at ± 0.01 °C. Rogers and Warren (2024) introduce the new method and
compare it against the Stull (2011) and other methods (https://essopenarchive.org/users/714325/articles/698601-fast-and-accurate-calculation-of-wet-bulb-temperature-for-humid-heat-extremes).
Here we use their python code to calculate adiabatic wet-bulb temperatures
using polynomial fits from surface pressure, air temperature and specific
humidity. This change only affects the wet-bulb temperature fields and
differences are negligible in large-scale means and far less than 1 °C for the
most part. Differences are largest over hot/dry and cold/humid air conditions. We
still use the Stull (2011) method to decide whether to calculate vapour
pressure with respect to ice or water because it is faster to implement so
there is no change to other variables.
All other processing steps for HadISDH.land
remain identical. The new version of HadISD (3.4.0.2023f) has pulled through
some historical changes to stations which are passed on to HadISDH.land resulting
in 9667 compared to 9555 initial stations. The end station count is further
reduced after completeness checks and homogenisation. The homogeneity
adjustments differ slightly due to sensitivity to the addition and loss of
stations, historical changes to stations previously included and the additional
12 months of data.
Rogers, C.D.W. and Warren, R.A. (2024). Fast and Accurate Calculation of Wet-bulb Temperature for
Humid-Heat Extremes. ESS Open Archive. January 18, 2024. DOI: 10.22541/essoar.170560423.39769387/v1
Stull, R., 2011: Wet-Bulb Temperature from
Relative Humidity and Air Temperature. J. Appl. Meteor. Climatol., 50,
2267–2269,
https://doi.org/10.1175/JAMC-D-11-0143.1.3) Summary of changes by level of technicality.
3) Summary of changes
MAJOR CHANGES (X):
MINOR BUG FIXES AND CHANGES (Y):
BUG FIXES AND HISTORICAL DATA UPDATES (Z):
- 9667 compared to 9555 initial selection stations
last year.
- Use of HadISD.3.4.0.2023f as the basis
which includes retrospective improvements (to correct data, add or remove
data sections) to the historical data in NCEI's ISD archive are ongoing. These
are not documented.
4) Station Counts
| Version | Initial Stations | Selected Stations | Final Stations q | Final Stations RH |
|---|
| v4.6.0.2023f | 9667 | 5629 | 5394 | 5446 |
| v4.5.1.2022f | 9555 | 5641 | 5397 | 5445 |
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